eFORGE: A Tool for Identifying Cell Type-Specific Signal in Epigenomic Data

An improved epigenetic counter to track mitotic age in normal and precancerous tissues

The cumulative number of stem cell divisions in a tissue, known as mitotic age, is thought to be a major determinant of cancer-risk. Somatic mutational and DNA methylation (DNAm) clocks are promising tools to molecularly track mitotic age, yet their relationship is underexplored and their potential for cancer risk prediction in normal tissues remains to be demonstrated. Here we build and validate an improved pan-tissue DNAm counter of total mitotic age called stemTOC. We demonstrate that stemTOC's mitotic age proxy increases with the tumor cell-of-origin fraction in each of 15 cancer-types, in precancerous lesions, and in normal tissues exposed to major cancer risk factors. Extensive benchmarking against 6 other mitotic counters shows that stemTOC compares favorably, specially in the preinvasive and normal-tissue contexts. By cross-correlating stemTOC to two clock-like somatic mutational signatures, we confirm the mitotic-like nature of only one of these. Our data points towards DNAm as a promising molecular substrate for detecting mitotic-age increases in normal tissues and precancerous lesions, and hence for developing cancer-risk prediction strategies.

African ancestry-derived APOL1 risk genotypes show proximal epigenetic associations

Apolipoprotein L1 (APOL1) coding variants, termed G1 and G2, are established genetic risk factors for a growing spectrum of diseases, including kidney disease, in individuals of African ancestry. Evidence suggests that the risk variants, which show a recessive mode of inheritance, lead to toxic gain-of-function changes of the APOL1 protein. Disease occurrence and presentation vary, likely due to modifiers or second hits. To understand the role of the epigenetic landscape in relation to APOL1 risk variants, we performed methylation quantitative trait locus (meQTL) analysis to identify differentially methylated CpGs influenced by APOL1 risk variants in 611 African American individuals. We identified five CpGs that were significantly associated with APOL1 risk alleles in discovery and replication studies, and one CpG-APOL1 association was independent of other genomic variants. Our study highlights proximal DNA methylation alterations that may help explain the variable disease risk and clinical manifestation of APOL1 variants.

DNA methylation marker identification and poly-methylation risk score in prediction of healthspan termination

Aim: To elucidate the epigenetic consequences of DNA methylation in healthspan termination (HST), considering the current limited understanding. Materials & methods: Genetically predicted DNA methylation models were established (n = 2478). These models were applied to genome-wide association study data on HST. Then, a poly-methylation risk score (PMRS) was established in 241,008 individuals from the UK Biobank. Results: Of the 63,046 CpGs from the prediction models, 13 novel CpGs were associated with HST. Furthermore, people with high PMRSs showed higher HST risk (hazard ratio: 1.18; 95% CI: 1.13-1.25). Conclusion: The study indicates that DNA methylation may influence HST by regulating the expression of genes (e.g., PRMT6, CTSK). PMRSs have a promising application in discriminating subpopulations to facilitate early prevention.

Comprehensive evaluation of smoking exposures and their interactions on DNA methylation

BACKGROUND

Smoking impacts DNA methylation, but data are lacking on smoking-related differential methylation by sex or dietary intake, recent smoking cessation (<1 year), persistence of differential methylation from in utero smoking exposure, and effects of environmental tobacco smoke (ETS).

METHODS

We meta-analysed data from up to 15,014 adults across 5 cohorts with DNA methylation measured in blood using Illumina's EPIC array for current smoking (2560 exposed), quit < 1 year (500 exposed), in utero (286 exposed), and ETS exposure (676 exposed). We also evaluated the interaction of current smoking with sex or diet (fibre, folate, and vitamin C).

FINDINGS

Using false discovery rate (FDR < 0.05), 65,857 CpGs were differentially methylated in relation to current smoking, 4025 with recent quitting, 594 with in utero exposure, and 6 with ETS. Most current smoking CpGs attenuated within a year of quitting. CpGs related to in utero exposure in adults were enriched for those previously observed in newborns. Differential methylation by current smoking at 4-71 CpGs may be modified by sex or dietary intake. Nearly half (35-50%) of differentially methylated CpGs on the 450 K array were associated with blood gene expression. Current smoking and in utero smoking CpGs implicated 3049 and 1067 druggable targets, including chemotherapy drugs.

INTERPRETATION

Many smoking-related methylation sites were identified with Illumina's EPIC array. Most signals revert to levels observed in never smokers within a year of cessation. Many in utero smoking CpGs persist into adulthood. Smoking-related druggable targets may provide insights into cancer treatment response and shared mechanisms across smoking-related diseases.

FUNDING

Intramural Research Program of the National Institutes of Health, Norwegian Ministry of Health and Care Services and the Ministry of Education and Research, Chief Scientist Office of the Scottish Government Health Directorates and the Scottish Funding Council, Medical Research Council UK and the Wellcome Trust.

Identification of candidate DNA methylation biomarkers related to Alzheimer's disease risk by integrating genome and blood methylome data

Alzheimer disease (AD) is a common neurodegenerative disease with a late onset. It is critical to identify novel blood-based DNA methylation biomarkers to better understand the extent of the molecular pathways affected in AD. Two sets of blood DNA methylation genetic prediction models developed using different reference panels and modelling strategies were leveraged to evaluate associations of genetically predicted DNA methylation levels with AD risk in 111,326 (46,828 proxy) cases and 677,663 controls. A total of 1,168 cytosine-phosphate-guanine (CpG) sites showed a significant association with AD risk at a false discovery rate (FDR) < 0.05. Methylation levels of 196 CpG sites were correlated with expression levels of 130 adjacent genes in blood. Overall, 52 CpG sites of 32 genes showed consistent association directions for the methylation-gene expression-AD risk, including nine genes (CNIH4, THUMPD3, SERPINB9, MTUS1, CISD1, FRAT2, CCDC88B, FES, and SSH2) firstly reported as AD risk genes. Nine of 32 genes were enriched in dementia and AD disease categories (P values ranged from 1.85 × 10-4 to 7.46 × 10-6), and 19 genes in a neurological disease network (score = 54) were also observed. Our findings improve the understanding of genetics and etiology for AD.

Sex-specific DNA methylation in saliva from the multi-ethnic Future of Families and Child Wellbeing Study

The prevalence and severity of many diseases differs by sex, potentially due to sex-specific patterns in DNA methylation. Autosomal sex-specific differences in DNA methylation have been observed in cord blood and placental tissue but are not well studied in saliva or in diverse populations. We sought to characterize sex-specific DNA methylation on autosomal chromosomes in saliva samples from children in the Future of Families and Child Wellbeing Study, a multi-ethnic prospective birth cohort containing an oversampling of Black, Hispanic and low-income families. DNA methylation from saliva samples was analysed on 796 children (50.6% male) at both ages 9 and 15 with DNA methylation measured using the Illumina HumanMethylation 450k array. An epigenome-wide association analysis of the age 9 samples identified 8,430 sex-differentiated autosomal DNA methylation sites (P < 2.4 × 10-7), of which 76.2% had higher DNA methylation in female children. The strongest sex-difference was in the cg26921482 probe, in the AMDHD2 gene, with 30.6% higher DNA methylation in female compared to male children (P < 1 × 10-300). Treating the age 15 samples as an internal replication set, we observed highly consistent results between the ages 9 and 15 measurements, indicating stable and replicable sex-differentiation. Further, we directly compared our results to previously published DNA methylation sex differences in both cord blood and saliva and again found strong consistency. Our findings support widespread and robust sex-differential DNA methylation across age, human tissues, and populations. These findings help inform our understanding of potential biological processes contributing to sex differences in human physiology and disease.

Multi-ancestry epigenome-wide analyses identify methylated sites associated with aortic augmentation index in TOPMed MESA

Despite the prognostic value of arterial stiffness (AS) and pulsatile hemodynamics (PH) for cardiovascular morbidity and mortality, epigenetic modifications that contribute to AS/PH remain unknown. To gain a better understanding of the link between epigenetics (DNA methylation) and AS/PH, we examined the relationship of eight measures of AS/PH with CpG sites and co-methylated regions using multi-ancestry participants from Trans-Omics for Precision Medicine (TOPMed) Multi-Ethnic Study of Atherosclerosis (MESA) with sample sizes ranging from 438 to 874. Epigenome-wide association analysis identified one genome-wide significant CpG (cg20711926-CYP1B1) associated with aortic augmentation index (AIx). Follow-up analyses, including gene set enrichment analysis, expression quantitative trait methylation analysis, and functional enrichment analysis on differentially methylated positions and regions, further prioritized three CpGs and their annotated genes (cg23800023-ETS1, cg08426368-TGFB3, and cg17350632-HLA-DPB1) for AIx. Among these, ETS1 and TGFB3 have been previously prioritized as candidate genes. Furthermore, both ETS1 and HLA-DPB1 have significant tissue correlations between Whole Blood and Aorta in GTEx, which suggests ETS1 and HLA-DPB1 could be potential biomarkers in understanding pathophysiology of AS/PH. Overall, our findings support the possible role of epigenetic regulation via DNA methylation of specific genes associated with AIx as well as identifying potential targets for regulation of AS/PH.

