Distinct Cytokine and Cytokine Receptor Expression Patterns Characterize Different Forms of Myositis

Distinct Cytokine and Cytokine Receptor Expression Patterns Characterize Different Forms of Myositis | 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 Distinct Cytokine and Cytokine Receptor Expression Patterns Characterize Different Forms of Myositis Raphael A. Kirou , View ORCID Profile Iago Pinal-Fernandez , Maria Casal-Dominguez , Katherine Pak , Corinna Preusse , Dilbe Dari , Stefania Del Orso , Faiza Naz , Shamima Islam , Gustavo Gutierrez-Cruz , View ORCID Profile Elie Naddaf , Teerin Liewluck , Werner Stenzel , Albert Selva-O’Callaghan , Jose C. Milisenda , Andrew L. Mammen doi: https://doi.org/10.1101/2025.02.17.25321047 Raphael A. Kirou 1 Muscle Disease Section, National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health , Bethesda, MD, USA 2 College of Medicine, State University of New York Downstate Health Sciences University , Brooklyn, NY, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Iago Pinal-Fernandez 1 Muscle Disease Section, National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health , Bethesda, MD, USA 3 Department of Neurology, Johns Hopkins University School of Medicine , Baltimore, MD, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Iago Pinal-Fernandez Maria Casal-Dominguez 1 Muscle Disease Section, National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health , Bethesda, MD, USA 3 Department of Neurology, Johns Hopkins University School of Medicine , Baltimore, MD, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Katherine Pak 1 Muscle Disease Section, National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health , Bethesda, MD, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Corinna Preusse 4 Department of Neurology, Charité-Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health (BIH) , Berlin, Germany 5 Department of Neuropathology, Charité-Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health (BIH) , Berlin, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Dilbe Dari 4 Department of Neurology, Charité-Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health (BIH) , Berlin, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Stefania Del Orso 6 Genomic Technology Section, National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health , Bethesda, MD, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Faiza Naz 6 Genomic Technology Section, National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health , Bethesda, MD, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Shamima Islam 6 Genomic Technology Section, National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health , Bethesda, MD, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Gustavo Gutierrez-Cruz 6 Genomic Technology Section, National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health , Bethesda, MD, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Elie Naddaf 7 Division of Neuromuscular Medicine, Department of Neurology, Mayo Clinic , Rochester, MN, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Elie Naddaf Teerin Liewluck 7 Division of Neuromuscular Medicine, Department of Neurology, Mayo Clinic , Rochester, MN, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Werner Stenzel 4 Department of Neurology, Charité-Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health (BIH) , Berlin, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Albert Selva-O’Callaghan 8 Systemic Autoimmune Disease Unit, Vall d’Hebron Institute of Research , Barcelona, Spain 9 Autonomous University of Barcelona , Barcelona, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site Jose C. Milisenda 10 Muscle Research Unit, Internal Medicine Department, Hospital Clinic , Barcelona, Spain 11 Barcelona University , Barcelona, Spain 12 CIBERER , Barcelona, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site Andrew L. Mammen 1 Muscle Disease Section, National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health , Bethesda, MD, USA 3 Department of Neurology, Johns Hopkins University School of Medicine , Baltimore, MD, USA 13 Department of Medicine, Johns Hopkins University School of Medicine , Baltimore, MD, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: andrew.mammen{at}nih.gov Abstract Full Text Info/History Metrics Supplementary material Data/Code Preview PDF ABSTRACT Objective Myositis is a heterogeneous family of inflammatory myopathies. We sought to define the differential expression of cytokines, cytokine receptors, and immune checkpoint genes in muscle