Epigenetics

Introduction: HIV and childhood maltreatment (CM) are both chronic stressors that disproportionately affect women, with each contributing to accelerated biological aging. Whether biological aging markers are convergent and associate with HIV and CM is unclear. Methods: We studied 238 women (122 with HIV), characterised for CM severity, and assessed biological aging using absolute telomere length (aTL), mitochondrial DNA copy number (mtDNAcn), magnetic resonance imaging-based brain-predicted age difference (MRI-BPAD), and DNA methylation age (DNAmAge) clocks. CM was measured with the Childhood Trauma Questionnaire-Short Form total score. We examined intercorrelations among biological aging markers to assess convergence and conducted linear regression models to test moderation by HIV status and CM severity. Results: PWH had shorter aTL, lower MRI-BPAD, and higher Horvath age acceleration (HorvathAA), HannumAA, PhenoAA, and extrinsic epigenetic age acceleration (EEAA). CM had limited associations with biological aging markers. Absolute TL correlated weakly with mtDNAcn (p = 0.36), PhenoAA (p = -0.18), and EEAA (p = -0.18), while MRI-BPAD correlated weakly with PhenoAA (r = 0.20). DNAmAge clocks were moderately to strongly intercorrelated (r = 0.35 - 0.93). No robust two- or three-way moderation effects were observed after false discovery rate correction. Conclusion: Our findings support a multidimensional pattern of biological aging, with substantial convergence among epigenetic aging measures but limited relationships across different markers, largely independent of HIV status and CM severity. Longitudinal approaches are needed to clarify how distinct biological aging markers relate to one another and to health outcomes over time in vulnerable populations.

Preterm birth is strongly linked to systemic inflammation and encephalopathy of prematurity, which underlies subsequent cognitive impairment. T-cell immunity contributes to brain-immune crosstalk across the life course but its role in the pathogenesis of encephalopathy of prematurity is unknown. Protein epigenetic scores are DNA methylation (DNAm)-based proxies of circulating proteins. We tested the hypothesis that T-cell dysregulation has a specific role in child neurodevelopment following preterm birth. Multimodal data were collected from 144 preterm infants (median gestational age at birth 29+5 weeks [range 23+3 to 32+6]) recruited to a prospective cohort study: saliva DNAm for protein epigenetic score derivation and brain MRI, both at term-equivalent age, and the Mullen Scales of Early Learning Composite score at 5 years from a subset. We investigated associations of the epigenetic scores for cytotoxic and regulatory T cell-associated molecule (DNAm CRTAM) and C-reactive protein (DNAm CRP; a non-specific marker of inflammation) with MRI metrics of encephalopathy of prematurity: global and regional brain volumes, and general factors of diffusion tensor imaging and neurite orientation dispersion and density imaging metrics averaged across 42 white matter tracts. We tested whether DNAm CRTAM explains more variance than DNAm CRP in MRI metrics of the encephalopathy of prematurity and cognitive scores in childhood. Higher neonatal DNAm CRTAM was associated with lower general factor of fractional anisotropy ({beta} = -0.252, q = 0.011) and higher general factors of radial diffusivity ({beta} = 0.215, q = 0.039), mean diffusivity ({beta} = 0.198, q = 0.047) and orientation dispersion index ({beta} = 0.201, q = 0.048), independent of inflammatory morbidities and other biological covariates after false discovery rate correction. DNAm CRTAM explained more variance than DNAm CRP (maximum incremental R2 = 4.2% vs 1.5%) in diffusion MRI metrics. Higher neonatal DNAm CRTAM was associated with lower cognitive scores at 5 years, independent of DNAm CRP and other covariates ({beta} = -0.332, P = 0.008), and explained more variance in cognitive scores than DNAm CRP (incremental R2 = 9.4% vs 1.2%). An epigenetic proxy of CRTAM in preterm infants is associated with both encephalopathy of prematurity in the neonatal period and lower cognitive performance at 5 years, explaining greater incremental variance than a non-specific marker of inflammation. The data implicate T-cell dysregulation in the pathophysiology of atypical neurodevelopment following preterm birth.

