Genomic and phenotypic insights from an atlas of genetic effects on DNA methylation

DNA methylation markers of insulin resistance surrogate measures in the Atherosclerosis Risk in Communities (ARIC) study

Insulin resistance (IR) is a risk factor for cardiovascular diseases and type 2 diabetes. Associations between DNA methylation (DNAm) and IR have been less studied in African ancestry (AA) populations than those of European ancestry (EA). We aimed to identify associations between whole blood DNAm and IR in up to 1,811 AA and 964 EA participants from the Atherosclerosis Risk in Communities (ARIC) study. We quantified IR using three surrogate measures: the homeostasis model assessment of insulin resistance (HOMA-IR), the triglyceride-glucose index (TyG), and the triglyceride glucose-body mass index (TyG-BMI). We used ancestry-stratified linear regression models to conduct epigenome-wide association studies of IR, adjusting for batch effects and relevant covariates. Among 484,436 tested CpG sites, 39 were significantly associated with IR, of which 31% (10 in AA and two in EA) were associated with TyG-BMI and not previously reported for IR or related traits. These include a positive association at cg18335991-SEMA7A in AA. SEMA7A inhibits adipogenesis of preadipocytes and lipogenesis of mature adipocytes. DNAm levels at cg18335991 have been reported to be negatively associated with SEMA7A expression in blood. After additionally adjusting for smoking and drinking status, 15 of the 39 significant CpG sites remained significant or suggestive. Our study identified novel IR-associated CpG sites, contributing to a broader understanding of the epigenetic mechanisms underlying IR in diverse populations.

Adverse childhood experiences and cardiometabolic biomarkers: A causal analysis

BACKGROUND

The associations between adverse childhood experiences (ACEs) and cardiometabolic biomarkers need to be further studied. Our objective was to investigate whether ACEs are causally associated with cardiometabolic biomarkers using observational study and two-sample Mendelian randomization (MR) analysis.

METHODS

The China Health and Retirement Longitudinal Study (CHARLS) data from 2014 to 2015 was used in the observational study. ACEs were divided into 4 groups (0, 1, 2, and 3 or more) according to whether they had experienced 12 items of negative experiences in childhood. A multilevel model was used to estimate the association between ACEs and each cardiometabolic biomarker. Further, we used two-sample MR to identify their potential causality.

RESULTS

A total of 11,422 participants (age:45-96) were eligible for the analyses in the observational study. Participants who experienced more ACEs were significantly higher in high-sensitivity C-reactive protein (hs-CRP) and high-density lipoprotein cholesterol (HDL-C) (all P < 0.05). Compared with those without ACE exposure, participants who experienced 3 or more ACEs had significantly lower total cholesterol (P < 0.05). In addition, a stronger association between ACEs and hs-CRP in males, as well as a stronger association between ACEs and HDL-C (Pinteraction = 0.036) in participants with higher education levels were observed. Consistently, in two-sample MR, we observed causal associations between DNA methylation loci and those cardiometabolic biomarkers.

CONCLUSION

Our results indicate that ACEs were causally associated with several cardiometabolic biomarkers. Further, adversity-associated DNA methylation loci might reflect buffering mechanisms against childhood adversity, which provides novel insight to the cardiovascular risk interventions.

A multi-omics and mediation-based genetic screening approach identifies STX4 as a key link between epigenetic regulation, immune cells, and childhood asthma

BACKGROUND

Childhood asthma presents a multifaceted immune-driven pathology shaped by genetic, epigenetic, and immune regulatory interactions. Despite extensive genome-wide analyses pinpointing multiple susceptibility loci, the precise functional contributors to asthma pathogenesis remain elusive. This study employs a comprehensive multi-omics framework and Mendelian randomization (MR) analysis to systematically identify and validate key genetic determinants implicated in childhood asthma.

METHODS

A genome-wide screening of over 19,000 human genes was performed to identify cis-eQTL-regulated genes associated with childhood asthma. Two-sample MR was conducted to assess causality, followed by Summary-based Mendelian Randomization (SMR) to validate findings in independent datasets. Colocalization analysis determined whether gene expression and asthma GWAS signals share a common causal variant. Protein quantitative trait loci (pQTL) analysis further validated gene associations at the protein level. DNA methylation quantitative trait loci (mQTL) MR and mediation analysis explored epigenetic regulatory mechanisms, while linkage disequilibrium score regression (LDSC) quantified genome-wide genetic correlations. Immune cell mediation analysis examined potential immune-driven effects, and Phenome-Wide Association Study (PheWAS) evaluated pleiotropy and therapeutic safety.

RESULTS

Following systematic screening, STX4 emerged as a strong candidate gene for childhood asthma. MR and SMR analyses confirmed its causal role, while colocalization analysis provided robust genetic evidence supporting STX4's regulatory influence on childhood asthma susceptibility. pQTL validation confirmed that STX4's effects extend to the protein level, strengthening its biological relevance. DNA methylation analysis revealed key CpG (Cytosine-phosphate-Guanine) sites regulating STX4 expression, with higher methylation levels reducing childhood asthma risk. Immune cell mediation analysis demonstrated that STX4 influences childhood asthma risk via CD4+ and CD8+ T cell subsets. LDSC analysis reinforced a significant genetic correlation between STX4 and childhood asthma, while PheWAS detected no major pleiotropy, suggesting that STX4 is a specific and promising therapeutic target.

CONCLUSIONS

This study systematically identifies and validates STX4 as a key genetic regulator in childhood asthma by integrating large-scale genetic, epigenetic, and immune regulatory data. These findings provide strong evidence for STX4's role in childhood asthma pathogenesis, highlighting STX4 as a potential target for future precision therapies in childhood asthma.

Epigenetic Modulation of Vascular Smooth Muscle Cell Phenotype Switching in Early-Onset Acute Myocardial Infarction

BACKGROUND

The epigenetic mechanisms underlying early-onset acute myocardial infarction (AMI) remain insufficiently characterized. The present study aims to elucidate the pathophysiology of early-onset AMI by investigating its epigenetic features as molecular indicators.

METHODS

A comparative differential methylation analysis was performed on whole blood samples from 298 patients with early-onset AMI with clinical follow-up and 247 controls using targeted bisulfite sequencing. Clusters of differentially methylated sites (CDMSs) were defined to highlight regions of concentrated methylation changes in patients with early-onset AMI. Cox proportional hazards regression was conducted to evaluate the prognostic significance of the methylation biomarkers.

RESULTS

A total of 692 differentially methylated sites (DMSs) were identified as biomarkers associated with early-onset AMI. Among these, 396 DMSs were grouped into 147 CDMSs. Notably, the UHRF1 and STIMATE genes, which regulate synthetic and osteoblast-like vascular smooth muscle cell phenotypes, respectively, contained CDMSs with the highest number of significant DMSs. UHRF1 demonstrated a CDMS with 10 significant DMSs within a 117-bp region, while STIMATE included a 264-bp CDMS with 10 significant DMSs. Both regions also exhibited consistent methylation patterns in coronary tissues, comparing human coronary plaque to normal coronary artery samples. Additionally, the HIPK3 gene, which modulates STAT3 (signal transducer and activator of transcription 3) expression, thereby promoting osteoblast-like transformation in vascular smooth muscle cells, showed a CDMS with 5 significant DMSs within a 123-bp region, with further validation in the corresponding tissues. Furthermore, over 66% biomarkers demonstrated significant associations with mortality in patients with early-onset AMI, providing evidence of the impact of these biomarkers on the pathophysiology of the disease.

CONCLUSIONS

This innovative epigenomic study into early-onset AMI not only identifies biomarkers associated with the disease and its mortality but also highlights the critical role of vascular smooth muscle cell phenotype regulation in early-onset AMI pathogenesis. Our findings suggest that changes in vascular smooth muscle cell phenotypes toward synthetic and osteoblast-like states play a crucial role in early-onset AMI.

Epigenome-wide association study of pregnancy exposure to green space and placental DNA methylation

Green space exposure during pregnancy has been associated with lower risk of adverse birth outcomes, but the biological mechanisms remain unclear. Epigenetic changes, such as DNA methylation (DNAm), may contribute to this association. The placenta, crucial for foetal development, has been understudied in relation to prenatal green space exposure and DNAm on a genome-wide scale. Here, we aimed to investigate the association between green space exposure during pregnancy and epigenome-wide placental DNAm in 550 mother-child pairs from the Barcelona Life Study Cohort (BiSC) in Spain. Green space exposure was assessed as (i) residential surrounding greenness (satellite-based Normalized Difference Vegetation Index (NDVI) in buffers of 100 m, 300 m and 500 m), (ii) residential distance to the nearest major green space (meters), (iii) use of green space (hours/week), and (iv) visual access to greenery through the home window (≥half of the view). Placental DNAm was measured with the EPIC array. Differentially methylated positions (DMPs) were identified using robust linear regression models adjusted for covariates, while differentially methylated regions (DMRs) were identified using the dmrff method. After Bonferroni correction, cg14852540, annotated to SLC25A10 gene, showed an inverse association with residential greenness within 500 m buffer. Additionally, 101 DMPs were suggestively significant (p-values <1 × 10-5) and annotated to genes involved in glucocorticoid-related pathways, inflammatory response, oxidative stress response, and oocyte maturation. No DMRs were identified. Overall, we identified an association between residential greenness and DNAm levels at one CpG in the SLC25A10 gene. Larger studies are needed to validate these findings and understand the biological pathways.