Multi-ancestry epigenome-wide analyses identify methylated sites associated with aortic augmentation index in TOPMed MESA

Despite the prognostic value of arterial stiffness (AS) and pulsatile hemodynamics (PH) for cardiovascular morbidity and mortality, epigenetic modifications that contribute to AS/PH remain unknown. To gain a better understanding of the link between epigenetics (DNA methylation) and AS/PH, we examined the relationship of eight measures of AS/PH with CpG sites and co-methylated regions using multi-ancestry participants from Trans-Omics for Precision Medicine (TOPMed) Multi-Ethnic Study of Atherosclerosis (MESA) with sample sizes ranging from 438 to 874. Epigenome-wide association analysis identified one genome-wide significant CpG (cg20711926-CYP1B1) associated with aortic augmentation index (AIx). Follow-up analyses, including gene set enrichment analysis, expression quantitative trait methylation analysis, and functional enrichment analysis on differentially methylated positions and regions, further prioritized three CpGs and their annotated genes (cg23800023-ETS1, cg08426368-TGFB3, and cg17350632-HLA-DPB1) for AIx. Among these, ETS1 and TGFB3 have been previously prioritized as candidate genes. Furthermore, both ETS1 and HLA-DPB1 have significant tissue correlations between Whole Blood and Aorta in GTEx, which suggests ETS1 and HLA-DPB1 could be potential biomarkers in understanding pathophysiology of AS/PH. Overall, our findings support the possible role of epigenetic regulation via DNA methylation of specific genes associated with AIx as well as identifying potential targets for regulation of AS/PH.

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

Increasing evidence supports the role of placenta in neurodevelopment and potentially, in the later onset of neuropsychiatric disorders. Recently, methylation quantitative trait loci (mQTL) and interaction QTL (iQTL) maps have proven useful to understand SNP-genome wide association study (GWAS) relationships, otherwise missed by conventional expression QTLs. In this context, we propose that part of the genetic predisposition to complex neuropsychiatric disorders acts through placental DNA methylation (DNAm). We constructed the first public placental cis-mQTL database including nearly eight million mQTLs calculated in 368 fetal placenta DNA samples from the INMA project, ran cell type- and gestational age-imQTL models and combined those data with the summary statistics of the largest GWAS on 10 neuropsychiatric disorders using Summary-based Mendelian Randomization (SMR) and colocalization. Finally, we evaluated the influence of the DNAm sites identified on placental gene expression in the RICHS cohort. We found that placental cis-mQTLs are highly enriched in placenta-specific active chromatin regions, and useful to map the etiology of neuropsychiatric disorders at prenatal stages. Specifically, part of the genetic burden for schizophrenia, bipolar disorder and major depressive disorder confers risk through placental DNAm. The potential causality of several of the observed associations is reinforced by secondary association signals identified in conditional analyses, regional pleiotropic methylation signals associated to the same disorder, and cell type-imQTLs, additionally associated to the expression levels of relevant immune genes in placenta. In conclusion, the genetic risk of several neuropsychiatric disorders could operate, at least in part, through DNAm and associated gene expression in placenta.

Distinct genome-wide DNA methylation and gene expression signatures in classical monocytes from African American patients with systemic sclerosis

BACKGROUND

Systemic sclerosis (SSc) is a multisystem autoimmune disorder that has an unclear etiology and disproportionately affects women and African Americans. Despite this, African Americans are dramatically underrepresented in SSc research. Additionally, monocytes show heightened activation in SSc and in African Americans relative to European Americans. In this study, we sought to investigate DNA methylation and gene expression patterns in classical monocytes in a health disparity population.

METHODS

Classical monocytes (CD14+ + CD16-) were FACS-isolated from 34 self-reported African American women. Samples from 12 SSc patients and 12 healthy controls were hybridized on MethylationEPIC BeadChip array, while RNA-seq was performed on 16 SSc patients and 18 healthy controls. Analyses were computed to identify differentially methylated CpGs (DMCs), differentially expressed genes (DEGs), and CpGs associated with changes in gene expression (eQTM analysis).

RESULTS

We observed modest DNA methylation and gene expression differences between cases and controls. The genes harboring the top DMCs, the top DEGs, as well as the top eQTM loci were enriched for metabolic processes. Genes involved in immune processes and pathways showed a weak upregulation in the transcriptomic analysis. While many genes were newly identified, several other have been previously reported as differentially methylated or expressed in different blood cells from patients with SSc, supporting for their potential dysregulation in SSc.

CONCLUSIONS

While contrasting with results found in other blood cell types in largely European-descent groups, the results of this study support that variation in DNA methylation and gene expression exists among different cell types and individuals of different genetic, clinical, social, and environmental backgrounds. This finding supports the importance of including diverse, well-characterized patients to understand the different roles of DNA methylation and gene expression variability in the dysregulation of classical monocytes in diverse populations, which might help explaining the health disparities.

Prenatal social support in low-risk pregnancy shapes placental epigenome

BACKGROUND

Poor social support during pregnancy has been linked to inflammation and adverse pregnancy and childhood health outcomes. Placental epigenetic alterations may underlie these links but are still unknown in humans.

METHODS

In a cohort of low-risk pregnant women (n = 301) from diverse ethnic backgrounds, social support was measured using the ENRICHD Social Support Inventory (ESSI) during the first trimester. Placental samples collected at delivery were analyzed for DNA methylation and gene expression using Illumina 450K Beadchip Array and RNA-seq, respectively. We examined association between maternal prenatal social support and DNA methylation in placenta. Associated cytosine-(phosphate)-guanine sites (CpGs) were further assessed for correlation with nearby gene expression in placenta.

RESULTS

The mean age (SD) of the women was 27.7 (5.3) years. The median (interquartile range) of ESSI scores was 24 (22-25). Prenatal social support was significantly associated with methylation level at seven CpGs (P_FDR < 0.05). The methylation levels at two of the seven CpGs correlated with placental expression of VGF and ILVBL (P_FDR < 0.05), genes known to be involved in neurodevelopment and energy metabolism. The genes annotated with the top 100 CpGs were enriched for pathways related to fetal growth, coagulation system, energy metabolism, and neurodevelopment. Sex-stratified analysis identified additional significant associations at nine CpGs in male-bearing pregnancies and 35 CpGs in female-bearing pregnancies.

CONCLUSIONS

The findings suggest that prenatal social support is linked to placental DNA methylation changes in a low-stress setting, including fetal sex-dependent epigenetic changes. Given the relevance of some of these changes in fetal neurodevelopmental outcomes, the findings signal important methylation targets for future research on molecular mechanisms of effect of the broader social environment on pregnancy and fetal outcomes.

TRIAL REGISTRATION

NCT00912132 ( ClinicalTrials.gov ).

A comparison of the genes and genesets identified by GWAS and EWAS of fifteen complex traits

Identifying genomic regions pertinent to complex traits is a common goal of genome-wide and epigenome-wide association studies (GWAS and EWAS). GWAS identify causal genetic variants, directly or via linkage disequilibrium, and EWAS identify variation in DNA methylation associated with a trait. While GWAS in principle will only detect variants due to causal genes, EWAS can also identify genes via confounding, or reverse causation. We systematically compare GWAS (N > 50,000) and EWAS (N > 4500) results of 15 complex traits. We evaluate if the genes or gene ontology terms flagged by GWAS and EWAS overlap, and find substantial overlap for diastolic blood pressure, (gene overlap P = 5.2 × 10^-6; term overlap P = 0.001). We superimpose our empirical findings against simulated models of varying genetic and epigenetic architectures and observe that in most cases GWAS and EWAS are likely capturing distinct genesets. Our results indicate that GWAS and EWAS are capturing different aspects of the biology of complex traits.

