Older more fit KL-VS heterozygotes have more favorable AD-relevant biomarker profiles

Older more fit KL-VS heterozygotes have more favorable AD-relevant biomarker profiles | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (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];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Older more fit KL-VS heterozygotes have more favorable AD-relevant biomarker profiles Mackenzie Jarchow , Ira Driscoll , Brianne M. Breidenbach , Noah Cook , Catherine L. Gallagher , Sterling C. Johnson , Sanjay Asthana , Bruce P. Hermann , Mark A. Sager , Kaj Blennow , Henrik Zetterberg , Cynthia M. Carlsson , Gwendlyn Kollmorgen , Clara Quijano-Rubio , Dane B. Cook , View ORCID Profile Dena B. Dubal , Ozioma C. Okonkwo doi: https://doi.org/10.1101/2025.02.27.25323056 Mackenzie Jarchow 1 Wisconsin Alzheimer’s Disease Research Center, Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison , Madison, WI, USA BS Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ira Driscoll 1 Wisconsin Alzheimer’s Disease Research Center, Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison , Madison, WI, USA 2 Wisconsin Alzheimer’s Institute Madison , WI, USA PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: idriscoll{at}medicine.wisc.edu ozioma{at}wisc.medicine.edu Brianne M. Breidenbach 1 Wisconsin Alzheimer’s Disease Research Center, Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison , Madison, WI, USA 2 Wisconsin Alzheimer’s Institute Madison , WI, USA PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Noah Cook 1 Wisconsin Alzheimer’s Disease Research Center, Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison , Madison, WI, USA 3 NeuroGenomics and Informatics Center, Washington University School of Medicine , St. Louis, MO, USA MS Find this author on Google Scholar Find this author on PubMed Search for this author on this site Catherine L. Gallagher 4 Geriatric Research Education and Clinical Center, William S. Middleton VA Hospital , Madison, WI, USA 5 Department of Neurology, School of Medicine and Public Health, University of Wisconsin-Madison , Madison, WI, USA MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Sterling C. Johnson 1 Wisconsin Alzheimer’s Disease Research Center, Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison , Madison, WI, USA 2 Wisconsin Alzheimer’s Institute Madison , WI, USA PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Sanjay Asthana 1 Wisconsin Alzheimer’s Disease Research Center, Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison , Madison, WI, USA 2 Wisconsin Alzheimer’s Institute Madison , WI, USA 4 Geriatric Research Education and Clinical Center, William S. Middleton VA Hospital , Madison, WI, USA MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Bruce P. Hermann 1 Wisconsin Alzheimer’s Disease Research Center, Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison , Madison, WI, USA 2 Wisconsin Alzheimer’s Institute Madison , WI, USA 5 Department of Neurology, School of Medicine and Public Health, University of Wisconsin-Madison , Madison, WI, USA PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Mark A. Sager 1 Wisconsin Alzheimer’s Disease Research Center, Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison , Madison, WI, USA 2 Wisconsin Alzheimer’s Institute Madison , WI, USA MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Kaj Blennow 6 Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg , Mölndal, Sweden 7 Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal , Sweden 8 Paris Brain Institute, ICM, Pitié-Salpêtrière Hospital, Sorbonne University , Paris, France 9 Neurodegenerative Disorder Research Center, Division of Life Sciences and Medicine, and Department of Neurology, Institute on Aging and Brain Disorders, University of Science and Technology of China and First Affiliated Hospital of USTC , Hefei, China MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Henrik Zetterberg 1 Wisconsin Alzheimer’s Disease Research Center, Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison , Madison, WI, USA 6 Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg , Mölndal, Sweden 7 Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal , Sweden 10 Department of Neurodegenerative Disease, UCL Institute of Neurology , Queen Square, London, UK 11 UK Dementia Research Institute at UCL , London, UK 12 Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay , Hong Kong, China 13 Roche Diagnostics GmbH , Penzberg, Germany MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Cynthia M. Carlsson 