Clinical Epigenetics

IntroductionDNA methylation (DNAm) has shown promise as a biological marker of gestational age (GA). Here, we aimed to characterize how plasma circulating miRNAs - another epigenetic mechanism regulating gene expression - associate with GA at birth, and to construct a miRNA-based GA clock (miRClock-GA). MethodsWe leveraged 2083 umbilical cord plasma-derived circulating miRNAs from Generation R (N=1695). First, we performed linear regressions to identify miRNome-wide significant miRNAs associated with GA. Second, we applied elastic net regression to construct miRClock-GA. These steps were validated in Gen3G (N=213). Finally, we computed age acceleration (miRClock-AA) and evaluated association of miRClock-GA and miRClock-AA with child developmental outcomes up to 17 years of age, including comparisons with DNAmClocks. FindingsWe identified 123 miRNAs associated with GA, with miR-150-5p showing the strongest positive association ( B=0.244, SE=0.036, P=2.3e-11) and miR-373-3p the strongest negative association ( B=-0.255, SE=0.065, P=8.6e-5). MiRClock-GA correlated consistently with GA in Generation R train (rrange=0.62-0.72) and test sets (rrange=0.45-0.52) and in the independent validation cohort (rGen3G =0.33). Correlations between miRClock-GA and DNAmClocks were weak to moderate (rrange=0.28-0.42). MiRClock-AA explained significant variance in birthweight and childhood BMI beyond clinical GA. ConclusionsThis study reveals widespread associations between circulating miRNAs and GA, supports miRClock-GA as a consistent, well-performing biological marker of GA, with miRClock-AA predicting birthweight and childhood BMI beyond GA itself. Our findings provide a broader perspective on the potential utility of miRNAs as early markers of development. FundingE.U. Horizon Europe Research and Innovation Programme (FAMILY,No.101057529); European Research Council (TEMPO,No.101039672). Full funding in Acknowledgements. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSEpigenetic clocks have emerged as powerful tools for assessing individual differences in biological ageing. Existing epigenetic clocks are typically constructed using DNA methylation (DNAm) data and are developed to estimate whether an individuals epigenetic age deviates relative to their chronological age. In adults, higher predicted biological epigenetic age than chronological age (accelerated epigenetic ageing) is an established indicator of mortality risk and other age-related morbidities. MicroRNAs are another epigenetic mechanism associated with chronological age and age-related phenotypes across species such as C. elegans, mice, primates and humans. Recently, a plasma-derived, cell-free circulating miRNA clock was developed in a sample of older European adults, with accelerated miRNA age predicting biological age-related conditions such as frailty and multi-system blood biomarkers. However, miRNA-based estimations of biological gestational age at birth have not been previously done and their relationship to child health outcomes are unknown. Added value of this studyTo gain a broader perspective on the role of epigenetic markers in biological gestational age at birth and the potential utility of miRNAs as early markers of (altered) development, we leveraged cord blood plasma circulating miRNA data collected at birth in a large population-based cohort. First, we identified 123 miRNAs associated with gestational age. Second, we used this information to construct a miRNA-based epigenetic clock for gestational age (miRClock-GA) and validated this clock in an independent cohort. MiRClock-GA showed moderate correlations with both gestational age and existing DNAm-based gestational clocks. Third, we found that miRClock-GA correlated cross-sectionally with birthweight, as well as prospectively with several adaptive, behavioural, cognitive, and growth outcomes measured up to age 17y, after taking into account maternal influences such as maternal education level, smoking, pre-pregnancy BMI, and age. Accelerated ageing of miRClock-GA (miRClock-AA) explained variance in birthweight and childhood BMI beyond clinical GA, after accounting for maternal influences. Implications of all available evidenceOur study provides the first large-scale evidence that circulating miRNAs in cord blood plasma show widespread associations with gestational age at birth and can be used to derive a robust biological marker of GA (MiRClock-GA), which explains a substantial proportion of the variation in clinical GA. MiRClock-AA provides information beyond GA in some child outcomes, such as BMI. These findings extend adult research, supporting the potential of miRNAs as promising markers for early risk assessment and health monitoring in a developmental context.

