Muscarinic receptor agonists and positive allosteric modulators in animal models of psychosis: protocol for a systematic review and meta-analysis

Muscarinic receptor agonists and positive... | F1000Research "use strict";function _typeof(t){return(_typeof="function"==typeof Symbol&&"symbol"==typeof Symbol.iterator?function(t){return typeof t}:function(t){return t&&"function"==typeof Symbol&&t.constructor===Symbol&&t!==Symbol.prototype?"symbol":typeof t})(t)}!function(){var t=function(){var t,e,o=[],n=window,r=n;for(;r;){try{if(r.frames.__tcfapiLocator){t=r;break}}catch(t){}if(r===n.top)break;r=r.parent}t||(!function t(){var e=n.document,o=!!n.frames.__tcfapiLocator;if(!o)if(e.body){var r=e.createElement("iframe");r.style.cssText="display:none",r.name="__tcfapiLocator",e.body.appendChild(r)}else setTimeout(t,5);return!o}(),n.__tcfapi=function(){for(var t=arguments.length,n=new Array(t),r=0;r 3&&2===parseInt(n[1],10)&&"boolean"==typeof n[3]&&(e=n[3],"function"==typeof n[2]&&n[2]("set",!0)):"ping"===n[0]?"function"==typeof n[2]&&n[2]({gdprApplies:e,cmpLoaded:!1,cmpStatus:"stub"}):o.push(n)},n.addEventListener("message",(function(t){var e="string"==typeof t.data,o={};if(e)try{o=JSON.parse(t.data)}catch(t){}else o=t.data;var n="object"===_typeof(o)&&null!==o?o.__tcfapiCall:null;n&&window.__tcfapi(n.command,n.version,(function(o,r){var a={__tcfapiReturn:{returnValue:o,success:r,callId:n.callId}};t&&t.source&&t.source.postMessage&&t.source.postMessage(e?JSON.stringify(a):a,"*")}),n.parameter)}),!1))};"undefined"!=typeof module?module.exports=t:t()}(); dataLayer = dataLayer || []; // Standard GTM initialization - Google Consent Mode handles consent automatically (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start': new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0], j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src= 'https://www.googletagmanager.com/gtm.js?id='+i+dl+ '>m_auth=hzk0Vc3qFsQYhCrIoHz68A>m_preview=env-1>m_cookies_win=x';f.parentNode.insertBefore(j,f); })(window,document,'script','dataLayer','GTM-MWFK8L5J'); ;window.NREUM||(NREUM={});NREUM.init={distributed_tracing:{enabled:true},privacy:{cookies_enabled:true},ajax:{deny_list:["bam.nr-data.net"]}}; ;NREUM.loader_config={accountID:"438030",trustKey:"438030",agentID:"772317073",licenseKey:"97f8f67f26",applicationID:"772317073"} ;NREUM.info={beacon:"bam.nr-data.net",errorBeacon:"bam.nr-data.net",licenseKey:"97f8f67f26",applicationID:"772317073",sa:1} ;/*! For license information please see nr-loader-spa-1.236.0.min.js.LICENSE.txt */ (()=>{"use strict";var e,t,r={5763:(e,t,r)=>{r.d(t,{P_:()=>l,Mt:()=>g,C5:()=>s,DL:()=>v,OP:()=>T,lF:()=>D,Yu:()=>y,Dg:()=>h,CX:()=>c,GE:()=>b,sU:()=>_});var n=r(8632),i=r(9567);const o={beacon:n.ce.beacon,errorBeacon:n.ce.errorBeacon,licenseKey:void 0,applicationID:void 0,sa:void 0,queueTime:void 0,applicationTime:void 0,ttGuid:void 0,user:void 0,account:void 0,product:void 0,extra:void 0,jsAttributes:{},userAttributes:void 0,atts:void 0,transactionName:void 0,tNamePlain:void 0},a={};function s(e){if(!e)throw new Error("All info objects require an agent identifier!");if(!a[e])throw new Error("Info for ".concat(e," was never set"));return a[e]}function c(e,t){if(!e)throw new Error("All info objects require an agent identifier!");a[e]=(0,i.D)(t,o),(0,n.Qy)(e,a[e],"info")}var u=r(7056);const d=()=>{const e={blockSelector:"[data-nr-block]",maskInputOptions:{password:!0}};return{allow_bfcache:!0,privacy:{cookies_enabled:!0},ajax:{deny_list:void 0,enabled:!0,harvestTimeSeconds:10},distributed_tracing:{enabled:void 0,exclude_newrelic_header:void 0,cors_use_newrelic_header:void 0,cors_use_tracecontext_headers:void 0,allowed_origins:void 0},session:{domain:void 0,expiresMs:u.oD,inactiveMs:u.Hb},ssl:void 0,obfuscate:void 0,jserrors:{enabled:!0,harvestTimeSeconds:10},metrics:{enabled:!0},page_action:{enabled:!0,harvestTimeSeconds:30},page_view_event:{enabled:!0},page_view_timing:{enabled:!0,harvestTimeSeconds:30,long_task:!1},session_trace:{enabled:!0,harvestTimeSeconds:10},harvest:{tooManyRequestsDelay:60},session_replay:{enabled:!1,harvestTimeSeconds:60,sampleRate:.1,errorSampleRate:.1,maskTextSelector:"*",maskAllInputs:!0,get blockClass(){return"nr-block"},get ignoreClass(){return"nr-ignore"},get maskTextClass(){return"nr-mask"},get blockSelector(){return e.blockSelector},set blockSelector(t){e.blockSelector+=",".concat(t)},get maskInputOptions(){return e.maskInputOptions},set maskInputOptions(t){e.maskInputOptions={...t,password:!0}}},spa:{enabled:!0,harvestTimeSeconds:10}}},f={};function l(e){if(!e)throw new Error("All configuration objects require an agent identifier!");if(!f[e])throw new Error("Configuration for ".concat(e," was never set"));return f[e]}function h(e,t){if(!e)throw new Error("All configuration objects require an agent identifier!");f[e]=(0,i.D)(t,d()),(0,n.Qy)(e,f[e],"config")}function g(e,t){if(!e)throw new Error("All configuration objects require an agent identifier!");var r=l(e);if(r){for(var n=t.split("."),i=0;i {r.d(t,{D:()=>i});var n=r(50);function i(e,t){try{if(!e||"object"!=typeof e)return(0,n.Z)("Setting a Configurable requires an object as input");if(!t||"object"!=typeof t)return(0,n.Z)("Setting a Configurable requires a model to set its initial properties");const r=Object.create(Object.getPrototypeOf(t),Object.getOwnPropertyDescriptors(t)),o=0===Object.keys(r).length?e:r;for(let a in o)if(void 0!==e[a])try{"object"==typeof e[a]&&"object"==typeof t[a]?r[a]=i(e[a],t[a]):r[a]=e[a]}catch(e){(0,n.Z)("An error occurred while setting a property of a Configurable",e)}return r}catch(e){(0,n.Z)("An error occured while setting a Configurable",e)}}},6818:(e,t,r)=>{r.d(t,{Re:()=>i,gF:()=>o,q4:()=>n});const n="1.236.0",i="PROD",o="CDN"},385:(e,t,r)=>{r.d(t,{FN:()=>a,IF:()=>u,Nk:()=>f,Tt:()=>s,_A:()=>o,il:()=>n,pL:()=>c,v6:()=>i,w1:()=>d});const n="undefined"!=typeof window&&!!window.document,i="undefined"!=typeof WorkerGlobalScope&&("undefined"!=typeof self&&self instanceof WorkerGlobalScope&&self.navigator instanceof WorkerNavigator||"undefined"!=typeof globalThis&&globalThis instanceof WorkerGlobalScope&&globalThis.navigator instanceof WorkerNavigator),o=n?window:"undefined"!=typeof WorkerGlobalScope&&("undefined"!=typeof self&&self instanceof WorkerGlobalScope&&self||"undefined"!=typeof globalThis&&globalThis instanceof WorkerGlobalScope&&globalThis),a=""+o?.location,s=/iPad|iPhone|iPod/.test(navigator.userAgent),c=s&&"undefined"==typeof SharedWorker,u=(()=>{const e=navigator.userAgent.match(/Firefox[/\s](\d+\.\d+)/);return Array.isArray(e)&&e.length>=2?+e[1]:0})(),d=Boolean(n&&window.document.documentMode),f=!!navigator.sendBeacon},1117:(e,t,r)=>{r.d(t,{w:()=>o});var n=r(50);const i={agentIdentifier:"",ee:void 0};class o{constructor(e){try{if("object"!=typeof e)return(0,n.Z)("shared context requires an object as input");this.sharedContext={},Object.assign(this.sharedContext,i),Object.entries(e).forEach((e=>{let[t,r]=e;Object.keys(i).includes(t)&&(this.sharedContext[t]=r)}))}catch(e){(0,n.Z)("An error occured while setting SharedContext",e)}}}},8e3:(e,t,r)=>{r.d(t,{L:()=>d,R:()=>c});var n=r(2177),i=r(1284),o=r(4322),a=r(3325);const s={};function c(e,t){const r={staged:!1,priority:a.p[t]||0};u(e),s[e].get(t)||s[e].set(t,r)}function u(e){e&&(s[e]||(s[e]=new Map))}function d(){let e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"feature";if(u(e),!e||!s[e].get(t))return a(t);s[e].get(t).staged=!0;const r=[...s[e]];function a(t){const r=e?n.ee.get(e):n.ee,a=o.X.handlers;if(r.backlog&&a){var s=r.backlog[t],c=a[t];if(c){for(var u=0;s&&u {let[t,r]=e;return r.staged}))&&(r.sort(((e,t)=>e[1].priority-t[1].priority)),r.forEach((e=>{let[t]=e;a(t)})))}function f(e,t){var r=e[1];(0,i.D)(t[r],(function(t,r){var n=e[0];if(r[0]===n){var i=r[1],o=e[3],a=e[2];i.apply(o,a)}}))}},2177:(e,t,r)=>{r.d(t,{c:()=>f,ee:()=>u});var n=r(8632),i=r(2210),o=r(1284),a=r(5763),s="nr@context";let c=(0,n.fP)();var u;function d(){}function f(e){return(0,i.X)(e,s,l)}function l(){return new d}function h(){u.aborted=!0,u.backlog={}}c.ee?u=c.ee:(u=function e(t,r){var n={},c={},f={},g=!1;try{g=16===r.length&&(0,a.OP)(r).isolatedBacklog}catch(e){}var p={on:b,addEventListener:b,removeEventListener:y,emit:v,get:x,listeners:w,context:m,buffer:A,abort:h,aborted:!1,isBuffering:E,debugId:r,backlog:g?{}:t&&"object"==typeof t.backlog?t.backlog:{}};return p;function m(e){return e&&e instanceof d?e:e?(0,i.X)(e,s,l):l()}function v(e,r,n,i,o){if(!1!==o&&(o=!0),!u.aborted||i){t&&o&&t.emit(e,r,n);for(var a=m(n),s=w(e),d=s.length,f=0;fn,p:()=>i});var n=r(2177).ee.get("handle");function i(e,t,r,i,o){o?(o.buffer([e],i),o.emit(e,t,r)):(n.buffer([e],i),n.emit(e,t,r))}},4322:(e,t,r)=>{r.d(t,{X:()=>o});var n=r(5546);o.on=a;var i=o.handlers={};function o(e,t,r,o){a(o||n.E,i,e,t,r)}function a(e,t,r,i,o){o||(o="feature"),e||(e=n.E);var a=t[o]=t[o]||{};(a[r]=a[r]||[]).push([e,i])}},3239:(e,t,r)=>{r.d(t,{bP:()=>s,iz:()=>c,m$:()=>a});var n=r(385);let i=!1,o=!1;try{const e={get passive(){return i=!0,!1},get signal(){return o=!0,!1}};n._A.addEventListener("test",null,e),n._A.removeEventListener("test",null,e)}catch(e){}function a(e,t){return i||o?{capture:!!e,passive:i,signal:t}:!!e}function s(e,t){let r=arguments.length>2&&void 0!==arguments[2]&&arguments[2],n=arguments.length>3?arguments[3]:void 0;window.addEventListener(e,t,a(r,n))}function c(e,t){let r=arguments.length>2&&void 0!==arguments[2]&&arguments[2],n=arguments.length>3?arguments[3]:void 0;document.addEventListener(e,t,a(r,n))}},4402:(e,t,r)=>{r.d(t,{Ht:()=>u,M:()=>c,Rl:()=>a,ky:()=>s});var n=r(385);const i="xxxxxxxx-xxxx-4xxx-yxxx-xxxxxxxxxxxx";function o(e,t){return e?15&e[t]:16*Math.random()|0}function a(){const e=n._A?.crypto||n._A?.msCrypto;let t,r=0;return e&&e.getRandomValues&&(t=e.getRandomValues(new Uint8Array(31))),i.split("").map((e=>"x"===e?o(t,++r).toString(16):"y"===e?(3&o()|8).toString(16):e)).join("")}function s(e){const t=n._A?.crypto||n._A?.msCrypto;let r,i=0;t&&t.getRandomValues&&(r=t.getRandomValues(new Uint8Array(31)));const a=[];for(var s=0;s {r.d(t,{Bq:()=>n,Hb:()=>o,oD:()=>i});const n="NRBA",i=144e5,o=18e5},7894:(e,t,r)=>{function n(){return Math.round(performance.now())}r.d(t,{z:()=>n})},7243:(e,t,r)=>{r.d(t,{e:()=>o});var n=r(385),i={};function o(e){if(e in i)return i[e];if(0===(e||"").indexOf("data:"))return{protocol:"data"};let t;var r=n._A?.location,o={};if(n.il)t=document.createElement("a"),t.href=e;else try{t=new URL(e,r.href)}catch(e){return o}o.port=t.port;var a=t.href.split("://");!o.port&&a[1]&&(o.port=a[1].split("/")[0].split("@").pop().split(":")[1]),o.port&&"0"!==o.port||(o.port="https"===a[0]?"443":"80"),o.hostname=t.hostname||r.hostname,o.pathname=t.pathname,o.protocol=a[0],"/"!==o.pathname.charAt(0)&&(o.pathname="/"+o.pathname);var s=!t.protocol||":"===t.protocol||t.protocol===r.protocol,c=t.hostname===r.hostname&&t.port===r.port;return o.sameOrigin=s&&(!t.hostname||c),"/"===o.pathname&&(i[e]=o),o}},50:(e,t,r)=>{function n(e,t){"function"==typeof console.warn&&(console.warn("New Relic: ".concat(e)),t&&console.warn(t))}r.d(t,{Z:()=>n})},2587:(e,t,r)=>{r.d(t,{N:()=>c,T:()=>u});var n=r(2177),i=r(5546),o=r(8e3),a=r(3325);const s={stn:[a.D.sessionTrace],err:[a.D.jserrors,a.D.metrics],ins:[a.D.pageAction],spa:[a.D.spa],sr:[a.D.sessionReplay,a.D.sessionTrace]};function c(e,t){const r=n.ee.get(t);e&&"object"==typeof e&&(Object.entries(e).forEach((e=>{let[t,n]=e;void 0===u[t]&&(s[t]?s[t].forEach((e=>{n?(0,i.p)("feat-"+t,[],void 0,e,r):(0,i.p)("block-"+t,[],void 0,e,r),(0,i.p)("rumresp-"+t,[Boolean(n)],void 0,e,r)})):n&&(0,i.p)("feat-"+t,[],void 0,void 0,r),u[t]=Boolean(n))})),Object.keys(s).forEach((e=>{void 0===u[e]&&(s[e]?.forEach((t=>(0,i.p)("rumresp-"+e,[!1],void 0,t,r))),u[e]=!1)})),(0,o.L)(t,a.D.pageViewEvent))}const u={}},2210:(e,t,r)=>{r.d(t,{X:()=>i});var n=Object.prototype.hasOwnProperty;function i(e,t,r){if(n.call(e,t))return e[t];var i=r();if(Object.defineProperty&&Object.keys)try{return Object.defineProperty(e,t,{value:i,writable:!0,enumerable:!1}),i}catch(e){}return e[t]=i,i}},1284:(e,t,r)=>{r.d(t,{D:()=>n});const n=(e,t)=>Object.entries(e||{}).map((e=>{let[r,n]=e;return t(r,n)}))},4351:(e,t,r)=>{r.d(t,{P:()=>o});var n=r(2177);const i=()=>{const e=new WeakSet;return(t,r)=>{if("object"==typeof r&&null!==r){if(e.has(r))return;e.add(r)}return r}};function o(e){try{return JSON.stringify(e,i())}catch(e){try{n.ee.emit("internal-error",[e])}catch(e){}}}},3960:(e,t,r)=>{r.d(t,{K:()=>a,b:()=>o});var n=r(3239);function i(){return"undefined"==typeof document||"complete"===document.readyState}function o(e,t){if(i())return e();(0,n.bP)("load",e,t)}function a(e){if(i())return e();(0,n.iz)("DOMContentLoaded",e)}},8632:(e,t,r)=>{r.d(t,{EZ:()=>u,Qy:()=>c,ce:()=>o,fP:()=>a,gG:()=>d,mF:()=>s});var n=r(7894),i=r(385);const o={beacon:"bam.nr-data.net",errorBeacon:"bam.nr-data.net"};function a(){return i._A.NREUM||(i._A.NREUM={}),void 0===i._A.newrelic&&(i._A.newrelic=i._A.NREUM),i._A.NREUM}function s(){let e=a();return e.o||(e.o={ST:i._A.setTimeout,SI:i._A.setImmediate,CT:i._A.clearTimeout,XHR:i._A.XMLHttpRequest,REQ:i._A.Request,EV:i._A.Event,PR:i._A.Promise,MO:i._A.MutationObserver,FETCH:i._A.fetch}),e}function c(e,t,r){let i=a();const o=i.initializedAgents||{},s=o[e]||{};return Object.keys(s).length||(s.initializedAt={ms:(0,n.z)(),date:new Date}),i.initializedAgents={...o,[e]:{...s,[r]:t}},i}function u(e,t){a()[e]=t}function d(){return function(){let e=a();const t=e.info||{};e.info={beacon:o.beacon,errorBeacon:o.errorBeacon,...t}}(),function(){let e=a();const t=e.init||{};e.init={...t}}(),s(),function(){let e=a();const t=e.loader_config||{};e.loader_config={...t}}(),a()}},7956:(e,t,r)=>{r.d(t,{N:()=>i});var n=r(3239);function i(e){let t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],r=arguments.length>2?arguments[2]:void 0,i=arguments.length>3?arguments[3]:void 0;return void(0,n.iz)("visibilitychange",(function(){if(t)return void("hidden"==document.visibilityState&&e());e(document.visibilityState)}),r,i)}},1214:(e,t,r)=>{r.d(t,{em:()=>v,u5:()=>N,QU:()=>S,_L:()=>I,Gm:()=>L,Lg:()=>M,gy:()=>U,BV:()=>Q,Kf:()=>ee});var n=r(2177);const i="nr@original";var o=Object.prototype.hasOwnProperty,a=!1;function s(e,t){return e||(e=n.ee),r.inPlace=function(e,t,n,i,o){n||(n="");var a,s,c,u="-"===n.charAt(0);for(c=0;c 2?n-2:0),o=2;o {r(A[T],e,w),r(E[T],e,w)})),r(l._A,"fetch",y),t.on(y+"end",(function(e,r){var n=this;if(r){var i=r.headers.get("content-length");null!==i&&(n.rxSize=i),t.emit(y+"done",[null,r],n)}else t.emit(y+"done",[e],n)})),t}const O={},j=["pushState","replaceState"];function S(e){const t=function(e){return(e||n.ee).get("history")}(e);return!l.il||O[t.debugId]++||(O[t.debugId]=1,s(t).inPlace(window.history,j,"-")),t}var P=r(3239);const C={},R=["appendChild","insertBefore","replaceChild"];function I(e){const t=function(e){return(e||n.ee).get("jsonp")}(e);if(!l.il||C[t.debugId])return t;C[t.debugId]=!0;var r=s(t),i=/[?&](?:callback|cb)=([^&#]+)/,o=/(.*)\.([^.]+)/,a=/^(\w+)(\.|$)(.*)$/;function c(e,t){var r=e.match(a),n=r[1],i=r[3];return i?c(i,t[n]):t[n]}return r.inPlace(Node.prototype,R,"dom-"),t.on("dom-start",(function(e){!function(e){if(!e||"string"!=typeof e.nodeName||"script"!==e.nodeName.toLowerCase())return;if("function"!=typeof e.addEventListener)return;var n=(a=e.src,s=a.match(i),s?s[1]:null);var a,s;if(!n)return;var u=function(e){var t=e.match(o);if(t&&t.length>=3)return{key:t[2],parent:c(t[1],window)};return{key:e,parent:window}}(n);if("function"!=typeof u.parent[u.key])return;var d={};function f(){t.emit("jsonp-end",[],d),e.removeEventListener("load",f,(0,P.m$)(!1)),e.removeEventListener("error",l,(0,P.m$)(!1))}function l(){t.emit("jsonp-error",[],d),t.emit("jsonp-end",[],d),e.removeEventListener("load",f,(0,P.m$)(!1)),e.removeEventListener("error",l,(0,P.m$)(!1))}r.inPlace(u.parent,[u.key],"cb-",d),e.addEventListener("load",f,(0,P.m$)(!1)),e.addEventListener("error",l,(0,P.m$)(!1)),t.emit("new-jsonp",[e.src],d)}(e[0])})),t}var k=r(5763);const H={};function L(e){const t=function(e){return(e||n.ee).get("mutation")}(e);if(!l.il||H[t.debugId])return t;H[t.debugId]=!0;var r=s(t),i=k.Yu.MO;return i&&(window.MutationObserver=function(e){return this instanceof i?new i(r(e,"fn-")):i.apply(this,arguments)},MutationObserver.prototype=i.prototype),t}const z={};function M(e){const t=function(e){return(e||n.ee).get("promise")}(e);if(z[t.debugId])return t;z[t.debugId]=!0;var r=n.c,o=s(t),a=k.Yu.PR;return a&&function(){function e(r){var n=t.context(),i=o(r,"executor-",n,null,!1);const s=Reflect.construct(a,[i],e);return t.context(s).getCtx=function(){return n},s}l._A.Promise=e,Object.defineProperty(e,"name",{value:"Promise"}),e.toString=function(){return a.toString()},Object.setPrototypeOf(e,a),["all","race"].forEach((function(r){const n=a[r];e[r]=function(e){let i=!1;[...e||[]].forEach((e=>{this.resolve(e).then(a("all"===r),a(!1))}));const o=n.apply(this,arguments);return o;function a(e){return function(){t.emit("propagate",[null,!i],o,!1,!1),i=i||!e}}}})),["resolve","reject"].forEach((function(r){const n=a[r];e[r]=function(e){const r=n.apply(this,arguments);return e!==r&&t.emit("propagate",[e,!0],r,!1,!1),r}})),e.prototype=a.prototype;const n=a.prototype.then;a.prototype.then=function(){var e=this,i=r(e);i.promise=e;for(var a=arguments.length,s=new Array(a),c=0;c e())),t};function m(e,t){i.inPlace(t,["onreadystatechange"],"fn-",E)}function b(){var e=this,t=r.context(e);e.readyState>3&&!t.resolved&&(t.resolved=!0,r.emit("xhr-resolved",[],e)),i.inPlace(e,f,"fn-",E)}if(function(e,t){for(var r in e)t[r]=e[r]}(o,p),p.prototype=o.prototype,i.inPlace(p.prototype,J,"-xhr-",E),r.on("send-xhr-start",(function(e,t){m(e,t),function(e){h.push(e),a&&(y?y.then(A):u?u(A):(w=-w,x.data=w))}(t)})),r.on("open-xhr-start",m),a){var y=c&&c.resolve();if(!u&&!c){var w=1,x=document.createTextNode(w);new a(A).observe(x,{characterData:!0})}}else t.on("fn-end",(function(e){e[0]&&e[0].type===d||A()}));function A(){for(var e=0;e {r.d(t,{t:()=>n});const n=r(3325).D.ajax},6660:(e,t,r)=>{r.d(t,{A:()=>i,t:()=>n});const n=r(3325).D.jserrors,i="nr@seenError"},3081:(e,t,r)=>{r.d(t,{gF:()=>o,mY:()=>i,t9:()=>n,vz:()=>s,xS:()=>a});const n=r(3325).D.metrics,i="sm",o="cm",a="storeSupportabilityMetrics",s="storeEventMetrics"},4649:(e,t,r)=>{r.d(t,{t:()=>n});const n=r(3325).D.pageAction},7633:(e,t,r)=>{r.d(t,{Dz:()=>i,OJ:()=>a,qw:()=>o,t9:()=>n});const n=r(3325).D.pageViewEvent,i="firstbyte",o="domcontent",a="windowload"},9251:(e,t,r)=>{r.d(t,{t:()=>n});const n=r(3325).D.pageViewTiming},3614:(e,t,r)=>{r.d(t,{BST_RESOURCE:()=>i,END:()=>s,FEATURE_NAME:()=>n,FN_END:()=>u,FN_START:()=>c,PUSH_STATE:()=>d,RESOURCE:()=>o,START:()=>a});const n=r(3325).D.sessionTrace,i="bstResource",o="resource",a="-start",s="-end",c="fn"+a,u="fn"+s,d="pushState"},7836:(e,t,r)=>{r.d(t,{BODY:()=>A,CB_END:()=>E,CB_START:()=>u,END:()=>x,FEATURE_NAME:()=>i,FETCH:()=>_,FETCH_BODY:()=>v,FETCH_DONE:()=>m,FETCH_START:()=>p,FN_END:()=>c,FN_START:()=>s,INTERACTION:()=>l,INTERACTION_API:()=>d,INTERACTION_EVENTS:()=>o,JSONP_END:()=>b,JSONP_NODE:()=>g,JS_TIME:()=>T,MAX_TIMER_BUDGET:()=>a,REMAINING:()=>f,SPA_NODE:()=>h,START:()=>w,originalSetTimeout:()=>y});var n=r(5763);const i=r(3325).D.spa,o=["click","submit","keypress","keydown","keyup","change"],a=999,s="fn-start",c="fn-end",u="cb-start",d="api-ixn-",f="remaining",l="interaction",h="spaNode",g="jsonpNode",p="fetch-start",m="fetch-done",v="fetch-body-",b="jsonp-end",y=n.Yu.ST,w="-start",x="-end",A="-body",E="cb"+x,T="jsTime",_="fetch"},5938:(e,t,r)=>{r.d(t,{W:()=>o});var n=r(5763),i=r(2177);class o{constructor(e,t,r){this.agentIdentifier=e,this.aggregator=t,this.ee=i.ee.get(e,(0,n.OP)(this.agentIdentifier).isolatedBacklog),this.featureName=r,this.blocked=!1}}},9144:(e,t,r)=>{r.d(t,{j:()=>m});var n=r(3325),i=r(5763),o=r(5546),a=r(2177),s=r(7894),c=r(8e3),u=r(3960),d=r(385),f=r(50),l=r(3081),h=r(8632);function g(){const e=(0,h.gG)();["setErrorHandler","finished","addToTrace","inlineHit","addRelease","addPageAction","setCurrentRouteName","setPageViewName","setCustomAttribute","interaction","noticeError","setUserId"].forEach((t=>{e[t]=function(){for(var r=arguments.length,n=new Array(r),i=0;i 1?r-1:0),i=1;i {e.exposed&&e.api[t]&&o.push(e.api[t](...n))})),o.length>1?o:o[0]}(t,...n)}}))}var p=r(2587);function m(e){let t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:{},m=arguments.length>2?arguments[2]:void 0,v=arguments.length>3?arguments[3]:void 0,{init:b,info:y,loader_config:w,runtime:x={loaderType:m},exposed:A=!0}=t;const E=(0,h.gG)();y||(b=E.init,y=E.info,w=E.loader_config),(0,i.Dg)(e,b||{}),(0,i.GE)(e,w||{}),(0,i.sU)(e,x),y.jsAttributes??={},d.v6&&(y.jsAttributes.isWorker=!0),(0,i.CX)(e,y),g();const T=function(e,t){t||(0,c.R)(e,"api");const h={};var g=a.ee.get(e),p=g.get("tracer"),m="api-",v=m+"ixn-";function b(t,r,n,o){const a=(0,i.C5)(e);return null===r?delete a.jsAttributes[t]:(0,i.CX)(e,{...a,jsAttributes:{...a.jsAttributes,[t]:r}}),x(m,n,!0,o||null===r?"session":void 0)(t,r)}function y(){}["setErrorHandler","finished","addToTrace","inlineHit","addRelease"].forEach((e=>h[e]=x(m,e,!0,"api"))),h.addPageAction=x(m,"addPageAction",!0,n.D.pageAction),h.setCurrentRouteName=x(m,"routeName",!0,n.D.spa),h.setPageViewName=function(t,r){if("string"==typeof t)return"/"!==t.charAt(0)&&(t="/"+t),(0,i.OP)(e).customTransaction=(r||"http://custom.transaction")+t,x(m,"setPageViewName",!0)()},h.setCustomAttribute=function(e,t){let r=arguments.length>2&&void 0!==arguments[2]&&arguments[2];if("string"==typeof e){if(["string","number"].includes(typeof t)||null===t)return b(e,t,"setCustomAttribute",r);(0,f.Z)("Failed to execute setCustomAttribute.\nNon-null value must be a string or number type, but a type of was provided."))}else(0,f.Z)("Failed to execute setCustomAttribute.\nName must be a string type, but a type of was provided."))},h.setUserId=function(e){if("string"==typeof e||null===e)return b("enduser.id",e,"setUserId",!0);(0,f.Z)("Failed to execute setUserId.\nNon-null value must be a string type, but a type of was provided."))},h.interaction=function(){return(new y).get()};var w=y.prototype={createTracer:function(e,t){var r={},i=this,a="function"==typeof t;return(0,o.p)(v+"tracer",[(0,s.z)(),e,r],i,n.D.spa,g),function(){if(p.emit((a?"":"no-")+"fn-start",[(0,s.z)(),i,a],r),a)try{return t.apply(this,arguments)}catch(e){throw p.emit("fn-err",[arguments,this,"string"==typeof e?new Error(e):e],r),e}finally{p.emit("fn-end",[(0,s.z)()],r)}}}};function x(e,t,r,i){return function(){return(0,o.p)(l.xS,["API/"+t+"/called"],void 0,n.D.metrics,g),i&&(0,o.p)(e+t,[(0,s.z)(),...arguments],r?null:this,i,g),r?void 0:this}}function A(){r.e(439).then(r.bind(r,7438)).then((t=>{let{setAPI:r}=t;r(e),(0,c.L)(e,"api")})).catch((()=>(0,f.Z)("Downloading runtime APIs failed...")))}return["actionText","setName","setAttribute","save","ignore","onEnd","getContext","end","get"].forEach((e=>{w[e]=x(v,e,void 0,n.D.spa)})),h.noticeError=function(e,t){"string"==typeof e&&(e=new Error(e)),(0,o.p)(l.xS,["API/noticeError/called"],void 0,n.D.metrics,g),(0,o.p)("err",[e,(0,s.z)(),!1,t],void 0,n.D.jserrors,g)},d.il?(0,u.b)((()=>A()),!0):A(),h}(e,v);return(0,h.Qy)(e,T,"api"),(0,h.Qy)(e,A,"exposed"),(0,h.EZ)("activatedFeatures",p.T),T}},3325:(e,t,r)=>{r.d(t,{D:()=>n,p:()=>i});const n={ajax:"ajax",jserrors:"jserrors",metrics:"metrics",pageAction:"page_action",pageViewEvent:"page_view_event",pageViewTiming:"page_view_timing",sessionReplay:"session_replay",sessionTrace:"session_trace",spa:"spa"},i={[n.pageViewEvent]:1,[n.pageViewTiming]:2,[n.metrics]:3,[n.jserrors]:4,[n.ajax]:5,[n.sessionTrace]:6,[n.pageAction]:7,[n.spa]:8,[n.sessionReplay]:9}}},n={};function i(e){var t=n[e];if(void 0!==t)return t.exports;var o=n[e]={exports:{}};return r[e](o,o.exports,i),o.exports}i.m=r,i.d=(e,t)=>{for(var r in t)i.o(t,r)&&!i.o(e,r)&&Object.defineProperty(e,r,{enumerable:!0,get:t[r]})},i.f={},i.e=e=>Promise.all(Object.keys(i.f).reduce(((t,r)=>(i.f[r](e,t),t)),[])),i.u=e=>(({78:"page_action-aggregate",147:"metrics-aggregate",242:"session-manager",317:"jserrors-aggregate",348:"page_view_timing-aggregate",412:"lazy-feature-loader",439:"async-api",538:"recorder",590:"session_replay-aggregate",675:"compressor",733:"session_trace-aggregate",786:"page_view_event-aggregate",873:"spa-aggregate",898:"ajax-aggregate"}[e]||e)+"."+{78:"ac76d497",147:"3dc53903",148:"1a20d5fe",242:"2a64278a",317:"49e41428",348:"bd6de33a",412:"2f55ce66",439:"30bd804e",538:"1b18459f",590:"cf0efb30",675:"ae9f91a8",733:"83105561",786:"06482edd",860:"03a8b7a5",873:"e6b09d52",898:"998ef92b"}[e]+"-1.236.0.min.js"),i.o=(e,t)=>Object.prototype.hasOwnProperty.call(e,t),e={},t="NRBA:",i.l=(r,n,o,a)=>{if(e[r])e[r].push(n);else{var s,c;if(void 0!==o)for(var u=document.getElementsByTagName("script"),d=0;d {s.onerror=s.onload=null,clearTimeout(h);var i=e[r];if(delete e[r],s.parentNode&&s.parentNode.removeChild(s),i&&i.forEach((e=>e(n))),t)return t(n)},h=setTimeout(l.bind(null,void 0,{type:"timeout",target:s}),12e4);s.onerror=l.bind(null,s.onerror),s.onload=l.bind(null,s.onload),c&&document.head.appendChild(s)}},i.r=e=>{"undefined"!=typeof Symbol&&Symbol.toStringTag&&Object.defineProperty(e,Symbol.toStringTag,{value:"Module"}),Object.defineProperty(e,"__esModule",{value:!0})},i.j=364,i.p="https://js-agent.newrelic.com/",(()=>{var e={364:0,953:0};i.f.j=(t,r)=>{var n=i.o(e,t)?e[t]:void 0;if(0!==n)if(n)r.push(n[2]);else{var o=new Promise(((r,i)=>n=e[t]=[r,i]));r.push(n[2]=o);var a=i.p+i.u(t),s=new Error;i.l(a,(r=>{if(i.o(e,t)&&(0!==(n=e[t])&&(e[t]=void 0),n)){var o=r&&("load"===r.type?"missing":r.type),a=r&&r.target&&r.target.src;s.message="Loading chunk "+t+" failed.\n("+o+": "+a+")",s.name="ChunkLoadError",s.type=o,s.request=a,n[1](s)}}),"chunk-"+t,t)}};var t=(t,r)=>{var n,o,[a,s,c]=r,u=0;if(a.some((t=>0!==e[t]))){for(n in s)i.o(s,n)&&(i.m[n]=s[n]);if(c)c(i)}for(t&&t(r);u {i.r(o);var e=i(3325),t=i(5763);const r=Object.values(e.D);function n(e){const n={};return r.forEach((r=>{n[r]=function(e,r){return!1!==(0,t.Mt)(r,"".concat(e,".enabled"))}(r,e)})),n}var a=i(9144);var s=i(5546),c=i(385),u=i(8e3),d=i(5938),f=i(3960),l=i(50);class h extends d.W{constructor(e,t,r){let n=!(arguments.length>3&&void 0!==arguments[3])||arguments[3];super(e,t,r),this.auto=n,this.abortHandler,this.featAggregate,this.onAggregateImported,n&&(0,u.R)(e,r)}importAggregator(){let e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:{};if(this.featAggregate||!this.auto)return;const r=c.il&&!0===(0,t.Mt)(this.agentIdentifier,"privacy.cookies_enabled");let n;this.onAggregateImported=new Promise((e=>{n=e}));const o=async()=>{let t;try{if(r){const{setupAgentSession:e}=await Promise.all([i.e(860),i.e(242)]).then(i.bind(i,3228));t=e(this.agentIdentifier)}}catch(e){(0,l.Z)("A problem occurred when starting up session manager. This page will not start or extend any session.",e)}try{if(!this.shouldImportAgg(this.featureName,t))return void(0,u.L)(this.agentIdentifier,this.featureName);const{lazyFeatureLoader:r}=await i.e(412).then(i.bind(i,8582)),{Aggregate:o}=await r(this.featureName,"aggregate");this.featAggregate=new o(this.agentIdentifier,this.aggregator,e),n(!0)}catch(e){(0,l.Z)("Downloading and initializing ".concat(this.featureName," failed..."),e),this.abortHandler?.(),n(!1)}};c.il?(0,f.b)((()=>o()),!0):o()}shouldImportAgg(r,n){return r!==e.D.sessionReplay||!1!==(0,t.Mt)(this.agentIdentifier,"session_trace.enabled")&&(!!n?.isNew||!!n?.state.sessionReplay)}}var g=i(7633),p=i(7894);class m extends h{static featureName=g.t9;constructor(r,n){let i=!(arguments.length>2&&void 0!==arguments[2])||arguments[2];if(super(r,n,g.t9,i),("undefined"==typeof PerformanceNavigationTiming||c.Tt)&&"undefined"!=typeof PerformanceTiming){const n=(0,t.OP)(r);n[g.Dz]=Math.max(Date.now()-n.offset,0),(0,f.K)((()=>n[g.qw]=Math.max((0,p.z)()-n[g.Dz],0))),(0,f.b)((()=>{const t=(0,p.z)();n[g.OJ]=Math.max(t-n[g.Dz],0),(0,s.p)("timing",["load",t],void 0,e.D.pageViewTiming,this.ee)}))}this.importAggregator()}}var v=i(1117),b=i(1284);class y extends v.w{constructor(e){super(e),this.aggregatedData={}}store(e,t,r,n,i){var o=this.getBucket(e,t,r,i);return o.metrics=function(e,t){t||(t={count:0});return t.count+=1,(0,b.D)(e,(function(e,r){t[e]=w(r,t[e])})),t}(n,o.metrics),o}merge(e,t,r,n,i){var o=this.getBucket(e,t,n,i);if(o.metrics){var a=o.metrics;a.count+=r.count,(0,b.D)(r,(function(e,t){if("count"!==e){var n=a[e],i=r[e];i&&!i.c?a[e]=w(i.t,n):a[e]=function(e,t){if(!t)return e;t.c||(t=x(t.t));return t.min=Math.min(e.min,t.min),t.max=Math.max(e.max,t.max),t.t+=e.t,t.sos+=e.sos,t.c+=e.c,t}(i,a[e])}}))}else o.metrics=r}storeMetric(e,t,r,n){var i=this.getBucket(e,t,r);return i.stats=w(n,i.stats),i}getBucket(e,t,r,n){this.aggregatedData[e]||(this.aggregatedData[e]={});var i=this.aggregatedData[e][t];return i||(i=this.aggregatedData[e][t]={params:r||{}},n&&(i.custom=n)),i}get(e,t){return t?this.aggregatedData[e]&&this.aggregatedData[e][t]:this.aggregatedData[e]}take(e){for(var t={},r="",n=!1,i=0;i t.max&&(t.max=e),e 2&&void 0!==arguments[2])||arguments[2];super(e,r,j.t,n),c.il&&((0,t.OP)(e).initHidden=Boolean("hidden"===document.visibilityState),(0,N.N)((()=>(0,s.p)("docHidden",[(0,p.z)()],void 0,j.t,this.ee)),!0),(0,O.bP)("pagehide",(()=>(0,s.p)("winPagehide",[(0,p.z)()],void 0,j.t,this.ee))),this.importAggregator())}}var P=i(3081);class C extends h{static featureName=P.t9;constructor(e,t){let r=!(arguments.length>2&&void 0!==arguments[2])||arguments[2];super(e,t,P.t9,r),this.importAggregator()}}var R,I=i(2210),k=i(1214),H=i(2177),L={};try{R=localStorage.getItem("__nr_flags").split(","),console&&"function"==typeof console.log&&(L.console=!0,-1!==R.indexOf("dev")&&(L.dev=!0),-1!==R.indexOf("nr_dev")&&(L.nrDev=!0))}catch(e){}function z(e){try{L.console&&z(e)}catch(e){}}L.nrDev&&H.ee.on("internal-error",(function(e){z(e.stack)})),L.dev&&H.ee.on("fn-err",(function(e,t,r){z(r.stack)})),L.dev&&(z("NR AGENT IN DEVELOPMENT MODE"),z("flags: "+(0,b.D)(L,(function(e,t){return e})).join(", ")));var M=i(6660);class B extends h{static featureName=M.t;constructor(r,n){let i=!(arguments.length>2&&void 0!==arguments[2])||arguments[2];super(r,n,M.t,i),this.skipNext=0;try{this.removeOnAbort=new AbortController}catch(e){}const o=this;o.ee.on("fn-start",(function(e,t,r){o.abortHandler&&(o.skipNext+=1)})),o.ee.on("fn-err",(function(t,r,n){o.abortHandler&&!n[M.A]&&((0,I.X)(n,M.A,(function(){return!0})),this.thrown=!0,(0,s.p)("err",[n,(0,p.z)()],void 0,e.D.jserrors,o.ee))})),o.ee.on("fn-end",(function(){o.abortHandler&&!this.thrown&&o.skipNext>0&&(o.skipNext-=1)})),o.ee.on("internal-error",(function(t){(0,s.p)("ierr",[t,(0,p.z)(),!0],void 0,e.D.jserrors,o.ee)})),this.origOnerror=c._A.onerror,c._A.onerror=this.onerrorHandler.bind(this),c._A.addEventListener("unhandledrejection",(t=>{const r=function(e){let t="Unhandled Promise Rejection: ";if(e instanceof Error)try{return e.message=t+e.message,e}catch(t){return e}if(void 0===e)return new Error(t);try{return new Error(t+(0,D.P)(e))}catch(e){return new Error(t)}}(t.reason);(0,s.p)("err",[r,(0,p.z)(),!1,{unhandledPromiseRejection:1}],void 0,e.D.jserrors,this.ee)}),(0,O.m$)(!1,this.removeOnAbort?.signal)),(0,k.gy)(this.ee),(0,k.BV)(this.ee),(0,k.em)(this.ee),(0,t.OP)(r).xhrWrappable&&(0,k.Kf)(this.ee),this.abortHandler=this.#e,this.importAggregator()}#e(){this.removeOnAbort?.abort(),this.abortHandler=void 0}onerrorHandler(t,r,n,i,o){"function"==typeof this.origOnerror&&this.origOnerror(...arguments);try{this.skipNext?this.skipNext-=1:(0,s.p)("err",[o||new F(t,r,n),(0,p.z)()],void 0,e.D.jserrors,this.ee)}catch(t){try{(0,s.p)("ierr",[t,(0,p.z)(),!0],void 0,e.D.jserrors,this.ee)}catch(e){}}return!1}}function F(e,t,r){this.message=e||"Uncaught error with no additional information",this.sourceURL=t,this.line=r}let U=1;const q="nr@id";function G(e){const t=typeof e;return!e||"object"!==t&&"function"!==t?-1:e===c._A?0:(0,I.X)(e,q,(function(){return U++}))}function V(e){if("string"==typeof e&&e.length)return e.length;if("object"==typeof e){if("undefined"!=typeof ArrayBuffer&&e instanceof ArrayBuffer&&e.byteLength)return e.byteLength;if("undefined"!=typeof Blob&&e instanceof Blob&&e.size)return e.size;if(!("undefined"!=typeof FormData&&e instanceof FormData))try{return(0,D.P)(e).length}catch(e){return}}}var X=i(7243);class W{constructor(e){this.agentIdentifier=e,this.generateTracePayload=this.generateTracePayload.bind(this),this.shouldGenerateTrace=this.shouldGenerateTrace.bind(this)}generateTracePayload(e){if(!this.shouldGenerateTrace(e))return null;var r=(0,t.DL)(this.agentIdentifier);if(!r)return null;var n=(r.accountID||"").toString()||null,i=(r.agentID||"").toString()||null,o=(r.trustKey||"").toString()||null;if(!n||!i)return null;var a=(0,_.M)(),s=(0,_.Ht)(),c=Date.now(),u={spanId:a,traceId:s,timestamp:c};return(e.sameOrigin||this.isAllowedOrigin(e)&&this.useTraceContextHeadersForCors())&&(u.traceContextParentHeader=this.generateTraceContextParentHeader(a,s),u.traceContextStateHeader=this.generateTraceContextStateHeader(a,c,n,i,o)),(e.sameOrigin&&!this.excludeNewrelicHeader()||!e.sameOrigin&&this.isAllowedOrigin(e)&&this.useNewrelicHeaderForCors())&&(u.newrelicHeader=this.generateTraceHeader(a,s,c,n,i,o)),u}generateTraceContextParentHeader(e,t){return"00-"+t+"-"+e+"-01"}generateTraceContextStateHeader(e,t,r,n,i){return i+"@nr=0-1-"+r+"-"+n+"-"+e+"----"+t}generateTraceHeader(e,t,r,n,i,o){if(!("function"==typeof c._A?.btoa))return null;var a={v:[0,1],d:{ty:"Browser",ac:n,ap:i,id:e,tr:t,ti:r}};return o&&n!==o&&(a.d.tk=o),btoa((0,D.P)(a))}shouldGenerateTrace(e){return this.isDtEnabled()&&this.isAllowedOrigin(e)}isAllowedOrigin(e){var r=!1,n={};if((0,t.Mt)(this.agentIdentifier,"distributed_tracing")&&(n=(0,t.P_)(this.agentIdentifier).distributed_tracing),e.sameOrigin)r=!0;else if(n.allowed_origins instanceof Array)for(var i=0;i 2&&void 0!==arguments[2])||arguments[2];super(r,n,Z.t,i),(0,t.OP)(r).xhrWrappable&&(this.dt=new W(r),this.handler=(e,t,r,n)=>(0,s.p)(e,t,r,n,this.ee),(0,k.u5)(this.ee),(0,k.Kf)(this.ee),function(r,n,i,o){function a(e){var t=this;t.totalCbs=0,t.called=0,t.cbTime=0,t.end=E,t.ended=!1,t.xhrGuids={},t.lastSize=null,t.loadCaptureCalled=!1,t.params=this.params||{},t.metrics=this.metrics||{},e.addEventListener("load",(function(r){_(t,e)}),(0,O.m$)(!1)),c.IF||e.addEventListener("progress",(function(e){t.lastSize=e.loaded}),(0,O.m$)(!1))}function s(e){this.params={method:e[0]},T(this,e[1]),this.metrics={}}function u(e,n){var i=(0,t.DL)(r);i.xpid&&this.sameOrigin&&n.setRequestHeader("X-NewRelic-ID",i.xpid);var a=o.generateTracePayload(this.parsedOrigin);if(a){var s=!1;a.newrelicHeader&&(n.setRequestHeader("newrelic",a.newrelicHeader),s=!0),a.traceContextParentHeader&&(n.setRequestHeader("traceparent",a.traceContextParentHeader),a.traceContextStateHeader&&n.setRequestHeader("tracestate",a.traceContextStateHeader),s=!0),s&&(this.dt=a)}}function d(e,t){var r=this.metrics,i=e[0],o=this;if(r&&i){var a=V(i);a&&(r.txSize=a)}this.startTime=(0,p.z)(),this.listener=function(e){try{"abort"!==e.type||o.loadCaptureCalled||(o.params.aborted=!0),("load"!==e.type||o.called===o.totalCbs&&(o.onloadCalled||"function"!=typeof t.onload)&&"function"==typeof o.end)&&o.end(t)}catch(e){try{n.emit("internal-error",[e])}catch(e){}}};for(var s=0;s 1?e[1]=i:e.push(i)}else e[0]&&e[0].headers&&s(e[0].headers,n)&&(this.dt=n);function s(e,t){var r=!1;return t.newrelicHeader&&(e.set("newrelic",t.newrelicHeader),r=!0),t.traceContextParentHeader&&(e.set("traceparent",t.traceContextParentHeader),t.traceContextStateHeader&&e.set("tracestate",t.traceContextStateHeader),r=!0),r}}function x(e,t){this.params={},this.metrics={},this.startTime=(0,p.z)(),this.dt=t,e.length>=1&&(this.target=e[0]),e.length>=2&&(this.opts=e[1]);var r,n=this.opts||{},i=this.target;"string"==typeof i?r=i:"object"==typeof i&&i instanceof Y?r=i.url:c._A?.URL&&"object"==typeof i&&i instanceof URL&&(r=i.href),T(this,r);var o=(""+(i&&i instanceof Y&&i.method||n.method||"GET")).toUpperCase();this.params.method=o,this.txSize=V(n.body)||0}function A(t,r){var n;this.endTime=(0,p.z)(),this.params||(this.params={}),this.params.status=r?r.status:0,"string"==typeof this.rxSize&&this.rxSize.length>0&&(n=+this.rxSize);var o={txSize:this.txSize,rxSize:n,duration:(0,p.z)()-this.startTime};i("xhr",[this.params,o,this.startTime,this.endTime,"fetch"],this,e.D.ajax)}function E(t){var r=this.params,n=this.metrics;if(!this.ended){this.ended=!0;for(var o=0;o 2&&void 0!==arguments[2])||arguments[2];super(e,t,we.t,r),this.importAggregator()}}new class{constructor(e){let t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:(0,_.ky)(16);c._A?(this.agentIdentifier=t,this.sharedAggregator=new y({agentIdentifier:this.agentIdentifier}),this.features={},this.desiredFeatures=new Set(e.features||[]),this.desiredFeatures.add(m),Object.assign(this,(0,a.j)(this.agentIdentifier,e,e.loaderType||"agent")),this.start()):(0,l.Z)("Failed to initial the agent. Could not determine the runtime environment.")}get config(){return{info:(0,t.C5)(this.agentIdentifier),init:(0,t.P_)(this.agentIdentifier),loader_config:(0,t.DL)(this.agentIdentifier),runtime:(0,t.OP)(this.agentIdentifier)}}start(){const t="features";try{const r=n(this.agentIdentifier),i=[...this.desiredFeatures];i.sort(((t,r)=>e.p[t.featureName]-e.p[r.featureName])),i.forEach((t=>{if(r[t.featureName]||t.featureName===e.D.pageViewEvent){const n=function(t){switch(t){case e.D.ajax:return[e.D.jserrors];case e.D.sessionTrace:return[e.D.ajax,e.D.pageViewEvent];case e.D.sessionReplay:return[e.D.sessionTrace];case e.D.pageViewTiming:return[e.D.pageViewEvent];default:return[]}}(t.featureName);n.every((e=>r[e]))||(0,l.Z)("".concat(t.featureName," is enabled but one or more dependent features has been disabled (").concat((0,D.P)(n),"). This may cause unintended consequences or missing data...")),this.features[t.featureName]=new t(this.agentIdentifier,this.sharedAggregator)}})),(0,T.Qy)(this.agentIdentifier,this.features,t)}catch(e){(0,l.Z)("Failed to initialize all enabled instrument classes (agent aborted) -",e);for(const e in this.features)this.features[e].abortHandler?.();const r=(0,T.fP)();return delete r.initializedAgents[this.agentIdentifier]?.api,delete r.initializedAgents[this.agentIdentifier]?.[t],delete this.sharedAggregator,r.ee?.abort(),delete r.ee?.get(this.agentIdentifier),!1}}}({features:[J,m,S,class extends h{static featureName=oe;constructor(t,r){if(super(t,r,oe,!(arguments.length>2&&void 0!==arguments[2])||arguments[2]),!c.il)return;const n=this.ee;let i;(0,k.QU)(n),this.eventsEE=(0,k.em)(n),this.eventsEE.on(se,(function(e,t){this.bstStart=(0,p.z)()})),this.eventsEE.on(ae,(function(t,r){(0,s.p)("bst",[t[0],r,this.bstStart,(0,p.z)()],void 0,e.D.sessionTrace,n)})),n.on(ce+ne,(function(e){this.time=(0,p.z)(),this.startPath=location.pathname+location.hash})),n.on(ce+ie,(function(t){(0,s.p)("bstHist",[location.pathname+location.hash,this.startPath,this.time],void 0,e.D.sessionTrace,n)}));try{i=new PerformanceObserver((t=>{const r=t.getEntries();(0,s.p)(te,[r],void 0,e.D.sessionTrace,n)})),i.observe({type:re,buffered:!0})}catch(e){}this.importAggregator({resourceObserver:i})}},C,xe,B,class extends h{static featureName=de;constructor(e,r){if(super(e,r,de,!(arguments.length>2&&void 0!==arguments[2])||arguments[2]),!c.il)return;if(!(0,t.OP)(e).xhrWrappable)return;try{this.removeOnAbort=new AbortController}catch(e){}let n,i=0;const o=this.ee.get("tracer"),a=(0,k._L)(this.ee),s=(0,k.Lg)(this.ee),u=(0,k.BV)(this.ee),d=(0,k.Kf)(this.ee),f=this.ee.get("events"),l=(0,k.u5)(this.ee),h=(0,k.QU)(this.ee),g=(0,k.Gm)(this.ee);function m(e,t){h.emit("newURL",[""+window.location,t])}function v(){i++,n=window.location.hash,this[ve]=(0,p.z)()}function b(){i--,window.location.hash!==n&&m(0,!0);var e=(0,p.z)();this[pe]=~~this[pe]+e-this[ve],this[ye]=e}function y(e,t){e.on(t,(function(){this[t]=(0,p.z)()}))}this.ee.on(ve,v),s.on(be,v),a.on(be,v),this.ee.on(ye,b),s.on(ge,b),a.on(ge,b),this.ee.buffer([ve,ye,"xhr-resolved"],this.featureName),f.buffer([ve],this.featureName),u.buffer(["setTimeout"+le,"clearTimeout"+fe,ve],this.featureName),d.buffer([ve,"new-xhr","send-xhr"+fe],this.featureName),l.buffer([me+fe,me+"-done",me+he+fe,me+he+le],this.featureName),h.buffer(["newURL"],this.featureName),g.buffer([ve],this.featureName),s.buffer(["propagate",be,ge,"executor-err","resolve"+fe],this.featureName),o.buffer([ve,"no-"+ve],this.featureName),a.buffer(["new-jsonp","cb-start","jsonp-error","jsonp-end"],this.featureName),y(l,me+fe),y(l,me+"-done"),y(a,"new-jsonp"),y(a,"jsonp-end"),y(a,"cb-start"),h.on("pushState-end",m),h.on("replaceState-end",m),window.addEventListener("hashchange",m,(0,O.m$)(!0,this.removeOnAbort?.signal)),window.addEventListener("load",m,(0,O.m$)(!0,this.removeOnAbort?.signal)),window.addEventListener("popstate",(function(){m(0,i>1)}),(0,O.m$)(!0,this.removeOnAbort?.signal)),this.abortHandler=this.