Chromatin profiling methods, such as ChIP-seq (chromatin immunoprecipitation followed by sequencing), are used to characterize the genomic localization of DNA-associated proteins. While ChIP and ChIP-seq have been used for decades, an orthogonal approach, CUT&Tag (Cleavage Under Targets and Tagmentation), is gaining popularity as an efficient and cost-effective alternative. Although previous comparative studies note discrepancies in signal-to-noise ratios and detection bias at certain genomic regions, many differences between ChIP-seq and CUT&Tag results remain largely unreconciled. Here, we systematically investigate the disagreeing signals captured by these two methods across well annotated genomic regions. We assess multiple histone mark profiles generated by different groups in two cell lines (K562 and MCF-7). Overall, our analysis indicates that compared to ChIP-seq, CUT&Tag may have limited sensitivity in low-GC environments and, as previously observed, increased signal in hyper-accessible chromatin. Notably, within GC-poor regions of active gene bodies and Polycomb-repressed domains, CUT&Tag exhibits a loss of H3K36me3 and H3K27me3 signal, respectively, where occupancy of these histone marks is otherwise expected. Further, active promoters with discrepant H3K4me3 and H3K27ac signal between the two assays differ systematically in GC content and chromatin accessibility. Promoters differentially enriched for CUT&Tag signal relative to ChIP-seq generally show higher, broader GC-content profiles and higher DNase-seq and ATAC-seq signal, while promoters enriched for ChIP-seq signal harbor the opposite characteristics. A local bias for high GC content and/or chromatin accessibility in CUT&Tag may also explain its differing signal patterns at nucleosome-depleted regions (NDRs) compared to ChIP-seq and MNase-seq promoter profiles. Altogether, our results highlight that studies focused on profiling the intensity and structure of histone modification occupancy can be sensitive to potential biases of CUT&Tag to GC content and chromatin accessibility. These characteristics should be accounted for when selecting a chromatin profiling approach, analyzing and interpreting data as well as drawing biological conclusions.

Environmental exposures can induce epigenetic modifications that persist across generations, potentially contributing to the transmission of environmentally-induced phenotypes. However, the extent to which such persistence of molecular changes are maintained independently of genetic mechanisms remains unclear. In this study, we investigated the evolution and genetic determinism of DNA methylation (DNAm) variation across three successive generations of Japanese quails (G0 to G2) belonging to two epilines, defined according to whether their female ancestor had received genistein supplementation (epi+) or not (epi-). Using reduced representation bisulfite sequencing (RRBS), we characterised CpG methylation patterns and identified differentially methylated cytosines (DMCs) and regions (DMRs) between control and genistein-supplemented epilines. Out of 112,745 CpG sites analysed, no DMCs or DMRs were detected between epilines in the first generation following exposure (G0), whereas 621 DMCs (36 DMRs) were identified in G1, and 1,381 DMCs (101 DMRs) in G2. Despite this progressive increase of differential methylation sites, mean differences in methylation rate between epilines were globally small. Similarly, genome-wide genetic differentiation between epilines was very limited. Overall, SNP-based heritability of DNA methylation was 0.19 indicating that genetic variation accounted for only a small part of the global variation of DNAm levels. By contrast, DNAm at differentially methylated CpG sites was extensively under genetic control, with a mean SNP-based heritability > 0.5, and meQTL analysis further identified significant associations between SNPs and methylation levels. Together, these results indicate that local DNAm differentiation in quail is under substantial genetic regulation, while the limited genetic differentiation between groups suggests that genetic variation alone can not fully explain the progressive accumulation of methylation differences following an ancestral exposure to genistein. These results support DNAm as a plausible molecular candidate mechanism in the multigenerational response to environmental exposure and highlight the complex interplay between genetic and epigenetic regulations in the inheritance of phenotypes.