AbstractO_ST_ABSBackgroundC_ST_ABSGlioblastoma (GB) is the most aggressive primary brain tumor, characterized by therapy resistance, attributed to a multitude of epi-genetic changes resulting in phenotypic plasticity with altered cell states. To uncover druggable epigenetic vulnerabilities, we disturbed GB-derived spheres and observed coordinated repression of the aberrantly activated hemopoietic stem-like cell signature, dominated by HOXA genes. This signature has been associated with poor prognosis and resistance to therapy in GB. Here we investigate biological vulnerabilities associated with the deregulated epigenetic landscape in high-HOX GB. MethodsGB-derived spheres (GS) were treated with an inhibitor of Bromodomain and extra-terminal motif proteins (BETi) (JQ1) or transduced with inducible constructs to genetically modulate HOXA10 expression (shRNA for knockdown, ectopic HOXA10). Functional effects were evaluated through proliferation, neurosphere formation, and senescence assays. Epigenomic profiling incorporated RNA-seq, ChIP-seq, ATAC-seq, promoter capture MicroC, and DNA methylation. ResultsBETi-mediated rapid, coordinated downregulation of the HOX-signature, suggested direct transcriptional regulation. Knockdown of HOXA10 alone yielded similar effects, decreasing expression of HOXA genes, reducing proliferation, self-renewal capacity, and triggering senescence. Conversely, ectopic HOXA10 expression was ineffective in reactivating the HOXA cluster, or reverse BETi-mediated biological effects. Integrative epigenomic analysis of high-HOX-GS revealed concerted activation of the HOXA region, with broad domains of H3K27ac/H3K4me3 associated with super-enhancer activity, open chromatin (ATAC) and focal DNA hypomethylation. Architectural changes included altered CTCF interactions and increased promoter-anchored looping. ConclusionThese results position the HOX-signature as a potential therapeutic target and offer a mechanistic rationale for disrupting BET-dependent transcriptional regulation in high-HOX GB. Key pointsO_LIEpigenetic activation of stem cell-related high-HOX signature in GB is associated with a super-enhancer encompassing the HOXA locus. C_LIO_LITargeting this vulnerability by BETi or HOXA10 knockdown results in concerted repression and loss of stemness features. C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=74 SRC="FIGDIR/small/727851v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@5bf4b9org.highwire.dtl.DTLVardef@11fa405org.highwire.dtl.DTLVardef@497a2eorg.highwire.dtl.DTLVardef@1f47084_HPS_FORMAT_FIGEXP M_FIG C_FIG Created in BioRender. Chiesi, D. (2026) https://BioRender.com/eknk0ez Importance of studyGlioblastoma (GB) are the most aggressive brain tumors in adults that are difficult to treat, due to their high plasticity resulting invariably to resistance to therapies. Here we report on the identification of epigenetic vulnerabilities that may be leveraged in combination therapies. Disturbing GB-derived stem-like cells with epigenetic drugs, we uncovered that a HOXA gene dominated hematopoietic stem cell-related signature, previously associated with aggressiveness and treatment resistance, can be repressed in a coordinated manner, resulting in loss of stem cell features. Analysis of the underlying epigenetic landscape revealed that the HOXA region was activated in high-HOX glioblastoma through the formation of a super-enhancer. This feature presents a particular vulnerability that may be leveraged by BETi as strategy of a combination therapy.

Background: It is an everyday observation that people of the same chronological age differ with respect to their physical and mental capacity. However, assessing these differences in biological age remains challenging. Methods: Here, we aggregate 89 age-associated variables from the Berlin Aging Study II (BASE-II, n=1,631) to generate MultiAge, a new marker of biological age that summarizes information from ten domains reflecting organ health and global biological age. We then used methylation data obtained from an Illumina MethylationEPIC array and supervised machine learning to translate MultiAge into a DNA methylation signature, MultiAgeEpi (309 CpGs), which was subsequently validated in four independent external validation cohorts (KORA FF4, KORA Age, SHIP-TREND, BiDirect, total n=4,339). MultiAgeEpi results were compared with previously published epigenetic clocks (GrimAge, DunedinPACE, SystemsAge). Results: We report that MultiAgeEpi showed similar, and in several cases, stronger associations with age-associated outcomes such as diabetes, metabolic syndrome, multimorbidity, frailty and mortality (q < 0.05) compared to the other clocks. Conclusions: MultiAge and MultiAgeEpi thus provide a comprehensive assessment of biological age through aggregation of numerous age-associated variables and the use of the high-resolution methylomics data makes transfer of this marker to other cohorts possible.

Background: The biological mechanisms linking generalized anxiety disorder (GAD) and COVID-19 remain poorly understood, despite substantial evidence of their comorbidity. To address this gap, we examined genetic and epigenetic factors underlying their co-occurrence. Methods: In a multi-ancestry sample of 893 participants, we conducted genome-wide and epigenome-wide analyses of GAD and COVID-19 severity. Integrating large-scale genome-wide datasets and information regarding methylation quantitative trait loci, complementary analytic approaches were used to identify regional methylation patterns, assess genetically regulated DNA methylation in blood and brain tissue, and evaluate causal loci shared between GAD and COVID-19. Results: GAD was associated with epigenome-wide significant variation in loci involved in chromatin regulation and synaptic signaling. Conversely, COVID-19-related epigenetic signals were enriched in immune-inflammatory and host-response pathways. Mild COVID-19 was epigenetically related to endothelial-inflammatory signals, while severe COVID-19 was linked to epigenetic changes implicated in myeloid and thrombo-inflammatory pathways. Epigenetic signals shared between GAD and COVID-19 implicated processes related to stress adaptation and tissue homeostasis. Genetically informed analyses identified 60 shared loci, including MAPT, ZFP57, and FBXL18, indicating pleiotropy between GAD and COVID-19 in genetically regulated DNA methylation variation. Brain-specific analyses further highlighted convergence in additional loci (i.e., MICB and HLA-DPB1), suggesting neuroimmune mechanisms underlying GAD-COVID-19 shared methylation patterns. Conclusions: These findings support that GAD and COVID-19 share epigenetic and genetic architecture involving pathways related to vascular integrity, immune function, and cellular adaptation, highlighting a potential neuroimmune basis for their co-occurrence.

