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PubMed2026

Epigenome-wide analysis of DNA-methylation signatures following climate-related disasters.

BACKGROUND: Floods and tropical cyclones (TCs), two of the most frequent and costliest climate-related disasters worldwide, have been linked to sustained health risks extending beyond acute hazards. However, evidence on the underlying epigenetic mechanisms remains scarce. We aimed to characterize DNA methylation patterns associated with exposure to floods and TCs of varying intensities. METHODS: We collected peripheral blood samples from 479 women (132 twin pairs and 215 of their sisters) across Australia. Blood-derived DNA methylation profiles were assessed using the Illumina HumanMethylation450 BeadChip array. Daily flood and TC exposure data for the 6 years preceding each blood draw were obtained from the Dartmouth Flood Observatory and the International Best Track Archive for Climate Stewardship, respectively, and linked to participants based on residential addresses. Using a within-sibship analytical framework that accounted for shared familial factors and other relevant covariates, we examined associations between flood and TC exposures of varying intensities and site-specific methylation at each cytosine-guanine dinucleotide (CpG). Differentially methylated regions (DMRs) were identified using a combination of the comb-p and DMRcate algorithms. RESULTS: There were 164 CpGs and 219 DMRs associated with flood and TC exposures (Bonferroni-adjusted p value < 0.05), mapping to 242 genes enriched in pathways related to inflammation and immune regulation. These genes have been implicated in a wide range of human diseases or phenotypes. The number of differentially methylated CpGs increased with more recent and higher-intensity exposures. Intensity-dependent gene regulation was observed, with genes such as AMT and C22orf45 consistently implicated across various exposure levels, whereas RNF39 and ACY3 emerged only at higher intensities. CONCLUSIONS: Exposures to floods and TCs were associated with differentially DNA methylated signals across the human genome, exhibiting intensity-dependent patterns. The identified signals and related gene pathways may shed light on the biological mechanism underlying the profound health effects of climate-related disasters.

Humans↗

PubMed2025

Epigenome-Wide Analysis Identifies Pollution-Sensitive Loci in Fibrotic Interstitial Lung Disease.

Rationale: Particulate matter ⩽2.5 μm (PM2.5) adversely impacts patients with fibrotic interstitial lung disease (fILD). Objectives: We sought to determine whether PM2.5-associated epigenetic alterations contribute to the environmental pathogenesis of fILD. Methods: A retrospective two-cohort study applied satellite-derived PM2.5 and constituent exposure matching to the residential location of patients with fILD. Robust linear regressions were used to evaluate cohort-specific, epigenome-wide differential blood DNA methylation with increasing pollutant exposures (Illumina MethylationEPIC BeadChip). Cox and linear regressions were used to evaluate associations of cytosine-phosphate-guanine (CpG) loci with transplant-free survival and lung function. A Wilcoxon test was used to evaluate cartilage-associated protein (CRTAP) levels in fILD and control lungs. Measurements and Main Results: The University of Pittsburgh cohort (n = 306) had 5-year median PM2.5 exposures of 12.1 μg/m3 compared with 5.1 μg/m3 in the University of British Columbia cohort (n = 170). Higher pollutant exposures in the University of Pittsburgh cohort were associated with lower methylation at cg25354716, annotated to CRTAP, a critical extracellular matrix remodeling enzyme. Higher exposures in the University of British Columbia cohort were associated with higher methylation at cg01019301, annotated to TLN2 (talin-2), a cytoskeletal protein involved in fibroblast migration. A 10% increase in cg25354716 methylation was associated with a hazard ratio of 0.81 for death or lung transplantation in the meta-analyzed cohorts (95% confidence interval = 0.69-0.96; P = 0.01), whereas the same change in cg01019301 was associated with a hazard ratio of 1.36 (95% confidence interval = 1.07-1.74; P = 0.01). CRTAP protein was more abundant in lungs from patients with fILD compared with those from donor controls (P < 0.001). Conclusions: PM2.5 is associated with altered blood DNA methylation in fILD. This work identifies novel pollution-sensitive targets that hold potential for therapeutic modulation in fILD.

