APOE4 genotype and MAPT haplotype modify repetitive head impact biomarkers in retired professional fighters

APOE4 genotype and MAPT haplotype modify repetitive head impact biomarkers in retired professional fighters | 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 APOE4 genotype and MAPT haplotype modify repetitive head impact biomarkers in retired professional fighters View ORCID Profile Xiaowei Zhuang , Dietmar Cordes , Lynn Bekris , Edwin C. Oh , Charles Bernick doi: https://doi.org/10.1101/2025.09.19.25335803 Xiaowei Zhuang 1 Lou Ruvo Center for Brain Health, Cleveland Clinic , Las Vegas, NV89106, United States 2 Laboratory of Neurogenetics and Precision Medicine, College of Sciences, University of Nevada , Las Vegas, Las Vegas, NV89154, United States Ph.D. Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Xiaowei Zhuang Dietmar Cordes 1 Lou Ruvo Center for Brain Health, Cleveland Clinic , Las Vegas, NV89106, United States 3 University of Colorado Boulder , Boulder, CO80309, United States Ph.D. Find this author on Google Scholar Find this author on PubMed Search for this author on this site Lynn Bekris 4 Department of Laboratory Medicine and Pathology, School of Medicine, University of Washington , WA98915, United States Ph.D. Find this author on Google Scholar Find this author on PubMed Search for this author on this site Edwin C. Oh 2 Laboratory of Neurogenetics and Precision Medicine, College of Sciences, University of Nevada , Las Vegas, Las Vegas, NV89154, United States 5 Department of Internal Medicine, Kirk Kerkorian School of Medicine at University of Nevada , Las Vegas, Las Vegas, NV89154, United States Ph.D. Find this author on Google Scholar Find this author on PubMed Search for this author on this site Charles Bernick 1 Lou Ruvo Center for Brain Health, Cleveland Clinic , Las Vegas, NV89106, United States M.D. Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: bernicc{at}ccf.org Abstract Full Text Info/History Metrics Data/Code Preview PDF Abstract Long-term vulnerability to brain injury after repetitive head impacts (RHI) is poorly predicted in vivo. The wide heterogeneity of outcomes suggests that common genetic variants may act as modifiers of RHI-related neurodegeneration. Here, we tested whether APOE ε4 and MAPT H1/H2 haplotypes function as genetic modifiers of biomarker trajectories in 111 retired professional fighters from the Professional Athletes Brain Health Study (PABHS), the largest systematically characterized living cohort of fighters. RHI exposure was indexed by lifetime number of professional bouts. Primary outcomes included plasma GFAP (astroglial activation), NfL (axonal injury), and hippocampal volumes, measured cross-sectionally and longitudinally. Pre-specified linear models tested exposure × genotype interactions with false-discovery-rate correction. Across genotypes, greater fight exposure was associated with higher GFAP and smaller hippocampal volume. APOE ε4 modified longitudinal GFAP responses, with carriers showing stronger exposure-related increases than noncarriers, consistent with heightened astroglial reactivity. Conversely, the MAPT H2 haplotype mitigated associations between exposure, NfL, and hippocampal atrophy, suggesting partial protection against neuroaxonal injury and structural decline. Exploratory analyses showed MAPT H1/H1 enrichment among fighters meeting traumatic encephalopathy syndrome (TES) criteria (OR=3.33). Plasma p-tau231 was unrelated to exposure, indicating these effects are unlikely to reflect concurrent Alzheimer-type tau pathology. Together, these findings provide in vivo evidence that APOE and MAPT act as genetic modifiers of RHI-related brain injury, complementing postmortem evidence linking MAPT to chronic traumatic encephalopathy and highlighting the potential of genotype-informed monitoring in contact-sport populations. Significance Statement Repetitive head impacts (RHI) can lead to lasting brain damage, but not everyone exposed to RHI experiences the same outcomes. In retired fighters, we show that common genetic variants influence whether individuals are more vulnerable or resilient to brain inflammation and injury after repeated trauma. Specifically, APOE4 increased susceptibility, while a MAPT H2 variant appeared protective. These results provide the first in vivo evidence that inherited genetic differences modify long-term brain responses to RHIs. Incorporating genetic risk into studies of brain injury could enable earlier identification of at-risk individuals and support more personalized strategies for monitoring, prevention, and intervention. Introduction Professional fighters are routinely exposed to repetitive head impacts (RHI) during both sanctioned matches and intensive training, substantially elevating their risk for long-term neurological conditions including chronic traumatic encephalopathy (CTE) 1 , 2 . RHI is a well-established primary driver of CTE pathology 3 , with greater exposure linked to altered blood-and brain-based biomarkers in professional fighters 4 – 6 . However, not all fighters with comparable RHI exposure develop the same degree of neurological impairment, suggesting that additional factors, such as genetic predisposition, may act as modifiers of susceptibility 2 , 7 . Defining genetic influences on RHI-related biomarkers could improve risk stratification, inform training practices, and guide development of personalized strategies to mitigate long-term neurological damage. Several genes have been studied in this context 8 . The Apolipoprotein E (APOE) E4 allele, a well-established risk factor for