Unified high-resolution immune cell fraction estimation in blood tissue from birth to old age

Variations in immune-cell fractions can confound or hamper interpretation of DNAm-based biomarkers in blood. Although cell-type deconvolution can address this challenge for cord and adult blood, currently there is no method applicable to blood from other age groups, including infants and children. Here we construct and extensively validate a DNAm reference panel, called UniLIFE, for 19 immune cell-types, applicable to blood tissue of any age. We use UniLIFE to delineate the dynamics of immune-cell fractions from birth to old age, and to infer disease associated immune cell fraction variations in newborns, infants, children and adults. In a prospective longitudinal study of type-1 diabetes in infants and children, UniLIFE identifies differentially methylated positions that precede type-1 diabetes diagnosis and that map to diabetes related signaling pathways. In summary, UniLIFE will improve the identification and interpretation of blood-based DNAm biomarkers for any age group, but specially for longitudinal studies that include infants and children. The UniLIFE panel and algorithms to estimate cell-type fractions are available from our EpiDISH Bioconductor R-package: https://bioconductor.org/packages/release/bioc/html/EpiDISH.html.

Father's adolescent body silhouette is associated with offspring asthma, lung function and BMI through DNA methylation

Boys' pubertal overweight associates with future offspring's asthma and low lung function. To identify how paternal overweight is associated with offspring's DNA methylation (DNAm), we conducted an epigenome-wide association study of father's body silhouette (FBS) at three timepoints (age 8, voice break and 30) and change in FBS between these times, with offspring DNAm, in the RHINESSA cohort (N = 339). We identified 2005 differentially methylated cytosine-phosphate-guanine (dmCpG) sites (FDR < 0.05), including dmCpGs associated with offspring asthma (119), lung function (178) and BMI (291). Voice break FBS associated with dmCpGs in loci including KCNJ10, FERMT1, NCK2 and WWP1. Change in FBS across sexual maturation associated with DNAm at loci including NOP10, TRRAP, EFHD1, MRPL17 and NORD59A;ATP5B and showed strong correlation in reduced gene expression in loci NAP1L5, ATP5B, ZNF695, ZNF600, VTRNA2-1, SOAT2 and AGPAT2. We identified 24 imprinted genes including: VTRNA2-1, BLCAP, WT1, NAP1L5 and PTPRN2. Identified pathways relate to lipid and glucose metabolism and adipogenesis. Father's overweight at puberty and during reproductive maturation was strongly associated with offspring DNA, suggesting a key role for epigenetic mechanisms in intergenerational transfer from father to offspring in humans. The results support an important vulnerability window in male puberty for future offspring health.

Twin pair analysis uncovers links between DNA methylation, mitochondrial DNA quantity and obesity

Alterations in mitochondrial metabolism in obesity may indicate disrupted communication between mitochondria and nucleus, and DNA methylation may influence this interplay. Here, we leverage data from the Finnish Twin Cohort study subcohort (n = 173; 86 full twin pairs, 1 singleton), including comprehensive measurements of obesity-related outcomes, mitochondrial DNA quantity and nuclear DNA methylation levels in adipose and muscle tissue, to identify one CpG at SH3BP4 significantly associated with mitochondrial DNA quantity in adipose tissue (FDR < 0.05). We also show that SH3BP4 methylation correlates with its gene expression. Additionally, we find that 14 out of the 35 obesity-related traits display significant associations with both SH3BP4 methylation and mitochondrial DNA quantity in adipose tissue. We use data from TwinsUK and the Scandinavian T2D-discordant monozygotic twin cohort, to validate the observed associations. Further analysis using ICE FALCON suggests that mitochondrial DNA quantity, insulin sensitivity and certain body fat measures are causal to SH3BP4 methylation. Examining mitochondrial DNA quantity and obesity-related traits suggests causation from mitochondrial DNA quantity to obesity, but unmeasured within-individual confounding cannot be ruled out. Our findings underscore the impact of mitochondrial DNA quantity on DNA methylation and expression of the SH3BP4 gene within adipose tissue, with potential implications for obesity.

Distinct methylomic signatures of high-altitude acclimatization and adaptation in the Tibetan Plateau

High altitude presents a challenging environment for human settlement. DNA methylation is an essential epigenetic mechanism that responds to environmental stimuli, but its roles in high-altitude short-term acclimatization (STA) and long-term adaptation (LTA) are poorly understood. Here, we conducted a methylome-wide association study involving 687 native highlanders and 299 acclimatized newcomers in the Tibetan Plateau and 462 native lowlanders to identify differentially methylated sites (DMSs) associated with STA or LTA. We identified 93 and 4070 DMSs for STA and LTA, respectively, which had no overlap, showed opposite asymmetric effect size patterns, and resided near genes enriched in distinct biological pathways/processes (e.g., cell cycle for STA and immune diseases and calcium signalling pathway for LTA). Epigenetic clock analysis revealed evidence of accelerated ageing in the acclimatized newcomers compared to the native lowlanders. Our research provides novel insights into epigenetic regulation in relation to high altitude and intervention strategies for altitude-related ageing or illnesses.

DNA methylome biomarkers of rheumatoid arthritis-associated interstitial lung disease reflecting lung fibrosis pathways, an exploratory case-control study

Rheumatoid Arthritis-associated Interstitial Lung Disease (RA-ILD) significantly reduces life quality and survival, necessitating improvements in its understanding and clinical management. We addressed these goals using DNA methylation analysis, which has not been done in RA-ILD samples, by comparing 32 RA patients with ILD diagnosed less than one year before (cases) and 32 matched RA patients without ILD (controls). This analysis identified 6679 differentially methylated positions (DMPs) with Δβ ≥ 2% and FDR < 0.05, and 576 differentially methylated regions in RA-ILD. Some DMPs were near mucin, collagen, and telomere maintenance genes. Also, the most notably enriched gene set (up to padj = 1.9 × 10-38) included genes overexpressed in fibrosis by monocytes and alveolar macrophages. Other significantly enriched gene sets, known to be dysregulated in fibrosis, included the mitotic spindle and the Rho GTPases. Additionally, analysis of transcription factor binding sites around DMPs showed unique enrichment near the liver X receptor element (LXRE), which is associated with fibrosis in multiple tissues. These results were consistent and unaffected by stricter significance thresholds. They indicated that differential DNA methylation may serve as blood biomarkers for RA-ILD including some related to lung fibrosis pathways.

Epigenetic associations with kidney disease in individuals of African ancestry with APOL1 high-risk genotypes and HIV

BACKGROUND

Apolipoprotein L1 (APOL1) high-risk variants are major determinants of chronic kidney disease (CKD) in people of African ancestry. Previous studies have identified epigenetic changes in relation to kidney function and CKD, but not in individuals with APOL1 high-risk genotypes. We conducted an epigenome-wide analysis of CKD and estimated glomerular filtration rate (eGFR) in in people of African ancestry and APOL1 high-risk genotypes with HIV.

METHODS

DNA methylation profiles from peripheral blood mononuclear cells of 119 individuals with APOL1 high-risk genotypes (mean age 48 years, 49% female, median CD4 count 515 cells/mm3, 90% HIV-1 RNA <200 copies/mL, 23% with CKD) were obtained by Illumina MethylationEPIC BeadChip. Differential methylation analysis of CKD considered technical and biological covariates. We also assessed associations with eGFR. Replication was pursued in three independent multi-ancestry cohorts with and without HIV.

RESULTS

DNA methylation levels at 14 regions were associated with CKD. The strongest signals were located in SCARB1, DNAJC5B and C4orf50. Seven of the 14 signals also associated with eGFR, and most showed evidence for a genetic basis. Four signals (in SCARB1, FRMD4A, CSRNP1 and RAB38) replicated in other cohorts, and 11 previously reported epigenetic signals for kidney function or CKD replicated in our cohort. We found no significant DNA methylation signals in, or near, the APOL1 promoter region.

CONCLUSIONS

We report several novel as well as previously reported epigenetic associations with CKD and eGFR in individuals with HIV having APOL1 high-risk genotypes. Further investigation of pathways linking DNA methylation to APOL1 nephropathies is warranted.

DNA methylation and 28 year incidence of two neuropathy phenotypes in type 1 diabetes: the Pittsburgh Epidemiology of Diabetes Complications cohort study

AIMS/HYPOTHESIS

Diabetic peripheral neuropathy (DPN) and neuropathic pain (NP) are common complications of type 1 diabetes that can greatly affect quality of life. Studying DNA methylation (DNAm) may help identify potential therapeutic targets; however, epigenome-wide association studies (EWAS) of DPN and NP are lacking. We thus performed prospective EWAS of 28 year DPN and NP incidence in the Pittsburgh Epidemiology of Diabetes Complications (EDC) study of childhood-onset (<17 years) type 1 diabetes.

METHODS

DPN was defined as two or more of the following criteria: symptoms consistent with DPN; decreased tendon reflexes; or abnormal sensory examination. NP was reported as burning, aching or stabbing pain in the feet during an EDC examination or on the Michigan Neuropathy Screening Instrument (MNSI). The time of the first available blood-derived DNA specimen collected between 1988-1998 was considered the analytic 'baseline' (mean age 27 years; diabetes duration 19 years). After quality control, DNAm (EPIC array) at 683,597 CpGs was analysed in Cox models for time-to-DPN in 282 individuals free of DPN at baseline and time to NP in 365 individuals free of NP at baseline. False discovery rate (FDR) <0.05 was considered statistically significant. We also identified differentially methylated regions (DMRs), functional interaction networks and genetic variants associated with DNAm (methylation quantitative trait loci [meQTLs]), and performed Mendelian randomisation (MR) to assess evidence of causality.