1 Wisconsin Alzheimer’s Disease Research Center, Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison , Madison, WI, USA 2 Wisconsin Alzheimer’s Institute Madison , WI, USA 5 Department of Neurology, School of Medicine and Public Health, University of Wisconsin-Madison , Madison, WI, USA MD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Gwendlyn Kollmorgen 13 Roche Diagnostics GmbH , Penzberg, Germany PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Clara Quijano-Rubio 14 Roche Diagnostics International Ltd , Rotkreuz, Switzerland PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Dane B. Cook 15 Research Service, William S. Middleton VA Hospital , Madison, WI, USA 16 Department of Kinesiology, School of Education, University of Wisconsin-Madison , Madison, WI, USA PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Dena B. Dubal 17 Department of Neurology and Weill Institute for Neurosciences, University of California , San Francisco, California, USA MD, PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Dena B. Dubal Ozioma C. Okonkwo 1 Wisconsin Alzheimer’s Disease Research Center, Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison , Madison, WI, USA 2 Wisconsin Alzheimer’s Institute Madison , WI, USA PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: idriscoll{at}medicine.wisc.edu ozioma{at}wisc.medicine.edu Abstract Full Text Info/History Metrics Data/Code Preview PDF Abstract INTRODUCTION While hallmarked by the accumulation of β-amyloid plaques (Aβ) and neurofibrillary tangles (tau) in the brain, Alzheimer’s disease (AD) is a multifactorial disorder that involves additional pathological events, including neuroinflammation, neurodegeneration and synaptic dysfunction. AD-associated biomolecular changes seem to be attenuated in carriers of the functionally advantageous variant of the KLOTHO gene (KL-VS HET ). Independently, better cardiorespiratory fitness (CRF) is associated with better health outcomes, both in general and specifically with regard to AD pathology. Here we investigate whether the relationships between CRF (peak oxygen consumption (VO 2peak )) and cerebrospinal fluid (CSF) core AD biomarkers and those of neuroinflammation, neurodegeneration, and synaptic dysfunction differ for KL-VS HET compared to non-carriers (KL-VS NC ). METHODS The cohort, enriched for AD risk, consisted of cognitively unimpaired adults (N=136; Mean AGE (SD)=62.5(6.7)) from the Wisconsin Registry for Alzheimer’s Prevention and the Wisconsin Alzheimer’s Disease Research Center. Covariate-adjusted (age, sex, parental AD history, APOE 4+ status, and age difference between CSF sampling and exercise test) linear models examined the interaction between VO 2peak and KLOTHO genotype on core AD biomarker levels in CSF [phosphorylated tau 181 (pTau 181 ), Aβ 42 /Aβ 40 , pTau 181 /Aβ 42 ]. Analyses were repeated for CSF biomarkers of neurodegeneration [total tau (tTau), α-synuclein (α-syn), neurofilament light polypeptide (NfL)], synaptic dysfunction [neurogranin (Ng)], and neuroinflammation [glial fibrillary acidic protein (GFAP), soluble triggering receptor expressed in myeloid cells (sTREM2), chitinase-3-like protein 1 (YKL-40), interleukin 6 (IL-6), S100 calcium-binding protein B (S100B)]. RESULTS The interaction between VO 2peak and KL-VS HET was significant for tTau ( P =0.05), pTau 181 ( P =0.03), Ng ( P =0.02), sTREM2 ( P =0.03), and YKL-40 ( P =0.03), such that lower levels of each biomarker were observed for KL-VS HET who were more fit. No significant KL-VSxVO 2peak interactions were observed for Aβ 42 /Aβ 40 , pTau 181 /Aβ 42 , α-syn, NfL, GFAP, IL-6 or S100B (all P s>0.09). CONCLUSIONS We report a synergistic relationship between KL-VS HET and CRF with regard to pTau 181 , tTau, Ng, sTREM2 and YKL-40, suggesting a protective role for both KL-VS HET and better cardiovascular fitness against unfavorable AD-related changes. Their potentially shared biological mechanisms will require future investigations. Systematic Review PubMed literature review suggests that both KLOTHO KL-VS genotype and cardiorespiratory fitness (CRF) are associated with pathophysiological processes related to Alzheimer’s Disease (AD). Both KL-VS heterozygotes (KL-VS HET ) and those with higher CRF fare better when faced with age-related biomolecular changes of relevance to AD. The present study investigates whether the relationships between CRF and cerebrospinal fluid biomarkers (CSF) of core AD neuropathology, neuroinflammation, neurodegeneration, and synaptic dysfunction differ for KL-VS HET compared to non-carriers. Interpretation Our findings suggest a synergistic relationship between KL-VS HET and higher CRF against core AD pathology along a range of unfavorable biomolecular changes implicated in this multifactorial disease. This supports the idea that CRF may interact with genetic factors to confer resilience against a multitude of adverse AD-associated processes. Future Directions Future studies should examine longitudinal changes in CSF biomarkers to determine whether maintaining or improving CRF over time enhances AD resilience in KL-VS HET . 