Genome-wide DNA methylation of Munro's microabscess reveals the epigenetic regulation in the pathogenesis of psoriasis

Introduction

Munro's microabscess is a typical pathological feature in the early psoriatic lesion, mainly characterized by the accumulation of neutrophils in the epidermis. DNA methylation microenvironment of Munro's microabscess and the crosstalk with transcription and its effect on neutrophils have not yet been revealed.

Methods

Performed genome-wide DNA methylation analysis and further differential methylation analysis of psoriatic skin lesions with and without Munro's microabscess from two batch samples consisting of 114 former samples in the discovery stage and 21 newly-collected samples in the validation stage. Utilized GO, MEME, and other tools to conduct downstream analysis on differentially methylated sites (DMSs). Correlation analysis of methylation level and transcriptome data was also conducted.

Results

We observed 647 overlapping DMSs associated with Munro's microabscess. Subsequently, GO pathway analysis revealed that DNA methylation might affect the physical properties associated with skin cells through focal adhesion and cellsubstrate junction and was likely to recruit neutrophils in the epidermis. Via the MEME tool, used to investigate the possible binding transcription factors (TFs) of 20 motifs around the 647 DMSs, it was found that DNA methylation regulated the binding of AP1 family members and the recruitment of neutrophils in the epidermis through the TGF-beta pathway and the TH17 pathway. Meanwhile, combined with our earlier transcriptome data, we found DNA methylation would regulate the expressions of CFDP, SIRT6, SMG6, TRAPPC9, HSD17B7, and KIAA0415, indicating these genes would potentially promote the process of Munro's microabscess.

Discussion

In conclusion, DNA methylation may affect the course of psoriasis by regulating the progression of Munro's microabscess in psoriatic skin lesions.

Clonal hematopoiesis of indeterminate potential, DNA methylation, and risk for coronary artery disease

Age-related changes to the genome-wide DNA methylation (DNAm) pattern observed in blood are well-documented. Clonal hematopoiesis of indeterminate potential (CHIP), characterized by the age-related acquisition and expansion of leukemogenic mutations in hematopoietic stem cells (HSCs), is associated with blood cancer and coronary artery disease (CAD). Epigenetic regulators DNMT3A and TET2 are the two most frequently mutated CHIP genes. Here, we present results from an epigenome-wide association study for CHIP in 582 Cardiovascular Health Study (CHS) participants, with replication in 2655 Atherosclerosis Risk in Communities (ARIC) Study participants. We show that DNMT3A and TET2 CHIP have distinct and directionally opposing genome-wide DNAm association patterns consistent with their regulatory roles, albeit both promoting self-renewal of HSCs. Mendelian randomization analyses indicate that a subset of DNAm alterations associated with these two leading CHIP genes may promote the risk for CAD.

Pulmonary Function and Blood DNA Methylation: A Multiancestry Epigenome-Wide Association Meta-analysis

Rationale: Methylation integrates factors present at birth and modifiable across the lifespan that can influence pulmonary function. Studies are limited in scope and replication. Objectives: To conduct large-scale epigenome-wide meta-analyses of blood DNA methylation and pulmonary function. Methods: Twelve cohorts analyzed associations of methylation at cytosine-phosphate-guanine probes (CpGs), using Illumina 450K or EPIC/850K arrays, with FEV₁, FVC, and FEV₁/FVC. We performed multiancestry epigenome-wide meta-analyses (total of 17,503 individuals; 14,761 European, 2,549 African, and 193 Hispanic/Latino ancestries) and interpreted results using integrative epigenomics. Measurements and Main Results: We identified 1,267 CpGs (1,042 genes) differentially methylated (false discovery rate, <0.025) in relation to FEV₁, FVC, or FEV₁/FVC, including 1,240 novel and 73 also related to chronic obstructive pulmonary disease (1,787 cases). We found 294 CpGs unique to European or African ancestry and 395 CpGs unique to never or ever smokers. The majority of significant CpGs correlated with nearby gene expression in blood. Findings were enriched in key regulatory elements for gene function, including accessible chromatin elements, in both blood and lung. Sixty-nine implicated genes are targets of investigational or approved drugs. One example novel gene highlighted by integrative epigenomic and druggable target analysis is TNFRSF4. Mendelian randomization and colocalization analyses suggest that epigenome-wide association study signals capture causal regulatory genomic loci. Conclusions: We identified numerous novel loci differentially methylated in relation to pulmonary function; few were detected in large genome-wide association studies. Integrative analyses highlight functional relevance and potential therapeutic targets. This comprehensive discovery of potentially modifiable, novel lung function loci expands knowledge gained from genetic studies, providing insights into lung pathogenesis.

Diversity in EWAS: current state, challenges, and solutions

Here, we report a lack of diversity in epigenome-wide association studies (EWAS) and DNA methylation (DNAm) data, discuss current challenges, and propose solutions for EWAS and DNAm research in diverse populations. The strategies we propose include fostering community involvement, new data generation, and cost-effective approaches such as locus-specific analysis and ancestry variable region analysis.

Embryo cryopreservation leads to sex-specific DNA methylation perturbations in both human and mouse placentas

In vitro fertilization (IVF) is associated with DNA methylation abnormalities and a higher incidence of adverse pregnancy outcomes. However, which exposure(s), among the many IVF interventions, contributes to these outcomes remains unknown. Frozen embryo transfer (ET) is increasingly utilized as an alternative to fresh ET, but reports suggest a higher incidence of pre-eclampsia and large for gestational age infants. This study examines DNA methylation in human placentas using the 850K Infinium MethylationEPIC BeadChip array obtained after 65 programmed frozen ET cycles, 82 fresh ET cycles and 45 unassisted conceptions. Nine patients provided placentas following frozen and fresh ET from consecutive pregnancies for a paired subgroup analysis. In parallel, eight mouse placentas from fresh and frozen ET were analyzed using the Infinium Mouse Methylation BeadChip array. Human and mouse placentas were significantly hypermethylated after frozen ET compared with fresh. Paired analysis showed similar trends. Sex-specific analysis revealed that these changes were driven by male placentas in humans and mice. Frozen and fresh ET placentas were significantly different from controls, with frozen samples hypermethylated compared with controls driven by males and fresh samples being hypomethylated compared with controls, driven by females. Sexually dimorphic epigenetic changes could indicate differential susceptibility to IVF-associated perturbations, which highlights the importance of sex-specific evaluation of adverse outcomes. Similarities between changes in mice and humans underscore the suitability of the mouse model in evaluating how IVF impacts the epigenetic landscape, which is valuable given limited access to human tissue and the ability to isolate specific interventions in mice.

Integrative multi-omic analysis identifies genetically influenced DNA methylation biomarkers for breast and prostate cancers

Aberrant DNA methylation has emerged as a hallmark in several cancers and contributes to risk, oncogenesis, progression, and prognosis. In this study, we performed imputation-based and conventional methylome-wide association analyses for breast cancer (BrCa) and prostate cancer (PrCa). The imputation-based approach identified DNA methylation at cytosine-phosphate-guanine sites (CpGs) associated with BrCa and PrCa risk utilising genome-wide association summary statistics (N_BrCa = 228,951, N_PrCa = 140,254) and prebuilt methylation prediction models, while the conventional approach identified CpG associations utilising TCGA and GEO experimental methylation data (N_BrCa = 621, N_PrCa = 241). Enrichment analysis of the association results implicated 77 and 81 genetically influenced CpGs for BrCa and PrCa, respectively. Furthermore, analysis of differential gene expression around these CpGs suggests a genome-epigenome-transcriptome mechanistic relationship. Conditional analyses identified multiple independent secondary SNP associations (P_cond < 0.05) around 28 BrCa and 22 PrCa CpGs. Cross-cancer analysis identified eight common CpGs, including a strong therapeutic target in SREBF1 (17p11.2)—a key player in lipid metabolism. These findings highlight the utility of integrative analysis of multi-omic cancer data to identify robust biomarkers and understand their regulatory effects on cancer risk.

Methylome-wide association studies identify genetically-influenced CpGs associated with breast and prostate cancer risk and (epi)genome-transcriptome mechanistic relationships, with lipid metabolism genes implicated as potential therapeutic targets.

