Blood-based Transcriptomics Reveal Sex- and Amyloid-Modulated Biology of Plasma pTau217 in Preclinical Alzheimer’s Disease

Blood-based Transcriptomics Reveal Sex- and Amyloid-Modulated Biology of Plasma pTau217 in Preclinical Alzheimer’s Disease | bioRxiv /* */ /* */ <!-- <!-- /*! * 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-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Blood-based Transcriptomics Reveal Sex- and Amyloid-Modulated Biology of Plasma pTau217 in Preclinical Alzheimer’s Disease Mabel Seto , Hannah M. Klinger , Michelle Clifton , Vaibhav A Janve , Jane A. Brown , Colin Birkenbihl , Gillian Coughlan , Diana L. Townsend , Ting-Chen Wang , Michael Properzi , Bernard Hanseeuw , View ORCID Profile Jasmeer Chhatwal , View ORCID Profile Hyun-Sik Yang , View ORCID Profile Robert A. Rissman , Paul Aisen , Madison Cuppels , Michael C. Donohue , Rema Raman , Keith A. Johnson , Reisa A. Sperling , Logan Dumitrescu , View ORCID Profile Timothy J. Hohman , View ORCID Profile Rachel F. Buckley doi: https://doi.org/10.1101/2025.11.21.689770 Mabel Seto 1 Massachusetts General Hospital/Harvard Medical School , Boston, MA 2 Brigham and Women’s Hospital , Boston, MA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Hannah M. Klinger 1 Massachusetts General Hospital/Harvard Medical School , Boston, MA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Michelle Clifton 3 Vanderbilt Memory & Alzheimer’s Center, Vanderbilt University Medical Center , Nashville, TN Find this author on Google Scholar Find this author on PubMed Search for this author on this site Vaibhav A Janve 3 Vanderbilt Memory & Alzheimer’s Center, Vanderbilt University Medical Center , Nashville, TN Find this author on Google Scholar Find this author on PubMed Search for this author on this site Jane A. Brown 1 Massachusetts General Hospital/Harvard Medical School , Boston, MA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Colin Birkenbihl 1 Massachusetts General Hospital/Harvard Medical School , Boston, MA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Gillian Coughlan 1 Massachusetts General Hospital/Harvard Medical School , Boston, MA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Diana L. Townsend 1 Massachusetts General Hospital/Harvard Medical School , Boston, MA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ting-Chen Wang 3 Vanderbilt Memory & Alzheimer’s Center, Vanderbilt University Medical Center , Nashville, TN Find this author on Google Scholar Find this author on PubMed Search for this author on this site Michael Properzi 1 Massachusetts General Hospital/Harvard Medical School , Boston, MA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Bernard Hanseeuw 1 Massachusetts General Hospital/Harvard Medical School , Boston, MA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Jasmeer Chhatwal 1 Massachusetts General Hospital/Harvard Medical School , Boston, MA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Jasmeer Chhatwal Hyun-Sik Yang 2 Brigham and Women’s Hospital , Boston, MA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Hyun-Sik Yang Robert A. Rissman 4 Alzheimer’s Therapeutic Research Institute, Keck School of Medicine of the University of Southern California , San Diego, CA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Robert A. Rissman Paul Aisen 4 Alzheimer’s Therapeutic Research Institute, Keck School of Medicine of the University of Southern California , San Diego, CA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Madison Cuppels 1 Massachusetts General Hospital/Harvard Medical School , Boston, MA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Michael C. Donohue 4 Alzheimer’s Therapeutic Research Institute, Keck School of Medicine of the University of Southern California , San Diego, CA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Rema Raman 4 Alzheimer’s Therapeutic Research Institute, Keck School of Medicine of the University of Southern California , San Diego, CA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Keith A. Johnson 1 Massachusetts General Hospital/Harvard Medical School , Boston, MA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Reisa A. Sperling 1 Massachusetts General Hospital/Harvard Medical School , Boston, MA 2 Brigham and Women’s Hospital , Boston, MA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Logan Dumitrescu 3 Vanderbilt Memory & Alzheimer’s Center, Vanderbilt University Medical Center , Nashville, TN Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: rfbuckley{at}mgh.harvard.edu Timothy J. Hohman 3 Vanderbilt Memory & Alzheimer’s Center, Vanderbilt University Medical Center , Nashville, TN Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Timothy J. Hohman For correspondence: rfbuckley{at}mgh.harvard.edu Rachel F. Buckley 1 Massachusetts General Hospital/Harvard Medical School , Boston, MA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Rachel F. Buckley For correspondence: rfbuckley{at}mgh.harvard.edu Abstract Full Text Info/History Metrics Supplementary material Preview PDF Abstract Plasma pTau217, an emerging Alzheimer’s disease (AD) biomarker, may reflect a synaptic response to β-amyloid (Aβ) plaques before cortical tangle formation, but the broader biological processes at play remain unclear. Using whole blood RNAseq, we sought to identify gene expression associated with plasma pTau217 and to determine whether APOE ε4, sex, and neocortical Aβ-PET burden further amplify these associations in 724 participants from the Anti-Amyloid Treatment in Asymptomatic Alzheimer’s (A4) and Longitudinal Evaluation of Amyloid Risk and Neurodegeneration (LEARN) Studies. 