#e,this.importAggregator()}#e(){this.removeOnAbort?.abort(),this.abortHandler=void 0}}],loaderType:"spa"})})(),window.NRBA=o})(); window.jQuery || document.write(' ') CKEDITOR_BASEPATH='https://f1000research.com/js/vendor/ckeditor/' window.reactTheme = 'research'; window.MathJax = { CommonHTML: { linebreaks: { automatic: true } }, 'HTML-CSS': { linebreaks: { automatic: true } }, SVG: { linebreaks: { automatic: true } }, AuthorInit: function() { MathJax.Hub.Register.MessageHook('End Process', function () { let timeout = false; // holder for timeout id const delay = 250; // delay after event is "complete" to run callback const reflowMath = function() { const dispFormulas = document.querySelectorAll('.disp-formula.panel'); if (!dispFormulas) { return; } for (const dispFormula of dispFormulas) { const child = dispFormula.querySelector('.MathJax_Preview').nextSibling.firstChild; const isMultiline = MathJax.Hub.getAllJax(dispFormula)[0].root.isMultiline; if (dispFormula.offsetWidth < child.offsetWidth || isMultiline) { MathJax.Hub.Queue(['Rerender', MathJax.Hub, dispFormula]); } } }; window.addEventListener('resize', function() { clearTimeout(timeout); // clear the timeout timeout = setTimeout(reflowMath, delay); // start timing for event "completion" }); }); }, }; if (window.location.hash == '#_=_'){ window.location = window.location.href.split('#')[0] } !function(f,b,e,v,n,t,s){if(f.fbq)return;n=f.fbq=function() {n.callMethod? n.callMethod.apply(n,arguments):n.queue.push(arguments)} ;if(!f._fbq)f._fbq=n; n.push=n;n.loaded=!0;n.version='2.0';n.queue=[];t=b.createElement(e);t.async=!0; t.src=v;s=b.getElementsByTagName(e)[0];s.parentNode.insertBefore(t,s)}(window, document,'script','https://connect.facebook.net/en_US/fbevents.js'); fbq('init', '1641728616063202'); fbq('track', "PixelInitialized", {}); (function(h,o,t,j,a,r){ h.hj=h.hj||function(){(h.hj.q=h.hj.q||[]).push(arguments)}; h._hjSettings={hjid:2318163,hjsv:6}; a=o.getElementsByTagName('head')[0]; r=o.createElement('script');r.async=1; r.src=t+h._hjSettings.hjid+j+h._hjSettings.hjsv; a.appendChild(r); })(window,document,'https://static.hotjar.com/c/hotjar-','.js?sv='); search file_upload Submit your research search menu close search Browse Gateways & Collections How to Publish Submit your Research My Submissions Article Guidelines Article Guidelines (New Versions) Open Data, Software and Code Guidelines Open Data and Accessible Source Materials Guidelines (HSS) Open Data, Software and Code Guidelines (PSE) Prepublication Checks Production Process Posters and Slides Guidelines Document Guidelines Article Processing Charges Peer Review Finding Article Reviewers About How it Works For Reviewers Our Advisors Policies Glossary FAQs For Developers Newsroom Contact My Research Submissions Content and Tracking Alerts My Details Sign In file_upload Submit your research { "@context": "https://schema.org", "@type": "ScholarlyArticle", "mainEntityOfPage": { "@type": "WebPage", "@id": "https://f1000research.com/articles/13-1017" }, "headline": "Muscarinic receptor agonists and positive allosteric modulators in animal models of psychosis: protocol for...", "datePublished": "2024-09-06T15:41:14", "dateModified": "2025-01-02T16:32:07", "author": [ { "@type": "Person", "name": "Spyridon Siafis" }, { "@type": "Person", "name": "Nobuyuki Nomura" }, { "@type": "Person", "name": "Johannes Schneider-Thoma" }, { "@type": "Person", "name": "Irene Bighelli" }, { "@type": "Person", "name": "Alexandra Bannach-Brown" }, { "@type": "Person", "name": "Fiona J. Ramage" }, { "@type": "Person", "name": "Francesca Tinsdeall" }, { "@type": "Person", "name": "Ioannis Mantas" }, { "@type": "Person", "name": "Sameer Jauhar" }, { "@type": "Person", "name": "Sridhar Natesan" }, { "@type": "Person", "name": "Anthony C. Vernon" }, { "@type": "Person", "name": "Andrea de Bartolomeis" }, { "@type": "Person", "name": "Sabine M. Hölter" }, { "@type": "Person", "name": "Natascha I. Drude" }, { "@type": "Person", "name": "Ulf Tölch" }, { "@type": "Person", "name": "Wulf-Peter Hansen" }, { "@type": "Person", "name": "Virginia Chiocchia" }, { "@type": "Person", "name": "Oliver D. Howes" }, { "@type": "Person", "name": "Josef Priller" }, { "@type": "Person", "name": "Malcolm R. Macleod" }, { "@type": "Person", "name": "Georgia Salanti" }, { "@type": "Person", "name": "Stefan Leucht" } ], "publisher": { "@type": "Organization", "name": "F1000Research", "logo": { "@type": "ImageObject", "url": "https://f1000research.com/img/AMP/F1000Research_image.png", "height": 480, "width": 60 } }, "image": { "@type": "ImageObject", "url": "https://f1000research.com/img/AMP/F1000Research_image.png", "height": 1200, "width": 150 }, "description": " Background Muscarinic receptor agonism and positive allosteric modulation is a promising mechanism of action for treating psychosis, not present in most D2R-blocking antipsychotics. Xanomeline, an M1/M4-preferring agonist, has shown efficacy in late-stage clinical trials, with more compounds being investigated. Therefore, we aim to synthesize evidence on the preclinical efficacy of muscarinic receptor agonists and positive allosteric modulators in animal models of psychosis to provide unique insights and evidence-based information to guide drug development. Methods We plan a systematic review and meta-analysis of in vivo animal studies comparing muscarinic receptor agonists or positive allosteric modulators with control conditions and existing D2R-blocking antipsychotics in animals subjected to any method that induces behavioural changes of relevance for psychosis. We will identify eligible studies by searching multiple electronic databases. At least two independent reviewers will conduct the study selection and data extraction using prespecified forms and assess the risk of bias with the SYRCLE’s tool. Our primary outcomes include locomotor activity and prepulse inhibition measured with standardized mean differences. We will examine other behavioural readouts of relevance for psychosis as secondary outcomes, such as social interaction and cognitive function. We will synthesize the data using multi-level meta-analysis with a predefined random-effects structure, considering the non-independence of the data. In meta-regressions we will explore potential sources of heterogeneity from a predefined list of characteristics of the animal population, model, and intervention. We will assess the confidence in the evidence considering a self-developed instrument thatconsiders the internal and external validity of the evidence. Protocol registration PROSPERO-ID: CRD42024520914 " } { "@context": "http://schema.org", "@type": "BreadcrumbList", "itemListElement": [ { "@type": "ListItem", "position": "1", "item": { "@id": "https://f1000research.com/", "name": "Home" } }, { "@type": "ListItem", "position": "2", "item": { "@id": "https://f1000research.com/browse/articles", "name": "Browse" } }, { "@type": "ListItem", "position": "3", "item": { "@id": "https://f1000research.com/articles/13-1017", "name": "Muscarinic receptor agonists and positive allosteric modulators in..." } } ] } Home Browse Muscarinic receptor agonists and positive allosteric modulators in... ALL Metrics - Views Downloads Get PDF Get XML Cite How to cite this article Siafis S, Nomura N, Schneider-Thoma J et al. Muscarinic receptor agonists and positive allosteric modulators in animal models of psychosis: protocol for a systematic review and meta-analysis [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 13 :1017 ( https://doi.org/10.12688/f1000research.155356.2 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. Close Copy Citation Details Export Export Citation Sciwheel EndNote Ref. Manager Bibtex ProCite Sente EXPORT Select a format first Track Share ▬ ✚ Study Protocol Revised Muscarinic receptor agonists and positive allosteric modulators in animal models of psychosis: protocol for a systematic review and meta-analysis [version 2; peer review: 1 approved, 2 approved with reservations] Previous title: Muscarinic receptor agonists in animal models of psychosis: protocol for a systematic review and meta-analysis Spyridon Siafis https://orcid.org/0000-0001-8264-2039 1,2 , Nobuyuki Nomura 1-3 , Johannes Schneider-Thoma https://orcid.org/0000-0002-3448-9532 1,2 , [...] Irene Bighelli 1,2 , Alexandra Bannach-Brown https://orcid.org/0000-0002-3161-1395 4 , Fiona J. Ramage 5 , Francesca Tinsdeall 5 , Ioannis Mantas 6 , Sameer Jauhar 7 , Sridhar Natesan 8,9 , Anthony C. Vernon 10,11 , Andrea de Bartolomeis 12 , Sabine M. Hölter https://orcid.org/0000-0003-4878-5241 1,13 , Natascha I. Drude 4 , Ulf Tölch 4 , Wulf-Peter Hansen 14 , Virginia Chiocchia 15 , Oliver D. Howes 8-10 , Josef Priller 1,2,16,17 , Malcolm R. Macleod https://orcid.org/0000-0001-9187-9839 5 , Georgia Salanti https://orcid.org/0000-0002-3830-8508 15 , Stefan Leucht https://orcid.org/0000-0002-4934-4352 1,2 Spyridon Siafis https://orcid.org/0000-0001-8264-2039 1,2 , Nobuyuki Nomura 1-3 , [...] Johannes Schneider-Thoma https://orcid.org/0000-0002-3448-9532 1,2 , Irene Bighelli 1,2 , Alexandra Bannach-Brown https://orcid.org/0000-0002-3161-1395 4 , Fiona J. Ramage 5 , Francesca Tinsdeall 5 , Ioannis Mantas 6 , Sameer Jauhar 7 , Sridhar Natesan 8,9 , Anthony C. Vernon 10,11 , Andrea de Bartolomeis 12 , Sabine M. Hölter https://orcid.org/0000-0003-4878-5241 1,13 , Natascha I. Drude 4 , Ulf Tölch 4 , Wulf-Peter Hansen 14 , Virginia Chiocchia 15 , Oliver D. Howes 8-10 , Josef Priller 1,2,16,17 , Malcolm R. Macleod https://orcid.org/0000-0001-9187-9839 5 , Georgia Salanti https://orcid.org/0000-0002-3830-8508 15 , Stefan Leucht https://orcid.org/0000-0002-4934-4352 1,2 PUBLISHED 02 Jan 2025 Author details Author details 1 German Center for Mental Health (DZPG), partner site München/Augsburg, Munich, Germany 2 Technical University of Munich, School of Medicine and Health, Department of Psychiatry and Psychotherapy, Munich, Germany 3 Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan 4 QUEST Center for Responsible Research, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany 5 Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK 6 Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden 7 Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London, UK 8 Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Hammersmith Hospital, Imperial College London, London, UK 9 Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London, UK 10 MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK 11 Department of Basic and Clinical Neuroscience, School of Neuroscience, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London, UK 12 Section of Psychiatry, Laboratory of Translational and Molecular Psychiatry and Unit of Treatment-Resistant Psychosis, Department of Neuroscience, Reproductive Sciences and Dentistry, University Medical School of Naples "Federico II", Naples, Italy 13 Institute of Developmental Genetics, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany 14 BASTA-Bündnis für psychisch erkrankte Menschen, Munich, Germany 15 Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland 16 University of Edinburgh and UK DRI, Edinburgh, UK 17 Neuropsychiatry and Laboratory of Molecular Psychiatry, Charité - Universitätsmedizin Berlin and DZNE, Berlin, Germany Spyridon Siafis Roles: Conceptualization, Funding Acquisition, Methodology, Project Administration, Supervision, Writing – Original Draft Preparation Nobuyuki Nomura Roles: Writing – Review & Editing Johannes Schneider-Thoma Roles: Methodology Irene Bighelli Roles: Methodology Alexandra Bannach-Brown Roles: Methodology, Writing – Review & Editing Fiona J. Ramage Roles: Methodology, Writing – Review & Editing Francesca Tinsdeall Roles: Methodology, Writing – Review & Editing Ioannis Mantas Roles: Methodology, Writing – Review & Editing Sameer Jauhar Roles: Methodology, Writing – Review & Editing Sridhar Natesan Roles: Methodology, Writing – Review & Editing Anthony C. Vernon Roles: Methodology, Writing – Review & Editing Andrea de Bartolomeis Roles: Methodology, Writing – Review & Editing Sabine M. Hölter Roles: Methodology, Writing – Review & Editing Natascha I. Drude Roles: Methodology, Writing – Review & Editing Ulf Tölch Roles: Methodology Wulf-Peter Hansen Roles: Methodology, Writing – Review & Editing Virginia Chiocchia Roles: Methodology, Writing – Review & Editing Oliver D. Howes Roles: Methodology Josef Priller Roles: Methodology Malcolm R. Macleod Roles: Methodology, Writing – Review & Editing Georgia Salanti Roles: Methodology, Writing – Review & Editing Stefan Leucht Roles: Conceptualization, Funding Acquisition, Methodology, Project Administration, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing OPEN PEER REVIEW DETAILS REVIEWER STATUS This article is included in the Cell & Molecular Biology gateway. Abstract Background Muscarinic receptor agonism and positive allosteric modulation is a promising mechanism of action for treating psychosis, not present in most D2R-blocking antipsychotics. Xanomeline, an M1/M4-preferring agonist, has shown efficacy in late-stage clinical trials, with more compounds being investigated. Therefore, we aim to synthesize evidence on the preclinical efficacy of muscarinic receptor agonists and positive allosteric modulators in animal models of psychosis to provide unique insights and evidence-based information to guide drug development. Methods We plan a systematic review and meta-analysis of in vivo animal studies comparing muscarinic receptor agonists or positive allosteric modulators with control conditions and existing D2R-blocking antipsychotics in animals subjected to any method that induces behavioural changes of relevance for psychosis. We will identify eligible studies by searching multiple electronic databases. At least two independent reviewers will conduct the study selection and data extraction using prespecified forms and assess the risk of bias with the SYRCLE’s tool. Our primary outcomes include locomotor activity and prepulse inhibition measured with standardized mean differences. We will examine other behavioural readouts of relevance for psychosis as secondary outcomes, such as social interaction and cognitive function. We will synthesize the data using multi-level meta-analysis with a predefined random-effects structure, considering the non-independence of the data. In meta-regressions we will explore potential sources of heterogeneity from a predefined list of characteristics of the animal population, model, and intervention. We will assess the confidence in the evidence considering a self-developed instrument thatconsiders the internal and external validity of the evidence. Protocol registration PROSPERO-ID: CRD42024520914 READ ALL READ LESS Keywords antipsychotic; schizophrenia; psychosis; muscarinic receptor; acetylcholine; meta-analysis Corresponding Author(s) Spyridon Siafis ( [email protected] ) Close Corresponding author: Spyridon Siafis Competing interests: Spyridon Siafis: None. Nobuyuki Nomura: N.N. has received manuscript fees from Sumitomo Pharma. Johannes Schneider-Thoma: None. Irene Bighelli: None. Alexandra Bannach-Brown: None. Fiona J. Ramage: None. Francesca Tinsdeall: None. Ioannis Mantas: None. Sameer Jauhar: SJ has received honoraria for educational talks given for Boehringer Ingelheim, Lundbeck, Janssen, and Sunovion, and has advised on antipsychotics to LB Pharmaceuticals. Sridhar Natesan: None. Anthony Vernon: ACV has received research support from UCB S.A and Bit.Bio (https://www.bit.bio/) and has received honoraria for seminars at GlaxoSmithKline. Andrea de Bartolomeis: AdB has received research support from Janssen, Lundbeck, and Otsuka and lecture fees for educational meeting from Chiesi, Lundbeck, Roche, Sunovion, Vitria, Recordati, Angelini and Takeda; he has served on advisory boards for Eli Lilly, Jansen, Lundbeck, Otsuka, Roche, and Takeda, Chiesi, Recordati, Angelini, Vitria. Sabine M. Hölter: None. Natascha I. Drude: None. Ulf Tölch: None. Wulf-Peter Hansen: None. Virginia Chiocchia: None. Oliver Howes: ODH has received investigator-initiated research funding from and/or participated in advisory/speaker meetings organised by Angellini, Autifony, Biogen, Boehringer-Ingelheim, Eli Lilly, Elysium, Heptares, Global Medical Education, Invicro, Jansenn, Karuna, Lundbeck, Merck, Neurocrine, Ontrack/ Pangea, Otsuka, Sunovion, Recordati, Roche, Rovi and Viatris/ Mylan. He was previously a part-time employee of Lundbeck A/v. Dr Howes has a patent for the use of dopaminergic imaging. Josef Priller: None. Georgia Salanti: None. Malcolm R. Macleod: None. Stefan Leucht: SL has received received honoraria for advising/consulting and/or for lectures and/or for educational material from Angelini, Boehringer Ingelheim, Eisai, Ekademia, GedeonRichter, Janssen, Karuna, Kynexis, Lundbeck, Medichem, Medscape, Mitsubishi, Otsuka, NovoNordisk, Recordati, Rovi, Teva. Grant information: Federal Ministry of Education and Research 01KC2312 The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Copyright: © 2025 Siafis S et al . This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. How to cite: Siafis S, Nomura N, Schneider-Thoma J et al. Muscarinic receptor agonists and positive allosteric modulators in animal models of psychosis: protocol for a systematic review and meta-analysis [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 13 :1017 ( https://doi.org/10.12688/f1000research.155356.2 ) First published: 06 Sep 2024, 13 :1017 ( https://doi.org/10.12688/f1000research.155356.1 ) Latest published: 02 Jan 2025, 13 :1017 ( https://doi.org/10.12688/f1000research.155356.2 ) Revised Amendments from Version 1 To address the reviewers' comments, we more clearly mentioned that muscarinic receptor positive allosteric modulators will also be examined alongside agonists (e.g., mentioned in the title and throughout the manuscript), provided additional details about the methodology (e.g., clarifications about the comparison groups, and details about the exploration of heterogeneity especially in terms of the pharmacological and physiochemical properties of the drugs) and limitations (e.g., not examining cholinergic adverse events), and revised the search strategy to include terms for allosteric modulation (and updated the extended data accordingly). To address the reviewers' comments, we more clearly mentioned that muscarinic receptor positive allosteric modulators will also be examined alongside agonists (e.g., mentioned in the title and throughout the manuscript), provided additional details about the methodology (e.g., clarifications about the comparison groups, and details about the exploration of heterogeneity especially in terms of the pharmacological and physiochemical properties of the drugs) and limitations (e.g., not examining cholinergic adverse events), and revised the search strategy to include terms for allosteric modulation (and updated the extended data accordingly). See the authors' detailed response to the review by Daniel Foster See the authors' detailed response to the review by William Messer READ REVIEWER RESPONSES Introduction Antipsychotic drugs that block the dopamine D2 receptor (D2R) have been the cornerstone of pharmacological treatment for schizophrenia for over 70 years. 1 – 3 These drugs have demonstrated efficacy in reducing symptoms of psychosis, particularly positive symptoms such as hallucinations and delusions, 1 yet approximately one-third of patients exhibit an inadequate response to these treatments. 4 This mechanism of action targets a downstream pathway of the aetiopathophysiology of psychosis, with limited efficacy on other core domains, such as negative symptoms like blunted affect and social withdrawal, as well as cognitive impairment. 5 Moreover, the risk-to-benefit ratio of antipsychotics is often challenged by their multiple side-effects associated with their receptor-binding profiles and frequently linked to off-target actions beyond D2R blockade. 1 , 2 Therefore, there has been a recognized need for more efficacious and tolerable medications for treating psychosis, but previous attempts to develop non-dopaminergic drugs have long been unsuccessful. 3 , 6 Muscarinic acetylcholine receptor agonism and positive allosteric modulation has recently been recognized as promising mechanism of action in the treatment of psychosis that can target components of the pathophysiology underlying schizophrenia, a property not present in most D2R-blocking antipsychotics. 7 – 9 Xanomeline, a muscarinic M1/M4-preferring receptor agonist, has demonstrated improvements in symptoms of schizophrenia in early and late-stage randomized placebo-controlled controlled trials with medium-to-large effect sizes, with potential cholinergic adverse events mitigated by its combination with trospium, a peripheral muscarinic antagonist. 10 – 13 In September 2024, the U.S. Food and Drug Administration approved xanomeline combined with trospium for schizophrenia, marking it as the first antipsychotic targeting muscarinic receptors. 14 Emraclidine, a drug with a different mode of action, acting as a selective M4 positive allosteric modulator (PAM), has also shown promising findings in an early clinical trial, 15 and additional muscarinic agents (e.g., NBI-1117568) 16 are under development. Several unanswered questions remain however, including the comparative efficacy of different muscarinic receptor agonists, their comparison with existing D2R-blocking antipsychotics, the roles of individual muscarinic receptor subtypes (M1-M5) and their effects on specific symptom domains, and the potential differences between orthosteric agonists and PAMs. For example, PAMs modulate receptor activity by binding to a site distinct from the natural ligand, offering theoretical advantages such as increased selectivity and safety over orthosteric agonists. 17 , 18 In this context, preclinical studies can provide early insights and inform further drug development. Their large number and limitations in terms of internal and external validity, however, make the translation of their findings challenging. For this reason, a critical synthesis of their evidence is required, but none exists. Objectives We therefore plan a systematic review and meta-analysis on the effects of muscarinic receptor agonists and PAMs in animal models of relevance for psychosis concerning behavioural and motor outcomes as compared to control conditions and existing D2R-blocking antipsychotics. We will also carefully assess the potential biases of these studies and evaluate the confidence in the evidence, ultimately providing evidence-based information to facilitate future drug development in schizophrenia. Protocol The protocol of the review is reported according to the PRISMA statement for protocols (PRISMA-P) 19 (see the checklist in the extended data ), the guidelines from SYRCLE 20 , 21 and CAMARADES. 22 The protocol was registered with PROSPERO (ID: CRD42024520914 ) on 04.04.2024. The methodology of the protocol has been informed by our previous systematic review and meta-analysis conducted with the GALENOS project, 23 which examined trace-amine associated receptor 1 (TAAR1) agonists in animal models of psychosis. 24 , 25 Study eligibility criteria and outcomes Study design We will include in vivo animal experimental studies examining any muscarinic receptor agonist or PAM versus inactive or active comparison groups in animal models of relevance for psychosis, as detailed below. There will be no restrictions on the inclusion criteria in terms of the randomization, blinding or other factors related to risk of bias, unit of allocation, duration of the study, publication status, year, country and language. We will exclude uncontrolled preclinical experiments, observational studies, and literature reviews. Animal population and model induction We will include animals that have undergone laboratory methods to induce psychosis-like behaviours and features. There are numerous models fitting this description, each with varying degrees of validity and unique strengths and weaknesses, but none are considered the gold standard. 26 – 33 Therefore, we will include the “classical” pharmacological models of psychosis and their behavioural readouts (see “Outcomes”), which have been widely utilized in drug discovery and possess some predictive validity, especially for positive symptoms, including the administration of psychostimulants (e.g., amphetamine, cocaine) or N-methyl-D-aspartate (NMDA) receptor antagonists (e.g., phencyclidine, ketamine, MK-801). 32 , 34 , 35 Other methods of induction will also be eligible and can include other pharmacological models, neurodevelopmental methods, lesion methods, genetic models, and combinations of different methods. 27 – 33 Such relatively broad inclusion criteria were utilized in our previous systematic review, 24 , 25 and any decision on the eligibility of the psychosis models will be made in consultation with experts in preclinical research (MRM, AB, FJ, FT, IM, SN, AdB, SH, NID, UT). There will be no restriction on species, strain, age, and sex. Regarding genetic composition, we will include both wildtype animals and those that have undergone genetic interventions, if these interventions belong to eligible methods of induction (see above). Moreover, in the eligible studies, we will extract data from “naïve” animal cohorts (i.e., animals that have not undergone models of psychosis), and animal cohorts that have undergone both models of psychosis and muscarinic receptor antagonism via genetic (i.e, genetically modified animals with knockout of all or specific muscarinic receptors, either globally or in specific neuron populations) 36 or pharmacological manipulation (e.g., co-administration of selective or non-selective muscarinic receptor antagonists like scopolamine) 37 (see further details in “Comparison groups”). The eligible animal cohorts can be found in Table 1 . Table 1. Eligible animal cohorts and planned comparisons. Animal cohort Interventions received by the animal cohort Planned comparisons with the following comparison groups Model for psychosis Muscarinic receptor agonists or PAMs D2R-blocking antipsychotics Vehicle only or no treatment Muscarinic receptor antagonism Muscarinic receptor agonists or PAMs Yes Yes No No No Inactive and active control conditions Combination of muscarinic receptor agonists or PAMs and D2R-blocking antipsychotics Yes Yes Yes No No Active control conditions Inactive control condition Yes No No Yes No Not applicable (comparison group only) Active control condition Yes No Yes No No Inactive control conditions (it will be used to inform the assessment of indirectness) Muscarinic receptor agonists or PAMS in the context of muscarinic antagonism Yes Yes No No Yes Inactive control conditions with or without muscarinic receptor antagonism Sham procedures No No No Yes No Not applicable (it will be used for the calculation of normalized mean differences) We will exclude animals that have undergone induction methods for other specific conditions (e.g., transgenic models of Alzheimer’s disease, 38 the valproic acid-induced model of relevance for autism 39 and methods aiming to specifically model depressive-like behaviours, such as animal models of physical, social, or chronic mild stress). 40 We will also exclude in vitro , ex vivo , in silico studies and studies in humans. We will however consider extracting data from ex vivo measurements (e.g., Fos expression, autoradiography) following eligible in vivo experiments, potentially analysed in secondary publications (see “Outcomes”). Interventions We will include any pharmacological agent acting as an agonist or positive allosteric modulator at any of the five subtypes of muscarinic acetylcholine M1-M5 receptors. There will be no restrictions on their receptor selectivity, pharmacological potency and efficacy (e.g., full or partial agonists), dose, timing of administration relative to the induction method, pharmacokinetic properties, or route of administration, provided the method is suitable for achieving effects in the central nervous system. These pharmacological agents can be administered individually or in combination with D2R-blocking antipsychotics or other medications, and combinations can be considered as distinct interventions. We will also consider data on the effects of muscarinic receptor agonists in the context of muscarinic receptor antagonism (see “Animal population and model induction”) to evaluate whether the effects depend on the activation of muscarinic receptors or other mechanisms ( Table 1 ). We will exclude clozapine, an existing antipsychotic acting on multiple neurotransmitter receptor systems and also as muscarinic receptor partial agonist, 2 , 8 which will be considered as a control intervention (see “Comparison groups”). Clozapine’s metabolite N-desmethylclozapine however, which has low affinity for dopamine receptors and acts as a muscarinic M1/M4 receptor agonist, 41 will be considered among the experimental interventions. Additionally, we will exclude pharmacological agents with different mechanisms of action (e.g., nicotinic acetylcholine receptor agonists, acetylcholinesterase inhibitors) and non-pharmacological interventions, including genetic interventions for muscarinic receptor overexpression. Comparison groups We will include the following comparison groups: i) inactive control conditions, consisting of animals undergoing models of a method to induce psychosis-like behaviour and features and receiving vehicle (e.g., injection of saline) or no treatment, and ii) active control conditions, consisting of the aforementioned animal cohorts treated with D2R-blocking antipsychotics. D2R-blocking antipsychotics will be defined as those medications listed in the Anatomical Therapeutic Chemical (ATC) classification with a code of N05A, except for lithium (N05AN01, a mood stabilizer primarily used for the treatment of bipolar disorder), pimavanserin (N05AX17, a 5-HT2A antagonist indicated for Parkinson’s disease psychosis but not schizophrenia), and any muscarinic receptor agonists approved by any regulatory body for schizophrenia (which will be considered as experimental interventions in this review, e.g., xanomeline combined with trospium 14 ), with no further restrictions. Table 1 outlines the planned comparisons, which include evaluating muscarinic receptor agonists or PAMs, alone or combined with D2R-blocking antipsychotics, against active and inactive control conditions in animal models of psychosis. Additionally, we will examine the comparison between active and inactive control conditions to provide insights into the consistency of the effects of D2R-blocking antipsychotic in the included experiments and to inform the assessment of indirectness (see “Assessment of indirectness of the animal experiments”). We will also compare muscarinic receptor agonists or PAMs with inactive control conditions in contexts of genetic or pharmacological muscarinic receptor antagonism (as described in “Animal population and model induction”) to determine if any observed differences result from muscarinic receptor activation. Separate analyses may be conducted for the antagonism of specific muscarinic receptor subtypes and/or within specific neuronal populations, if sufficient data are available. We will also consider data in the eligible studies from sham procedures, consisting of “naïve” animal cohorts not subjected to methods of inducing psychosis-like behaviours or features and receiving either vehicle or no treatment, to calculate normalized mean differences in a sensitivity analysis (see “Effect sizes”). Outcome measures There is no gold standard measure of preclinical antipsychotic efficacy due to the limited homology with the clinical symptoms of psychosis and the lack of an established biomarker. 6 , 28 , 29 , 32 – 35 , 42 – 44 Therefore, we aim to provide a comprehensive assessment of the effects of muscarinic receptor agonists by using data from a broad range of behavioral measures in various animal models of relevance for psychosis (see “Animal population and model induction”). This approach will facilitate the identification of strong clinical canditates. 27 , 28 , 33 – 35 We will examine as co-primary outcomes the effects on i) locomotor activity and ii) prepulse inhibition of the acoustic startle reflex, as these have been widely used with some predictive validity to identify antipsychotic effects in animal models of relevance for psychosis (see “Animal population and model induction”). 24 , 29 , 34 Furthermore, we will examine additional behavioral measures as secondary outcomes, including potential proxies for positive symptoms (e.g., stereotypies, hallucinatory-like percepts), 45 negative symptoms (e.g., lack of social interaction, operant-based motivational tasks), 34 , 46 depressive- (e.g., forced swim, tail suspension, sucrose preference tasks) 34 , 46 and anxiety-like behaviors (e.g., elevated plus maze), and cognitive function (e.g., tests recommended by the CNTRICS initiative). 33 , 42 , 44 The eligibility and any potential grouping of the behavioral measures will be evaluated in collaboration with experts in preclinical research prior to commencing data analysis, and any decisions will be documented. We will exclude non-behavioural outcomes, such as histopathological and neurobiological measures due to the lack of an established biomarker, 6 and adverse events due to the inconsistent and scarce reporting in animal studies, as identified in our previous review. 24 Nonetheless, we will aim to extract their data, if available, and potentially analyse them in secondary publications. Study identification We will conduct searches in PubMed, MEDLINE via Ovid, Web of Science, EMBASE, PsychINFO, from database inception using keywords for psychosis, muscarinic agents, and animal filters, 47 similar to a previous review. 24 , 25 For muscarinic agents, we will use broad terms like muscarinic agonists or allosteric modulators and the names/synonyms of specific relevant agents identified from IUPHAR/BPS 48 and previous reviews. 7 , 49 There will be no restrictions such as on language or publication date. The search strategies will be developed in collaboration with information specialist (see “Acknowledgment”). A draft search strategy in MEDLINE via Ovid can be found in the extended data , and the final search strategies will be reported according to the PRISMA statement for reporting literature searches (PRISMA-S). 50 We plan additional searches to improve the coverage of the study identification and identify potentially unpublished studies: 1) We will aim to search in the Systematic Online Living Evidence Summaries for preclinical psychosis research ( psychosis-SOLES ), 51 which is a dedicated and continuously updated database utilizing machine learning and text mining algorithms. 2) We will search preclinical animal study registries (i.e., animalstudyregistry.org , https://preclinicaltrials.eu/ ), although pre-registration of animal studies has not been widely adopted. 3) We will aim to search preprint registries (i.e., medRxiv, bioRxiv), Google patents, specific journals of neuropsychopharmacology. 4) We will inspect reference lists of included studies, previous reviews, 7 , 8 , 49 , 52 and conference proceedings published within the last 20 years. 5) We will contact the first/corresponding author of included studies and pharmaceutical industries of muscarinic agents for additional studies and/or missing data in their studies. We will send emails with two follow-up reminders in case of no response. Study selection At least two independent reviewers will screen in the Systematic Review Facility (SyRF) 26 the de-duplicated records identified in the searches in two phases: i) title and abstract, and ii) full-text screening. Any discrepancy between the two reviewers will be resolved through discussion with a more senior reviewer. If not resolved by discussion, the full-text of the study will be acquired (if at the title/abstract level) or additional information from the original study authors will be obtained (if at the full-text level). At the title/abstract screening, records will be excluded according to the following hierarchy: i) review articles, ii) not referring to in vivo animal study, iii) not referring to muscarinic receptors or agents acting on them. At the full-text screening, records will be excluded from the review and/or meta-analysis according to the following hierarchy against the eligibility criteria: i) ineligible study design, ii) ineligible animals/population, iii) ineligible intervention, iv) ineligible comparison groups, v) ineligible outcome measure, vi) inadequate reporting of outcome data. If possible, we will consider the studies excluded in terms of their reported outcomes in the assessment of reporting bias (see “Data synthesis”). The study selection process and the reasons for exclusions at the full-text level will be reported in a flow diagram. 53 Data extraction At least two independent reviewers will conduct the data extraction in SyRF 26 using pre-specified data extraction forms that will be adapted from a previous systematic review. 24 Discrepancies between the two reviewers will be reconciled by a more senior reviewer, or if not possible, by contacting study authors for additional information. We will extract data regarding study identification (e.g., author names, title, publication year), study design (e.g., risk of bias, reporting completeness), animal population and model induction (e.g., age, sex, species strain, body weight, characteristics of the induction method), experimental and control interventions (e.g., type, dose and timing of the administration of drugs), and outcome measures (e.g., exact name of the behavioural task, methods of measurement, quantitative data). We will seek information from various sources in the following order of priority: i) text and tables, ii) figures using WebPlotDigitizer version 4 (a free and opensource tool distributed under GNU Affero General Public License Version 3 ), 54 iii) contacting authors for missing information, and iv) employing imputation methods. We will extract quantitative data for the outcomes anticipated to be reported as continuous measures. Endpoint and change scores will both be eligible and jointly synthesized. 55 When both are reported, we will prefer endpoint scores because they do not require baseline assessments and are expected to be the most frequently reported in the eligible animal experiments. We will extract the unit of measurement, mean, standard deviation and the number of participants that these correspond to. We will apply a minus transformation whenever appropriate to harmonize the direction of effects across the extracted data (e.g., a higher score indicating a better outcome). Missing standard deviations will be derived by the following methods according to their order of priority: i) calculation from standard error, ii) estimation from test statistics (e.g., p-values, t-tests, median and ranges), iii) contacting the authors of the original studies for additional information, iv) imputed from the standard deviations of other studies (although this method has not been validated in animal studies that often have small sample sizes). 56 , 57 If the exact number of animals is not reported, 58 we will estimate it with available information (e.g., using the lower boundary of a range, if reported) or consider imputation methods. If dichotomous measures are reported, we will extract the number of animals with the event and the total number of animals analysed. We will exclude studies with imputed data in a sensitivity analysis (see “Sensitivity analysis”). For crossover trials, we will prefer data from the first phase to avoid carryover effects, but we will also use data from the entire phase by applying appropriate corrections considering the within-subject correlation. 59 These studies will be excluded in a sensitivity analysis (see “Sensitivity analysis”). We will use data from any reported time point, but preference will be given for the longest time point following multiple administrations of the intervention over an extended period. If outcomes are measured multiple times after a single administration, we will consider calculating the area under the curve. 25 , 60 If multiple variations of the same outcome are reported, we will extract and jointly analyse them (see “Data synthesis”). Assessment of risk of bias and reporting completeness Two independent reviewers will assess risk of bias using the SYRCLE’s tool considering domains for selection, performance, detection, attrition, reporting and other biases. 61 We will assign an overall high risk of bias to a study if at least one domain in the SYRCLE’s tool is assessed as having a high risk of bias. Since high-quality reporting is essential for assessing the risk of bias, two independent reviewers will also evaluate the completeness of reporting using a modified version of the ARRIVE Essential 10 checklist. 25 , 62 This is necessary because the reporting completeness of animal studies is often poor, frequently leading to unclear assessments of risk of bias. Any discrepancies between the two reviewers will be resolved through discussion with a more senior reviewer or by contacting the study authors for additional information. Assessment of indirectness of animal experiments We expect that the findings from various animal models of relevance for psychosis will have different degrees of applicability to clinical trial settings. However, there is no established method for assessing their indirectness in the context of a systematic review. Moreover, there is limited synthesized evidence on the validity of animal models of relevance for psychosis, and we expect substantial variability in the methods of modelling and measuring psychosis-like behaviours in animals. 28 , 29 This makes it challenging to set predefined criteria for assessing the indirectness of animal experiments in the context of psychosis. Nevertheless, we will aim to use the extracted data to provide an experiment-level judgment of indirectness as “low risk”, “high risk”, or “some concerns”, considering how closely the experiment reflects the clinical trial setting in terms of animal population, model induction, intervention, and outcome. This assessment will inform the evaluation of indirectness domain in the confidence in the evidence (see “Confidence in the evidence”). To achieve this, we will evaluate the validity in animal experiments and the applicability of the intervention (e.g., treatment over an extended period, initiation of treatment after model induction) based on previous frameworks and checklists. 24 , 63 – 67 Specifically, we will apply the framework of Belzung and Lemoine 67 to assess the following domains (and sub-domains) of validity in animal experiments, i.e., homological (species strain), pathogenic (ontopathogenic, triggering), mechanistic, face (ethological, biomarker) and predictive (induction, remission). This framework can offer a more refined and systematic approach compared to the traditional domains of construct, face and predictive validity, which have often been inconsistently applied in the literature. 