biopsies from patients with different forms of myositis in order to characterize patterns of inflammation in each. Methods Bulk RNA sequencing was performed on muscle biopsy samples from 669 patients, including 105 with dermatomyositis, 80 with immune-mediated necrotizing myopathy (IMNM), 65 with anti-synthetase syndrome, 53 with inclusion body myositis (IBM), 19 with anti-PM/Scl myositis, 310 with other inflammatory or genetic myopathies, and 37 controls with normal tissue (NT). Myositis clinical groups and autoantibody subgroups were analyzed separately. Expression data was analyzed for 338 genes encoding cytokines, cytokine receptors, and immune checkpoints. Myositis group-specific genes were identified from this list by finding genes that were specifically differentially expressed in one group compared to all samples and compared to NT (α<0.001). Results IBM patients had the most differentially overexpressed genes (71) among all clinical groups, including 37 that were IBM-specific. Among the top genes were several involved in type 1 inflammation, including CCL5 , CXCR3 , CCR5 , CXCL9 , and IFNG . Anti-Jo1 and anti-PM/Scl patients exhibited differential overexpression of a similar set of genes, while dermatomyositis patients exhibited differential overexpression of a different set of genes involved in type 1 inflammation. IMNM patients had the least number of differentially overexpressed genes with no predominant inflammatory pattern. Conclusion Each myositis clinical group and autoantibody subgroup had differentially overexpressed inflammatory mediators, including a strong type 1 inflammatory gene signature in IBM. Key Messages Inclusion Body Myositis (IBM) muscle biopsies exhibit differential overexpression of a set of genes involved in type 1 inflammation. The CCL5 - CCR5 and XCL1 - XCL2 - XCR1 axes are specifically differentially overexpressed in IBM muscle and may contribute to T C 1-mediated inflammation. Dermatomyositis, anti-Jo1 myositis, and anti-PM/Scl myositis muscle biopsies also exhibit overexpression of type 1 inflammatory genes, but to a lesser extent than IBM. INTRODUCTION Myositis refers to several major groups of inflammatory diseases of the skeletal muscle, including dermatomyositis (DM), immune-mediated necrotizing myopathy (IMNM), anti-synthetase syndrome (ASyS), inclusion body myositis (IBM), and overlap myositis, among others. Each of these clinical groups can be further divided into autoantibody subgroups, based on seropositivity for myositis autoantibodies. These include anti-Mi2 DM (Mi2), anti-MDA5 DM (MDA5), anti-NXP2 DM (NXP2), anti-TIF1γ DM (TIF1), anti-HMGCR IMNM (HMGCR), anti-SRP IMNM (SRP), anti-Jo1 ASyS (Jo1), and anti-PM/Scl overlap myositis (PM/Scl). Clinicopathologically-defined myositis groups and autoantibody-defined subgroups are characterized by distinct clinical phenotypes and muscle biopsy features with unique transcriptomic signatures[ 1 , 2 ]. Autoimmune diseases are frequently characterized by specific patterns of inflammation, including type I interferon (IFN-I)-mediated inflammation, type 1 (T helper 1-mediated) inflammation, type 2 (T helper 2-mediated) inflammation, and type 3 (T helper 17-mediated) inflammation, which can each be targeted by biologic agents[ 3 ]. Analyzing the expression of cytokines, cytokine receptors, and immune checkpoint genes could help us better understand disease-specific patterns of inflammation and their key mediators. In myositis, this could lead to the use of additional more targeted biologic agents, in addition to the current strategies of autoantibody depletion (e.g., rituximab, intravenous immunoglobulin) and targeting of a common cytokine receptor signaling pathway (e.g., Janus kinase inhibitors)[ 4 ]. For IBM in particular, where no immunosuppressants or other medications have been shown to be effective, identifying possible immunological targets is of special importance[ 5 ]. Thus far, studies of cytokine expression in skeletal muscle of myositis patients have been few and limited in scope[ 6 – 13 ]. A notable exception is the IFN-I pathway, which has been shown in multiple studies to be overactive in the muscle of juvenile and adult DM patients compared to other myositis patients and controls[ 6 , 7 , 14 – 17 ]. We previously showed that this is mainly driven by IFNB1 , whose transcript is detectable in muscle of >60% of DM patients and whose protein product (IFN-β) drives the expression of itself and IFN-I-inducible genes in cultured human myoblasts[ 18 ]. In addition, IFNG , the only type II IFN and an important mediator in type 1 inflammation, as