1,540 genes were moderated by Aβ-PET, and 772 genes were moderated by both Aβ-PET and sex. Our findings include genes previously associated with AD (e.g., TREML2 ) and implicate biological functions such as chromatin remodeling, lipid signaling, and RNA processing that interact with Aβ-PET and sex to impact plasma pTau217. Our results underscore the complexity of molecular mechanisms that can be linked to plasma pTau217, particularly in the context of elevated Aβ-PET. Introduction Over the past few years, phosphorylated tau at threonine 217 (pTau217) has become one of the most sensitive blood-based biomarkers for Alzheimer’s disease (AD). 1 It has outperformed other pTau species (such as pTau181) in detecting abnormal AD brain pathology at the earliest stages of disease. 2 , 3 In cognitively unimpaired older adults, higher plasma pTau217 is associated with elevated neocortical amyloid-β (Aβ) PET and tau-PET burden. 2 , 4 pTau217 is closely associated with Aβ-PET burden; higher pTau217 is apparent in those with abnormal Aβ-PET even if tau-PET levels are low 5 . Work comparing distinct CSF pTau species suggest that pTau217 rises earliest in the preclinical phase of AD, 1 aligning with elevations in neocortical Aβ. Higher plasma pTau217 also predicts future cognitive decline 6 and progression to mild cognitive impairment (MCI) and dementia 5 , 7 – 9 , underscoring its role as an early marker of disease. Despite this sensitivity, the biological processes driving increases in plasma pTau217 remain poorly understood. Recent neuropathological studies have shown that pTau217 levels may be selective for AD pathology and very closely reliant on the presence of Aβ plaques. For instance, pTau217 appears in synapses surrounding Aβ plaques 10 even prior to overt tau neurofibrillary tangle formation and is associated with signals of synaptic loss and stress, such as granulovacuolar degeneration and the appearance of multivesicular bodies 11 . Together, these findings point to the presence of pTau217 as a very early signal of Aβ deposition prior to tau tangle formation. And while they provide some answers as to what pTau217 might be signaling, they remain elusive as to why . Relevant peripheral biological pathways that might be associated with elevated plasma pTau217 are unknown, particularly in the context of abnormal Aβ burden and APOE ε4 carriership, a genetic risk allele associated with Aβ and increased risk of AD dementia 12 . Sex represents another critical, and often overlooked, factor when considering the earliest AD pathophysiological changes. Women not only show a higher prevalence of AD dementia but also appear more vulnerable to tau pathology as measured with tau-PET 13 , 14 . Elevated pTau217 predicts faster tau accumulation much more strongly in women compared with men 15 , supporting the notion sex plays a role in shaping the trajectory of biomarker changes. Beyond hormonal influences, the whole genome – including the X chromosome – is increasingly being found to play a central role. A growing body of work shows that genetic associations with AD endophenotypes differ by sex 16 , suggesting the involvement of distinct sex-specific biological pathways. Sex chromosomes themselves are also an important but understudied contributor 17 . The X chromosome, which accounts for approximately 5% of the genome 18 , harbors many brain-expressed genes 19 , and has been implicated in AD through genetic studies 16 , 17 , 20 . Yet X-linked mechanisms, particularly transcriptomic signals in whole blood that could illuminate the regulation of pTau217, have rarely been examined in the earliest phases of disease. The overall aim of this study was to identify associations between whole blood gene expression, including both the autosome and the X chromosome, and plasma pTau217 levels, including moderating associations with Aβ-PET, APOE ε4 and sex, in more than 700 cognitively unimpaired older adults. Methods We analyzed 724 cognitively unimpaired participants drawn the A4 clinical trial (n = 445) and the adjoining LEARN observational study (n = 279) 21 , 22 . Eligibility for the current analysis required availability of a single 18 F-florbetapir Aβ-PET scan, plasma pTau217, whole blood RNAseq data, and APOE genotype. All data come from the pre-randomization screening visit. The A4 study protocol was approved by institutional review boards (IRBs) at each study site, with all participants providing written informed consent. This work was conducted in accordance with ethical guidelines of the Mass General Brigham (MGB) Human Research Committee. Deidentified data are publicly available at https://www.a4studydata.org and via www.synapse.org . RNA sequencing data can be found at https://atri-a4.atrihub.org/docs/mgh_rnaseq . Plasma pTau217. Screening samples of plasma pTau217 were processed by Eli Lilly and Company using an automated electrochemiluminescent immunoassay (Tecan Fluent workstation for preparation, MSD Sector S Imager 600MM for detection). 4 Data are represented as pg/ml. RNA sequencing pipeline. At screening, whole blood (2.5 mL) was collected in PAXgene tubes, frozen on site, shipped on dry ice, and stored at −80°C until processing. RNA extraction was performed using the QIASymphony RNA Kit (QIAGEN, 931636), followed by depletion of ribosomal RNA and hemoglobin with the NEBNext Globin and rRNA Depletion Kit (New England BioLabs, E7750). Libraries were prepared using the NEBNext Ultra Directional Library Prep Kit (New England BioLabs, E7420) and sequenced on an Illumina NovaSeq 6000 using 151 bp paired end reads, targeting an average depth of 60 million reads per sample. All sequencing was carried out at the VANTAGE core at Vanderbilt University Medical Center (Nashville, TN, USA). Quality control and preprocessing were conducted by the Vanderbilt Memory and Alzheimer’s Center using established bulk RNAseq pipelines 16 . Briefly, gene-level counts were quantile normalized and adjusted for technical variation (e.g., batch effects) according to these standards. Counts for X-linked genes were normalized and adjusted separately from autosomal gene counts. A β -PET burden. All participants in this study underwent Aβ PET imaging with 18 F-Florbetapir (10 mCi), acquired 50–70 minutes post-injection. Aβ burden was quantified as a mean cortical standardized uptake value ratio (SUVr) using the whole cerebellum as the reference region. Aβ status was determined using a primary threshold of SUVr ≥ 1.15 to define Aβ positivity. 