RESULTS

Over 28 years, 154 individuals (54.6%) developed DPN and 148 (40.5%) developed NP. Greater methylation at three CpGs was significantly associated (FDR≤0.05) with reduced hazard of DPN: cg06163904 (CHMP6); cg10835127 (CACNA1B); and cg18945945 (PKNOX1). CpG associations with DPN remained similar after adjustment for clinical risk factors. We identified 75 meQTLs for cg18945945 in the PKNOX1 region, 59 of which were validated in an external diabetes cohort. One-sample MR provided nominal evidence for a potentially causal association between cg18945945 and DPN (p=0.01). While no individual CpGs were significantly associated with NP, there were 49 NP-associated DMRs.

CONCLUSIONS/INTERPRETATION

Our study identified associations between DNAm and 28 year incidence of DPN and NP at several biologically plausible loci. Most notably, we identified a novel association between DNAm of PKNOX1 and future DPN, including evidence of a genetic influence on PKNOX1 methylation that was validated in an external diabetes cohort. PKNOX1 has previously been implicated in drug-induced neuropathy; our results provide strong evidence that epigenetic regulation of PKNOX1 may also play a functional role in the development of diabetic neuropathy. Our results suggest that epigenetic modification of the identified loci warrants further study to inform potential targets for prevention of DPN.

DNA methylation signature of a lifestyle-based resilience index for cognitive health

Cognitive resilience (CR) contributes to the variability in risk for developing and progressing in Alzheimer's disease (AD) among individuals. Beyond genetics, recent studies highlight the critical role of lifestyle factors in enhancing CR and delaying cognitive decline. DNA methylation (DNAm), an epigenetic mechanism influenced by both genetic and environmental factors, including CR-related lifestyle factors, offers a promising pathway for understanding the biology of CR. We studied DNAm changes associated with the Resilience Index (RI), a composite measure of lifestyle factors, using blood samples from the Healthy Brain Initiative (HBI) cohort. After corrections for multiple comparisons, our analysis identified 19 CpGs and 24 differentially methylated regions significantly associated with the RI, adjusting for covariates age, sex, APOE ε4, and immune cell composition. The RI-associated methylation changes are significantly enriched in pathways related to lipid metabolism, synaptic plasticity, and neuroinflammation, and highlight the connection between cardiovascular health and cognitive function. By identifying RI-associated DNAm, our study provided an alternative approach to discovering future targets and treatment strategies for AD, complementary to the traditional approach of identifying disease-associated variants directly. Furthermore, we developed a Methylation-based Resilience Score (MRS) that successfully predicted future cognitive decline in an external dataset from the Alzheimer's Disease Neuroimaging Initiative (ADNI), even after accounting for age, sex, APOE ε4, years of education, baseline diagnosis, and baseline MMSE score. Our findings are particularly relevant for a better understanding of epigenetic architecture underlying cognitive resilience. Importantly, the significant association between baseline MRS and future cognitive decline demonstrated that DNAm could be a predictive marker for AD, laying the foundation for future studies on personalized AD prevention.

Strengthening Rigor and Reproducibility in Epigenome-Wide Association Studies of Social Exposures and Brain-Based Health Outcomes

PURPOSE OF REVIEW

Studies examining the effects of social factors on the epigenome have proliferated over the last two decades. Social epigenetics research to date has broadly demonstrated that social factors spanning childhood adversity, to neighborhood disadvantage, educational attainment, and economic instability are associated with alterations to DNA methylation that may have a functional impact on health. These relationships are particularly relevant to brain-based health outcomes such as psychiatric disorders, which are strongly influenced by social exposures and are also the leading cause of disability worldwide. However, social epigenetics studies are limited by the many challenges faced by both epigenome-wide association studies (EWAS) and the study of social factors.

FINDINGS

In this manuscript, we provide a framework to achieve greater rigor and reproducibility in social epigenetics research. We discuss current limitations of the social epigenetics field, as well as existing and new solutions to improve rigor and reproducibility. Readers will gain a better understanding of the current considerations and processes that could maximize rigor when conducting social epigenetics research, as well as the technologies and approaches that merit attention and investment to propel continued discovery into the future.

Differential DNA methylation 7 months after SARS-CoV-2 infection

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19), and SARS-CoV-2 has been linked to changes in DNA methylation (DNAm) patterns. Studies focused on post-SARS-CoV-2 infection and DNAm have been mainly carried out among severe COVID-19 cases or without distinguishing the severity of cases. However, investigations into mild and asymptomatic cases after SARS-CoV-2 infection are limited. In this study, we analyzed DNAm patterns of mild and asymptomatic cases seven months after SARS-CoV-2 infection in a household setting by conducting epigenome-wide association studies (EWAS).

RESULTS

We identified DNAm changes at 42 CpG sites associated with anti-SARS-CoV-2 antibody levels. We additionally report EWAS between COVID-19 cases and controls, with the case status being confirmed by either an antibody test or a PCR test. The EWAS with an antibody test case definition identified 172 CpG sites to be differentially methylated, while the EWAS with a PCR test case definition identified 502 CpG sites. Two common sites, namely cg17126990 (annotated to AFAP1L2) and cg25483596 (annotated to PC), were identified to be hypermethylated across the three EWAS. Both CpG sites have been reported to be involved in molecular pathways after SARS-CoV-2 infection. While AFAP1L2 has been found to be upregulated after SARS-CoV-2 infection, the pyruvate carboxylase (PC) activity seems to be affected by SARS-CoV-2 infection resulting in changes to the host cell metabolism. Additionally, an EWAS to assess persistent health restrictions among PCR-confirmed cases showed 40 CpG sites to be differentially methylated.

CONCLUSIONS

We detected associations between DNAm in individuals who had asymptomatic and mild SARS-CoV-2 infections as compared to their household controls. These findings contribute to our understanding of the molecular consequences of SARS-CoV-2 infection observed months after infection.

Molecular Effects of Physical Activity and Body Composition: A Systematic Review and Meta-Analysis

Physical activity (PA) and body composition are important lifestyle factors that influence public health. Research suggests that DNA regions (CpG site locations) are differentially methylated in a physically active population. This meta-analysis aimed to identify CpG sites associated with various levels of PA and associated metabolic pathways. The meta-analysis followed PRISMA guidelines using PubMed, SportDISCUS, Embase, Scopus, Cochrane and Web of Science. Epigenomic analyses performed on DNA of participants with no underlying health conditions were included. Articles were screened using Rayyan AI and extracted CpG sites, and their location were confirmed using the EWAS catalogue. Six studies comprising 770 subjects were included in this meta-analysis. The meta-analysis was performed on clinical metrics extracted from the six studies and showed that BMI, blood pressure, insulin and glucose testing are significantly improved upon PA intervention. Amongst the included studies, a total of 257 CpG sites were differentially methylated in physically active participants, with 134 CpGs located in 92 genes associated with obesity-related pathways. The identified differentially methylated genes either belonged to the lipid metabolism or insulin signalling pathway. The genes which were differentially regulated in multiple tissue types and studies are JAZF1 (insulin signalling, and lipid and carbohydrate metabolism pathways) and NAV1 (mTOR signalling pathway). In conclusion, the current epigenomic meta-analysis showed that PA levels induce differential DNA methylation signatures on genes that affect metabolism. To understand the positive molecular effects of PA, further research on the above candidate genes needs to be conducted amongst various levels of a physically active population.

Epigenetic timing effects on child developmental outcomes: a longitudinal meta-regression of findings from the Pregnancy And Childhood Epigenetics Consortium

BACKGROUND

DNA methylation (DNAm) is a developmentally dynamic epigenetic process; yet, most epigenome-wide association studies (EWAS) have examined DNAm at only one timepoint or without systematic comparisons between timepoints. Thus, it is unclear whether DNAm alterations during certain developmental periods are more informative than others for health outcomes, how persistent epigenetic signals are across time, and whether epigenetic timing effects differ by outcome.

METHODS

We applied longitudinal meta-regression models to published meta-analyses from the PACE consortium that examined DNAm at two timepoints-prospectively at birth and cross-sectionally in childhood-in relation to the same child outcome (ADHD symptoms, general psychopathology, sleep duration, BMI, asthma). These models allowed systematic comparisons of effect sizes and statistical significance between timepoints. Furthermore, we tested correlations between DNAm regression coefficients to assess the consistency of epigenetic signals across time and outcomes. Finally, we performed robustness checks, estimated between-study heterogeneity, and tested pathway enrichment.

RESULTS

Our findings reveal three new insights: (i) across outcomes, DNAm effect sizes are consistently larger in childhood cross-sectional analyses compared to prospective analyses at birth; (ii) higher effect sizes do not necessarily translate into more significant findings, as associations also become noisier in childhood for most outcomes (showing larger standard errors in cross-sectional vs prospective analyses); and (iii) DNAm signals are highly time-specific, while also showing evidence of shared associations across health outcomes (ADHD symptoms, general psychopathology, and asthma). Notably, these observations could not be explained by sample size differences and only partly to differential study-heterogeneity. DNAm sites changing associations were enriched for neural pathways.

CONCLUSIONS

Our results highlight developmentally-specific associations between DNAm and child health outcomes, when assessing DNAm at birth vs childhood. This implies that EWAS results from one timepoint are unlikely to generalize to another. Longitudinal studies with repeated epigenetic assessments are direly needed to shed light on the dynamic relationship between DNAm, development and health, as well as to enable the creation of more reliable and generalizable epigenetic biomarkers. More broadly, this study underscores the importance of considering the time-varying nature of DNAm in epigenetic research and supports the potential existence of epigenetic "timing effects" on child health.

Evolution of genome-wide methylation profiling technologies

In this mini-review, we explore the advancements in genome-wide DNA methylation profiling, tracing the evolution from traditional methods such as methylation arrays and whole-genome bisulfite sequencing to the cutting-edge single-molecule profiling enabled by long-read sequencing (LRS) technologies. We highlight how LRS is transforming clinical and translational research, particularly by its ability to simultaneously measure genetic and epigenetic information, providing a more comprehensive understanding of complex disease mechanisms. We discuss current challenges and future directions in the field, emphasizing the need for innovative computational tools and robust, reproducible approaches to fully harness the capabilities of LRS in molecular diagnostics.