Cell Type-Specific Signal Analysis in Epigenome-Wide Association Studies

Hundreds of epigenome-wide association studies (EWAS) have been performed, successfully identifying replicated epigenomic signals in processes such as aging and smoking. Despite this progress, it remains a major challenge in EWAS to detect both cell type-specific and cell type confounding effects impacting study results. One way to identify these effects is through eFORGE (experimentally derived Functional element Overlap analysis of ReGions from EWAS), a published tool that uses 815 datasets from large-scale mapping studies to detect enriched tissues, cell types, and genomic regions. Here, I show that eFORGE analysis can be extended to EWAS differentially variable positions (DVPs), identifying target cell types and tissues. In addition, I also show that eFORGE tissue-specific enrichment can be detected for sites below EWAS significance threshold. I develop on these and other analysis examples, extending our knowledge of eFORGE cell type- and tissue-specific enrichment results for different EWAS.

Maternal iron status in early pregnancy and DNA methylation in offspring: an epigenome-wide meta-analysis

BACKGROUND

Unbalanced iron homeostasis in pregnancy is associated with an increased risk of adverse birth and childhood health outcomes. DNA methylation has been suggested as a potential underlying mechanism linking environmental exposures such as micronutrient status during pregnancy with offspring health. We performed a meta-analysis on the association of maternal early-pregnancy serum ferritin concentrations, as a marker of body iron stores, and cord blood DNA methylation. We included 1286 mother-newborn pairs from two population-based prospective cohorts. Serum ferritin concentrations were measured in early pregnancy. DNA methylation was measured with the Infinium HumanMethylation450 BeadChip (Illumina). We examined epigenome-wide associations of maternal early-pregnancy serum ferritin and cord blood DNA methylation using robust linear regression analyses, with adjustment for confounders and performed fixed-effects meta-analyses. We additionally examined whether associations of any CpGs identified in cord blood persisted in the peripheral blood of older children and explored associations with other markers of maternal iron status. We also examined whether similar findings were present in the association of cord blood serum ferritin concentrations with cord blood DNA methylation.

RESULTS

Maternal early-pregnancy serum ferritin concentrations were inversely associated with DNA methylation at two CpGs (cg02806645 and cg06322988) in PRR23A and one CpG (cg04468817) in PRSS22. Associations at two of these CpG sites persisted at each of the follow-up time points in childhood. Cord blood serum ferritin concentrations were not associated with cord blood DNA methylation levels at the three identified CpGs.

CONCLUSION

Maternal early-pregnancy serum ferritin concentrations were associated with lower cord blood DNA methylation levels at three CpGs and these associations partly persisted in older children. Further studies are needed to uncover the role of these CpGs in the underlying mechanisms of the associations of maternal iron status and offspring health outcomes.

Placental multi-omics integration identifies candidate functional genes for birthweight

Abnormal birthweight is associated with increased risk for cardiometabolic diseases in later life. Although the placenta is critical to fetal development and later life health, it has not been integrated into largescale functional genomics initiatives, and mechanisms of birthweight-associated variants identified by genome wide association studies (GWAS) are unclear. The goal of this study is to provide functional mechanistic insight into the causal pathway from a genetic variant to birthweight by integrating placental methylation and gene expression with established GWAS loci for birthweight. We identify placental DNA methylation and gene expression targets for several birthweight GWAS loci. The target genes are broadly enriched in cardiometabolic, immune response, and hormonal pathways. We find that methylation causally influences WNT3A, CTDNEP1, and RANBP2 expression in placenta. Multi-trait colocalization identifies PLEKHA1, FES, CTDNEP1, and PRMT7 as likely functional effector genes. These findings reveal candidate functional pathways that underpin the genetic regulation of birthweight via placental epigenetic and transcriptomic mechanisms. Clinical trial registration; ClinicalTrials.gov, NCT00912132.

scDeconv: an R package to deconvolve bulk DNA methylation data with scRNA-seq data and paired bulk RNA-DNA methylation data

Many DNA methylation (DNAm) data are from tissues composed of various cell types, and hence cell deconvolution methods are needed to infer their cell compositions accurately. However, a bottleneck for DNAm data is the lack of cell-type-specific DNAm references. On the other hand, scRNA-seq data are being accumulated rapidly with various cell-type transcriptomic signatures characterized, and also, many paired bulk RNA-DNAm data are publicly available currently. Hence, we developed the R package scDeconv to use these resources to solve the reference deficiency problem of DNAm data and deconvolve them from scRNA-seq data in a trans-omics manner. It assumes that paired samples have similar cell compositions. So the cell content information deconvolved from the scRNA-seq and paired RNA data can be transferred to the paired DNAm samples. Then an ensemble model is trained to fit these cell contents with DNAm features and adjust the paired RNA deconvolution in a co-training manner. Finally, the model can be used on other bulk DNAm data to predict their relative cell-type abundances. The effectiveness of this method is proved by its accurate deconvolution on the three testing datasets here, and if given an appropriate paired dataset, scDeconv can also deconvolve other omics, such as ATAC-seq data. Furthermore, the package also contains other functions, such as identifying cell-type-specific inter-group differential features from bulk DNAm data. scDeconv is available at: https://github.com/yuabrahamliu/scDeconv.

Enhanced cell deconvolution of peripheral blood using DNA methylation for high-resolution immune profiling

DNA methylation microarrays can be employed to interrogate cell-type composition in complex tissues. Here, we expand reference-based deconvolution of blood DNA methylation to include 12 leukocyte subtypes (neutrophils, eosinophils, basophils, monocytes, naïve and memory B cells, naïve and memory CD4 + and CD8 + T cells, natural killer, and T regulatory cells). Including derived variables, our method provides 56 immune profile variables. The IDOL (IDentifying Optimal Libraries) algorithm was used to identify libraries for deconvolution of DNA methylation data for current and previous platforms. The accuracy of deconvolution estimates obtained using our enhanced libraries was validated using artificial mixtures and whole-blood DNA methylation with known cellular composition from flow cytometry. We applied our libraries to deconvolve cancer, aging, and autoimmune disease datasets. In conclusion, these libraries enable a detailed representation of immune-cell profiles in blood using only DNA and facilitate a standardized, thorough investigation of immune profiles in human health and disease.

Integrative analysis of 3604 GWAS reveals multiple novel cell type-specific regulatory associations

Background

Genome-wide association study (GWAS) single nucleotide polymorphisms (SNPs) are known to preferentially co-locate to active regulatory elements in tissues and cell types relevant to disease aetiology. Further characterisation of associated cell type-specific regulation can broaden our understanding of how GWAS signals may contribute to disease risk.

Results

To gain insight into potential functional mechanisms underlying GWAS associations, we developed FORGE2 (https://forge2.altiusinstitute.org/), which is an updated version of the FORGE web tool. FORGE2 uses an expanded atlas of cell type-specific regulatory element annotations, including DNase I hotspots, five histone mark categories and 15 hidden Markov model (HMM) chromatin states, to identify tissue- and cell type-specific signals. An analysis of 3,604 GWAS from the NHGRI-EBI GWAS catalogue yielded at least one significant disease/trait-tissue association for 2,057 GWAS, including > 400 associations specific to epigenomic marks in immune tissues and cell types, > 30 associations specific to heart tissue, and > 60 associations specific to brain tissue, highlighting the key potential of tissue- and cell type-specific regulatory elements. Importantly, we demonstrate that FORGE2 analysis can separate previously observed accessible chromatin enrichments into different chromatin states, such as enhancers or active transcription start sites, providing a greater understanding of underlying regulatory mechanisms. Interestingly, tissue-specific enrichments for repressive chromatin states and histone marks were also detected, suggesting a role for tissue-specific repressed regions in GWAS-mediated disease aetiology.

Conclusion

In summary, we demonstrate that FORGE2 has the potential to uncover previously unreported disease-tissue associations and identify new candidate mechanisms. FORGE2 is a transparent, user-friendly web tool for the integrative analysis of loci discovered from GWAS.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13059-021-02560-3.

Stochastic Epigenetic Mutations Influence Parkinson's Disease Risk, Progression, and Mortality

BACKGROUND

Stochastic epigenetic mutations (SEM) reflect a deviation from normal site-specific methylation patterns. Epigenetic mutation load (EML) captures the accumulation of SEMs across an individual's genome and may reflect dysfunction of the epigenetic maintenance system in response to epigenetic challenges.

OBJECTIVE

We investigate whether EML is associated with PD risk and time to events (i.e., death and motor symptom decline).