22 Statistical analyses. Linear regression models adjusting for age, body mass index (BMI – to account for blood volume), and cohort (i.e., A4, LEARN) examined associations between the following terms and pTau217 (pg/mL): gene, gene*Aβ continuous , gene* APOE ε4 status, gene*sex, and gene*Aβ continuous *sex. Stratified models (i.e., sex stratified, APOE ε4 status stratified) were examined post hoc . Results were corrected for the number of tested autosomal and X-linked genes (n=20,621) using the false discovery rate (FDR) method. Pre-ranked gene set enrichment analyses based on beta coefficients from each regression model were performed using the R package, fgsea (v1.26.0) and Gene Ontology: Biological Process terms (GO:BP, downloaded October 31, 2025 23 ) of 15 to 500 genes. Significance for all analyses was set a priori at FDR-corrected p < 0.05. All significant transcriptomic results are available in Supplementary Materials. Additional information for significant genes was obtained via the NIH Genotype-Tissue Expression (GTEx) Project portal ( https://www.gtexportal.org/ ) on 11/20/2025. Replication in ROSMAP bulk brain tissue RNAseq data. Gene expression data derived from dorsolateral prefrontal cortex (DLPFC) were also drawn from the Religious Orders Study and the Rush Memory and Aging Project (ROSMAP) for independent validation of our findings in whole blood 24 , 25 . This longitudinal cohort enrolls older adults without dementia who agree to annual clinical evaluations and brain donation at death. All participants provided written informed consent, and study procedures were approved by the Rush Institutional Review Board, with secondary analyses of existing data approved by the Vanderbilt University Medical Center IRB. ROSMAP data are publicly available through the Accelerating Medicines Partnership – Alzheimer’s Disease (AMP-AD) Knowledge Portal ( https://adknowledgeportal.synapse.org/Explore/Studies/DetailsPage/StudyDetails?Study=syn3219045 ) and the Rush Alzheimer’s Disease Center Resource Sharing Hub ( https://www.radc.rush.edu/ ). ROSMAP RNAseq data followed the same processing protocol as A4. Results All participant demographics are shown in Table 1 and stratified by study (i.e., A4 and LEARN). For this sample, the average age was 71.3 years (SD±4.7; range: 65-85.5 years), 63% were female and had 16.5 years of education (SD±2.6; range: 7-30 years). Due to the preponderance of participants enrolled in the A4 clinical trials, 62% were Aβ-positive and 45% carried APOE ε4. As per eligibility criteria, individuals enrolled in A4 exhibited abnormal levels of Aβ-PET, whereas individuals enrolled in LEARN exhibited low Aβ-PET burden. There were no significant differences in mean age or years of education between individuals enrolled in A4 compared to LEARN, though baseline pTau217, global Aβ-PET burden, and APOE ε4 status differed between the samples (p<0.001). View this table: View inline View popup Download powerpoint Table 1. Participant demographics No autosomal or X-linked genes were directly associated with pTau217 levels. Only one gene was found to associate with pTau217 via APOE ε4 status, a relatively uncharacterized long noncoding RNA (lncRNA; ENSG00000273139). For this gene, greater expression was associated with lower plasma pTau217 levels among APOE ε4 carriers (β=-0.11(0.02), p uncorrected =5.02×10 −6 ). By contrast, 1,540 genes were found to moderate associations between Aβ-PET and pTau217 (7.8% X-linked, Supplementary Table 1 ). 63% of these genes were found to be protective; that is, higher gene expression ameliorated the effects of Aβ-PET on pTau217 levels. 6 of the 1,540 significant genes ( EED , IL34, EPHA1, WDR81 , TREML2 , CASP7 ) appeared on the “List of AD Loci and Genes with Genetic Evidence” compiled by the Alzheimer’s Disease Sequencing Project (ADSP) Gene Verification Committee 26 – 31 . Of these genes, EPHA1 and TREML2 exacerbated the Aβ association with pTau217 whereas EED , IL34, WDR81 , and CASP7 demonstrated a protective effect against Aβ ( Table 2 ). View this table: View inline View popup Download powerpoint Table 2. Summary Statistics for Genes Appearing on the ADSP List of AD Loci and Genes with Genetic Evidence List Among novel autosomal genes, SMIM38 showed the largest negative association with pTau217 moderated by Aβ-PET (β=-0.13(0.02), p FDR =2.84×10 −5 ), while FAM13A-AS1 showed the largest positive association (β=0.67(0.13), p FDR =1.62×10 −4 ). SMIM38 expression was associated with lower plasma pTau217 levels among individuals with elevated Aβ-PET ( Figure 1A ) , while FAM13A-AS1 was associated with higher plasma pTau217 levels in individuals with elevated Aβ-PET ( Figure 1B ) . SMIM38 has no known function, though it is predicted to be in the cell membrane and is expressed most highly in the stomach. FAM13A-AS1 is the antisense RNA that corresponds to the FAM13A gene and is expressed most highly in the brain (cerebellum), and which has been related to adipocyte function 32 . Download figure Open in new tab Figure 1. Model estimates predicting pTau217 levels from (A) an SMIM38 *Aβ interaction and (B) a