BackgroundDNA methylation-based biomarkers have been widely used to predict biological age; however, most blood-derived data have been used in most existing models, and whether cheek mucosa can serve as an alternative indicator for methylation-based estimation of aging-related and clinical phenotypes is unclear. MethodsDNA methylation profiles from cheek mucosa and whole blood of 186 Japanese adults were analyzed using Illumina Infinium Methylation Screening Array (MSA). Models were constructed to predict chronological age, phenotypic age, and clinical laboratory biomarkers from cheek mucosa- and blood-derived methylation data. In addition to applying the ordinary elastic net method, a two-stage residual learning method incorporating existing blood-based epigenetic clocks was applied for more accurate prediction of biological age. Sex-stratified analyses and comparisons of selected CpG features across sexes and tissues were performed. ResultsCheek mucosa-derived MSA methylation data enabled accurate prediction of chronological age (R = 0.965) and phenotypic age (R = 0.964) using the two-stage method. The performance gain achieved by the two-stage approach was greater for phenotypic age than for chronological age. Multiple clinical laboratory biomarkers could be predicted using cheek mucosa-derived methylation data, particularly after sex stratification, including inflammatory, metabolic, thyroid-related, and sex hormone-related markers. Most biomarkers that could be predicted using blood-derived methylation data were also predicted using cheek mucosa-derived methylation data. However, the CpG sites selected for prediction showed minimal overlap across sexes and tissues despite overlap in the corresponding predictable phenotypes. ConclusionsCheek mucosa-derived DNA methylation profiles measured using the MSA can predict chronological age, phenotypic age, and multiple clinically relevant laboratory biomarkers, supporting the utility of cheek mucosa as a less invasive alternative for methylation-based assessment of biological aging and systemic physiological state.

Background Preterm birth (PTB) rates among Hispanic/Latina individuals in the United States have risen over the past decade. Data suggests this rise may be driven in part by psychosocial stress. Leukocyte telomere length (LTL), a marker of cumulative cellular aging that shortens under chronic stress, may capture stress-related biological vulnerability, but has not been examined as a potential population-level contributor to PTB in Hispanic/Latina pregnancies. Objective To examine the association between mid-pregnancy maternal LTL and PTB in a population-based Hispanic/Latina cohort. Methods In a case-control study nested within a California singleton birth cohort (n = 436 Hispanic/Latina individuals; 215 PTB, 221 term births), LTL was measured by quantitative PCR from biobank specimens collected from 15 to 20 weeks of gestation. Covariates from linked birth certificate and hospital discharge records were included. Logistic regression estimated ORs and 95% CIs of PTB by LTL examined continuously and by percentile category (<=10th, 11th-89th, >=90th) with and without adjustment for covariates. Results Mean and median LTL did not differ between PTB and term births. LTL at or below the 10th percentile was associated with elevated odds of PTB relative to full-term birth (12.6% versus 4.3%; ORc = 3.2, 95% CI 1.3-7.9), persisting after partial (ORadj1 = 3.2, 95% CI 1.3-8.3) and full covariate adjustment (ORadj2 = 3.4, 95% CI 1.3-9.3). Subgroup analyses showed consistent directional patterns across PTB subgroups and for early term birth (ORadj2 = 5.1, 95% CI 1.5-17.0). Conclusions Mid-pregnancy maternal LTL <=10th percentile was associated with more than three times the odds of PTB, with risk concentrated at the extreme low tail of the distribution. Consistent with a cumulative allostatic load model, markedly short LTL at mid-gestation may reflect elevated stress-related biological risk for preterm delivery. These findings support upstream investment in stress reduction and prospective LTL research in high-burden populations.

Objective: To characterize genome-wide DNA methylation patterns associated with sepsis using the Infinium Methylation EPIC v2.0 platform and to evaluate the feasibility of pooled methylation profiling in a pilot critical care cohort. Design: Single-center pilot epigenome-wide association study using pooled whole-blood genomic DNA and pool-level bioinformatic analysis. Setting: Academic medical center. Patients: Fifty critically ill adults enrolled within 48 hours of illness onset and 20 healthy controls. Interventions: None. Measurements and Main Results: Critically ill patients required mechanical ventilation and/or vasopressor support. Sepsis was defined according to Sepsis-3 criteria. Seventy individual samples were organized into 14 intended pools of 5 individuals each: 7 sepsis pools, 3 critically ill non-septic pools, and 4 healthy-control pools. One critically ill non-septic pool was excluded because of poor DNA quality, yielding 13 analyzable pools. For the primary pooled comparison, 7 sepsis pools were compared with 6 non-sepsis comparator pools comprising 2 critically ill non-septic and 4 healthy-control pools. After quality control and preprocessing with SeSAMe, 876,094 CpG sites were retained. The initial pool-level screen identified 170,897 candidate differentially methylated regions. Application of stringent secondary filters (false discovery rate <= 1%, absolute delta-beta >= 7.5%, and >= 5 CpGs per region) yielded a high-confidence subset with marked directional skewing, including 155 hypomethylated and 32 hypermethylated regions in sepsis. Differentially methylated region-associated genes were enriched in myeloid leukocyte activation, myeloid leukocyte-mediated immunity, defense response to bacterium, neutrophil granule biology, and hematopoietic cell lineage pathways. Additional signals involved microRNA-associated targets, ribosome biogenesis, RNA processing, long noncoding RNAs, and previously uncharacterized loci. Conclusions: In this pilot pooled EPIC v2.0 study, sepsis was associated with a biologically coherent, predominantly hypomethylated methylation signature enriched in myeloid and host-defense pathways. These findings support the feasibility of pooled methylation profiling for discovery-oriented sepsis biobank studies but should be interpreted as hypothesis-generating given the pool-level design, limited effective sample size, heterogeneous comparator group, and lack of direct validation against individual-level methylation profiles.