METHODS

We employed logistic regression and Cox proportional hazards regression to assess the association between EML and several outcomes. Our analyses are based on 568 PD patients and 238 controls from the Parkinson's disease, Environment and Genes (PEG) study, for whom blood-based methylation data was available.

RESULTS

We found an association for PD onset and EML in all genes (OR = 1.90; 95%CI 1.52-2.37) and PD-related genes (OR = 1.87; 95%CI 1.50-2.32). EML was also associated with time to a minimum score of 35 points on the motor UPDRS exam (OR = 1.28; 95%CI 1.06-1.56) and time to death (OR = 1.29, 95%CI 1.11-1.49). An analysis of PD related genes only revealed five intragenic hotspots of high SEM density associated with PD risk.

CONCLUSION

Our findings suggest an enrichment of methylation dysregulation in PD patients in general and specifically in five PD related genes. EML may also be associated with time to death and motor symptom progression in PD patients.

Genetic variation influencing DNA methylation provides insights into molecular mechanisms regulating genomic function

We determined the relationships between DNA sequence variation and DNA methylation using blood samples from 3,799 Europeans and 3,195 South Asians. We identify 11,165,559 SNP-CpG associations (methylation quantitative trait loci (meQTL), P < 10-14), including 467,915 meQTL that operate in trans. The meQTL are enriched for functionally relevant characteristics, including shared chromatin state, High-throuhgput chromosome conformation interaction, and association with gene expression, metabolic variation and clinical traits. We use molecular interaction and colocalization analyses to identify multiple nuclear regulatory pathways linking meQTL loci to phenotypic variation, including UBASH3B (body mass index), NFKBIE (rheumatoid arthritis), MGA (blood pressure) and COMMD7 (white cell counts). For rs6511961 , chromatin immunoprecipitation followed by sequencing (ChIP-seq) validates zinc finger protein (ZNF)333 as the likely trans acting effector protein. Finally, we used interaction analyses to identify population- and lineage-specific meQTL, including rs174548 in FADS1, with the strongest effect in CD8+ T cells, thus linking fatty acid metabolism with immune dysregulation and asthma. Our study advances understanding of the potential pathways linking genetic variation to human phenotype.

DNA Methylation Profiles of Purified Cell Types in Bronchoalveolar Lavage: Applications for Mixed Cell Paediatric Pulmonary Studies

In epigenome-wide association studies analysing DNA methylation from samples containing multiple cell types, it is essential to adjust the analysis for cell type composition. One well established strategy for achieving this is reference-based cell type deconvolution, which relies on knowledge of the DNA methylation profiles of purified constituent cell types. These are then used to estimate the cell type proportions of each sample, which can then be incorporated to adjust the association analysis. Bronchoalveolar lavage is commonly used to sample the lung in clinical practice and contains a mixture of different cell types that can vary in proportion across samples, affecting the overall methylation profile. A current barrier to the use of bronchoalveolar lavage in DNA methylation-based research is the lack of reference DNA methylation profiles for each of the constituent cell types, thus making reference-based cell composition estimation difficult. Herein, we use bronchoalveolar lavage samples collected from children with cystic fibrosis to define DNA methylation profiles for the four most common and clinically relevant cell types: alveolar macrophages, granulocytes, lymphocytes and alveolar epithelial cells. We then demonstrate the use of these methylation profiles in conjunction with an established reference-based methylation deconvolution method to estimate the cell type composition of two different tissue types; a publicly available dataset derived from artificial blood-based cell mixtures and further bronchoalveolar lavage samples. The reference DNA methylation profiles developed in this work can be used for future reference-based cell type composition estimation of bronchoalveolar lavage. This will facilitate the use of this tissue in studies examining the role of DNA methylation in lung health and disease.

DNA Methylation Signature in Monozygotic Twins Discordant for Psoriatic Disease

Background: Psoriatic disease is a multifactorial inflammatory condition spanning from skin and nail psoriasis (Pso) to spine and joint involvement characterizing psoriatic arthritis (PsA). Monozygotic twins provide a model to investigate genetic, early life environmental exposure and stochastic influences to complex diseases, mainly mediated by epigenetics.

Methods: We performed a genome-wide DNA methylation study on whole blood of monozygotic twins from 7 pairs discordant for Pso/PsA using the Infinium Methylation EPIC array (Illumina). MeDiP—qPCR was used to confirm specific signals. Data were replicated in an independent cohort of seven patients with Pso/PsA and 3 healthy controls. Transcriptomic profiling was performed by RNAsequence on the same 7 monozygotic twin pairs.

Results: We identified 2,564 differentially methylated positions between psoriatic disease and controls, corresponding to 1,703 genes, 59% within gene bodies. There were 19 regions with at least two DMPs within 1 kb of distance and significant within-pair Δβ-values (p < 0.005), among them SNX25, BRG1 and SMAD3 genes, all involved in TGF-β signaling pathway, were identified. Co-expression analyses on transcriptome data identified IL-6/JAK/STAT3 and TNF-α pathways as important signaling axes involved in the disease, and they also suggested an altered glucose metabolism in patients’ immune cells, characteristic of pro-inflammatory T lymphocytes.

Conclusion: The study suggests the presence of an epigenetic signature in affected individuals, pointing to genes involved in immunological and inflammatory responses. This result is also supported by transcriptome data, that altogether suggest a higher activation state of the immune system, that could promote the disease status.

Epigenome-wide association study of serum urate reveals insights into urate co-regulation and the SLC2A9 locus

Elevated serum urate levels, a complex trait and major risk factor for incident gout, are correlated with cardiometabolic traits via incompletely understood mechanisms. DNA methylation in whole blood captures genetic and environmental influences and is assessed in transethnic meta-analysis of epigenome-wide association studies (EWAS) of serum urate (discovery, n = 12,474, replication, n = 5522). The 100 replicated, epigenome-wide significant (p < 1.1E-7) CpGs explain 11.6% of the serum urate variance. At SLC2A9, the serum urate locus with the largest effect in genome-wide association studies (GWAS), five CpGs are associated with SLC2A9 gene expression. Four CpGs at SLC2A9 have significant causal effects on serum urate levels and/or gout, and two of these partly mediate the effects of urate-associated GWAS variants. In other genes, including SLC7A11 and PHGDH, 17 urate-associated CpGs are associated with conditions defining metabolic syndrome, suggesting that these CpGs may represent a blood DNA methylation signature of cardiometabolic risk factors. This study demonstrates that EWAS can provide new insights into GWAS loci and the correlation of serum urate with other complex traits.

Meta-analyses identify DNA methylation associated with kidney function and damage

Chronic kidney disease is a major public health burden. Elevated urinary albumin-to-creatinine ratio is a measure of kidney damage, and used to diagnose and stage chronic kidney disease. To extend the knowledge on regulatory mechanisms related to kidney function and disease, we conducted a blood-based epigenome-wide association study for estimated glomerular filtration rate (n = 33,605) and urinary albumin-to-creatinine ratio (n = 15,068) and detected 69 and seven CpG sites where DNA methylation was associated with the respective trait. The majority of these findings showed directionally consistent associations with the respective clinical outcomes chronic kidney disease and moderately increased albuminuria. Associations of DNA methylation with kidney function, such as CpGs at JAZF1, PELI1 and CHD2 were validated in kidney tissue. Methylation at PHRF1, LDB2, CSRNP1 and IRF5 indicated causal effects on kidney function. Enrichment analyses revealed pathways related to hemostasis and blood cell migration for estimated glomerular filtration rate, and immune cell activation and response for urinary albumin-to-creatinineratio-associated CpGs.

Ten Years of EWAS

Epigenome-wide association study (EWAS) has been applied to analyze DNA methylation variation in complex diseases for a decade, and epigenome as a research target has gradually become a hot topic of current studies. The DNA methylation microarrays, next-generation, and third-generation sequencing technologies have prepared a high-quality platform for EWAS. Here, the progress of EWAS research is reviewed, its contributions to clinical applications, and mainly describe the achievements of four typical diseases. Finally, the challenges encountered by EWAS and make bold predictions for its future development are presented.

Association of medically assisted reproduction with offspring cord blood DNA methylation across cohorts

STUDY QUESTION

Is cord blood DNA methylation associated with having been conceived by medically assisted reproduction?

SUMMARY ANSWER

This study does not provide strong evidence of an association of conception by medically assisted reproduction with variation in infant blood cell DNA methylation.