FAM13A-AS1 *Aβ interaction after adjusting for sex, age, BMI, and cohort. The mean ± 1 standard deviation (SD) of Aβ-PET SUVr is given such that blue represents the mean Aβ-PET SUVr, red is 1SD above the mean, and green is 1SD below the mean. From the X chromosome, we found 120 X chromosome genes significantly moderated by Aβ-PET. The most significant X-linked gene in our gene*Aβ analyses was MIRLET7F2 (β=-0.09(0.01), p FDR =2.84×10 −5 , Figure 2A ). Higher MIRLET7F2 (microRNA) was associated with lower pTau217 levels among individuals with higher Aβ-PET burden. We found two X-linked genes that were previously implicated in AD studies also showed significance: FAM156B 20 and KDM6A 33 . Higher FAM156B expression (β=-0.09(0.03), p FDR <0.001, Figure 2B ) was associated with lower pTau217 levels among individuals with higher Aβ-PET burden whereas higher KDM6A expression (β=0.31(0.10), p FDR =0.003, Figure 2C ) was associated with higher pTau217 levels. These three genes, two of which are highly expressed in brain, highlight transcriptional regulation and histone modification 33 as biological pathways associated with plasma pTau217. Download figure Open in new tab Figure 2. Model estimates predicting pTau217 levels from (A) an MIRLET7F2 *Aβ interaction, (B) a KDM6A *Aβ interaction, and (C) a FAM156B *Aβ interaction after adjusting for sex, age, BMI, and cohort. The mean ± 1 standard deviation (SD) of Aβ-PET SUVr is given such that blue represents the mean Aβ-PET SUVr, red is 1SD above the mean, and green is 1SD below the mean. In addition, some of the most significant GO:BP terms from our transcriptome-wide gene set enrichment analyses suggest a downregulation of functions such as aerobic respiration and fatty acid metabolism, though no terms survived correction for multiple comparisons ( Supplementary Table 2 ). There were no gene*sex associations with pTau217 levels. Additional analyses examined gene*Aβ*sex associations with pTau217 and found 772 genes (3.5% X-linked, Supplementary Table 3 ) involved in significant three-way interactions on plasma pTau217. No significant genes overlapped with the ADSP List of AD Loci and Genes with Genetic Evidence. Among novel genes identified, AMIGO2 showed the largest negative effect, with higher pTau217 levels corresponding with greater gene expression in the setting of higher Aβ-PET burden in women, while the opposite was true in men (see Figure 3A ). CERKL showed the largest positive effect, with lower pTau217 levels corresponding with greater gene expression in the setting of higher Aβ-PET burden in women; the opposite effect was apparent in men (see Figure 3B ). AMIGO2 encodes a cell adhesion molecule involved in axon guidance and survival 34 , while CERKL , expressed most highly in the brain (cerebellum), is suggested to play a role in mitochondrial function and autophagy regulation 35 . Download figure Open in new tab Figure 3. Model estimates predicting pTau217 levels from (A) an AMIGO2 *Aβ*sex interaction, (B) a CERKL *Aβ*sex interaction, (C) a HK2P1 *Aβ*sex interaction, and (D) a WWC3 *Aβ*sex interaction after adjusting for age, BMI, and cohort. The mean ± 1 standard deviation (SD) of Aβ-PET SUVr is given such that blue represents the mean Aβ-PET SUVr, red is 1SD above the mean, and green is 1SD below the mean. 27 X-linked genes showed a significant three-way interaction with sex and Aβ-PET on plasma pTau217. The most significant X-linked gene was HK2P1 which is a pseudogene of HK2. HK2 plays a role in glycolysis 36 and HK2P1 is suggested to play a similar function in addition to endometrial cellular preparation for pregnancy (decidualization) 37 . When stratifying by sex, greater expression of HK2P1 was associated with lower baseline pTau217 levels among females with elevated Aβ-PET (β=-0.11(0.03), p uncorrected =4.0×10 −4 ) and greater baseline pTau217 among males (β=0.15(0.05), p uncorrected =0.008) with elevated Aβ-PET ( Figure 3C ). Another X-linked gene of note was WWC3 (β=0.79(0.21), p FDR =0.02, Figure 3D ), which regulates the Wnt and Hippo signaling pathways 38 and is suggested to play an immune-related role in AD via B lymphocytes 39 . In females with elevated Aβ-PET, greater WWC3 expression was associated with lower pTau217 burden (β=-0.44(0.15), p FDR =0.004) whereas males with Aβ-PET had higher levels of pTau217 (β=0.37(0.14), p FDR =0.01). Other X-linked genes among the top 5 most significant in these analyses included SLC35A2 (cellular transport/glycosylation) 40 , PNMA6A (expressed highly in brain and associated with apoptosis) 41 , and ENSG00000227042 (unnamed long non-coding RNA) altogether underscoring axonal, immune, metabolic, and post-translational modification mechanisms relevant to early AD. The top 10 most significant GO:BP terms in gene set enrichment analyses largely related to ribosome biogenesis and RNA processing ( Supplementary Table 4 ), which were downregulated. We identified 28 genes overlapped in both the gene*Aβ and gene*Aβ*sex models. These genes were broadly associated with mechanisms in mitochondrial and metabolic regulation (e.g., UCP2 42 , MMUT 43 ), calcium homeostasis (e.g., ANO9 44 , CACNG6 45 ), extracellular matrix remodeling (e.g., ACAN 46 , ADAMTS5 47 ), cellular transport (e.g., MTMR2 48 , ACTR1A 49 ), and transcriptional regulation (e.g., KAT2A 50 , MOCS3 51 , SMIM10L2A 52 ). Of these, only one gene, SMIM10L2A (highly expressed in brain), was X-linked. Finally, we validated our whole blood gene candidates from the gene*Aβ and gene*Aβ*sex models in bulk brain tissue (DLPFC, n=946) RNA sequencing data from ROSMAP. Of the 2,312 significant genes we identified in our whole blood analyses, 1,545 were available to test in ROSMAP after quality control. For gene*Aβ, we found that 84 