A blood- and brain-based EWAS of smoking

DNA methylation offers an objective method to assess the impact of smoking. In this work, we conduct a Bayesian EWAS of smoking pack years (n = 17,865, ~850k sites, Illumina EPIC array) and extend it by analysing whole genome data of smokers and non-smokers from Generation Scotland (n = 46, ~4-21 million sites via TWIST and Oxford Nanopore sequencing). We develop mCigarette, an epigenetic biomarker of smoking, and test it in two British cohorts. Results of brain- and blood-based EWAS (nbrain=14, nblood = 882, >450k sites, Illumina arrays) reveal several loci with near-perfect discrimination of smoking status, but which do not overlap across tissues. Furthermore, we perform a GWAS of epigenetic smoking, identifying several smoking-related loci. Overall, we improve smoking-related biomarker accuracy and enhance the understanding of the effects of smoking by integrating DNA methylation data from multiple tissues and cohorts.

Intergenerational transmission of complex traits and the offspring methylome

The genetic makeup of parents can directly or indirectly affect their offspring phenome through genetic transmission or via the environment that is influenced by parental heritable traits. Our understanding of the mechanisms by which indirect genetic effects operate is limited. Here, we hypothesize that one mechanism is via the offspring methylome. To test this hypothesis, polygenic scores (PGSs) for schizophrenia, smoking initiation, educational attainment (EA), social deprivation, body mass index (BMI), and height were analyzed in a cohort of 1528 offspring and their parents (51.5% boys, mean [SD] age = 10 [2.8] years). We modelled parent and offspring PGSs on offspring buccal-DNA methylation, accounting for the own PGS of offspring, and found significant associations between parental PGSs for schizophrenia, EA, BMI, and height, and offspring buccal methylation sites, comprising 16, 2, 1, and 6 sites, respectively (alpha = 2.7 × 10-5). More DNA methylation sites were associated with maternal than paternal PGSs, possibly reflecting the maternal pre- and periconceptional environment or stronger maternal involvement in shaping the offspring's environment during early childhood.

Sex-specific DNA methylation marks associated with sex-biased risk of recurrence in unprovoked venous thromboembolism

BACKGROUND

Whether to stop oral anticoagulants after a first unprovoked venous thromboembolism (VTE) is challenging, partially due to an intriguingly higher risk of VTE recurrence (rVTE) in men after therapy discontinuation. DNA methylation (DNAm) differences between men and women might underlie this sex-biased rVTE risk difference.

OBJECTIVES

To investigate sex-specific associations between DNAm at cytosine-phosphate-guanine (CpG) sites and rVTE.

METHODS

In 417 unprovoked VTE patients, including 101 experiencing recurrences over a 5-year follow-up (REcurrent VEnous thromboembolism Risk Stratification Evaluation [REVERSE] I), we analyzed blood DNAm using the Illumina EPIC array and performed a sex-stratified epigenome-wide association study. We further examined 181 major provoked VTE patients, including 36 recurrences over a 14-year follow-up (the MARseille THrombosis Association [MARTHA]), to investigate whether DNAm is a risk factor for rVTE after anticoagulation therapy.

RESULTS

Hypomethylated CpGs at genes TBC1D22B-cg01060850 and ZHX2-cg07808424 in men and DIP2B-ch.12.1038646R and DENND3-cg03401656 in women were associated with rVTE at genome-wide level (P < 7x10-8). Though not statistically significant, DENND3-cg03401656 had the same direction of effect in MARTHA women. Sensitivity analysis confirmed the robustness of the estimates, including potential confounders, adaptations of the Cox model, non-Europeans, and proximal methylation quantitative trait loci in the association. The associated CpGs were situated at genes for membrane trafficking, corroborating the participation of Rab regulatory proteins in rVTE and transcription factors.

CONCLUSION

We identified DNAm marks as potential risk factors for sex-biased recurrence in unprovoked VTE. Further replication and experimental validation could refine our understanding of the regulation of the identified DNAm sites and help optimize personalized decision-making for long-term anticoagulation after a first VTE.

Multi-Omics Analysis Links Mitochondrial-Related Genes to Idiopathic Pulmonary Fibrosis and In Vivo Transcriptome Validation

Mitochondrial dysfunction is closely associated with idiopathic pulmonary fibrosis (IPF). However, the causal association between mitochondria-related genes and IPF remains to be determined. We obtained gene expression, protein abundance, and methylation quantitative trait locus data for mitochondria-related genes from previous studies. Genome-wide association study data for patients with IPF were obtained from the FinnGen study. A two-sample Mendelian randomisation analysis was conducted to assess the association between mitochondria-related genes and IPF. Furthermore, we conducted validation of expression differences utilizing transcriptome data derived from the BLM-induced pulmonary fibrosis mouse model (n=15). Concurrently, multiphoton imaging was utilized to quantify collagen contents and structural assessment. The direction of causality was verified using the Steiger test, and colocalisation analysis was used to better validate causality. Single-cell data were used to explore the localisation and expression of positive genes across different cell types. The study identified significant associations between mitochondria-related genes and IPF, with POLG and NDUFB10 classified as Grade 1; LYRM4, NBR1, and ACSF3 as Grade 2; MCL1, GFER, MFN2, IVD, and SLC25A35 as Grade 3; and METAP1D and MTX1 as Grade 4. Single-cell analysis showed elevated expression of NBR1, MCL1, and MTX1 in pulmonary myofibroblasts of IPF. This study elucidated the causal effects of mitochondria-related genes on IPF, underscoring their significance in pathogenesis. These findings contribute to an improved understanding of the mechanisms underlying IPF, offering new potential therapeutic targets for interventions.

Epigenetic biomarkers of socioeconomic status are associated with age-related chronic diseases and mortality in older adults

Later-life health is patterned by socioeconomic influences across the lifecourse. However, the pathways underlying the biological embedding of socioeconomic status (SES) and its consequences on downstream morbidity and mortality are not fully understood. Epigenetic markers like DNA methylation (DNAm) may be promising surrogates of underlying biological processes that can enhance our understanding of how SES shapes population health. Studies have shown that SES is associated with epigenetic aging measures, but few have examined relationships between early and later-life SES and DNAm sites across the epigenome. In this study, we trained and tested DNAm-based surrogates, or "biomarkers," of childhood and adult SES in two large, multiracial/ethnic samples of older adults-the Health and Retirement Study (n = 3,527) and the Multi-Ethnic Study of Atherosclerosis (n = 1,182). Both biomarkers were associated with downstream morbidity and mortality, and these associations persisted after controlling for measured SES, and in some cases, epigenetic aging clocks. Both childhood and adult SES biomarker CpG sites were enriched for genomic features that regulate gene expression (e.g. DNAse hypersensitivity sites and enhancers) and were implicated in prior epigenome-wide studies of inflammation, aging, and chronic disease. Distinct patterns also emerged between childhood CpGs and immune system dysregulation and adult CpGs and metabolic functioning, health behaviors, and cancer. Results suggest DNAm-based surrogate biomarkers of SES may be useful proxies for unmeasured social exposures that can augment our understanding of the biological mechanisms between social disadvantage and downstream health.

Mendelian Randomization Reveals Causalities Between DNA Methylation and Schizophrenia

BACKGROUND

Epigenetic factors (such as DNA methylation) have been widely reported to be associated with schizophrenia (SCZ). However, the causal relationships between epigenetic factors and SCZ remain largely unknown.

METHODS

Here, we conducted a Mendelian randomization (MR) study to investigate the causal relationships between DNA methylation and SCZ. Brain methylation quantitative trait loci (mQTL) (N = 1160) and blood mQTL (N = 27,750) data were used as exposures, and genome-wide association data of SCZ (53,386 cases and 77,258 controls) were used as the outcome.

RESULTS

We identified 172 (mapped to 160 genes) and 157 (mapped to 155 genes) methylation sites whose methylation levels in brain and blood are causally associated with SCZ, respectively. Among the mapped genes, 36 overlapping genes were identified. Interestingly, 3 methylation sites (near BRD2, CNNM2, and RERE) showed significant associations in both brain and blood, with the same direction of effect. We also performed MR analysis using brain expression quantitative trait loci (eQTLs) as exposures and identified 123 genes whose expression levels were causally associated with SCZ. Comparing the significant genes from eQTLs and brain mQTLs prioritized 15 overlapping genes, suggesting that both epigenetic modification and expression of these genes confer risk of SCZ. Finally, we validated our findings with genome editing and animal model experiments.

CONCLUSIONS

Our study identified methylation sites whose methylation levels are causally associated with SCZ and demonstrated the important roles of epigenetic factors in SCZ. Our findings also reveal pivotal risk genes whose expression and epigenetic regulation are causally associated with SCZ.

Potentially causal associations between placental DNA methylation and schizophrenia and other neuropsychiatric disorders

Increasing evidence supports the role of the placenta in neurodevelopment and in the onset of neuropsychiatric disorders. Recently, mQTL and iQTL maps have proven useful in understanding relationships between SNPs and GWAS that are not captured by eQTL. In this context, we propose that part of the genetic predisposition to complex neuropsychiatric disorders acts through placental DNA methylation. We construct a public placental cis-mQTL database including 214,830 CpG sites calculated in 368 fetal placenta DNA samples from the INMA project, and run cell type-, gestational age- and sex-imQTL models. We combine these data with summary statistics of GWAS on ten neuropsychiatric disorders using summary-based Mendelian randomization and colocalization. We also evaluate the influence of identified DNA methylation sites on placental gene expression in the RICHS cohort. We find that placental cis-mQTLs are enriched in placenta-specific active chromatin regions, and establish that part of the genetic burden for schizophrenia, bipolar disorder, and major depressive disorder confers risk through placental DNA methylation. The potential causality of several of the observed associations is reinforced by secondary association signals identified in conditional analyses, the involvement of cell type-imQTLs, and the correlation of identified DNA methylation sites with the expression levels of relevant genes in the placenta.

