Genome-wide identification of genes regulating DNA methylation using genetic anchors for causal inference

BACKGROUND: DNA methylation is a key epigenetic modification in human development and disease, yet there is limited understanding of its highly coordinated regulation. Here, we identify 818 genes that affect DNA methylation patterns in blood using large-scale population genomics data. RESULTS: By employing genetic instruments as causal anchors, we establish directed associations between gene expression and distant DNA methylation levels, while ensuring specificity of the associations by correcting for linkage disequilibrium and pleiotropy among neighboring genes. The identified genes are enriched for transcription factors, of which many consistently increased or decreased DNA methylation levels at multiple CpG sites. In addition, we show that a substantial number of transcription factors affected DNA methylation at their experimentally determined binding sites. We also observe genes encoding proteins with heterogenous functions that have widespread effects on DNA methylation, e.g., NFKBIE, CDCA7(L), and NLRC5, and for several examples, we suggest plausible mechanisms underlying their effect on DNA methylation. CONCLUSION: We report hundreds of genes that affect DNA methylation and provide key insights in the principles underlying epigenetic regulation

Autosomal genetic variation is associated with DNA methylation in regions variably escaping X-chromosome inactivation

This is the final version of the article. Available from Springer Nature via the DOI in this record.Raw data were submitted to the European Genome-phenome Archive (EGA) under accession EGAS00001001077.X-chromosome inactivation (XCI), i.e., the inactivation of one of the female X chromosomes, restores equal expression of X-chromosomal genes between females and males. However, ~10% of genes show variable degrees of escape from XCI between females, although little is known about the causes of variable XCI. Using a discovery data-set of 1867 females and 1398 males and a replication sample of 3351 females, we show that genetic variation at three autosomal loci is associated with female-specific changes in X-chromosome methylation. Through cis-eQTL expression analysis, we map these loci to the genes SMCHD1/METTL4, TRIM6/HBG2, and ZSCAN9. Low-expression alleles of the loci are predominantly associated with mild hypomethylation of CpG islands near genes known to variably escape XCI, implicating the autosomal genes in variable XCI. Together, these results suggest a genetic basis for variable escape from XCI and highlight the potential of a population genomics approach to identify genes involved in XCI.This research was financially supported by several institutions: BBMRI-NL, a Research Infrastructure financed by the Dutch government (NWO, numbers 184.021.007 and 184.033.111); the UK Medical Research Council; Wellcome (www.wellcome.ac.uk; [grant number 102215/2/13/2 to ALSPAC]); the University of Bristol to ALSPAC; the UK Economic and Social Research Council (www.esrc.ac.uk; [ES/N000498/1] to CR); the UK Medical Research Council (www.mrc.ac.uk; grant numbers [MC_UU_12013/1, MC_UU_12013/2 to JLM, CR]); the Helmholtz Zentrum München – German Research Center for Environmental Health, which is funded by the German Federal Ministry of Education and Research (BMBF) and by the State of Bavaria; the Munich Center of Health Sciences (MC-Health), Ludwig-Maximilians-Universität, as part of LMUinnovativ; the Wellcome Trust, Medical Research Council, European Union (EU), and the National Institute for Health Research (NIHR)- funded BioResource, Clinical Research Facility, and Biomedical Research Centre based at Guy’s and St Thomas’ NHS Foundation Trust in partnership with King’s College London

Genome-wide identification of genes regulating DNA methylation using genetic anchors for causal inference

Background DNA methylation is a key epigenetic modification in human development and disease, yet there is limited understanding of its highly coordinated regulation. Here, we identify 818 genes that affect DNA methylation patterns in blood using large-scale population genomics data. Results By employing genetic instruments as causal anchors, we establish directed associations between gene expression and distant DNA methylation levels, while ensuring specificity of the associations by correcting for linkage disequilibrium and pleiotropy among neighboring genes. The identified genes are enriched for transcription factors, of which many consistently increased or decreased DNA methylation levels at multiple CpG sites. In addition, we show that a substantial number of transcription factors affected DNA methylation at their experimentally determined binding sites. We also observe genes encoding proteins with heterogenous functions that have widespread effects on DNA methylation, e.g.,NFKBIE,CDCA7(L), andNLRC5, and for several examples, we suggest plausible mechanisms underlying their effect on DNA methylation. Conclusion We report hundreds of genes that affect DNA methylation and provide key insights in the principles underlying epigenetic regulation.Development and application of statistical models for medical scientific researc