sporadic Alzheimer’s disease (AD) 9 , 10 , has been linked to pathological mechanisms including neuroaxonal injury, neuroinflammation, neurometabolic changes and neurotoxicity, all of which are implicated in both single episode and repetitive head trauma 11 , 12 . Post-mortem analysis of 364 CTE brain donors demonstrated that APOE4 was associated with more advanced CTE stages and increased phosphorylated tau (ptau) burden in individuals over 65, suggesting a potential role of APOE4 in CTE pathogenesis 7 . Yet its contribution to other RHI-related pathologies, such as chronic neuroinflammation or axonal injury, remains unclear. In vivo studies of APOE4 in fighters and athletes have produced inconclusive results 13 – 15 , often limited by small samples, cross-sectional designs, and the inclusion of both active and retired athletes, which reduces statistical power and generalizability. Beyond APOE , the microtubule-associated protein tau (MAPT) gene is also of interest. MAPT encodes the tau protein that becomes hyperphosphorylated and forms neurofibrillary tangles (NFTs) in various neurodegenerative disorders including CTE 16 . The MAPT H2 haplotype has been reported to confer protection against certain sporadic and primary tauopathies like progressive supranuclear palsy (PSP), compared to the more common H1 haplotype 16 – 18 . Although tauopathy is central to CTE, limited studies have examined the influence of MAPT haplotype on CTE neuropathology or RHI-related biomarkers. One study found a trend towards a higher frequency of MAPT H1/H1 carriers in athletes with CTE compared to those without 19 . More recently, a structural haplotype in the 17q21.31 region (encompassing MAPT ) was significantly associated with dementia and post-mortem tau-burdens in CTE-affected brain regions 20 . Nevertheless, to our knowledge, no studies to date have investigated the influence of MAPT haplotype on in vivo biomarkers reflecting various RHI-related neuropathological processes. The Professional Athletes Brain Health Study (PABHS), a longitudinal study of RHI effects in living fighters 21 , provides a unique opportunity to fill this gap. Prior work using PABHS data has linked fighting exposures to increased plasma levels of neurofilament light chain (NfL) and glial fibrillary astrocytic protein (GFAP) levels 22 – 25 , as well as reduced hippocampal volumes 4 , 5 , 25 , 26 . GFAP reflects astrocytic activation and neuroinflammation 27 , NfL is a marker of axonal injury 28 , and hippocampal volume loss indicates neuronal degeneration. Together, these biomarkers capture processes central to RHI-related neurodegeneration. With the recent addition of genotyping data, PABHS now enables direct investigation of whether genetic factors moderate these biomarker changes. In this study, we tested whether APOE4 and MAPT haplotype act as genetic modifiers of these biomarker trajectories. We hypothesized that greater fight exposure would associate with adverse biomarker changes post-retirement and that APOE4 and MAPT H1/H1 carriers would show greater vulnerability compared to their counterparts. Methods Participants This study is part of the PABHS approved by the Cleveland Clinic Institutional Review Board (IRB protocol #10-944). Details of PABHS have been previously reported 21 , 22 We included fighters (boxers, mixed martial artists (MMA), and martial artists (MA)) with available genotyping data and at least one visit classified as post-retirement. We focused on retired fighters to rule out effects of acute head trauma on biomarker levels. Fighting histories, including numbers of professional fights (nof_pro) and last fighting dates, were verified using Boxrec ( www.boxrec.com ) for boxers and Sherdog ( www.sherdog.com ) for MMAs and MAs. Cumulative RHI exposure was quantified as the nof_pro throughout the career. We defined qualified visits as occurring at least two years post-retirement. The final analytical sample comprised 111 retired fighters with blood biomarkers and MRI data collected at qualified visits. ( blue boxes in Fig. 1 ). Download figure Open in new tab Figure 1. Flow diagram of participant inclusion. Of 151 retired fighters enrolled in the Professional Athletes Brain Health Study (PABHS), exclusions were due to missing genotyping, inconsistent fight histories, or absence of biomarker/MRI data. The final Core Baseline Cohort comprised 111 fighters with blood or MRI biomarkers, and a Core Longitudinal Cohort of 74 fighters contributed ≥2 qualified post-retirement visits. MRI scans were required to pass a signal-to-noise ratio (SNR) >14. Abbreviations: MRI, magnetic resonance imaging; SNR, signal-to-noise ratio; PABHS, Professional Athletes Brain Health Study. Real-time polymerase chain reaction (PCR) for APOE and MAPT genotyping APOE and MAPT single nucleotide polymorphisms (SNPs) were genotyped using allelic discrimination PCR in the Bekris Lab at the Cleveland Clinic main campus 29 . APOE genotype was determined by SNPs rs429358 and rs7412, while MAPT haplotypes were determined via SNP rs1800547 that tags to haplotype 30 . Retired fighters were categorized into APOE4 carriers (i.e. C/C or C/T at rs429358) or non-carriers (i.e. T/T at rs429358), and MAPT H1/H1 carriers (A/A at rs1800547) or H2 carriers (A/G or G/G at rs1800547), respectively. Fighting-related blood- and brain-based biomarkers Blood-based biomarkers: Venipuncture was performed at fighters’ annual visit. Plasma NfL and GFAP concentrations were measured using ultrasensitive molecule array assays (Quanterix, Billerica, MA, USA) at the Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital (Mölndal, Sweden). A subset of fighters had plasma ptau-231 measured following published protocols 31 . All procedures were performed by board-certified laboratory technicians blinded to clinical data and followed manufacturer specifications. Brain-based biomarkers: High-resolution T1-weighted structural MRI was acquired on a 3T Siemens scanner during fighters’ annual visit using a standard 3D MPRAGE sequence (TR=2300ms, TE=2.98ms, TI=900ms, flip angle=9°, in-plane resolution=1mmx1mm, slice thickness=1.2mm). Hippocampal volumes were calculated using the FreeSurfer 6.0 longitudinal processing pipeline 32 . A signal-to-noise ratio (SNR) was computed for every scan using the FreeSurfer quality assessment tool, and only data with a SNR>14 was utilized in the following analyses ( Fig. 1 ). Statistical analysis Demographic differences between genetic groups were assessed using Chi-square tests for categorical variables and two-sample t-tests for continuous variables. Linear regression models were utilized to evaluate the genetic effect on the relationship between nof_pro and each biomarker. For cross-sectional analysis, biomarker measure from the first qualified visit of each retired fighter (i.e., Baseline) served as the dependent variable; while nof_pro, genotype, and their interactions were the independent variables. Additional covariates included sex, age at measurement, years of education, race and types of fighters. Total intracranial volume was included as a covariate brain regional volume analysis. For longitudinal analysis, the annual rate of change for each biomarker was first estimated for retired fighters with multiple qualified visits. The same linear regression model was applied to evaluate the genetic effect on biomarkers’ annual rate of change. For measures showing an interaction effect between genotype and nof_pro (i.e., p-value for interaction term ≤0.05), post-hoc partial correlations (r) between nof_pro and the biomarker or biomarker annual changing rate were calculated within each genotype group, adjusting for covariates using regression coefficients estimated in the regression model. In addition, false discovery rate method (FDR-p) was utilized to correct for total 48 multiple corrections, given that we were interested in effects of fighting exposure, genotype and interaction terms on both cross-sectional and longitudinal blood- and brain-based biomarkers (i.e., 3x2x2x4). Results Participants The Core Baseline Cohort included 111 retired fighters (91.9% male; mean [SD] age, 46.2 [9.5]) with verified fight histories, genotyping, and blood or MRI data passing quality control ( Table 1 ). Race differed significantly between MAPT groups, with H2 carriers rare among African American participants (p=0.002). MAPT H1/H1 carriers were more likely to meet consensus criteria for traumatic encephalopathy syndrome (TES; OR=3.33, p=0.007). A Core Longitudinal Cohort of 74 fighters (mean [SD] follow-up 5.2 [2.1] years) contributed biomarker trajectories ( Supplementary Table 1 ). Twelve participants (2 with no MRI, 10 failing SNR QC) were excluded from hippocampal analyses. View this table: View inline View popup Download powerpoint Table 1. Characteristics of 111 retired fighters with genotyping and biomarker data, stratified by APOE4 carrier status and MAPT haplotype. Values are reported as mean [SD] unless otherwise specified. TES = traumatic encephalopathy syndrome. Group comparisons were tested using t-tests for continuous variables and χ² tests for categorical variables. Genetic influence on neuroinflammation biomarker profiles Significant positive associations were observed between nof_pro and GFAP levels at the first qualified post-retirement visit (i.e., Baseline) in models with either APOE (β=1.324, SE=0.349, p=0.0003, FDR-p=0.012) or MAPT (β=1.021, SE=0.387, p=0.010, FDR-p=0.077, Fig. 2 ) as genetic factors. Higher number of fights was correlated with higher GFAP levels across all genetic subgroups (solid lines in last columns). Download figure Open in new tab Figure 2. Cross-sectional associations of lifetime fight exposure (x-axis) with plasma NfL (top panels) and GFAP (bottom panels) at the first qualified post-retirement visit. Results are stratified by (A, C) APOE4 status and (B, D) MAPT haplotype. Non-carriers ( APOE4 – or MAPT H1/H1) are shown in blue; carriers ( APOE4 + or MAPT H2) in red. Regression lines reflect associations with 95% confidence interval shading. Violin plots show baseline biomarker distributions by genotype. For models with significant moderation (p<0.05), adjusted partial correlations (r) are reported. Solid regression lines indicate significant partial correlations in individual genotype groups. FDR correction was applied across cross-sectional and longitudinal analyses. While longitudinal GFAP changes did not significantly correlate with fighting exposure across the entire cohort, APOE4 carrier status significantly moderated this association (β=0.857, SE=0.296, p=0.005, FDR-p=0.049, Fig. 3 ). APOE4 carriers showed a stronger positive relationship between nof_pro and longitudinal GFAP increases (partial-r=0.497) compared to non-carriers (partial-r=-0.133). Approximately 75.34% of retired fighters exhibited GFAP increases during the observation period. Download figure Open in new tab Figure 3. Longitudinal associations of lifetime fight exposure (x-axis) with annualized change in plasma NfL (top panels) and GFAP (bottom panels). Results are stratified by (A, C) APOE4 status and (B, D) MAPT haplotype. Non- carriers (APOE4– or MAPT H1/H1) are shown in blue; carriers ( APOE4 + or