28 , 67 , 68 However, the exact methods will be determined a posteriori in consultation with experts in preclinical research. Data synthesis Planned comparisons Our main aim is to synthesize data for each outcome and for the comparisons described in Table-1. Meta-analysis will be conducted when there are at least two independent effect sizes for the same outcome, as in our previous systematic review. 24 We will examine the data and if there is reasonable consistency across the comparisons, we will consider network meta-analysis to examining the comparative effects of the different muscarinic receptor agonists, various D2R-blocking antipsychotics, and inactive control conditions. 69 Effect sizes The main effect size will be the standardized mean difference (SMD) due to the varying measures and units of the behavioural outcome measures across the studies. We will also use normalized mean difference (NMD) in a sensitivity analysis. 58 , 70 If outcomes are reported as dichotomous, we will calculate odds ratios (ORs) and convert them into SMDs using the Hasselblad and Hedges method 71 to enable their combination with results of continuous measures. In addition to the estimation of the average treatment effects, we also aim to conduct a meta-analysis of variation to estimate the inter-individual variability of the effects using the variability ratio (VR) or the coefficient of the variation ratio (CVR) in case a mean-variance relationship is expected. 70 , 72 This analysis will be conducted for the comparison of muscarinic receptor agonists to inactive control conditions. Data synthesis approach We will opt for synthesizing the data using multilevel meta-analytic models, which enable handling non-independent data. 70 We will use a predefined multilevel random-effects structure with nested levels, from higher to lower, for animal strain, study, and experiment, provided there are at least five distinct categories for at least one of the levels, as in our previous systematic review. 24 For non-independent sampling errors, we will estimate the within-study variance-covariance (VCV) matrix using any reported correlation in the original studies or assuming a correlation of 0.5 (see other assumed correlations in “Sensitivity analysis”). 70 The restricted maximum likelihood (REML) method will be used to estimate the between-study variance (τ 2 ) and between-study VCV. 70 , 73 We will adjust the confidence intervals using t- or F-distributions with degrees of freedom appropriate for the multilevel model. 74 To our knowledge, network meta-analysis has not been widely applied to the synthesis of animal experiments, and we anticipate several challenging issues, including the limited evidence for or against inconsistency, small sample sizes, and non-independent effect sizes. 65 We will examine whether the assumptions of a network meta-analysis can be fulfilled by comparing the distribution of potential effect modifiers across treatment comparisons and measuring incoherence using statistical tests. 75 Justifying these assumptions with preclinical data however, might be challenging. If a network meta-analysis is deemed feasible, we will extend the multilevel models and consider covariate-adjusted analysis (see “Exploration of heterogeneity”). The exact methodology will be defined a posteriori , and, if a network meta-analysis is justified, will be thoroughly reported in an amendment of the protocol before conducting it. We will present the effect sizes with their 95% confidence intervals and prediction intervals. Exploration of heterogeneity We will quantify heterogeneity using the variance of the random effects with its components, and the 95% prediction intervals. We will explore potential sources of heterogeneity for each outcome through meta-regression or subgroup analyses, if sufficient data are available, considering the following tentative list of potential effect-modifiers: age, sex, species/strain, comorbidities, characteristics of the model of induction of psychosis-like behaviours (e.g., pharmacological or genetic, severity), type of muscarinic receptor agonists or PAMs, their pharmacological and physiochemical properties, and dose (details below), route of administration, duration of treatment, timing of the intervention (e.g., before or after model induction), co-treatments, characteristics of the study (e.g., publication year, reporting completeness, and risk of bias), and outcome measurements (e.g., different measures for locomotor activity). Additional variables will be considered if they are deemed relevant and there are sufficient data. We will examine the pharmacological properties of muscarinic receptor agonists, considering mode of action (e.g., orthosteric agonism, positive allosteric modulation) and other key characteristics as sources of heterogeneity, using data primarily from established databases (e.g., IUPHAR/BPS) 48 and original publications that characterize these compounds. Specifically, we will assess potency (half-maximal effective concentration, EC50) and efficacy (maximal response, distinguishing between full and partial agonism) for orthosteric agonists, and modulation of acetylcholine potency and efficacy (cooperative factors α and β), intrinsic efficacy (τ B ), and affinity for the allosteric site (K B ) for PAMs. 17 , 76 These properties will be examined across various muscarinic receptor subtypes, with a preference for human receptors while considering potential cross-species differences, and across downstream signaling pathways (e.g., via Gα s , Gα q , Gα i/o subunits, β-arrestin). Given the variability across assays and experimental settings, we will consider calculating a common standardized index, if possible, such as estimating differences in log((maximal response)/EC50) between the examined drugs and the natural ligand acetylcholine. 76 This approach may enable comparisons across compounds, receptor and signaling pathway selectivity, but summarizing the different properties into a single index may result in information loss, necessitating additional analyses. Moreover, the exact procedure cannot be predetermined due to anticipated heterogeneity in the data across the different compounds examined. Additionally, we will assess off-target actions by evaluating the mode of action and affinity of each compound toward other neurotransmitter receptors. We will use the Central Nervous System Multiparameter Optimization Desirability algorithm 77 , 78 to examine the physicochemical properties of the drugs as source of heterogeneity. This algorithm calculates a composite desirability score based on six key properties, i.e., lipophilicity, distribution coefficient, molecular weight, topological polar surface area, number of hydrogen bond donors, and the most basic center, which aligns well with the pharmacokinetic attributes, blood-brain barrier permeability and safety. 77 , 78 Values for these properties will be estimated based on the chemical structure information using OPEn structure–activity/property Relationship App (OPERA) version 2.9.1 (a freely available, open-source provided distributed under MIT license). 79 We will also aim to standardize doses across drugs to examine dose-effects relationships using the standardized dose as a covariate in a meta-regression. However, any potential standardization method cannot be predefined due to the pharmacological differences among various drugs 24 and differences across species/strains. 80 Sensitivity analysis The robustness of the findings for each outcome will be examined through sensitivity analysis by: i) excluding studies with an overall high risk of bias (see “Assessment of risk of bias and reporting completeness”), ii) using normalized mean difference (see “Effect Sizes”), iii) excluding studies with imputed data (e.g., standard deviations, number of animals) and crossover studies reporting data from the entire period, iv) excluding interventions examined in single studies due to potentially inflated effect estimates, 65 v) assuming correlations of 0.2 and 0.8 in estimating the within-study VCV, 70 and vi) using a robust variance estimation to obtain cluster-robust standard errors. 70 , 81 Reporting bias and small-study effects Publication and other non-reporting biases are highly prevalent in preclinical research, potentially having a substantial impact on the estimated efficacy. 82 , 83 We will aim to evaluate potential within- and across-study non-reporting biases by adapting the framework for assessing the risk of bias due to missing evidence (ROB-ME) in clinical trials, assigning ratings of “low risk”, “high risk”, or “some concerns”. 84 – 86 We will include both published and unpublished studies, although the latter may be difficult to find due to the limited adoption of pre-registration protocols. We will evaluate potential reasons of non-reporting of outcome data in studies excluded due to ineligible outcome measures or inadequate reporting of outcome data, although this may be more challenging due to the poor reporting quality of animal studies (see “Assessment of risk of bias and reporting completeness”). Moreover, we will explore small-study effects for each outcome using contour-enhanced funnel plots and multilevel regression-based tests, 70 using the square root of the sample size, when there are sufficient data from at least 10 studies. Confidence in the evidence We will evaluate the confidence in the evidence for each of outcome using a modified version of the GRADE framework 63 , 64 taking into account the domains of risk of bias (and reporting completeness), indirectness, heterogeneity, imprecision, and reporting bias, similar to our previous systematic review. 24 Ultimately, we will aim to draw an overall conclusion on the preclinical efficacy of muscarinic receptor agonists by considering the evidence from the different behavioural domains. Statistical software Data analysis will be conducted in R statistical software 87 using the package metafor , 74 along with other appropriate packages for data cleaning, specific meta-analytic models, and visualization. We will report the complete list of packages used along with their versions in the publication of the results. Dissemination of information We plan to publish the systematic review and meta-analysis as open access in peer-reviewed journals, potentially resulting in multiple publications, and present the findings at conferences. Lay language summaries will be prepared and disseminated with the help of patient and relative groups, such as BASTA (Bündnis für psychisch erkrankte Menschen) and ApK (Aktionsgemeinschaft der Angehörigen psychisch Kranker e.V.). We will also make the methods, data, and code publicly available in a GitHub repository. Study status As of the date of the first submission of this protocol on 18.08.2024, we have completed the preliminary searches and piloting of study selection process and started, but not completed, the full searches and the full screening of search results against the eligibility criteria. We have not yet started the data extraction, risk of bias and quality assessment, or data synthesis. There were no changes from the original PROSPERO registration of the protocol, except for expanding the methods with additional details (also in response to the reviewer’s comments), 88 , 89 revising the search strategy to include terms for allosteric modulation as suggested by a reviewer, 88 adding physicochemical properties of the compounds in the “Exploration of Heterogeneity” per another reviewer’s comment, 89 and deciding not to search Scopus and CINAHL after consulting with the information specialist (which is not expected to affect the coverage of our search). Any additional deviations or modifications will be reported along with the findings and in updates to the PROSPERO registration. Discussion The planned systematic review and meta-analysis aims to evaluate the preclinical efficacy of muscarinic receptor agonists or positive allosteric modulators in animal models of relevance for psychosis. This will be achieved through a comprehensive search, advanced data synthesis methods, and a critical evaluation of potential risks of bias and confidence in the evidence. The systematic review has the potential to provide unique insights into important unanswered questions regarding muscarinic receptor agonism in the treatment of psychosis. It may also identify promising muscarinic agents or specific mechanisms of action, which could guide future drug development for schizophrenia. Furthermore, conducting a systematic review to examine the preclinical efficacy of antipsychotics is a relatively novel approach. Only a few such reviews currently exist, 24 , 29 , 90 making this work particularly valuable. Therefore, our review has the potential to highlight the limitations of existing animal models of relevance for psychosis and address potential translational disconnects to improve the design of future preclinical research. 6 , 28 , 34 We focused on muscarinic receptor agonism due to its potential to target the underlying pathophysiology of schizophrenia and the promising findings for agonists or PAMs of M1/M4 muscarinic receptors, 7 – 9 with xanomeline combined with trospium approved by the Food and Drug Administration in September 2024. 14 Muscarinic receptor agonism has also the most advanced data compared to other novel mechanisms of action being investigated in the treatment of psychosis. 9 For example, there were encouraging results from a phase II trial for ulotaront, a dual TAAR1 agonist and 5-HT 1A partial agonist. 91 A recent synthesis of evidence from early- and late-stage clinical trials, and animal studies however, suggested that TAAR1 agonists may be less efficacious compared to existing D2R-blocking antipsychotics, but additional data are required to draw more definitive conclusions and more drugs are under development. 24 We anticipate limitations and challenges in conducting the review. There is no gold standard animal model for psychosis, 6 , 28 , 34 and cross-species differences in the muscarinic receptor system and the effects of their agonists or PAMs may exist. 8 Therefore, we will include all relevant animal models and behavioural readouts of preclinical efficacy, critically evaluating the confidence in the evidence to provide a comprehensive synthesis with potential translational relevance. We will not analyse neurobiological measures due to their heterogeneous use across studies and the lack of an established biomarker in schizophrenia, 6 but they could further elucidate the mechanisms of muscarinic receptor agonism and its role in regulating dopaminergic signalling and other underlying pathophysiological mechanisms. 8 , 52 Similarly, we will not examine cholinergic adverse events in animals, such as salivation, lacrimation and diarrhea, which may offer insights into the risk-benefit profile but could be mitigated in clinical settings with peripheral muscarinic receptor antagonists, as shown with the xanomeline-trospium combination. 10 – 13 We will aim to extract and potentially analyse these measures in secondary publications. Additionally, we will explore whether heterogeneity in behavioral effects may be explained by differences in drug interactions with muscarinic receptors. Given the limited availability and application of in vivo readouts for muscarinic agonism, we will use in vitro data. We will not conduct a systematic review of in vitro assays and pharmacokinetic studies to synthesize information about the pharmacological properties of the drugs, but instead will consider reliable sources and using standardized methods to assess these as sources of heterogeneity (see “Exploration of heterogeneity”). Finally, the methods for systematic reviews of animal studies in psychiatry are not well established and may present unique challenges. 92 Our interdisciplinary team, which includes methodologists, statisticians, and clinical and preclinical researchers, will address any potential issues to ensure a robust synthesis of preclinical evidence. In conclusion, our planned systematic review and meta-analysis will be the first to examine the preclinical efficacy of muscarinic receptor agonists or positive allosteric modulators for schizophrenia, with the potential to provide evidence-based information to guide future preclinical and clinical research on this topic. Ethics and consent Not applicable. Authors contributions Spyridon Siafis: Conceptualization, Methodology, Writing – Original Draft, Supervision, Project administration, Funding acquisition. Nobuyuki Nomura: Writing – Review & Editing. Johannes Schneider-Thoma: Methodology. Irene Bighelli: Methodology. Alexandra Bannach-Brown: Methodology, Writing – Review & Editing. Fiona J. Ramage: Methodology, Writing – Review & Editing. Francesca Tinsdeall: Methodology, Writing – Review & Editing. Ioannis Mantas: Methodology, Writing – Review & Editing. Sameer Jauhar: Methodology, Writing – Review & Editing. Sridhar Natesan: Methodology, Writing – Review & Editing. Anthony C. Vernon: Methodology, Writing – Review & Editing. Andrea de Bartolomeis: Methodology, Writing – Review & Editing. Sabine M. Hölter: Methodology, Writing – Review & Editing. Natascha I. Drude: Methodology, Writing – Review & Editing. Ulf Tölch: Methodology. Wulf-Peter Hansen: Methodology, Writing – Review & Editing. Virginia Chiocchia: Methodology, Writing – Review & Editing. Oliver Howes: Methodology. Josef Priller: Methodology. Georgia Salanti: Methodology, Writing – Review & Editing. Malcolm R. Macleod: Methodology, Writing – Review & Editing. Stefan Leucht: Conceptualization, Writing – Original Draft, Writing – Review & Editing, Supervision, Project administration, Funding acquisition Data availability Underlying data No data associated with this article. Extended data Zenodo: Protocol for meta-analysis on muscarinic receptor agonists in animal models of psychosis (ANIMUS-SR), https://doi.org/10.5281/zenodo.14534308 . 93 This project contains the following extended data: - Draft search strategy in MEDLINE via Ovid.pdf - PRISMA-P checklist.pdf Reporting guidelines Zenodo: PRISMA-P checklist for “Protocol for meta-analysis on muscarinic receptor agonists in animal models of psychosis (ANIMUS-SR)”, https://doi.org/10.5281/zenodo.14534308 . 93 Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0). Acknowledgments We would like to thank Dr Farhad Shokraneh (Systematic Review Consultants LTD, Oxford, UK) for the collaboration in designing, revising and testing the search strategies, and in writing the search methods. References 1. Huhn M, Nikolakopoulou A, Schneider-Thoma J, et al. : Comparative efficacy and tolerability of 32 oral antipsychotics for the acute treatment of adults with multi-episode schizophrenia: a systematic review and network meta-analysis. Lancet. 2019 Sep 14; 394 (10202): 939–951. PubMed Abstract | Publisher Full Text | Free Full Text 2. Kaar SJ, Natesan S, McCutcheon R, et al. : Antipsychotics: Mechanisms underlying clinical response and side-effects and novel treatment approaches based on pathophysiology. Neuropharmacology. 2020 Aug 1; 172 : 107704. Epub 2019/07/13. eng. PubMed Abstract | Publisher Full Text 3. Girgis RR, Zoghbi AW, Javitt DC, et al. : The past and future of novel, non-dopamine-2 receptor therapeutics for schizophrenia: A critical and comprehensive review. J. Psychiatr. Res. 2019 Jan; 108 : 57–83. PubMed Abstract | Publisher Full Text 4. Kane JM, Agid O, Baldwin ML, et al. : Clinical Guidance on the Identification and Management of Treatment-Resistant Schizophrenia. J. Clin. Psychiatry. 2019 Mar 5; 80 (2). Epub 2019/03/07. eng. PubMed Abstract | Publisher Full Text 5. McCutcheon RA, Reis Marques T, Howes OD: Schizophrenia-An Overview. JAMA Psychiatry. 2020 Feb 1; 77 (2): 201–210. PubMed Abstract | Publisher Full Text 6. Spark DL, Fornito A, Langmead CJ, et al. : Beyond antipsychotics: a twenty-first century update for preclinical development of schizophrenia therapeutics. Transl. Psychiatry. 2022; 12 (1): 147. PubMed Abstract | Publisher Full Text | Free Full Text 7. Paul SM, Yohn SE, Popiolek M, et al. : Muscarinic Acetylcholine Receptor Agonists as Novel Treatments for Schizophrenia. Am. J. Psychiatry. 2022 Sep; 179 (9): 611–627. PubMed Abstract | Publisher Full Text 8. McCutcheon RA, Weber LAE, Nour MM, et al. : Psychosis as a disorder of muscarinic signalling: psychopathology and pharmacology. Lancet Psychiatry. 2024; 11 : 554–565. PubMed Abstract | Publisher Full Text 9. Howes OD, Dawkins E, Lobo MC, et al. : New drug treatments for schizophrenia: a review of approaches to target circuit dysfunction. Biol. Psychiatry. 2024. PubMed Abstract | Publisher Full Text 10. Brannan SK, Sawchak S, Miller AC, et al. : Muscarinic cholinergic receptor agonist and peripheral antagonist for schizophrenia. N. Engl. J. Med. 2021; 384 (8): 717–726. PubMed Abstract | Publisher Full Text | Free Full Text 11. Kaul I, Sawchak S, Correll CU, et al. : Efficacy and safety of the muscarinic receptor agonist KarXT (xanomeline-trospium) in schizophrenia (EMERGENT-2) in the USA: results from a randomised, double-blind, placebo-controlled, flexible-dose phase 3 trial. Lancet. 2024 Jan 13; 403 (10422): 160–170. PubMed Abstract | Publisher Full Text 12. Kaul I, Sawchak S, Walling DP, et al. : Efficacy and Safety of Xanomeline-Trospium Chloride in Schizophrenia: A Randomized Clinical Trial. JAMA Psychiatry. 2024 May 1; 81 : 749–756. PubMed Abstract | Publisher Full Text | Free Full Text 13. Shekhar A, Potter WZ, Lightfoot J, et al. : Selective muscarinic receptor agonist xanomeline as a novel treatment approach for schizophrenia. Am. J. Psychiatry. 2008 Aug; 165 (8): 1033–1039. PubMed Abstract | Publisher Full Text 14. U.S. Food and Drug Administration. FDA Approves Drug with New Mechanism of Action for Treatment of Schizophrenia. 2024 [2024.10.25]. Reference Source 15. Krystal J, Kane J, Correll C, et al. : CVL-231 as a Novel Positive Allosteric Modulator of Cholinergic M4 Receptors for the Treatment of Schizophrenia: Results From an Early Proof-Of-Concept Study in Patients With Schizophrenia. Neuropharmacology. 2021 2021; 46 : 338. Epub SUPPL 1. 16. NCT05545111: Efficacy, Safety, Tolerability, and Pharmacokinetics of NBI-1117568 in Adults With Schizophrenia.2022. 17. Kenakin T: Know your molecule: pharmacological characterization of drug candidates to enhance efficacy and reduce late-stage attrition. Nat. Rev. Drug Discov. 2024; 23 : 626–644. Publisher Full Text 18. Foster DJ, Conn PJ: Allosteric Modulation of GPCRs: New Insights and Potential Utility for Treatment of Schizophrenia and Other CNS Disorders.Neuron.2017 May 3; 94 (3): 431–446. PubMed Abstract | Publisher Full Text | Free Full Text 19. Moher D, Shamseer L, Clarke M, et al. : Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Syst. Rev. 2015; 4 (1): 1–9. PubMed Abstract | Publisher Full Text | Free Full Text 20. Hooijmans C, Wever KE, de Vries RBM : SYRCLEs starting guide for systematic reviews of preclinical animal interventions studies, 2016.2016. Reference Source 21. de Vries RBM , Hooijmans CR, Langendam MW, et al. : A protocol format for the preparation, registration and publication of systematic reviews of animal intervention studies. Evid. Based Preclin. Med. 2015 2015/08/01; 2 (1): 1–9. Publisher Full Text 22. CAMARADES Berlin: Preclinical Systematic Reviews & Meta-Analysis Wiki.2022. 23. Cipriani A, Seedat S, Milligan L, et al. : New living evidence resource of human and non-human studies for early intervention and research prioritisation in anxiety, depression and psychosis. BMJ Ment Health. 2023 Jun; 26 (1): e300759. Epub 2023/06/09. eng. PubMed Abstract | Publisher Full Text | Free Full Text 24. Siafis S, Chiocchia V, Macleod MR, et al. : Trace amine-associated receptor 1 (TAAR1) agonism for psychosis: a living systematic review and meta-analysis of human and non-human data. Wellcome Open Res. 2024; 9 : 182. PubMed Abstract | Publisher Full Text | Free Full Text 25. Siafis S, McCutcheon R, Chiocchia V, et al. : Trace amine-associated receptor 1 (TAAR1) agonists for psychosis: protocol for a living systematic review and meta-analysis of human and non-human studies. Wellcome Open Res. 2023; 8 : 365. PubMed Abstract | Publisher Full Text | Free Full Text 26. Bahor Z, Liao J, Currie G, et al. : Development and uptake of an online systematic review platform: the early years of the CAMARADES systematic review facility (SyRF). BMJ Open Sci. 2021; 5 (1): e100103. PubMed Abstract | Publisher Full Text 27. Sotiropoulos MG, Poulogiannopoulou E, Delis F, et al. : Innovative screening models for the discovery of new schizophrenia drug therapies: an integrated approach. Expert Opin. Drug Discov. 2021 Jul; 16 (7): 791–806. PubMed Abstract | Publisher Full Text 28. Jones CA, Watson DJG, Fone KCF: Animal models of schizophrenia. Br. J. Pharmacol. 2011; 164 (4): 1162–1194. PubMed Abstract | Publisher Full Text | Free Full Text 29. Bahor Z: Improving our understanding of the in vivo modelling of psychotic disorders: a systematic review and meta-analysis.2018. 30. Steeds H, Carhart-Harris RL, Stone JM: Drug models of schizophrenia. Ther. Adv. Psychopharmacol. 2015 Feb; 5 (1): 43–58. PubMed Abstract | Publisher Full Text | Free Full Text 31. Gobira PH, Ropke J, Aguiar DC, et al. : Animal models for predicting the efficacy and side effects of antipsychotic drugs. Braz. J. Psychiatry. 2013; 35 : S132–S139. PubMed Abstract | Publisher Full Text 32. Spark DL, Fornito A, Langmead CJ, et al. : Beyond antipsychotics: a twenty-first century update for preclinical development of schizophrenia therapeutics. Transl. Psychiatry. 2022 Apr 7; 12 (1): 147. the Turner Institute for Brain and Mental Health, Monash University. The authors have no conflict of interest to disclose. Epub 2022/04/09. eng. PubMed Abstract | Publisher Full Text | Free Full Text 33. Arguello PA, Gogos JA: Modeling madness in mice: one piece at a time. Neuron. 2006; 52 (1): 179–196. PubMed Abstract | Publisher Full Text 34. Pratt J, Winchester C, Dawson N, et al. : Advancing schizophrenia drug discovery: optimizing rodent models to bridge the translational gap. Nat. Rev. Drug Discov. 2012; 11 (7): 560–579. PubMed Abstract | Publisher Full Text 35. Pratt JA, Morris B, Dawson N: Deconstructing Schizophrenia: Advances in Preclinical Models for Biomarker Identification. Curr. Top. Behav. Neurosci. 2018; 40 : 295–323. PubMed Abstract | Publisher Full Text 36. Thomsen M, Sørensen G, Dencker D: Physiological roles of CNS muscarinic receptors gained from knockout mice.Neuropharmacology.2018 Jul 1; 136 (Pt C): 411–420. PubMed Abstract | Publisher Full Text | Free Full Text 37. Klinkenberg I, Blokland A: The validity of scopolamine as a pharmacological model for cognitive impairment: a review of animal behavioral studies. Neurosci. Biobehav. Rev. 2010 Jul; 34 (8): 1307–1350. PubMed Abstract | Publisher Full Text 38. Elder GA, Gama Sosa MA, De Gasperi R: Transgenic mouse models of Alzheimer’s disease. Mt. Sinai J. Med. 2010 Jan-Feb; 77 (1): 69–81. eng. PubMed Abstract | Publisher Full Text | Free Full Text 39. Nicolini C, Fahnestock M: The valproic acid-induced rodent model of autism. Exp. Neurol. 2018 Jan; 299 (Pt A): 217–227. PubMed Abstract | Publisher Full Text 40. Bannach-Brown A: Understanding in vivo modelling of depression.2019. 41. Natesan S, Reckless GE, Barlow KB, et al. : Evaluation of N-desmethylclozapine as a potential antipsychotic--preclinical studies. Neuropsychopharmacology. 2007 Jul; 32 (7): 1540–1549. PubMed Abstract | Publisher Full Text 42. Young JW, Geyer MA: Developing treatments for cognitive deficits in schizophrenia: the challenge of translation. J. Psychopharmacol. 2015 Feb; 29 (2): 178–196. PubMed Abstract | Publisher Full Text | Free Full Text 43. Ang MJ, Lee S, Kim JC, et al. : Behavioral Tasks Evaluating Schizophrenia-like Symptoms in Animal Models: A Recent Update. Curr. Neuropharmacol. 2021; 19 (5): 641–664. PubMed Abstract | Publisher Full Text | Free Full Text 44. Carter CS, Barch DM: Cognitive neuroscience-based approaches to measuring and improving treatment effects on cognition in schizophrenia: the CNTRICS initiative. Schizophr. Bull. 2007 Sep; 33 (5): 1131–1137. PubMed Abstract | Publisher Full Text | Free Full Text 45. Schmack K, Bosc M, Ott T, et al. : Striatal dopamine mediates hallucination-like perception in mice. Science. 2021; 372 (6537): eabf4740. PubMed Abstract | Publisher Full Text 46. Barnes SA, Der-Avakian A, Markou A: Anhedonia, avolition, and anticipatory deficits: assessments in animals with relevance to the negative symptoms of schizophrenia. Eur. Neuropsychopharmacol. 2014 May; 24 (5): 744–758. PubMed Abstract | Publisher Full Text | Free Full Text 47. van der Mierden S , Hooijmans CR, Tillema AH, et al. : Laboratory animals search filter for different literature databases: PubMed, Embase, Web of Science and PsycINFO. Lab. Anim. 2022 Jun; 56 (3): 279–286. PubMed Abstract | Publisher Full Text | Free Full Text 48. Harding SD, Armstrong JF, Faccenda E, et al. : The IUPHAR/BPS guide to PHARMACOLOGY in 2022: curating pharmacology for COVID-19, malaria and antibacterials. Nucleic Acids Res. 2022 Jan 7; 50 (D1): D1282–D1294. PubMed Abstract | Publisher Full Text | Free Full Text 49. Moran SP, Maksymetz J, Conn PJ: Targeting Muscarinic Acetylcholine Receptors for the Treatment of Psychiatric and Neurological Disorders. Trends Pharmacol. Sci. 2019 Dec; 40 (12): 1006–1020. PubMed Abstract | Publisher Full Text | Free Full Text 50. Rethlefsen ML, Kirtley S, Waffenschmidt S, et al. : PRISMA-S: an extension to the PRISMA Statement for Reporting Literature Searches in Systematic Reviews. Syst. Rev. 2021 2021/01/26; 10 (1): 39. PubMed Abstract | Publisher Full Text | Free Full Text 51. Smith S, Ramage F, Tinsdeall F, et al. : Psychosis-SOLES.2024 [March 04 2024]. March 4, 2024. Reference Source 52. Yohn SE, Weiden PJ, Felder CC, et al. : Muscarinic acetylcholine receptors for psychotic disorders: bench-side to clinic. Trends Pharmacol. Sci. 2022 Dec; 43 (12): 1098–1112. PubMed Abstract | Publisher Full Text 53. Page MJ, McKenzie JE, Bossuyt PM, et al. : The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021; 372 : n71. Publisher Full Text 54. Rohatgi A: WebPlotDigitizer version 4.6.2022. Reference Source 55. Ostinelli EG, Efthimiou O, Luo Y, et al. : Combining endpoint and change data did not affect the summary standardised mean difference in pairwise and network meta-analyses: An empirical study in depression. Res. Synth. Methods. 2024 May 9. Epub 20240509. eng. PubMed Abstract | Publisher Full Text 56. Furukawa TA, Barbui C, Cipriani A, et al. : Imputing missing standard deviations in meta-analyses can provide accurate results. J. Clin. Epidemiol. 2006 Jan; 59 (1): 7–10. PubMed Abstract | Publisher Full Text 57. Higgins JPT, Thomas J, Chandler J, et al. : Cochrane handbook for systematic reviews of interventions. John Wiley & Sons; 2019. Publisher Full Text 58. Vesterinen HM, Sena ES, Egan KJ, et al. : Meta-analysis of data from animal studies: A practical guide. J. Neurosci. Methods. 2014 2014/01/15/; 221 : 92–102. Publisher Full Text 59. Elbourne DR, Altman DG, Higgins JP, et al. : Meta-analyses involving cross-over trials: methodological issues. Int. J. Epidemiol. 2002 Feb; 31 (1): 140–149. PubMed Abstract | Publisher Full Text 60. Chiou WL: Critical evaluation of the potential error in pharmacokinetic studies of using the linear trapezoidal rule method for the calculation of the area under the plasma level--time curve. J. Pharmacokinet. Biopharm. 1978 Dec; 6 (6): 539–546. PubMed Abstract | Publisher Full Text 61. Hooijmans CR, Rovers MM, de Vries RBM , et al. : SYRCLE’s risk of bias tool for animal studies. BMC Med. Res. Methodol. 2014 2014/03/26; 14 (1): 43. PubMed Abstract | Publisher Full Text | Free Full Text 62. Percie du Sert N, Ahluwalia A, Alam S, et al. : Reporting animal research: Explanation and elaboration for the ARRIVE guidelines 2.0. PLoS Biol. 2020; 18 (7): e3000411. PubMed Abstract | Publisher Full Text | Free Full Text 63. Hooijmans CR, de Vries RBM , Ritskes-Hoitinga M, et al. : Facilitating healthcare decisions by assessing the certainty in the evidence from preclinical animal studies. PLoS One. 2018; 13 (1): e0187271. Epub 2018/01/13. eng. PubMed Abstract | Publisher Full Text | Free Full Text 64. Schünemann H, Brożek J, Guyatt G, et al. : The GRADE handbook. UK: Cochrane Collaboration London; 2013. 65. Lalu MM, Fergusson DA, Cheng W, et al. : Identifying stroke therapeutics from preclinical models: A protocol for a novel application of network meta-analysis. F1000Res. 2019; 8 : 11. Epub 2019/03/25. eng. PubMed Abstract | Publisher Full Text | Free Full Text 66. Henderson VC, Kimmelman J, Fergusson D, et al. : Threats to validity in the design and conduct of preclinical efficacy studies: a systematic review of guidelines for in vivo animal experiments. PLoS Med. 2013; 10 (7): e1001489. other authors have declared that no competing interests exist. Epub 2013/08/13. eng. PubMed Abstract | Publisher Full Text | Free Full Text 67. Belzung C, Lemoine M: Criteria of validity for animal models of psychiatric disorders: focus on anxiety disorders and depression. Biol. Mood Anxiety Disord. 2011 Nov 7; 1 (1): 9. Epub 2011/01/01. eng. PubMed Abstract | Publisher Full Text | Free Full Text 68. Willner P: The validity of animal models of depression. Psychopharmacology. 1984; 83 (1): 1–16. eng. PubMed Abstract | Publisher Full Text 69. Salanti G, Higgins JP, Ades AE, et al. : Evaluation of networks of randomized trials. Stat. Methods Med. Res. 2008 Jun; 17 (3): 279–301. PubMed Abstract | Publisher Full Text 70. Yang Y, Macleod M, Pan J, et al. : Advanced methods and implementations for the meta-analyses of animal models: Current practices and future recommendations. Neurosci. Biobehav. Rev. 2023 2023/03/01/; 146 : 105016. PubMed Abstract | Publisher Full Text 71. da Costa BR , Rutjes AW, Johnston BC, et al. : Methods to convert continuous outcomes into odds ratios of treatment response and numbers needed to treat: meta-epidemiological study. Int. J. Epidemiol. 2012; 41 (5): 1445–1459. PubMed Abstract | Publisher Full Text 72. Usui T, Macleod MR, McCann SK, et al. : Meta-analysis of variation suggests that embracing variability improves both replicability and generalizability in preclinical research. PLoS Biol. 2021; 19 (5): e3001009. PubMed Abstract | Publisher Full Text | Free Full Text 73. Jackson D, Riley R, White IR: Multivariate meta-analysis: potential and promise. Stat. Med. 2011; 30 (20): 2481–2498. PubMed Abstract | Publisher Full Text | Free Full Text 74. Viechtbauer W: Conducting meta-analyses in R with the metafor package. J. Stat. Softw. 2010; 36 (3): 1–48. Publisher Full Text 75. Efthimiou O, Debray TP, van Valkenhoef G , et al. : GetReal in network meta-analysis: a review of the methodology. Res. Synth. Methods. 2016 Sep; 7 (3): 236–263. PubMed Abstract | Publisher Full Text 76. Kenakin T: A Scale of Agonism and Allosteric Modulation for Assessment of Selectivity, Bias, and Receptor Mutation. Mol. Pharmacol. 2017 Oct; 92 (4): 414–424. PubMed Abstract | Publisher Full Text 77. Wager TT, Hou X, Verhoest PR, et al. : Moving beyond rules: the development of a central nervous system multiparameter optimization (CNS MPO) approach to enable alignment of druglike properties.ACS Chem. Neurosci.2010 Jun 16; 1 (6): 435–449. PubMed Abstract | Publisher Full Text | Free Full Text 78. Wager TT, Hou X, Verhoest PR, et al. : Central Nervous System Multiparameter Optimization Desirability: Application in Drug Discovery.ACS Chem. Neurosci.2016 Jun 15; 7 (6): 767–775. PubMed Abstract | Publisher Full Text 79. Mansouri K, Grulke CM, Judson RS, et al. : OPERA models for predicting physicochemical properties and environmental fate endpoints.J. Cheminf.2018 2018/03/08; 10 (1): 10. Publisher Full Text 80. Reagan-Shaw S, Nihal M, Ahmad N: Dose translation from animal to human studies revisited. FASEB J. 2008 Mar; 22 (3): 659–661. PubMed Abstract | Publisher Full Text 81. Pustejovsky JE, Tipton E: Meta-analysis with Robust Variance Estimation: Expanding the Range of Working Models. Prev. Sci. 2022 2022/04/01; 23 (3): 425–438. PubMed Abstract | Publisher Full Text 82. Sena ES, van der Worp HB , Bath PMW, et al. : Publication Bias in Reports of Animal Stroke Studies Leads to Major Overstatement of Efficacy. PLoS Biol. 2010; 8 (3): e1000344. PubMed Abstract | Publisher Full Text | Free Full Text 83. ter Riet G , Korevaar DA, Leenaars M, et al. : Publication bias in laboratory animal research: a survey on magnitude, drivers, consequences and potential solutions.2012. 84. Chiocchia V, Holloway A, Salanti G: Semi-automated assessment of the risk of bias due to missing evidence in network meta-analysis: a guidance paper for the ROB-MEN web-application. BMC Med. Res. Methodol. 2023 2023/10/07; 23 (1): 223. PubMed Abstract | Publisher Full Text | Free Full Text 85. Chiocchia V, Nikolakopoulou A, Higgins JPT, et al. : ROB-MEN: a tool to assess risk of bias due to missing evidence in network meta-analysis. BMC Med. 2021 2021/11/23; 19 (1): 304. PubMed Abstract | Publisher Full Text | Free Full Text 86. Page MJ, Sterne JAC, Boutron I, et al. : ROB-ME: a tool for assessing risk of bias due to missing evidence in systematic reviews with meta-analysis. BMJ. 2023; 383 . Publisher Full Text 87. R Core Team: R: A language and environment for statistical computing.2013. 88. Foster D: Peer Review Report For: Muscarinic receptor agonists in animal models of psychosis: protocol for a systematic review and meta-analysis [version 1; peer review: 2 approved with reservations]. F1000Research. 2024; 13 : 1017. 89. Messer W: Peer Review Report For: Muscarinic receptor agonists in animal models of psychosis: protocol for a systematic review and meta-analysis [version 1; peer review: 2 approved with reservations]. F1000Research. 2024; 13 : 1017. 90. Hazani R, Lavidor M, Weller A: Treatments for social interaction impairment in animal models of schizophrenia: a critical review and meta-analysis. Schizophr. Bull. 2022; 48 (6): 1179–1193. PubMed Abstract | Publisher Full Text | Free Full Text 91. Koblan KS, Kent J, Hopkins SC, et al. : A Non-D2-Receptor-Binding Drug for the Treatment of Schizophrenia. N. Engl. J. Med. 2020 Apr 16; 382 (16): 1497–1506. PubMed Abstract | Publisher Full Text 92. Hair K, Wilson E, Wong C, et al. : Systematic online living evidence summaries: emerging tools to accelerate evidence synthesis. Clin. Sci. (Lond.). 2023 May 31; 137 (10): 773–784. PubMed Abstract | Publisher Full Text | Free Full Text 93. Siafis S: Protocol for meta-analysis on muscarinic receptor agonists in animal models of psychosis (ANIMUS-SR). Zenodo. 