genes reached significance (p FDR < 0.05; 5 were X-linked), with 36 showing the same direction of effect (3 were X-linked). Some of the replicated genes implicated processes such as mitochondrial function and protein translation ( ELAC2 53 ), synaptic transport ( TMEM230 54 ) , lysosomal degradation ( GNPTG 55 ), RNA splicing ( CASC3 56 ), and cell proliferation and immunity ( HMGB3 57 ) . The X-linked gene SMIM10L2A , originally significant in both gene*Aβ and gene*Aβ*sex models ( Supplementary Figure 1 and 2 ), also replicated when examining the gene*Aβ interaction on tau in the ROSMAP dataset. The autosomal gene, ACAN (highly expressed in arteries, Supplementary Figure 1 and 2 ), was also found to replicate when examining the gene*Aβ interaction in the ROSMAP dataset ( Table 3 ). No other genes from the gene*Aβ*sex models were found to replicate in ROSMAP. Similar to its results in A4 whole blood, ACAN was associated with greater tau tangle burden among individuals when brain amyloid burden is high (β=0.07(0.02), p FDR =0.04, Figure 4A , B ). By contrast, SMIM10L2A was associated with lower tau tangle burden when brain amyloid burden is high (β=-0.09(0.03), p FDR =0.02, Figure 4C , D ). Download figure Open in new tab Figure 4. Model estimates predicting tau burden from an (A) ACAN *Aβ interaction in A4/LEARN and (B) ACAN *Aβ interaction in ROSMAP as well as a (C) SMIM10L2A *Aβ interaction in A4/LEARN and (D) SMIM10L2A *Aβ interaction in ROSMAP. Models in A4 were adjusted for age, sex, BMI, and cohort; models in ROSMAP were adjusted for age of death, sex, and post-mortem interval.The mean ± 1 standard deviation (SD) Aβ burden is given such that blue represents the mean Aβ burden, red is 1SD above the mean, and green is 1SD below the mean. View this table: View inline View popup Download powerpoint Table 3. Summary statistics for ACAN and SMIM10L2A across two– and three-way interaction models in A4/LEARN and the gene*Aβ replication model in ROSMAP DISCUSSION In this study of 724 cognitively unimpaired older adults, we examined whole blood transcriptomic correlates of plasma pTau217, a biomarker that has emerged as one of the most sensitive indicators of preclinical Alzheimer’s disease (AD). We found no direct gene associations with pTau217 itself; instead, more than 1,500 genes showed associations moderated by Aβ burden, including known AD risk genes such as EPHA1 and TREML2 26 – 31 as well as novel candidates linked to cell metabolism and transcriptional regulation. An additional 772 genes demonstrated sex-moderated associations in the presence of Aβ, implicating pathways in cellular metabolism, immunity, and RNA processing. In these three-way interaction models, the strongest effects were observed for AMIGO2 and CERKL , which showed opposite directions of association in women and men. These genes have been implicated in axonal guidance and mitochondrial function 34 , 35 , respectively, with CERKL demonstrating brain relevance on GTEx. These findings support the view that elevation in plasma pTau217 reflects systemic responses to Aβ-related stress and dysregulation early in the disease process. Importantly, our validation in ROSMAP brain tissue linked peripheral whole blood signals to the brain. Of the more than 2,300 significant genes identified in our discovery analyses in whole blood, 84 genes reached the FDR threshold for replication, and 36 genes showed consistent directionality across the two tissues. These concordant genes suggest that mitochondrial function, lysosomal degradation, RNA splicing, and immunity may be relevant for AD in both whole blood and brain. A key innovation of this study was the systematic inclusion of the X chromosome. We identified MIRLET7F2 , FAM156B , and KDM6A as significant moderators of the pTau217-Aβ relationship, highlighting the roles of X-linked chromatin remodeling and gene regulation in shaping early pTau appearance. Notably, the X-linked gene, SMIM10L2A , emerged consistently across blood and brain analyses, highlighting it as a potentially novel contributor to early pathological processes. SMIM10L2A is thought to interact with enhancer regions on DNA, highlighting gene regulation 52 . GTEx also demonstrated robust and consistent expression of this gene in limbic and neocortical brain tissue, as well as the adrenal gland. The preponderance of evidence underscores the necessity for further validation of this candidate gene in future studies. Among the 27 significant X-linked loci found in our exploratory gene*Aβ continuous *sex models, hits such as HK2P1 and WWC3 converged on cellular signaling and glycolysis 38 , suggesting possible molecular pathways through which sex may shape vulnerability to tau phosphorylation. We also identified ACAN as a gene showing significance across both whole blood interaction models as well as in brain tissue. ACAN encodes aggrecan, a major extracellular matrix proteoglycan and key component of perineuronal nets 58 . Given the role of perineuronal nets in stabilizing synaptic connections and protecting neurons from excitotoxic and oxidative stress 59 , dysregulation of ACAN may point to extracellular matrix remodeling as an important pathway through which Aβ burden shapes early tau dysregulation, and potentially in a sex-specific manner. These cross-tissue convergences highlight a set of AD-relevant pathways that may play a role in the appearance of plasma pTau217 in preclinical AD. Our study leverages the advantages of transcriptomic data derived from whole blood. Blood draws are both minimally invasive and scalable providing an opportunity to assess systemic biological processes that may relate to AD dementia and brain aging in more individuals. Despite this advantage, several limitations warrant