Non-small cell lung cancer (NSCLC) remains one of the leading causes of cancer-related mortality, partly because it is often diagnosed at advanced stages and frequently develops resistance to platinum-based chemotherapy. We previously showed that MAFG becomes derepressed following miR-7 hypermethylation, promoting platinum resistance in NSCLC and ovarian cancer cell lines. Although MAFG is a well-established regulator of oxidative stress, recent evidence in melanoma and colorectal cancer suggests an additional role as a regulator of methylator phenotypes. However, how MAFG reshapes the lung cancer epigenome remains unknown. Here, we investigated the contribution of MAFG to DNA methylation remodeling by combining CRISPR/Cas9-mediated MAFG deletion with CpG-Methyl-Array profiling, followed by expression (qPCR) and methylation (qMSP) validation in tumor cell lines. Our translational approach integrated aptahistochemistry using MAFG-specific aptamers in 127 NSCLC patients, methylation analysis in 35 fresh-frozen tumors and 40 FFPE samples, and interrogation of TCGA methylation datasets. MAFG loss reduced promoter methylation of LIF and MAFG itself. Importantly, these effects were subtype-specific, with MAFG expression and methylation displaying distinct transcriptional programs in LUAD versus LUSC, and prognostic associations restricted to KRAS-mutated adenocarcinomas. In NSCL in silico and in house cohorts, lower MAFG methylation and higher MAFG protein levels were both associated with worse prognosis. In summary, our findings identify MAFG as a regulator of DNA methylation in NSCLC and support the use of MAFG DNA methylation, or protein levels as clinically relevant prognostic biomarkers, particularly in lung adenocarcinoma.

Stressful life events (SLEs) are associated with increased risk of psychiatric and somatic disease, yet the molecular correlates of stress exposure across time remain incompletely characterised. We conducted a multi-omic analysis in the Finnish Twin Cohort, examining genomic (n = 8,286), epigenomic (n = 387), proteomic (n = 401) and metabolomic (n = 434) data across three exposure windows: recent (within 6 months), proximal (within 5 years) and lifetime. Genome-wide association analysis identified a single significant locus on chromosome 1 (lead SNP rs10158287, p = 9.7 x 10-9), mapping to DAB1/C8B, with immune cell-specific eQTL effects in Th1/Th17 CD4+ T cells and cross-trait links to cardiometabolic risk; common variants explained 33.6% of variance in SLE scores; the DAB1/C8B locus alone accounted for 0.4%, consistent with a highly polygenic architecture. No epigenome-wide significant associations or relationships with epigenetic ageing measures (PCPhenoAge, DunedinPACE, PCGrimAge) were detected. Circulating molecular layers showed temporally structured signatures. Recent SLEs were characterised by coordinated immune-metabolic changes, including five proteins (IL-1{beta}, TIGIT, Nectin-1, Carnosinase-1, Calcyphosin; all decreased) and 16 metabolites predominantly reflecting reduced HDL-related lipids and broader lipid pools, alongside enrichment of the lipoprotein assembly and clearance pathway and lower thyroid and lung proteomic age estimates. Proximal exposure showed no significant single-analyte associations but convergent negative pathway-level signals involving cell-cycle and centrosome-associated processes. Lifetime SLEs were characterised by immune-vascular and tissue-remodelling signatures, including ten proteins (all increased), enrichment of TNF/IL-10 signalling, cellular maintenance and epithelial differentiation pathways, and higher arterial proteomic age. These findings indicate that molecular correlates of stress exposure are temporally contingent rather than uniformly accumulating across the life course, with convergent involvement of adaptive immune regulation alongside metabolic and vascular remodelling.

Atherosclerosis is a systemic vascular process linked to cardiovascular, cognitive and renal outcomes. DNA methylation (DNAm)-based scores of atherosclerosis may capture cumulative biological processes underlying vascular aging. Here, we examined associations of DNAm scores for coronary artery calcification (DNAm-CAC) and carotid plaque (DNAm-cPlaque), derived from a large study of imaging-based subclinical atherosclerosis, with prevalent and incident outcomes in two population-based cohorts of older adults: the Health and Retirement Study (HRS; n = 3,875) and The Irish Longitudinal Study on Ageing (TILDA; n = 487). Higher DNAm scores were associated with adverse cardiometabolic profiles and socioeconomic indicators. In HRS, higher DNAm-CAC was associated with prevalent cardiovascular disease (odds ratio per SD, 1.16; 95% confidence interval (CI), 1.07-1.26), lower cognitive function ({beta} = -0.50, 95% CI -0.68 to -0.32) and lower estimated glomerular filtration rate (eGFR; -1.7 ml min-1 1.73 m-2, 95% CI -2.6 to -0.8) in unadjusted models. After adjustment for demographic and clinical risk factors, DNAm-CAC ({beta} = -0.29, 95% CI -0.46 to -0.13) and DNAm-cPlaque ({beta} = -0.24, 95% CI -0.42 to -0.06) remained associated with lower cognitive function, and DNAm-cPlaque was associated with incident cognitive impairment or dementia (hazard ratio per SD, 1.16; 95% CI, 1.01-1.32). Associations were attenuated after further adjustment for race/ethnicity and socioeconomic indicators. In TILDA, higher DNAm-cPlaque was associated with worse cognitive performance (incidence rate ratio, 1.11; 95% CI, 1.01-1.21), increased risk of incident cardiovascular disease (hazard ratio, 1.18; 95% CI, 1.00-1.42) and lower eGFR, with consistent associations observed for DNAm-CAC. These findings suggest that DNAm-based scores of atherosclerosis capture systemic vascular processes linked to multiple age-related outcomes across populations. Further work is needed to clarify the biological pathways reflected by these scores and their relation to cumulative and socially patterned vascular risk.