Developmental air pollution exposure augments airway hyperreactivity, alters transcriptome, and DNA methylation in female adult progeny

Maternal exposure to particulate air pollution increases the incidence and severity of asthma in offspring, yet the mechanisms for this are unclear. Known susceptibility loci are a minor component of this effect. We interrogate a mouse allergic airway disease model to assess epigenetic associations between maternal air pollution exposure and asthma responses in offspring. Maternal air pollution exposure increased allergic airway disease severity in adult offspring associated with a suppressed transcriptomic response. Control progeny showed differential expression of 2842 genes across several important pathways, whilst air pollutant progeny showed an 80% reduction in differentially expressed genes and abrogation of many pathway associations. Whole genome CpG methylome analysis following allergen challenge detected differential methylation regions across the genome. Differentially methylated regions were markedly reduced in air pollutant offspring, and this was most evident in intronic regions and some transposable element classes. This study shows that asthma in adult offspring of PM2.5 exposed mothers had a markedly repressed transcriptomic response, a proportion of which was associated with identifiable changes in the lung's methylome. The results point to an epigenetic contribution to the severity of asthma in offspring of mothers exposed to particulate air pollution.

Dissecting the causal effects of smoking, alcohol consumption, and related DNA methylation markers on electrocardiographic indices

BACKGROUND

Tobacco and alcohol are recognized risk factors for heart disease, yet their causal effects on electrocardiogram (ECG) signaling and mechanisms remain unclear. Previous studies may be susceptible to confounding or bias, and this study dissected the genetic architecture linking tobacco and alcohol consumption with P-wave duration, PR interval, and QT interval.

METHODS

Utilizing genetic instruments for tobacco and alcohol consumption, associated methylation quantitative trait locus (mQTL), and summary-level GWAS data for ECG indices, we assessed heritability and genetic causal associations using linkage disequilibrium score regression and Mendelian randomization (MR) analysis. Fine mapping was performed via colocalization analysis and summary-data-based MR (SMR) to identify potential shared genetic variants.

RESULTS

A positive causal relationship was found between drinks per week (DrnkWk) and QT interval [β (95%CI): 1.06 (0.91, 5.05), P = 0.005], with causality substantiated through multiple robust MR models. Multivariable MR confirmed independence from smoking phenotypes. In epigenetic MR analyses, two alcohol-related CpG loci (cg03345232 and cg04605617) were causally associated with QT interval changes, with cg04605617 mapping to PLA2G2C gene significantly prolonging QT. The mQTL rs10916683 at cg04605617 is a strong eQTL for PLA2G2C. Additionally, cg03345232 shared a causal variant (rs12881206) with QT interval predisposition through colocalization analysis. SMR analysis did not identify shared putative functional genes passing the HEIDI test between DrnkWk and the QT interval.

CONCLUSIONS

There is a causal relationship between DrnkWk and QT interval prolongation, and targeting specific DNA methylation sites like cg04605617 mapped to PLA2G2C may provide novel targets for preventing QT interval prolongation.

Blood DNA methylation signature for incident dementia: Evidence from longitudinal cohorts

INTRODUCTION

Distinguishing between molecular changes that precede dementia onset and those resulting from the disease is challenging with cross-sectional studies.

METHODS

We studied blood DNA methylation (DNAm) differences and incident dementia in two large longitudinal cohorts: the Offspring cohort of the Framingham Heart Study (FHS) and the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. We analyzed blood DNAm samples from > 1000 cognitively unimpaired subjects.

RESULTS

Meta-analysis identified 44 CpGs and 44 differentially methylated regions consistently associated with time to dementia in both cohorts. Our integrative analysis identified early processes in dementia, such as immune responses and metabolic dysfunction. Furthermore, we developed a methylation-based risk score, which successfully predicted future cognitive decline in an independent validation set, even after accounting for age, sex, apolipoprotein E ε4, years of education, baseline diagnosis, and baseline Mini-Mental State Examination score.

DISCUSSION

DNAm offers a promising source as a biomarker for dementia risk assessment.

HIGHLIGHTS

Blood DNA methylation (DNAm) differences at individual CpGs and differentially methylated regions are significantly associated with incident dementia. Pathway analysis revealed DNAm differences associated with incident dementia are significantly enriched in biological pathways involved in immune responses and metabolic processes. Out-of-sample validation analysis demonstrated that a methylation-based risk score successfully predicted future cognitive decline in an independent dataset, even after accounting for age, sex, apolipoprotein E ε4, years of education, baseline diagnosis, and baseline Mini-Mental State Examination score.

Identification of Potential Drug Targets for Immunoglobulin A Nephropathy: A Mendelian Randomization Study

Background: The current pharmacological treatments for Immunoglobulin A nephropathy (IgAN) demonstrate limited effectiveness and may cause serious side effects. This study aimed to explore novel potential drug targets for IgAN. Methods: We utilized summarized data from a recent genome-wide association study on IgAN, cis-expression quantitative trait loci data for druggable genes obtained from the eQTLGen Consortium, and DNA methylation quantitative trait loci data derived from the GoDMC database. Two-sample Mendelian randomization (MR) analysis, Bayesian colocalization, and mediation analysis through a two-step MR approach were performed to investigate their causal relationships. Results: Two-sample MR and colocalization analyses demonstrated that the expression of HLA-DPA1 and C4A was associated with an increased risk of IgAN. In contrast, TUBB, CYP21A2, and C4B were associated with a decreased risk of IgAN. Mediation analysis revealed that the expression of HLA-DPA1 acted as a mediator in the potential causal relationship between three DNA methylation sites (cg01140143, cg08898074, and cg12168509) and IgAN, with mediated proportions of 33.74% (95% CI 1.64-73.27), 41.67% (95% CI 20.78-66.97), and 50.34% (95% CI 27.89-74.76), respectively. Conclusions: Several druggable genes and DNA methylation sites were identified to show potential causal associations with IgAN risk and may be targeted for drug development. Nevertheless, additional experimental validation is warranted to clarify the specific roles of DNA methylation and the identified druggable genes in the pathogenesis of IgAN.

Genetic-epigenetic interactions (meQTLs) in orofacial clefts etiology

Objectives

Nonsyndromic orofacial clefts (OFCs) etiology involves multiple genetic and environmental factors with over 60 identified risk loci; however, they account for only a minority of the estimated risk. Epigenetic factors such as differential DNA methylation (DNAm) are also associated with OFCs risk and can alter risk for different cleft types and modify OFCs penetrance. DNAm is a covalent addition of a methyl (CH3) group to the nucleotide cytosine that can lead to changes in expression of the targeted gene. DNAm can be affected by environmental influences and genetic variation via methylation quantitative loci (meQTLs). We hypothesize that aberrant DNAm and the resulting alterations in gene expression play a key role in the etiology of OFCs, and that certain common genetic variants that affect OFCs risk do so by influencing DNAm.

Methods

We used genotype from 10 cleft-associated SNPs and genome-wide DNA methylation data (Illumina 450K array) for 409 cases with OFCs and 456 controls and identified 23 cleft-associated meQTLs. We then used an independent cohort of 362 cleft-discordant sib pairs for replication. We used methylation-specific qPCR to measure methylation levels of each CpG site and combined genotypic and methylation data for an interaction analysis of each SNP-CpG pair using the R package MatrixeQTL in a linear model. We also performed a Paired T-test to analyze differences in DNA methylation between each member of the sibling pairs.

Results

We replicated 9 meQTLs, showing interactions between rs13041247 (MAFB) - cg18347630 (PLCG1) (P=0.04); rs227731 (NOG) - cg08592707 (PPM1E) (P=0.01); rs227731 (NOG) - cg10303698 (CUEDC1) (P=0.001); rs3758249 (FOXE1) - cg20308679 (FRZB) (P=0.04); rs8001641 (SPRY2) - cg19191560 (LGR4) (P=0.04); rs987525(8q24) - cg16561172(MYC) (P=0.00000963); rs7590268(THADA) - cg06873343 (TTYH3) (P=0.04); rs7078160 (VAX1) - cg09487139 (P=0.05); rs560426 (ABCA4/ARHGAP29) - cg25196715 (ABCA4/ARHGAP29) (P=0,03). Paired T-test showed significant differences for cg06873343 (TTYH3) (P=0.04); cg17103269 (LPIN3) (P=0.002), and cg19191560 (LGR4) (P=0.05).

Conclusions

Our results confirm previous evidence that some of the common non-coding variants detected through GWAS studies can influence the risk of OFCs via epigenetic mechanisms, such as DNAm, which can ultimately affect and regulate gene expression. Given the large prevalence of non-coding SNPs in most OFCs genome wide association studies, our findings can potentially address major knowledge gaps, like missing heritability, reduced penetrance, and variable expressivity associated with OFCs phenotypes.