2 Introduction Alzheimer’s disease (AD), the most prevalent type of dementia, has garnered increasing attention as a pressing public health concern, particularly in light of the growing elderly population [ 1 ]. Given that age is the most significant risk factor for AD, this demographic shift is expected to lead to a marked rise in the number of individuals afflicted by this neurodegenerative disease [ 1 ]. Characterized by distinct pathophysiological hallmarks, the accumulation of beta-amyloid (Aβ) plaques and neurofibrillary tangles (tau) in the brain, AD causes irreparable cognitive and functional impairments [ 2 ]. This growing burden—affecting over 55 million people globally—highlights the critical need for advancing research efforts to develop preventative measures and therapeutic strategies to combat AD [ 1 ]. There is a growing interest in research surrounding modifiable and non-modifiable factors that might mitigate AD risk. Two such factors, a functionally advantageous KLOTHO KL-VS genotype (non-modifiable) and cardiorespiratory fitness (CRF; modifiable), are of particular interest as they are both associated with various favorable outcomes related to AD [ 3 – 12 ]. KLOTHO is considered an anti-aging and longevity gene that encodes klotho, a transmembrane protein responsible for regulating various aging processes in mammals [ 13 , 14 ] . In humans, two genetic variants of KLOTHO , rs9536314 and rs9527025, combine to form a functional haplotype known as KL-VS [ 15 ]. The functionally advantageous KL-VS genotype (KL-VS HET ) is associated with higher circulating klotho protein levels and more favorable outcomes related to cardiovascular health, renal sufficiency, and cognitive function [ 14 – 17 ] within the context of aging. More recent literature examining KLOTHO in relation to AD suggests that KL-VS HET is associated with lower Aβ aggregation [ 11 ], tau burden [ 3 , 4 ] and AD risk in apolipoprotein E ( APOE ) ε4 carriers [ 18 ]. Additionally, KL-VS HET ’s protective properties seem to extend to deleterious age-related changes in synaptic integrity, neurodegeneration, and neuroinflammatory responses [ 12 ]. This apparent broad neuroprotection suggests a critical role for KL-VS HET in safeguarding the brain from AD-associated biomolecular changes and related pathological events [ 3 , 4 , 11 , 12 ]. CRF, a widely recognized index of habitual physical activity, is associated with reduced risk for AD-related dementia mortality [ 19 ], slower rates of gray matter atrophy in AD-relevant brain regions [ 5 , 10 ], attenuation of white matter hyperintensities [ 20 ], and preservation of hippocampal volume with age [ 21 ]. Furthermore, emerging evidence suggests that physical exercise positively impacts not only cognition [ 5 , 6 , 10 , 21 ] but also the underlying disease mechanisms, including Aβ deposition [ 7 , 22 , 23 ] and tau burden [ 24 ]. Additionally, higher CRF is also associated with less neuroinflammation [ 25 ] and better neuroplasticity [ 26 ]. The literature highlights the potential of CRF as a therapeutic strategy to address various pathological mechanisms of AD. While both KL-VS HET and CRF seem to confer resilience against deleterious AD-associated changes, there is a notable absence of research that concurrently examines the synergy between these two factors with respect to their combined impact on biomolecular changes associated with AD. Moreover, existent interventions largely focus on mitigating Aβ and tau burden, even though AD is a multifactorial disease involving additional pathological processes, such as neuroinflammation, neurodegeneration, and synaptic dysfunction [ 27 ]. Hence, the objective of the current study is to investigate whether the relationships between CRF, indexed here by VO 2peak , and cerebrospinal fluid (CSF) biomarkers of core AD pathology, neurodegeneration, synaptic dysfunction, and neuroinflammation differ for KLOTHO KL-VS non-carriers (KL-VS NC ) and KL-VS HET in an older, cognitively unimpaired cohort enriched for AD risk. We hypothesize that KL-VS HET individuals with higher CRF will have a more favorable profile of investigated CSF biomarkers compared to KL-VS NC . 