Quantifying the differentiation state of cells is an important task in regenerative medicine, cellular reprogramming and in elucidating how differentiation hierarchies are altered in aging and disease. For DNA methylation data (DNAm) there is however an accute shortage of methods for quantifying differentiation state. Here we use machine learning to build EpiDiff, a predictor of differentiation that yields a continuous absolute differentiation index (DI) when applied to a DNAm sample. We extensively validate EpiDiff in single-cells, sorted cells and bulk tissue, as well as in in-vitro differentiation, organoid, reprogramming and cellular rejuvenation experiments. In mixed samples, EpiDiff measures the extent of differentiation across all cellular lineages. In sorted cell populations, we find that DI increases with age and, underpinning this increase, we discover that many cell-types undergo a developmental epigenetic drift that is most prominent towards the mesenchymal lineage. When applied to normal-tissues, EpiDiff is predictive of carcinogenic exposure and cancer risk. In summary, EpiDiff is a unique, general and versatile tool that can accurately quantify the global differentiation state of a DNAm sample with broad applicability to many disciplines.

Somatic mutations in the de novo DNA methyltransferase DNMT3A are frequent in clonal hematopoiesis, but how they alter the function of differentiated myeloid cells remains unclear. Here, we used isogenic human embryonic stem cell-derived macrophage models to define the consequences of DNMT3A dysfunction during myeloid differentiation. DNMT3A-mutant macrophages selectively upregulated bivalent Polycomb target genes, accompanied by DNA hypomethylation, reduced H3K27me3 and increased promoter accessibility. Despite broad epigenetic changes across bivalent promoters, transcriptional derepression occurred at a subset of loci characterized by lower baseline DNA methylation and higher H3K27me3, identifying pre-existing chromatin state as a determinant of transcriptional response. This Polycomb-associated program was conserved in murine macrophages and enriched for genes involved in cell migration and wound repair. DNMT3A-mutant macrophages exhibited enhanced migration and preferential early recruitment to injured tissue. These findings link clonal hematopoiesis-associated epigenetic alterations to selective transcriptional reprogramming and altered function of differentiated myeloid cells.

Background: Infants <30 weeks gestational age (very preterm (VPT)), are at risk of experiencing multiple serious neonatal morbidities. These morbidities impart serious biological stress, which may be reflected in dysregulated protein expression even after the morbidities have resolved. Recent studies suggest that DNA methylation-based predictors of circulating proteins may reflect the molecular effects of neonatal adversity. The objective of this study is to examine associations between DNA methylation-derived EpiScores, which are externally trained methylation signatures that proxy circulating protein levels, and neonatal morbidity burden in children born VPT. Buccal DNA methylation was obtained at NICU discharge in 537 infants from the NOVI cohort. A total of 111 EpiScores were calculated and tested for association with multimorbidity (0-1 vs. [&ge;] 2 morbidities) using adjusted linear regression models. Cross-tissue analyses in an external paired blood-buccal dataset (n=21) were used to identify EpiScores with moderate-to-strong correlations across tissues. Results: Eighteen EpiScores were nominally associated with multimorbidity (p < 0.05), with Melanoma-derived growth regulatory protein (MIA) with FDR < 0.05 (beta = 0.0023, p = 0.0004). In cross-tissue analyses, 35 EpiScores yielded r > 0.50 (p<0.05), 11 of which showed nominal associations with multimorbidity, including MIA. Overall, the morbidity-associated EpiScores reflected immune, inflammatory, metabolic, and growth-related pathways. Conclusions: Buccal DNA methylation-derived EpiScores capture biological signatures associated with neonatal morbidity burden in very preterm infants.