BackgroundCDH1 (E-cadherin) is a key epithelial adhesion molecule traditionally associated with tumor suppression and epithelial-mesenchymal transition (EMT). However, its roles across cancers remain incompletely understood, particularly within multilayer regulatory contexts involving genomic, epigenetic, transcriptional, and immune mechanisms. MethodsCDH1 expression, survival associations, EMT-correlated gene profiles (VIM, SNAI1, ZEB1), immune infiltration patterns, immune checkpoint correlations (PDCD1, CD274, CTLA4), promoter methylation, and genomic alterations were assessed across five epithelial cancers, breast invasive carcinoma (BRCA), colon adenocarcinoma (COAD), lung adenocarcinoma (LUAD), ovarian cancer (OV), and stomach adenocarcinoma (STAD). Cross-platform validation was performed using TCGA/GDC datasets, GEPIA2, UALCAN, TIMER, KM Plotter, cBioPortal, and g:Profiler. ResultsCDH1 was overexpressed but showed variable prognostic significance; higher expression predicted better survival in COAD, LUAD and STAD, worse survival in BRCA and had no impact in OV. Classic inverse relationships between CDH1 and VIM or ZEB1 were evident only in STAD, and SNAI1 showed no consistent association. Immune infiltration patterns were tumor-specific, ranging from cytotoxic T-cell dominance in LUAD to macrophage-rich profiles in OV; immune checkpoint correlations were similarly context-dependent. Co-expressed genes were enriched for endomembrane transport rather than adhesion pathways. Promoter methylation patterns varied by cancer, whereas genomic alterations of CDH1 were rare. ConclusionsCDH1 does not function as a universal epithelial or EMT marker across epithelial cancers. Instead, its associations with EMT, immune contexture, methylation, and prognosis are context-dependent, supporting a model of CDH1 as a heterogeneous regulator of epithelial plasticity. These findings challenge single-function interpretations and support cancer-specific CDH1 evaluation in translational research.

Clonal hematopoiesis of indeterminate potential (CHIP) represents the age-related expansion of hematopoietic stem cells with preleukemic mutations. However, its association with all-cause and cause-specific mortality has not been well characterized in older adults. We aimed to evaluate whether CHIP is associated with all-cause and cause-specific mortality in a population of older women in the United States. Our study included 6,704 participants in the Women?s Health Initiative Long Life Study (WHI-LLS) without hematologic malignancy. The co-primary exposures were any CHIP (variant allele frequency [VAF] [&ge;] 2%) and large CHIP (VAF [&ge;] 10%), and the primary outcome was all-cause mortality. Multivariable-adjusted Cox proportional hazards models tested the associations of CHIP and CHIP subtypes with all-cause and cause-specific mortality. Any CHIP and large CHIP were independently associated with all-cause mortality, with multivariable-adjusted hazard ratios (aHRs) of 1.12 (95% confidence interval [CI] 1.04-1.21; P = 0.003) and 1.28 (95% CI 1.15-1.43; P < 0.001), respectively. In gene-specific analyses, non-DNMT3A CHIP was associated with all-cause mortality (aHR: 1.22 [95% CI: 1.12-1.34], P < 0.001), while DNMT3A CHIP was not (aHR: 1.07 [95% CI: 0.98-1.18], P = 0.13). Furthermore, large CHIP was associated with cardiovascular (aHR: 1.29 [95% CI: 1.08-1.55], P = 0.006), cancer (aHR: 1.49 [95% CI: 1.11-2.02], P = 0.009), and neurologic (aHR: 1.40 [95% CI: 1.07-1.84], P = 0.02) death. In this cohort of older women, CHIP, particularly large clones and non-DNMT3A CHIP, was associated with all-cause and cause-specific mortality. These findings suggest that clonal size and subtype may differentially influence mortality risk.