3 Methods 3.1 Participants The current sample is comprised of 136 (Mean AGE (SD) = 62.5(6.7); 64% female) cognitively unimpaired, middle-aged and older adults from the Wisconsin Registry for Alzheimer’s Prevention (WRAP) [ 28 ] and Wisconsin Alzheimer’s Disease Research Center (WADRC) [ 11 ] who were genotyped for APOE and KLOTHO , underwent CSF sampling, and had available VO 2peak data. The cohort was enriched for parental history of AD at enrollment, and subsequently has a higher prevalence of APOE ε4 allele carriers ( APOE 4+) than what is observed in the general population. Cognitive normalcy was determined by a standardized and multidisciplinary consensus based on performance on a comprehensive battery of neuropsychological tests, lack of functional impairment, and absence of neurologic/psychiatric conditions that might impair cognition [ 11 , 28 ]. All study procedures were approved by the Institutional Review Board at the University of Wisconsin and each participant provided written informed consent before taking part. 3.2 Genotyping Using the PUREGENE DNA Isolation Kit (Gentra Systems, Inc., Minneapolis, MN), DNA was isolated from whole-blood samples. Ultraviolet spectrophotometry (DU 530 Spectrophotometer, Beckman Coulter, Fullerton, CA) was used to measure DNA concentrations. Genotyping for APOE (rs429358 and rs7412) and KLOTHO (rs9536314 for F352V and rs9527025 for C370S) was done by LGC Genomics (Beverly, MA) via competitive allele-specific PCR-based KASP genotyping assays. Quality control procedures have been previously published [ 11 ] and are considered acceptable. KL-VS homozygosity, a rare genotype associated with lower klotho levels [ 16 ], was excluded from analyses due to sparse sample size (N=6). 3.3 CSF Assessment After a 12-hour fast, a lumbar puncture was conducted at L3-4 or L4-5 using a drip method and/or gentle extraction technique into polypropylene syringes using a Sprotte 24- or 25-gauge spinal needle. A thin needle was used to inject 1% lidocaine as a local anesthetic prior to the insertion of the Sprotte spinal needle. 22 milliliters of CSF from each sample were pooled, gently mixed, and centrifuged at 2,000 g for 10 minutes. Supernatants were kept at 80°C and frozen in 0.5 milliliters aliquots in polypropylene tubes. Samples were analyzed for phosphorylated tau (pTau 181 ), Aβ 40, and Aβ 42 to obtain biomarkers of core AD pathology (pTau 181 , Aβ 42 /Aβ 40, and pTau 181 /Aβ 42 ), neurodegeneration [total tau (tTau), α-synuclein (α-syn), neurofilament light polypeptide (NfL)], synaptic dysfunction [neurogranin (Ng)], and neuroinflammation [glial fibrillary acidic protein (GFAP), soluble triggering receptor expressed in myeloid cells 2 (sTREM2), chitinase-3-like protein 1 (YKL-40), interleukin 6 (IL-6), S100 calcium-binding protein B (S100B)]) using the NeuroToolKit (NTK; Roche Diagnostics International Ltd, Rotkruez, Switzerland). The NTK is a panel of exploratory prototype assays designed to robustly evaluate established AD biomarkers (Aβ and tau) as well as emerging markers. This toolkit enables a comprehensive characterization of AD pathology as well as a panel of synaptic, axonal, and glial biomarkers, providing enhanced insights into the disease’s pathophysiological processes [ 29 ]. 3.4 Cardiorespiratory Fitness (VO 2peak ) Assessment Details of VO 2peak assessment have been previously published [ 6 , 20 ]. To assess VO 2peak , the gold standard for direct assessment of CRF [ 30 ], participants completed a maximal graded exercise test administered by a certified exercise physiologist using standard operating procedures defined by American College of Sports Medicine guidelines. Participants underwent medical screening, including a resting ECG, to ensure safety before testing. Heart rate and rhythm were monitored continuously alongside oxygen uptake (VO), carbon dioxide production, and other respiratory metrics using a calibrated metabolic cart (TrueOne® 2400, Parvomedics). Participants walked at a self-selected speed, with treadmill incline increasing 2.5% every two minutes until volitional exhaustion. Peak effort was defined by at least two of the following criteria: (1) respiratory exchange ratio greater than or equal to 1.1, (2) achievement of 90% of age-predicted maximum heart rate, (3) perceived exertion greater than or equal to 17, or (4) change in VO 2 less than 200 milliliters with an increase in work. Participants could stop the test at any point, and recovery involved walking at 2 mph and 0% grade for five minutes. The analyses were limited to participants who reached peak effort during graded exercise testing. 