Humans↗

PubMed2022

Epigenome-wide meta-analysis of PTSD symptom severity in three military cohorts implicates DNA methylation changes in genes involved in immune system and oxidative stress.

Epigenetic factors modify the effects of environmental factors on biological outcomes. Identification of epigenetic changes that associate with PTSD is therefore a crucial step in deciphering mechanisms of risk and resilience. In this study, our goal is to identify epigenetic signatures associated with PTSD symptom severity (PTSS) and changes in PTSS over time, using whole blood DNA methylation (DNAm) data (MethylationEPIC BeadChip) of military personnel prior to and following combat deployment. A total of 429 subjects (858 samples across 2 time points) from three male military cohorts were included in the analyses. We conducted two different meta-analyses to answer two different scientific questions: one to identify a DNAm profile of PTSS using a random effects model including both time points for each subject, and the other to identify a DNAm profile of change in PTSS conditioned on pre-deployment DNAm. Four CpGs near four genes (F2R, CNPY2, BAIAP2L1, and TBXAS1) and 88 differentially methylated regions (DMRs) were associated with PTSS. Change in PTSS after deployment was associated with 15 DMRs, of those 2 DMRs near OTUD5 and ELF4 were also associated with PTSS. Notably, three PTSS-associated CpGs near F2R, BAIAP2L1 and TBXAS1 also showed nominal evidence of association with change in PTSS. This study, which identifies PTSD-associated changes in genes involved in oxidative stress and immune system, provides novel evidence that epigenetic differences are associated with PTSS.

Adaptor Proteins, Signal Transducing↗

PubMed2020

Epigenome-wide meta-analysis of PTSD across 10 military and civilian cohorts identifies methylation changes in AHRR.

Epigenetic differences may help to distinguish between PTSD cases and trauma-exposed controls. Here, we describe the results of the largest DNA methylation meta-analysis of PTSD to date. Ten cohorts, military and civilian, contribute blood-derived DNA methylation data from 1,896 PTSD cases and trauma-exposed controls. Four CpG sites within the aryl-hydrocarbon receptor repressor (AHRR) associate with PTSD after adjustment for multiple comparisons, with lower DNA methylation in PTSD cases relative to controls. Although AHRR methylation is known to associate with smoking, the AHRR association with PTSD is most pronounced in non-smokers, suggesting the result was independent of smoking status. Evaluation of metabolomics data reveals that AHRR methylation associated with kynurenine levels, which are lower among subjects with PTSD. This study supports epigenetic differences in those with PTSD and suggests a role for decreased kynurenine as a contributor to immune dysregulation in PTSD.

Basic Helix-Loop-Helix Proteins↗

PubMed2026

Epigenome-wide placental methylation landscapes in relation to antenatal depressive symptoms.

Antenatal depressive symptoms (ADS) are common during pregnancy and are linked to adverse maternal and offspring neurodevelopmental outcomes. The placenta plays a central role in maternal-fetal communication and may function as an epigenetic sensor of maternal psychological stress. However, placental epigenetic signatures associated with ADS remain poorly understood. This study investigated epigenome-wide placental DNA methylation patterns associated with ADS in an Indian cohort. Placental samples were collected at delivery from women recruited in early pregnancy into the STRiDE cohort. Depressive symptoms were assessed at 24-28 weeks' gestation using the Patient Health Questionnaire-9 (PHQ-9). Participants were classified as controls (PHQ-9 ≤ 4; n = 53) or ADS (PHQ-9 > 4; n = 54). Genome-wide DNA methylation profiling was performed using the Illumina Infinium MethylationEPIC array. Epigenome-wide association analysis identified no CpG sites that remained statistically significant after Benjamini-Hochberg FDR correction. Top nominal CpGs showed medium-to-large effect sizes for ADS. Exploratory analyses of the top nominally associated CpGs annotated to genes including TAP2, LRCH1, SLITRK2, RASSF1 and IL3 implicated in immune regulation, cellular signalling and neurodevelopment. Gene enrichment analysis suggested the involvement of biological processes and pathways related to synaptic organization, ion transport, Hippo signalling, and thyroid hormone regulation. In conclusion, the study findings provide preliminary evidence of DNA methylation signatures linked to potential candidate genes and biological pathways that may be relevant to ADS, supporting the need for validation in larger independent cohorts and functional experimental studies.