Background: It is well-established that males have a higher mortality risk than females. Immune cells and their function are known to undergo characteristic changes during aging, and immune cells are known to have sex differences. Immune cells and their function have been linked to mortality risk, but no studies have investigated to what degree, if at all, Immune Cell Biomarkers (ICBs) contribute to the known differences in mortality risk by sex. Methods: Using participant data from the Health and Retirement Study (n = 8,822), we applied multivariable linear regressions adjusting for age, cytomegalovirus (CMV) serostatus, sex, and race/ethnicity to identify differences by sex in 48 immune cell biomarker (ICB, e.g. T cells, B cells, Monocytes, etc.) percentages and counts (measured in 2016). We studied how the associations between ICBs and mortality risk differ by sex using stratified Cox Proportional Hazard (CPH) models. We estimated how inclusion of sex explained the relationship between ICBs and all-cause mortality, and conversely, how inclusion of individual and all ICBs combined explain the relationship between sex and all-cause mortality using multivariable modeling approaches. Results: Differences in ICBs by sex range between 2-38% (39/48 statistically significant). 9 ICBs were significantly associated with mortality risk in the entire sample. While different ICBs were significantly associated with mortality risk in the stratified analyses, particularly with respect to monocyte, B cell, and NK cell populations, adjusting for sex modestly influenced the hazard ratios of the ICBs (sex: 8 ICBs, percent change <5.4%). Furthermore, individual and cumulative contributions of ICBs in explaining the differences in mortality risk by sex were not significant.

IntroductionClonal hematopoiesis of indeterminate potential (CHIP) is a recognized risk factor for hematologic malignancies, but its contribution to different types of solid cancers remains incompletely defined. MethodsHere, we performed a systematic, gene-specific analysis of CHIP across 19 common solid cancer types using two large population-based cohorts, the UK Biobank and All of Us with Cox proportional hazards models and nested case-control logistic models. ResultsWe demonstrate that the relationship between CHIP and solid tumors is highly cancer-type specific, with lung cancer exhibiting the strongest association. In lung cancer, this association is largely driven by ASXL1-mutant clones. Specifically, high variant allele fraction (high-VAF) ASXL1 conferring a significantly increased risk (hazard ratio = 3.2), and the associations remained robust after adjustment for age, sex, body mass index (BMI), smoking status, and genetic ancestry. Notably, ASXL1 CHIP was substantially enriched among smokers, and its association with lung cancer risk was restricted to ever-smokers, highlighting a key interaction between CHIP and environmental exposure. The enrichment of ASXL1 CHIP in lung cancer was further validated in two independent cancer-only cohorts, including MSK-IMPACT and TCGA. In addition, rare germline variant association analysis revealed that germline variation in ASXL1 had the strongest association with lung cancer susceptibility among all solid tumors. ConclusionsCollectively, our findings support a model in which smoking-associated expansion of ASXL1-mutant clones contributes to lung cancer development and suggest that gene-specific CHIP metrics may enhance risk stratification and early detection strategies.

Background: Despite epidemiological interest in aspirin's chemopreventive potential against glioma, the underlying multi-layered molecular mechanisms -- spanning COX-2/PGE2 signaling, iron metabolism, ferroptosis, epigenetic regulation, and the NEO1/hepcidin regulatory axis -- have not been systematically characterized at the multi-omics level. Methods: We conducted an integrative multi-omics analysis leveraging TCGA-GBM (n=172) and TCGA-LGG (n=534) transcriptomes, CPTAC GBM proteomics (n=99), TCGA HM450K DNA methylation data (GBM n=140, LGG n=516), GEO aspirin perturbation datasets, IEU OpenGWAS summary statistics, and independent single-cell RNA-seq data (GSE131928, 28 GBM patients). Eight analytical tracks were executed: (1) COX-2/PGE2 pathway profiling, (2) BBB tight junction characterization, (3) GEO-derived aspirin response signature projection, (4) gut-brain axis evaluation, (5) Mendelian randomization (MR) using PTGS2 cis-SNPs, (6) iron metabolism and ferroptosis pathway analysis, (7) NEO1/HFE2/BMP6/HAMP regulatory axis characterization with multi-omics validation, and (8) single-cell transcriptomic validation across GBM malignant cell states. Results: Transcriptomic analysis revealed profound reprogramming of the NEO1/hepcidin iron regulatory axis in GBM: HAMP (hepcidin) was massively upregulated (log2FC=+2.92, P=5.0e-37), accompanied by TFRC upregulation (log2FC=+1.38, HR=2.30, P=3.6e-42) and NEO1 downregulation (log2FC=-0.57, HR=0.59, P=4.6e-6). De novo HM450K methylation analysis revealed HAMP as the dominant epigenetic target in the iron network, exhibiting the strongest hypomethylation signal (DeltaBeta=-0.265, P=1.4e-48), while NEO1 and TFRC showed constitutively low baseline methylation (Beta<0.05). Gene set enrichment analysis identified ferroptosis driver genes (NES=+1.861, P=0.030) and the iron deficiency response pathway (NES=+1.698, P=0.010) as the most significantly enriched pathways in GBM. Molecular subtype analysis revealed that the mesenchymal GBM subtype exhibits the highest iron metabolism gene expression. Mendelian randomization established a causal relationship between PTGS2 expression and glioma risk (IVW OR=1.31, P=1.1e-4). Single-cell RNA-seq analysis validated that iron metabolism gene expression is heterogeneously distributed across malignant cell states, with the mesenchymal state exhibiting the highest HAMP expression and elevated ferroptosis vulnerability. GPX4 was universally highly expressed across all cell states, indicating pan-GBM dependence on GPX4-mediated ferroptosis suppression. Conclusions: This multi-omics investigation reveals that the NEO1/hepcidin iron regulatory axis is epigenetically reprogrammed in glioma, driving iron-dependent vulnerability that bridges COX-2 signaling with ferroptosis susceptibility. The convergent evidence from transcriptomics, proteomics, epigenomics, and causal inference provides a comprehensive mechanistic framework for aspirin's protective effects against glioma and identifies the NEO1/HAMP/TFRC axis as a promising therapeutic target.