3.5 Statistical Analyses All analyses were performed in R Statistical Software version 4.3.0 [ 31 ]. Demographic characteristics were compared between KL-VS NC (N=93) and KL-VS HET (N=43) using independent-sample t-tests for continuous measures and χ 2 tests for categorical measures. To examine whether the relationship between VO 2peak and CSF biomarkers of core AD pathology, neurodegeneration, synaptic dysfunction, and neuroinflammation differed between KL-VS NC and KL-VS HET , we fitted a series of linear regression models that incorporated a KL-VS* VO 2peak interaction term, while covarying for age, sex, age difference between CSF sampling and exercise test, APOE ε4 status, and parental history of AD. If the interaction was not significant, analyses were repeated after removing the KL-VS* VO 2peak term to examine the main effects of KL-VS and VO 2peak to assess whether CSF biomarker levels differed by either factor independently. 4 Results 4.1 Sample Characteristics Table 1 details the background characteristics of the entire sample and by KL-VS genotype. The sample was predominantly white (98%) and female (64%), with an average age of 62.5±6.7 years and enriched for AD risk, with 38% carrying at least one APOE ε4 allele and 75% having a parental history of AD. VO 2peak averaged 26.0±6.4 mL/kg/min. For the entire sample, the average age difference between CSF sampling and the exercise test was 1.8±2.6 years. There were no significant differences in any of the above-mentioned characteristics between KL-VS NC and KL-VS HET ( P s ≥ 0.17). View this table: View inline View popup Download powerpoint Table 1. Background characteristics of study participants. 4.2 CSF biomarkers of core AD pathology as a function of the KLOTHO KL VS and VO 2peak A significant interaction was observed between KL-VS genotype and VO 2peak for pTau 181 ( P= 0.03; Table 2 ). Figure 1 illustrates this relationship, whereby KL-VS HET who were more fit had lower levels of pTau 181. While KL-VSxVO 2peak interaction was not significant for Aβ 42 /Aβ 40, the levels differed by KL-VS genotype as indicated by a significant main effect of KL-VS ( P =0.03). No significant interaction ( P =0.36) nor main effects of either KL-VS or VO 2peak were observed for pTau 181 /Aβ 42 ( Ps ≥ 0.07). Download figure Open in new tab Figure 1. KL-VS genotype differences in CSF pTau 181 based on CRF (VO 2peak ). KL-VS HET with high CRF had lower levels of pTau 181 . View this table: View inline View popup Table 2. CSF biomarkers of core AD neuropathology, neurodegeneration, synaptic dysfunction, and neuroinflammation as a function of the KLOTHO KL VS and VO 2peak . 4.3 CSF biomarkers of neurodegeneration, synaptic dysfunction and inflammation as a function of the KLOTHO KL VS and VO 2peak A significant KL-VSxVO 2peak interaction was observed for markers of neurodegeneration [ tTau : P =0.05], synaptic dysfunction [ Ng : P =0.02] and neuroinflammation [ Table 2 ; sTREM2 : P =0.03; YKL-40 : P =0.03]. Figure 2A-D illustrates these findings; KL-VS HET with greater VO 2peak had lower levels of tTau (A), Ng (B), YKL-40 (C) and sTREM2 (D). KL-VSxVO 2peak interaction was not significant for α-syn, NfL, GFAP, S100B or IL-6 (all P s>0.09). Additionally, no main effects of either KL-VS or VO 2peak were significant for α-syn, NfL, GFAP or IL-6 (all P s>0.10). S100B levels differed based on CRF, as indicated by a significant main effect of VO 2peak ( P =0.02). Download figure Open in new tab Figure 2. KL-VS differences in CSF A) tTau, B) Ng, C) YKL-40, and D) sTREM2 based on CRF (VO 2peak ). KL-VS HET with high CRF had lower levels of neurodegeneration (tTau), synaptic dysfunction (Neurogranin) and neuroinflammation (sTREM2 and YKL-40). 