well as IFN-II-inducible genes have been shown to be overexpressed in the muscle of IBM, ASyS, and DM patients as compared to IMNM and control patients[ 6 – 11 , 16 , 17 ]. Two of these studies examined muscle expression of a large number of cytokines in IBM, identifying cytokines overexpressed in IBM compared to healthy controls and other myositis patients. These included several cytokines involved in type 1 inflammation, such as CCL5 , CXCL9 , CXCL10 , CXCL11 , and TNF [ 6 , 8 ]. However, there remains a need to better characterize the cytokines and cytokine receptors specific to IBM and other myositis groups. In this study, we perform a comparison of the expression of 338 genes encoding cytokines, cytokine receptors, and immune checkpoints in the muscle biopsies of 669 myositis patients stratified by clinical group and autoantibody subgroup, in order to better characterize group-specific patterns of inflammation and identify potential therapeutic targets. METHODS Patients The classification process of skeletal muscle biopsies from 669 patients into clinical groups and autoantibody subgroups is outlined in the Supplemental Methods, with the classifications listed in Table 1 [ 19 – 21 ]. View this table: View inline View popup Download powerpoint Table 1. Patient samples analyzed by clinical group and autoantibody subgroup. Italicized groups were not analyzed separately but were included when calculating the differential expression of genes in groups of interest. RNA sequencing Bulk RNA-seq was performed on frozen muscle biopsy specimens as previously described[ 2 , 16 , 22 – 25 ]. Briefly, muscle biopsies underwent immediate flash freezing and were stored at -80°C across all contributing centers. Samples were then transported in dry ice to the NIH and processed uniformly to prepare the library and conduct the analysis. RNA was extracted with TRIzol. Libraries were either prepared with the NeoPrep system according to the TruSeq Stranded mRNA Library Prep protocol (Illumina, San Diego, CA) or with the NEBNext Poly(A) mRNA Magnetic Isolation Module and Ultra ™ II Directional RNA Library Prep Kit for Illumina (New England BioLabs, ref. #E7490, and #E7760). Gene Selection The selection process of 338 genes of interest, encoding cytokines, cytokine receptors, and immune checkpoints is outlined in the Supplementary Methods, with the genes listed and categorized in Supplementary Tables S1-S2[ 3 , 26 – 31 ]. Statistical and bioinformatic analysis For RNA-seq analysis, sequencing reads were demultiplexed using bcl2fastq/2.20.0 and preprocessed using fastp/0.23.4. The abundance of each gene was determined using Salmon/1.5.2. Counts were normalized using the Trimmed Means of M values (TMM) from edgeR/4.2.1 for graphical analysis. Differential expression was performed using limma/3.60.6. The Benjamin-Hochberg correction was used to adjust for multiple comparisons if appropriate. The set of genes associated with each myositis group of interest was generated by finding genes that were differentially expressed ( q -value 0) and under- (log-fold change > 0) expressed genes. The set of genes associated with NT was generated by finding genes that were differentially expressed ( q -value < 0.001) versus all samples. Venn diagrams were used to represent these analyses graphically. Heatmaps and individual boxplots were used to visualize gene expression for each group. Correlation heatmaps were generated by correlating expression of top overexpressed genes for each group with representative muscle and leukocyte markers, including markers of macrophages, dendritic cells, B cells, and T cell subsets. R and Python software were used to generate all figures. RESULTS Identification and Quantification of Differentially Expressed Genes by Group The differentially overexpressed and underexpressed genes for each myositis group and for NT are listed in Table 2 . Genes in a given cell of the table are listed from lowest q -value vs. all samples to highest ( q -value < 0.001). In order to visualize the group-specific and group-overlapping genes, Venn Diagram representations of Table 2 were generated (Supplementary Figure S1). Group-specific genes extrapolated from the Venn Diagrams are listed in Table 3 . View this table: View inline View popup Download powerpoint Table 2. All differentially expressed genes by clinical group and autoantibody subgroup. In order to be included in a given myositis group, genes must have had a q -value < 0.001 vs. all samples and vs. NT. In order to be included for NT, genes must have had a q -value < 0.001 vs. all samples. Genes are