mention. Whole blood transcriptomic data may not fully reflect brain-specific processes, although they likely capture systemic immune and metabolic states relevant to AD. Although we explored validation of our findings in brain-derived data, concordance was partial: only 5% of our identified genes replicated in ROSMAP. This underscores both the complementary and distinct biology captured by peripheral versus central tissues and highlights the need for future studies that integrate blood– and brain-based transcriptomics with other multi-omic layers in longitudinal cohorts. The sample sizes remain modest for our interaction models, and larger independent datasets will be needed to confirm these effects. Our analyses were cross-sectional and cannot establish causation. Finally, our analyses were run on a cohort that is low in racial and ethnic diversity, leaving an open question as to how these findings might replicate in a more population-representative sample. Despite these caveats, the present study provides novel evidence that peripheral transcriptomic signatures, moderated by Aβ and sex, are associated with plasma pTau217 levels. By implicating pathways in cell metabolism, transport, immunity, and gene regulation among others, this work advances a more nuanced view of plasma pTau217 as a biomarker and highlights promising new avenues for mechanistic discovery and sex-informed risk stratification in AD. Article Information Corresponding Author Correspondence should be addressed to Rachel F. Buckley, Ph.D. (e-mail: rfbuckley{at}mgh.harvard.edu ). Conflict of Interest MS, HMK, and RFB have no disclosures relevant to this manuscript. RAS has served as a consultant for AbbVie, AC Immune, Acumen, Alector, Apellis, Biohaven, Bristol Myers Squibb, Genentech, Ionis, Janssen, Oligomerix, Prothena, Roche, and Vaxxinity over the past 3 years. She has received research funding from Eisai and Eli Lilly for public-private partnership clinical trials and receives research grant funding from the National Institute on Aging/National Institutes of Health, GHR Foundation, and the Alzheimer’s Association. Her spouse, K. Johnson, reports consulting fees from Novartis, Merck, and Janssen. Author Contributions Concept and design: Seto, Buckley Acquisition, analysis, or interpretation of data: All authors. Drafting of the manuscript: Seto, Buckley Critical revision of the manuscript for important intellectual content: All authors. Statistical analysis: Seto, Klinger Obtained funding: Buckley, Sperling Supervision: Buckley Funding This work was funded by the United States National Institutes of Health, DP2AG082342 [R.F.B.]), R01AG063689 [R.A.S. and others], and U19AG010483 [R.A.S. and others]. The A4 Study is funded by NIH grants, Eli Lilly and Co, and several philanthropic organizations. Acknowledgements We thank the participants and study staff of the A4 Study. The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS. The GTEx portal was accessed on 11/20/2025. Funder Information Declared United States National Institutes of Health , DP2AG082342 , R01AG063689 , U19AG010483 The A4 Study is funded by NIH grants, Eli Lilly and Co, and several philanthropic organizations. References 1. ↵ Lai , R. , Li , B. & Bishnoi , R . P-tau217 as a Reliable Blood-Based Marker of Alzheimer’s Disease . Biomedicines 12 ( 2024 ). 2. ↵ Jonaitis , E.M. , et al. Plasma phosphorylated tau 217 in preclinical Alzheimer’s disease . Brain Commun 5 , fcad057 ( 2023 ). OpenUrl 3. ↵ Thijssen , E.H. , et al. Plasma phosphorylated tau 217 and phosphorylated tau 181 as biomarkers in Alzheimer’s disease and frontotemporal lobar degeneration: a retrospective diagnostic performance study . Lancet Neurol 20 , 739 – 752 ( 2021 ). OpenUrl CrossRef PubMed 4. ↵ Rissman , R.A. , et al. Longitudinal Phospho-tau217 Predicts Amyloid Positron Emission Tomography in Asymptomatic Alzheimer’s Disease . J Prev Alzheimers Dis 11 , 823 – 830 ( 2024 ). OpenUrl PubMed 5. ↵ Mattsson-Carlgren , N. , et al. Longitudinal plasma p-tau217 is increased in early stages of Alzheimer’s disease . Brain 143 , 3234 – 3241 ( 2020 ). OpenUrl CrossRef PubMed 6. ↵ Ossenkoppele , R. , et al. Plasma p-tau217 and tau-PET predict future cognitive decline among cognitively unimpaired individuals: implications for clinical trials . Nature Aging 5 , 883 – 896 ( 2025 ). OpenUrl PubMed 7. ↵ Palmqvist , S. , et al. Prediction of future Alzheimer’s disease dementia using plasma phospho-tau combined with other accessible measures . Nat Med 27 , 1034 – 1042 ( 2021 ). OpenUrl CrossRef PubMed 8. Rissman , R.A. , et al. Plasma Aβ42/Aβ40 and phospho-tau217 concentration ratios increase the accuracy of amyloid PET classification in preclinical Alzheimer’s disease . Alzheimers Dement 20 , 1214 – 1224 ( 2024 ). OpenUrl PubMed 9. ↵ Sperling , R.A. , et al. Amyloid and Tau Prediction of Cognitive and Functional Decline in Unimpaired Older Individuals: Longitudinal Data from the A4 and LEARN Studies . J Prev Alzheimers Dis 11 , 802 – 813 ( 2024 ). OpenUrl PubMed 10. ↵ Hirota , Y. , et al. Biomarker-related phospho-tau217 appears in synapses around Aβ plaques prior to tau tangle in cerebral cortex of preclinical Alzheimer’s disease . Cell Rep 44 , 116203 ( 2025 ). OpenUrl PubMed 11. ↵ Wennström , M. , et al. Cellular localization of p-tau217 in brain and its association with p-tau217 plasma levels . Acta Neuropathol Commun 10 , 3 ( 2022 ). 