Asian Indians↗

PubMed2025

Estimating population structure using epigenome-wide methylation data.

INTRODUCTION: In epigenome-wide association analysis (EWAS), unaddressed population stratification often leads to inflation. We aimed to compute methylation population scores (MPSs) that predict genetic principal components (GPCs) using a feature selection and regression approach. METHODS: We used multi-ethnic methylation data (Illumina 450K/EPIC array) from unrelated MESA (n=929), CARDIA (n=1123), JHS (n=1365), ARIC (n=2338), and HCHS/SOL (n=1475) individuals, randomly assigning 85% of participants from each cohort to a training dataset and the remaining 15% to a test dataset. First, we estimated the associations of GPCs with each available CpG methylation site using linear regression within each cohort, adjusting for age, sex, smoking status, race/ethnic background (as a proxy for background information associated with lifestyle and other environmental exposures that may impact methylation), alcohol use status, body mass index, and cell type proportions. We meta-analyzed the associations across cohorts and selected CpG sites with association FDR-adjusted q-value <0.05. We next aggregated individuallevel data across the cohort-specific training datasets, and applied two-stage weighted least squares Lasso regression, with the GPCs as the outcomes and the selected CpG sites as penalized predictors, adjusting for the aforementioned covariates. The developed MPSs are the weighted sum of selected CpG sites from the Lasso. To evaluate the developed MPSs, we constructed them in the test dataset, and compared them with GPCs, and with MPSs constructed based on a previously-published paper. Comparison was based on correlation analysis and data visualization. We demonstrate the use of the MPSs in EWAS. RESULTS: In the test dataset, the MPSs were highly correlated with GPCs, with correlation decreasing, though not monotonically, for later components. Specifically, MPS1 and GPC1 had R2= 0.99, while MPS7 and GPC7 had R2=0.27 (the lowest observed correlation). In data visualization, MPSs had similar patterns as GPCs in differentiating self-reported White, Black, and Hispanic/Latino groups, while outperforming MPC constructed using alternative published methods. MPSs showed comparable performance to GPCs in reducing some of the inflation in EWAS. CONCLUSIONS: Methylation-based population scores provide a reliable estimate of population structure in the data and can complement GPCs when genetic data are absent. Unlike previous methods based on unsupervised methylation PCA, MPSs uses supervised learning with covariate adjustment to capture genetic structure across diverse populations. The weights for each GPCs derived in our study can be applied to generate MPSs in other studies.

Journal Article↗

PubMed2026

Genome-wide methylation profiling identifies signatures of pain, fatigue and health scores in women with systemic lupus erythematosus.

OBJECTIVES: People with systemic lupus erythematosus (SLE) experience high levels of pain and fatigue with poor overall health, which persist in those with low disease activity. By performing epigenome-wide DNA methylation analysis, this study aims to identify epigenetic alterations associated with self-reported scores for pain, fatigue and health in women with SLE. METHODS: Forty-eight women with SLE from the SLEGOT cohort were included. Study participants exhibited low disease activity (median SLEDAI-2K = 0) and minimal damage (median SLICC damage index = 0). An epigenome-wide DNA methylation analysis in whole blood identified 704 237 CpG loci, with 511 673 annotated to known genes. RESULTS: We identified 485, 591 and 577 differentially methylated CpGs linked to pain, fatigue and poor health, respectively. The association of reported pain with CpGs in GPR107, SPHK2, HBA1 and RERE genes suggested a potential role for neuromodulation in pain perception in SLE. For fatigue, enrichment analysis highlighted pathways related to neuronal development, morphogenesis and synaptic signalling. Nine genes, including BDNF and TGIF1, showed strong correlations with all three scores, suggesting a shared epigenetic influence that may underlie pain, fatigue and poor health in SLE. Specific microRNA genes were differentially methylated in relation to pain and fatigue. CONCLUSION: By studying a cohort of women with well-controlled SLE, we identified several CpGs and genes associated with pain, fatigue and general health. Our findings suggest that epigenetic changes in genes involved in neuronal modulation, rather than inflammatory pathways, could be involved in the development of these symptoms in patients with SLE.