WHAT IS KNOWN ALREADY

Medically assisted reproduction consists of procedures used to help infertile/subfertile couples conceive, including ART. Due to its importance in gene regulation during early development programming, DNA methylation and its perturbations associated with medically assisted reproduction could reveal new insights into the biological effects of assisted reproductive technologies and potential adverse offspring outcomes.

STUDY DESIGN, SIZE, DURATION

We investigated the association of DNA methylation and medically assisted reproduction using a case–control study design (N = 205 medically assisted reproduction cases and N = 2439 naturally conceived controls in discovery cohorts; N = 149 ART cases and N = 58 non-ART controls in replication cohort).

PARTICIPANTS/MATERIALS, SETTINGS, METHODS

We assessed the association between medically assisted reproduction and DNA methylation at birth in cord blood (205 medically assisted conceptions and 2439 naturally conceived controls) at >450 000 CpG sites across the genome in two sub-samples of the UK Avon Longitudinal Study of Parents and Children (ALSPAC) and two sub-samples of the Norwegian Mother, Father and Child Cohort Study (MoBa) by meta-analysis. We explored replication of findings in the Australian Clinical review of the Health of adults conceived following Assisted Reproductive Technologies (CHART) study (N = 149 ART conceptions and N = 58 controls).

MAIN RESULTS AND THE ROLE OF CHANCE

The ALSPAC and MoBa meta-analysis revealed evidence of association between conception by medically assisted reproduction and DNA methylation (false-discovery-rate-corrected P-value < 0.05) at five CpG sites which are annotated to two genes (percentage difference in methylation per CpG, cg24051276: Beta = 0.23 (95% CI 0.15,0.31); cg00012522: Beta = 0.47 (95% CI 0.31, 0.63); cg17855264: Beta = 0.31 (95% CI 0.20, 0.43); cg17132421: Beta = 0.30 (95% CI 0.18, 0.42); cg18529845: Beta = 0.41 (95% CI 0.25, 0.57)). Methylation at three of these sites has been previously linked to cancer, aging, HIV infection and neurological diseases. None of these associations replicated in the CHART cohort. There was evidence of a functional role of medically assisted reproduction-induced hypermethylation at CpG sites located within regulatory regions as shown by putative transcription factor binding and chromatin remodelling.

LIMITATIONS, REASONS FOR CAUTIONS

While insufficient power is likely, heterogeneity in types of medically assisted reproduction procedures and between populations may also contribute. Larger studies might identify replicable variation in DNA methylation at birth due to medically assisted reproduction.

WIDER IMPLICATIONS OF THE FINDINGS

Newborns conceived with medically assisted procedures present with divergent DNA methylation in cord blood white cells. If these associations are true and causal, they might have long-term consequences for offspring health.

STUDY FUNDING/COMPETING INTERESTS(S)

This study has been supported by the US National Institute of Health (R01 DK10324), the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013)/ERC Grant agreement no. 669545, European Union’s Horizon 2020 research and innovation programme under Grant agreement no. 733206 (LifeCycle) and the NIHR Biomedical Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol. The UK Medical Research Council and Wellcome (Grant ref: 102215/2/13/2) and the University of Bristol provide core support for ALSPAC. Methylation data in the ALSPAC cohort were generated as part of the UK BBSRC funded (BB/I025751/1 and BB/I025263/1) Accessible Resource for Integrated Epigenomic Studies (ARIES, http://www.ariesepigenomics.org.uk). D.C., J.J., C.L.R. D.A.L and H.R.E. work in a Unit that is supported by the University of Bristol and the UK Medical Research Council (Grant nos. MC_UU_00011/1, MC_UU_00011/5 and MC_UU_00011/6). B.N. is supported by an NHMRC (Australia) Investigator Grant (1173314). ALSPAC GWAS data were generated by Sample Logistics and Genotyping Facilities at Wellcome Sanger Institute and LabCorp (Laboratory Corporation of America) using support from 23andMe. The Norwegian Mother, Father and Child Cohort Study is supported by the Norwegian Ministry of Health and Care Services and the Ministry of Education and Research, NIH/NIEHS (Contract no. N01-ES-75558), NIH/NINDS (Grant nos. (i) UO1 NS 047537-01 and (ii) UO1 NS 047537-06A1). For this work, MoBa 1 and 2 were supported by the Intramural Research Program of the NIH, National Institute of Environmental Health Sciences (Z01-ES-49019) and the Norwegian Research Council/BIOBANK (Grant no. 221097). This work was partly supported by the Research Council of Norway through its Centres of Excellence funding scheme, Project no. 262700.

D.A.L. has received support from national and international government and charity funders, as well as from Roche Diagnostics and Medtronic for research unrelated to this study. The other authors declare no conflicts of interest.

TRIAL REGISTRATION NUMBER

N/A.

A genome-wide study of DNA methylation in white blood cells and asthma in Latino children and youth

Latinos are heavily affected with childhood asthma. Little is known about epigenetic mechanisms of asthma in Latino youth. We conducted a meta-analysis of two epigenome-wide association studies (EWAS) of asthma, using DNA from white blood cells (WBCs) from 1,136 Latino children and youth aged 6 to 20 years. Genes near the top CpG sites in this EWAS were examined in a pathway enrichment analysis, and we then assessed whether our results replicated those from publicly available data from three independent EWAS conducted in non-Latino populations. We found that DNA methylation profiles differed between subjects with and without asthma. After adjustment for covariates and multiple testing, two CpGs were differentially methylated at a false discovery rate (FDR)-adjusted P < 0.1, and 193 CpG sites were differentially methylated at FDR-adjusted P < 0.2. The two top CpGs are near genes relevant to inflammatory signalling, including CAMK1D (Calcium/Calmodulin Dependent Protein Kinase ID) and TIGIT (T Cell Immunoreceptor With Ig And ITIM Domains). Moreover, 25 genomic regions were differentially methylated between subjects with and without asthma, at Šidák-corrected P < 0.10. An enrichment analysis then identified the TGF-beta pathway as most relevant to asthma in our analysis, and we replicated some of the top signals from publicly available EWAS datasets in non-Hispanic populations. In conclusion, we have identified novel epigenetic markers of asthma in WBCs from Latino children and youth, while also replicating previous results from studies conducted in non-Latinos.

Epigenome-wide association study of kidney function identifies trans-ethnic and ethnic-specific loci

BACKGROUND

DNA methylation (DNAm) is associated with gene regulation and estimated glomerular filtration rate (eGFR), a measure of kidney function. Decreased eGFR is more common among US Hispanics and African Americans. The causes for this are poorly understood. We aimed to identify trans-ethnic and ethnic-specific differentially methylated positions (DMPs) associated with eGFR using an agnostic, genome-wide approach.

METHODS

The study included up to 5428 participants from multi-ethnic studies for discovery and 8109 participants for replication. We tested the associations between whole blood DNAm and eGFR using beta values from Illumina 450K or EPIC arrays. Ethnicity-stratified analyses were performed using linear mixed models adjusting for age, sex, smoking, and study-specific and technical variables. Summary results were meta-analyzed within and across ethnicities. Findings were assessed using integrative epigenomics methods and pathway analyses.

RESULTS

We identified 93 DMPs associated with eGFR at an FDR of 0.05 and replicated 13 and 1 DMPs across independent samples in trans-ethnic and African American meta-analyses, respectively. The study also validated 6 previously published DMPs. Identified DMPs showed significant overlap enrichment with DNase I hypersensitive sites in kidney tissue, sites associated with the expression of proximal genes, and transcription factor motifs and pathways associated with kidney tissue and kidney development.

CONCLUSIONS

We uncovered trans-ethnic and ethnic-specific DMPs associated with eGFR, including DMPs enriched in regulatory elements in kidney tissue and pathways related to kidney development. These findings shed light on epigenetic mechanisms associated with kidney function, bridging the gap between population-specific eGFR-associated DNAm and tissue-specific regulatory context.

Prenatal lead exposure and cord blood DNA methylation in the Korean Exposome Study

BACKGROUND

Prenatal lead exposure has been reported to affect infant growth and nervous system development, as well as to influence DNA methylation. We conducted an epigenome-wide association study to identify associations between prenatal lead exposure and cord blood DNA methylation in Korean infants.

METHODS

Cord blood samples were assayed with the Illumina HumanMethylationEPIC BeadChip kits, and maternal blood lead levels during early and late pregnancy, as well as cord blood lead level, were measured. The association between CpG methylation and lead level was analyzed using the limma package, with adjusting for infant sex, maternal pre-pregnancy body mass index, and estimated leukocyte composition.