Background: Millions of textile and agricultural workers inhale organic dust containing endotoxin, an exposure associated with impaired respiratory function. However, the underlying biological pathways remain unclear. We conducted a two-cohort epigenome-wide association study (EWAS) to identify airborne endotoxin-associated DNA methylation (DNAm) alterations and pathways. Methods: In the discovery phase, we compared blood DNAm in 281 endotoxin-exposed cotton workers and 253 unexposed silk-workers from the Shanghai Textile Worker Study (STWS) measured using Illumina MethylationEPICv2 arrays. STWS endotoxin assessment combined detailed work histories and onsite measurements. For targeted parallel validation, we tested STWS signals in 686 incident lung cancer cases and 683 matched controls from the Shanghai Women's Health Study (SWHS), using occupation-derived low, medium, or high exposure-intensity ranks based on published evidence. To gain biological insight, we analyzed pathway enrichment, immune-cell composition, DNAm inflammation risk scores (IRSs), and respiratory phenotype associations in STWS. Results: In STWS, we identified 36 epigenome-wide significant DNAm sites (P<5e-8), of which, 35 were hypomethylated. Among 30 sites testable in SWHS, 18 had concordant effect directions, and four were nominally significant: cg11869499 (POLG; P=0.041), cg16290931 (TSKS; P=0.044), cg05019530 (EPIC1; P=0.042), and cg26033526 (PSMB9/TAP1; P=0.013). Enrichment implicated immune and signal-transduction pathways, including IgSF cell-adhesion-molecule signaling (FDR=8.2e-6;). Neutrophil were higher in cotton workers than in silk workers (63.5% vs 58.9%, p=7.52e-10). Cumulative endotoxin was associated with higher CRP-based IRSs, which showed the most consistent associations with lower lung function and airflow obstruction. Conclusions: Our EWAS findings suggest that occupational endotoxin may operate partly through immune-cell composition and inflammatory pathways.

Hallmarks of biological ageing are closely interconnected with neurodegenerative diseases. Deoxyribonucleic acid methylation (DNAm) clocks quantify biological age and may serve as peripheral biomarkers of neurodegenerative diseases. This systematic review and meta-analysis aim to examine associations between DNAm-based biological age metrics and neurodegenerative diseases. Six databases were systematically searched from 1st January 2011 to 15th April 2026 for studies reporting associations between DNAm-based ages and neurodegenerative diseases including all-cause dementia, Parkinson's Disease, Multiple Sclerosis, and Amyotrophic Lateral Sclerosis. Correlated-and-hierarchical-effects meta-analyses were fitted using restricted maximum likelihood with Knapp-Hartung adjustment. Of 42,023 records screened, 37 observational studies (n=46365; 60.5% female; median of mean age 69.4 years [IQR 62.5-73.3)) and seven Mendelian randomization studies met inclusion criteria. In longitudinal meta-analyses, higher GrimAge epigenetic age acceleration (EAA) was significantly associated with higher dementia risk (HR per SD 1.11 [95% CI 1.02-1.20]; I^2 = 0.0%; p = 0.018), whereas Horvath1 EAA, Hannum EAA, PhenoAge EAA, and DunedinPACE were not significantly associated with dementia risk. Evidence for other neurodegenerative diseases were heterogeneous across clock generations and study designs. Mendelian randomization provided limited evidence for causality. Higher GrimAge EAA was the only DNAm age measure consistently predictive of higher all-cause dementia risk. Overall, however, DNAm age clocks show limited and inconsistent associations with neurodegenerative diseases, providing insufficient support for their use as disease biomarkers. These findings highlight the need to develop and independently validate disease-specific DNAm clocks and undertake pathway analyses to identify methylation changes associated with neurodegeneration and the biological processes they reflect.