2024. Publisher Full Text Comments on this article Comments (0) Version 2 VERSION 2 PUBLISHED 06 Sep 2024 ADD YOUR COMMENT Comment Author details Author details 1 German Center for Mental Health (DZPG), partner site München/Augsburg, Munich, Germany 2 Technical University of Munich, School of Medicine and Health, Department of Psychiatry and Psychotherapy, Munich, Germany 3 Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan 4 QUEST Center for Responsible Research, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany 5 Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK 6 Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden 7 Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London, UK 8 Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Hammersmith Hospital, Imperial College London, London, UK 9 Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London, UK 10 MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK 11 Department of Basic and Clinical Neuroscience, School of Neuroscience, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London, UK 12 Section of Psychiatry, Laboratory of Translational and Molecular Psychiatry and Unit of Treatment-Resistant Psychosis, Department of Neuroscience, Reproductive Sciences and Dentistry, University Medical School of Naples "Federico II", Naples, Italy 13 Institute of Developmental Genetics, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany 14 BASTA-Bündnis für psychisch erkrankte Menschen, Munich, Germany 15 Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland 16 University of Edinburgh and UK DRI, Edinburgh, UK 17 Neuropsychiatry and Laboratory of Molecular Psychiatry, Charité - Universitätsmedizin Berlin and DZNE, Berlin, Germany Spyridon Siafis Roles: Conceptualization, Funding Acquisition, Methodology, Project Administration, Supervision, Writing – Original Draft Preparation Nobuyuki Nomura Roles: Writing – Review & Editing Johannes Schneider-Thoma Roles: Methodology Irene Bighelli Roles: Methodology Alexandra Bannach-Brown Roles: Methodology, Writing – Review & Editing Fiona J. Ramage Roles: Methodology, Writing – Review & Editing Francesca Tinsdeall Roles: Methodology, Writing – Review & Editing Ioannis Mantas Roles: Methodology, Writing – Review & Editing Sameer Jauhar Roles: Methodology, Writing – Review & Editing Sridhar Natesan Roles: Methodology, Writing – Review & Editing Anthony C. Vernon Roles: Methodology, Writing – Review & Editing Andrea de Bartolomeis Roles: Methodology, Writing – Review & Editing Sabine M. Hölter Roles: Methodology, Writing – Review & Editing Natascha I. Drude Roles: Methodology, Writing – Review & Editing Ulf Tölch Roles: Methodology Wulf-Peter Hansen Roles: Methodology, Writing – Review & Editing Virginia Chiocchia Roles: Methodology, Writing – Review & Editing Oliver D. Howes Roles: Methodology Josef Priller Roles: Methodology Malcolm R. Macleod Roles: Methodology, Writing – Review & Editing Georgia Salanti Roles: Methodology, Writing – Review & Editing Stefan Leucht Roles: Conceptualization, Funding Acquisition, Methodology, Project Administration, Supervision, Writing – Original Draft Preparation, Writing – Review & Editing Competing interests Spyridon Siafis: None. Nobuyuki Nomura: N.N. has received manuscript fees from Sumitomo Pharma. Johannes Schneider-Thoma: None. Irene Bighelli: None. Alexandra Bannach-Brown: None. Fiona J. Ramage: None. Francesca Tinsdeall: None. Ioannis Mantas: None. Sameer Jauhar: SJ has received honoraria for educational talks given for Boehringer Ingelheim, Lundbeck, Janssen, and Sunovion, and has advised on antipsychotics to LB Pharmaceuticals. Sridhar Natesan: None. Anthony Vernon: ACV has received research support from UCB S.A and Bit.Bio (https://www.bit.bio/) and has received honoraria for seminars at GlaxoSmithKline. Andrea de Bartolomeis: AdB has received research support from Janssen, Lundbeck, and Otsuka and lecture fees for educational meeting from Chiesi, Lundbeck, Roche, Sunovion, Vitria, Recordati, Angelini and Takeda; he has served on advisory boards for Eli Lilly, Jansen, Lundbeck, Otsuka, Roche, and Takeda, Chiesi, Recordati, Angelini, Vitria. Sabine M. Hölter: None. Natascha I. Drude: None. Ulf Tölch: None. Wulf-Peter Hansen: None. Virginia Chiocchia: None. Oliver Howes: ODH has received investigator-initiated research funding from and/or participated in advisory/speaker meetings organised by Angellini, Autifony, Biogen, Boehringer-Ingelheim, Eli Lilly, Elysium, Heptares, Global Medical Education, Invicro, Jansenn, Karuna, Lundbeck, Merck, Neurocrine, Ontrack/ Pangea, Otsuka, Sunovion, Recordati, Roche, Rovi and Viatris/ Mylan. He was previously a part-time employee of Lundbeck A/v. Dr Howes has a patent for the use of dopaminergic imaging. Josef Priller: None. Georgia Salanti: None. Malcolm R. Macleod: None. Stefan Leucht: SL has received received honoraria for advising/consulting and/or for lectures and/or for educational material from Angelini, Boehringer Ingelheim, Eisai, Ekademia, GedeonRichter, Janssen, Karuna, Kynexis, Lundbeck, Medichem, Medscape, Mitsubishi, Otsuka, NovoNordisk, Recordati, Rovi, Teva. Grant information Federal Ministry of Education and Research 01KC2312 The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Article Versions (2) version 2 Revised Published: 02 Jan 2025, 13:1017 https://doi.org/10.12688/f1000research.155356.2 version 1 Published: 06 Sep 2024, 13:1017 https://doi.org/10.12688/f1000research.155356.1 Copyright © 2025 Siafis S et al . This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Download Export To Sciwheel Bibtex EndNote ProCite Ref. Manager (RIS) Sente metrics Views Downloads F1000Research - - PubMed Central info_outline Data from PMC are received and updated monthly. - - Citations open_in_new 0 open_in_new 0 open_in_new SEE MORE DETAILS CITE how to cite this article Siafis S, Nomura N, Schneider-Thoma J et al. Muscarinic receptor agonists and positive allosteric modulators in animal models of psychosis: protocol for a systematic review and meta-analysis [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 13 :1017 ( https://doi.org/10.12688/f1000research.155356.2 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS track receive updates on this article Track an article to receive email alerts on any updates to this article. TRACK THIS ARTICLE Share Open Peer Review Current Reviewer Status: ? Key to Reviewer Statuses VIEW HIDE Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Version 2 VERSION 2 PUBLISHED 02 Jan 2025 Revised Views 0 Cite How to cite this report: Guo X. Reviewer Report For: Muscarinic receptor agonists and positive allosteric modulators in animal models of psychosis: protocol for a systematic review and meta-analysis [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 13 :1017 ( https://doi.org/10.5256/f1000research.176234.r357863 ) The direct URL for this report is: https://f1000research.com/articles/13-1017/v2#referee-response-357863 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 21 Jan 2025 Xiaonan Guo , Zhejiang University, Hangzhou, Zhejiang, China Approved VIEWS 0 https://doi.org/10.5256/f1000research.176234.r357863 This paper is a comprehensive protocol studying muscarinic receptor agonists and positive allosteric modulators in animal models of psychosis. Generally, I think it will promote the clinical use and biological insight of the muscarinic receptor agonists and positive allosteric modulators in ... Continue reading READ ALL This paper is a comprehensive protocol studying muscarinic receptor agonists and positive allosteric modulators in animal models of psychosis. Generally, I think it will promote the clinical use and biological insight of the muscarinic receptor agonists and positive allosteric modulators in treating schizophrenia. The method is so perfect that no obvious limitations can be found. I only provide the minor suggestion to improve the article, which the authors could consider. Since psychosis is strongly associated with dopamine function, it's better to introduce the influence of dopamine function when treating animal models of psychosis with muscarinic receptor agonists and positive allosteric modulators. Linking the muscarinic function with dopamine function will shed light on clinical translation of muscarinic agonist. Is the rationale for, and objectives of, the study clearly described? Yes Is the study design appropriate for the research question? Yes Are sufficient details of the methods provided to allow replication by others? Yes Are the datasets clearly presented in a useable and accessible format? Yes Competing Interests: No competing interests were disclosed. Reviewer Expertise: Brain, metabolic, and genetic mechanism in psychiatric disorders (especially in BD). I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Guo X. Reviewer Report For: Muscarinic receptor agonists and positive allosteric modulators in animal models of psychosis: protocol for a systematic review and meta-analysis [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 13 :1017 ( https://doi.org/10.5256/f1000research.176234.r357863 ) The direct URL for this report is: https://f1000research.com/articles/13-1017/v2#referee-response-357863 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Respond or Comment COMMENT ON THIS REPORT Version 1 VERSION 1 PUBLISHED 06 Sep 2024 Views 0 Cite How to cite this report: Messer W. Reviewer Report For: Muscarinic receptor agonists and positive allosteric modulators in animal models of psychosis: protocol for a systematic review and meta-analysis [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 13 :1017 ( https://doi.org/10.5256/f1000research.170522.r325671 ) The direct URL for this report is: https://f1000research.com/articles/13-1017/v1#referee-response-325671 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 24 Oct 2024 William Messer , Department of Medicinal and Biological Chemistry, College of Pharmacy and Pharmaceutical Sciences, Department of Pharmacology and Experimental Therapeutics,, University of Toledo, Toledo, OH, USA Approved with Reservations VIEWS 0 https://doi.org/10.5256/f1000research.170522.r325671 The article outlines a protocol for a specific systematic review and meta-analysis examining the impact of muscarinic agonists (and allosteric modulators) in animal models of psychosis. As such, it is more a research proposal than a paper describing results. ... Continue reading READ ALL The article outlines a protocol for a specific systematic review and meta-analysis examining the impact of muscarinic agonists (and allosteric modulators) in animal models of psychosis. As such, it is more a research proposal than a paper describing results. The authors indicate that D 2 dopamine antagonists have been the cornerstone for schizophrenia therapy for the last 70 years, although atypical antipsychotics target other receptors, including 5-HT 2 receptors. Such compounds, including clozapine and olanzapine, are linked to a different set of adverse effects than classical dopamine antagonists including hypoglycemia and weight gain. Nevertheless, the topic is timely given the recent approval of xanomeline, in combination with trospium, for the treatment of schizophrenia. A systematic review and a meta-analysis are proposed for examining the impact of muscarinic agonists and allosteric modulators in animal models of psychosis. The level of complexity is high with respect to the varying types of compounds (agonists vs. partial agonists, receptor subtype selectivity, binding affinity, etc.), which will make it difficult to accurately categorize compounds. For example, positive allosteric modulators often exhibit a range of effects that include modulation of acetylcholine potency and efficacy in addition to allosteric agonist activity. The degree to which such activities have been adequately assessed will likely vary from lab to lab and such data may not be readily available in the papers that address in vivo efficacy in animal models of psychosis. These concerns are addressed to some extent in the “Exploration of heterogeneity” section, but a more explicit discussion of how concepts of potency and efficacy, for example, will be handled is warranted. In addition to the sources of heterogeneity discussed, the physicochemical properties of compounds may impact the effectiveness of treatments; consideration of ADME properties of compounds could provide an important perspective. For example, multiparameter optimization values could help explain variability in responses for compounds with similar receptor activity profiles. Beyond the pharmacological properties of the compounds under investigation, the impact of muscarinic receptor activation might vary significantly depending on the different compounds utilized to induce behavioral changes (e.g., NMDA antagonists vs. dopamine agonists) or the behavioral readouts (e.g., pre-pulse inhibition of startle response vs. apomorphine induced climbing). The authors refer to some of the inherent difficulties in the “Assessment of indirectness of animal experiments” section, including concerns about the applicability of various animal models to clinical utility. In this sense, it might be helpful to examine the consistency of comparator compounds (e.g., D 2 and 5-HT 2 antagonists) that are used clinically in treatment of schizophrenia, and are often used as control compounds in studies of muscarinic agonists and other potential therapeutic compounds. This is perhaps alluded to in the “Data synthesis/planned comparisons” section, although additional details would be helpful. An additional consideration is the presence or absence of adverse effects for the compounds under investigation. The clinical utility of muscarinic agonists has been limited by adverse effect profiles, which vary from compound to compound, but likely include both off-target (e.g., M 3 receptor-mediated) and on-target (i.e., M 1 or M 4 receptor-mediated) effects. Adverse effects such as salivation, lacrimation, diarrhea, or convulsions would provide important information regarding the in vivo pharmacological profile of compounds and the separation between beneficial and undesirable effects (i.e., the therapeutic window). Overall, the topic is of timely interest and worth pursuing with some additional attention to the details to be evaluated. Is the rationale for, and objectives of, the study clearly described? Yes Is the study design appropriate for the research question? Yes Are sufficient details of the methods provided to allow replication by others? Partly Are the datasets clearly presented in a useable and accessible format? Not applicable Competing Interests: I am an inventor on patents related to the use of muscarinic agonists and allosteric modulators for the treatment of neuropsychiatric disorders. I am also the founder and owner of Psyneurgy Pharmaceuticals LLC, a company focused on the development of treatments for neuropsychiatric disorders. Reviewer Expertise: My research focuses on the design and development of selective agonists and allosteric modulators of muscarinic receptors with potential utility in the treatment of neuropsychiatric disorders. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Messer W. Reviewer Report For: Muscarinic receptor agonists and positive allosteric modulators in animal models of psychosis: protocol for a systematic review and meta-analysis [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 13 :1017 ( https://doi.org/10.5256/f1000research.170522.r325671 ) The direct URL for this report is: https://f1000research.com/articles/13-1017/v1#referee-response-325671 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Author Response 02 Jan 2025 Spyridon Siafis , Technical University of Munich, School of Medicine and Health, Department of Psychiatry and Psychotherapy, Munich, Germany 02 Jan 2025 Author Response #2.1: The article outlines a protocol for a specific systematic review and meta-analysis examining the impact of muscarinic agonists (and allosteric modulators) in animal models of psychosis. As such, it ... Continue reading #2.1: The article outlines a protocol for a specific systematic review and meta-analysis examining the impact of muscarinic agonists (and allosteric modulators) in animal models of psychosis. As such, it is more a research proposal than a paper describing results. Our reply: We would like to thank the reviewer for their constructive comments on our protocol, which have helped improve the clarity of the methods. This manuscript indeed corresponds to a protocol for a systematic review, and the results of the completed review will be published in a peer-reviewed journal, as outlined in the “Dissemination of information” section. Please find our point-by-point responses to the comments below. #2.2: The authors indicate that D 2 dopamine antagonists have been the cornerstone for schizophrenia therapy for the last 70 years, although atypical antipsychotics target other receptors, including 5-HT 2 receptors. Such compounds, including clozapine and olanzapine, are linked to a different set of adverse effects than classical dopamine antagonists including hypoglycemia and weight gain. Nevertheless, the topic is timely given the recent approval of xanomeline, in combination with trospium, for the treatment of schizophrenia. Our reply: We agree with this point that although the primary mechanism of action for antipsychotics has historically been the blockade of dopamine D2 receptors, these drugs also interact with other neurotransmitter receptors, with adverse events often linked to their receptor-binding profiles. Accordingly, we have revised the introduction to incorporate this information and have also noted the recent approval of xanomeline-trospium, which had not been approved at the time of the initial manuscript submission. Changes in the manuscript : We revised the introduction to mention the association of adverse events of antipsychotics with their receptor-binding profiles and off-target actions on other neurotransmitter receptors, as well as the approval of xanomeline-trospium for schizophrenia by the US FDA: “Antipsychotic drugs that block the dopamine D2 receptor (D2R) have been the cornerstone of pharmacological treatment for schizophrenia for over 70 years. 1 – 3 …..Moreover, the risk-to-benefit ratio of antipsychotics is often challenged by their multiple side-effects associated with their receptor-binding profiles and frequently linked to off-target actions beyond D2R blockade. 1 , 2 …… Xanomeline, a muscarinic M1/M4-preferring receptor agonist, has demonstrated improvements in symptoms of schizophrenia in early and late-stage randomized placebo-controlled controlled trials with medium-to-large effect sizes, with potential cholinergic adverse events mitigated by its combination with trospium, a peripheral muscarinic antagonist. 10 – 13 In September 2024, the U.S. Food and Drug Administration approved xanomeline combined with trospium for schizophrenia, marking it as the first antipsychotic targeting muscarinic receptors. (1) “ #2.3: A systematic review and a meta-analysis are proposed for examining the impact of muscarinic agonists and allosteric modulators in animal models of psychosis. The level of complexity is high with respect to the varying types of compounds (agonists vs. partial agonists, receptor subtype selectivity, binding affinity, etc.), which will make it difficult to accurately categorize compounds. For example, positive allosteric modulators often exhibit a range of effects that include modulation of acetylcholine potency and efficacy in addition to allosteric agonist activity. The degree to which such activities have been adequately assessed will likely vary from lab to lab and such data may not be readily available in the papers that address in vivo efficacy in animal models of psychosis. These concerns are addressed to some extent in the “Exploration of heterogeneity” section, but a more explicit discussion of how concepts of potency and efficacy, for example, will be handled is warranted. Our reply: We would like to thank the reviewer for this insightful comment. We have now expanded the “Exploration of heterogeneity” section to elaborate on how these pharmacological properties will be examined, taking into account different modes of action and efforts to calculate indices that minimize potential variability and heterogeneity in measuring these properties (e.g., if possible, differences in the log((maximal efficacy/EC50)).(2) We will aim to use reliable sources for obtaining information about these properties (e.g., IUPHAR/BPS database)(3); however, we will not conduct a systematic review of studies to synthesize them, and we have noted this limitation in the “Discussion” section. Changes in the manuscript : We expanded the methods in the “Exploration of heterogeneity” accordingly: We will examine the pharmacological properties of muscarinic receptor agonists, considering mode of action (e.g., orthosteric agonism, positive allosteric modulation) and other key characteristics as sources of heterogeneity, using data primarily from established databases (e.g., IUPHAR/BPS) 43 and original publications that characterize these compounds. Specifically, we will assess potency (half-maximal effective concentration, EC50) and efficacy (maximal response, distinguishing between full and partial agonism) for orthosteric agonists, and modulation of acetylcholine potency and efficacy (cooperative factors α and β), intrinsic efficacy (τ B ), and affinity for the allosteric site (K B ) for PAMs. (2,4) These properties will be examined across various muscarinic receptor subtypes, with a preference for human receptors while considering potential cross-species differences, and across downstream signaling pathways (e.g., via Gα s , Gα q , Gα i/o subunits, β -arrestin). Given the variability across assays and experimental settings, we will consider calculating a common standardized index, if possible, such as estimating differences in log((maximal response)/EC50) between the examined drugs and the natural ligand acetylcholine. (2) This approach may enable comparisons across compounds, receptor and signaling pathway selectivity, but summarizing the different properties into a single index may result in information loss, necessitating additional analyses . Moreover, the exact procedure cannot be predetermined due to anticipated heterogeneity in the data across the different compounds examined . Additionally, we will assess off-target actions by evaluating the mode of action and affinity of each compound toward other neurotransmitter receptors .” We added to the limitations that a systematic review of in vitro assays and pharmacokinetic studies will not be conducted: “… Additionally, we will explore whether heterogeneity in behavioral effects may be explained by differences in drug interactions with muscarinic receptors. Given the limited availability and application of in vivo readouts for muscarinic agonism, we will use in vitro data. We will not conduct a systematic review of in vitro assays and pharmacokinetic studies to synthesize information about the pharmacological properties of the drugs, but instead will aim to use reliable sources and standardized methods to assess these as sources of heterogeneity (see “Exploration of heterogeneity”)…” #2.4: In addition to the sources of heterogeneity discussed, the physicochemical properties of compounds may impact the effectiveness of treatments; consideration of ADME properties of compounds could provide an important perspective. For example, multiparameter optimization values could help explain variability in responses for compounds with similar receptor activity profiles. Our reply: Thank you for raising this important point. Similarly to the above, we expanded the “Exploration of heterogeneity” section to include physicochemical parameters and their integration with the Central Nervous System Multiparameter Optimization Desirability approach. (5,6) Changes in the manuscript : We expanded accordingly the “Exploration of heterogeneity” section: “… We will explore potential sources of heterogeneity for …. type of muscarinic receptor agonists or PAMs, their pharmacological and physiochemical properties, and dose (details below), … We will use the Central Nervous System Multiparameter Optimization Desirability algorithm (5,6) to examine the physicochemical properties of the drugs as source of heterogeneity. This algorithm calculates a composite desirability score based on six key properties, i.e., lipophilicity, distribution coefficient, molecular weight, topological polar surface area, number of hydrogen bond donors, and the most basic center, which aligns well with the pharmacokinetic attributes, blood-brain barrier permeability and safety . (5,6) Values for these properties will be estimated based on the chemical structure information using OPEn structure–activity/property Relationship App (OPERA) version 2.9.1 (a freely available, open-source provided distributed under MIT license ) . (7) ” #2.5: Beyond the pharmacological properties of the compounds under investigation, the impact of muscarinic receptor activation might vary significantly depending on the different compounds utilized to induce behavioral changes (e.g., NMDA antagonists vs. dopamine agonists) or the behavioral readouts (e.g., pre-pulse inhibition of startle response vs. apomorphine induced climbing). The authors refer to some of the inherent difficulties in the “Assessment of indirectness of animal experiments” section, including concerns about the applicability of various animal models to clinical utility. In this sense, it might be helpful to examine the consistency of comparator compounds (e.g., D 2 and 5-HT 2 antagonists) that are used clinically in treatment of schizophrenia, and are often used as control compounds in studies of muscarinic agonists and other potential therapeutic compounds. This is perhaps alluded to in the “Data synthesis/planned comparisons” section, although additional details would be helpful. Our reply: We agree with this point, and we have added a comparison of D2R-blocking antipsychotics with inactive control conditions (e.g., vehicle) to examine the consistency of their effects in the included experiments and to inform the “Assessment of indirectness of animal experiments”. This is now described in the “Comparison groups” Changes in the manuscript : We added this comparison in the “Comparison groups”: “Table 1 outlines the planned comparisons, …. Additionally, we will examine the comparison between active and inactive control conditions to provide insights into the consistency of the effects of D2R-blocking antipsychotic in the included experiments and to inform the assessment of indirectness (see “Assessment of indirectness of the animal experiments”).” #2.6: An additional consideration is the presence or absence of adverse effects for the compounds under investigation. The clinical utility of muscarinic agonists has been limited by adverse effect profiles, which vary from compound to compound, but likely include both off-target (e.g., M 3 receptor-mediated) and on-target (i.e., M 1 or M 4 receptor-mediated) effects. Adverse effects such as salivation, lacrimation, diarrhea, or convulsions would provide important information regarding the in vivo pharmacological profile of compounds and the separation between beneficial and undesirable effects (i.e., the therapeutic window). Our reply: Thank you for this point. We agree that examining adverse events is important for assessing the risk-to-benefit ratio of these drugs. However, we had chosen already from the start of our protocol to focus on behavioural outcomes and not include adverse events due to their sparse and inconsistent reporting in studies of animal models of psychosis (as also noted in our previous review on TAAR1 agonists)(8) and their examination in other study designs excluded from our review (e.g., using naïve animals not subjected to models of psychosis). Furthermore, cholinergic adverse events may potentially be mitigated in clinical settings through the combination of peripheral antagonists, as seen with xanomeline-trospium.(9)Nonetheless, we will aim to extract adverse event data if found in the included studies and consider secondary publications where relevant. These considerations are addressed in the “Discussion” section under limitations. Changes in the manuscript: We expanded the limitations in the “Discussion” section to include consideration of cholinergic adverse events, similar to the previously reported neurobiological measures: “We will not analyse neurobiological measures due to their heterogeneous use across studies and the lack of an established biomarker in schizophrenia, 6 .. Similarly, we will not examine cholinergic adverse events in animals, such as salivation, lacrimation and diarrhea, which may offer insights into the risk-benefit profile but could be mitigated in clinical settings with peripheral muscarinic receptor antagonists, as shown with the xanomeline-trospium combination. 10 – 13 We will aim to extract and potentially analyse these measures in secondary publications .” #2.7: Overall, the topic is of timely interest and worth pursuing with some additional attention to the details to be evaluated. Our reply: Thank you once again for your overall endorsement and for the thoughtful comments that have substantially strengthened our protocol. In addition to the above-mentioned changes, we have also updated the “Study status” to reflect the changes during the revision: “…There were no changes from the original PROSPERO registration of the protocol, except for expanding the methods with additional details (also in response to the reviewer’s comments), (10,11) revising the search strategy to include terms for allosteric modulation as suggested by a reviewer, (10) adding physicochemical properties of the compounds in the “Exploration of Heterogeneity” per another reviewer’s comment, (11) and deciding not to search Scopus and CINAHL after consulting with the information specialist (which is not expected to affect the coverage of our search)….” References 1.U.S. Food and Drug Administration. FDA Approves Drug with New Mechanism of Action for Treatment of Schizophrenia 2024 [Available from: https://www.fda.gov/news-events/press-announcements/fda-approves-drug-new-mechanism-action-treatment-schizophrenia . 2. Kenakin T. A Scale of Agonism and Allosteric Modulation for Assessment of Selectivity, Bias, and Receptor Mutation. Mol Pharmacol. 2017;92(4):414-24. 3. Harding SD, et al. The IUPHAR/BPS guide to PHARMACOLOGY in 2022: curating pharmacology for COVID-19, malaria and antibacterials. Nucleic Acids Res. 2022;50(D1):D1282-d94. 4. Kenakin T. Know your molecule: pharmacological characterization of drug candidates to enhance efficacy and reduce late-stage attrition. Nature Reviews Drug Discovery. 2024:1-19. 5. Wager TT, et al. Moving beyond rules: the development of a central nervous system multiparameter optimization (CNS MPO) approach to enable alignment of druglike properties. ACS Chem Neurosci. 2010;1(6):435-49. 6. Wager TT, et al. Central Nervous System Multiparameter Optimization Desirability: Application in Drug Discovery. ACS Chem Neurosci. 2016;7(6):767-75. 7. Mansouri K, et al. OPERA models for predicting physicochemical properties and environmental fate endpoints. Journal of Cheminformatics. 2018;10(1):10. 8. Siafis S, et al. Trace amine-associated receptor 1 (TAAR1) agonism for psychosis: a living systematic review and meta-analysis of human and non-human data. Wellcome Open Research. 2024;9. 9. Paul SM, et al. Muscarinic Acetylcholine Receptor Agonists as Novel Treatments for Schizophrenia. Am J Psychiatry. 2022;179(9):611-27. 10. Foster D. Peer Review Report For: Muscarinic receptor agonists in animal models of psychosis: protocol for a systematic review and meta-analysis [version 1; peer review: 2 approved with reservations]. F1000Research. 2024;13:1017. 11. Messer W. Peer Review Report For: Muscarinic receptor agonists in animal models of psychosis: protocol for a systematic review and meta-analysis [version 1; peer review: 2 approved with reservations]. F1000Research 2024;13:1017. #2.1: The article outlines a protocol for a specific systematic review and meta-analysis examining the impact of muscarinic agonists (and allosteric modulators) in animal models of psychosis. As such, it is more a research proposal than a paper describing results. Our reply: We would like to thank the reviewer for their constructive comments on our protocol, which have helped improve the clarity of the methods. This manuscript indeed corresponds to a protocol for a systematic review, and the results of the completed review will be published in a peer-reviewed journal, as outlined in the “Dissemination of information” section. Please find our point-by-point responses to the comments below. #2.2: The authors indicate that D 2 dopamine antagonists have been the cornerstone for schizophrenia therapy for the last 70 years, although atypical antipsychotics target other receptors, including 5-HT 2 receptors. Such compounds, including clozapine and olanzapine, are linked to a different set of adverse effects than classical dopamine antagonists including hypoglycemia and weight gain. Nevertheless, the topic is timely given the recent approval of xanomeline, in combination with trospium, for the treatment of schizophrenia. Our reply: We agree with this point that although the primary mechanism of action for antipsychotics has historically been the blockade of dopamine D2 receptors, these drugs also interact with other neurotransmitter receptors, with adverse events often linked to their receptor-binding profiles. Accordingly, we have revised the introduction to incorporate this information and have also noted the recent approval of xanomeline-trospium, which had not been approved at the time of the initial manuscript submission. Changes in the manuscript : We revised the introduction to mention the association of adverse events of antipsychotics with their receptor-binding profiles and off-target actions on other neurotransmitter receptors, as well as the approval of xanomeline-trospium for schizophrenia by the US FDA: “Antipsychotic drugs that block the dopamine D2 receptor (D2R) have been the cornerstone of pharmacological treatment for schizophrenia for over 70 years. 1 – 3 …..Moreover, the risk-to-benefit ratio of antipsychotics is often challenged by their multiple side-effects associated with their receptor-binding profiles and frequently linked to off-target actions beyond D2R blockade. 1 , 2 …… Xanomeline, a muscarinic M1/M4-preferring receptor agonist, has demonstrated improvements in symptoms of schizophrenia in early and late-stage randomized placebo-controlled controlled trials with medium-to-large effect sizes, with potential cholinergic adverse events mitigated by its combination with trospium, a peripheral muscarinic antagonist. 10 – 13 In September 2024, the U.S. Food and Drug Administration approved xanomeline combined with trospium for schizophrenia, marking it as the first antipsychotic targeting muscarinic receptors. (1) “ #2.3: A systematic review and a meta-analysis are proposed for examining the impact of muscarinic agonists and allosteric modulators in animal models of psychosis. The level of complexity is high with respect to the varying types of compounds (agonists vs. partial agonists, receptor subtype selectivity, binding affinity, etc.), which will make it difficult to accurately categorize compounds. For example, positive allosteric modulators often exhibit a range of effects that include modulation of acetylcholine potency and efficacy in addition to allosteric agonist activity. The degree to which such activities have been adequately assessed will likely vary from lab to lab and such data may not be readily available in the papers that address in vivo efficacy in animal models of psychosis. These concerns are addressed to some extent in the “Exploration of heterogeneity” section, but a more explicit discussion of how concepts of potency and efficacy, for example, will be handled is warranted. Our reply: We would like to thank the reviewer for this insightful comment. We have now expanded the “Exploration of heterogeneity” section to elaborate on how these pharmacological properties will be examined, taking into account different modes of action and efforts to calculate indices that minimize potential variability and heterogeneity in measuring these properties (e.g., if possible, differences in the log((maximal efficacy/EC50)).(2) We will aim to use reliable sources for obtaining information about these properties (e.g., IUPHAR/BPS database)(3); however, we will not conduct a systematic review of studies to synthesize them, and we have noted this limitation in the “Discussion” section. Changes in the manuscript : We expanded the methods in the “Exploration of heterogeneity” accordingly: We will examine the pharmacological properties of muscarinic receptor agonists, considering mode of action (e.g., orthosteric agonism, positive allosteric modulation) and other key characteristics as sources of heterogeneity, using data primarily from established databases (e.g., IUPHAR/BPS) 43 and original publications that characterize these compounds. Specifically, we will assess potency (half-maximal effective concentration, EC50) and efficacy (maximal response, distinguishing between full and partial agonism) for orthosteric agonists, and modulation of acetylcholine potency and efficacy (cooperative factors α and β), intrinsic efficacy (τ B ), and affinity for the allosteric site (K B ) for PAMs. (2,4) These properties will be examined across various muscarinic receptor subtypes, with a preference for human receptors while considering potential cross-species differences, and across downstream signaling pathways (e.g., via Gα s , Gα q , Gα i/o subunits, β -arrestin). Given the variability across assays and experimental settings, we will consider calculating a common standardized index, if possible, such as estimating differences in log((maximal response)/EC50) between the examined drugs and the natural ligand acetylcholine. (2) This approach may enable comparisons across compounds, receptor and signaling pathway selectivity, but summarizing the different properties into a single index may result in information loss, necessitating additional analyses . Moreover, the exact procedure cannot be predetermined due to anticipated heterogeneity in the data across the different compounds examined . Additionally, we will assess off-target actions by evaluating the mode of action and affinity of each compound toward other neurotransmitter receptors .” We added to the limitations that a systematic review of in vitro assays and pharmacokinetic studies will not be conducted: “… Additionally, we will explore whether heterogeneity in behavioral effects may be explained by differences in drug interactions with muscarinic receptors. Given the limited availability and application of in vivo readouts for muscarinic agonism, we will use in vitro data. We will not conduct a systematic review of in vitro assays and pharmacokinetic studies to synthesize information about the pharmacological properties of the drugs, but instead will aim to use reliable sources and standardized methods to assess these as sources of heterogeneity (see “Exploration of heterogeneity”)…” #2.4: In addition to the sources of heterogeneity discussed, the physicochemical properties of compounds may impact the effectiveness of treatments; consideration of ADME properties of compounds could provide an important perspective. For example, multiparameter optimization values could help explain variability in responses for compounds with similar receptor activity profiles. Our reply: Thank you for raising this important point. Similarly to the above, we expanded the “Exploration of heterogeneity” section to include physicochemical parameters and their integration with the Central Nervous System Multiparameter Optimization Desirability approach. (5,6) Changes in the manuscript : We expanded accordingly the “Exploration of heterogeneity” section: “… We will explore potential sources of heterogeneity for …. type of muscarinic receptor agonists or PAMs, their pharmacological and physiochemical properties, and dose (details below), … We will use the Central Nervous System Multiparameter Optimization Desirability algorithm (5,6) to examine the physicochemical properties of the drugs as source of heterogeneity. This algorithm calculates a composite desirability score based on six key properties, i.e., lipophilicity, distribution coefficient, molecular weight, topological polar surface area, number of hydrogen bond donors, and the most basic center, which aligns well with the pharmacokinetic attributes, blood-brain barrier permeability and safety . (5,6) Values for these properties will be estimated based on the chemical structure information using OPEn structure–activity/property Relationship App (OPERA) version 2.9.1 (a freely available, open-source provided distributed under MIT license ) . (7) ” #2.5: Beyond the pharmacological properties of the compounds under investigation, the impact of muscarinic receptor activation might vary significantly depending on the different compounds utilized to induce behavioral changes (e.g., NMDA antagonists vs. dopamine agonists) or the behavioral readouts (e.g., pre-pulse inhibition of startle response vs. apomorphine induced climbing). The authors refer to some of the inherent difficulties in the “Assessment of indirectness of animal experiments” section, including concerns about the applicability of various animal models to clinical utility. In this sense, it might be helpful to examine the consistency of comparator compounds (e.g., D 2 and 5-HT 2 antagonists) that are used clinically in treatment of schizophrenia, and are often used as control compounds in studies of muscarinic agonists and other potential therapeutic compounds. This is perhaps alluded to in the “Data synthesis/planned comparisons” section, although additional details would be helpful. Our reply: We agree with this point, and we have added a comparison of D2R-blocking antipsychotics with inactive control conditions (e.g., vehicle) to examine the consistency of their effects in the included experiments and to inform the “Assessment of indirectness of animal experiments”. This is now described in the “Comparison groups” Changes in the manuscript : We added this comparison in the “Comparison groups”: “Table 1 outlines the planned comparisons, …. Additionally, we will examine the comparison between active and inactive control conditions to provide insights into the consistency of the effects of D2R-blocking antipsychotic in the included experiments and to inform the assessment of indirectness (see “Assessment of indirectness of the animal experiments”).” #2.6: An additional consideration is the presence or absence of adverse effects for the compounds under investigation. The clinical utility of muscarinic agonists has been limited by adverse effect profiles, which vary from compound to compound, but likely include both off-target (e.g., M 3 receptor-mediated) and on-target (i.e., M 1 or M 4 receptor-mediated) effects. Adverse effects such as salivation, lacrimation, diarrhea, or convulsions would provide important information regarding the in vivo pharmacological profile of compounds and the separation between beneficial and undesirable effects (i.e., the therapeutic window). Our reply: Thank you for this point. We agree that examining adverse events is important for assessing the risk-to-benefit ratio of these drugs. However, we had chosen already from the start of our protocol to focus on behavioural outcomes and not include adverse events due to their sparse and inconsistent reporting in studies of animal models of psychosis (as also noted in our previous review on TAAR1 agonists)(8) and their examination in other study designs excluded from our review (e.g., using naïve animals not subjected to models of psychosis). Furthermore, cholinergic adverse events may potentially be mitigated in clinical settings through the combination of peripheral antagonists, as seen with xanomeline-trospium.(9)Nonetheless, we will aim to extract adverse event data if found in the included studies and consider secondary publications where relevant. These considerations are addressed in the “Discussion” section under limitations. Changes in the manuscript: We expanded the limitations in the “Discussion” section to include consideration of cholinergic adverse events, similar to the previously reported neurobiological measures: “We will not analyse neurobiological measures due to their heterogeneous use across studies and the lack of an established biomarker in schizophrenia, 6 .. Similarly, we will not examine cholinergic adverse events in animals, such as salivation, lacrimation and diarrhea, which may offer insights into the risk-benefit profile but could be mitigated in clinical settings with peripheral muscarinic receptor antagonists, as shown with the xanomeline-trospium combination. 