Scalable Screening of Ternary-Code DNA Methylation Dynamics Associated with Human Traits

Epigenome-wide association studies (EWAS) are transforming our understanding of the interplay between epigenetics and complex human traits and phenotypes. We introduce the Methylation Screening Array (MSA), a new iteration of the Infinium technology for scalable and quantitative screening of trait associations of nuanced ternary-code cytosine modifications in larger, more inclusive, and stratified human populations. MSA integrates EWAS, single-cell, and cell-type-resolved methylome profiles, covering diverse human traits and diseases. Our first MSA applications yield multiple biological insights: we revealed a previously unappreciated role of 5-hydroxymethylcytosine (5hmC) in trait associations and epigenetic clocks. We demonstrated that 5hmCs complement 5-methylcytosines (5mCs) in defining tissues and cells' epigenetic identities. In-depth analyses highlighted the cell type context of EWAS and GWAS hits. Using this platform, we conducted a comprehensive human 5hmC aging EWAS, discovering tissue-invariant and tissue-specific aging dynamics, including distinct tissue-specific rates of mitotic hyper- and hypomethylation rates. These findings chart a landscape of the complex interplay of the two forms of cytosine modifications in diverse human tissues and their roles in health and disease.

Effect of smoking behaviour and related blood DNA methylation on visceral adipose tissues

BACKGROUND

Recent studies have found that tobacco smoking is associated with fat distribution, yet limited research has focused on its relationship with visceral adipose tissues (VATs). Furthermore, the cellular and molecular mechanisms underlying the interactions among smoking, epigenetic modifications, and VATs remain unknown.

METHOD

We performed univariable Mendelian randomization (MR) analysis to elucidate the causal relationship between smoking behaviours and VATs, including epicardial and pericardial adipose tissue (EPAT), liver fat (LF), and pancreas fat (PF). This approach could minimize the impact of confounders and reverse causality through utilizing genetic variants to proxy the smoking behaviours. Mediation MR analysis were conducted to detect potential mediators. Additionally, summary-data-based MR (SMR) and colocalization analysis were performed to explore the association between smoking-related DNA methylation and VATs.

RESULTS

We identified a convincing association between smoking initiation and increased EPAT (beta: 0.15, 95% CI: 0.06, 0.23, p = 7.01 × 10-4) and LF area (beta: 0.15, 95% CI = 0.05, 0.24, p = 2.85 × 10-3), respectively. Further mediation analysis suggested type 2 diabetes mellitus (T2DM) as a potential mediator within these co-relationships. When further exploring the associations between the smoking related DNA methylation and VATs, we identified that WT1 methylation at cg05222924 was significantly linked to a lower EPAT area (beta: -0.12, 95% CI: -0.16, -0.06, PFDR = 2.24 × 10-3), while GPX1 methylation at cg18642234 facilitated the deposition of EPAT (beta: 0.15, 95% CI: 0.10, 0.20, PFDR = 1.66 × 10-4).

CONCLUSION

Our study uncovered a significant causal effect between smoking and VATs, with T2DM identified as a potential mediator. Further investigation into DNA methylation yielded novel insights into the pathogenic role of smoking on EPAT.

Genetic landscape for screening and early diagnosis of pancreatic ductal adenocarcinoma: is there a signature?

The last 15 years have seen unprecedent advancement in genomics techniques such as dense single nucleotide variants (SNVs) arrays or next generation Sequencing. In parallel, new analytical methodologies have been developed to streamline data understanding and integration. These advances have been instrumental in identifying common genetic variants associated with pancreatic ductal adenocarcinoma (PDAC) risk. The role of the individual variants is rather small, and they have no clinical utility for screening or early detection. However, their combined effect computed though polygenic risk scores (PGS) are showing promising potentiality in PDAC risk prediction. There still caveats, and limitations that need to be properly addressed however it is foreseeable that the genetic background will become a powerful tool in PDAC prediction, leveraging the advantage that it has compared to other biomarkers: germline genetics is invariable from birth to death.

Leveraging epigenetic alterations in pancreatic ductal adenocarcinoma for clinical applications

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy characterized by late detection and poor prognosis. Recent research highlights the pivotal role of epigenetic alterations in driving PDAC development and progression. These changes, in conjunction with genetic mutations, contribute to the intricate molecular landscape of the disease. Specific modifications in DNA methylation, histone marks, and non-coding RNAs are emerging as robust predictors of disease progression and patient survival, offering the potential for more precise prognostic tools compared to conventional clinical staging. Moreover, the detection of epigenetic alterations in blood and other non-invasive samples holds promise for earlier diagnosis and improved management of PDAC. This review comprehensively summarises current epigenetic research in PDAC and identifies persisting challenges. These include the complex nature of epigenetic profiles, tumour heterogeneity, limited access to early-stage samples, and the need for highly sensitive liquid biopsy technologies. Addressing these challenges requires the standardisation of methodologies, integration of multi-omics data, and leveraging advanced computational tools such as machine learning and artificial intelligence. While resource-intensive, these efforts are essential for unravelling the functional consequences of epigenetic changes and translating this knowledge into clinical applications. By overcoming these hurdles, epigenetic research has the potential to revolutionise the management of PDAC and improve patient outcomes.

Associations of maternal night shift work during pregnancy with DNA methylation in offspring: a meta-analysis in the PACE consortium

BACKGROUND

Night shift work during pregnancy has been associated with differential DNA methylation in placental tissue, but no studies have explored this association in cord blood. We aimed to examine associations of maternal night shift work with cord blood DNA methylation.

METHODS

A total of 4487 mother-newborn pairs from 7 studies were included. Maternal night shift work during pregnancy was ascertained via questionnaires and harmonized into "any" versus "no". DNA methylation was measured in cord blood using the Illumina Infinium Methylation arrays. Robust linear regression models adjusted for relevant confounders were run in the individual cohorts, and results were meta-analyzed.

RESULTS

Maternal night shift work during pregnancy ranged from 3.4% to 26.3%. Three CpGs were differentially methylated in relation to maternal night shift work during pregnancy at a false discovery rate adjusted P < 0.05: cg10945885 (estimate (β) 0.38%, standard error (SE) 0.07), cg00773359 (β 0.25%, SE 0.05), and cg21836426 (β - 0.29%, SE 0.05). Associations of the identified CpGs were found in previous literature for gestational age and childhood and adolescent BMI. In a mouse model of prenatal jet lag exposure, information on offspring DNA methylation of ten homologous genes annotated to the 16 CpGs with P < 1 × 10-5 in our analysis was available, of which eight were associated (enrichment P: 1.62 × 10-11).

CONCLUSION

Maternal night shift work during pregnancy was associated with newborn DNA methylation at 3 CpGs. Top findings overlapped with those in a mouse model of gestational jet lag. This work strengthens evidence that DNA methylation could be a marker or mediator of impacts of circadian rhythm disturbances.

DMRdb: a disease-centric Mendelian randomization database for systematically assessing causal relationships of diseases with genes, proteins, CpG sites, metabolites and other diseases

Exploring the causal relationships of diseases with genes, proteins, CpG sites, metabolites and other diseases is fundamental to the life sciences. However, large-scale research using Mendelian randomization (MR) analysis is currently lacking. To address this, we introduce DMRdb (http://www.inbirg.com/DMRdb/), a disease-centric Mendelian randomization database, designed to systematically assess causal relationships of diseases with genes, proteins, CpG sites, metabolites and other diseases. The database consists of three main components: (i) 6640 high-quality disease genome-wide association studies (GWASs) from public sources that were subjected to rigorous quality filtering and standardization; (ii) over 497 billion results from MR analyses involving 6640 disease GWAS datasets, 16 238 expression quantitative trait loci (eQTLs) data, 2564 protein quantitative trait loci (pQTLs) data, 12 000 methylation quantitative trait locus (meQTLs) data and 825 metabolites data and (iii) over 380 000 causal relationship pairs from 1223 literature sources relevant to MR analyses. A user-friendly online database was developed to allow users to query, search, and download all the results. In summary, we anticipate that DMRdb will be a valuable resource for advancing our understanding of disease mechanisms and identifying new biomarkers and therapeutic targets.

Unraveling the causal impact of smoking and its DNA methylation signatures on cardiovascular disease: Mendelian randomization and colocalization analysis

BACKGROUND

To explore the mechanisms linking smoking to cardiovascular diseases (CVDs) from an epigenetic perspective.

METHODS

Mendelian Randomization (MR) analysis was performed to assess the causal effects of smoking behavior and DNA methylation levels at smoking-related CpG sites on nine CVDs, including aortic aneurysm, atrial fibrillation, coronary atherosclerosis, coronary heart disease, heart failure, intracerebral hemorrhage, ischemic stroke, myocardial infarction, subarachnoid hemorrhage. Colocalization analysis was used to further identify key smoking-related CpG sites from the MR causal estimates. Reactome enrichment analysis was used to elucidate the potential mechanisms.

RESULTS

MR analysis indicates that smoking behaviors are significantly associated with an increased risk of nine CVDs (OR > 1, P < 0.05). Through MR and colocalization analysis, five key smoking-related CpG sites were ultimately determined. DNA methylation alteration at cg25313468 (located in the TSS1500 region of REST) is simultaneously associated with the risk of atrial fibrillation, coronary atherosclerosis, coronary heart disease, and myocardial infarction. Additionally, cg21647257 (located in the TSS200 region of CLIP3) is associated with the risk of atrial fibrillation; cg06197751 (located in SGEF gene body) and cg07520810 (located in ARID5B gene body) are associated with the risk of coronary atherosclerosis; cg16822035 (located in MCF2L gene body) is associated with the risk of myocardial infarction. Enrichment analysis suggests that phosphatase and tensin homologue (PTEN) may be involved in the downstream mechanisms of cg25313468 (REST).

CONCLUSION

This study uncovers the relationship between smoking, DNA methylation, and CVDs, providing new insights into the pathogenic effect of smoking on CVDs from an epigenetic perspective.