This systematic review aimed to synthesize evidence on the association between DNA methylation (DNAm) age and all-cause and disease-specific mortality risks in adults. A systematic search of six databases from Jan 1 2011 to April 15 2026 identified articles assessing the association of DNAm age measures and all-cause or disease-specific mortality in adults from general or disease-specific populations. Effect sizes were pooled as hazard ratios (HRs) with 95% confidence intervals (CIs) using inverse-variance random-effects models. Of 42 023 records screened, 125 articles (380 705 participants) met the inclusion criteria, with 53 included in meta-analyses. Overall, 48 distinct DNAm clocks were evaluated. Higher DNAm ages were associated with higher risks of all-cause, cardiovascular, and cancer mortality risks. In general populations, GrimAge epigenetic age acceleration (EAA) showed consistent associations across mortality outcomes, with each 1 year higher GrimAge EAA associated with ~6-10% higher all-cause (31 cohorts, n=53 642, HR per SD: 1.46 [95% CI 1.38, 1.55], HR per 1-year: 1.09 [95% CI 1.08, 1.11], I^2=84.1%, p-value=1.21 x 10^(-14)), cardiovascular (6 cohorts, n=30 751, HR per SD: 1.55 [95% CI 1.38, 1.73], HR per 1-year: 1.10 [95% CI 1.07, 1.13], I^2=28.0%, p-value=1.71 x 10^(-4)), and cancer (5 cohorts, n=27 187, HR per SD: 1.31 [95% CI 1.15, 1.50], HR per 1-year: 1.06 [95% CI 1.03, 1.10], I^2=33.6%, p-value=4.76 x 10^(-3)) mortality. Clocks incorporating additional surrogates and technical refinements showed numerically larger pooled associations than their original counterparts. GrimAge2 (HR per SD: 1.65 [95% CI 1.53, 1.77] vs 1.46 [1.38, 1.55]) and PCGrimAge (1.56 [1.36, 1.78] vs 1.51 [1.32, 1.74]) showed higher pooled HR association with all-cause mortality than GrimAge. Further work is warranted to evaluate the responsiveness of DNAm clocks to interventions and potential clinical utility.

Palmitate-associated lipotoxic stress activates the endoplasmic-reticulum stress sensor protein IRE1, but how IRE1 signaling influences genotoxic-stress responses in triple-negative breast cancer remains unclear. Here, we investigated IRE1 and XBP1 signaling in MDA-MB-231 cells exposed to palmitate and etoposide. Under combined lipotoxic and genotoxic stress, XBP1 depletion increased DNA-damage accumulation in IRE1 wild-type cells but not in IRE1-deficient cells, whereas IRE1 re-expression reduced DNA damage. Pharmacologic IRE1 RNase inhibition also increased etoposide-associated DNA damage, supporting a protective role for IRE1 RNase-dependent signaling. IRE1 status and XBP1 manipulation differentially affected H2A.X and {gamma}H2A.X abundance, indicating context-dependent regulation of chromatin-associated DNA-damage signaling. At the RNA level, H2A.X was enriched in IRE1 immunoprecipitates, and the H2A.X-linked DNA-damage-response transcripts HUWE1 and BRCA2 also associated with IRE1 under combined stress. These findings link palmitate-activated IRE1-XBP1 signaling to genome-protective responses during genotoxic stress and identify a network of IRE1-associated DNA-damage-response transcripts in triple-negative breast cancer cells. Direct IRE1-mediated cleavage of these transcripts remains to be established.

Features of urbanicity have been linked to poor psychiatric health in adulthood, but little is known about their relationship with biological age and cognition earlier in life. Using the Avon Longitudinal Study of Parents and Children (ALSPAC), we tested associations between the built environment and epigenetic ages (EpiAgeAltum, EpiAgeHorvath, EpiAgePACE) (n=2,452), brain age (n=751), and cognition (n=12,199). Analyses were replicated in Generation R and triangulated in the Millennium Cohort Study. The built environment was not associated with epigenetic ages ({beta}Altum range = 0.013-0.015, p range = .466-.689; {beta}Horvath range = -0.011-0.023, p range = .182-.728; {beta}PACE range = -0.045-0.013, p range = .131-.524) or brain age ({beta} range = 0.022-0.028, p range = .337-.429). A negative association with cognition was observed in Generation R. We provide no consistent evidence that childhood built environment exposure relates to biological age and cognition in adolescence, suggesting these relationships may emerge in later life.