10 – 13 We will aim to extract and potentially analyse these measures in secondary publications .” #2.7: Overall, the topic is of timely interest and worth pursuing with some additional attention to the details to be evaluated. Our reply: Thank you once again for your overall endorsement and for the thoughtful comments that have substantially strengthened our protocol. In addition to the above-mentioned changes, we have also updated the “Study status” to reflect the changes during the revision: “…There were no changes from the original PROSPERO registration of the protocol, except for expanding the methods with additional details (also in response to the reviewer’s comments), (10,11) revising the search strategy to include terms for allosteric modulation as suggested by a reviewer, (10) adding physicochemical properties of the compounds in the “Exploration of Heterogeneity” per another reviewer’s comment, (11) and deciding not to search Scopus and CINAHL after consulting with the information specialist (which is not expected to affect the coverage of our search)….” References 1.U.S. Food and Drug Administration. FDA Approves Drug with New Mechanism of Action for Treatment of Schizophrenia 2024 [Available from: https://www.fda.gov/news-events/press-announcements/fda-approves-drug-new-mechanism-action-treatment-schizophrenia . 2. Kenakin T. A Scale of Agonism and Allosteric Modulation for Assessment of Selectivity, Bias, and Receptor Mutation. Mol Pharmacol. 2017;92(4):414-24. 3. Harding SD, et al. The IUPHAR/BPS guide to PHARMACOLOGY in 2022: curating pharmacology for COVID-19, malaria and antibacterials. Nucleic Acids Res. 2022;50(D1):D1282-d94. 4. Kenakin T. Know your molecule: pharmacological characterization of drug candidates to enhance efficacy and reduce late-stage attrition. Nature Reviews Drug Discovery. 2024:1-19. 5. Wager TT, et al. Moving beyond rules: the development of a central nervous system multiparameter optimization (CNS MPO) approach to enable alignment of druglike properties. ACS Chem Neurosci. 2010;1(6):435-49. 6. Wager TT, et al. Central Nervous System Multiparameter Optimization Desirability: Application in Drug Discovery. ACS Chem Neurosci. 2016;7(6):767-75. 7. Mansouri K, et al. OPERA models for predicting physicochemical properties and environmental fate endpoints. Journal of Cheminformatics. 2018;10(1):10. 8. Siafis S, et al. Trace amine-associated receptor 1 (TAAR1) agonism for psychosis: a living systematic review and meta-analysis of human and non-human data. Wellcome Open Research. 2024;9. 9. Paul SM, et al. Muscarinic Acetylcholine Receptor Agonists as Novel Treatments for Schizophrenia. Am J Psychiatry. 2022;179(9):611-27. 10. Foster D. Peer Review Report For: Muscarinic receptor agonists in animal models of psychosis: protocol for a systematic review and meta-analysis [version 1; peer review: 2 approved with reservations]. F1000Research. 2024;13:1017. 11. Messer W. Peer Review Report For: Muscarinic receptor agonists in animal models of psychosis: protocol for a systematic review and meta-analysis [version 1; peer review: 2 approved with reservations]. F1000Research 2024;13:1017. Competing Interests: Spyridon Siafis: None. Nobuyuki Nomura: N.N. has received manuscript fees from Sumitomo Pharma. Johannes Schneider-Thoma: None. Irene Bighelli: None. Alexandra Bannach-Brown: None. Fiona J. Ramage: None. Francesca Tinsdeall: None. Ioannis Mantas: None. Sameer Jauhar: SJ has received honoraria for educational talks given for Boehringer Ingelheim, Lundbeck, Janssen, and Sunovion, and has advised on antipsychotics to LB Pharmaceuticals. Sridhar Natesan: None. Anthony Vernon: ACV has received research support from UCB S.A and Bit.Bio (https://www.bit.bio/) and has received honoraria for seminars at GlaxoSmithKline. Andrea de Bartolomeis: AdB has received research support from Janssen, Lundbeck, and Otsuka and lecture fees for educational meeting from Chiesi, Lundbeck, Roche, Sunovion, Vitria, Recordati, Angelini and Takeda; he has served on advisory boards for Eli Lilly, Jansen, Lundbeck, Otsuka, Roche, and Takeda, Chiesi, Recordati, Angelini, Vitria. Sabine M. Hölter: None. Natascha I. Drude: None. Ulf Tölch: None. Wulf-Peter Hansen: None. Virginia Chiocchia: None. Oliver Howes: ODH has received investigator-initiated research funding from and/or participated in advisory/speaker meetings organised by Angellini, Autifony, Biogen, Boehringer-Ingelheim, Eli Lilly, Elysium, Heptares, Global Medical Education, Invicro, Jansenn, Karuna, Lundbeck, Merck, Neurocrine, Ontrack/ Pangea, Otsuka, Sunovion, Recordati, Roche, Rovi and Viatris/ Mylan. He was previously a part-time employee of Lundbeck A/v. Dr Howes has a patent for the use of dopaminergic imaging. Josef Priller: None. Georgia Salanti: None. Malcolm R. Macleod: None. Stefan Leucht: SL has received received honoraria for advising/consulting and/or for lectures and/or for educational material from Angelini, Boehringer Ingelheim, Eisai, Ekademia, GedeonRichter, Janssen, Karuna, Kynexis, Lundbeck, Medichem, Medscape, Mitsubishi, Otsuka, NovoNordisk, Recordati, Rovi, Teva. Close Report a concern Respond or Comment COMMENTS ON THIS REPORT Author Response 02 Jan 2025 Spyridon Siafis , Technical University of Munich, School of Medicine and Health, Department of Psychiatry and Psychotherapy, Munich, Germany 02 Jan 2025 Author Response #2.1: The article outlines a protocol for a specific systematic review and meta-analysis examining the impact of muscarinic agonists (and allosteric modulators) in animal models of psychosis. As such, it ... Continue reading #2.1: The article outlines a protocol for a specific systematic review and meta-analysis examining the impact of muscarinic agonists (and allosteric modulators) in animal models of psychosis. As such, it is more a research proposal than a paper describing results. Our reply: We would like to thank the reviewer for their constructive comments on our protocol, which have helped improve the clarity of the methods. This manuscript indeed corresponds to a protocol for a systematic review, and the results of the completed review will be published in a peer-reviewed journal, as outlined in the “Dissemination of information” section. Please find our point-by-point responses to the comments below. #2.2: The authors indicate that D 2 dopamine antagonists have been the cornerstone for schizophrenia therapy for the last 70 years, although atypical antipsychotics target other receptors, including 5-HT 2 receptors. Such compounds, including clozapine and olanzapine, are linked to a different set of adverse effects than classical dopamine antagonists including hypoglycemia and weight gain. Nevertheless, the topic is timely given the recent approval of xanomeline, in combination with trospium, for the treatment of schizophrenia. Our reply: We agree with this point that although the primary mechanism of action for antipsychotics has historically been the blockade of dopamine D2 receptors, these drugs also interact with other neurotransmitter receptors, with adverse events often linked to their receptor-binding profiles. Accordingly, we have revised the introduction to incorporate this information and have also noted the recent approval of xanomeline-trospium, which had not been approved at the time of the initial manuscript submission. Changes in the manuscript : We revised the introduction to mention the association of adverse events of antipsychotics with their receptor-binding profiles and off-target actions on other neurotransmitter receptors, as well as the approval of xanomeline-trospium for schizophrenia by the US FDA: “Antipsychotic drugs that block the dopamine D2 receptor (D2R) have been the cornerstone of pharmacological treatment for schizophrenia for over 70 years. 1 – 3 …..Moreover, the risk-to-benefit ratio of antipsychotics is often challenged by their multiple side-effects associated with their receptor-binding profiles and frequently linked to off-target actions beyond D2R blockade. 1 , 2 …… Xanomeline, a muscarinic M1/M4-preferring receptor agonist, has demonstrated improvements in symptoms of schizophrenia in early and late-stage randomized placebo-controlled controlled trials with medium-to-large effect sizes, with potential cholinergic adverse events mitigated by its combination with trospium, a peripheral muscarinic antagonist. 10 – 13 In September 2024, the U.S. Food and Drug Administration approved xanomeline combined with trospium for schizophrenia, marking it as the first antipsychotic targeting muscarinic receptors. (1) “ #2.3: A systematic review and a meta-analysis are proposed for examining the impact of muscarinic agonists and allosteric modulators in animal models of psychosis. The level of complexity is high with respect to the varying types of compounds (agonists vs. partial agonists, receptor subtype selectivity, binding affinity, etc.), which will make it difficult to accurately categorize compounds. For example, positive allosteric modulators often exhibit a range of effects that include modulation of acetylcholine potency and efficacy in addition to allosteric agonist activity. The degree to which such activities have been adequately assessed will likely vary from lab to lab and such data may not be readily available in the papers that address in vivo efficacy in animal models of psychosis. These concerns are addressed to some extent in the “Exploration of heterogeneity” section, but a more explicit discussion of how concepts of potency and efficacy, for example, will be handled is warranted. Our reply: We would like to thank the reviewer for this insightful comment. We have now expanded the “Exploration of heterogeneity” section to elaborate on how these pharmacological properties will be examined, taking into account different modes of action and efforts to calculate indices that minimize potential variability and heterogeneity in measuring these properties (e.g., if possible, differences in the log((maximal efficacy/EC50)).(2) We will aim to use reliable sources for obtaining information about these properties (e.g., IUPHAR/BPS database)(3); however, we will not conduct a systematic review of studies to synthesize them, and we have noted this limitation in the “Discussion” section. Changes in the manuscript : We expanded the methods in the “Exploration of heterogeneity” accordingly: We will examine the pharmacological properties of muscarinic receptor agonists, considering mode of action (e.g., orthosteric agonism, positive allosteric modulation) and other key characteristics as sources of heterogeneity, using data primarily from established databases (e.g., IUPHAR/BPS) 43 and original publications that characterize these compounds. Specifically, we will assess potency (half-maximal effective concentration, EC50) and efficacy (maximal response, distinguishing between full and partial agonism) for orthosteric agonists, and modulation of acetylcholine potency and efficacy (cooperative factors α and β), intrinsic efficacy (τ B ), and affinity for the allosteric site (K B ) for PAMs. (2,4) These properties will be examined across various muscarinic receptor subtypes, with a preference for human receptors while considering potential cross-species differences, and across downstream signaling pathways (e.g., via Gα s , Gα q , Gα i/o subunits, β -arrestin). Given the variability across assays and experimental settings, we will consider calculating a common standardized index, if possible, such as estimating differences in log((maximal response)/EC50) between the examined drugs and the natural ligand acetylcholine. (2) This approach may enable comparisons across compounds, receptor and signaling pathway selectivity, but summarizing the different properties into a single index may result in information loss, necessitating additional analyses . Moreover, the exact procedure cannot be predetermined due to anticipated heterogeneity in the data across the different compounds examined . Additionally, we will assess off-target actions by evaluating the mode of action and affinity of each compound toward other neurotransmitter receptors .” We added to the limitations that a systematic review of in vitro assays and pharmacokinetic studies will not be conducted: “… Additionally, we will explore whether heterogeneity in behavioral effects may be explained by differences in drug interactions with muscarinic receptors. Given the limited availability and application of in vivo readouts for muscarinic agonism, we will use in vitro data. We will not conduct a systematic review of in vitro assays and pharmacokinetic studies to synthesize information about the pharmacological properties of the drugs, but instead will aim to use reliable sources and standardized methods to assess these as sources of heterogeneity (see “Exploration of heterogeneity”)…” #2.4: In addition to the sources of heterogeneity discussed, the physicochemical properties of compounds may impact the effectiveness of treatments; consideration of ADME properties of compounds could provide an important perspective. For example, multiparameter optimization values could help explain variability in responses for compounds with similar receptor activity profiles. Our reply: Thank you for raising this important point. Similarly to the above, we expanded the “Exploration of heterogeneity” section to include physicochemical parameters and their integration with the Central Nervous System Multiparameter Optimization Desirability approach. (5,6) Changes in the manuscript : We expanded accordingly the “Exploration of heterogeneity” section: “… We will explore potential sources of heterogeneity for …. type of muscarinic receptor agonists or PAMs, their pharmacological and physiochemical properties, and dose (details below), … We will use the Central Nervous System Multiparameter Optimization Desirability algorithm (5,6) to examine the physicochemical properties of the drugs as source of heterogeneity. This algorithm calculates a composite desirability score based on six key properties, i.e., lipophilicity, distribution coefficient, molecular weight, topological polar surface area, number of hydrogen bond donors, and the most basic center, which aligns well with the pharmacokinetic attributes, blood-brain barrier permeability and safety . (5,6) Values for these properties will be estimated based on the chemical structure information using OPEn structure–activity/property Relationship App (OPERA) version 2.9.1 (a freely available, open-source provided distributed under MIT license ) . (7) ” #2.5: Beyond the pharmacological properties of the compounds under investigation, the impact of muscarinic receptor activation might vary significantly depending on the different compounds utilized to induce behavioral changes (e.g., NMDA antagonists vs. dopamine agonists) or the behavioral readouts (e.g., pre-pulse inhibition of startle response vs. apomorphine induced climbing). The authors refer to some of the inherent difficulties in the “Assessment of indirectness of animal experiments” section, including concerns about the applicability of various animal models to clinical utility. In this sense, it might be helpful to examine the consistency of comparator compounds (e.g., D 2 and 5-HT 2 antagonists) that are used clinically in treatment of schizophrenia, and are often used as control compounds in studies of muscarinic agonists and other potential therapeutic compounds. This is perhaps alluded to in the “Data synthesis/planned comparisons” section, although additional details would be helpful. Our reply: We agree with this point, and we have added a comparison of D2R-blocking antipsychotics with inactive control conditions (e.g., vehicle) to examine the consistency of their effects in the included experiments and to inform the “Assessment of indirectness of animal experiments”. This is now described in the “Comparison groups” Changes in the manuscript : We added this comparison in the “Comparison groups”: “Table 1 outlines the planned comparisons, …. Additionally, we will examine the comparison between active and inactive control conditions to provide insights into the consistency of the effects of D2R-blocking antipsychotic in the included experiments and to inform the assessment of indirectness (see “Assessment of indirectness of the animal experiments”).” #2.6: An additional consideration is the presence or absence of adverse effects for the compounds under investigation. The clinical utility of muscarinic agonists has been limited by adverse effect profiles, which vary from compound to compound, but likely include both off-target (e.g., M 3 receptor-mediated) and on-target (i.e., M 1 or M 4 receptor-mediated) effects. Adverse effects such as salivation, lacrimation, diarrhea, or convulsions would provide important information regarding the in vivo pharmacological profile of compounds and the separation between beneficial and undesirable effects (i.e., the therapeutic window). Our reply: Thank you for this point. We agree that examining adverse events is important for assessing the risk-to-benefit ratio of these drugs. However, we had chosen already from the start of our protocol to focus on behavioural outcomes and not include adverse events due to their sparse and inconsistent reporting in studies of animal models of psychosis (as also noted in our previous review on TAAR1 agonists)(8) and their examination in other study designs excluded from our review (e.g., using naïve animals not subjected to models of psychosis). Furthermore, cholinergic adverse events may potentially be mitigated in clinical settings through the combination of peripheral antagonists, as seen with xanomeline-trospium.(9)Nonetheless, we will aim to extract adverse event data if found in the included studies and consider secondary publications where relevant. These considerations are addressed in the “Discussion” section under limitations. Changes in the manuscript: We expanded the limitations in the “Discussion” section to include consideration of cholinergic adverse events, similar to the previously reported neurobiological measures: “We will not analyse neurobiological measures due to their heterogeneous use across studies and the lack of an established biomarker in schizophrenia, 6 .. Similarly, we will not examine cholinergic adverse events in animals, such as salivation, lacrimation and diarrhea, which may offer insights into the risk-benefit profile but could be mitigated in clinical settings with peripheral muscarinic receptor antagonists, as shown with the xanomeline-trospium combination. 10 – 13 We will aim to extract and potentially analyse these measures in secondary publications .” #2.7: Overall, the topic is of timely interest and worth pursuing with some additional attention to the details to be evaluated. Our reply: Thank you once again for your overall endorsement and for the thoughtful comments that have substantially strengthened our protocol. In addition to the above-mentioned changes, we have also updated the “Study status” to reflect the changes during the revision: “…There were no changes from the original PROSPERO registration of the protocol, except for expanding the methods with additional details (also in response to the reviewer’s comments), (10,11) revising the search strategy to include terms for allosteric modulation as suggested by a reviewer, (10) adding physicochemical properties of the compounds in the “Exploration of Heterogeneity” per another reviewer’s comment, (11) and deciding not to search Scopus and CINAHL after consulting with the information specialist (which is not expected to affect the coverage of our search)….” References 1.U.S. Food and Drug Administration. FDA Approves Drug with New Mechanism of Action for Treatment of Schizophrenia 2024 [Available from: https://www.fda.gov/news-events/press-announcements/fda-approves-drug-new-mechanism-action-treatment-schizophrenia . 2. Kenakin T. A Scale of Agonism and Allosteric Modulation for Assessment of Selectivity, Bias, and Receptor Mutation. Mol Pharmacol. 2017;92(4):414-24. 3. Harding SD, et al. The IUPHAR/BPS guide to PHARMACOLOGY in 2022: curating pharmacology for COVID-19, malaria and antibacterials. Nucleic Acids Res. 2022;50(D1):D1282-d94. 4. Kenakin T. Know your molecule: pharmacological characterization of drug candidates to enhance efficacy and reduce late-stage attrition. Nature Reviews Drug Discovery. 2024:1-19. 5. Wager TT, et al. Moving beyond rules: the development of a central nervous system multiparameter optimization (CNS MPO) approach to enable alignment of druglike properties. ACS Chem Neurosci. 2010;1(6):435-49. 6. Wager TT, et al. Central Nervous System Multiparameter Optimization Desirability: Application in Drug Discovery. ACS Chem Neurosci. 2016;7(6):767-75. 7. Mansouri K, et al. OPERA models for predicting physicochemical properties and environmental fate endpoints. Journal of Cheminformatics. 2018;10(1):10. 8. Siafis S, et al. Trace amine-associated receptor 1 (TAAR1) agonism for psychosis: a living systematic review and meta-analysis of human and non-human data. Wellcome Open Research. 2024;9. 9. Paul SM, et al. Muscarinic Acetylcholine Receptor Agonists as Novel Treatments for Schizophrenia. Am J Psychiatry. 2022;179(9):611-27. 10. Foster D. Peer Review Report For: Muscarinic receptor agonists in animal models of psychosis: protocol for a systematic review and meta-analysis [version 1; peer review: 2 approved with reservations]. F1000Research. 2024;13:1017. 11. Messer W. Peer Review Report For: Muscarinic receptor agonists in animal models of psychosis: protocol for a systematic review and meta-analysis [version 1; peer review: 2 approved with reservations]. F1000Research 2024;13:1017. #2.1: The article outlines a protocol for a specific systematic review and meta-analysis examining the impact of muscarinic agonists (and allosteric modulators) in animal models of psychosis. As such, it is more a research proposal than a paper describing results. Our reply: We would like to thank the reviewer for their constructive comments on our protocol, which have helped improve the clarity of the methods. This manuscript indeed corresponds to a protocol for a systematic review, and the results of the completed review will be published in a peer-reviewed journal, as outlined in the “Dissemination of information” section. Please find our point-by-point responses to the comments below. #2.2: The authors indicate that D 2 dopamine antagonists have been the cornerstone for schizophrenia therapy for the last 70 years, although atypical antipsychotics target other receptors, including 5-HT 2 receptors. Such compounds, including clozapine and olanzapine, are linked to a different set of adverse effects than classical dopamine antagonists including hypoglycemia and weight gain. Nevertheless, the topic is timely given the recent approval of xanomeline, in combination with trospium, for the treatment of schizophrenia. Our reply: We agree with this point that although the primary mechanism of action for antipsychotics has historically been the blockade of dopamine D2 receptors, these drugs also interact with other neurotransmitter receptors, with adverse events often linked to their receptor-binding profiles. Accordingly, we have revised the introduction to incorporate this information and have also noted the recent approval of xanomeline-trospium, which had not been approved at the time of the initial manuscript submission. Changes in the manuscript : We revised the introduction to mention the association of adverse events of antipsychotics with their receptor-binding profiles and off-target actions on other neurotransmitter receptors, as well as the approval of xanomeline-trospium for schizophrenia by the US FDA: “Antipsychotic drugs that block the dopamine D2 receptor (D2R) have been the cornerstone of pharmacological treatment for schizophrenia for over 70 years. 1 – 3 …..Moreover, the risk-to-benefit ratio of antipsychotics is often challenged by their multiple side-effects associated with their receptor-binding profiles and frequently linked to off-target actions beyond D2R blockade. 1 , 2 …… Xanomeline, a muscarinic M1/M4-preferring receptor agonist, has demonstrated improvements in symptoms of schizophrenia in early and late-stage randomized placebo-controlled controlled trials with medium-to-large effect sizes, with potential cholinergic adverse events mitigated by its combination with trospium, a peripheral muscarinic antagonist. 10 – 13 In September 2024, the U.S. Food and Drug Administration approved xanomeline combined with trospium for schizophrenia, marking it as the first antipsychotic targeting muscarinic receptors. (1) “ #2.3: A systematic review and a meta-analysis are proposed for examining the impact of muscarinic agonists and allosteric modulators in animal models of psychosis. The level of complexity is high with respect to the varying types of compounds (agonists vs. partial agonists, receptor subtype selectivity, binding affinity, etc.), which will make it difficult to accurately categorize compounds. For example, positive allosteric modulators often exhibit a range of effects that include modulation of acetylcholine potency and efficacy in addition to allosteric agonist activity. The degree to which such activities have been adequately assessed will likely vary from lab to lab and such data may not be readily available in the papers that address in vivo efficacy in animal models of psychosis. These concerns are addressed to some extent in the “Exploration of heterogeneity” section, but a more explicit discussion of how concepts of potency and efficacy, for example, will be handled is warranted. Our reply: We would like to thank the reviewer for this insightful comment. We have now expanded the “Exploration of heterogeneity” section to elaborate on how these pharmacological properties will be examined, taking into account different modes of action and efforts to calculate indices that minimize potential variability and heterogeneity in measuring these properties (e.g., if possible, differences in the log((maximal efficacy/EC50)).(2) We will aim to use reliable sources for obtaining information about these properties (e.g., IUPHAR/BPS database)(3); however, we will not conduct a systematic review of studies to synthesize them, and we have noted this limitation in the “Discussion” section. Changes in the manuscript : We expanded the methods in the “Exploration of heterogeneity” accordingly: We will examine the pharmacological properties of muscarinic receptor agonists, considering mode of action (e.g., orthosteric agonism, positive allosteric modulation) and other key characteristics as sources of heterogeneity, using data primarily from established databases (e.g., IUPHAR/BPS) 43 and original publications that characterize these compounds. Specifically, we will assess potency (half-maximal effective concentration, EC50) and efficacy (maximal response, distinguishing between full and partial agonism) for orthosteric agonists, and modulation of acetylcholine potency and efficacy (cooperative factors α and β), intrinsic efficacy (τ B ), and affinity for the allosteric site (K B ) for PAMs. (2,4) These properties will be examined across various muscarinic receptor subtypes, with a preference for human receptors while considering potential cross-species differences, and across downstream signaling pathways (e.g., via Gα s , Gα q , Gα i/o subunits, β -arrestin). Given the variability across assays and experimental settings, we will consider calculating a common standardized index, if possible, such as estimating differences in log((maximal response)/EC50) between the examined drugs and the natural ligand acetylcholine. (2) This approach may enable comparisons across compounds, receptor and signaling pathway selectivity, but summarizing the different properties into a single index may result in information loss, necessitating additional analyses . Moreover, the exact procedure cannot be predetermined due to anticipated heterogeneity in the data across the different compounds examined . Additionally, we will assess off-target actions by evaluating the mode of action and affinity of each compound toward other neurotransmitter receptors .” We added to the limitations that a systematic review of in vitro assays and pharmacokinetic studies will not be conducted: “… Additionally, we will explore whether heterogeneity in behavioral effects may be explained by differences in drug interactions with muscarinic receptors. Given the limited availability and application of in vivo readouts for muscarinic agonism, we will use in vitro data. We will not conduct a systematic review of in vitro assays and pharmacokinetic studies to synthesize information about the pharmacological properties of the drugs, but instead will aim to use reliable sources and standardized methods to assess these as sources of heterogeneity (see “Exploration of heterogeneity”)…” #2.4: In addition to the sources of heterogeneity discussed, the physicochemical properties of compounds may impact the effectiveness of treatments; consideration of ADME properties of compounds could provide an important perspective. For example, multiparameter optimization values could help explain variability in responses for compounds with similar receptor activity profiles. Our reply: Thank you for raising this important point. Similarly to the above, we expanded the “Exploration of heterogeneity” section to include physicochemical parameters and their integration with the Central Nervous System Multiparameter Optimization Desirability approach. (5,6) Changes in the manuscript : We expanded accordingly the “Exploration of heterogeneity” section: “… We will explore potential sources of heterogeneity for …. type of muscarinic receptor agonists or PAMs, their pharmacological and physiochemical properties, and dose (details below), … We will use the Central Nervous System Multiparameter Optimization Desirability algorithm (5,6) to examine the physicochemical properties of the drugs as source of heterogeneity. This algorithm calculates a composite desirability score based on six key properties, i.e., lipophilicity, distribution coefficient, molecular weight, topological polar surface area, number of hydrogen bond donors, and the most basic center, which aligns well with the pharmacokinetic attributes, blood-brain barrier permeability and safety . (5,6) Values for these properties will be estimated based on the chemical structure information using OPEn structure–activity/property Relationship App (OPERA) version 2.9.1 (a freely available, open-source provided distributed under MIT license ) . (7) ” #2.5: Beyond the pharmacological properties of the compounds under investigation, the impact of muscarinic receptor activation might vary significantly depending on the different compounds utilized to induce behavioral changes (e.g., NMDA antagonists vs. dopamine agonists) or the behavioral readouts (e.g., pre-pulse inhibition of startle response vs. apomorphine induced climbing). The authors refer to some of the inherent difficulties in the “Assessment of indirectness of animal experiments” section, including concerns about the applicability of various animal models to clinical utility. In this sense, it might be helpful to examine the consistency of comparator compounds (e.g., D 2 and 5-HT 2 antagonists) that are used clinically in treatment of schizophrenia, and are often used as control compounds in studies of muscarinic agonists and other potential therapeutic compounds. This is perhaps alluded to in the “Data synthesis/planned comparisons” section, although additional details would be helpful. Our reply: We agree with this point, and we have added a comparison of D2R-blocking antipsychotics with inactive control conditions (e.g., vehicle) to examine the consistency of their effects in the included experiments and to inform the “Assessment of indirectness of animal experiments”. This is now described in the “Comparison groups” Changes in the manuscript : We added this comparison in the “Comparison groups”: “Table 1 outlines the planned comparisons, …. Additionally, we will examine the comparison between active and inactive control conditions to provide insights into the consistency of the effects of D2R-blocking antipsychotic in the included experiments and to inform the assessment of indirectness (see “Assessment of indirectness of the animal experiments”).” #2.6: An additional consideration is the presence or absence of adverse effects for the compounds under investigation. The clinical utility of muscarinic agonists has been limited by adverse effect profiles, which vary from compound to compound, but likely include both off-target (e.g., M 3 receptor-mediated) and on-target (i.e., M 1 or M 4 receptor-mediated) effects. Adverse effects such as salivation, lacrimation, diarrhea, or convulsions would provide important information regarding the in vivo pharmacological profile of compounds and the separation between beneficial and undesirable effects (i.e., the therapeutic window). Our reply: Thank you for this point. We agree that examining adverse events is important for assessing the risk-to-benefit ratio of these drugs. However, we had chosen already from the start of our protocol to focus on behavioural outcomes and not include adverse events due to their sparse and inconsistent reporting in studies of animal models of psychosis (as also noted in our previous review on TAAR1 agonists)(8) and their examination in other study designs excluded from our review (e.g., using naïve animals not subjected to models of psychosis). Furthermore, cholinergic adverse events may potentially be mitigated in clinical settings through the combination of peripheral antagonists, as seen with xanomeline-trospium.(9)Nonetheless, we will aim to extract adverse event data if found in the included studies and consider secondary publications where relevant. These considerations are addressed in the “Discussion” section under limitations. Changes in the manuscript: We expanded the limitations in the “Discussion” section to include consideration of cholinergic adverse events, similar to the previously reported neurobiological measures: “We will not analyse neurobiological measures due to their heterogeneous use across studies and the lack of an established biomarker in schizophrenia, 6 .. Similarly, we will not examine cholinergic adverse events in animals, such as salivation, lacrimation and diarrhea, which may offer insights into the risk-benefit profile but could be mitigated in clinical settings with peripheral muscarinic receptor antagonists, as shown with the xanomeline-trospium combination. 10 – 13 We will aim to extract and potentially analyse these measures in secondary publications .” #2.7: Overall, the topic is of timely interest and worth pursuing with some additional attention to the details to be evaluated. Our reply: Thank you once again for your overall endorsement and for the thoughtful comments that have substantially strengthened our protocol. In addition to the above-mentioned changes, we have also updated the “Study status” to reflect the changes during the revision: “…There were no changes from the original PROSPERO registration of the protocol, except for expanding the methods with additional details (also in response to the reviewer’s comments), (10,11) revising the search strategy to include terms for allosteric modulation as suggested by a reviewer, (10) adding physicochemical properties of the compounds in the “Exploration of Heterogeneity” per another reviewer’s comment, (11) and deciding not to search Scopus and CINAHL after consulting with the information specialist (which is not expected to affect the coverage of our search)….” References 1.U.S. Food and Drug Administration. FDA Approves Drug with New Mechanism of Action for Treatment of Schizophrenia 2024 [Available from: https://www.fda.gov/news-events/press-announcements/fda-approves-drug-new-mechanism-action-treatment-schizophrenia . 2. Kenakin T. A Scale of Agonism and Allosteric Modulation for Assessment of Selectivity, Bias, and Receptor Mutation. Mol Pharmacol. 2017;92(4):414-24. 3. Harding SD, et al. The IUPHAR/BPS guide to PHARMACOLOGY in 2022: curating pharmacology for COVID-19, malaria and antibacterials. Nucleic Acids Res. 2022;50(D1):D1282-d94. 4. Kenakin T. Know your molecule: pharmacological characterization of drug candidates to enhance efficacy and reduce late-stage attrition. Nature Reviews Drug Discovery. 2024:1-19. 5. Wager TT, et al. Moving beyond rules: the development of a central nervous system multiparameter optimization (CNS MPO) approach to enable alignment of druglike properties. ACS Chem Neurosci. 2010;1(6):435-49. 6. Wager TT, et al. Central Nervous System Multiparameter Optimization Desirability: Application in Drug Discovery. ACS Chem Neurosci. 2016;7(6):767-75. 7. Mansouri K, et al. OPERA models for predicting physicochemical properties and environmental fate endpoints. Journal of Cheminformatics. 2018;10(1):10. 8. Siafis S, et al. Trace amine-associated receptor 1 (TAAR1) agonism for psychosis: a living systematic review and meta-analysis of human and non-human data. Wellcome Open Research. 2024;9. 9. Paul SM, et al. Muscarinic Acetylcholine Receptor Agonists as Novel Treatments for Schizophrenia. Am J Psychiatry. 2022;179(9):611-27. 10. Foster D. Peer Review Report For: Muscarinic receptor agonists in animal models of psychosis: protocol for a systematic review and meta-analysis [version 1; peer review: 2 approved with reservations]. F1000Research. 2024;13:1017. 11. Messer W. Peer Review Report For: Muscarinic receptor agonists in animal models of psychosis: protocol for a systematic review and meta-analysis [version 1; peer review: 2 approved with reservations]. F1000Research 2024;13:1017. Competing Interests: Spyridon Siafis: None. Nobuyuki Nomura: N.N. has received manuscript fees from Sumitomo Pharma. Johannes Schneider-Thoma: None. Irene Bighelli: None. Alexandra Bannach-Brown: None. Fiona J. Ramage: None. Francesca Tinsdeall: None. Ioannis Mantas: None. Sameer Jauhar: SJ has received honoraria for educational talks given for Boehringer Ingelheim, Lundbeck, Janssen, and Sunovion, and has advised on antipsychotics to LB Pharmaceuticals. Sridhar Natesan: None. Anthony Vernon: ACV has received research support from UCB S.A and Bit.Bio (https://www.bit.bio/) and has received honoraria for seminars at GlaxoSmithKline. Andrea de Bartolomeis: AdB has received research support from Janssen, Lundbeck, and Otsuka and lecture fees for educational meeting from Chiesi, Lundbeck, Roche, Sunovion, Vitria, Recordati, Angelini and Takeda; he has served on advisory boards for Eli Lilly, Jansen, Lundbeck, Otsuka, Roche, and Takeda, Chiesi, Recordati, Angelini, Vitria. Sabine M. Hölter: None. Natascha I. Drude: None. Ulf Tölch: None. Wulf-Peter Hansen: None. Virginia Chiocchia: None. Oliver Howes: ODH has received investigator-initiated research funding from and/or participated in advisory/speaker meetings organised by Angellini, Autifony, Biogen, Boehringer-Ingelheim, Eli Lilly, Elysium, Heptares, Global Medical Education, Invicro, Jansenn, Karuna, Lundbeck, Merck, Neurocrine, Ontrack/ Pangea, Otsuka, Sunovion, Recordati, Roche, Rovi and Viatris/ Mylan. He was previously a part-time employee of Lundbeck A/v. Dr Howes has a patent for the use of dopaminergic imaging. Josef Priller: None. Georgia Salanti: None. Malcolm R. Macleod: None. Stefan Leucht: SL has received received honoraria for advising/consulting and/or for lectures and/or for educational material from Angelini, Boehringer Ingelheim, Eisai, Ekademia, GedeonRichter, Janssen, Karuna, Kynexis, Lundbeck, Medichem, Medscape, Mitsubishi, Otsuka, NovoNordisk, Recordati, Rovi, Teva. Close Report a concern COMMENT ON THIS REPORT Views 0 Cite How to cite this report: Foster D. Reviewer Report For: Muscarinic receptor agonists and positive allosteric modulators in animal models of psychosis: protocol for a systematic review and meta-analysis [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 13 :1017 ( https://doi.org/10.5256/f1000research.170522.r325666 ) The direct URL for this report is: https://f1000research.com/articles/13-1017/v1#referee-response-325666 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 11 Oct 2024 Daniel Foster , Department of Pharmacology, Physiology and Neuroscience, University of South Carolina School of Medicine, Columbia, USA Approved with Reservations VIEWS 0 https://doi.org/10.5256/f1000research.170522.r325666 The authors provide a study protocol to conduct a systematic review and meta-analyses to assess pharmacological targeting of muscarinic receptors in preclinical studies relevant to schizophrenia. This is an especially timely study that has the potential to summarize a ... Continue reading READ ALL The authors provide a study protocol to conduct a systematic review and meta-analyses to assess pharmacological targeting of muscarinic receptors in preclinical studies relevant to schizophrenia. This is an especially timely study that has the potential to summarize a vast preclinical literature and provide insights into the efficacy of targeting muscarinic receptors and possible sources of heterogeneity in these data sets that could arise due to drugs that have different selectivity for muscarinic receptor subtypes, or different modes of pharmacological activity. The choice of primary and secondary behaviors is well justified, and the exclusion of studies that only assess neurophysiological or histopathological measures is clearly stated. One potential caveat of this study protocol is the use of the pharmacological term "agonist" throughout the protocol. In specific sentences, the authors acknowledge the potential role for allosteric modulators in mediating antipsychotic-like effects. For example, in the interventions section, the authors write: "We will include any pharmacological agent acting as an agonist or positive allosteric modulator at any of the five subtypes". They then state in the Exploration of Heterogeneity section that they will consider: "pharmacological characteristics (e.g., mode of action, selectivity for muscarinic or other receptors, potency, efficacy)". These statements are much appreciated, and these meta-analyses could provide important insights into how positive allosteric modulators and agonists differ in efficacy in preclinical studies across numerous symptom domains. Given the potential importance of understanding how allosteric modulators and agonists are similar or differ in their ability to modulate different preclinical assays relating to numerous schizophrenia symptom domains, it may be worth changing the title and clarifying the importance of this pharmacological distinction more clearly. The agonist vs allosteric modulator issue is also evident in the search terms included in the extended data where only "agonist" is used and "allosteric modulator" is absent. In these searches, numerous allosteric modulators are included by name. However, this approach has the potential to miss any allosteric modulators not included by name in the search terms. The importance of studying potential discrepancies between agonist and allosteric modulators is highlighted by ongoing clinical trials for both types of compounds, with allosteric modulators currently being investigated in the clinic by AbbieVie, Neumora, and Neurosterix, and muscarinic agonist therapy having been approved for Karuna/Bristol Myers Squibb and under clinical investigation by several other companies including Neurocrine, Anavex, and Maplight. Another potential issue that warrants attention is the use of genetically modified knockout animals. Some of the most compelling evidence we have for determining which muscarinic receptor subtypes mediate specific behavioral effects comes from studies that combine selective pharmacology tools in mice where the receptor has been deleted either globally or from specific populations of neurons. However, the current study design does not clearly outline how or if studies in these knockout animals will be evaluated. The use of a similar methodology by the authors previously to assess TARR1 agonists in non-human studies is a strength, and the team assembled is well-suited to carry out this study. Overall, this study protocol is thoughtfully written and addresses important and timely questions with the potential to unveil critical insights into the ability of compounds targeting muscarinic receptors to modulate schizophrenia-relevant behaviors across numerous symptom domains in preclinical studies. Is the rationale for, and objectives of, the study clearly described? Yes Is the study design appropriate for the research question? Yes Are sufficient details of the methods provided to allow replication by others? Yes Are the datasets clearly presented in a useable and accessible format? Not applicable Competing Interests: No competing interests were disclosed. Reviewer Expertise: I study muscarinic receptor modulation of preclinical physiology and behaviors relevant to schizophrenia. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Foster D. Reviewer Report For: Muscarinic receptor agonists and positive allosteric modulators in animal models of psychosis: protocol for a systematic review and meta-analysis [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 13 :1017 ( https://doi.org/10.5256/f1000research.170522.r325666 ) The direct URL for this report is: https://f1000research.com/articles/13-1017/v1#referee-response-325666 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Author Response 02 Jan 2025 Spyridon Siafis , Technical University of Munich, School of Medicine and Health, Department of Psychiatry and Psychotherapy, Munich, Germany 02 Jan 2025 Author Response #1.1: The authors provide a study protocol to conduct a systematic review and meta-analyses to assess pharmacological targeting of muscarinic receptors in preclinical studies relevant to schizophrenia. This is an ... Continue reading #1.1: The authors provide a study protocol to conduct a systematic review and meta-analyses to assess pharmacological targeting of muscarinic receptors in preclinical studies relevant to schizophrenia. This is an especially timely study that has the potential to summarize a vast preclinical literature and provide insights into the efficacy of targeting muscarinic receptors and possible sources of heterogeneity in these data sets that could arise due to drugs that have different selectivity for muscarinic receptor subtypes, or different modes of pharmacological activity. The choice of primary and secondary behaviors is well justified, and the exclusion of studies that only assess neurophysiological or histopathological measures is clearly stated. Our reply: We would like to thank the reviewer for recognizing the relevance of our planned work, for the overall endorsement of our methods, as well as for the constructive comments that further improved our methodology. Please find our point-by-point responses to the comments below. #1.2 One potential caveat of this study protocol is the use of the pharmacological term "agonist" throughout the protocol. In specific sentences, the authors acknowledge the potential role for allosteric modulators in mediating antipsychotic-like effects. For example, in the interventions section, the authors write: "We will include any pharmacological agent acting as an agonist or positive allosteric modulator at any of the five subtypes". They then state in the Exploration of Heterogeneity section that they will consider: "pharmacological characteristics (e.g., mode of action, selectivity for muscarinic or other receptors, potency, efficacy)". These statements are much appreciated, and these meta-analyses could provide important insights into how positive allosteric modulators and agonists differ in efficacy in preclinical studies across numerous symptom domains. Given the potential importance of understanding how allosteric modulators and agonists are similar or differ in their ability to modulate different preclinical assays relating to numerous schizophrenia symptom domains, it may be worth changing the title and clarifying the importance of this pharmacological distinction more clearly. Our reply: We would like to thank the reviewer for raising this important point. We had already planned to examine both orthosteric receptor agonists and positive allosteric modulators, as well as their differences, which we had highlighted in several parts of the manuscript. However, for simplicity, we had generally used the term 'agonism' throughout the protocol. We agree with the reviewer on the importance of this distinction, and we have clarified this in response to the reviewer’s comments. Changes in the manuscript : We have revised the title to include 'positive allosteric modulation': “ Muscarinic receptor agonists and positive allosteric modulators in animal models of psychosis: protocol for a systematic review and meta-analysis .” We have incorporated 'positive allosteric modulation' more frequently throughout the manuscript to emphasize this distinction. We have clarified its significance further in the introduction: “…., and the potential differences between orthosteric agonists and PAMs. For example, PAMs modulate receptor activity by binding to a site distinct from the natural ligand, offering theoretical advantages such as increased selectivity and safety over orthosteric agonists. (1,2) ”. In relationship to the comments of another reviewer,(3) we have also expanded the “Exploration of heterogeneity” section by providing more details in the pharmacological properties considered for orthosteric agonists and positive allosteric modulators: “ We will examine the pharmacological properties of muscarinic receptor agonists, considering mode of action (e.g., orthosteric agonism, positive allosteric modulation) and other key characteristics as sources of heterogeneity, using data primarily from established databases (e.g., IUPHAR/BPS) 43 and original publications that characterize these compounds. Specifically, we will assess potency (half-maximal effective concentration, EC50) and efficacy (maximal response, distinguishing between full and partial agonism) for orthosteric agonists, and modulation of acetylcholine potency and efficacy (cooperative factors α and β), intrinsic efficacy (τ B ), and affinity for the allosteric site (K B ) for PAMs. (1,4) These properties will be examined across various muscarinic receptor subtypes, with a preference for human receptors while considering potential cross-species differences, and across downstream signaling pathways (e.g., via Gα s , Gα q , Gα i/o subunits, β -arrestin). Given the variability across assays and experimental settings, we will consider calculating a common standardized index, if possible, such as estimating differences in log((maximal response)/EC50) between the examined drugs and the natural ligand acetylcholine. (4) This approach may enable comparisons across compounds, receptor and signaling pathway selectivity, but summarizing the different properties into a single index may result in information loss, necessitating additional analyses. Moreover, the exact procedure cannot be predetermined due to anticipated heterogeneity in the data across the different compounds examined.” #1.3 The agonist vs allosteric modulator issue is also evident in the search terms included in the extended data where only "agonist" is used and "allosteric modulator" is absent. In these searches, numerous allosteric modulators are included by name. However, this approach has the potential to miss any allosteric modulators not included by name in the search terms. The importance of studying potential discrepancies between agonist and allosteric modulators is highlighted by ongoing clinical trials for both types of compounds, with allosteric modulators currently being investigated in the clinic by AbbieVie, Neumora, and Neurosterix, and muscarinic agonist therapy having been approved for Karuna/Bristol Myers Squibb and under clinical investigation by several other companies including Neurocrine, Anavex, and Maplight. Our reply: We would like to thank the reviewer for highlighting this potential caveat in our search strategy. In collaboration with Dr. Farhad Shokraneh, an experienced information specialist (see Acknowledgments in the manuscript), we have revised the search strategy across multiple electronic databases to include terms relevant to allosteric modulation, ensuring we capture any studies on this category of medications. As it was already noted in the methods section, we will also supplement our searches using the psychosis-SOLES,(5)a dedicated database of preclinical psychosis studies, allowing us to conduct broader searches without restricting terms to “agonism” or “allosteric modulation”. These methods will enhance our search coverage and reduce the risk of missing relevant studies on positive allosteric modulators. Changes in the manuscript : We have revised the methods to clarify that the search strategies will encompass both agonism and allosteric modulation: 'For muscarinic agents, we will use broad terms like muscarinic agonists or allosteric modulators and…' Additionally, we have updated the draft search strategy in MEDLINE via Ovid within the extended data to include terms for “allosteric modulation”. See the revised extended data( https://doi.org/10.5281/zenodo.14534308 ): “...  #3. Muscarinic Agonists/ or Muscarine/ or (Muscarin or Muscarine or Muscarinic or M1 or M2 or M3 or M4 or M5 or Muscarinomimetic*).ti,ab,tw. #4. Allosteric Regulation/ or Allosteric Site/ or (Alloster* or PAM or PAMs or Modulat* or Agonis*).ti,ab,tw. #5. 3 and 4…. ” #1.4: Another potential issue that warrants attention is the use of genetically modified knockout animals. Some of the most compelling evidence we have for determining which muscarinic receptor subtypes mediate specific behavioral effects comes from studies that combine selective pharmacology tools in mice where the receptor has been deleted either globally or from specific populations of neurons. However, the current study design does not clearly outline how or if studies in these knockout animals will be evaluated. Our reply: Thank you for this point. We agree that genetically modified knockout animals can be important tools for delineating the potential receptor mechanisms of pharmacological interventions. We had already planned to compare muscarinic receptor agonists or PAMs with inactive control conditions in the context of genetic or pharmacological muscarinic receptor antagonism to determine if any observed differences result from muscarinic receptor activation, as it had been outlined in Table 1 and “Animal Population and Model Induction”. However, we agree that this was not clearly described, and we have therefore revised the methods accordingly. Changes in the manuscript : We revised the “Animal Population and Model Induction” section to better describe the inclusion of animal cohorts with genetic knockouts of muscarinic receptors or those receiving pharmacological muscarinic antagonists: “….Moreover, in the eligible studies, we will extract data from “naïve” animal cohorts (i.e., animals that have not undergone models of psychosis), and animal cohorts that have undergone both models of psychosis and muscarinic receptor antagonism via genetic (i.e, genetically modified animals with knockout of all or specific muscarinic receptors, either globally or in specific neuron populations) (6) or pharmacological manipulation (e.g., co-administration of selective or non-selective muscarinic receptor antagonists like scopolamine) (7) (see further details in “Comparison groups”)….” We expanded the “Comparison groups” to mention explicitly the comparison of muscarinic drugs versus inactive control conditions (e.g., vehicle) in animal models of psychosis in the context of muscarinic receptor antagonism: “… We will also compare muscarinic receptor agonists or PAMs with inactive control conditions in contexts of genetic or pharmacological muscarinic receptor antagonism (as described in “Animal population and model induction”) to determine if any observed differences result from muscarinic receptor activation. Separate analyses may be conducted for the antagonism of specific muscarinic receptor subtypes and/or within specific neuronal populations, if sufficient data are available..” #1.5: The use of a similar methodology by the authors previously to assess TARR1 agonists in non-human studies is a strength, and the team assembled is well-suited to carry out this study. Overall, this study protocol is thoughtfully written and addresses important and timely questions with the potential to unveil critical insights into the ability of compounds targeting muscarinic receptors to modulate schizophrenia-relevant behaviors across numerous symptom domains in preclinical studies. Our reply : Thank you once again for your overall endorsement and for the thoughtful comments that have substantially strengthened our protocol. In addition to the above-mentioned changes, we have also updated the “Study status” to reflect the changes during the revision: “…There were no changes from the original PROSPERO registration of the protocol, except for expanding the methods with additional details (also in response to the reviewer’s comments), (3,8) revising the search strategy to include terms for allosteric modulation as suggested by a reviewer, (8) adding physicochemical properties of the compounds in the “Exploration of Heterogeneity” per another reviewer’s comment, (3) and deciding not to search Scopus and CINAHL after consulting with the information specialist (which is not expected to affect the coverage of our search)….” References 1. Kenakin T. Know your molecule: pharmacological characterization of drug candidates to enhance efficacy and reduce late-stage attrition. Nature Reviews Drug Discovery. 2024:1-19. 2. Foster DJ, et al. Allosteric Modulation of GPCRs: New Insights and Potential Utility for Treatment of Schizophrenia and Other CNS Disorders. Neuron. 2017;94(3):431-46. 3. Messer W. Peer Review Report For: Muscarinic receptor agonists in animal models of psychosis: protocol for a systematic review and meta-analysis [version 1; peer review: 2 approved with reservations]. F1000Research 2024;13:1017. 4. Kenakin T. A Scale of Agonism and Allosteric Modulation for Assessment of Selectivity, Bias, and Receptor Mutation. Mol Pharmacol. 2017;92(4):414-24. 5. Smith S, et al . Psychosis-SOLES 2024 [Available from: https://camarades.shinyapps.io/psychosis-soles March 4, 2024. 6. Thomsen M, et al. Physiological roles of CNS muscarinic receptors gained from knockout mice. Neuropharmacology. 2018;136(Pt C):411-20. 7. Klinkenberg I, et al. The validity of scopolamine as a pharmacological model for cognitive impairment: a review of animal behavioral studies. Neurosci Biobehav Rev. 2010;34(8):1307-50. 8. Foster D. Peer Review Report For: Muscarinic receptor agonists in animal models of psychosis: protocol for a systematic review and meta-analysis [version 1; peer review: 2 approved with reservations]. F1000Research. 2024;13:1017. #1.1: The authors provide a study protocol to conduct a systematic review and meta-analyses to assess pharmacological targeting of muscarinic receptors in preclinical studies relevant to schizophrenia. This is an especially timely study that has the potential to summarize a vast preclinical literature and provide insights into the efficacy of targeting muscarinic receptors and possible sources of heterogeneity in these data sets that could arise due to drugs that have different selectivity for muscarinic receptor subtypes, or different modes of pharmacological activity. The choice of primary and secondary behaviors is well justified, and the exclusion of studies that only assess neurophysiological or histopathological measures is clearly stated. Our reply: We would like to thank the reviewer for recognizing the relevance of our planned work, for the overall endorsement of our methods, as well as for the constructive comments that further improved our methodology. Please find our point-by-point responses to the comments below. #1.2 One potential caveat of this study protocol is the use of the pharmacological term "agonist" throughout the protocol. In specific sentences, the authors acknowledge the potential role for allosteric modulators in mediating antipsychotic-like effects. For example, in the interventions section, the authors write: "We will include any pharmacological agent acting as an agonist or positive allosteric modulator at any of the five subtypes". They then state in the Exploration of Heterogeneity section that they will consider: "pharmacological characteristics (e.g., mode of action, selectivity for muscarinic or other receptors, potency, efficacy)". These statements are much appreciated, and these meta-analyses could provide important insights into how positive allosteric modulators and agonists differ in efficacy in preclinical studies across numerous symptom domains. Given the potential importance of understanding how allosteric modulators and agonists are similar or differ in their ability to modulate different preclinical assays relating to numerous schizophrenia symptom domains, it may be worth changing the title and clarifying the importance of this pharmacological distinction more clearly. Our reply: We would like to thank the reviewer for raising this important point. We had already planned to examine both orthosteric receptor agonists and positive allosteric modulators, as well as their differences, which we had highlighted in several parts of the manuscript. However, for simplicity, we had generally used the term 'agonism' throughout the protocol. We agree with the reviewer on the importance of this distinction, and we have clarified this in response to the reviewer’s comments. Changes in the manuscript : We have revised the title to include 'positive allosteric modulation': “ Muscarinic receptor agonists and positive allosteric modulators in animal models of psychosis: protocol for a systematic review and meta-analysis .” We have incorporated 'positive allosteric modulation' more frequently throughout the manuscript to emphasize this distinction. We have clarified its significance further in the introduction: “…., and the potential differences between orthosteric agonists and PAMs. For example, PAMs modulate receptor activity by binding to a site distinct from the natural ligand, offering theoretical advantages such as increased selectivity and safety over orthosteric agonists. (1,2) ”. In relationship to the comments of another reviewer,(3) we have also expanded the “Exploration of heterogeneity” section by providing more details in the pharmacological properties considered for orthosteric agonists and positive allosteric modulators: “ We will examine the pharmacological properties of muscarinic receptor agonists, considering mode of action (e.g., orthosteric agonism, positive allosteric modulation) and other key characteristics as sources of heterogeneity, using data primarily from established databases (e.g., IUPHAR/BPS) 43 and original publications that characterize these compounds. Specifically, we will assess potency (half-maximal effective concentration, EC50) and efficacy (maximal response, distinguishing between full and partial agonism) for orthosteric agonists, and modulation of acetylcholine potency and efficacy (cooperative factors α and β), intrinsic efficacy (τ B ), and affinity for the allosteric site (K B ) for PAMs. (1,4) These properties will be examined across various muscarinic receptor subtypes, with a preference for human receptors while considering potential cross-species differences, and across downstream signaling pathways (e.g., via Gα s , Gα q , Gα i/o subunits, β -arrestin). Given the variability across assays and experimental settings, we will consider calculating a common standardized index, if possible, such as estimating differences in log((maximal response)/EC50) between the examined drugs and the natural ligand acetylcholine. (4) This approach may enable comparisons across compounds, receptor and signaling pathway selectivity, but summarizing the different properties into a single index may result in information loss, necessitating additional analyses. Moreover, the exact procedure cannot be predetermined due to anticipated heterogeneity in the data across the different compounds examined.” #1.3 The agonist vs allosteric modulator issue is also evident in the search terms included in the extended data where only "agonist" is used and "allosteric modulator" is absent. In these searches, numerous allosteric modulators are included by name. However, this approach has the potential to miss any allosteric modulators not included by name in the search terms. The importance of studying potential discrepancies between agonist and allosteric modulators is highlighted by ongoing clinical trials for both types of compounds, with allosteric modulators currently being investigated in the clinic by AbbieVie, Neumora, and Neurosterix, and muscarinic agonist therapy having been approved for Karuna/Bristol Myers Squibb and under clinical investigation by several other companies including Neurocrine, Anavex, and Maplight. Our reply: We would like to thank the reviewer for highlighting this potential caveat in our search strategy. In collaboration with Dr. Farhad Shokraneh, an experienced information specialist (see Acknowledgments in the manuscript), we have revised the search strategy across multiple electronic databases to include terms relevant to allosteric modulation, ensuring we capture any studies on this category of medications. As it was already noted in the methods section, we will also supplement our searches using the psychosis-SOLES,(5)a dedicated database of preclinical psychosis studies, allowing us to conduct broader searches without restricting terms to “agonism” or “allosteric modulation”. These methods will enhance our search coverage and reduce the risk of missing relevant studies on positive allosteric modulators. Changes in the manuscript : We have revised the methods to clarify that the search strategies will encompass both agonism and allosteric modulation: 'For muscarinic agents, we will use broad terms like muscarinic agonists or allosteric modulators and…' Additionally, we have updated the draft search strategy in MEDLINE via Ovid within the extended data to include terms for “allosteric modulation”. See the revised extended data( https://doi.org/10.5281/zenodo.14534308 ): “...  #3. Muscarinic Agonists/ or Muscarine/ or (Muscarin or Muscarine or Muscarinic or M1 or M2 or M3 or M4 or M5 or Muscarinomimetic*).ti,ab,tw. #4. Allosteric Regulation/ or Allosteric Site/ or (Alloster* or PAM or PAMs or Modulat* or Agonis*).ti,ab,tw. #5. 3 and 4…. ” #1.4: Another potential issue that warrants attention is the use of genetically modified knockout animals. Some of the most compelling evidence we have for determining which muscarinic receptor subtypes mediate specific behavioral effects comes from studies that combine selective pharmacology tools in mice where the receptor has been deleted either globally or from specific populations of neurons. However, the current study design does not clearly outline how or if studies in these knockout animals will be evaluated. Our reply: Thank you for this point. We agree that genetically modified knockout animals can be important tools for delineating the potential receptor mechanisms of pharmacological interventions. We had already planned to compare muscarinic receptor agonists or PAMs with inactive control conditions in the context of genetic or pharmacological muscarinic receptor antagonism to determine if any observed differences result from muscarinic receptor activation, as it had been outlined in Table 1 and “Animal Population and Model Induction”. However, we agree that this was not clearly described, and we have therefore revised the methods accordingly. Changes in the manuscript : We revised the “Animal Population and Model Induction” section to better describe the inclusion of animal cohorts with genetic knockouts of muscarinic receptors or those receiving pharmacological muscarinic antagonists: “….Moreover, in the eligible studies, we will extract data from “naïve” animal cohorts (i.e., animals that have not undergone models of psychosis), and animal cohorts that have undergone both models of psychosis and muscarinic receptor antagonism via genetic (i.e, genetically modified animals with knockout of all or specific muscarinic receptors, either globally or in specific neuron populations) (6) or pharmacological manipulation (e.g., co-administration of selective or non-selective muscarinic receptor antagonists like scopolamine) (7) (see further details in “Comparison groups”)….” We expanded the “Comparison groups” to mention explicitly the comparison of muscarinic drugs versus inactive control conditions (e.g., vehicle) in animal models of psychosis in the context of muscarinic receptor antagonism: “… We will also compare muscarinic receptor agonists or PAMs with inactive control conditions in contexts of genetic or pharmacological muscarinic receptor antagonism (as described in “Animal population and model induction”) to determine if any observed differences result from muscarinic receptor activation. Separate analyses may be conducted for the antagonism of specific muscarinic receptor subtypes and/or within specific neuronal populations, if sufficient data are available..” #1.5: The use of a similar methodology by the authors previously to assess TARR1 agonists in non-human studies is a strength, and the team assembled is well-suited to carry out this study. Overall, this study protocol is thoughtfully written and addresses important and timely questions with the potential to unveil critical insights into the ability of compounds targeting muscarinic receptors to modulate schizophrenia-relevant behaviors across numerous symptom domains in preclinical studies. Our reply : Thank you once again for your overall endorsement and for the thoughtful comments that have substantially strengthened our protocol. In addition to the above-mentioned changes, we have also updated the “Study status” to reflect the changes during the revision: “…There were no changes from the original PROSPERO registration of the protocol, except for expanding the methods with additional details (also in response to the reviewer’s comments), (3,8) revising the search strategy to include terms for allosteric modulation as suggested by a reviewer, (8) adding physicochemical properties of the compounds in the “Exploration of Heterogeneity” per another reviewer’s comment, (3) and deciding not to search Scopus and CINAHL after consulting with the information specialist (which is not expected to affect the coverage of our search)….” References 1. Kenakin T. Know your molecule: pharmacological characterization of drug candidates to enhance efficacy and reduce late-stage attrition. Nature Reviews Drug Discovery. 2024:1-19. 2. Foster DJ, et al. Allosteric Modulation of GPCRs: New Insights and Potential Utility for Treatment of Schizophrenia and Other CNS Disorders. Neuron. 2017;94(3):431-46. 3. Messer W. Peer Review Report For: Muscarinic receptor agonists in animal models of psychosis: protocol for a systematic review and meta-analysis [version 1; peer review: 2 approved with reservations]. F1000Research 2024;13:1017. 4. Kenakin T. A Scale of Agonism and Allosteric Modulation for Assessment of Selectivity, Bias, and Receptor Mutation. Mol Pharmacol. 2017;92(4):414-24. 5. Smith S, et al . Psychosis-SOLES 2024 [Available from: https://camarades.shinyapps.io/psychosis-soles March 4, 2024. 6. Thomsen M, et al. Physiological roles of CNS muscarinic receptors gained from knockout mice. Neuropharmacology. 2018;136(Pt C):411-20. 7. Klinkenberg I, et al. The validity of scopolamine as a pharmacological model for cognitive impairment: a review of animal behavioral studies. Neurosci Biobehav Rev. 2010;34(8):1307-50. 8. Foster D. Peer Review Report For: Muscarinic receptor agonists in animal models of psychosis: protocol for a systematic review and meta-analysis [version 1; peer review: 2 approved with reservations]. F1000Research. 2024;13:1017. Competing Interests: Spyridon Siafis: None. Nobuyuki Nomura: N.N. has received manuscript fees from Sumitomo Pharma. Johannes Schneider-Thoma: None. Irene Bighelli: None. Alexandra Bannach-Brown: None. Fiona J. Ramage: None. Francesca Tinsdeall: None. Ioannis Mantas: None. Sameer Jauhar: SJ has received honoraria for educational talks given for Boehringer Ingelheim, Lundbeck, Janssen, and Sunovion, and has advised on antipsychotics to LB Pharmaceuticals. Sridhar Natesan: None. Anthony Vernon: ACV has received research support from UCB S.A and Bit.Bio (https://www.bit.bio/) and has received honoraria for seminars at GlaxoSmithKline. Andrea de Bartolomeis: AdB has received research support from Janssen, Lundbeck, and Otsuka and lecture fees for educational meeting from Chiesi, Lundbeck, Roche, Sunovion, Vitria, Recordati, Angelini and Takeda; he has served on advisory boards for Eli Lilly, Jansen, Lundbeck, Otsuka, Roche, and Takeda, Chiesi, Recordati, Angelini, Vitria. Sabine M. Hölter: None. Natascha I. Drude: None. Ulf Tölch: None. Wulf-Peter Hansen: None. Virginia Chiocchia: None. Oliver Howes: ODH has received investigator-initiated research funding from and/or participated in advisory/speaker meetings organised by Angellini, Autifony, Biogen, Boehringer-Ingelheim, Eli Lilly, Elysium, Heptares, Global Medical Education, Invicro, Jansenn, Karuna, Lundbeck, Merck, Neurocrine, Ontrack/ Pangea, Otsuka, Sunovion, Recordati, Roche, Rovi and Viatris/ Mylan. He was previously a part-time employee of Lundbeck A/v. Dr Howes has a patent for the use of dopaminergic imaging. Josef Priller: None. Georgia Salanti: None. Malcolm R. Macleod: None. Stefan Leucht: SL has received received honoraria for advising/consulting and/or for lectures and/or for educational material from Angelini, Boehringer Ingelheim, Eisai, Ekademia, GedeonRichter, Janssen, Karuna, Kynexis, Lundbeck, Medichem, Medscape, Mitsubishi, Otsuka, NovoNordisk, Recordati, Rovi, Teva. Close Report a concern Respond or Comment COMMENTS ON THIS REPORT Author Response 02 Jan 2025 Spyridon Siafis , Technical University of Munich, School of Medicine and Health, Department of Psychiatry and Psychotherapy, Munich, Germany 02 Jan 2025 Author Response #1.1: The authors provide a study protocol to conduct a systematic review and meta-analyses to assess pharmacological targeting of muscarinic receptors in preclinical studies relevant to schizophrenia. This is an ... Continue reading #1.1: The authors provide a study protocol to conduct a systematic review and meta-analyses to assess pharmacological targeting of muscarinic receptors in preclinical studies relevant to schizophrenia. This is an especially timely study that has the potential to summarize a vast preclinical literature and provide insights into the efficacy of targeting muscarinic receptors and possible sources of heterogeneity in these data sets that could arise due to drugs that have different selectivity for muscarinic receptor subtypes, or different modes of pharmacological activity. The choice of primary and secondary behaviors is well justified, and the exclusion of studies that only assess neurophysiological or histopathological measures is clearly stated. Our reply: We would like to thank the reviewer for recognizing the relevance of our planned work, for the overall endorsement of our methods, as well as for the constructive comments that further improved our methodology. Please find our point-by-point responses to the comments below. #1.2 One potential caveat of this study protocol is the use of the pharmacological term "agonist" throughout the protocol. In specific sentences, the authors acknowledge the potential role for allosteric modulators in mediating antipsychotic-like effects. For example, in the interventions section, the authors write: "We will include any pharmacological agent acting as an agonist or positive allosteric modulator at any of the five subtypes". They then state in the Exploration of Heterogeneity section that they will consider: "pharmacological characteristics (e.g., mode of action, selectivity for muscarinic or other receptors, potency, efficacy)". These statements are much appreciated, and these meta-analyses could provide important insights into how positive allosteric modulators and agonists differ in efficacy in preclinical studies across numerous symptom domains. Given the potential importance of understanding how allosteric modulators and agonists are similar or differ in their ability to modulate different preclinical assays relating to numerous schizophrenia symptom domains, it may be worth changing the title and clarifying the importance of this pharmacological distinction more clearly. Our reply: We would like to thank the reviewer for raising this important point. We had already planned to examine both orthosteric receptor agonists and positive allosteric modulators, as well as their differences, which we had highlighted in several parts of the manuscript. However, for simplicity, we had generally used the term 'agonism' throughout the protocol. We agree with the reviewer on the importance of this distinction, and we have clarified this in response to the reviewer’s comments. Changes in the manuscript : We have revised the title to include 'positive allosteric modulation': “ Muscarinic receptor agonists and positive allosteric modulators in animal models of psychosis: protocol for a systematic review and meta-analysis .” We have incorporated 'positive allosteric modulation' more frequently throughout the manuscript to emphasize this distinction. We have clarified its significance further in the introduction: “…., and the potential differences between orthosteric agonists and PAMs. For example, PAMs modulate receptor activity by binding to a site distinct from the natural ligand, offering theoretical advantages such as increased selectivity and safety over orthosteric agonists. (1,2) ”. In relationship to the comments of another reviewer,(3) we have also expanded the “Exploration of heterogeneity” section by providing more details in the pharmacological properties considered for orthosteric agonists and positive allosteric modulators: “ We will examine the pharmacological properties of muscarinic receptor agonists, considering mode of action (e.g., orthosteric agonism, positive allosteric modulation) and other key characteristics as sources of heterogeneity, using data primarily from established databases (e.g., IUPHAR/BPS) 43 and original publications that characterize these compounds. Specifically, we will assess potency (half-maximal effective concentration, EC50) and efficacy (maximal response, distinguishing between full and partial agonism) for orthosteric agonists, and modulation of acetylcholine potency and efficacy (cooperative factors α and β), intrinsic efficacy (τ B ), and affinity for the allosteric site (K B ) for PAMs. (1,4) These properties will be examined across various muscarinic receptor subtypes, with a preference for human receptors while considering potential cross-species differences, and across downstream signaling pathways (e.g., via Gα s , Gα q , Gα i/o subunits, β -arrestin). Given the variability across assays and experimental settings, we will consider calculating a common standardized index, if possible, such as estimating differences in log((maximal response)/EC50) between the examined drugs and the natural ligand acetylcholine. (4) This approach may enable comparisons across compounds, receptor and signaling pathway selectivity, but summarizing the different properties into a single index may result in information loss, necessitating additional analyses. Moreover, the exact procedure cannot be predetermined due to anticipated heterogeneity in the data across the different compounds examined.” #1.3 The agonist vs allosteric modulator issue is also evident in the search terms included in the extended data where only "agonist" is used and "allosteric modulator" is absent. In these searches, numerous allosteric modulators are included by name. However, this approach has the potential to miss any allosteric modulators not included by name in the search terms. The importance of studying potential discrepancies between agonist and allosteric modulators is highlighted by ongoing clinical trials for both types of compounds, with allosteric modulators currently being investigated in the clinic by AbbieVie, Neumora, and Neurosterix, and muscarinic agonist therapy having been approved for Karuna/Bristol Myers Squibb and under clinical investigation by several other companies including Neurocrine, Anavex, and Maplight. Our reply: We would like to thank the reviewer for highlighting this potential caveat in our search strategy. In collaboration with Dr. Farhad Shokraneh, an experienced information specialist (see Acknowledgments in the manuscript), we have revised the search strategy across multiple electronic databases to include terms relevant to allosteric modulation, ensuring we capture any studies on this category of medications. As it was already noted in the methods section, we will also supplement our searches using the psychosis-SOLES,(5)a dedicated database of preclinical psychosis studies, allowing us to conduct broader searches without restricting terms to “agonism” or “allosteric modulation”. These methods will enhance our search coverage and reduce the risk of missing relevant studies on positive allosteric modulators. Changes in the manuscript : We have revised the methods to clarify that the search strategies will encompass both agonism and allosteric modulation: 'For muscarinic agents, we will use broad terms like muscarinic agonists or allosteric modulators and…' Additionally, we have updated the draft search strategy in MEDLINE via Ovid within the extended data to include terms for “allosteric modulation”. See the revised extended data( https://doi.org/10.5281/zenodo.14534308 ): “...  #3. Muscarinic Agonists/ or Muscarine/ or (Muscarin or Muscarine or Muscarinic or M1 or M2 or M3 or M4 or M5 or Muscarinomimetic*).ti,ab,tw. #4. Allosteric Regulation/ or Allosteric Site/ or (Alloster* or PAM or PAMs or Modulat* or Agonis*).ti,ab,tw. #5. 