The gut microbiome has been implicated in alcohol use disorder (AUD), but its relationship to drinking intensity and treatment response remains poorly understood. We conducted a longitudinal multi-omics analysis of stool samples collected at baseline and endpoint (after 12 weeks) from 122 participants enrolled in a double-blind, placebo-controlled trial of dutasteride for AUD. Gut microbiome composition was characterized using 16S rRNA gene sequencing, and fecal metabolites were measured by LC-MS-based metabolomics. At baseline, drinking intensity was associated with increasingly lower microbial richness. Genera in the class Clostridia emerged as key microbial hubs associated with drinking intensity in an age- and sex-dependent manner. Drinking intensity promoted co-enrichment of [Ruminococcus] gnavus group and [Clostridium] inocuum group with amino acid catabolites, as well as the co-depletion of diverse Clostridia taxa and lipid metabolites. Dutasteride treatment and drinking reduction had minimal impact on gut microbiome composition. Random forest models integrating baseline clinical, microbiome, and metabolome data improved the classification of clinically meaningful drinking reduction compared to models using clinical data alone. These findings show that a coupled baseline gut microbiome-metabolome signature is associated with drinking intensity and future treatment response in AUD, highlighting the potential for multi-omics integration to inform precision treatment approaches.

ABSTRACTUlcerative colitis is a chronic inflammatory bowel disease that can progress from dysplasia to cancer. Inflammatory responses are critical drivers in this process, typically triggered by epithelial lesions and the ensuing infiltration of microbiota into the interstitial layer. Here, we focus on the pro-inflammatory state of the interstitial fibroblasts, which promotes immune infiltration and augments disease progression. The study aims to provide a mechanistic link how fibroblasts of the colitis-associated microenvironment integrate inflammatory signals, microbial infiltration and cellular memory. To this end, we investigated a large number of primary colon fibroblasts obtained from normal, colitis and colon cancer samples using a range of in vitro approaches and an in vivo co-inoculation cancer model. mRNA sequencing analysis identified that the disease-associated fibroblasts are exhibit a cellular inflammatory status, which involves the injury-induced senescence pathway. Using CXCL8, a potent chemokine upregulated in colitis and cancer colon fibroblasts, as a paradigm, this inflammatory status is triggered by the activation of the NF{kappa}B signaling via immune-derived cytokines (TNF, IL-1{beta}), bacterial signals (LPS) and the microbiome itself using mycoplasma as a paradigm. Finally, iPSC reprogramming studies indicate that fibroblasts from ulcerative colitis retain an epigenetic memory that sustains elevated CXCL8 expression. Together, our findings demonstrate that the senescence associated secretory phenotype of colon fibroblasts is a robust indicator for inflammation-driven colon tumorigenesis.

BackgroundThe Netrin-1 dependence receptor pathway plays critical roles in neural development, but its expression landscape and prognostic significance in glioblastoma (GBM) remain poorly characterized. MethodsSingle-cell RNA-seq data from 148,019 cells across 34 tumors (Neftel et al., 2019) were analyzed to map Netrin-1 pathway gene expression across GBM cellular states. Differential gene expression and pathway enrichment analyses were performed on NEO1-defined subpopulations. Bulk RNA-seq survival analysis was conducted across three independent GBM cohorts TCGA (n=106), CGGA mRNAseq_325 (n=137), and CGGA mRNAseq_693 (n=237), totaling 480 patients. Primary analysis used continuous Cox regression (per-SD hazard ratios); meta-analysis employed fixed-effects inverse-variance weighting. ResultsIn GBM single-cell data, Netrin-1 pathway genes showed state-specific enrichment --NEO1, DCC, NTN1, and RGMB were predominantly expressed in oligodendrocyte-precursor (OPC) and neural-progenitor (NPC) states. Cells positive for NEO1 were enriched for neural differentiation programs (nervous system development, p=9.6x10-; Axon Guidance, p=2.8x10-), whereas NEO1-negative cells were dominated by ribosomal/translational and immune activation programs. In the 3-cohort survival meta-analysis, NTN1 (Netrin-1 ligand) emerged as the sole gene reaching meta-analytic significance as a risk factor (Meta HR=1.163 per SD, 95% CI 1.056-1.281, p=0.0021, I{superscript 2}=0%, 3/3 cohorts concordant), while DCC and RGMB showed directionally consistent protective trends (DCC: Meta HR=0.938, 95% CI 0.858-1.025, p=0.156; RGMB: Meta HR=0.979, 95% CI 0.881-1.087, p=0.686; both 3/3 cohorts concordant). NEO1 itself did not independently predict survival (Meta HR=1.008, 95% CI 0.885-1.147, p=0.910). After Bonferroni correction for 10 genes tested (threshold p<0.005), only NTN1 met strict significance. In exploratory sex-stratified analysis of a single cohort (CGGA 693, n=237), NEO1 and NTN1 exhibited female-specific risk enhancement (NEO1: HR=1.417, p=0.014; NTN1: HR=1.249, p=0.019), with minimal effects in males. UNC5B showed context-dependent risk in MGMT-unmethylated tumors (HR=1.331, p=0.037). These sex-dimorphic findings require independent validation. ConclusionsThe Netrin-1 pathway exhibits divergent prognostic trends in GBM, with NTN1 as a risk factor and DCC trending toward protection--consistent with the dependence receptor model. These findings, which should be interpreted as hypothesis-generating, nominate NTN1 as a candidate therapeutic target and highlight the potential importance of sex-stratified evaluation in future Netrin-1-directed trials. Independent replication in larger cohorts is warranted.