MAPT H2) in red. Regression lines reflect associations with 95% confidence interval shading. . Violin plots display average biomarker change per year by genotype group. Moderation effects with p<0.05 are annotated with partial correlations (r) adjusted for covariates. Solid regression lines indicate significant partial correlations in individual genotype groups. FDR correction was applied across families of analyses. Genetic influences on neuroaxonal injury biomarker profiles Baseline NfL levels did not correlate with fighting exposure across the entire cohort. The MAPT H2 significantly moderated this relationship (β=-0.143, SE=0.057, p=0.014, FDR-p=0.084, Fig. 2 ), with MAPT H1/H1 carriers showing a positive association (partial-r=0.236), while H2 carriers exhibited a negative association (partial-r=-0.268). MAPT further moderated the relationship between nof_pro and longitudinal NfL changes at trend level significance (β=0.081, SE=0.037, p=0.032, FDR-p=0.118, Fig. 3 ). In addition, MAPT H2 carriers showed significantly attenuated longitudinal NfL increases compared to H1/H1 carriers (β=-3.543, SE=1.219, p=0.005, FDR-p=0.049). Around 40% of MAPT H2 carriers (8/20) showed decreasing NfL levels over time, with this NfL recovery effect diminishing as nof_pro increased. Two retired fighters did not undergo MRI, and structural MRI scans from ten fighters at their first qualified post-retirement visit failed quality control. Therefore, these 12 fighters were not included in the analysis of hippocampal volumes. Nof_pro was significantly associated with reduced left hippocampal volumes (β=-15.424, SE=5.358, p=0.005, FDR-p=0.049), with this negative relationship consistent across all genetic subgroups (solid lines in last column plots in Supplementary Fig. 1). No significant genetic moderation effects were observed on cross-sectional hippocampal volumes. Longitudinal analysis demonstrated that greater fighting exposure significantly associated with accelerated left hippocampal volume loss (β=-1.035, SE=0.319, p=0.002, FDR-p=0.048, Fig. 4 ). This relationship was further moderated by MAPT haplotype (β=1.250, SE=0.539, p=0.024, FDR-p=0.115), with H1/H1 carriers exhibiting more pronounced nof_pro-related volume loss compared to H2 carriers (partial-r=-0.496 vs. 0.105). Similar moderation patterns were observed for the right hippocampal volume loss (β=1.344, SE=0.625, p=0.044, Fig. 4 ). Download figure Open in new tab Figure 4. Longitudinal associations of lifetime fight exposure (x-axis) with annualized change in hippocampal volume (y-axis), stratified by APOE4 status (A, C) and MAPT haplotype (B, D). Left hippocampus (top panels) and right hippocampus (bottom panels) are shown separately. Non-carriers (APOE4– or MAPT H1/H1) are plotted in blue; carriers ( APOE4 + or MAPT H2) in red. Regression lines with 95% CI shading depict exposure-outcome relationships. Partial correlations are reported when interaction p<0.05. Solid regression lines indicate significant partial correlations in individual genotype groups. FDR correction was applied across cross-sectional and longitudinal analyses. . Discussion In this study of 111 retired professional fighters, we examined whether the APOE4 allele and MAPT H2 haplotype modify the relationship between repetitive head impact (RHI) exposure and in vivo biomarkers of neurodegeneration. Across the cohort, greater fighting exposure was associated with elevated baseline GFAP, reduced hippocampal volume, and accelerated hippocampal atrophy, reinforcing the link between RHI and both neuroinflammatory and neurodegenerative processes. Importantly, genetic variation moderated these associations: MAPT H2 carriers exhibited relatively preserved hippocampal volumes and attenuated NfL elevations, while APOE4 carriers showed steeper longitudinal GFAP increases, suggesting heightened astroglial reactivity. Effect of RHI and APOE4 on neuroinflammation GFAP is a well-established biomarker of astrocytic activation and neuroinflammation 33 . Following severe TBI, GFAP levels would peak during a 12-hour window and may remain elevated into the chronic phase due to the persistent astrogliosis 34 , 35 . Meta-analyses suggest that APOE4 carriers experience worse clinical and neuropsychological outcomes months to years after TBI, though with a small effect-size 11 , 36 , 37 , potentially through mechanisms including exacerbated direct neurotoxicity, modulation of tau pathology, disruption of the blood-brain barrier, and increased inflammation and oxidant injury 11 . In the context of RHI, sustained GFAP elevation likely result from subsequent head traumas occurring before complete recovery to homeostasis from prior injuries, leading to prolonged astroglia activation and persistent neuroinflammation, which could be further exacerbated in APOE4 carriers. Previous PABHS data demonstrated elevated GFAP levels in both active and retired fighters compared to controls 23 ( Supplementary Fig. 3), corroborating these RHI-related neuroinflammatory changes. Our finding that a greater number of professional bouts associates with higher baseline GFAP levels approximately 10.8 years post-retirement, regardless of APOE4 status, additionally highlight the dose-dependent and enduring nature of RHI-related neuroinflammatory responses. Importantly, APOE4 status influenced the longitudinal trajectory of GFAP, with only APOE4 carriers demonstrating a significant positive relationship between fight number and GFAP increases over time ( Fig. 3 ). This finding supports our hypothesis that APOE4 carriers may experience more pronounced neuroinflammatory