Background: Preeclampsia (PE) is a hypertensive pregnancy disorder with contributions from both maternal and fetal genetic factors, but how both genomes regulate placental transcription remains incompletely understood. Results: We analyzed placental 5'-end RNA sequencing data from 59 pregnancies in the FINNPEC cohort and performed separate maternal and fetal cis-eQTL analyses using gene-level expression and promoter-level expression defined as Transcript Far 5' Ends (TFE). Genotype-by-PE interaction models were used to identify genetic effects that differ according to PE status. No gene-level interaction eQTLs remained significant after multiple-testing correction, although suggestive signals included LILRB2 in the maternal and LPCAT3 in the fetal analyses. In contrast, we identified two significant syntenic promoter-level interaction eQTLs: rs12504642-TFE61820 at the FHDC1 locus in the maternal analysis and rs1557150-TFE9032 at the PPIAP31 locus in the fetal analysis. Conclusion: These findings suggest that PE-dependent genetic interaction effects may be detectable at specific transcript promoter regions even when they are not captured at annotated gene levels.

Background: Current recommendations limit the use of menopausal hormone therapy (MHT) principally to the management of menopausal symptoms, largely because of concerns regarding increased breast cancer (BC) risk. The impact of MHT use on systemic biological aging and blood methylome and its overlap with that of menopause timing remains incompletely understood. Methods: In females (N=78,209) of the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial, we used Cox models to assess the associations of menopause timing (ordinal age at menopause; binary early-M [<45 years] vs non-early-M [[&ge;]45 years]) and MHT use with BC incidence, mortality, and survival. In a nested case-control subset with blood DNA methylome (DNAm; 758 cases, 745 controls), we related both exposures to epigenetic clocks and DNAm-based telomere length (DNAmTL) and used polygenic instruments to test both causal directions. Results: Ever MHT use was associated with higher BC incidence (aHR 1.17, 95% CI 1.10-1.24), particularly for hormone-receptor positive (HR+) subtypes (1.19, 1.11-1.27), whereas early-M was associated with lower HR+ incidence (0.88, 0.81-0.96) but not with overall incidence after adjustment (0.94, 0.88-1.01). However, ev-er MHT use was associated with lower BC mortality (0.72, 0.62-0.83) and better overall survival (0.87, 0.81-0.95). In the DNAm subset, non-early-M was associated with slower epigenetic aging and longer DNAmTL par-ticularly in cases. Higher cumulative aging and pace-of-aging markers predicted worse survival and partially mediated the early-M associations. Genetic analyses supported shared polygenic architecture between meno-pause timing and DNAm aging biomarkers rather than simple causation. MHT showed no broad epigenetic age acceleration and its profound methylome and immune-marker signatures largely did not overlap with those of menopause timing. Conclusions: Ever MHT use was associated with lower BC mortality and better overall survival despite higher BC incidence. Systemic aging detected more than a decade after menopausal transition correlates with early menopause. MHT use shows molecular signatures distinct to those seen for menopause timing.

The gut-brain axis has emerged as a critical modulator in neurological diseases, including stroke. While acute post-stroke dysbiosis is well established, it remains unclear whether these alterations persist long-term and can be therapeutically modulated. This study addresses this gap through integrated metagenomic and metabolomic profiling in two independent clinical stroke cohorts, complemented by experimental models. Experimental stroke induced persistent changes in gut microbiota composition and altered short-chain fatty acid profiles. In patients, microbiota composition remained distinct from controls up to three months after ischemic stroke or transient ischemic attack (TIA), accompanied by persistent reductions in propionic and valeric acid and reduced abundance of Prevotella-associated microbial signatures. We performed a randomized, double-blind interventional trial (PRISE) testing a multispecies probiotic versus placebo, using household members as additional controls. Probiotic intervention led to microbiome compositional changes with increased abundance of beneficial taxa and significantly improved functional recovery. The tested probiotic strains showed anti-inflammatory and antioxidant effects in vitro. These findings suggest that targeted modulation of the microbiome represents a promising therapeutic avenue to improve chronic stroke recovery, warranting validation in larger Phase III clinical trials.