COVID-19 related epigenetic changes and atopic dermatitis: An exploratory analysis

Background

While epidemiological data suggest a connection between atopic dermatitis (AD) and COVID-19, the molecular mechanisms underlying this relationship remain unclear.

Objective

To investigate whether COVID-19-related CpGs may contribute to AD development and whether this association is mediated through the regulation of specific genes' expression.

Methods

We combined Mendelian randomization and transcriptome analysis for data-driven explorations.

Results

Among the 172 CpGs -associated with COVID-19 infection, merely 3 of them exhibited significant impacts on the risk of AD, including cg04543273, cg11916609, and cg10636246. In the following analysis of the causal effects of CpGs and their related gene expression, cg04543273 inhibited LMAN2 expression. However, there was not a significant impact of cg11916609 and cg10636246 on the expression of their corresponding genes. Besides, transcriptome analysis suggested that LMAN2 expression was significantly upregulated among the COVID-19-infected population, and LMAN2 expression was obviously correlated with Type 2 helper cells across different post-infection time points.

Conclusion

Overall, this study provides new insights of the COVID-19-related onset and exacerbation of AD-COVID-19-related epigenetic changes and their regulatory impact on transcription. A novel role of LMAN2 was proposed in the relationship between viral infection and AD. More studies are warranted to further explore the mechanism of LMAN2-related immunopathology.

Novel Genetic Loci in Early-Onset Gout Derived From Whole-Genome Sequencing of an Adolescent Gout Cohort

OBJECTIVE

Mechanisms underlying the adolescent-onset and early-onset gout are unclear. This study aimed to discover variants associated with early-onset gout.

METHODS

We conducted whole-genome sequencing in a discovery adolescent-onset gout cohort of 905 individuals (gout onset 12 to 19 years) to discover common and low-frequency single-nucleotide variants (SNVs) associated with gout. Candidate common SNVs were genotyped in an early-onset gout cohort of 2,834 individuals (gout onset ≤30 years old), and meta-analysis was performed with the discovery and replication cohorts to identify loci associated with early-onset gout. Transcriptome and epigenomic analyses, quantitative real-time polymerase chain reaction and RNA sequencing in human peripheral blood leukocytes, and knock-down experiments in human THP-1 macrophage cells investigated the regulation and function of candidate gene RCOR1.

RESULTS

In addition to ABCG2, a urate transporter previously linked to pediatric-onset and early-onset gout, we identified two novel loci (Pmeta < 5.0 × 10-8): rs12887440 (RCOR1) and rs35213808 (FSTL5-MIR4454). Additionally, we found associations at ABCG2 and SLC22A12 that were driven by low-frequency SNVs. SNVs in RCOR1 were linked to elevated blood leukocyte messenger RNA levels. THP-1 macrophage culture studies revealed the potential of decreased RCOR1 to suppress gouty inflammation.

CONCLUSION

This is the first comprehensive genetic characterization of adolescent-onset gout. The identified risk loci of early-onset gout mediate inflammatory responsiveness to crystals that could mediate gouty arthritis. This study will contribute to risk prediction and therapeutic interventions to prevent adolescent-onset gout.

Unidirectional and bidirectional causation between smoking and blood DNA methylation: evidence from twin-based Mendelian randomisation

Cigarette smoking is associated with numerous differentially-methylated genomic loci in multiple human tissues. These associations are often assumed to reflect the causal effects of smoking on DNA methylation (DNAm), which may underpin some of the adverse health sequelae of smoking. However, prior causal analyses with Mendelian Randomisation (MR) have found limited support for such effects. Here, we apply an integrated approach combining MR with twin causal models to examine causality between smoking and blood DNAm in the Netherlands Twin Register (N = 2577). Analyses revealed potential causal effects of current smoking on DNAm at > 500 sites in/near genes enriched for functional pathways relevant to known biological effects of smoking (e.g., hemopoiesis, cell- and neuro-development, and immune regulation). Notably, we also found evidence of reverse and bidirectional causation at several DNAm sites, suggesting that variation in DNAm at these sites may influence smoking liability. Seventeen of the loci with putative effects of DNAm on smoking showed highly specific enrichment for gene-regulatory functional elements in the brain, while the top three sites annotated to genes involved in G protein-coupled receptor signalling and innate immune response. These novel findings are partly attributable to the analyses of current smoking in twin models, rather than lifetime smoking typically examined in MR studies, as well as the increased statistical power achieved using multiallelic/polygenic scores as instrumental variables while controlling for potential horizontal pleiotropy. This study highlights the value of twin studies with genotypic and DNAm data for investigating causal relationships of DNAm with health and disease.

Association of exposure to second-hand smoke during childhood with blood DNA methylation

INTRODUCTION

By recent estimates, 40% of children worldwide are exposed to second-hand smoke (SHS), which has been associated with adverse health outcomes. While numerous studies have linked maternal smoking during pregnancy (MSDP) to widespread differences in child blood DNA methylation (DNAm), research specifically examining postnatal SHS exposure remains sparse. To address this gap, we conducted epigenome-wide meta-analyses to identify associations of postnatal SHS and child blood DNAm.

METHODS

Six cohorts from the Pregnancy And Childhood Epigenetics (PACE) Consortium (total N = 2,695), with SHS data and child blood DNAm (aged 7-9 years) measured with the Illumina 450K array were included in the meta-analysis. Linear regression models adjusted for covariates were fitted to examine the association between the number of household smokers in postnatal life (0, 1, 2+) and child blood DNAm. Sensitivity models without adjusting for MSDP and restricted to mothers who did not smoke during pregnancy were evaluated.

RESULTS

Our analysis revealed significant associations (False Discovery Rate < 0.05) between household postnatal SHS exposure and DNAm at 11 CpGs in exposed children. Nine CpGs were mapped to genes (MYO1G, FAM184B, CTDSPL2, LTBP3, PDE10A, and FIBCD1), while 2 CpGs were located in open sea regions. Notably, all except 2 CpGs (mapped to FIBCD1 and CTDSPL2) have previously been linked to either personal smoking habits or in utero exposure to smoking. The models restricted to non-smoking mothers provided similar results. Importantly, several of these CpGs and their associated genes are implicated in conditions exacerbated by or directly linked to SHS.

CONCLUSIONS

Our findings highlight the potential biological effects of SHS on blood DNAm. These findings support further research on epigenetic factors mediating deleterious effects of SHS on child health and call for public health policies aimed at reducing exposure, particularly in environments where children are present.

DNA methylation models of protein abundance across the lifecourse

BACKGROUND

Multiple studies have shown that DNA methylation (DNAm) models of protein abundance can be informative about exposure, phenotype and disease risk. Here we investigate and provide descriptive details of the capacity of DNAm to capture non-genetic variation in protein abundance across the lifecourse.

METHODS

We evaluated the performance of 14 previously published DNAm models of protein abundance (episcores) in peripheral blood from a large adult population using the Avon Longitudinal Study of Parents and Children (ALSPAC) at ages 7-24 and their mothers antenatally and in middle age (N range = 145-1464). New age-specific episcores were trained in ALSPAC and evaluated at different ages. In all instances, episcore-protein associations were evaluated with and without adjustment for genetics. The association between longitudinal protein stability and longitudinal episcore projection was also evaluated, as was sex-specificity of episcores derived solely in female participants.

FINDINGS

Of the 14 Gadd episcores, 10 generated estimates associated with abundance in middle age, 9 at age 24, and none at age 9. Eight of these episcores explained variation beyond genotype in adulthood (6 at age 24; 7 at midlife). At age 9, the abundances of 22 proteins could be modelled by DNAm, 7 beyond genotype of which one trained model generated informative estimates at ages 24 and in middle age. At age 24, 31 proteins could be modelled by DNAm, 19 beyond genotype, of which 5 trained models generated informative estimates at age 9 and 8 in middle age. In middle age, 23 proteins could be modelled, 13 beyond genotype, of which 3 were informative at age 9 and 7 at age 24.

INTERPRETATION

We observed that episcores performed better at older ages than in children with several episcores capturing non-genetic variation at all ages.

Maximizing insights from longitudinal epigenetic age data: simulations, applications, and practical guidance

BACKGROUND

Epigenetic age (EA) is an age estimate, developed using DNA methylation (DNAm) states of selected CpG sites across the genome. Although EA and chronological age are highly correlated, EA may not increase uniformly with time. Departures, known as epigenetic age acceleration (EAA), are common and have been linked to various traits and future disease risk. Limited by available data, most studies investigating these relationships have been cross-sectional, using a single EA measurement. However, the recent growth in longitudinal DNAm studies has led to analyses of associations with EA over time. These studies differ in (1) their choice of model; (2) the primary outcome (EA vs. EAA); and (3) in their use of chronological age or age-independent time variables to account for the temporal dynamic. We evaluated the robustness of each approach using simulations and tested our results in two real-world examples, using biological sex and birthweight as predictors of longitudinal EA.

RESULTS

Our simulations showed most accurate effect sizes in a linear mixed model or generalized estimating equation, using chronological age as the time variable. The use of EA versus EAA as an outcome did not strongly impact estimates. Applying the optimal model in real-world data uncovered advanced GrimAge in individuals assigned male at birth that decelerates over time.

CONCLUSION

Our results can serve as a guide for forthcoming longitudinal EA studies, aiding in methodological decisions that may determine whether an association is accurately estimated, overestimated, or potentially overlooked.

Epigenome-wide association studies identify novel DNA methylation sites associated with PTSD: a meta-analysis of 23 military and civilian cohorts

BACKGROUND

The occurrence of post-traumatic stress disorder (PTSD) following a traumatic event is associated with biological differences that can represent the susceptibility to PTSD, the impact of trauma, or the sequelae of PTSD itself. These effects include differences in DNA methylation (DNAm), an important form of epigenetic gene regulation, at multiple CpG loci across the genome. Moreover, these effects can be shared or specific to both central and peripheral tissues. Here, we aim to identify blood DNAm differences associated with PTSD and characterize the underlying biological mechanisms by examining the extent to which they mirror associations across multiple brain regions.