listed in order from lowest q -value to highest q -value vs. all samples. View this table: View inline View popup Download powerpoint Table 3. Myositis clinical group- and autoantibody subgroup-specific differentially expressed genes. Genes were included for a given myositis clinical group (DM, IMNM, ASyS, IBM, PM/Scl) if differentially expressed in that group and not differentially expressed in any other myositis group, except its autoantibody subgroups (e.g., HMGCR and SRP for IMNM). Genes were included for a given autoantibody subgroup (Mi2, MDA5, NXP2, TIF1, HMGCR, SRP, Jo1) if differentially expressed in that subgroup and not differentially expressed in any other group, except the clinical group it belongs to (e.g., IMNM for HMGCR). Among myositis clinical groups, IBM had the most differentially overexpressed genes (71), followed by DM (49), PM/Scl (26), IMNM (9), and ASyS (6). The autoantibody subgroup with the most differentially overexpressed genes (after PM/Scl) was Jo1 with 27, including all 6 genes differentially overexpressed in the clinical group it belongs to, ASyS. Among the DM autoantibody subgroups, Mi2 had the most differentially overexpressed genes (16), followed by NXP2 (15), TIF1 (6), and MDA5 (1). Among the IMNM autoantibody subgroups, HMGCR had the most differentially overexpressed genes (4), followed by SRP (1) ( Table 2 ). IBM had the most group-specific differentially overexpressed genes with 37, followed by DM and its autoantibody subgroups (36), PM/Scl (8), ASyS and its autoantibody subgroup (6), and IMNM and its autoantibody subgroups (5) (Supplementary Figure S1A). Among the 36 DM-specific genes, 8 were Mi2-specific, 7 were NXP2-specific, 1 was TIF1-specific, and none were MDA5-specific (Supplementary Figure S1B). Among the 5 IMNM-specific genes, 3 were HMGCR-specific and none were SRP-specific. The largest number of genes differentially overexpressed in more than one group was 11 for the pair IBM-PM/Scl, followed by 7 for the pairs DM-IBM and ASyS-IBM. The largest number of genes differentially overexpressed in three groups was 4 for the trio ASyS-IBM-PM/Scl. As expected by the nature of the analysis, there were no genes differentially overexpressed in all 5 groups. However, there were 117 genes differentially underexpressed in NT vs. all samples, an imperfect surrogate for pan-myositis overexpressed genes. Differentially underexpressed genes for myositis groups were very few, ranging from 0 to 3 per group. Genes differentially expressed in DM and correlation with muscle and leukocyte markers DM patients exhibited differential overexpression of 49 of the 338 genes examined (14%), of which 31 were specific to the DM clinical group (not including genes only overexpressed in a DM autoantibody subgroup but not in the clinical group). The top 5 DM-specific genes were TNFSF10 , GDF15 (a member of the TGFB family), IL1RN (interleukin-1 receptor antagonist, an IFN-I-inducible gene), IFNB1 , and TNFSF18 . CXCL11 , an IFN-II-inducible chemokine, was the third highest differentially overexpressed gene in DM, but was shared with Jo1 and IBM. The top 15 overexpressed genes in DM were negatively correlated with mature muscle markers ( ACTA1 , MYH1 , MYH2 ) and mitochondrial genes ( MT-CO1 , MT-CO2 ) and positively correlated with markers of muscle regeneration ( NCAM1 , MYOG , PAX7 , MYH3 , MYH8 ), indicating correlation with disease activity. The top 15 genes were also generally correlated with T cell markers ( CD3E , CD4 , CD8A ), macrophage markers ( CD68 , CD14 ), and markers of type 1 inflammation ( TBX21 , STAT1 ), more so than markers of type 2 inflammation ( GATA3 , STAT6 ) ( Figure 1A ). There was only 1 differentially underexpressed gene for DM patients, BMP6 (another member of the TGFB family). Download figure Open in new tab Figure 1. Correlation heatmaps for top differentially overexpressed genes by clinical group vs. muscle and leukocyte markers. For all heatmaps, the x-axis displays the top 15 differentially overexpressed genes for that clinical group, or all differentially overexpressed genes if there are less than 15, ordered from lowest q -value vs. all samples to highest. The y-axis displays mature muscle markers ( ACTA1 , MYH1 , MYH2 ), markers of muscle regeneration ( NCAM1 , MYOG , PAX7 , MYH3 , MYH8 ), mitochondrial markers ( MT-CO1 , MT-CO2 ), B cell markers ( CD19 , MS4A1 ), T cell markers ( CD3E , CD4 , CD8A ), macrophage markers ( CD14 , CD68 ), dendritic cell markers ( CD1C , CD1E ), type 1 markers ( TBX21 , STAT1 ), type 2 markers ( GATA3 , STAT6 ), and type 3 markers ( RORC , STAT3 ). Heatmaps