responses to RHI compared to non-carriers. However, both elevated GFAP and APOE4 carrier status are associated with increased AD risks 10 . To address the possibility that underlying AD pathology might explain these findings, we conducted additional analyses in a subset of fighters with measured plasma ptau-231, a validated AD biomarker that correlates with post-mortem AD pathology and in vivo amyloid/tau positivity 31 . We found no association between fighting exposure and either baseline ptau-231 levels or longitudinal ptau-231 changes in either APOE4 carriers or non-carriers ( Supplementary Fig. 2 ) , suggesting the observed GFAP findings are not driven by coexisting AD pathology in this cohort. Collectively, these results indicate that APOE4 may augment the neuroinflammatory response to RHI and suggest that elevated blood GFAP levels, when considered alongside APOE4 genotype, may help identify retired fighters at increased risk for CTE-related neurodegeneration. Effect of RHI and MAPT haplotype on neuroaxonal damage Blood-based NfL is an established biomarker of neuroaxonal injury 28 . Previous studies have documented acute NfL elevations following head trauma, such as after a single bout in Olympic boxers 38 , and throughout a season in American football players 39 . Our previous PABHS investigation demonstrated elevated NfL levels in active but not retired fighters 22 , 23 . Consistent with these reports, the present study found no significant associations between cumulative fighting exposure and either cross-sectional NfL levels or longitudinal NfL changes across the entire retired cohort. Instead, we observed that MAPT haplotype significantly moderates these associations ( Figs 2 and 3 ), suggesting that while NfL effectively reflects acute neural injury during active RHI exposure, its utility in characterizing long-term neurobiological changes post-retirement may depend on genetic factors. The MAPT H1 haplotype has been strongly associated with various primary tauopathies such as PSP 16 – 18 . Sub-haplotypes or structural variants such as H1c and H1β1γ1 have been further linked to increased risks of AD 40 and CTE 20 , respectively. In our cohort, a significantly greater proportion of retired fighters diagnosed with TES were MAPT H1/H1 carriers (odds ratio=3.33, p =0.007; Table 1 ), highlighting the potential role of MAPT in modulating susceptibility to neurodegeneration following RHI 19 . Our analysis provides novel in vivo evidence for a protective role of the H2 haplotype against long-term axonal degenerations, with H1/H1 carriers showing a positive association between fighting exposure and NfL levels, while H2 carriers demonstrated a negative association ( Fig 2 ). This protective effect was further supported by the longitudinal NfL variations, where a substantial proportion of H2 carriers with lower fighting exposure exhibited decreasing NfL concentrations over time, potentially indicating neurobiological recovery post-retirement 6 . Yet, this protective effect appeared to diminish with increasing fighting exposure, suggesting a potential RHI-dependent loss of resilience ( Fig. 3 ). We further examined this moderation effect using hippocampal volume as an anatomical marker of neurodegeneration, which is also known to be vulnerable in CTE 41 . While the hippocampus showed reduced volumes with greater fighting exposure across all genetic subgroups, longitudinal analyses revealed that only MAPT H1/H1 carriers exhibited significant hippocampal atrophy with increasing exposure ( Fig. 4 ). These convergent findings suggest the MAPT H2 haplotype confers neuroprotective effects against RHI-related structural and molecular neurodegeneration, with important implications for identifying individuals at differential risk and developing targeted monitoring strategies. Limitations We used the number of professional fights (nof_pro) as a proxy for cumulative RHI exposure in retired fighters. While previous research from PABHS has validated nof_pro as a reasonable proxy for fighting-related head impacts 21 , and we cross-referenced fight histories with online records to ensure accuracy, nof_pro may not capture unrecorded exposures such as those incurred during training. Future studies would benefit from a more comprehensive and individualized assessment of RHI exposure. To boost the statistical power, we included both male and female retired fighters. However, the small number of female participants and sex-specific RHI responses could bias our results. Reanalysis restricted to male fighters revealed the same moderation effects of APOE4 on longitudinal GFAP variation and MAPT haplotype on NfL levels ( Supplementary Table 2 ). Furthermore, the MAPT H2 haplotype is predominantly found in Caucasians, and our inclusion of all racial groups may have introduced additional bias. Reanalyzing MAPT -related data in only Caucasian male fighters did not fully replicate our results, with only a trend-level significance remained for cross-sectional and longitudinal NfL variations ( Supplementary Table 2 ). Future studies with larger cohorts will be necessary to further confirm these findings. The biomarkers analyzed in this study (GFAP, NfL, and hippocampal volumes) are not specific to CTE, which limits our ability to draw direct conclusions about CTE pathology. Instead, the findings reflect genetic influences on broader RHI-related processes of neuroinflammation, axonal injury, and structural brain change. We also found no significant associations between RHI or genetic factors and plasma p-tau231 in retired fighters, suggesting that