BackgroundPatients with systemic lupus erythematosus (SLE) face markedly increased cardiovascular disease (CVD) risk driven by mechanisms beyond traditional risk factors. Thoracic aortic perivascular adipose tissue (tPVAT) is dysfunctional in lupus and exacerbates endothelial dysfunction, yet the molecular basis of this dysfunction remains poorly defined. MethodsIntegrated multi-omics profiling, including bulk RNA-seq, untargeted proteomics, lipidomics, and high-dimensional spectral flow cytometry, was performed on tPVAT from 15-week-old MRL/lpr mice (active lupus, n = 4-6) and MRL control mice (n = 5-6). Adipogenic differentiation capacity of tPVAT adipose stromal and progenitor cells (ASPCs) from MRL/lpr was assessed by Oil Red O staining at 5 (pre-dieasea) and 15 weeks (active disease), with subcutaneous ASPCs used as depot controls. ResultsTranscriptomic profiling of tPVAT from MRL/lpr mice identified 2,742 upregulated and 1,494 downregulated genes (adjusted p < 0.001, |log2FC| > 1), with strong activation of interferon, IL6-JAK-STAT3, and TNFA signaling pathways together with suppression of fatty acid metabolism, oxidative phosphorylation, and adipogenic pathways. Proteomic and lipidomic analyses were concordant, revealing broad downregulation of mitochondrial bioenergetic machinery, depletion of cardiolipin and acylcarnitines, and enrichment of ceramide phosphoinositols and lysophosphatidylcholines. Cardiolipin strongly correlated with the mitochondrial/metabolic protein module (r = 0.95) and inversely with the immune/inflammatory protein module (r = -0.92). Spectral flow cytometry confirmed marked CD45+ leukocyte infiltration dominated by T cells, together with a significantly reduced Treg/CD4+ ratio indicating loss of local immunoregulatory balance. ASPCs derived from PVAT of 15-week-old MRL/lpr mice exhibited impaired white and beige adipogenic differentiation, while APCs from PVAT of 5-week-old MRL/lpr mice, and from subcutaneous adipose tissues of 15-week-old MRL/lpr mice, had normal white and beige differentiation, consistent with an acquired, depot-specific, disease-stage-dependent progenitor defect in PVAT of MRL/lpr mice. ConclusionsLupus tPVAT undergoes a concordant cross-platform molecular reprogramming of mitochondrial bioenergetic genes coupled with establishment of an interferon-dominant immune niche and acquired loss of ASPC adipogenic capacity. These findings provide a molecular framework for lupus PVAT dysfunction and identify restoration of mitochondrial function, suppression of interferon-driven inflammation, and renewal of progenitor differentiation as potential therapeutic strategies for lupus vasculopathy.

Background As dementia prevalence rises globally, it is critical to find preventions that target modifiable risk factors like blood pressure. Pulse pressure (PP), a marker of arterial stiffness, contributes independently to cognitive impairment. Yet, clinically interpretable thresholds for PP for cognitive decline remain undefined. We examined the independent association between PP and domain-specific cognitive trajectories and identified PP thresholds associated with greater cognitive decline across ethnically diverse regional populations. Methods Data were harmonized across three longitudinal cohorts (54,878 participants with up to 20 years follow-ups and 266,144 observations). Linear mixed-effects models identified a nonlinear association between PP and cognition (memory, orientation, and executive function), whereby cognitive decline accelerated after around 50 mmHg of pulse pressure, despite controlling for mean arterial pressure and dementia risk factors. Stratification based on PP thresholds (Low: PP <30; Normal: 30 to <50; Borderline: [&ge;]50; and High: [&ge;]60 mmHg), and tested for differences in memory decline across groups. Stratified analyses were similarly conducted across other blood pressure measures, racial, age and sex groups. Findings Non-linear associations indicated that memory decline was particularly noticeable for pulse pressure [&ge;]60 mmHg. Compared with normal pulse pressure, [&ge;]60 mmHg was associated with worse memory performance (pooled {beta} -0.062 SD; 95% CI -0.107 to -0.016) and greater memory decline with age (-0.026 SD/year; -0.036 to -0.015), including among normotensive individuals. Findings were consistent across diverse regional cohorts (UK, US and China), racial groups, age strata and sexes. Interpretation Pulse pressure over 60 mmHg is associated with elevated cognitive risk, independent of blood pressure measures, even among normotensive individuals. These findings support pulse pressure thresholds as clinically interpretable and complementary markers of cognitive risk.