displayed are for DM (A), IMNM (B), ASyS (C), IBM (D), and PM/Scl (E). Mi2 patients exhibited differential overexpression of 16 genes, of which 8 were not shared with any other DM autoantibody subgroup or non-DM group. These included 3 genes ( IL11 , IL1RAP , and TNFSF9 ) that were differentially overexpressed in Mi2 patients, but not in the DM clinical group, indicating strong Mi2 specificity. We previously established IL11 as one of the genes that is derepressed following the internalization of anti-Mi2 autoantibodies[ 25 ]. The top 15 differentially overexpressed genes in Mi2 patients exhibited characteristically strong negative correlation with mature muscle and mitochondrial markers and strong positive correlation with markers of muscle regeneration. They were also positively correlated with leukocyte markers, including B cell markers ( CD19 , MS4A1 ), T cell markers, macrophage markers, and markers of type 1 inflammation more so than markers of type 2 inflammation ( Figure 2A ). Download figure Open in new tab Figure 2. Correlation heatmaps for top differentially overexpressed genes by autoantibody subgroup vs. muscle and leukocyte markers. For all heatmaps, the x-axis displays the top 15 differentially overexpressed genes for that autoantibody subgroup, or all differentially overexpressed genes if there are less than 15, ordered from lowest q -value vs. all samples to highest. The y-axis displays mature muscle markers ( ACTA1 , MYH1 , MYH2 ), markers of muscle regeneration ( NCAM1 , MYOG , PAX7 , MYH3 , MYH8 ), mitochondrial markers ( MT-CO1 , MT-CO2 ), B cell markers ( CD19 , MS4A1 ), T cell markers ( CD3E , CD4 , CD8A ), macrophage markers ( CD14 , CD68 ), dendritic cell markers ( CD1C , CD1E ), type 1 markers ( TBX21 , STAT1 ), type 2 markers ( GATA3 , STAT6 ), and type 3 markers ( RORC , STAT3 ). Heatmaps displayed are for Mi2 (A), MDA5 (B), NXP2 (C), TIF1 (D), HMGCR (E), SRP (F), and Jo1 (G). MDA5 patients only exhibited differential overexpression of 1 gene ( TNFSF10 ), but this was not MDA5-specific. TNFSF10 was inversely correlated with mature muscle markers and mitochondrial markers, and strongly positively correlated with CD3E and macrophage markers in MDA5 patients ( Figure 2B ). NXP2 patients exhibited differential overexpression of 15 genes, of which 7 were not shared with any other DM autoantibody subgroup or non-DM group. These included 1 gene ( NAMPT ) that was differentially overexpressed in NXP2 patients, but not in the DM clinical group, indicating strong NXP2 specificity. The 15 differentially overexpressed genes in NXP2 also exhibited correlation with muscle markers and leukocyte markers, including macrophage markers and markers of type 1 inflammation, but correlations were weaker than for Mi2 patients ( Figure 2C ). TIF1 patients exhibited differential overexpression of 6 genes, of which 1 was not shared with any other group ( IL31RA ). The top differentially overexpressed genes in TIF1 exhibited similar levels of correlation with muscle markers and leukocyte markers as for NXP2 patients ( Figure 2D ). Genes differentially overexpressed in IMNM and correlation with muscle and leukocyte markers The IMNM patient group exhibited differential overexpression of only 9 of the 338 genes examined (3%). The top gene was SPP1 (osteopontin), which was also overexpressed in Jo1 patients. There were 5 IMNM-specific genes, including IL17B , IL13RA1 , IL10RB , CMTM7 , and MIF . All 9 genes were negatively correlated with mature muscle markers and mitochondrial genes and positively correlated with markers of muscle regeneration, indicating correlation with disease activity. There was less correlation with leukocyte markers, but SPP1 , OSMR , and CMTM7 were notably well correlated with CD4 and macrophage markers. There was no strong correlation between the 9 genes and markers of T subsets, indicating a lack of predominant type 1, type 2, or type 3 inflammation ( Figure 1B ). There was one gene differentially underexpressed in IMNM patients, the immune checkpoint CD274 (PD-L1). HMGCR patients exhibited differential overexpression of 4 genes ( IL17B , IL10RB , SPP1 , IL13RA1 ), which were all also differentially overexpressed in the IMNM clinical group. As with IMNM, these genes were correlated well with muscle markers, while SPP1 was strongly correlated with CD4 and macrophage markers ( Figure 2E ). SRP patients exhibited differential overexpression of only 1 gene ( SPP1 ). The same correlations between SPP1 and muscle and leukocyte markers were seen in the SRP group ( Figure 2F ). Genes differentially overexpressed in ASyS