Humans↗

PubMed2024

Association analysis between an epigenetic alcohol risk score and blood pressure.

BACKGROUND: Epigenome-wide association studies have identified multiple DNA methylation sites (CpGs) associated with alcohol consumption, an important lifestyle risk factor for cardiovascular diseases. This study aimed to test the hypothesis that an alcohol consumption epigenetic risk score (ERS) is associated with blood pressure (BP) traits. RESULTS: We implemented an ERS based on a previously reported epigenetic signature of 144 alcohol-associated CpGs in meta-analysis of participants of European ancestry. We found a one-unit increment of ERS was associated with eleven drinks of alcohol consumed per day, on average, across several cohorts (p < 0.0001). We examined the association of the ERS with systolic blood pressure (SBP), diastolic blood pressure (DBP), and hypertension (HTN) in 3,898 Framingham Heart Study (FHS) participants. Cross-sectional analyses in FHS revealed that a one-unit increment of the ERS was associated with 1.93 mm Hg higher SBP (p = 4.64E-07), 0.68 mm Hg higher DBP (p = 0.006), and an odds ratio of 1.78 for HTN (p < 2E-16). Meta-analysis of the cross-sectional association of the ERS with BP traits in eight independent external cohorts (n = 11,544) showed similar relationships with BP levels, i.e., a one-unit increase in ERS was associated with 0.74 mm Hg (p = 0.002) higher SBP and 0.50 mm Hg (p = 0.0006) higher DBP, but not with HTN. Longitudinal analyses in FHS (n = 3260) and five independent external cohorts (n = 4021) showed that the baseline ERS was not associated with a change in BP over time or with incident HTN. CONCLUSIONS: Our findings demonstrate that the ERS has potential clinical utility in assessing lifestyle factors related to cardiovascular risk, especially when self-reported behavioral data (e.g., alcohol consumption) are unreliable or unavailable.

Humans↗

PubMed2024

A Strong Dysregulated Myeloid Component in the Epigenetic Landscape of Systemic Sclerosis: An Integrated DNA Methylome and Transcriptome Analysis.

OBJECTIVE: Nongenetic factors influence systemic sclerosis (SSc) pathogenesis, underscoring epigenetics as a relevant contributor to the disease. We aimed to unravel DNA methylation abnormalities associated with SSc through an epigenome-wide association study. METHODS: We analyzed DNA methylation data from whole-blood samples in 179 patients with SSc and 241 unaffected individuals to identify differentially methylated positions (DMPs) with a false discovery rate (FDR) <0.05. These results were further integrated with RNA sequencing data from the same patients to assess their functional consequence. Additionally, we examined the impact of DNA methylation changes on transcription factors and analyzed the relationship between alterations of the methylation and gene expression profile and serum proteins levels. RESULTS: This analysis yielded 525 DMPs enriched in immune-related pathways, with leukocyte cell-cell adhesion being the most significant (FDR = 4.91 × 10-9), prioritizing integrins as they were exposed by integrating methylome and transcriptome data. Furthermore, through this integrative approach, we observed an enrichment of neutrophil-related pathways, highlighting this myeloid cell type as a relevant contributor in SSc pathogenesis. In addition, we uncovered novel profibrotic and proinflammatory mechanisms involved in the disease. Finally, the altered epigenetic and transcriptomic signature revealed an increased activity of CCAAT/enhancer-binding protein transcription factor family in SSc, which is crucial in the myeloid lineage development. CONCLUSION: Our findings uncover the impaired epigenetic regulation of the disease and its impact on gene expression, identifying new molecules for potential clinical applications and improving our understanding of SSc pathogenesis.