12. ↵ Huang , Y. & Mahley , R.W . Apolipoprotein E: structure and function in lipid metabolism, neurobiology, and Alzheimer’s diseases . Neurobiol Dis 72 Pt A , 3 – 12 ( 2014 ). OpenUrl CrossRef PubMed 13. ↵ Buckley , R.F. , et al. Sex, amyloid, and APOE ε4 and risk of cognitive decline in preclinical Alzheimer’s disease: Findings from three well-characterized cohorts . Alzheimers Dement 14 , 1193 – 1203 ( 2018 ). OpenUrl CrossRef PubMed 14. ↵ Buckley , R.F. , et al. Sex Mediates Relationships Between Regional Tau Pathology and Cognitive Decline . Ann Neurol 88 , 921 – 932 ( 2020 ). OpenUrl CrossRef PubMed 15. ↵ Coughlan , G . Sex Moderates Relationships Between P-Tau217 and Longitudinal Tau-PET: A Multi-Cohort Study . ( Alzheimer’s Association International Conference 2025 , 2025 ). 16. ↵ Seto , M. , et al. Sex-specific Associations of Gene Expression with Alzheimer’s Disease Neuropathology and Ante-mortem Cognitive Performance . bioRxiv , 2025.2001.2002.631098 ( 2025 ). 17. ↵ Belloy , M.E. , et al. Role of the X Chromosome in Alzheimer Disease Genetics . JAMA Neurology 81 , 1032 – 1042 ( 2024 ). OpenUrl PubMed 18. ↵ Ross , M.T. , et al. The DNA sequence of the human X chromosome . Nature 434 , 325 – 337 ( 2005 ). OpenUrl CrossRef PubMed Web of Science 19. ↵ Nguyen , D.K. & Disteche , C.M . Dosage compensation of the active X chromosome in mammals . Nature genetics 38 , 47 – 53 ( 2006 ). OpenUrl CrossRef PubMed Web of Science 20. ↵ Davis , E.J. , et al. Sex-Specific Association of the X Chromosome With Cognitive Change and Tau Pathology in Aging and Alzheimer Disease . JAMA Neurology 78 , 1249 – 1254 ( 2021 ). OpenUrl PubMed 21. ↵ Sperling , R.A. , et al. The A4 study: stopping AD before symptoms begin? Sci Transl Med 6 , 228 – 213 ( 2014 ). OpenUrl 22. ↵ Sperling , R.A. , et al. Trial of Solanezumab in Preclinical Alzheimer’s Disease . N Engl J Med 389 , 1096 – 1107 ( 2023 ). OpenUrl CrossRef PubMed 23. ↵ Ashburner , M. , et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium . Nature genetics 25 , 25 – 29 ( 2000 ). OpenUrl CrossRef PubMed Web of Science 24. ↵ Bennett , D.A. , et al. Religious Orders Study and Rush Memory and Aging Project . J Alzheimers Dis 64 , S161 – S189 ( 2018 ). OpenUrl PubMed 25. ↵ De Jager , P.L. , et al. A multi-omic atlas of the human frontal cortex for aging and Alzheimer’s disease research . Sci Data 5 , 180142 ( 2018 ). OpenUrl PubMed 26. ↵ King , E.A. , Davis , J.W. & Degner , J.F . Are drug targets with genetic support twice as likely to be approved? Revised estimates of the impact of genetic support for drug mechanisms on the probability of drug approval . PLoS Genet 15 , e1008489 ( 2019 ). OpenUrl CrossRef PubMed 27. Bellenguez , C. , et al. New insights into the genetic etiology of Alzheimer’s disease and related dementias . Nature genetics 54 , 412 – 436 ( 2022 ). OpenUrl CrossRef PubMed 28. Kunkle , B.W. , et al. Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing . Nature genetics 51 , 414 – 430 ( 2019 ). OpenUrl CrossRef PubMed 29. Novikova , G. , et al. Integration of Alzheimer’s disease genetics and myeloid genomics identifies disease risk regulatory elements and genes . Nat Commun 12 , 1610 ( 2021 ). OpenUrl CrossRef PubMed 30. Mountjoy , E. , et al. An open approach to systematically prioritize causal variants and genes at all published human GWAS trait-associated loci . Nature genetics 53 , 1527 – 1533 ( 2021 ). OpenUrl CrossRef PubMed 31. ↵ Amlie-Wolf , A. , et al. INFERNO: inferring the molecular mechanisms of noncoding genetic variants . Nucleic Acids Res 46 , 8740 – 8753 ( 2018 ). OpenUrl PubMed 32. ↵ Fathzadeh , M. , et al. FAM13A affects body fat distribution and adipocyte function . Nature Communications 11 , 1465 ( 2020 ). OpenUrl PubMed 33. ↵ Davis , E.J. , et al. A second X chromosome contributes to resilience in a mouse model of Alzheimer’s disease . Sci Transl Med 12 ( 2020 ). 34. ↵ Kuja-Panula , J. , Kiiltomäki , M. , Yamashiro , T. , Rouhiainen , A. & Rauvala , H . AMIGO, a transmembrane protein implicated in axon tract development, defines a novel protein family with leucine-rich repeats . J Cell Biol 160 , 963 – 973 ( 2003 ). OpenUrl Abstract / FREE Full Text 35. ↵ Mirra , S. , et al. CERKL, a retinal dystrophy gene, regulates mitochondrial function and dynamics in the mammalian retina . Neurobiol Dis 156 , 105405 ( 2021 ). OpenUrl PubMed 36. ↵ DeWaal , D. , et al. Hexokinase-2 depletion inhibits glycolysis and induces oxidative phosphorylation in hepatocellular carcinoma and sensitizes to metformin . Nature Communications 9 , 446 ( 2018 ). OpenUrl PubMed 37. ↵ Lv , H. , et al. Dysregulated Pseudogene HK2P1 May Contribute to Preeclampsia as a Competing Endogenous RNA for Hexokinase 2 by Impairing Decidualization . Hypertension 71 , 648 – 658 ( 2018 ). OpenUrl 38. ↵ Han , Q. , et al. WWC3 regulates the Wnt and Hippo pathways via Dishevelled proteins and large tumour suppressor 1, to suppress lung cancer invasion and metastasis . J Pathol 242 , 435 – 447 ( 2017 ). OpenUrl CrossRef PubMed 39. ↵ Xiong , L.L. , et al. Single-cell RNA sequencing reveals B cell-related molecular biomarkers for Alzheimer’s disease . Exp Mol Med 53 , 1888 – 1901 ( 2021 ). OpenUrl PubMed 40. ↵ Lai , D. , et al. SLC35A2 loss-of-function variants affect glycomic signatures, neuronal fate and network dynamics . Brain ( 2025 ). 41. ↵ Pang , S.W. , Lahiri , C. , Poh , C.L. & Tan , K.O . PNMA family: Protein interaction network and cell signalling pathways implicated in cancer and apoptosis . Cellular Signalling 45 , 54 – 62 ( 2018 ). OpenUrl CrossRef PubMed 42. ↵ Stanzione , R. , et al. Uncoupling Protein 2 as a Pathogenic Determinant and Therapeutic Target in Cardiovascular and Metabolic Diseases . Curr Neuropharmacol 20 , 662 – 674 ( 2022 ). OpenUrl CrossRef PubMed 43. ↵ Keyfi , F. , Sankian , M. , Moghaddassian , M. , Rolfs , A. & Varasteh , A.R . Molecular, biochemical, and structural analysis of a novel mutation in patients with methylmalonyl-CoA mutase deficiency . Gene 576 , 208 – 213 ( 2016 ). OpenUrl PubMed 44. ↵ Schreiber , R. , Ousingsawat , J. & Kunzelmann , K . Anoctamin 9 determines Ca(2+) signals during activation of T-lymphocytes . Front Immunol 16 , 1562871 ( 2025 ). 