and correlation with muscle and leukocyte markers As mentioned previously, there were 27 genes differentially overexpressed in Jo1 patients, which included all 6 genes differentially overexpressed in ASyS patients, suggesting that Jo1 was the main source of this transcriptomic pattern. Of the 27 genes, there were only 6 that were ASyS/Jo1-specific ( CXCL8 , CCL20 , CCL3L3 , CD28 , CCL3 , and CSF2 ), with many overexpressed genes shared with the IBM (15), DM (8), and PM/Scl (6) groups. This included the top differentially overexpressed gene in Jo1 ( CXCL9 ), which was shared with IBM and PM/Scl. The top 15 differentially overexpressed genes in Jo1 were negatively correlated with mature muscle markers and mitochondrial markers, while all but CXCL8 were positively correlated with markers of muscle regeneration. The same genes were also generally correlated with leukocyte markers, especially for CD8 and markers of type 1 inflammation more than type 2 inflammation ( Figure 2G ). The same correlations were seen in the ASyS clinical group for the 6 overexpressed genes in ASyS patients ( Figure 1C ). Genes differentially overexpressed in IBM and correlation with muscle and leukocyte markers IBM patients exhibited differential overexpression of 71 of the 338 genes examined (21%), of which 37 were specific to IBM. The top 5 IBM-specific genes were CCL5 , CCR5 (the receptor for CCL5), ITGA4 , XCL1 , and XCL2 . XCR1 , a dendritic cell marker and the receptor for XCL1 and XCL2, was also specifically differentially overexpressed in IBM. The top 7 differentially overexpressed genes in IBM also included CD27 (a co-stimulatory protein on T cells), CXCR3 (a T H 1/T C 1 marker), IL2RG (a common cytokine receptor subunit), the IFN-II-inducible chemokine CXCL9 , and IFNG . The top 15 differentially overexpressed genes in IBM were negatively correlated with mature muscle markers and mitochondrial markers, while all but TNFRSF17 were positively correlated with markers of muscle regeneration. The same genes were also strongly correlated with leukocyte markers, especially CD8 and type 1 inflammatory cells slightly more than type 2 inflammatory cells, but also macrophages and dendritic cells ( Figure 1D ). There were three differentially underexpressed genes in IBM patients, CRLF1 , CTF1 , and NAMPT . Genes differentially overexpressed in PM/Scl and correlation with muscle and leukocyte markers PM/Scl patients exhibited differential overexpression of 26 of the 338 genes examined (8%), of which 8 were specific to PM/Scl. The top 5 PM/Scl-specific genes were TNFRSF25 , TNFRSF4 , LTB , CX3CL1 , and EBI3 (a common subunit of IL-27 and IL-35). The top 5 differentially overexpressed genes in PM/Scl also included CXCL13 and CD27 . The top 15 differentially overexpressed genes in PM/Scl were generally negatively correlated with mature muscle markers and mitochondrial markers, but also largely negatively correlated or not correlated with markers of muscle regeneration. The same genes were strongly correlated with leukocytes including T cells (both type 1 and type 2 inflammation), macrophages, and dendritic cells ( Figure 1E ). There was one differentially underexpressed gene in PM/Scl, the type 2 alarmin cytokine TSLP . Genes associated with type 1 inflammation are comparatively enriched in IBM, PM/Scl, Jo1, and DM patients Given the observed correlations of overexpressed genes and markers of type 1 and type 2 inflammation, we also sought to compare the expression of markers of type 1, type 2, and type 3 inflammation we previously defined in Supplementary Table S2. For each gene, the q -value of differential overexpression and log-fold change for each group are shown in Supplementary Tables S3-S5. For visualization, we generated a heatmap of the median expression of these genes for each of the autoantibody subgroups, IBM, and NT ( Figure 3 ). Download figure Open in new tab Figure 3. Heatmap of type 1, type 2, and type 3 gene expression by group. The heatmap displays median expression levels of type 1, type 2, and type 3 genes for each group. Groups included are all autoantibody subgroups (Mi2, MDA5, NXP2, TIF1, HMGCR, SRP, Jo1, PM/Scl), as well as IBM (no autoantibody subgroup) and NT (control). Expression of markers associated with type 1 inflammation predominated over markers of type 2 and type 3 inflammation in DM, Jo1, IBM, and PM/Scl patients, while none of the three were particularly overexpressed in IMNM ( Figure 3 ). In particular, Jo1, IBM, and PM/Scl patients exhibited shared overexpression of a particular set of markers associated with type 1 inflammation, generally