Humans↗

PubMed2024

Epigenome-wide Association Study Shows Differential DNA Methylation of MDC1, KLF9, and CUTA in Autoimmune Thyroid Disease.

CONTEXT: Autoimmune thyroid disease (AITD) includes Graves disease (GD) and Hashimoto disease (HD), which often run in the same family. AITD etiology is incompletely understood: Genetic factors may account for up to 75% of phenotypic variance, whereas epigenetic effects (including DNA methylation [DNAm]) may contribute to the remaining variance (eg, why some individuals develop GD and others HD). OBJECTIVE: This work aimed to identify differentially methylated positions (DMPs) and differentially methylated regions (DMRs) comparing GD to HD. METHODS: Whole-blood DNAm was measured across the genome using the Infinium MethylationEPIC array in 32 Australian patients with GD and 30 with HD (discovery cohort) and 32 Danish patients with GD and 32 with HD (replication cohort). Linear mixed models were used to test for differences in quantile-normalized β values of DNAm between GD and HD and data were later meta-analyzed. Comb-p software was used to identify DMRs. RESULTS: We identified epigenome-wide significant differences (P < 9E-8) and replicated (P < .05) 2 DMPs between GD and HD (cg06315208 within MDC1 and cg00049440 within KLF9). We identified and replicated a DMR within CUTA (5 CpGs at 6p21.32). We also identified 64 DMPs and 137 DMRs in the meta-analysis. CONCLUSION: Our study reveals differences in DNAm between GD and HD, which may help explain why some people develop GD and others HD and provide a link to environmental risk factors. Additional research is needed to advance understanding of the role of DNAm in AITD and investigate its prognostic and therapeutic potential.

Humans↗

PubMed2026

Novel epigenetic loci identified from an epigenome-wide association study underlying brain structural changes in bipolar disorder.

BACKGROUND: DNA methylation influences gene-environment interactions and brain development in bipolar disorder (BD). We aimed to identify BD-associated epigenetic loci and examine their associations with brain structural variation. METHODS: We conducted an epigenome-wide association study (BD group, n = 90; healthy controls group, n = 161) to identify BD-associated DNA methylation loci, and we additionally performed copy number alteration and functional enrichment analyses. The correlations between epigenetic loci and cortical thickness (CT) were assessed using Pearson's partial correlation analysis, and the co-methylation effect of the epigenetic loci identified in the neuroimaging-epigenetic analysis was investigated. FINDINGS: A total of 156 differentially methylated positions (DMPs) and 7 differentially methylated regions were identified, and the genes associated with them were observed to be enriched in biological processes related to muscle hypertrophy and neuronal activity. Significant correlations between the methylation levels of 13 DMPs associated with three genes (miR886, PLEC1, and ICAM5) and the CT of the right postcentral gyrus and inferior frontal gyrus were identified. Specifically, 10 DMPs associated with the CpG island in the upstream region of the miR886 gene showed negative correlations with the right postcentral gyrus CT, implicating miR886-associated CpG-island methylation in regional cortical thinning. CONCLUSION: Epigenetic changes might play an important role in brain structural changes in BD. These multimodal findings nominate miR886-related methylation as a candidate molecular correlate of cortical thinning and warrant replication and mechanistic follow-up in larger, state-diverse cohorts.

Humans↗

PubMed2026

Genome-wide DNA methylation analysis revealed epigenetic mechanism underlying end-stage renal disease.