Age-related accrual of methylomic variability is linked to fundamental ageing mechanisms

Background: Epigenetic change is a hallmark of ageing but its link to ageing mechanisms in humans remains poorly understood. While DNA methylation at many CpG sites closely tracks chronological age, DNA methylation changes relevant to biological age are expected to gradually dissociate from chronological age, mirroring the increased heterogeneity in health status at older ages. Results: Here, we report on the large-scale identification of 6366 age-related variably methylated positions (aVMPs) identified in 3295 whole blood DNA methylation profiles, 2044 of which have a matching RNA-seq gene expression profile. aVMPs are enriched at polycomb repressed regions and, accordingly, methylation at those positions is associated with the expression of genes encoding components of polycomb repressive complex 2 (PRC2) in trans. Further analysis revealed trans-associations for 1816 aVMPs with an additional 854 genes. These trans-associated aVMPs are characterized by either an age-related

Systems genomics analysis of complex cognitive traits

The study of the genetic underpinnings of human cognitive traits is deemed an important tool to increase our understanding of molecular processes related to physiological and pathological cognitive functioning. The polygenic architecture of such complex traits implies that multiple naturally occurring genetic variations, each of small effect size, are likely to influence jointly the biological processes underlying cognitive ability. Genetic association results are yet devoid of biological context, thus limiting both the identification and functional interpretation of susceptibility variants. This biological gap can be reduced by the integrative analysis of intermediate molecular traits, as mediators of genomic action. In this thesis, I present results from two such systems genomics analyses, as attempts to identify molecular patterns underlying cognitive trait variability. In the first study, we adopted a system-level approach to investigate the relationship between global age-related patterns of epigenetic variation and cortical thickness, a brain morphometric measure that is linked to cognitive functioning. The integration of both genome-wide methylomic and genetic profiles allowed the identification of a peripheral molecular signature that showed association with both cortical thickness and episodic memory performance. In the second study, we explicitly modeled the interdependencies between local genetic markers and peripherally measured epigenetic variations. We thus generated robust estimators of epigenetic regulation and showed that these estimators resulted in the identification of epigenetic underpinnings of schizophrenia, a common genetically complex disorder. These results underscore the potential of systems genomics approaches, capitalizing on the integration of high-dimensional multi-layered molecular data, for the study of brain- related complex traits

Characterising lymphocyte mediated mechanisms of genetic risk in rheumatoid arthritis

Ph. D. ThesisRheumatoid arthritis (RA) is an immune-mediated inflammatory disease of the synovial joints with a global prevalence of 1%, causing pain, work instability and disability. The condition’s genetic aetiology is complex, and genome-wide association studies have highlighted over 100 susceptibility loci. The vast majority of implicated variants are noncoding, posing a major challenge in defining genetic mechanisms of cell-mediated immune dysregulation. The precise contribution to this process of epigenetic factors at a cellular level, such as the addition of methyl groups to DNA, also remains to be deciphered. By conducting comprehensive molecular profiling of circulating immune cells from early arthritis patients, my project aimed to elucidate mechanisms of genetic risk and prioritise causal disease genes in RA. To address this, genomewide DNA methylation, transcriptome and genotype data were available from peripheral blood CD4+ T cells and B cells of treatment-naïve early arthritis patients. Firstly, a comparison of DNA methylation between patients with early RA and those with other arthropathies was undertaken. Subsequently, the capacity of RA-associated variants to influence DNA methylation by mapping methylation quantitative trait loci (meQTLs) was confirmed. Here, it was observed that disease variants preferentially modified DNA methylation at sites mapping to lymphocyte enhancers and regions flanking transcription start sites, as well as positions bound by the NFκB transcription factor. By integrating transcriptomic data and employing a statistical approach to infer causality, loci were identified at which genetically conferred modifications in DNA methylation regulate transcription of genes including FCRL3, ANKRD55, IL6ST, and JAZF1 in CD4+ T cells. Finally, in vitro assays were used to validate meQTLs at loci of interest, and to confirm regulatory mechanisms. This work highlights genes and pathways of potential relevance to lymphocyte-mediated pathology in early RA and, potentially, other immune mediated diseases. It has implications for the functional interpretation of genome/epigenome-wide association studies.JGW Patterson Foundatio