RESULTS

Among 364 blood samples (182 males and 182 females), those for which maternal and cord blood lead concentrations during early and later pregnancy was known were used for analysis. Maternal lead concentration in blood during early pregnancy was significantly associated with the methylation status of specific positions. After data stratification by infant sex, we found that, in males, the level of maternal blood lead was associated with 18 CpG sites during early pregnancy, and with one CpG site near the NBAS gene, during late pregnancy. In female samples, there was no significant association between DNA methylation and lead concentrations.

CONCLUSIONS

Prenatal lead exposure was associated with altered, gender-specific patterns of DNA methylation in Korean infants.

Epigenome-wide association study of whole blood gene expression in Framingham Heart Study participants provides molecular insight into the potential role of CHRNA5 in cigarette smoking-related lung diseases

Background

DNA methylation is a key epigenetic modification that can directly affect gene regulation. DNA methylation is highly influenced by environmental factors such as cigarette smoking, which is causally related to chronic obstructive pulmonary disease (COPD) and lung cancer. To date, there have been few large-scale, combined analyses of DNA methylation and gene expression and their interrelations with lung diseases.

Results

We performed an epigenome-wide association study of whole blood gene expression in ~ 6000 individuals from four cohorts. We discovered and replicated numerous CpGs associated with the expression of cis genes within 500 kb of each CpG, with 148 to 1,741 cis CpG-transcript pairs identified across cohorts. We found that the closer a CpG resided to a transcription start site, the larger its effect size, and that 36% of cis CpG-transcript pairs share the same causal genetic variant. Mendelian randomization analyses revealed that hypomethylation and lower expression of CHRNA5, which encodes a smoking-related nicotinic receptor, are causally linked to increased risk of COPD and lung cancer. This putatively causal relationship was further validated in lung tissue data.

Conclusions

Our results provide a large and comprehensive association study of whole blood DNA methylation with gene expression. Expression platform differences rather than population differences are critical to the replication of cis CpG-transcript pairs. The low reproducibility of trans CpG-transcript pairs suggests that DNA methylation regulates nearby rather than remote gene expression. The putatively causal roles of methylation and expression of CHRNA5 in relation to COPD and lung cancer provide evidence for a mechanistic link between patterns of smoking-related epigenetic variation and lung diseases, and highlight potential therapeutic targets for lung diseases and smoking cessation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-021-01041-5.

Epigenetic mutation load is weakly correlated with epigenetic age acceleration

DNA methylation (DNAm) age estimators are widely used to study aging-related conditions. It is not yet known whether DNAm age is associated with the accumulation of stochastic epigenetic mutations (SEMs), which reflect dysfunctions of the epigenetic maintenance system. Here, we defined epigenetic mutation load (EML) as the total number of SEMs per individual. We assessed associations between EML and DNAm age acceleration estimators using biweight midcorrelations in four population-based studies (total n = 6,388). EML was not only positively associated with chronological age (meta r = 0.171), but also with four measures of epigenetic age acceleration: the Horvath pan tissue clock, intrinsic epigenetic age acceleration, the Hannum clock, and the GrimAge clock (meta-analysis correlation ranging from r = 0.109 to 0.179). We further conducted pathway enrichment analyses for each participant's SEMs. The enrichment result demonstrated the stochasticity of epigenetic mutations, meanwhile implicated several pathways: signaling, neurogenesis, neurotransmitter, glucocorticoid, and circadian rhythm pathways may contribute to faster DNAm age acceleration. Finally, investigating genomic-region specific EML, we found that EMLs located within regions of transcriptional repression (TSS1500, TSS200, and 1stExon) were associated with faster age acceleration. Overall, our findings suggest a role for the accumulation of epigenetic mutations in the aging process.

A cell-type deconvolution meta-analysis of whole blood EWAS reveals lineage-specific smoking-associated DNA methylation changes

Highly reproducible smoking-associated DNA methylation changes in whole blood have been reported by many Epigenome-Wide-Association Studies (EWAS). These epigenetic alterations could have important implications for understanding and predicting the risk of smoking-related diseases. To this end, it is important to establish if these DNA methylation changes happen in all blood cell subtypes or if they are cell-type specific. Here, we apply a cell-type deconvolution algorithm to identify cell-type specific DNA methylation signals in seven large EWAS. We find that most of the highly reproducible smoking-associated hypomethylation signatures are more prominent in the myeloid lineage. A meta-analysis further identifies a myeloid-specific smoking-associated hypermethylation signature enriched for DNase Hypersensitive Sites in acute myeloid leukemia. These results may guide the design of future smoking EWAS and have important implications for our understanding of how smoking affects immune-cell subtypes and how this may influence the risk of smoking related diseases.

Smoking-associated DNA methylation changes in whole blood have been reported by many EWAS. Here, the authors use a cell-type deconvolution algorithm to identify cell-type specific DNA methylation signals in seven EWAS, identifying lineage-specific smoking-associated DNA methylation changes.

An integrative multi-omics analysis to identify candidate DNA methylation biomarkers related to prostate cancer risk

It remains elusive whether some of the associations identified in genome-wide association studies of prostate cancer (PrCa) may be due to regulatory effects of genetic variants on CpG sites, which may further influence expression of PrCa target genes. To search for CpG sites associated with PrCa risk, here we establish genetic models to predict methylation (N = 1,595) and conduct association analyses with PrCa risk (79,194 cases and 61,112 controls). We identify 759 CpG sites showing an association, including 15 located at novel loci. Among those 759 CpG sites, methylation of 42 is associated with expression of 28 adjacent genes. Among 22 genes, 18 show an association with PrCa risk. Overall, 25 CpG sites show consistent association directions for the methylation-gene expression-PrCa pathway. We identify DNA methylation biomarkers associated with PrCa, and our findings suggest that specific CpG sites may influence PrCa via regulating expression of candidate PrCa target genes.

eFORGE v2.0: updated analysis of cell type-specific signal in epigenomic data

SUMMARY

The Illumina Infinium EPIC BeadChip is a new high-throughput array for DNA methylation analysis, extending the earlier 450k array by over 400 000 new sites. Previously, a method named eFORGE was developed to provide insights into cell type-specific and cell-composition effects for 450k data. Here, we present a significantly updated and improved version of eFORGE that can analyze both EPIC and 450k array data. New features include analysis of chromatin states, transcription factor motifs and DNase I footprints, providing tools for epigenome-wide association study interpretation and epigenome editing.

AVAILABILITY AND IMPLEMENTATION

eFORGE v2.0 is implemented as a web tool available from https://eforge.altiusinstitute.org and https://eforge-tf.altiusinstitute.org/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Molecular networks in Network Medicine: Development and applications

Network Medicine applies network science approaches to investigate disease pathogenesis. Many different analytical methods have been used to infer relevant molecular networks, including protein-protein interaction networks, correlation-based networks, gene regulatory networks, and Bayesian networks. Network Medicine applies these integrated approaches to Omics Big Data (including genetics, epigenetics, transcriptomics, metabolomics, and proteomics) using computational biology tools and, thereby, has the potential to provide improvements in the diagnosis, prognosis, and treatment of complex diseases. We discuss briefly the types of molecular data that are used in molecular network analyses, survey the analytical methods for inferring molecular networks, and review efforts to validate and visualize molecular networks. Successful applications of molecular network analysis have been reported in pulmonary arterial hypertension, coronary heart disease, diabetes mellitus, chronic lung diseases, and drug development. Important knowledge gaps in Network Medicine include incompleteness of the molecular interactome, challenges in identifying key genes within genetic association regions, and limited applications to human diseases. This article is categorized under: Models of Systems Properties and Processes > Mechanistic Models Translational, Genomic, and Systems Medicine > Translational Medicine Analytical and Computational Methods > Analytical Methods Analytical and Computational Methods > Computational Methods.

Genetically Predicted Levels of DNA Methylation Biomarkers and Breast Cancer Risk: Data From 228 951 Women of European Descent

BACKGROUND

DNA methylation plays a critical role in breast cancer development. Previous studies have identified DNA methylation marks in white blood cells as promising biomarkers for breast cancer. However, these studies were limited by low statistical power and potential biases. Using a new methodology, we investigated DNA methylation marks for their associations with breast cancer risk.