End-stage renal disease (ESRD) remains a major clinical challenge with high morbidity and mortality, and its molecular mechanisms, particularly those shared among diverse primary kidney diseases during progression to ESRD, have not been studied. Here we conduct a large-scale two-stage epigenome-wide association study of ESRD in two independent cohorts consisting of 704 controls and 1031 ESRD cases. We identify 52 ESRD-associated differentially methylated CpG positions (ESRD DMPs) showing consistent association between the two cohorts and across diverse kidney diseases, implicating 144 candidate genes enriched in inflammatory and immune pathways. Five of the 52 DMPs are associated with ESRD complications, and seven with renal function decline in early-stage chronic kidney disease, demonstrating their potential as prognostic biomarkers for ESRD and its complications. Our findings highlight inflammation, immune dysregulation, and renal fibrosis as shared epigenetic drivers of ESRD progression, and identify biomarkers with potential utility for risk stratification and therapeutic intervention.

Humans↗

PubMed2025

Immediate and durable effects of maternal tobacco consumption on placental DNA methylation: a replication and discovery study.

An increasing number of epigenome-wide association studies report tobacco smoking-associated DNA methylation levels. However, comprehensive replication studies remain scarce, particularly in placenta, despite their crucial interest in such a large-scale context. Using DNA methylation data from the EPIC array of 341 new placentas (85 smokers, 219 non-smokers, and 37 former smokers) from the EDEN cohort, we used a candidate approach to replicate maternal smoking-associated CpGs and regions previously identified using the 450K array, and an exploratory approach to discover new associations within EPIC-specific CpGs. Smoking-associated changes in DNA methylation in CpGs and regions were classified as either transient or persistent (indicating epigenetic memory), depending on the stability of their association with smoking status. Among candidate loci, 38% of probes and 9% of regions were replicated, providing robust evidence of effects of prenatal smoke exposure on methylation patterns of these loci. LEKR1 was the top hit in both the initial and replication studies. Most of the replicated loci were transient CpGs (i.e. current smokers), while persistent CpGs (i.e. former smokers) remained scarce and somewhat inconsistent with previous findings. The additional exploratory analysis identified 733 novel probes and 75 novel regions, including 18% and 30% of transient loci, respectively. Results suggested that most of the effects were related to in utero exposure only, supporting pregnant women's efforts to quit smoking. This replication study also evidences the importance of reproducible work in omic investigations to provide a more in-depth and robust understanding of the effects of environmental exposures on health biomarkers..

DNA methylation↗

PubMed2026

EWAS in a polyphenol dense, DNA methylation-targeted, controlled diet and lifestyle study.

BACKGROUND: Dietary and lifestyle factors can influence DNA methylation patterns. We previously reported epigenetic age attenuation following a controlled study using an 8-week polyphenol-dense, DNA methylation-targeted diet and lifestyle intervention in healthy males (Methylation Diet and Lifestyle Study), with phytonutrient/polyphenol-rich foods (green tea, oolong tea, curcumin, garlic, and berries) being most predictive of this effect. METHODS: Here we conducted an epigenome-wide association study (EWAS) in 38 participants from the Methylation Diet and Lifestyle Study. The intervention included a dietary pattern intentionally rich in substrate and cofactor nutrients for methylation pathways, and components known to alter DNA-methyltransferase (DNMT) enzyme activity. In line with prior EWAS studies with small sample sizes where FDR-significant findings are unlikely, we used pre-specified nominal P-value thresholds (0.001, 0.0001) for the exploratory analyses. RESULTS: At P < 0.001 (unadjusted), 676 differentially methylated loci (DML) were identified in the intervention group versus 286 in controls. At P < 0.0001 (unadjusted), 50 DML were identified in the intervention group compared to 13 in controls. Fifteen DML were in transcription start site-proximal regions of genes including those involved in zinc homeostasis and nutrient sensing, development and pluripotency, proteostasis and genome stability, tumor suppression, and synaptic function. A group-by-time interaction analysis identified 70 intervention-specific DML at P < 0.0001, with nominal enrichment including autophagy, mTOR signaling, and chromatin remodeling pathways. A regional DMR analysis identified 128 within-group and 129 interaction-specific DMRs. DMR functional enrichment analyses revealed convergent nominal associations with lipid metabolism (alpha-linolenic acid, lipoic acid, biosynthesis of unsaturated fatty acids, PPAR signaling, cholesterol homeostasis), central energy metabolism (TCA cycle, glycolysis/gluconeogenesis, pentose phosphate, pyruvate), and nutrient sensing (PI3K-Akt, mTOR, AMPK, autophagy as well as other pathways). As expected for the limited cohort size and short intervention duration, none of the single CpG findings or enrichment analyses survived multiple test correction and are therefore considered exploratory and hypothesis-generating only. CONCLUSION: This EWAS identified a larger number of nominally changing CpGs in the intervention group compared to controls as well as biologically coherent methylation changes. These findings provide mechanistic hypotheses for previously observed epigenetic age attenuation. Replication in larger cohorts, longer intervention durations, and functional validation remain essential.