distinct from the set overexpressed in DM patients ( Figure 3 , Supplemental Table 3). IBM patients had the most differentially overexpressed markers of type 1 inflammation (12), of which 2/3 were also differentially overexpressed in one or more other groups ( CCL4 , CXCL9 , CXCL10 , CXCL11 , CXCR3 , IFNG , IL27 , and LTA ). The most IBM-specific markers of type 1 inflammation were the ligand-receptor pair CCL5 - CCR5 (first and sixth most differentially overexpressed genes in IBM), while IBM patients also exhibited markedly higher median expression of the T H 1/T C 1 marker CXCR3 and IFNG than other groups. PM/Scl patients exhibited markedly higher median expression of LTA and EBI3 than other groups. Notably, there were four differentially overexpressed markers of type 1 inflammation unique to DM patients ( IL12RB2 , TNFRSF1A , and the ligand-receptor pair IL18 - IL18R1 ), while they also exhibited markedly higher median expression of CXCL11 than the other groups. Markers of type 2 inflammation were generally less commonly overexpressed among myositis groups ( Figure 3 , Supplemental Table 4). A notable exception was PM/Scl, where the top two differentially overexpressed genes, TNFRSF25 and TNFRSF4 , are both implicated in type 2 inflammation. Other notable markers of type 2 inflammation that were group-specific were AREG (DM), CCL11 (DM), IL13RA1 (IMNM), CCL17 (IBM), and IL5RA (IBM). Markers of type 3 inflammation were even less commonly overexpressed among the myositis groups, with exceptions being IL22RA1 in DM and CCL20 in Jo1 ( Figure 3 , Supplemental Table 5). DISCUSSION Our findings add support to previous work implicating mediators of type 1 inflammation in the pathogenesis of IBM. For example, it has been demonstrated that highly differentiated CD8 + T cells are elevated in muscle and peripheral blood of IBM patients, including TBX21 + CD8 + T cells (T C 1 cells) in particular[ 8 , 11 , 32 , 33 ]. Previous studies have also shown elevated muscle levels of numerous cytokines associated with type 1 inflammation, including CCL5 , CXCL9 , CXCL10 , CXCL11 , IFNG , and TNF in IBM patients compared to various myositis and non-myositis controls[ 6 , 8 – 11 ]. Similar elevations of cytokines associated with type 1 inflammation, including CXCL9, CXCL10, IFN-γ, IL-12, and TNF have been demonstrated at the protein level in serum of IBM patients versus non-myositis controls[ 11 , 34 ]. In our study, we confirmed the elevation of these cytokines in IBM, while also finding a strong correlation between the most differentially overexpressed inflammatory mediators in IBM and CD8A and TBX21 . Furthermore, we found that the T H 1/T C 1 markers CXCR3 and CCR5 were differentially overexpressed in IBM, with higher median expression than in any other myositis group. The CCL5 - CCR5 ligand-receptor pair was particularly specific for IBM, representing the top two IBM-specific differentially overexpressed genes. Interestingly, an allelic variant of CCR5 resulting in a non-functional receptor (CCR5Δ32) is thought to be protective against IBM according to a large genetic association study[ 35 ]. Furthermore, CCR5 is a macrophage entry receptor for R5-tropic strains of the human immunodeficiency virus (HIV), which has been associated with IBM[ 36 ]. Taken together, the CCL5 - CCR5 axis seems to be particularly important to the type 1 inflammation in IBM and could represent a therapeutic target. CCR5 inhibitors are indicated for HIV infection and have been in clinical trials for a variety of other autoimmune diseases, including rheumatoid arthritis, graft-versus-host disease, and primary sclerosing cholangitis[ 37 ]. Furthermore, antigen-presenting dendritic cells have also been implicated in IBM inflammation[ 38 ]. Here, we found the type 1 conventional dendritic cell marker XCR1 and its ligands, XCL1 and XCL2 , to be overexpressed in IBM patients and IBM-specific. The XCL1 - XCR1 interaction activates T C 1 cells and has been implicated in other autoimmune disorders with type 1 inflammation, including sarcoidosis, Crohn’s disease, and rheumatoid arthritis [ 39 , 40 ]. Although IBM has proved to be refractory to corticosteroids and some other immunosuppressants, this may be due to the durable nature of highly differentiated CD8 + T cells in evading cell death mechanisms, and they may be more susceptible to more targeted therapeutics[ 5 ]. Our findings also demonstrated a similar overexpression of markers of type 1 inflammation in Jo1 and PM/Scl patients, albeit weaker than in IBM. For Jo1, the IFN-II-inducible chemokine CXCL9 was the top differentially