this tau marker may not capture RHI-related neurodegeneration. Given the established relevance of p-tau231 in Alzheimer’s disease (AD), these results support the view that AD and CTE involve overlapping but distinct neurodegenerative mechanisms. Future research incorporating both AD patients and healthy controls will be essential to clarify the specificity of genetic and biomarker signatures in RHI-related outcomes. Conclusion In this cohort of 111 retired fighters from PABHS, APOE4 carrier status was associated with increased vulnerability to RHI-related neuroinflammation, while the MAPT H2 haplotype appeared to mitigate RHI-associated axonal injury and hippocampal atrophy, suggesting partial genetic protection. These findings provide the first in vivo evidence that common genetic variants shape long-term trajectories of astroglial activation and neuroaxonal degeneration after repetitive head impacts, complementing post-mortem evidence implicating MAPT structural haplotypes in chronic traumatic encephalopathy. Incorporating genetic risk profiling into studies of RHI-related neurodegeneration may enable earlier identification of high-risk individuals and support the development of genotype-informed monitoring and prevention strategies, with replication in larger and more diverse cohorts needed to refine these applications. Transparency, Rigor, and Reproducibility Statement This study is part of the PABHS. The study protocol of PABHS have been previously reported 21 , 22 . It included a general analytic plan, although the analysis plan for this specific article was not formally pre-registered. A total of 151 retired fighters in PABHS (as of Dec. 2024) were screened, and the final sample included 111 retired fighters with genotyping information, verified fighting histories, and at least one visit occurring two or more years post-retirement (as detailed in Fig. 1 ). Data for the study were collected by research staff who were blind to the relevant characteristics of the participants. The blood- and brain-based biomarker measures in the current analyses were not provided to the participants. A deidentified data set for this study is not available in a public archive. However, a deidentified participant data set and a data dictionary used to reproduce reported results can be made available upon reasonable request from a qualified investigator, subject to a signed data access agreement as allowable according to the institutional ethics board standard, by contacting the senior author (CB: bernickc{at}ccf.org). Data Availability All data produced in the present study are available upon reasonable request to the authors Authorship confirmation/contribution statement XZ: conceptualization, methodology, formal analysis, visualization, writing original draft and review & editing. DC: methodology, visualization, and review & editing the manuscript. LB : data collection, visualization, and review & editing the manuscript. ECO : conceptualization, methodology, visualization, and review & editing the manuscript. CB : conceptualization, data collection, methodology, visualization, and review and editing the manuscript. Funding Statement Funding for this project came from Lincy Foundation, Belator, Ultimate Fighting Championship Company (UFC), the August Rapone Family Foundation, Top Rank, Haymon Boxing, and the National Institutes of Health (NIA-grant 1RF1AG071566, NIGMS-grant P20GM109025 and NIA-grant P20AG068053). Author(s’) disclosure (Conflict of Interest) statement(s) The author(s) have no competing interest to disclose. Ethics approval This study is part of the PABHS that is approved by the Cleveland Clinic Institutional Review Board (IRB protocol #10-944). Written informed consent has been obtained from all participants. The protocols of the experiment have been explained to all subjects and performed according to the Declaration of Helsinki guidelines and Belmont Report. Supplementary Figure 1. Cross-sectional associations between lifetime fight exposure (x-axis) and hippocampal volume, stratified by APOE4 status (A, C) and MAPT haplotype (B, D). Left (top panels) and right (bottom panels) hippocampi are shown separately. Non-carriers ( APOE4 – or MAPT H1/H1) are plotted in blue; carriers ( APOE4 + or MAPT H2) in red. Regression lines with 95% CI shading depict exposure–volume relationships. Violin plots display baseline hippocampal volumes by genotype. Interaction p-values are shown; FDR-significant associations are indicated with solid lines. Supplementary Figure 2. Cross-sectional (A, B) and longitudinal (C, D) associations between lifetime fight exposure (x-axis) and plasma p-tau231, stratified by APOE4 status (A, C) and MAPT haplotype (B, D). Non-carriers (APOE4– or MAPT H1/H1) are shown in blue; carriers ( APOE4 + or MAPT H2) in red. Regression lines with 95% CI shading depict exposure-outcome relationships. Violin plots illustrate baseline distributions or annualized changes by genotype. No associations were FDR-significant. Supplementary Figure 3. Schematic summary of observed associations among RHI exposure, genetic factors, and biomarker variation in retired fighters. Solid black lines indicate previously reported associations in PABHS; grey lines indicate significant main effects of RHI exposure in the current study; dashed orange lines represent moderation effects of APOE4 ; dashed purple lines represent moderation effects of MAPT H2. Double lines denote findings added in the present analysis. Only associations with p<0.05 are displayed; ** indicates FDR-significant associations. View this table: View inline View popup