DNA methylation↗

PubMed2026

Estimating population structure using epigenome-wide methylation data.

Population stratification is one of the source of inflation in epigenome-wide association studies (EWAS) when not properly accounted for. To address this, we developed methylation population scores (MPSs) to predict genetic principal components (GPCs) using a feature selection approach. We used multi-ethnic DNA methylation data from Illumina EPIC arrays across five cohorts, including MESA (n = 929), CARDIA (n = 1123), JHS (n = 1365), ARIC (n = 2338), and HCHS/SOL (n = 1475), randomly splitting participants into training (85%) and test (15%) sets. Within each cohort, associations between GPCs and CpG sites were estimated using linear regression adjusting for age, sex, smoking and alcohol use, race/ethnicity, body mass index, and cell type proportions, followed by meta-analysis and selection of CpGs with FDR <0.05. We then applied a two-stage weighted least squares Lasso regression to construct MPSs, adjusting for the aforementioned covariates. In the test dataset, MPSs showed strong correlation with GPCs, with R² ranging from 0.27 (MPS7 vs. GPC7) to 0.98 (MPS1 vs. GPC1). Visualization demonstrated that MPSs recapitulated the pattern shown by GPCs in differentiating self-reported White, Black, and Hispanic/Latino groups and outperformed methylation-based principal components constructed using alternative published methods. Additionally, MPSs showed comparable performance to GPCs in reducing inflation in EWAS. Overall, MPSs uses supervised learning with covariate adjustment to capture genetic structure across diverse populations, and provide a reliable estimate of population structure in the data and can complement GPCs when genetic data are absent.

Humans↗

PubMed2022

Temporal associations between leukocytes DNA methylation and blood lipids: a longitudinal study.

BACKGROUND: The associations between blood lipids and DNA methylation have been investigated in epigenome-wide association studies mainly among European ancestry populations. Several studies have explored the direction of the association using cross-sectional data, while evidence of longitudinal data is still lacking. RESULTS: We tested the associations between peripheral blood leukocytes DNA methylation and four lipid measures from Illumina 450 K or EPIC arrays in 1084 participants from the Chinese National Twin Registry and replicated the result in 988 participants from the China Kadoorie Biobank. A total of 23 associations of 19 CpG sites were identified, with 4 CpG sites located in or adjacent to 3 genes (TMEM49, SNX5/SNORD17 and CCDC7) being novel. Among the validated associations, we conducted a cross-lagged analysis to explore the temporal sequence and found temporal associations of methylation levels of 2 CpG sites with triglyceride and 2 CpG sites with high-density lipoprotein-cholesterol (HDL-C) in all twins. In addition, methylation levels of cg11024682 located in SREBF1 at baseline were temporally associated with triglyceride at follow-up in only monozygotic twins. We then performed a mediation analysis with the longitudinal data and the result showed that the association between body mass index and HDL-C was partially mediated by the methylation level of cg06500161 (ABCG1), with a mediation proportion of 10.1%. CONCLUSIONS: Our study indicated that the DNA methylation levels of ABCG1, AKAP1 and SREBF1 may be involved in lipid metabolism and provided evidence for elucidating the regulatory mechanism of lipid homeostasis.