45. ↵ Glossmann , H. , et al. Interaction between calcium channel ligands and calcium channels . Circ Res 61 , I30 – 36 ( 1987 ). OpenUrl PubMed 46. ↵ Aspberg , A . The different roles of aggrecan interaction domains . J Histochem Cytochem 60 , 987 – 996 ( 2012 ). OpenUrl CrossRef PubMed Web of Science 47. ↵ Hurskainen , T.L. , Hirohata , S. , Seldin , M.F. & Apte , S.S . ADAM-TS5, ADAM-TS6, and ADAM-TS7, Novel Members of a New Family of Zinc Metalloproteases: GENERAL FEATURES AND GENOMIC DISTRIBUTION OF THE ADAM-TS FAMILY * 210 . Journal of Biological Chemistry 274 , 25555 – 25563 ( 1999 ). OpenUrl Abstract / FREE Full Text 48. ↵ Laporte , J. , Blondeau , F. , Buj-Bello , A. & Mandel , J.L . The myotubularin family: from genetic disease to phosphoinositide metabolism . Trends Genet 17 , 221 – 228 ( 2001 ). OpenUrl CrossRef PubMed Web of Science 49. ↵ Schafer , D.A. , Gill , S.R. , Cooper , J.A. , Heuser , J.E. & Schroer , T.A . Ultrastructural analysis of the dynactin complex: an actin-related protein is a component of a filament that resembles F-actin . Journal of Cell Biology 126 , 403 – 412 ( 1994 ). OpenUrl Abstract / FREE Full Text 50. ↵ Kufrin , V. , et al. The histone modifier KAT2A presents a selective target in a subset of well-differentiated microsatellite-stable colorectal cancers . Cell Death & Differentiation 32 , 1259 – 1272 ( 2025 ). OpenUrl PubMed 51. ↵ Chowdhury , M.M. , Dosche , C. , Löhmannsröben , H.G. & Leimkühler , S . Dual role of the molybdenum cofactor biosynthesis protein MOCS3 in tRNA thiolation and molybdenum cofactor biosynthesis in humans . J Biol Chem 287 , 17297 – 17307 ( 2012 ). OpenUrl Abstract / FREE Full Text 52. ↵ National Library of Medicine (US), N.C.f.B.I. SMIM10L2A [Internet] . ( 2004 ). 53. ↵ Brzezniak , L.K. , Bijata , M. , Szczesny , R.J. & Stepien , P.P . Involvement of human ELAC2 gene product in 3’ end processing of mitochondrial tRNAs . RNA Biol 8 , 616 – 626 ( 2011 ). OpenUrl CrossRef PubMed Web of Science 54. ↵ Deng , H.-X. , et al. Identification of TMEM230 mutations in familial Parkinson’s disease . Nature genetics 48 , 733 – 739 ( 2016 ). OpenUrl CrossRef PubMed 55. ↵ Du , S. , et al. Structural insights into how GlcNAc-1-phosphotransferase directs lysosomal protein transport . J Biol Chem 298 , 101702 ( 2022 ). 56. ↵ Gerbracht , J.V. , et al. CASC3 promotes transcriptome-wide activation of nonsense-mediated decay by the exon junction complex . Nucleic Acids Res 48 , 8626 – 8644 ( 2020 ). OpenUrl CrossRef PubMed 57. ↵ Wen , B. , Wei , Y.T. & Zhao , K . The role of high mobility group protein B3 (HMGB3) in tumor proliferation and drug resistance . Mol Cell Biochem 476 , 1729 – 1739 ( 2021 ). OpenUrl PubMed 58. ↵ Grødem , S. , et al. Differential impacts of germline and adult aggrecan knockout in PV+ neurons on perineuronal nets and PV+ neuronal function . Molecular Psychiatry 30 , 2907 – 2921 ( 2025 ). OpenUrl PubMed 59. ↵ Tewari , B.P. , et al. Perineuronal nets decrease membrane capacitance of peritumoral fast spiking interneurons in a model of epilepsy . Nature Communications 9 , 4724 ( 2018 ). OpenUrl PubMed View the discussion thread. Back to top Previous Next Posted November 24, 2025. Download PDF Supplementary Material Email Thank you for your interest in spreading the word about bioRxiv. 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 Blood-based Transcriptomics Reveal Sex- and Amyloid-Modulated Biology of Plasma pTau217 in Preclinical Alzheimer’s Disease Message Subject (Your Name) has forwarded a page to you from bioRxiv Message Body (Your Name) thought you would like to see this page from the bioRxiv 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 Blood-based Transcriptomics Reveal Sex- and Amyloid-Modulated Biology of Plasma pTau217 in Preclinical Alzheimer’s Disease Mabel Seto , Hannah M. Klinger , Michelle Clifton , Vaibhav A Janve , Jane A. Brown , Colin Birkenbihl , Gillian Coughlan , Diana L. Townsend , Ting-Chen Wang , Michael Properzi , Bernard Hanseeuw , Jasmeer Chhatwal , Hyun-Sik Yang , Robert A. Rissman , Paul Aisen , Madison Cuppels , Michael C. Donohue , Rema Raman , Keith A. Johnson , Reisa A. Sperling , Logan Dumitrescu , Timothy J. Hohman , Rachel F. Buckley bioRxiv 2025.11.21.689770; doi: https://doi.org/10.1101/2025.11.21.689770 Share This Article: Copy Citation Tools Blood-based Transcriptomics Reveal Sex- and Amyloid-Modulated Biology of Plasma pTau217 in Preclinical Alzheimer’s Disease Mabel Seto , Hannah M. Klinger , Michelle Clifton , Vaibhav A Janve , Jane A. Brown , Colin Birkenbihl , Gillian Coughlan , Diana L. Townsend , Ting-Chen Wang , Michael Properzi , Bernard Hanseeuw , Jasmeer Chhatwal , Hyun-Sik Yang , Robert A. Rissman , Paul Aisen , Madison Cuppels , Michael C. Donohue , Rema Raman , Keith A. Johnson , Reisa A. Sperling , Logan Dumitrescu , Timothy J. Hohman , Rachel F. Buckley bioRxiv 2025.11.21.689770; doi: https://doi.org/10.1101/2025.11.21.689770 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Neuroscience Subject Areas All Articles Animal Behavior and Cognition (7642) Biochemistry (17715) Bioengineering (13907) Bioinformatics (42003) Biophysics (21470) Cancer Biology (18624) Cell Biology (25533) Clinical Trials (138) Developmental Biology (13390) Ecology (19935) Epidemiology (2067) Evolutionary Biology (24356) Genetics (15617) Genomics (22529) Immunology (17753) Microbiology (40432) Molecular Biology (17200) Neuroscience (88681) Paleontology (667) Pathology (2840) Pharmacology and Toxicology (4828) Physiology (7653) Plant Biology (15161) Scientific Communication and Education (2046) Synthetic Biology (4304) Systems Biology (9826) Zoology (2271)