METHODS

Statistical models were built to predict levels of DNA methylation marks using genetic data and DNA methylation data from HumanMethylation450 BeadChip from the Framingham Heart Study (n = 1595). The prediction models were validated using data from the Women's Health Initiative (n = 883). We applied these models to genomewide association study (GWAS) data of 122 977 breast cancer patients and 105 974 controls to evaluate if the genetically predicted DNA methylation levels at CpG sites (CpGs) are associated with breast cancer risk. All statistical tests were two-sided.

RESULTS

Of the 62 938 CpG sites CpGs investigated, statistically significant associations with breast cancer risk were observed for 450 CpGs at a Bonferroni-corrected threshold of P less than 7.94 × 10-7, including 45 CpGs residing in 18 genomic regions, that have not previously been associated with breast cancer risk. Of the remaining 405 CpGs located within 500 kilobase flaking regions of 70 GWAS-identified breast cancer risk variants, the associations for 11 CpGs were independent of GWAS-identified variants. Integrative analyses of genetic, DNA methylation, and gene expression data found that 38 CpGs may affect breast cancer risk through regulating expression of 21 genes.

CONCLUSION

Our new methodology can identify novel DNA methylation biomarkers for breast cancer risk and can be applied to other diseases.

The Promises and Challenges of Toxico-Epigenomics: Environmental Chemicals and Their Impacts on the Epigenome

BACKGROUND

It has been estimated that a substantial portion of chronic and noncommunicable diseases can be caused or exacerbated by exposure to environmental chemicals. Multiple lines of evidence indicate that early life exposure to environmental chemicals at relatively low concentrations could have lasting effects on individual and population health. Although the potential adverse effects of environmental chemicals are known to the scientific community, regulatory agencies, and the public, little is known about the mechanistic basis by which these chemicals can induce long-term or transgenerational effects. To address this question, epigenetic mechanisms have emerged as the potential link between genetic and environmental factors of health and disease.

OBJECTIVES

We present an overview of epigenetic regulation and a summary of reported evidence of environmental toxicants as epigenetic disruptors. We also discuss the advantages and challenges of using epigenetic biomarkers as an indicator of toxicant exposure, using measures that can be taken to improve risk assessment, and our perspectives on the future role of epigenetics in toxicology.

DISCUSSION

Until recently, efforts to apply epigenomic data in toxicology and risk assessment were restricted by an incomplete understanding of epigenomic variability across tissue types and populations. This is poised to change with the development of new tools and concerted efforts by researchers across disciplines that have led to a better understanding of epigenetic mechanisms and comprehensive maps of epigenomic variation. With the foundations now in place, we foresee that unprecedented advancements will take place in the field in the coming years. https://doi.org/10.1289/EHP6104.

The role of epigenetics in the development of childhood asthma

Introduction: The development of childhood asthma is caused by a combination of genetic factors and environmental exposures. Epigenetics describes mechanisms of (heritable) regulation of gene expression that occur without changes in DNA sequence. Epigenetics is strongly related to aging, is cell-type specific, and includes DNA methylation, noncoding RNAs, and histone modifications.Areas covered: This review summarizes recent epigenetic studies of childhood asthma in humans, which mostly involve studies of DNA methylation published in the recent five years. Environmental exposures, in particular cigarette smoking, have significant impact on epigenetic changes, but few of these epigenetic signals are also associated with asthma. Several asthma-associated genetic variants relate to DNA methylation. Epigenetic signals can be better understood by studying their correlation with gene expression, which revealed higher presence and activation of blood eosinophils in asthma. Strong associations of nasal methylation signatures and atopic asthma were identified, which were replicable across different populations.Expert commentary: Epigenetic markers have been strongly associated with asthma, and might serve as biomarker of asthma. The causal and longitudinal relationships between epigenetics and disease, and between environmental exposures and epigenetic changes need to be further investigated. Efforts should be made to understand cell-type-specific epigenetic mechanisms in asthma.

The epiGenomic Efficient Correlator (epiGeEC) tool allows fast comparison of user datasets with thousands of public epigenomic datasets

Summary

In recent years, major initiatives such as the International Human Epigenome Consortium have generated thousands of high-quality genome-wide datasets for a large variety of assays and cell types. This data can be used as a reference to assess whether the signal from a user-provided dataset corresponds to its expected experiment, as well as to help reveal unexpected biological associations. We have developed the epiGenomic Efficient Correlator (epiGeEC) tool to enable genome-wide comparisons of very large numbers of datasets. A public Galaxy implementation of epiGeEC allows comparison of user datasets with thousands of public datasets in a few minutes.

Availability and implementation

The source code is available at https://bitbucket.org/labjacquespe/epigeec and the Galaxy implementation at http://epigeec.genap.ca.

Supplementary information

Supplementary data are available at Bioinformatics online.

Methylome-wide association study provides evidence of particulate matter air pollution-associated DNA methylation

BACKGROUND

DNA methylation (DNAm) may contribute to processes that underlie associations between air pollution and poor health. Therefore, our objective was to evaluate associations between DNAm and ambient concentrations of particulate matter (PM) ≤2.5, ≤10, and 2.5-10 μm in diameter (PM2.5; PM10; PM2.5-10).

METHODS

We conducted a methylome-wide association study among twelve cohort- and race/ethnicity-stratified subpopulations from the Women's Health Initiative and the Atherosclerosis Risk in Communities study (n = 8397; mean age: 61.5 years; 83% female; 45% African American; 9% Hispanic/Latino American). We averaged geocoded address-specific estimates of daily and monthly mean PM concentrations over 2, 7, 28, and 365 days and 1 and 12 months before exams at which we measured leukocyte DNAm in whole blood. We estimated subpopulation-specific, DNAm-PM associations at approximately 485,000 Cytosine-phosphate-Guanine (CpG) sites in multi-level, linear, mixed-effects models. We combined subpopulation- and site-specific estimates in fixed-effects, inverse variance-weighted meta-analyses, then for associations that exceeded methylome-wide significance and were not heterogeneous across subpopulations (P < 1.0 × 10-7; PCochran's Q > 0.10), we characterized associations using publicly accessible genomic databases and attempted replication in the Cooperative Health Research in the Region of Augsburg (KORA) study.

RESULTS

Analyses identified significant DNAm-PM associations at three CpG sites. Twenty-eight-day mean PM10 was positively associated with DNAm at cg19004594 (chromosome 20; MATN4; P = 3.33 × 10-8). One-month mean PM10 and PM2.5-10 were positively associated with DNAm at cg24102420 (chromosome 10; ARPP21; P = 5.84 × 10-8) and inversely associated with DNAm at cg12124767 (chromosome 7; CFTR; P = 9.86 × 10-8). The PM-sensitive CpG sites mapped to neurological, pulmonary, endocrine, and cardiovascular disease-related genes, but DNAm at those sites was not associated with gene expression in blood cells and did not replicate in KORA.

CONCLUSIONS

Ambient PM concentrations were associated with DNAm at genomic regions potentially related to poor health among racially, ethnically and environmentally diverse populations of U.S. women and men. Further investigation is warranted to uncover mechanisms through which PM-induced epigenomic changes may cause disease.

DNA methylation modules associate with incident cardiovascular disease and cumulative risk factor exposure

BACKGROUND

Epigenome-wide association studies using DNA methylation have the potential to uncover novel biomarkers and mechanisms of cardiovascular disease (CVD) risk. However, the direction of causation for these associations is not always clear, and investigations to-date have often failed to replicate at the level of individual loci.

METHODS

Here, we undertook module- and region-based DNA methylation analyses of incident CVD in the Women's Health Initiative (WHI) and Framingham Heart Study Offspring Cohort (FHS) in order to find more robust epigenetic biomarkers for cardiovascular risk. We applied weighted gene correlation network analysis (WGCNA) and the Comb-p algorithm to find methylation modules and regions associated with incident CVD in the WHI dataset.

RESULTS

We discovered two modules whose activation correlated with CVD risk and replicated across cohorts. One of these modules was enriched for development-related processes and overlaps strongly with epigenetic aging sites. For the other, we showed preliminary evidence for monocyte-specific effects and statistical links to cumulative exposure to traditional cardiovascular risk factors. Additionally, we found three regions (associated with the genes SLC9A1, SLC1A5, and TNRC6C) whose methylation associates with CVD risk.

CONCLUSIONS

In sum, we present several epigenetic associations with incident CVD which reveal disease mechanisms related to development and monocyte biology. Furthermore, we show that epigenetic modules may act as a molecular readout of cumulative cardiovascular risk factor exposure, with implications for the improvement of clinical risk prediction.