3 and 4…. ” #1.4: Another potential issue that warrants attention is the use of genetically modified knockout animals. Some of the most compelling evidence we have for determining which muscarinic receptor subtypes mediate specific behavioral effects comes from studies that combine selective pharmacology tools in mice where the receptor has been deleted either globally or from specific populations of neurons. However, the current study design does not clearly outline how or if studies in these knockout animals will be evaluated. Our reply: Thank you for this point. We agree that genetically modified knockout animals can be important tools for delineating the potential receptor mechanisms of pharmacological interventions. We had already planned to compare muscarinic receptor agonists or PAMs with inactive control conditions in the context of genetic or pharmacological muscarinic receptor antagonism to determine if any observed differences result from muscarinic receptor activation, as it had been outlined in Table 1 and “Animal Population and Model Induction”. However, we agree that this was not clearly described, and we have therefore revised the methods accordingly. Changes in the manuscript : We revised the “Animal Population and Model Induction” section to better describe the inclusion of animal cohorts with genetic knockouts of muscarinic receptors or those receiving pharmacological muscarinic antagonists: “….Moreover, in the eligible studies, we will extract data from “naïve” animal cohorts (i.e., animals that have not undergone models of psychosis), and animal cohorts that have undergone both models of psychosis and muscarinic receptor antagonism via genetic (i.e, genetically modified animals with knockout of all or specific muscarinic receptors, either globally or in specific neuron populations) (6) or pharmacological manipulation (e.g., co-administration of selective or non-selective muscarinic receptor antagonists like scopolamine) (7) (see further details in “Comparison groups”)….” We expanded the “Comparison groups” to mention explicitly the comparison of muscarinic drugs versus inactive control conditions (e.g., vehicle) in animal models of psychosis in the context of muscarinic receptor antagonism: “… We will also compare muscarinic receptor agonists or PAMs with inactive control conditions in contexts of genetic or pharmacological muscarinic receptor antagonism (as described in “Animal population and model induction”) to determine if any observed differences result from muscarinic receptor activation. Separate analyses may be conducted for the antagonism of specific muscarinic receptor subtypes and/or within specific neuronal populations, if sufficient data are available..” #1.5: The use of a similar methodology by the authors previously to assess TARR1 agonists in non-human studies is a strength, and the team assembled is well-suited to carry out this study. Overall, this study protocol is thoughtfully written and addresses important and timely questions with the potential to unveil critical insights into the ability of compounds targeting muscarinic receptors to modulate schizophrenia-relevant behaviors across numerous symptom domains in preclinical studies. Our reply : Thank you once again for your overall endorsement and for the thoughtful comments that have substantially strengthened our protocol. In addition to the above-mentioned changes, we have also updated the “Study status” to reflect the changes during the revision: “…There were no changes from the original PROSPERO registration of the protocol, except for expanding the methods with additional details (also in response to the reviewer’s comments), (3,8) revising the search strategy to include terms for allosteric modulation as suggested by a reviewer, (8) adding physicochemical properties of the compounds in the “Exploration of Heterogeneity” per another reviewer’s comment, (3) and deciding not to search Scopus and CINAHL after consulting with the information specialist (which is not expected to affect the coverage of our search)….” References 1. Kenakin T. Know your molecule: pharmacological characterization of drug candidates to enhance efficacy and reduce late-stage attrition. Nature Reviews Drug Discovery. 2024:1-19. 2. Foster DJ, et al. Allosteric Modulation of GPCRs: New Insights and Potential Utility for Treatment of Schizophrenia and Other CNS Disorders. Neuron. 2017;94(3):431-46. 3. Messer W. Peer Review Report For: Muscarinic receptor agonists in animal models of psychosis: protocol for a systematic review and meta-analysis [version 1; peer review: 2 approved with reservations]. F1000Research 2024;13:1017. 4. Kenakin T. A Scale of Agonism and Allosteric Modulation for Assessment of Selectivity, Bias, and Receptor Mutation. Mol Pharmacol. 2017;92(4):414-24. 5. Smith S, et al . Psychosis-SOLES 2024 [Available from: https://camarades.shinyapps.io/psychosis-soles March 4, 2024. 6. Thomsen M, et al. Physiological roles of CNS muscarinic receptors gained from knockout mice. Neuropharmacology. 2018;136(Pt C):411-20. 7. Klinkenberg I, et al. The validity of scopolamine as a pharmacological model for cognitive impairment: a review of animal behavioral studies. Neurosci Biobehav Rev. 2010;34(8):1307-50. 8. Foster D. Peer Review Report For: Muscarinic receptor agonists in animal models of psychosis: protocol for a systematic review and meta-analysis [version 1; peer review: 2 approved with reservations]. F1000Research. 2024;13:1017. #1.1: The authors provide a study protocol to conduct a systematic review and meta-analyses to assess pharmacological targeting of muscarinic receptors in preclinical studies relevant to schizophrenia. This is an especially timely study that has the potential to summarize a vast preclinical literature and provide insights into the efficacy of targeting muscarinic receptors and possible sources of heterogeneity in these data sets that could arise due to drugs that have different selectivity for muscarinic receptor subtypes, or different modes of pharmacological activity. The choice of primary and secondary behaviors is well justified, and the exclusion of studies that only assess neurophysiological or histopathological measures is clearly stated. Our reply: We would like to thank the reviewer for recognizing the relevance of our planned work, for the overall endorsement of our methods, as well as for the constructive comments that further improved our methodology. Please find our point-by-point responses to the comments below. #1.2 One potential caveat of this study protocol is the use of the pharmacological term "agonist" throughout the protocol. In specific sentences, the authors acknowledge the potential role for allosteric modulators in mediating antipsychotic-like effects. For example, in the interventions section, the authors write: "We will include any pharmacological agent acting as an agonist or positive allosteric modulator at any of the five subtypes". They then state in the Exploration of Heterogeneity section that they will consider: "pharmacological characteristics (e.g., mode of action, selectivity for muscarinic or other receptors, potency, efficacy)". These statements are much appreciated, and these meta-analyses could provide important insights into how positive allosteric modulators and agonists differ in efficacy in preclinical studies across numerous symptom domains. Given the potential importance of understanding how allosteric modulators and agonists are similar or differ in their ability to modulate different preclinical assays relating to numerous schizophrenia symptom domains, it may be worth changing the title and clarifying the importance of this pharmacological distinction more clearly. Our reply: We would like to thank the reviewer for raising this important point. We had already planned to examine both orthosteric receptor agonists and positive allosteric modulators, as well as their differences, which we had highlighted in several parts of the manuscript. However, for simplicity, we had generally used the term 'agonism' throughout the protocol. We agree with the reviewer on the importance of this distinction, and we have clarified this in response to the reviewer’s comments. Changes in the manuscript : We have revised the title to include 'positive allosteric modulation': “ Muscarinic receptor agonists and positive allosteric modulators in animal models of psychosis: protocol for a systematic review and meta-analysis .” We have incorporated 'positive allosteric modulation' more frequently throughout the manuscript to emphasize this distinction. We have clarified its significance further in the introduction: “…., and the potential differences between orthosteric agonists and PAMs. For example, PAMs modulate receptor activity by binding to a site distinct from the natural ligand, offering theoretical advantages such as increased selectivity and safety over orthosteric agonists. (1,2) ”. In relationship to the comments of another reviewer,(3) we have also expanded the “Exploration of heterogeneity” section by providing more details in the pharmacological properties considered for orthosteric agonists and positive allosteric modulators: “ We will examine the pharmacological properties of muscarinic receptor agonists, considering mode of action (e.g., orthosteric agonism, positive allosteric modulation) and other key characteristics as sources of heterogeneity, using data primarily from established databases (e.g., IUPHAR/BPS) 43 and original publications that characterize these compounds. Specifically, we will assess potency (half-maximal effective concentration, EC50) and efficacy (maximal response, distinguishing between full and partial agonism) for orthosteric agonists, and modulation of acetylcholine potency and efficacy (cooperative factors α and β), intrinsic efficacy (τ B ), and affinity for the allosteric site (K B ) for PAMs. (1,4) These properties will be examined across various muscarinic receptor subtypes, with a preference for human receptors while considering potential cross-species differences, and across downstream signaling pathways (e.g., via Gα s , Gα q , Gα i/o subunits, β -arrestin). Given the variability across assays and experimental settings, we will consider calculating a common standardized index, if possible, such as estimating differences in log((maximal response)/EC50) between the examined drugs and the natural ligand acetylcholine. (4) This approach may enable comparisons across compounds, receptor and signaling pathway selectivity, but summarizing the different properties into a single index may result in information loss, necessitating additional analyses. Moreover, the exact procedure cannot be predetermined due to anticipated heterogeneity in the data across the different compounds examined.” #1.3 The agonist vs allosteric modulator issue is also evident in the search terms included in the extended data where only "agonist" is used and "allosteric modulator" is absent. In these searches, numerous allosteric modulators are included by name. However, this approach has the potential to miss any allosteric modulators not included by name in the search terms. The importance of studying potential discrepancies between agonist and allosteric modulators is highlighted by ongoing clinical trials for both types of compounds, with allosteric modulators currently being investigated in the clinic by AbbieVie, Neumora, and Neurosterix, and muscarinic agonist therapy having been approved for Karuna/Bristol Myers Squibb and under clinical investigation by several other companies including Neurocrine, Anavex, and Maplight. Our reply: We would like to thank the reviewer for highlighting this potential caveat in our search strategy. In collaboration with Dr. Farhad Shokraneh, an experienced information specialist (see Acknowledgments in the manuscript), we have revised the search strategy across multiple electronic databases to include terms relevant to allosteric modulation, ensuring we capture any studies on this category of medications. As it was already noted in the methods section, we will also supplement our searches using the psychosis-SOLES,(5)a dedicated database of preclinical psychosis studies, allowing us to conduct broader searches without restricting terms to “agonism” or “allosteric modulation”. These methods will enhance our search coverage and reduce the risk of missing relevant studies on positive allosteric modulators. Changes in the manuscript : We have revised the methods to clarify that the search strategies will encompass both agonism and allosteric modulation: 'For muscarinic agents, we will use broad terms like muscarinic agonists or allosteric modulators and…' Additionally, we have updated the draft search strategy in MEDLINE via Ovid within the extended data to include terms for “allosteric modulation”. See the revised extended data( https://doi.org/10.5281/zenodo.14534308 ): “...  #3. Muscarinic Agonists/ or Muscarine/ or (Muscarin or Muscarine or Muscarinic or M1 or M2 or M3 or M4 or M5 or Muscarinomimetic*).ti,ab,tw. #4. Allosteric Regulation/ or Allosteric Site/ or (Alloster* or PAM or PAMs or Modulat* or Agonis*).ti,ab,tw. #5. 3 and 4…. ” #1.4: Another potential issue that warrants attention is the use of genetically modified knockout animals. Some of the most compelling evidence we have for determining which muscarinic receptor subtypes mediate specific behavioral effects comes from studies that combine selective pharmacology tools in mice where the receptor has been deleted either globally or from specific populations of neurons. However, the current study design does not clearly outline how or if studies in these knockout animals will be evaluated. Our reply: Thank you for this point. We agree that genetically modified knockout animals can be important tools for delineating the potential receptor mechanisms of pharmacological interventions. We had already planned to compare muscarinic receptor agonists or PAMs with inactive control conditions in the context of genetic or pharmacological muscarinic receptor antagonism to determine if any observed differences result from muscarinic receptor activation, as it had been outlined in Table 1 and “Animal Population and Model Induction”. However, we agree that this was not clearly described, and we have therefore revised the methods accordingly. Changes in the manuscript : We revised the “Animal Population and Model Induction” section to better describe the inclusion of animal cohorts with genetic knockouts of muscarinic receptors or those receiving pharmacological muscarinic antagonists: “….Moreover, in the eligible studies, we will extract data from “naïve” animal cohorts (i.e., animals that have not undergone models of psychosis), and animal cohorts that have undergone both models of psychosis and muscarinic receptor antagonism via genetic (i.e, genetically modified animals with knockout of all or specific muscarinic receptors, either globally or in specific neuron populations) (6) or pharmacological manipulation (e.g., co-administration of selective or non-selective muscarinic receptor antagonists like scopolamine) (7) (see further details in “Comparison groups”)….” We expanded the “Comparison groups” to mention explicitly the comparison of muscarinic drugs versus inactive control conditions (e.g., vehicle) in animal models of psychosis in the context of muscarinic receptor antagonism: “… We will also compare muscarinic receptor agonists or PAMs with inactive control conditions in contexts of genetic or pharmacological muscarinic receptor antagonism (as described in “Animal population and model induction”) to determine if any observed differences result from muscarinic receptor activation. Separate analyses may be conducted for the antagonism of specific muscarinic receptor subtypes and/or within specific neuronal populations, if sufficient data are available..” #1.5: The use of a similar methodology by the authors previously to assess TARR1 agonists in non-human studies is a strength, and the team assembled is well-suited to carry out this study. Overall, this study protocol is thoughtfully written and addresses important and timely questions with the potential to unveil critical insights into the ability of compounds targeting muscarinic receptors to modulate schizophrenia-relevant behaviors across numerous symptom domains in preclinical studies. Our reply : Thank you once again for your overall endorsement and for the thoughtful comments that have substantially strengthened our protocol. In addition to the above-mentioned changes, we have also updated the “Study status” to reflect the changes during the revision: “…There were no changes from the original PROSPERO registration of the protocol, except for expanding the methods with additional details (also in response to the reviewer’s comments), (3,8) revising the search strategy to include terms for allosteric modulation as suggested by a reviewer, (8) adding physicochemical properties of the compounds in the “Exploration of Heterogeneity” per another reviewer’s comment, (3) and deciding not to search Scopus and CINAHL after consulting with the information specialist (which is not expected to affect the coverage of our search)….” References 1. Kenakin T. Know your molecule: pharmacological characterization of drug candidates to enhance efficacy and reduce late-stage attrition. Nature Reviews Drug Discovery. 2024:1-19. 2. Foster DJ, et al. Allosteric Modulation of GPCRs: New Insights and Potential Utility for Treatment of Schizophrenia and Other CNS Disorders. Neuron. 2017;94(3):431-46. 3. Messer W. Peer Review Report For: Muscarinic receptor agonists in animal models of psychosis: protocol for a systematic review and meta-analysis [version 1; peer review: 2 approved with reservations]. F1000Research 2024;13:1017. 4. Kenakin T. A Scale of Agonism and Allosteric Modulation for Assessment of Selectivity, Bias, and Receptor Mutation. Mol Pharmacol. 2017;92(4):414-24. 5. Smith S, et al . Psychosis-SOLES 2024 [Available from: https://camarades.shinyapps.io/psychosis-soles March 4, 2024. 6. Thomsen M, et al. Physiological roles of CNS muscarinic receptors gained from knockout mice. Neuropharmacology. 2018;136(Pt C):411-20. 7. Klinkenberg I, et al. The validity of scopolamine as a pharmacological model for cognitive impairment: a review of animal behavioral studies. Neurosci Biobehav Rev. 2010;34(8):1307-50. 8. Foster D. Peer Review Report For: Muscarinic receptor agonists in animal models of psychosis: protocol for a systematic review and meta-analysis [version 1; peer review: 2 approved with reservations]. F1000Research. 2024;13:1017. Competing Interests: Spyridon Siafis: None. Nobuyuki Nomura: N.N. has received manuscript fees from Sumitomo Pharma. Johannes Schneider-Thoma: None. Irene Bighelli: None. Alexandra Bannach-Brown: None. Fiona J. Ramage: None. Francesca Tinsdeall: None. Ioannis Mantas: None. Sameer Jauhar: SJ has received honoraria for educational talks given for Boehringer Ingelheim, Lundbeck, Janssen, and Sunovion, and has advised on antipsychotics to LB Pharmaceuticals. Sridhar Natesan: None. Anthony Vernon: ACV has received research support from UCB S.A and Bit.Bio (https://www.bit.bio/) and has received honoraria for seminars at GlaxoSmithKline. Andrea de Bartolomeis: AdB has received research support from Janssen, Lundbeck, and Otsuka and lecture fees for educational meeting from Chiesi, Lundbeck, Roche, Sunovion, Vitria, Recordati, Angelini and Takeda; he has served on advisory boards for Eli Lilly, Jansen, Lundbeck, Otsuka, Roche, and Takeda, Chiesi, Recordati, Angelini, Vitria. Sabine M. Hölter: None. Natascha I. Drude: None. Ulf Tölch: None. Wulf-Peter Hansen: None. Virginia Chiocchia: None. Oliver Howes: ODH has received investigator-initiated research funding from and/or participated in advisory/speaker meetings organised by Angellini, Autifony, Biogen, Boehringer-Ingelheim, Eli Lilly, Elysium, Heptares, Global Medical Education, Invicro, Jansenn, Karuna, Lundbeck, Merck, Neurocrine, Ontrack/ Pangea, Otsuka, Sunovion, Recordati, Roche, Rovi and Viatris/ Mylan. He was previously a part-time employee of Lundbeck A/v. Dr Howes has a patent for the use of dopaminergic imaging. Josef Priller: None. Georgia Salanti: None. Malcolm R. Macleod: None. Stefan Leucht: SL has received received honoraria for advising/consulting and/or for lectures and/or for educational material from Angelini, Boehringer Ingelheim, Eisai, Ekademia, GedeonRichter, Janssen, Karuna, Kynexis, Lundbeck, Medichem, Medscape, Mitsubishi, Otsuka, NovoNordisk, Recordati, Rovi, Teva. Close Report a concern COMMENT ON THIS REPORT Comments on this article Comments (0) Version 2 VERSION 2 PUBLISHED 06 Sep 2024 ADD YOUR COMMENT Comment keyboard_arrow_left keyboard_arrow_right Open Peer Review Reviewer Status info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Reviewer Reports Invited Reviewers 1 2 3 Version 2 (revision) 02 Jan 25 read Version 1 06 Sep 24 read read Daniel Foster , University of South Carolina School of Medicine, Columbia, USA William Messer , University of Toledo, Toledo, OH, USA Xiaonan Guo , Zhejiang University, Hangzhou, China Comments on this article All Comments (0) Add a comment Sign up for content alerts Sign Up You are now signed up to receive this alert Browse by related subjects keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2025 Guo X. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 21 Jan 2025 | for Version 2 Xiaonan Guo , Zhejiang University, Hangzhou, Zhejiang, China 0 Views copyright © 2025 Guo X. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Approved info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions This paper is a comprehensive protocol studying muscarinic receptor agonists and positive allosteric modulators in animal models of psychosis. Generally, I think it will promote the clinical use and biological insight of the muscarinic receptor agonists and positive allosteric modulators in treating schizophrenia. The method is so perfect that no obvious limitations can be found. I only provide the minor suggestion to improve the article, which the authors could consider. Since psychosis is strongly associated with dopamine function, it's better to introduce the influence of dopamine function when treating animal models of psychosis with muscarinic receptor agonists and positive allosteric modulators. Linking the muscarinic function with dopamine function will shed light on clinical translation of muscarinic agonist. Is the rationale for, and objectives of, the study clearly described? Yes Is the study design appropriate for the research question? Yes Are sufficient details of the methods provided to allow replication by others? Yes Are the datasets clearly presented in a useable and accessible format? Yes Competing Interests No competing interests were disclosed. Reviewer Expertise Brain, metabolic, and genetic mechanism in psychiatric disorders (especially in BD). I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. reply Respond to this report Responses (0) Guo X. Peer Review Report For: Muscarinic receptor agonists and positive allosteric modulators in animal models of psychosis: protocol for a systematic review and meta-analysis [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 13 :1017 ( https://doi.org/10.5256/f1000research.176234.r357863) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/13-1017/v2#referee-response-357863 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2024 Messer W. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 24 Oct 2024 | for Version 1 William Messer , Department of Medicinal and Biological Chemistry, College of Pharmacy and Pharmaceutical Sciences, Department of Pharmacology and Experimental Therapeutics,, University of Toledo, Toledo, OH, USA 0 Views copyright © 2024 Messer W. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (1) Approved With Reservations info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions The article outlines a protocol for a specific systematic review and meta-analysis examining the impact of muscarinic agonists (and allosteric modulators) in animal models of psychosis. As such, it is more a research proposal than a paper describing results. The authors indicate that D 2 dopamine antagonists have been the cornerstone for schizophrenia therapy for the last 70 years, although atypical antipsychotics target other receptors, including 5-HT 2 receptors. Such compounds, including clozapine and olanzapine, are linked to a different set of adverse effects than classical dopamine antagonists including hypoglycemia and weight gain. Nevertheless, the topic is timely given the recent approval of xanomeline, in combination with trospium, for the treatment of schizophrenia. A systematic review and a meta-analysis are proposed for examining the impact of muscarinic agonists and allosteric modulators in animal models of psychosis. The level of complexity is high with respect to the varying types of compounds (agonists vs. partial agonists, receptor subtype selectivity, binding affinity, etc.), which will make it difficult to accurately categorize compounds. For example, positive allosteric modulators often exhibit a range of effects that include modulation of acetylcholine potency and efficacy in addition to allosteric agonist activity. The degree to which such activities have been adequately assessed will likely vary from lab to lab and such data may not be readily available in the papers that address in vivo efficacy in animal models of psychosis. These concerns are addressed to some extent in the “Exploration of heterogeneity” section, but a more explicit discussion of how concepts of potency and efficacy, for example, will be handled is warranted. In addition to the sources of heterogeneity discussed, the physicochemical properties of compounds may impact the effectiveness of treatments; consideration of ADME properties of compounds could provide an important perspective. For example, multiparameter optimization values could help explain variability in responses for compounds with similar receptor activity profiles. Beyond the pharmacological properties of the compounds under investigation, the impact of muscarinic receptor activation might vary significantly depending on the different compounds utilized to induce behavioral changes (e.g., NMDA antagonists vs. dopamine agonists) or the behavioral readouts (e.g., pre-pulse inhibition of startle response vs. apomorphine induced climbing). The authors refer to some of the inherent difficulties in the “Assessment of indirectness of animal experiments” section, including concerns about the applicability of various animal models to clinical utility. In this sense, it might be helpful to examine the consistency of comparator compounds (e.g., D 2 and 5-HT 2 antagonists) that are used clinically in treatment of schizophrenia, and are often used as control compounds in studies of muscarinic agonists and other potential therapeutic compounds. This is perhaps alluded to in the “Data synthesis/planned comparisons” section, although additional details would be helpful. An additional consideration is the presence or absence of adverse effects for the compounds under investigation. The clinical utility of muscarinic agonists has been limited by adverse effect profiles, which vary from compound to compound, but likely include both off-target (e.g., M 3 receptor-mediated) and on-target (i.e., M 1 or M 4 receptor-mediated) effects. Adverse effects such as salivation, lacrimation, diarrhea, or convulsions would provide important information regarding the in vivo pharmacological profile of compounds and the separation between beneficial and undesirable effects (i.e., the therapeutic window). Overall, the topic is of timely interest and worth pursuing with some additional attention to the details to be evaluated. Is the rationale for, and objectives of, the study clearly described? Yes Is the study design appropriate for the research question? Yes Are sufficient details of the methods provided to allow replication by others? Partly Are the datasets clearly presented in a useable and accessible format? Not applicable Competing Interests I am an inventor on patents related to the use of muscarinic agonists and allosteric modulators for the treatment of neuropsychiatric disorders. I am also the founder and owner of Psyneurgy Pharmaceuticals LLC, a company focused on the development of treatments for neuropsychiatric disorders. Reviewer Expertise My research focuses on the design and development of selective agonists and allosteric modulators of muscarinic receptors with potential utility in the treatment of neuropsychiatric disorders. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. reply Respond to this report Responses (1) Author Response 02 Jan 2025 Spyridon Siafis, Technical University of Munich, School of Medicine and Health, Department of Psychiatry and Psychotherapy, Munich, Germany #2.1: The article outlines a protocol for a specific systematic review and meta-analysis examining the impact of muscarinic agonists (and allosteric modulators) in animal models of psychosis. As such, it is more a research proposal than a paper describing results. Our reply: We would like to thank the reviewer for their constructive comments on our protocol, which have helped improve the clarity of the methods. This manuscript indeed corresponds to a protocol for a systematic review, and the results of the completed review will be published in a peer-reviewed journal, as outlined in the “Dissemination of information” section. Please find our point-by-point responses to the comments below. #2.2: The authors indicate that D 2 dopamine antagonists have been the cornerstone for schizophrenia therapy for the last 70 years, although atypical antipsychotics target other receptors, including 5-HT 2 receptors. Such compounds, including clozapine and olanzapine, are linked to a different set of adverse effects than classical dopamine antagonists including hypoglycemia and weight gain. Nevertheless, the topic is timely given the recent approval of xanomeline, in combination with trospium, for the treatment of schizophrenia. Our reply: We agree with this point that although the primary mechanism of action for antipsychotics has historically been the blockade of dopamine D2 receptors, these drugs also interact with other neurotransmitter receptors, with adverse events often linked to their receptor-binding profiles. Accordingly, we have revised the introduction to incorporate this information and have also noted the recent approval of xanomeline-trospium, which had not been approved at the time of the initial manuscript submission. Changes in the manuscript : We revised the introduction to mention the association of adverse events of antipsychotics with their receptor-binding profiles and off-target actions on other neurotransmitter receptors, as well as the approval of xanomeline-trospium for schizophrenia by the US FDA: “Antipsychotic drugs that block the dopamine D2 receptor (D2R) have been the cornerstone of pharmacological treatment for schizophrenia for over 70 years. 1 – 3 …..Moreover, the risk-to-benefit ratio of antipsychotics is often challenged by their multiple side-effects associated with their receptor-binding profiles and frequently linked to off-target actions beyond D2R blockade. 1 , 2 …… Xanomeline, a muscarinic M1/M4-preferring receptor agonist, has demonstrated improvements in symptoms of schizophrenia in early and late-stage randomized placebo-controlled controlled trials with medium-to-large effect sizes, with potential cholinergic adverse events mitigated by its combination with trospium, a peripheral muscarinic antagonist. 10 – 13 In September 2024, the U.S. Food and Drug Administration approved xanomeline combined with trospium for schizophrenia, marking it as the first antipsychotic targeting muscarinic receptors. (1) “ #2.3: A systematic review and a meta-analysis are proposed for examining the impact of muscarinic agonists and allosteric modulators in animal models of psychosis. The level of complexity is high with respect to the varying types of compounds (agonists vs. partial agonists, receptor subtype selectivity, binding affinity, etc.), which will make it difficult to accurately categorize compounds. For example, positive allosteric modulators often exhibit a range of effects that include modulation of acetylcholine potency and efficacy in addition to allosteric agonist activity. The degree to which such activities have been adequately assessed will likely vary from lab to lab and such data may not be readily available in the papers that address in vivo efficacy in animal models of psychosis. These concerns are addressed to some extent in the “Exploration of heterogeneity” section, but a more explicit discussion of how concepts of potency and efficacy, for example, will be handled is warranted. Our reply: We would like to thank the reviewer for this insightful comment. We have now expanded the “Exploration of heterogeneity” section to elaborate on how these pharmacological properties will be examined, taking into account different modes of action and efforts to calculate indices that minimize potential variability and heterogeneity in measuring these properties (e.g., if possible, differences in the log((maximal efficacy/EC50)).(2) We will aim to use reliable sources for obtaining information about these properties (e.g., IUPHAR/BPS database)(3); however, we will not conduct a systematic review of studies to synthesize them, and we have noted this limitation in the “Discussion” section. Changes in the manuscript : We expanded the methods in the “Exploration of heterogeneity” accordingly: We will examine the pharmacological properties of muscarinic receptor agonists, considering mode of action (e.g., orthosteric agonism, positive allosteric modulation) and other key characteristics as sources of heterogeneity, using data primarily from established databases (e.g., IUPHAR/BPS) 43 and original publications that characterize these compounds. Specifically, we will assess potency (half-maximal effective concentration, EC50) and efficacy (maximal response, distinguishing between full and partial agonism) for orthosteric agonists, and modulation of acetylcholine potency and efficacy (cooperative factors α and β), intrinsic efficacy (τ B ), and affinity for the allosteric site (K B ) for PAMs. (2,4) These properties will be examined across various muscarinic receptor subtypes, with a preference for human receptors while considering potential cross-species differences, and across downstream signaling pathways (e.g., via Gα s , Gα q , Gα i/o subunits, β -arrestin). Given the variability across assays and experimental settings, we will consider calculating a common standardized index, if possible, such as estimating differences in log((maximal response)/EC50) between the examined drugs and the natural ligand acetylcholine. (2) This approach may enable comparisons across compounds, receptor and signaling pathway selectivity, but summarizing the different properties into a single index may result in information loss, necessitating additional analyses . Moreover, the exact procedure cannot be predetermined due to anticipated heterogeneity in the data across the different compounds examined . Additionally, we will assess off-target actions by evaluating the mode of action and affinity of each compound toward other neurotransmitter receptors .” We added to the limitations that a systematic review of in vitro assays and pharmacokinetic studies will not be conducted: “… Additionally, we will explore whether heterogeneity in behavioral effects may be explained by differences in drug interactions with muscarinic receptors. Given the limited availability and application of in vivo readouts for muscarinic agonism, we will use in vitro data. We will not conduct a systematic review of in vitro assays and pharmacokinetic studies to synthesize information about the pharmacological properties of the drugs, but instead will aim to use reliable sources and standardized methods to assess these as sources of heterogeneity (see “Exploration of heterogeneity”)…” #2.4: In addition to the sources of heterogeneity discussed, the physicochemical properties of compounds may impact the effectiveness of treatments; consideration of ADME properties of compounds could provide an important perspective. For example, multiparameter optimization values could help explain variability in responses for compounds with similar receptor activity profiles. Our reply: Thank you for raising this important point. Similarly to the above, we expanded the “Exploration of heterogeneity” section to include physicochemical parameters and their integration with the Central Nervous System Multiparameter Optimization Desirability approach. (5,6) Changes in the manuscript : We expanded accordingly the “Exploration of heterogeneity” section: “… We will explore potential sources of heterogeneity for …. type of muscarinic receptor agonists or PAMs, their pharmacological and physiochemical properties, and dose (details below), … We will use the Central Nervous System Multiparameter Optimization Desirability algorithm (5,6) to examine the physicochemical properties of the drugs as source of heterogeneity. This algorithm calculates a composite desirability score based on six key properties, i.e., lipophilicity, distribution coefficient, molecular weight, topological polar surface area, number of hydrogen bond donors, and the most basic center, which aligns well with the pharmacokinetic attributes, blood-brain barrier permeability and safety . (5,6) Values for these properties will be estimated based on the chemical structure information using OPEn structure–activity/property Relationship App (OPERA) version 2.9.1 (a freely available, open-source provided distributed under MIT license ) . (7) ” #2.5: Beyond the pharmacological properties of the compounds under investigation, the impact of muscarinic receptor activation might vary significantly depending on the different compounds utilized to induce behavioral changes (e.g., NMDA antagonists vs. dopamine agonists) or the behavioral readouts (e.g., pre-pulse inhibition of startle response vs. apomorphine induced climbing). The authors refer to some of the inherent difficulties in the “Assessment of indirectness of animal experiments” section, including concerns about the applicability of various animal models to clinical utility. In this sense, it might be helpful to examine the consistency of comparator compounds (e.g., D 2 and 5-HT 2 antagonists) that are used clinically in treatment of schizophrenia, and are often used as control compounds in studies of muscarinic agonists and other potential therapeutic compounds. This is perhaps alluded to in the “Data synthesis/planned comparisons” section, although additional details would be helpful. Our reply: We agree with this point, and we have added a comparison of D2R-blocking antipsychotics with inactive control conditions (e.g., vehicle) to examine the consistency of their effects in the included experiments and to inform the “Assessment of indirectness of animal experiments”. This is now described in the “Comparison groups” Changes in the manuscript : We added this comparison in the “Comparison groups”: “Table 1 outlines the planned comparisons, …. Additionally, we will examine the comparison between active and inactive control conditions to provide insights into the consistency of the effects of D2R-blocking antipsychotic in the included experiments and to inform the assessment of indirectness (see “Assessment of indirectness of the animal experiments”).” #2.6: An additional consideration is the presence or absence of adverse effects for the compounds under investigation. The clinical utility of muscarinic agonists has been limited by adverse effect profiles, which vary from compound to compound, but likely include both off-target (e.g., M 3 receptor-mediated) and on-target (i.e., M 1 or M 4 receptor-mediated) effects. Adverse effects such as salivation, lacrimation, diarrhea, or convulsions would provide important information regarding the in vivo pharmacological profile of compounds and the separation between beneficial and undesirable effects (i.e., the therapeutic window). Our reply: Thank you for this point. We agree that examining adverse events is important for assessing the risk-to-benefit ratio of these drugs. However, we had chosen already from the start of our protocol to focus on behavioural outcomes and not include adverse events due to their sparse and inconsistent reporting in studies of animal models of psychosis (as also noted in our previous review on TAAR1 agonists)(8) and their examination in other study designs excluded from our review (e.g., using naïve animals not subjected to models of psychosis). Furthermore, cholinergic adverse events may potentially be mitigated in clinical settings through the combination of peripheral antagonists, as seen with xanomeline-trospium.(9)Nonetheless, we will aim to extract adverse event data if found in the included studies and consider secondary publications where relevant. These considerations are addressed in the “Discussion” section under limitations. Changes in the manuscript: We expanded the limitations in the “Discussion” section to include consideration of cholinergic adverse events, similar to the previously reported neurobiological measures: “We will not analyse neurobiological measures due to their heterogeneous use across studies and the lack of an established biomarker in schizophrenia, 6 .. Similarly, we will not examine cholinergic adverse events in animals, such as salivation, lacrimation and diarrhea, which may offer insights into the risk-benefit profile but could be mitigated in clinical settings with peripheral muscarinic receptor antagonists, as shown with the xanomeline-trospium combination. 10 – 13 We will aim to extract and potentially analyse these measures in secondary publications .” #2.7: Overall, the topic is of timely interest and worth pursuing with some additional attention to the details to be evaluated. Our reply: Thank you once again for your overall endorsement and for the thoughtful comments that have substantially strengthened our protocol. In addition to the above-mentioned changes, we have also updated the “Study status” to reflect the changes during the revision: “…There were no changes from the original PROSPERO registration of the protocol, except for expanding the methods with additional details (also in response to the reviewer’s comments), (10,11) revising the search strategy to include terms for allosteric modulation as suggested by a reviewer, (10) adding physicochemical properties of the compounds in the “Exploration of Heterogeneity” per another reviewer’s comment, (11) and deciding not to search Scopus and CINAHL after consulting with the information specialist (which is not expected to affect the coverage of our search)….” References 1.U.S. Food and Drug Administration. FDA Approves Drug with New Mechanism of Action for Treatment of Schizophrenia 2024 [Available from: https://www.fda.gov/news-events/press-announcements/fda-approves-drug-new-mechanism-action-treatment-schizophrenia . 2. Kenakin T. A Scale of Agonism and Allosteric Modulation for Assessment of Selectivity, Bias, and Receptor Mutation. Mol Pharmacol. 2017;92(4):414-24. 3. Harding SD, et al. The IUPHAR/BPS guide to PHARMACOLOGY in 2022: curating pharmacology for COVID-19, malaria and antibacterials. Nucleic Acids Res. 2022;50(D1):D1282-d94. 