Fetal development is highly sensitive to environmental influences, including maternal smoking during pregnancy (MSDP) and air pollution. The placenta may play a central role in mediating these effects through epigenetic mechanisms, including small non-coding RNAs (sncRNAs). While most studies have focused on microRNAs (miRNAs), other sncRNA classes remain poorly characterized. Here, we characterized the placental sncRNA landscape and investigated its associations with prenatal exposure to MSDP and air pollution. The sncRNA expression profile of 390 chorionic villi samples from the Barcelona Life Study Cohort (BiSC) was measured using small RNA sequencing and the seqBuster/seqCluster pipeline. MSDP was assessed via questionnaire, and prenatal exposure to black carbon (BC), particulate matter [&le;]2.5 m (PM2.5), and nitrogen dioxide (NO2) was estimated using hybrid dispersion-land-use regression (LUR) spatiotemporal models. Associations were evaluated using linear regressions adjusted for relevant covariates. We identified 979 placental sncRNA clusters, assigned primarily to miRNAs (33.2%), piRNAs (26.4%), snoRNAs (12.2%), tRFs (7.8%), and others (20.4%). MSDP was associated with the downregulation of miR-421 and the upregulation of multiple snoRNAs from the imprinted DLK1-DIO3 locus (SNORD113-4, SNORD114-2, SNORD114-3, and SNORD114-17), as well as the piR-26394. No sncRNAs remained significantly associated with air pollution after multiple-testing correction, although several miRNAs showed suggestive associations. Overall, this study provides a comprehensive characterization of placental sncRNAs and identifies previously unreported smoking-associated sncRNAs within the imprinted DLK1-DIO3 locus, expanding our understanding of placental epigenetic responses to prenatal environmental exposures.

Despite recent evidence of the ability of systemic and organ-specific proteomic aging clocks to predict a large range of age-related diseases, their utility in cancer research remains largely underexplored. In this study, we evaluated the predictive ability of systemic and organ-specific proteomic aging clocks for (i) all-cause mortality, (ii) cancer-related mortality, and (iii) cancer incidence in a sample of Finnish twins (N = 401, mean age at baseline 62.3 years) with Olink proteomic data. Participants were followed for a mean of 10.6 years (SD +- 1.6), with estimates from four systemic and 18 organ-specific proteomic aging clocks calculated at baseline. Cox proportional hazards regression models adjusted for sex and age at baseline identified 15 proteomic aging clocks as significant predictors of all-cause mortality (Ncases = 28) after multiple testing correction (FDR < 0.05), with 11 remaining significant after lifestyle adjustment (Ncases = 27). For several clocks, effect sizes were large, with hazard ratios (HR) approximately doubling per one standard deviation (SD) increase in clock estimates. In predicting cancer-related deaths among participants without a prior cancer diagnosis at baseline (Ncases = 9), only the Immune clock showed a significant positive association after multiple testing correction in basic (HR = 2.94, 95% CI: 1.88-4.59) and lifestyle-adjusted models (HR = 3.31, 95% CI: 1.78-6.17). No associations with cancer incidence (Ncases = 34 basic, Ncases = 31 adjusted) survived multiple testing correction, although several nominal associations were observed. In conclusion, our findings suggest that proteomic aging clocks are strong predictors of all-cause and cancer-specific mortality, independent of lifestyle factors. Proteomic aging clocks may further serve as valuable tools for stratifying cancers by mortality risk.

Changes of DNA sequence in the human genome may contribute to human aging, but it has been difficult for the field to define the details of the contribution. Cancer cells have altered ratios of DNA damage and repair pathways, and thus it is inappropriate to utilize them as models for normal cells. Also, somatic mutations from each lineage cannot be clearly identified in cell populations with multiple lineages. Normal human colon crypts are one of the few mini-organ systems where monoclonal cell populations can be found for somatic mutation analysis. In a parallel study, we described complex insertion/deletion (indel) events in normal human colon. Here we focus on simple deletions that lack any nucleotide addition or adjacent base substitutions. We find that ~58% of the simple deletions are consistent with a strand slippage event, and the remainder provide insights into other important repair processes. Among the 4,264 >=2-nucleotide simple deletions, ~71% are most consistent with nonhomologous DNA end joining (NHEJ), with <1.5% of the events being more consistent with alternative end joining (aEJ). The incidence of NHEJ-type simple deletions is ~8-fold more frequent than the complex indels that also show NHEJ features. Similar to the complex indels, the simple deletions show a linear trend of event accumulation (positive slope) with an overall ~10-fold increase in absolute number across the human lifespan, 0.8 months to 90 years old, for individuals with no radiation or chemotherapy treatment. Interestingly, radiation treatment increases non-slippage deletions with little effect on slip deletions.