Supplementary Table 1. Demographic and clinical characteristics of the 74 retired fighters contributing longitudinal biomarker data, stratified by APOE4 carrier status and MAPT haplotype. Values are mean [SD] unless otherwise specified. Between-group differences were assessed with t-tests for continuous variables and χ² tests for categorical variables. TES = traumatic encephalopathy syndrome. View this table: View inline View popup Supplementary Table 2. Significance of APOE4 and MAPT H2 moderation effects across biomarker outcomes. P-values are shown for all retired fighters, male-only analyses, and Caucasian male-only analyses (for MAPT ). Outcomes include baseline NfL and GFAP, annualized change (Δ) in NfL and GFAP, and annualized change in left and right hippocampal volumes. FDR-corrected results are bolded in the main text; nominal associations are reported here for completeness. References 1. ↵ Alosco ML , Stern RA . The long-term consequences of repetitive head impacts: Chronic traumatic encephalopathy . Handb Clin Neurol . 2019 ; 167 : 337 – 355 . doi: 10.1016/B978-0-12-804766-8.00018-2 OpenUrl CrossRef PubMed 2. ↵ Stern RA , Riley DO , Daneshvar DH , Nowinski CJ , Cantu RC , McKee AC . Long-term Consequences of Repetitive Brain Trauma: Chronic Traumatic Encephalopathy . PM and R . 2011 ; 3 ( 10 SUPPL. 2 ): S460 – S467 . doi: 10.1016/j.pmrj.2011.08.008 OpenUrl CrossRef PubMed Web of Science 3. ↵ McKee AC , Daneshvar DH , Alvarez VE , Stein TD . The neuropathology of sport . Acta Neuropathol . 2014 ; 127 ( 1 ): 29 . doi: 10.1007/S00401-013-1230-6 OpenUrl CrossRef PubMed 4. ↵ Bernick C , Banks SJ , Shin W , et al. Repeated head trauma is associated with smaller thalamic volumes and slower processing speed: The Professional Fighters’ Brain Health Study . Br J Sports Med . 2015 ; 49 ( 15 ): 1007 – 1011 . doi: 10.1136/bjsports-2014-093877 OpenUrl Abstract / FREE Full Text 5. ↵ Mishra VR , Zhuang X , Sreenivasan KR , et al. Multimodal MR Imaging Signatures of Cognitive Impairment in Active Professional Fighters . Radiology . 2017 ; 285 ( 2 ). doi: 10.1148/radiol.2017162403 OpenUrl CrossRef 6. ↵ Zhuang X , Bennett L , Nandy R , Cordes D , Bernick C , Ritter A . Longitudinal Changes in Cognitive Functioning and Brain Structure in Professional Boxers and Mixed Martial Artists after They Stop Fighting . Neurology . 2022 ; 99 ( 20 ): E2275 – E2284 . doi: 10.1212/WNL.0000000000201158 OpenUrl CrossRef PubMed 7. ↵ Atherton K , Han X , Chung J , et al. Association of APOE Genotypes and Chronic Traumatic Encephalopathy . JAMA Neurol . 2022 ; 79 ( 8 ): 787 – 796 . doi: 10.1001/JAMANEUROL.2022.1634 OpenUrl CrossRef PubMed 8. ↵ Abdolmohammadi B , Dupre A , Evers L , Mez J . Genetics of Chronic Traumatic Encephalopathy . Semin Neurol . 2020 ; 40 ( 4 ): 420 – 429 . doi: 10.1055/S-0040-1713631 OpenUrl CrossRef PubMed 9. ↵ Bellenguez C , Küçükali F , Jansen IE , et al. New insights into the genetic etiology of Alzheimer’s disease and related dementias . Nat Genet . 2022 ; 54 ( 4 ): 412 – 436 . doi: 10.1038/s41588-022-01024-z OpenUrl CrossRef PubMed 10. ↵ Raber J , Huang Y , Ashford JW . ApoE genotype accounts for the vast majority of AD risk and AD pathology . Neurobiol Aging . 2004 ; 25 ( 5 ): 641 – 650 . doi: 10.1016/j.neurobiolaging.2003.12.023 OpenUrl CrossRef PubMed Web of Science 11. ↵ McFadyen CA , Zeiler FA , Newcombe V , et al. Apolipoprotein E4 Polymorphism and Outcomes from Traumatic Brain Injury: A Living Systematic Review and Meta-Analysis . J Neurotrauma . 2021 ; 38 ( 8 ): 1124 . doi: 10.1089/NEU.2018.6052 OpenUrl CrossRef PubMed 12. ↵ Shahim P , Gill JM , Blennow K , Zetterberg H . Fluid Biomarkers for Chronic Traumatic Encephalopathy . Semin Neurol . 2020 ; 40 ( 4 ): 411 – 419 . doi: 10.1055/S-0040-1715095 OpenUrl CrossRef PubMed 13. ↵ Barry D. , Jordan MM , Norman R. , Relkin MP , Lisa D. , Ravdin P , Alan R. , Jacobs M , Alexandre Bennett P , Sam Gandy MP. Apolipoprotein E ∈4 Associated With Chronic Traumatic Brain Injury in Boxing . JAMA: The Journal of the American Medical Association . 1997 ; 278 ( 2 ): 136 . doi: 10.1001/jama.1997.03550020068040 OpenUrl CrossRef PubMed Web of Science 14. Banks SJ , Miller JB , Rissman RA , Bernick CB . Lack of Influence of Apolipoprotein e Status on Cognition or Brain Structure in Professional Fighters . J Neurotrauma . 2017 ; 34 ( 2 ): 380 – 384 . doi: 10.1089/neu.2016.4453 OpenUrl CrossRef PubMed 15. ↵ Kristman VL , Tator CH , Kreiger N , et al. Does the apolipoprotein ε4 allele predispose varsity athletes to concussion? A prospective cohort study . Clinical Journal of Sport Medicine . 2008 ; 18 ( 4 ): 322 – 328 . doi: 10.1097/JSM.0B013E31817E6F3E OpenUrl CrossRef PubMed 16. ↵ Gallo D , Ruiz A , Sánchez-Juan P . Genetic Architecture of Primary Tauopathies . Neuroscience . 2023 ; 518 : 27 – 37 . doi: 10.1016/J.NEUROSCIENCE.2022.05.022 OpenUrl CrossRef PubMed 17. Labbé C , Heckman MG , Lorenzo-Betancor O , et al. MAPT haplotype H1G is associated with increased risk of dementia with Lewy bodies . Alzheimers Dement . 2016 ; 12 ( 12 ): 1297 – 1304 . doi: 10.1016/J.JALZ.2016.05.002 OpenUrl CrossRef PubMed 18. ↵ Kouri N , Murray ME , Reddy JS , et al. Latent trait modeling of tau neuropathology in progressive supranuclear palsy . Acta Neuropathol . 2021 ; 141 ( 5 ): 667 . doi: 10.1007/S00401-021-02289-0 OpenUrl CrossRef PubMed 19. ↵ Bieniek KF , Ross OA , Cormier KA , et al. Chronic traumatic encephalopathy pathology in a neurodegenerative disorders brain bank . Acta Neuropathol . 