overexpressed gene, while the neutrophil chemoattractant CXCL8 was the most Jo1-specific differentially overexpressed gene. Both have been previously shown to be elevated in serum of ASyS patients compared to healthy controls[ 41 , 42 ]. In PM/Scl, besides type 1 genes, we identified several PM/Scl-specific differentially overexpressed genes, including TNFRSF25 and TNFRSF4 . In DM, our data also revealed a strong type 1 inflammation pattern, but the specific type 1 genes that were most differentially overexpressed (e.g., IL18 and IL12RB2 ) were different from those in IBM, Jo1, and PM/Scl. IFNB1 was the fourth most differentially overexpressed gene analyzed in DM, consistent with our previous results demonstrating a strong type I IFN signature in DM[ 16 , 18 ]. The top three DM-specific differentially overexpressed genes were TNFSF10 , GDF15 , and IL1RN , which have all been studied as potential biomarkers for DM[ 43 – 45 ]. Finally, IMNM had the least number of differentially overexpressed genes among myositis clinical groups with no predominant inflammatory pattern. Our study has several limitations. Firstly, we only measured RNA, so the results reflect muscle expression of cytokines rather than circulating cytokines. Secondly, we used bulk RNA sequencing, so we were not able to distinguish cellular sources of gene expression. Thirdly, sample sizes between groups varied, which impacted q -values. The variable sample sizes also meant that some groups were weighed more than others when calculating differential expression. Finally, the differential expression analysis was designed to identify group-specific genes, rather than common overexpressed genes among multiple groups. In conclusion, we identified differentially overexpressed cytokines, cytokine receptors, and immune checkpoints in different myositis clinical groups and autoantibody subgroups. Our results point to a predominance of type 1 inflammation in IBM, Jo1, and PM/Scl, while DM patients exhibited overexpression of a different set of type 1 inflammatory genes, in addition to a strong Type I IFN signature. Our results also highlight the CCL5 - CCR5 and XCL1 - XCL2 - XCR1 axes as especially IBM-specific, potentially representing therapeutic targets. Funding This study was funded, in part, by the Intramural Research Program of the National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health. Conflict of interest statement The authors report no conflicts of interest. Contributorship All authors contributed to the development of the manuscript, including interpretation of results, substantive review of drafts, and approval of the final draft for submission. Ethical approval information All biopsies were from subjects enrolled in institutional review board (IRB)-approved longitudinal cohorts in the National Institutes of Health, the Johns Hopkins, the Clinic Hospital, the Vall d’Hebron Hospital, the Mayo Clinic, and the Charité-Universitätsmedizin Berlin. Patient and public involvement Patients and/or the public were not involved in the design, conduct, reporting, or dissemination plans of this research. 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Download PDF Supplementary Material Data/Code Email Thank you for your interest in spreading the word about medRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following Distinct Cytokine and Cytokine Receptor Expression Patterns Characterize Different Forms of Myositis Message Subject (Your Name) has forwarded a page to you from medRxiv Message Body (Your Name) thought you would like to see this page from the medRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share Distinct Cytokine and Cytokine Receptor Expression Patterns Characterize Different Forms of Myositis Raphael A. Kirou , Iago Pinal-Fernandez , Maria Casal-Dominguez , Katherine Pak , Corinna Preusse , Dilbe Dari , Stefania Del Orso , Faiza Naz , Shamima Islam , Gustavo Gutierrez-Cruz , Elie Naddaf , Teerin Liewluck , Werner Stenzel , Albert Selva-O’Callaghan , Jose C. Milisenda , Andrew L. Mammen medRxiv 2025.02.17.25321047; doi: https://doi.org/10.1101/2025.02.17.25321047 Share This Article: Copy Citation Tools Distinct Cytokine and Cytokine Receptor Expression Patterns Characterize Different Forms of Myositis Raphael A. Kirou , Iago Pinal-Fernandez , Maria Casal-Dominguez , Katherine Pak , Corinna Preusse , Dilbe Dari , Stefania Del Orso , Faiza Naz , Shamima Islam , Gustavo Gutierrez-Cruz , Elie Naddaf , Teerin Liewluck , Werner Stenzel , Albert Selva-O’Callaghan , Jose C. Milisenda , Andrew L. 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