Humans↗

PubMed2025

Detection of cell-type-specific differentially methylated regions in epigenome-wide association studies.

MOTIVATION: DNA methylation at cytosine-phosphate-guanine (CpG) sites is one of the most important epigenetic markers. Therefore, epidemiologists are interested in investigating DNA methylation in large cohorts through epigenome-wide association studies (EWAS). However, the observed EWAS data are bulk data with signals aggregated from distinct cell types. Deconvolution of cell-type-specific signals from EWAS data is challenging because phenotypes can affect both cell-type proportions and cell-type-specific methylation levels. Recently, there has been active research on detecting cell-type-specific risk CpG sites for EWAS data. However, existing methods all assume that the methylation levels of different CpG sites are independent and perform association detection for each CpG site separately. Although these methods significantly improve the detection at the aggregated-level-identifying a CpG site as a risk CpG site as long as it is associated with the phenotype in any cell type, they have low power in detecting cell-type-specific associations for EWAS with typical sample sizes. RESULTS: Here, we develop a new method, Fine-scale inference for Differentially Methylated Regions (FineDMR), to borrow strengths of nearby CpG sites to improve the cell-type-specific association detection. Via a Bayesian hierarchical model built upon Gaussian process functional regression, FineDMR takes advantage of the spatial dependencies between CpG sites. FineDMR can provide cell-type-specific association detection as well as output subject-specific and cell-type-specific methylation profiles for each subject. Simulation studies and real data analysis show that FineDMR substantially improves the power in detecting cell-type-specific associations for EWAS data. AVAILABILITY AND IMPLEMENTATION: FineDMR is freely available at https://github.com/JiaRuofan/Detection-of-Cell-type-specific-DMRs-in-EWAS.

DNA Methylation↗

PubMed2026

DNA methylation landscape of cerebrospinal fluid cells in multiple sclerosis: an epigenome-wide association study.

BACKGROUND: Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system in which DNA methylation may link genetic and environmental risk factors. METHODS: We profiled genome-wide DNA methylation in cerebrospinal fluid (CSF) cells from people with MS (pwMS) and matched controls. Differentially methylated positions (DMPs) and regions (DMRs) were integrated with transcriptomic data, T-cell chromatin annotations, and pathway analyses. Protocadherin gamma (PCDHγ) expression was assessed in primary CD4+ T-cell subsets and confirmed by flow cytometry. FINDINGS: We identified 2710 DMPs and 4330 DMRs associating with genes that were enriched in immune signalling, adhesion and migration processes, and were accompanied by corresponding RNA changes. MS-associated methylation changes enriched in the cohesin chromatin-regulation pathway localised to T-cell regulatory regions, and this pathway included multiple protocadherin (PCDH) genes, which displayed consistent methylation and expression changes in CSF cells of pwMS compared to controls. PCDHγ cluster gene expression was detected in CD4+ T-cell subsets, and flow cytometry confirmed PCDHγ protein expression in peripheral blood T cells. Moreover, co-expression analysis suggests a role of PCDH genes in aryl hydrocarbon receptor (AHR) signalling. Protein-level validation showed fewer PCDHγ-positive CD4+ T cells in pwMS and activation-induced PCDHγ upregulation after T-cell stimulation. INTERPRETATION: DNA methylation changes in CSF resident cells reflect dysregulated T cell activation and migration in pwMS and suggest involvement of protocadherin molecules in MS pathogenesis. FUNDING: European Research Council, Swedish Research Council, Swedish Brain Foundation, Swedish MS Foundation, Knut and Alice Wallenberg Foundation, European Union and others.

Humans↗