2015 ; 130 ( 6 ): 877 – 889 . doi: 10.1007/S00401-015-1502-4/METRICS OpenUrl CrossRef PubMed 20. ↵ Han X , Zhang Y , Petrosky JN , et al. A structural haplotype in the 17q21.31 MAPT region is associated with increased risk for chronic traumatic encephalopathy endophenotypes . Cell Rep Med . 2025 ; 0 ( 0 ): 102084 . doi: 10.1016/J.XCRM.2025.102084 OpenUrl CrossRef 21. ↵ Bernick C , Banks S , Phillips M , et al. Professional fighters brain health study: Rationale and methods . Am J Epidemiol . 2013 ; 178 ( 2 ): 280 – 286 . doi: 10.1093/aje/kws456 OpenUrl CrossRef PubMed Web of Science 22. ↵ Bernick C , Zetterberg H , Shan G , Banks S , Blennow K . Longitudinal Performance of Plasma Neurofilament Light and Tau in Professional Fighters: The Professional Fighters Brain Health Study . J Neurotrauma . 2018 ; 35 ( 20 ): 2351 – 2356 . doi: 10.1089/neu.2017.5553 OpenUrl CrossRef PubMed 23. ↵ Bernick C , Shan G , Ritter A , et al. Blood biomarkers and neurodegeneration in individuals exposed to repetitive head impacts . Alzheimers Res Ther . 2023 ; 15 ( 1 ). doi: 10.1186/S13195-023-01310-W OpenUrl CrossRef 24. Zhuang X , Bennett L , Nandy R , Cordes D , Bernick C , Ritter A . Longitudinal Changes in Cognitive Functioning and Brain Structure in Professional Boxers and Mixed Martial Artists after They Stop Fighting . Neurology . 2022 ; 99 ( 20 ): E2275 – E2284 . doi: 10.1212/WNL.0000000000201158 OpenUrl Abstract / FREE Full Text 25. ↵ Bernick C , Shan G , Zetterberg H , et al. Longitudinal change in regional brain volumes with exposure to repetitive head impacts . Neurology . 2020 ; 94 ( 3 ): e232 – e240 . doi: 10.1212/WNL.0000000000008817 OpenUrl Abstract / FREE Full Text 26. ↵ Bennett L , Bernick C , Banks S . Relationship Between Verbal Fluency Performance, Fight Exposure, and Subcortical Region Brain Volumes in Professional Fighters . Archives of Clinical Neuropsychology . 2019 ; 34 ( 5 ): 735 . doi: 10.1093/arclin/acz026.05 OpenUrl CrossRef 27. ↵ Bignami A , Eng LF , Dahl D , Uyeda CT . Localization of the glial fibrillary acidic protein in astrocytes by immunofluorescence . Brain Res . 1972 ; 43 ( 2 ): 429 – 435 . doi: 10.1016/0006-8993(72)90398-8 OpenUrl CrossRef PubMed Web of Science 28. ↵ Zetterberg H , Blennow K . Fluid biomarkers for mild traumatic brain injury and related conditions . Nat Rev Neurol . 2016 ; 12 ( 10 ): 563 – 574 . doi: 10.1038/NRNEUROL.2016.127 OpenUrl CrossRef PubMed 29. ↵ Bekris LM , Millard S , Lutz F , et al. Tau Phosphorylation Pathway Genes and Cerebrospinal Fluid Tau Levels in Alzheimer’s Disease . Am J Med Genet B Neuropsychiatr Genet . 2012 ; 0 ( 7 ): 874 . doi: 10.1002/AJMG.B.32094 OpenUrl CrossRef 30. ↵ Sánchez-Juan P , Moreno S , de Rojas I , et al. The MAPT H1 Haplotype Is a Risk Factor for Alzheimer’s Disease in APOE ε4 Non-carriers . Front Aging Neurosci . 2019 ; 11 : 327 . doi: 10.3389/FNAGI.2019.00327 OpenUrl CrossRef 31. ↵ Ashton NJ , Pascoal TA , Karikari TK , et al. Plasma p-tau231: a new biomarker for incipient Alzheimer’s disease pathology . Acta Neuropathol . 2021 ; 141 ( 5 ): 709 . doi: 10.1007/S00401-021-02275-6 OpenUrl CrossRef PubMed 32. ↵ Fischl B. FreeSurfer . Neuroimage. 2012 ; 62 ( 2 ): 774 – 781 . doi: 10.1016/j.neuroimage.2012.01.021 OpenUrl CrossRef PubMed Web of Science 33. ↵ Jack CR , Andrews JS , Beach TG , et al. Revised criteria for diagnosis and staging of Alzheimer’s disease: Alzheimer’s Association Workgroup . Alzheimer’s & Dementia. Published online 2024 . doi: 10.1002/ALZ.13859 OpenUrl CrossRef 34. ↵ Hossain I , Marklund N , Czeiter E , Hutchinson P , Buki A . Blood biomarkers for traumatic brain injury: A narrative review of current evidence . Brain & Spine . 2024 ; 4 : 102735 . doi: 10.1016/J.BAS.2023.102735 OpenUrl CrossRef 35. ↵ Halicki MJ , Hind K , Chazot PL . Blood-Based Biomarkers in the Diagnosis of Chronic Traumatic Encephalopathy: Research to Date and Future Directions . Int J Mol Sci . 2023 ; 24 ( 16 ). doi: 10.3390/IJMS241612556 OpenUrl CrossRef 36. ↵ Zeng S , Jiang JX , Xu MH , et al. Prognostic Value of Apolipoprotein E Epsilon4 Allele in Patients with Traumatic Brain Injury: A Meta-Analysis and Meta-Regression . https://home.liebertpub.com/gtmb . 2014 ; 18 ( 3 ): 202 – 210 . doi: 10.1089/GTMB.2013.0421 OpenUrl CrossRef 37. ↵ Zhou W , Xu DI , Peng X , Zhang Q , Jia J , Crutcher KA . Meta-Analysis of APOE4 Allele and Outcome after Traumatic Brain Injury . J Neurotrauma . 2008 ; 25 : 279 – 290 . doi: 10.1089/neu.2007.0489 OpenUrl CrossRef PubMed Web of Science 38. ↵ Neselius S , Brisby H , Theodorsson A , Blennow K , Zetterberg H , Marcusson J . CSF-Biomarkers in Olympic Boxing: Diagnosis and Effects of Repetitive Head Trauma . PLoS One . 2012 ; 7 ( 4 ). doi: 10.1371/JOURNAL.PONE.0033606 OpenUrl CrossRef 39. ↵ Oliver JM , Jones MT , Kirk KM , et al. Serum Neurofilament Light in American Football Athletes over the Course of a Season . https://home.liebertpub.com/neu . 2016 ; 33 ( 19 ): 1784 – 1789 . doi: 10.1089/NEU.2015.4295 OpenUrl CrossRef 40. ↵ Myers AJ , Kaleem M , Marlowe L , et al. The H1c haplotype at the MAPT locus is associated with Alzheimer’s disease . Hum Mol Genet . 2005 ; 14 ( 16 ): 2399 – 2404 . doi: 10.1093/HMG/DDI241 OpenUrl CrossRef PubMed Web of Science 41. ↵ Cherry JD , Esnault CD , Baucom ZH , et al. Tau isoforms are differentially expressed across the hippocampus in chronic traumatic encephalopathy and Alzheimer’s disease . Acta Neuropathol Commun . 2021 ; 9 ( 1 ): 1 – 17 . doi: 10.1186/S40478-021-01189-4/FIGURES/11 OpenUrl CrossRef PubMed View the discussion thread. Back to top Previous Next Posted September 21, 2025. Download PDF 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. 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