METHODS

As the Psychiatric Genomics Consortium (PGC) PTSD Epigenetics Workgroup, we conducted the largest cross-sectional meta-analysis of epigenome-wide association studies (EWASs) of PTSD to date, involving 5077 participants (2156 PTSD cases and 2921 trauma-exposed controls) from 23 civilian and military studies. PTSD diagnosis assessments were harmonized following the standardized guidelines established by the PGC-PTSD Workgroup. DNAm was assayed from blood using Illumina HumanMethylation450 or MethylationEPIC (850 K) BeadChips. Within each cohort, DNA methylation was regressed on PTSD, sex (if applicable), age, blood cell proportions, and ancestry. An inverse variance-weighted meta-analysis was performed. We conducted replication analyses in tissue from multiple brain regions, neuronal nuclei, and a cellular model of prolonged stress.

RESULTS

We identified 11 CpG sites associated with PTSD in the overall meta-analysis (1.44e - 09 < p < 5.30e - 08), as well as 14 associated in analyses of specific strata (military vs civilian cohort, sex, and ancestry), including CpGs in AHRR and CDC42BPB. Many of these loci exhibit blood-brain correlation in methylation levels and cross-tissue associations with PTSD in multiple brain regions. Out of 9 CpGs annotated to a gene expressed in blood, methylation levels at 5 CpGs showed significant correlations with the expression levels of their respective annotated genes.

CONCLUSIONS

This study identifies 11 PTSD-associated CpGs and leverages data from postmortem brain samples, GWAS, and genome-wide expression data to interpret the biology underlying these associations and prioritize genes whose regulation differs in those with PTSD.

Integrating Whole Genome and Transcriptome Sequencing to Characterize the Genetic Architecture of Isoform Variation and its Implications for Health and Disease

We created a comprehensive whole blood splice variation quantitative trait locus (sQTL) resource by analyzing isoform expression ratio (isoform-to-gene) in Framingham Heart Study (FHS) participants (discovery: n=2,622; validation: n=1,094) with whole genome (WGS) and transcriptome sequencing (RNA-seq) data. External replication was conducted using WGS and RNA-seq from the Jackson Heart Study (JHS, n=1,020). We identified over 3.5 million cis -sQTL-isoform pairs ( p <5e-8), comprising 1,176,624 cis -sQTL variants and 10,883 isoform transcripts from 4,971 sGenes, with significant change in isoform-to-gene ratio due to allelic variation. We validated 61% of these pairs in the FHS validation sample ( p <1e-4). External validation ( p <1e-4) in JHS for the top 10,000 and 100,000 most significant cis -sQTL-isoform pairs was 88% and 69%, respectively, while overall pairs validated at 23%. For 20% of cis -sQTLs in the FHS discovery sample, allelic variation did not significantly correlate with overall gene expression. sQTLs are enriched in splice donor and acceptor sites, as well as in GWAS SNPs, methylation QTLs, and protein QTLs. We detailed several sentinel cis -sQTLs influencing alternative splicing, with potential causal effects on cardiovascular disease risk. Notably, rs12898397 (T>C) affects splicing of ULK3 , lowering levels of the full-length transcript ENST00000440863.7 and increasing levels of the truncated transcript ENST00000569437.5, encoding proteins of different lengths. Mendelian randomization analysis demonstrated that a lower ratio of the full-length isoform is causally associated with lower diastolic blood pressure and reduced lymphocyte percentages. This sQTL resource provides valuable insights into how transcriptomic variation may influence health outcomes.

The methylomic landscape of human articular cartilage development contains epigenetic signatures of osteoarthritis risk

Increasing evidence is emerging to link age-associated complex musculoskeletal diseases, including osteoarthritis (OA), to developmental factors. Multiple studies have shown a functional role for DNA methylation in the genetic mechanisms of OA risk using articular cartilage samples taken from aged individuals, yet knowledge of temporal changes to the methylome during human cartilage development is limited. We quantified DNA methylation at ∼700,000 individual CpGs across the epigenome of developing human chondrocytes in 72 samples ranging from 7 to 21 post-conception weeks. We identified significant changes in 3% of all CpGs and >8,200 developmental differentially methylated regions. We further identified 24 loci at which OA genetic variants colocalize with methylation quantitative trait loci. Through integrating developmental and mature human chondrocyte datasets, we find evidence for functional effects exerted solely in development or throughout the life course. This will have profound impacts on future approaches to translating genetic pathways for therapeutic intervention.

Identification and functional characterisation of DNA methylation differences between East- and West-originating Finns

Eastern and Western Finns show a striking difference in coronary heart disease-related mortality; genetics is a known contributor for this discrepancy. Here, we discuss the potential role of DNA methylation in mediating the discrepancy in cardiometabolic disease-risk phenotypes between the sub-populations. We used data from the Young Finns Study (n = 969) to compare the genome-wide DNA methylation levels of East- and West-originating Finns. We identified 21 differentially methylated loci (FDR < 0.05; Δβ >2.5%) and 7 regions (smoothed FDR < 0.05; CpGs ≥ 5). Methylation at all loci and regions associates with genetic variants (p < 5 × 10-8). Independently of genetics, methylation at 11 loci and 4 regions associates with transcript expression, including genes encoding zinc finger proteins. Similarly, methylation at 5 loci and 4 regions associates with cardiometabolic disease-risk phenotypes including triglycerides, glucose, cholesterol, as well as insulin treatment. This analysis was also performed in LURIC (n = 2371), a German cardiovascular patient cohort, and results replicated for the association of methylation at cg26740318 and DMR_11p15 with diabetes-related phenotypes and methylation at DMR_22q13 with triglyceride levels. Our results indicate that DNA methylation differences between East and West Finns may have a functional role in mediating the cardiometabolic disease discrepancy between the sub-populations.

A multi-omics Mendelian randomization identifies putatively causal genes and DNA methylation sites for asthma

Background

Asthma is a global chronic respiratory disease with complex pathogenesis. While current therapies offer some relief, they often fall short in effectively managing symptoms and preventing exacerbations for numerous patients. Thus, understanding its mechanisms and discovering new drug targets remains a pressing need for better treatment.

Methods

Using the GEO dataset, we screened differentially expressed genes (DEGs) in asthma patients' blood. Employing Summary Data-based Mendelian Randomization (SMR) and Two-Sample Mendelian Randomization (TSMR), we pinpointed asthma causal genes, causal DNA methylation sites, and methylation sites affecting gene expression, cross validated with at least 2 large-scale GWAS from each source. We utilized colocalization for genetic associations, meta-analysis for data integration, two-step MR for methylation-gene-asthma mediation mechanism. Druggability was evaluated using Open Target, virtual screening, and docking.

Results

Among the 954 DEGs found in asthma patients' blood, increased expression of CEP95 (discovery, OR_SMR = 0.94, 95% CI: 0.91-0.97), RBM6 (discovery, OR_SMR = 0.97, 95% CI: 0.95-0.99), and ITPKB (discovery, OR_SMR = 0.82, 95% CI: 0.74-0.92) in the blood decreased the risk of asthma, higher levels of HOXB-AS1 (discovery, OR_SMR = 1.05, 95% CI: 1.03-1.07), ETS1 (discovery, OR_SMR = 1.62, 95% CI: 1.29-2.04), and JAK2 (discovery, OR_SMR = 1.13, 95% CI: 1.06-1.21) in the blood increased the risk of asthma. Additionally, a total of 8 methylation sites on ITPKB, ETS1, and JAK2 were identified to influence asthma. An increase in methylation at site cg16265553 raised the risk of asthma partially by suppressing ITPKB expression. Similarly, increased methylation at cg13661497 reduced the asthma risk totally by suppressing JAK2 expression. The impact of CEP95, HOXB-AS1, and RBM6 expressions on asthma was further confirmed in lung tissues. Except for HOXB-AS1, all the other genes were potential druggable targets.

Conclusion

Our study highlighted that specific gene expressions and methylation sites significantly influence asthma risk and revealed a potential methylation-to-gene-to-asthma mechanism. This provided pivotal evidence for future targeted functional studies and the development of preventive and treatment strategies.

Critical evaluation of the reliability of DNA methylation probes on the Illumina MethylationEPIC v1.0 BeadChip microarrays

DNA methylation (DNAm) plays a crucial role in a number of complex diseases. However, the reliability of DNAm levels measured using Illumina arrays varies across different probes. Previous research primarily assessed probe reliability by comparing duplicate samples between the 450k-450k or 450k-EPIC platforms, with limited investigations on Illumina EPIC v1.0 arrays. We conducted a comprehensive assessment of the EPIC v1.0 array probe reliability using 69 blood DNA samples, each measured twice, generated by the Alzheimer's Disease Neuroimaging Initiative study. We observed higher reliability in probes with average methylation beta values of 0.2 to 0.8, and lower reliability in type I probes or those within the promoter and CpG island regions. Importantly, we found that probe reliability has significant implications in the analyses of Epigenome-wide Association Studies (EWAS). Higher reliability is associated with more consistent effect sizes in different studies, the identification of differentially methylated regions (DMRs) and methylation quantitative trait locus (mQTLs), and significant correlations with downstream gene expression. Moreover, blood DNAm measurements obtained from probes with higher reliability are more likely to show concordance with brain DNAm measurements. Our findings, which provide crucial reliability information for probes on the EPIC v1.0 array, will serve as a valuable resource for future DNAm studies.