4. Kenakin T. Know your molecule: pharmacological characterization of drug candidates to enhance efficacy and reduce late-stage attrition. Nature Reviews Drug Discovery. 2024:1-19. 5. Wager TT, et al. Moving beyond rules: the development of a central nervous system multiparameter optimization (CNS MPO) approach to enable alignment of druglike properties. ACS Chem Neurosci. 2010;1(6):435-49. 6. Wager TT, et al. Central Nervous System Multiparameter Optimization Desirability: Application in Drug Discovery. ACS Chem Neurosci. 2016;7(6):767-75. 7. Mansouri K, et al. OPERA models for predicting physicochemical properties and environmental fate endpoints. Journal of Cheminformatics. 2018;10(1):10. 8. Siafis S, et al. Trace amine-associated receptor 1 (TAAR1) agonism for psychosis: a living systematic review and meta-analysis of human and non-human data. Wellcome Open Research. 2024;9. 9. Paul SM, et al. Muscarinic Acetylcholine Receptor Agonists as Novel Treatments for Schizophrenia. Am J Psychiatry. 2022;179(9):611-27. 10. Foster D. Peer Review Report For: Muscarinic receptor agonists in animal models of psychosis: protocol for a systematic review and meta-analysis [version 1; peer review: 2 approved with reservations]. F1000Research. 2024;13:1017. 11. Messer W. Peer Review Report For: Muscarinic receptor agonists in animal models of psychosis: protocol for a systematic review and meta-analysis [version 1; peer review: 2 approved with reservations]. F1000Research 2024;13:1017. View more View less Competing Interests Spyridon Siafis: None. Nobuyuki Nomura: N.N. has received manuscript fees from Sumitomo Pharma. Johannes Schneider-Thoma: None. Irene Bighelli: None. Alexandra Bannach-Brown: None. Fiona J. Ramage: None. Francesca Tinsdeall: None. Ioannis Mantas: None. Sameer Jauhar: SJ has received honoraria for educational talks given for Boehringer Ingelheim, Lundbeck, Janssen, and Sunovion, and has advised on antipsychotics to LB Pharmaceuticals. Sridhar Natesan: None. Anthony Vernon: ACV has received research support from UCB S.A and Bit.Bio (https://www.bit.bio/) and has received honoraria for seminars at GlaxoSmithKline. Andrea de Bartolomeis: AdB has received research support from Janssen, Lundbeck, and Otsuka and lecture fees for educational meeting from Chiesi, Lundbeck, Roche, Sunovion, Vitria, Recordati, Angelini and Takeda; he has served on advisory boards for Eli Lilly, Jansen, Lundbeck, Otsuka, Roche, and Takeda, Chiesi, Recordati, Angelini, Vitria. Sabine M. Hölter: None. Natascha I. Drude: None. Ulf Tölch: None. Wulf-Peter Hansen: None. Virginia Chiocchia: None. Oliver Howes: ODH has received investigator-initiated research funding from and/or participated in advisory/speaker meetings organised by Angellini, Autifony, Biogen, Boehringer-Ingelheim, Eli Lilly, Elysium, Heptares, Global Medical Education, Invicro, Jansenn, Karuna, Lundbeck, Merck, Neurocrine, Ontrack/ Pangea, Otsuka, Sunovion, Recordati, Roche, Rovi and Viatris/ Mylan. He was previously a part-time employee of Lundbeck A/v. Dr Howes has a patent for the use of dopaminergic imaging. Josef Priller: None. Georgia Salanti: None. Malcolm R. Macleod: None. Stefan Leucht: SL has received received honoraria for advising/consulting and/or for lectures and/or for educational material from Angelini, Boehringer Ingelheim, Eisai, Ekademia, GedeonRichter, Janssen, Karuna, Kynexis, Lundbeck, Medichem, Medscape, Mitsubishi, Otsuka, NovoNordisk, Recordati, Rovi, Teva. reply Respond Report a concern Messer W. Peer Review Report For: Muscarinic receptor agonists and positive allosteric modulators in animal models of psychosis: protocol for a systematic review and meta-analysis [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 13 :1017 ( https://doi.org/10.5256/f1000research.170522.r325671) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/13-1017/v1#referee-response-325671 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2024 Foster D. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 11 Oct 2024 | for Version 1 Daniel Foster , Department of Pharmacology, Physiology and Neuroscience, University of South Carolina School of Medicine, Columbia, USA 0 Views copyright © 2024 Foster D. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (1) Approved With Reservations info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions The authors provide a study protocol to conduct a systematic review and meta-analyses to assess pharmacological targeting of muscarinic receptors in preclinical studies relevant to schizophrenia. This is an especially timely study that has the potential to summarize a vast preclinical literature and provide insights into the efficacy of targeting muscarinic receptors and possible sources of heterogeneity in these data sets that could arise due to drugs that have different selectivity for muscarinic receptor subtypes, or different modes of pharmacological activity. The choice of primary and secondary behaviors is well justified, and the exclusion of studies that only assess neurophysiological or histopathological measures is clearly stated. One potential caveat of this study protocol is the use of the pharmacological term "agonist" throughout the protocol. In specific sentences, the authors acknowledge the potential role for allosteric modulators in mediating antipsychotic-like effects. For example, in the interventions section, the authors write: "We will include any pharmacological agent acting as an agonist or positive allosteric modulator at any of the five subtypes". They then state in the Exploration of Heterogeneity section that they will consider: "pharmacological characteristics (e.g., mode of action, selectivity for muscarinic or other receptors, potency, efficacy)". These statements are much appreciated, and these meta-analyses could provide important insights into how positive allosteric modulators and agonists differ in efficacy in preclinical studies across numerous symptom domains. Given the potential importance of understanding how allosteric modulators and agonists are similar or differ in their ability to modulate different preclinical assays relating to numerous schizophrenia symptom domains, it may be worth changing the title and clarifying the importance of this pharmacological distinction more clearly. The agonist vs allosteric modulator issue is also evident in the search terms included in the extended data where only "agonist" is used and "allosteric modulator" is absent. In these searches, numerous allosteric modulators are included by name. However, this approach has the potential to miss any allosteric modulators not included by name in the search terms. The importance of studying potential discrepancies between agonist and allosteric modulators is highlighted by ongoing clinical trials for both types of compounds, with allosteric modulators currently being investigated in the clinic by AbbieVie, Neumora, and Neurosterix, and muscarinic agonist therapy having been approved for Karuna/Bristol Myers Squibb and under clinical investigation by several other companies including Neurocrine, Anavex, and Maplight. Another potential issue that warrants attention is the use of genetically modified knockout animals. Some of the most compelling evidence we have for determining which muscarinic receptor subtypes mediate specific behavioral effects comes from studies that combine selective pharmacology tools in mice where the receptor has been deleted either globally or from specific populations of neurons. However, the current study design does not clearly outline how or if studies in these knockout animals will be evaluated. The use of a similar methodology by the authors previously to assess TARR1 agonists in non-human studies is a strength, and the team assembled is well-suited to carry out this study. Overall, this study protocol is thoughtfully written and addresses important and timely questions with the potential to unveil critical insights into the ability of compounds targeting muscarinic receptors to modulate schizophrenia-relevant behaviors across numerous symptom domains in preclinical studies. Is the rationale for, and objectives of, the study clearly described? Yes Is the study design appropriate for the research question? Yes Are sufficient details of the methods provided to allow replication by others? Yes Are the datasets clearly presented in a useable and accessible format? Not applicable Competing Interests No competing interests were disclosed. Reviewer Expertise I study muscarinic receptor modulation of preclinical physiology and behaviors relevant to schizophrenia. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. reply Respond to this report Responses (1) Author Response 02 Jan 2025 Spyridon Siafis, Technical University of Munich, School of Medicine and Health, Department of Psychiatry and Psychotherapy, Munich, Germany #1.1: The authors provide a study protocol to conduct a systematic review and meta-analyses to assess pharmacological targeting of muscarinic receptors in preclinical studies relevant to schizophrenia. This is an especially timely study that has the potential to summarize a vast preclinical literature and provide insights into the efficacy of targeting muscarinic receptors and possible sources of heterogeneity in these data sets that could arise due to drugs that have different selectivity for muscarinic receptor subtypes, or different modes of pharmacological activity. The choice of primary and secondary behaviors is well justified, and the exclusion of studies that only assess neurophysiological or histopathological measures is clearly stated. Our reply: We would like to thank the reviewer for recognizing the relevance of our planned work, for the overall endorsement of our methods, as well as for the constructive comments that further improved our methodology. Please find our point-by-point responses to the comments below. #1.2 One potential caveat of this study protocol is the use of the pharmacological term "agonist" throughout the protocol. In specific sentences, the authors acknowledge the potential role for allosteric modulators in mediating antipsychotic-like effects. For example, in the interventions section, the authors write: "We will include any pharmacological agent acting as an agonist or positive allosteric modulator at any of the five subtypes". They then state in the Exploration of Heterogeneity section that they will consider: "pharmacological characteristics (e.g., mode of action, selectivity for muscarinic or other receptors, potency, efficacy)". These statements are much appreciated, and these meta-analyses could provide important insights into how positive allosteric modulators and agonists differ in efficacy in preclinical studies across numerous symptom domains. Given the potential importance of understanding how allosteric modulators and agonists are similar or differ in their ability to modulate different preclinical assays relating to numerous schizophrenia symptom domains, it may be worth changing the title and clarifying the importance of this pharmacological distinction more clearly. Our reply: We would like to thank the reviewer for raising this important point. We had already planned to examine both orthosteric receptor agonists and positive allosteric modulators, as well as their differences, which we had highlighted in several parts of the manuscript. However, for simplicity, we had generally used the term 'agonism' throughout the protocol. We agree with the reviewer on the importance of this distinction, and we have clarified this in response to the reviewer’s comments. Changes in the manuscript : We have revised the title to include 'positive allosteric modulation': “ Muscarinic receptor agonists and positive allosteric modulators in animal models of psychosis: protocol for a systematic review and meta-analysis .” We have incorporated 'positive allosteric modulation' more frequently throughout the manuscript to emphasize this distinction. We have clarified its significance further in the introduction: “…., and the potential differences between orthosteric agonists and PAMs. For example, PAMs modulate receptor activity by binding to a site distinct from the natural ligand, offering theoretical advantages such as increased selectivity and safety over orthosteric agonists. (1,2) ”. In relationship to the comments of another reviewer,(3) we have also expanded the “Exploration of heterogeneity” section by providing more details in the pharmacological properties considered for orthosteric agonists and positive allosteric modulators: “ We will examine the pharmacological properties of muscarinic receptor agonists, considering mode of action (e.g., orthosteric agonism, positive allosteric modulation) and other key characteristics as sources of heterogeneity, using data primarily from established databases (e.g., IUPHAR/BPS) 43 and original publications that characterize these compounds. Specifically, we will assess potency (half-maximal effective concentration, EC50) and efficacy (maximal response, distinguishing between full and partial agonism) for orthosteric agonists, and modulation of acetylcholine potency and efficacy (cooperative factors α and β), intrinsic efficacy (τ B ), and affinity for the allosteric site (K B ) for PAMs. (1,4) These properties will be examined across various muscarinic receptor subtypes, with a preference for human receptors while considering potential cross-species differences, and across downstream signaling pathways (e.g., via Gα s , Gα q , Gα i/o subunits, β -arrestin). Given the variability across assays and experimental settings, we will consider calculating a common standardized index, if possible, such as estimating differences in log((maximal response)/EC50) between the examined drugs and the natural ligand acetylcholine. (4) This approach may enable comparisons across compounds, receptor and signaling pathway selectivity, but summarizing the different properties into a single index may result in information loss, necessitating additional analyses. Moreover, the exact procedure cannot be predetermined due to anticipated heterogeneity in the data across the different compounds examined.” #1.3 The agonist vs allosteric modulator issue is also evident in the search terms included in the extended data where only "agonist" is used and "allosteric modulator" is absent. In these searches, numerous allosteric modulators are included by name. However, this approach has the potential to miss any allosteric modulators not included by name in the search terms. The importance of studying potential discrepancies between agonist and allosteric modulators is highlighted by ongoing clinical trials for both types of compounds, with allosteric modulators currently being investigated in the clinic by AbbieVie, Neumora, and Neurosterix, and muscarinic agonist therapy having been approved for Karuna/Bristol Myers Squibb and under clinical investigation by several other companies including Neurocrine, Anavex, and Maplight. Our reply: We would like to thank the reviewer for highlighting this potential caveat in our search strategy. In collaboration with Dr. Farhad Shokraneh, an experienced information specialist (see Acknowledgments in the manuscript), we have revised the search strategy across multiple electronic databases to include terms relevant to allosteric modulation, ensuring we capture any studies on this category of medications. As it was already noted in the methods section, we will also supplement our searches using the psychosis-SOLES,(5)a dedicated database of preclinical psychosis studies, allowing us to conduct broader searches without restricting terms to “agonism” or “allosteric modulation”. These methods will enhance our search coverage and reduce the risk of missing relevant studies on positive allosteric modulators. Changes in the manuscript : We have revised the methods to clarify that the search strategies will encompass both agonism and allosteric modulation: 'For muscarinic agents, we will use broad terms like muscarinic agonists or allosteric modulators and…' Additionally, we have updated the draft search strategy in MEDLINE via Ovid within the extended data to include terms for “allosteric modulation”. See the revised extended data( https://doi.org/10.5281/zenodo.14534308 ): “...  #3. Muscarinic Agonists/ or Muscarine/ or (Muscarin or Muscarine or Muscarinic or M1 or M2 or M3 or M4 or M5 or Muscarinomimetic*).ti,ab,tw. #4. Allosteric Regulation/ or Allosteric Site/ or (Alloster* or PAM or PAMs or Modulat* or Agonis*).ti,ab,tw. #5. 3 and 4…. ” #1.4: Another potential issue that warrants attention is the use of genetically modified knockout animals. Some of the most compelling evidence we have for determining which muscarinic receptor subtypes mediate specific behavioral effects comes from studies that combine selective pharmacology tools in mice where the receptor has been deleted either globally or from specific populations of neurons. However, the current study design does not clearly outline how or if studies in these knockout animals will be evaluated. Our reply: Thank you for this point. We agree that genetically modified knockout animals can be important tools for delineating the potential receptor mechanisms of pharmacological interventions. We had already planned to compare muscarinic receptor agonists or PAMs with inactive control conditions in the context of genetic or pharmacological muscarinic receptor antagonism to determine if any observed differences result from muscarinic receptor activation, as it had been outlined in Table 1 and “Animal Population and Model Induction”. However, we agree that this was not clearly described, and we have therefore revised the methods accordingly. Changes in the manuscript : We revised the “Animal Population and Model Induction” section to better describe the inclusion of animal cohorts with genetic knockouts of muscarinic receptors or those receiving pharmacological muscarinic antagonists: “….Moreover, in the eligible studies, we will extract data from “naïve” animal cohorts (i.e., animals that have not undergone models of psychosis), and animal cohorts that have undergone both models of psychosis and muscarinic receptor antagonism via genetic (i.e, genetically modified animals with knockout of all or specific muscarinic receptors, either globally or in specific neuron populations) (6) or pharmacological manipulation (e.g., co-administration of selective or non-selective muscarinic receptor antagonists like scopolamine) (7) (see further details in “Comparison groups”)….” We expanded the “Comparison groups” to mention explicitly the comparison of muscarinic drugs versus inactive control conditions (e.g., vehicle) in animal models of psychosis in the context of muscarinic receptor antagonism: “… We will also compare muscarinic receptor agonists or PAMs with inactive control conditions in contexts of genetic or pharmacological muscarinic receptor antagonism (as described in “Animal population and model induction”) to determine if any observed differences result from muscarinic receptor activation. Separate analyses may be conducted for the antagonism of specific muscarinic receptor subtypes and/or within specific neuronal populations, if sufficient data are available..” #1.5: The use of a similar methodology by the authors previously to assess TARR1 agonists in non-human studies is a strength, and the team assembled is well-suited to carry out this study. Overall, this study protocol is thoughtfully written and addresses important and timely questions with the potential to unveil critical insights into the ability of compounds targeting muscarinic receptors to modulate schizophrenia-relevant behaviors across numerous symptom domains in preclinical studies. Our reply : Thank you once again for your overall endorsement and for the thoughtful comments that have substantially strengthened our protocol. In addition to the above-mentioned changes, we have also updated the “Study status” to reflect the changes during the revision: “…There were no changes from the original PROSPERO registration of the protocol, except for expanding the methods with additional details (also in response to the reviewer’s comments), (3,8) revising the search strategy to include terms for allosteric modulation as suggested by a reviewer, (8) adding physicochemical properties of the compounds in the “Exploration of Heterogeneity” per another reviewer’s comment, (3) and deciding not to search Scopus and CINAHL after consulting with the information specialist (which is not expected to affect the coverage of our search)….” References 1. Kenakin T. Know your molecule: pharmacological characterization of drug candidates to enhance efficacy and reduce late-stage attrition. Nature Reviews Drug Discovery. 2024:1-19. 2. Foster DJ, et al. Allosteric Modulation of GPCRs: New Insights and Potential Utility for Treatment of Schizophrenia and Other CNS Disorders. Neuron. 2017;94(3):431-46. 3. Messer W. Peer Review Report For: Muscarinic receptor agonists in animal models of psychosis: protocol for a systematic review and meta-analysis [version 1; peer review: 2 approved with reservations]. F1000Research 2024;13:1017. 4. Kenakin T. A Scale of Agonism and Allosteric Modulation for Assessment of Selectivity, Bias, and Receptor Mutation. Mol Pharmacol. 2017;92(4):414-24. 5. Smith S, et al . Psychosis-SOLES 2024 [Available from: https://camarades.shinyapps.io/psychosis-soles March 4, 2024. 6. Thomsen M, et al. Physiological roles of CNS muscarinic receptors gained from knockout mice. Neuropharmacology. 2018;136(Pt C):411-20. 7. Klinkenberg I, et al. The validity of scopolamine as a pharmacological model for cognitive impairment: a review of animal behavioral studies. Neurosci Biobehav Rev. 2010;34(8):1307-50. 8. Foster D. Peer Review Report For: Muscarinic receptor agonists in animal models of psychosis: protocol for a systematic review and meta-analysis [version 1; peer review: 2 approved with reservations]. F1000Research. 2024;13:1017. View more View less Competing Interests Spyridon Siafis: None. Nobuyuki Nomura: N.N. has received manuscript fees from Sumitomo Pharma. Johannes Schneider-Thoma: None. Irene Bighelli: None. Alexandra Bannach-Brown: None. Fiona J. Ramage: None. Francesca Tinsdeall: None. Ioannis Mantas: None. Sameer Jauhar: SJ has received honoraria for educational talks given for Boehringer Ingelheim, Lundbeck, Janssen, and Sunovion, and has advised on antipsychotics to LB Pharmaceuticals. Sridhar Natesan: None. Anthony Vernon: ACV has received research support from UCB S.A and Bit.Bio (https://www.bit.bio/) and has received honoraria for seminars at GlaxoSmithKline. Andrea de Bartolomeis: AdB has received research support from Janssen, Lundbeck, and Otsuka and lecture fees for educational meeting from Chiesi, Lundbeck, Roche, Sunovion, Vitria, Recordati, Angelini and Takeda; he has served on advisory boards for Eli Lilly, Jansen, Lundbeck, Otsuka, Roche, and Takeda, Chiesi, Recordati, Angelini, Vitria. Sabine M. Hölter: None. Natascha I. Drude: None. Ulf Tölch: None. Wulf-Peter Hansen: None. Virginia Chiocchia: None. Oliver Howes: ODH has received investigator-initiated research funding from and/or participated in advisory/speaker meetings organised by Angellini, Autifony, Biogen, Boehringer-Ingelheim, Eli Lilly, Elysium, Heptares, Global Medical Education, Invicro, Jansenn, Karuna, Lundbeck, Merck, Neurocrine, Ontrack/ Pangea, Otsuka, Sunovion, Recordati, Roche, Rovi and Viatris/ Mylan. He was previously a part-time employee of Lundbeck A/v. Dr Howes has a patent for the use of dopaminergic imaging. Josef Priller: None. Georgia Salanti: None. Malcolm R. Macleod: None. Stefan Leucht: SL has received received honoraria for advising/consulting and/or for lectures and/or for educational material from Angelini, Boehringer Ingelheim, Eisai, Ekademia, GedeonRichter, Janssen, Karuna, Kynexis, Lundbeck, Medichem, Medscape, Mitsubishi, Otsuka, NovoNordisk, Recordati, Rovi, Teva. reply Respond Report a concern Foster D. Peer Review Report For: Muscarinic receptor agonists and positive allosteric modulators in animal models of psychosis: protocol for a systematic review and meta-analysis [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 13 :1017 ( https://doi.org/10.5256/f1000research.170522.r325666) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/13-1017/v1#referee-response-325666 Alongside their report, reviewers assign a status to the article: Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions Adjust parameters to alter display View on desktop for interactive features Includes Interactive Elements View on desktop for interactive features Competing Interests Policy Provide sufficient details of any financial or non-financial competing interests to enable users to assess whether your comments might lead a reasonable person to question your impartiality. Consider the following examples, but note that this is not an exhaustive list: Examples of 'Non-Financial Competing Interests' Within the past 4 years, you have held joint grants, published or collaborated with any of the authors of the selected paper. You have a close personal relationship (e.g. parent, spouse, sibling, or domestic partner) with any of the authors. You are a close professional associate of any of the authors (e.g. scientific mentor, recent student). You work at the same institute as any of the authors. You hope/expect to benefit (e.g. favour or employment) as a result of your submission. You are an Editor for the journal in which the article is published. Examples of 'Financial Competing Interests' You expect to receive, or in the past 4 years have received, any of the following from any commercial organisation that may gain financially from your submission: a salary, fees, funding, reimbursements. You expect to receive, or in the past 4 years have received, shared grant support or other funding with any of the authors. You hold, or are currently applying for, any patents or significant stocks/shares relating to the subject matter of the paper you are commenting on. Stay Updated Sign up for content alerts and receive a weekly or monthly email with all newly published articles Register with F1000Research Already registered? Sign in Not now, thanks close PLEASE NOTE If you are an AUTHOR of this article, please check that you signed in with the account associated with this article otherwise we cannot automatically identify your role as an author and your comment will be labelled as a “User Comment”. If you are a REVIEWER of this article, please check that you have signed in with the account associated with this article and then go to your account to submit your report, please do not post your review here. If you do not have access to your original account, please contact us . All commenters must hold a formal affiliation as per our Policies . The information that you give us will be displayed next to your comment. User comments must be in English, comprehensible and relevant to the article under discussion. We reserve the right to remove any comments that we consider to be inappropriate, offensive or otherwise in breach of the User Comment Terms and Conditions . Commenters must not use a comment for personal attacks. When criticisms of the article are based on unpublished data, the data should be made available. I accept the User Comment Terms and Conditions Please confirm that you accept the User Comment Terms and Conditions. Affiliation ✕ refresh Please enter your institution. Note: To add your institution or organisation, start typing the name and then select the correct name from the list. Where applicable, the name will appear in both the original language and in English. Do not paste in the name. If the name does not appear in the drop-down list, we will display the information you have entered. ✕ refresh Country/Region * USA UK Canada China France Germany Afghanistan Aland Islands Albania Algeria American Samoa Andorra Angola Anguilla Antarctica Antigua and Barbuda Argentina Armenia Aruba Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bermuda Bhutan Bolivia Bosnia and Herzegovina Botswana Bouvet Island Brazil British Indian Ocean Territory British Virgin Islands Brunei Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Cape Verde Cayman Islands Central African Republic Chad Chile China Christmas Island Cocos (Keeling) Islands Colombia Comoros Congo Cook Islands Costa Rica Cote d'Ivoire Croatia Cuba Cyprus Czech Republic Democratic Republic of the Congo Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Eritrea Estonia Ethiopia Falkland Islands Faroe Islands Federated States of Micronesia Fiji Finland France French Guiana French Polynesia French Southern Territories Gabon Georgia Germany Ghana Gibraltar Greece Greenland Grenada Guadeloupe Guam Guatemala Guernsey Guinea Guinea-Bissau Guyana Haiti Heard Island and Mcdonald Islands Holy See (Vatican City State) Honduras Hong Kong Hungary Iceland India Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jersey Jordan Kazakhstan Kenya Kiribati Kosovo (Serbia and Montenegro) Kuwait Kyrgyzstan Lao People's Democratic Republic Latvia Lebanon Lesotho Liberia Libya Liechtenstein Lithuania Luxembourg Macao Madagascar Malawi Malaysia Maldives Mali Malta Marshall Islands Martinique Mauritania Mauritius Mayotte Mexico Minor Outlying Islands of the United States Moldova Monaco Mongolia Montenegro Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands Antilles New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norfolk Island North Korea North Macedonia Northern Mariana Islands Norway Oman Pakistan Palau Palestinian Territory Panama Papua New Guinea Paraguay Peru Philippines Pitcairn Poland Portugal Puerto Rico Qatar Reunion Romania Russian Federation Rwanda Saint Helena Saint Kitts and Nevis Saint Lucia Saint Pierre and Miquelon Saint Vincent and the Grenadines Samoa San Marino Sao Tome and Principe Saudi Arabia Senegal Serbia Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa South Georgia and the South Sandwich Is South Korea South Sudan Spain Sri Lanka Sudan Suriname Svalbard and Jan Mayen Swaziland Sweden Switzerland Syria Taiwan Tajikistan Tanzania Thailand The Gambia The Netherlands Timor-Leste Togo Tokelau Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Turks and Caicos Islands Tuvalu UK USA Uganda Ukraine United Arab Emirates United States Virgin Islands Uruguay Uzbekistan Vanuatu Venezuela Vietnam Wallis and Futuna West Bank and Gaza Strip Western Sahara Yemen Zambia Zimbabwe Please select your country/region. You must enter a comment. Competing Interests Please disclose any competing interests that might be construed to influence your judgment of the article's or peer review report's validity or importance. Competing Interests Policy Provide sufficient details of any financial or non-financial competing interests to enable users to assess whether your comments might lead a reasonable person to question your impartiality. Consider the following examples, but note that this is not an exhaustive list: Examples of 'Non-Financial Competing Interests' Within the past 4 years, you have held joint grants, published or collaborated with any of the authors of the selected paper. You have a close personal relationship (e.g. parent, spouse, sibling, or domestic partner) with any of the authors. You are a close professional associate of any of the authors (e.g. scientific mentor, recent student). You work at the same institute as any of the authors. You hope/expect to benefit (e.g. favour or employment) as a result of your submission. You are an Editor for the journal in which the article is published. Examples of 'Financial Competing Interests' You expect to receive, or in the past 4 years have received, any of the following from any commercial organisation that may gain financially from your submission: a salary, fees, funding, reimbursements. You expect to receive, or in the past 4 years have received, shared grant support or other funding with any of the authors. You hold, or are currently applying for, any patents or significant stocks/shares relating to the subject matter of the paper you are commenting on. Please state your competing interests The comment has been saved. An error has occurred. Please try again. Cancel Post var lTitle = "Muscarinic receptor agonists and positive...".replace("'", ''); var linkedInUrl = "http://www.linkedin.com/shareArticle?url=https://f1000research.com/articles/13-1017/v2" + "&title=" + encodeURIComponent(lTitle) + "&summary=" + encodeURIComponent('Read the article by '); var deliciousUrl = "https://del.icio.us/post?url=https://f1000research.com/articles/13-1017/v2&title=" + encodeURIComponent(lTitle); var redditUrl = "http://reddit.com/submit?url=https://f1000research.com/articles/13-1017/v2" + "&title=" + encodeURIComponent(lTitle); linkedInUrl += encodeURIComponent('Siafis S et al.'); var offsetTop = /chrome/i.test( navigator.userAgent ) ? 4 : -10; var addthis_config = { ui_offset_top: offsetTop, services_compact : "facebook,twitter,www.linkedin.com,www.mendeley.com,reddit.com", services_expanded : "facebook,twitter,www.linkedin.com,www.mendeley.com,reddit.com", services_custom : [ { name: "LinkedIn", url: linkedInUrl, icon:"/img/icon/at_linkedin.svg" }, { name: "Mendeley", url: "http://www.mendeley.com/import/?url=https://f1000research.com/articles/13-1017/v2/mendeley", icon:"/img/icon/at_mendeley.svg" }, { name: "Reddit", url: redditUrl, icon:"/img/icon/at_reddit.svg" }, ] }; var addthis_share = { url: "https://f1000research.com/articles/13-1017", templates : { twitter : "Muscarinic receptor agonists and positive allosteric modulators.... Siafis S et al., published by " + "@F1000Research" + ", https://f1000research.com/articles/13-1017/v2" } }; if (typeof(addthis) != "undefined"){ addthis.addEventListener('addthis.ready', checkCount); addthis.addEventListener('addthis.menu.share', checkCount); } $(".f1r-shares-twitter").attr("href", "https://twitter.com/intent/tweet?text=" + addthis_share.templates.twitter); $(".f1r-shares-facebook").attr("href", "https://www.facebook.com/sharer/sharer.php?u=" + addthis_share.url); $(".f1r-shares-linkedin").attr("href", addthis_config.services_custom[0].url); $(".f1r-shares-reddit").attr("href", addthis_config.services_custom[2].url); $(".f1r-shares-mendelay").attr("href", addthis_config.services_custom[1].url); function checkCount(){ setTimeout(function(){ $(".addthis_button_expanded").each(function(){ var count = $(this).text(); if (count !== "" && count != "0") $(this).removeClass("is-hidden"); else $(this).addClass("is-hidden"); }); }, 1000); } close How to cite this report {{reportCitation}} Cancel Copy Citation Details $(function(){R.ui.buttonDropdowns('.dropdown-for-downloads');}); $(function(){R.ui.toolbarDropdowns('.toolbar-dropdown-for-downloads');}); $.get("/articles/acj/155356/176234") new F1000.Clipboard(); new F1000.ThesaurusTermsDisplay("articles", "article", "176234"); $(document).ready(function() { $( "#frame1" ).on('load', function() { var mydiv = $(this).contents().find("div"); var h = mydiv.height(); console.log(h) }); var tooltipLivingFigure = jQuery(".interactive-living-figure-label .icon-more-info"), titleLivingFigure = tooltipLivingFigure.attr("title"); tooltipLivingFigure.simpletip({ fixed: true, position: ["-115", "30"], baseClass: 'small-tooltip', content:titleLivingFigure + " " }); tooltipLivingFigure.removeAttr("title"); $("body").on("click", ".cite-living-figure", function(e) { e.preventDefault(); var ref = $(this).attr("data-ref"); $(this).closest(".living-figure-list-container").find("#" + ref).fadeIn(200); }); $("body").on("click", ".close-cite-living-figure", function(e) { e.preventDefault(); $(this).closest(".popup-window-wrapper").fadeOut(200); }); $(document).on("mouseup", function(e) { var metricsContainer = $(".article-metrics-popover-wrapper"); if (!metricsContainer.is(e.target) && metricsContainer.has(e.target).length === 0) { $(".article-metrics-close-button").click(); } }); var articleId = $('#articleId').val(); if($("#main-article-count-box").attachArticleMetrics) { $("#main-article-count-box").attachArticleMetrics(articleId, { articleMetricsView: true }); } }); var figshareWidget = $(".new_figshare_widget"); if (figshareWidget.length > 0) { window.figshare.load("f1000", function(Widget) { // Select a tag/tags defined in your page. In this tag we will place the widget. _.map(figshareWidget, function(el){ var widget = new Widget({ articleId: $(el).attr("figshare_articleId") //height:300 // this is the height of the viewer part. [Default: 550] }); widget.initialize(); // initialize the widget widget.mount(el); // mount it in a tag that's on your page // this will save the widget on the global scope for later use from // your JS scripts. This line is optional. //window.widget = widget; }); }); } close Error Close Add Reset F1000.MICROSERVICES.AFFILIATION = ''; $(document).ready(function () { $('.js-affiliations-form').each((index, form) => { new AffiliationForm({ formId: form.id, institutionErrorSelector: '.comment-enter-institution', departmentErrorSelector: '.comment-enter-department', placeSelector: '.js-add-comment-place', stateSelector: '.js-add-comment-state', zipCodeSelector: '.js-add-comment-zipcode', countrySelector: '.js-add-comment-country', countryErrorSelector: '.comment-enter-country', }); }); }); $(document).ready(function () { var reportIds = { "355397": 0, "355398": 0, "330141": 0, "330140": 0, "330143": 0, "325662": 0, "330142": 0, "325663": 0, "330137": 0, "330139": 0, "330138": 0, "325668": 0, "325669": 0, "357863": 13, "325670": 0, "325671": 19, "330145": 0, "325664": 0, "325665": 0, "330144": 0, "325666": 29, "330146": 0, "325667": 0, "333293": 0, "357868": 0, "333292": 0, "333295": 0, "321838": 0, "333294": 0, "321839": 0, "357865": 0, "357864": 0, "357867": 0, "357866": 0, "333301": 0, "321844": 0, "333300": 0, "321845": 0, "321846": 0, "321847": 0, "333297": 0, "321840": 0, "333296": 0, "321841": 0, "333299": 0, "321842": 0, "333298": 0, "321843": 0, }; $(".referee-response-container,.js-referee-report").each(function(index, el) { var reportId = $(el).attr("data-reportid"), reportCount = reportIds[reportId] || 0; $(el).find(".comments-count-container,.js-referee-report-views").html(reportCount); }); var uuidInput = $("#article_uuid"), oldUUId = uuidInput.val(), newUUId = "09dc3030-ed9e-42e4-a2a3-7ca6d66994ba"; uuidInput.val(newUUId); $("a[href*='article_uuid=']").each(function(index, el) { var newHref = $(el).attr("href").replace(oldUUId, newUUId); $(el).attr("href", newHref); }); }); An innovative open access publishing platform offering rapid publication and open peer review, whilst supporting data deposition and sharing. Browse Gateways Collections How it Works Contact For Developers Cookie Notice Privacy Notice RSS Submit Your Research Follow us © 2012-2026 F1000 Research Ltd. ISSN 2046-1402 | Legal | Partner of Research4Life • CrossRef • ORCID • FAIRSharing R.templateTests.simpleTemplate = R.template(' $text $text $text $text $text '); R.templateTests.runTests(); var F1000platform = new F1000.Platform({ name: "f1000research", displayName: "F1000Research", hostName: "f1000research.com", id: "1", editorialEmail: "[email protected]", infoEmail: "[email protected]", usePmcStats: true }); $(function(){R.ui.dropdowns('.dropdown-for-authors, .dropdown-for-about, .dropdown-for-myresearch');}); // $(function(){R.ui.dropdowns('.dropdown-for-referees');}); $(document).ready(function () { if ($(".cookie-warning").is(":visible")) { $(".sticky").css("margin-bottom", "35px"); $(".devices").addClass("devices-and-cookie-warning"); } $(".cookie-warning .close-button").click(function (e) { $(".devices").removeClass("devices-and-cookie-warning"); $(".sticky").css("margin-bottom", "0"); }); $("#tweeter-feed .tweet-message").each(function (i, message) { var self = $(message); self.html(linkify(self.html())); }); $(".partner").on("mouseenter mouseleave", function() { $(this).find(".gray-scale, .colour").toggleClass("is-hidden"); }); }); Sign In Remember me Forgotten your password? Sign In Cancel Email or password not correct. Please try again Please wait... $(function(){ // Note: All the setup needs to run against a name attribute and *not* the id due the clonish // nature of facebox... $("a[id=googleSignInButton]").click(function(event){ event.preventDefault(); $("input[id=oAuthSystem]").val("GOOGLE"); $("form[id=oAuthForm]").submit(); }); $("a[id=facebookSignInButton]").click(function(event){ event.preventDefault(); $("input[id=oAuthSystem]").val("FACEBOOK"); $("form[id=oAuthForm]").submit(); }); $("a[id=orcidSignInButton]").click(function(event){ event.preventDefault(); $("input[id=oAuthSystem]").val("ORCID"); $("form[id=oAuthForm]").submit(); }); }); If you've forgotten your password, please enter your email address below and we'll send you instructions on how to reset your password. The email address should be the one you originally registered with F1000. Email address not valid, please try again You registered with F1000 via Google, so we cannot reset your password. To sign in, please click here . If you still need help with your Google account password, please click here . You registered with F1000 via Facebook, so we cannot reset your password. To sign in, please click here . If you still need help with your Facebook account password, please click here . Code not correct, please try again Reset password Cancel Email us for further assistance. Server error, please try again. If your email address is registered with us, we will email you instructions to reset your password. If you think you should have received this email but it has not arrived, please check your spam filters and/or contact for further assistance. Please wait... Register $(document).ready(function () { signIn.createSignInAsRow($("#sign-in-form-gfb-popup")); $(".target-field").each(function () { var uris = $(this).val().split("/"); if (uris.pop() === "login") { $(this).val(uris.toString().replace(",","/")); } }); });