5 Discussion Our findings suggest that KL-VS HET in conjunction with higher CRF may offer protection against a variety of adverse biomolecular changes associated with AD. Specifically, we report a synergistic relationship between KL-VS HET and higher CRF with regard to core AD pathology (pTau 181 ), neurodegeneration (tTau), synaptic dysfunction (Ng) and neuroinflammation (sTREM2 and YKL-40). Together, our results contribute to the growing literature supporting the role for KLOTHO in modulating age-related neuropathological processes and provide novel insights into how modifiable lifestyle factors, CRF specifically, may interact with genetic factors to influence AD risk. The significant interaction between KL-VS HET and CRF in relation to pTau 181 and tTau suggests a key role for both fitness and genetic variation in mitigating tau-related pathology. Tau hyperphosphorylation and aggregation are hallmark features of AD, contributing to neuronal dysfunction and cognitive decline [ 27 ]. While CSF tTau and pTau are predictive markers of AD-related neurodegeneration and tangle formation, they are not direct markers of these processes [ 32 ]. pTau 181 is also increasingly recognized as more indicative of Aβ-related tau dysmetabolism [ 32 ]. Furthermore, we caution against the simplistic interpretation of tTau as a marker of neurodegeneration given its nearly perfect correlation (∼98%) with pTau 181 across our center-wide data [ 29 ], which suggests that the two measures may be largely reflective of overlapping rather than distinct pathological processes in our cognitively unimpaired cohort enriched for AD risk. Based on extant literature, we know that individuals with higher plasma tau who engage in more physical activity show a deceleration in cognitive decline [ 33 ]. Moreover, there is evidence that KL-VS HET is associated with lower tau burden in aging adults [ 3 , 4 ], suggesting that the KL-VS HET genotype may play a role in tau clearance or stabilization. Our study advances this understanding by observing that, in KL-VS HET , higher CRF is associated with lesser CSF pTau and tTau levels, suggesting a combined role of genetic predisposition and physical activity in potentially slowing AD- related tau pathology. This supports the notion that physical activity may exert genotype-specific effects, providing greater neuroprotection in individuals with the KL-VS HET genotype. Thus, increasing CRF through exercise may serve as a preventative therapeutic strategy for KL-VS HET individuals, potentially mitigating AD-related tau pathology and its detrimental effects on cognitive health. Ng is a postsynaptic protein expressed on postsynaptic spines of dendrites that is critical for synaptic plasticity and memory formation [ 34 ]. Elevated Ng levels in CSF are increasingly recognized as a marker of synaptic damage in AD [ 35 ]. Accumulating evidence suggests a protective effect of exercise on synaptic health [ 26 , 36 , 37 ]. For instance, recent literature showed that higher levels of physical activity are associated with lower Ng levels in individuals with low cardiovascular risk [ 36 ] and enhanced synaptic plasticity through the upregulation of brain-derived neurotrophic factor (BDNF) [ 37 ]. Animal models have demonstrated that elevated circulating protein klotho levels enhances synaptic plasticity and increases the expression of GluN2B, a key NMDA receptor subunit involved in synaptic transmission [ 16 , 17 ]. Our findings add to this body of research, showing that those with higher CRF who concomitantly harbor the KL-VS HET genotype have lower CSF Ng levels, indicative of preserved synaptic integrity. Furthermore, our results complement a recent study by our group, which reported that KL-VS HET exhibit resilience against age-related increases in Ng levels [ 12 ]. While potentially protective effects of KL-VS HET on synaptic health were present independent of fitness in our group’s previous work [ 12 ] our current findings suggest that higher CRF may amplify this neuroprotective effect, highlighting a potential synergistic protective relationship between KL-VS HET and CRF against AD- related synaptic dysfunction. Neuroinflammation plays a central role in the progression of AD, contributing to neuronal injury and the accumulation of amyloid and tau pathology [ 38 , 39 ]. Two key biomarkers of neuroinflammation, sTREM2 and YKL-40, reflect activity in microglia and astrocytes, respectively [ 40 – 42 ]. sTREM2 is a soluble form of triggering receptor expressed in myeloid cells 2 (TREM2), which is predominantly expressed on microglia, the immune cells of the central nervous system [ 43 ]. Upon microglial activation, TREM2 signaling plays a crucial role in regulating microglial survival, proliferation, and phagocytic activity in response to neuronal injury or the accumulation of pathological proteins such as Aβ and tau. The release of sTREM2 into CSF reflects this activation process and is thought to act as a modulator of neuroinflammation, amplifying protective microglial responses [ 43 ]. In AD, the elevation of sTREM2 is seen across different stages of the disease, with the largest increase reported during the mild cognitive impairment (MCI) phase before transitioning to AD [ 44 ]. Moreover, CSF sTREM2 levels are significantly elevated in individuals with AD compared to healthy controls [ 45 ]. This suggests that microglial activation intensifies early in the disease process and persists throughout its progression, making sTREM2 a useful biomarker for tracking neuroinflammation within the context of neurodegeneration. Similarly, YKL-40, a glycoprotein primarily expressed by astrocytes, acts as an early indicator of neuroinflammation and disease progression [ 42 ]. Growing evidence suggests that YKL-40 is also a promising biomarker for glial inflammatory response in AD, with significantly elevated CSF levels reported in individuals with AD compared to those cognitively unimpaired [ 42 , 46 ], and also higher levels in APOE ε4 carriers with MCI [ 47 ]. Exercise modulates these neuroinflammatory markers in AD; CSF sTREM2 levels increase following physical activity, which may reflect transient microglial activation in response to acute exercise in individuals with AD [ 48 ]. However, it is important to note that individuals with AD typically exhibit elevated baseline CSF sTREM2 due to disease-related microglial activation [ 45 ], which may amplify the observed acute response. In contrast, our findings demonstrate that, in KL-VS HET , higher CRF is associated with lower CSF concentrations of both sTREM2 and YKL-40. This contrast suggests that while acute exercise may transiently activate microglia in individuals with AD, habitual exercise, reflected by higher CRF, may confer long-term neuroprotective effects by reducing chronic neuroinflammation in otherwise healthy populations. This implies a synergistic benefit of KL-VS HET and physical fitness, suggesting that exercise could offer targeted benefits in reducing AD-related neuroinflammation in certain populations. Additionally, in the present study, higher CRF was associated with elevated S100B levels regardless of KL-VS genotype, contrary to what would be expected based on the literature. Although S100B is generally linked to inflammatory processes [ 49 ], its upregulation in individuals with higher CRF could indicate an adaptive response, promoting repair and neurotrophic effects in the brain rather than solely reflecting pathological inflammation. Further investigation is needed to clarify the role of S100B within the context of fitness and neurodegeneration. Overall, our findings reinforce the idea that klotho, which is inherently higher in KL-VS HET , and CRF might interact to mitigate neuroinflammatory processes in AD, providing a promising approach for slowing disease progression. No significant interactions were observed for Aβ-related biomarkers. This is noteworthy given that the literature suggests that tau pathology might be more responsive to KL-VS heterozygosity compared to Aβ accumulation [ 4 ]. Moreover, KL-VS-related effects on Aβ are more pronounced in individuals carrying the APOE ε4 allele [ 13 ], potentially explaining the absence of significant findings related to Aβ in our sample. Further studies are needed to elucidate whether longitudinal fitness interventions yield stronger effects on these biomarkers in KL-VS HET , especially in APOE ε4-positive individuals. Together, the evidence underscores the complexity of genetic and environmental interplay in modulating AD-related biomolecular changes and emphasizes the importance of refining intervention strategies to target specific pathways and patient subgroups effectively [ 50 ]. This study is not without limitations. The cohort is predominantly white and well-educated, with a higher proportion of participants with parental history of AD or carrying at least one APOE ε4 allele compared to the general population. These characteristics may limit the generalizability of our results. Furthermore, as this is a cross-sectional study, we cannot assess the effects of the exposures on changes in CSF biomarker levels over time. Another potential limitation is the time lag between the lumbar puncture and the maximal graded exercise test; we did statistically adjust for this differential by incorporating the time lag as a covariate in the model. Notwithstanding the limitations, we believe this work makes a clinically meaningful contribution to the literature. Furthermore, WRAP and WADRC are ongoing longitudinal studies that continue to collect data and have also recently increased efforts to enroll participants from groups historically under-represented in research. Thus, future investigations will be able to examine how the interaction between KL-VS HET and VO 2peak relates to prospective