Multiple sclerosis (MS) is approximately three times more common in females than in males, but sex-linked epigenetic mechanisms remain incompletely understood. We tested whether X-chromosome DNA methylation differs in females with MS and whether associated sites preferentially map to genes normally subject to X-chromosome inactivation (XCI). An X-chromosome-focused epigenome-wide association study was performed in whole blood from three datasets comprising 496 females with MS and 509 female controls, with independent evaluation in isolated CD4+ T cells (80 cases, 76 controls). At FDR < 0.01, 3 182 X-chromosome CpGs were hypomethylated in MS (mean {Delta}{beta} = -0.035). Hypomethylated CpGs were strongly enriched in non-escape genes normally subject to XCI relative to escape genes (OR 6.77; p = 1.55x10-57) and mapped to immune and chromatin-related processes. Exploratory cis-mQTL analysis identified strong local genetic effects at a small subset of loci, including WAS, IRAK1 and TLR7. In CD4+ T cells, 2 080 of the 3,182 whole-blood hypomethylated CpGs (65.4%) were also significantly hypomethylated. These findings identify a reproducible X-chromosome hypomethylation signature in female MS and support direct investigation of inactive-X regulation, XCI escape and X-linked immune gene dosage.

Background: Sex differences in asthma are well recognized, but sex-associated airway DNA methylation (DNAm) patterns and their relationships with gene expression remain incompletely characterized. We therefore conducted cis- and trans-expression quantitative trait methylation (eQTM) analyses using sex-stratified and CpG-by-sex interaction models. Methods: We analyzed nasal airway epithelial DNAm and transcriptomic data from 298 participants in the CAAPA discovery cohort. Asthma-associated differentially methylated CpGs (DMCs) were identified using sex-combined and sex-stratified models. Cis- and trans-eQTM analyses were then performed in participants with asthma using sex-combined, sex-stratified, and CpG-by-sex interaction models. To prioritize asthma-associated regulatory relationships, eQTMs that were also significant in non-asthmatic controls were excluded from downstream analyses. Replication in an independent bronchial epithelial cohort was defined by concordant effect direction and P < 0.05. Replicated targets underwent pathway and network analyses. Findings: Asthma-associated DMCs were predominantly hypomethylated in females and hypermethylated in males. Among trans-eQTMs, 379 associations were shared across all four models, whereas the majority were model-specific, indicating extensive sex-dependent regulatory architecture. We replicated 3, 1, 9, and 2 cis-eQTMs and 96, 84, 216, and 41 trans-eQTMs in the sex-combined, female-stratified, male-stratified, and interaction models, respectively. Sex-combined targets implicated innate immune and inflammatory signaling (TNF, IRF8); female-stratified targets implicated cytoskeletal remodeling, focal adhesion, and PI3K-Akt signaling (ITGA10); male-stratified targets implicated transcriptional regulation and post-translational modification (MOV10, HDAC7, CSF1, KAT2A); and interaction targets implicated lipid-mediator metabolism and inflammatory signaling and resolution (CYP2C9, LTB4R, CCL19). Our sex-dependent analyses showed that the majority of eQTMs resided within the trans-regulatory architecture, suggesting that sex-dependent gene expression differences are associated predominantly with trans rather than cis regulatory mechanisms. Pathway analyses revealed enrichment of innate immunity in the sex-combined model, structural remodeling in females, transcriptional control in males, and inflammatory resolution in the sex-interaction model. Interpretation: Sex-specific and sex-dependent airway methylation-expression associations were largely undetected by sex-combined analysis. Sex-aware analytical models may help resolve epigenetic mechanisms underlying sex differences in asthma biology.