changes in the biomarkers examined in this study in larger, more diverse samples. Overall, these findings suggest a positive synergy between KL-VS HET and better CRF. While the precise mechanisms by which the KL-VS HET genotype or CRF exerts protective effects are not entirely clear, a better understanding of lifestyle interventions aimed at improving fitness levels and genetic variants that modify AD risk hold promise to provide new avenues for prevention or treatment. Data Availability All data produced in the present study are available upon reasonable request to the authors. Conflict of Interest Statement All authors have no conflict of interest directly related to this study. S.C.J. has served on advisory boards for ALZPath and Enigma Biosciences. K.B. has served as a consultant, on advisory boards, or on data monitoring committees for Acumen, ALZPath, AriBio, BioArctic, Biogen, Eisai, Lilly, Moleac Pte. Ltd, Novartis, Ono Pharma, Prothena, Roche Diagnostics, and Siemens Healthineers; has served at data monitoring committees for Julius Clinical and Novartis; has given lectures, produced educational materials and participated in educational programs for AC Immune, Biogen, Celdara Medical, Eisai and Roche Diagnostics; and is a co-founder of Brain Biomarker Solutions in Gothenburg AB, which is a part of the GU Ventures Incubator Program (outside submitted work). H.Z. has served at scientific advisory boards and/or as a consultant for Abbvie, Acumen, Alector, Alzinova, ALZPath, Amylyx, Annexon, Apellis, Artery Therapeutics, AZTherapies, Cognito Therapeutics, CogRx, Denali, Eisai, LabCorp, Merry Life, Nervgen, Novo Nordisk, Optoceutics, Passage Bio, Pinteon Therapeutics, Prothena, Red Abbey Labs, reMYND, Roche, Samumed, Siemens Healthineers, Triplet Therapeutics, and Wave, has given lectures in symposia sponsored by Alzecure, Biogen, Cellectricon, Fujirebio, Lilly, Novo Nordisk, and Roche, and is a co-founder of Brain Biomarker Solutions in Gothenburg AB (BBS), which is a part of the GU Ventures Incubator Program (outside submitted work). G.K. is a full-time employee of Roche Diagnostics GmbH. C. Q.-R. is a full-time employee of Roche Diagnostics International Ltd. D.B.D . has consulted for Unity Biotechnology and S.V. Health Investors. All other authors have no relevant disclosures to report. Disclosures Klotho is the subject of an international patent issued and held by the Regents of the University of California. The NeuroToolKit is a panel of exploratory prototype assays designed to robustly evaluate biomarkers associated with key pathologic events characteristic of AD and other neurological disorders, used for research purposes only and not approved for clinical use (Roche Diagnostics International Ltd, Rotkreuz, Switzerland). Elecsys β-amyloid (1–42) and Elecsys Phospho-Tau (181P) CSF assays are approved for clinical use. COBAS and ELECSYS are trademarks of Roche. All other product names and trademarks are the property of their respective owners. Acknowledgements We would like to acknowledge and thank the staff and study participants of the Wisconsin Registry for Alzheimer’s Prevention and the Wisconsin Alzheimer’s Disease Research Center and the laboratory technicians at the Clinical Neurochemistry Laboratory at the Mölndal campus, University of Gothenburg, Sweden, without whom this work would not be possible. This work was supported by National Institute on Aging grants R01AG077507 (O.C.O.), R01AG062167 (O.C.O.), R01AG085592 (O.C.O.), R01AG027161 (S.C.J), R01AG021155 (S.C.J.), R01AG054059 (C.E.G.) and P30AG062715 (S.A.); by National Institute of Neurological Disorders and Stroke grant R01NS092918 (D.B.D.); and a Clinical and Translational Science Award (UL1RR025011) to the University of Wisconsin, Madison. Portions of this research were supported by the Veterans Administration, including facilities and resources at the Geriatric Research Education and Clinical Center of the William S. 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Okonkwo medRxiv 2025.02.27.25323056; doi: https://doi.org/10.1101/2025.02.27.25323056 Share This Article: Copy Citation Tools Older more fit KL-VS heterozygotes have more favorable AD-relevant biomarker profiles Mackenzie Jarchow , Ira Driscoll , Brianne M. Breidenbach , Noah Cook , Catherine L. Gallagher , Sterling C. Johnson , Sanjay Asthana , Bruce P. Hermann , Mark A. Sager , Kaj Blennow , Henrik Zetterberg , Cynthia M. Carlsson , Gwendlyn Kollmorgen , Clara Quijano-Rubio , Dane B. Cook , Dena B. Dubal , Ozioma C. 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