Methylation Notes

1 EWAS Reference Sources

• EWAS Open Platform: maintained by Beijing Institute of Genomics and supported by the Chinese Academy of Sciences, provides three resources:

  • EWAS Atlas: aggregated knowledgebase of epigenome-wide association studies, across multiple tissue/trait/cohorts

  • EWAS Data Hub: data hub of DNA methylation array data and metadata

  • EWAS Toolkit: online resource for EWAS annotation

• MRC-IEU EWAS Catalog: developed and is maintained by the Integrative Epidemiology Unit (IEU) at the University of Bristol

  • Summary data used for web interface can be found at Zenodo

• EpiSCOREDNAm-atlas: Reference DNA methylation profiles in multiple tissues for cell-type deconvolution.

2 Methylation-QTL/eQTM References

• BIOS QTL browser: Reference data for cis-meQTL and cis-eQTMs detected at FDR < 0.05, maintained by Dr. Lude Franke at University of Groningen in the Netherlands

• Biobank-BIOS Consortium: meQTL data for 27,720 Illumina 450K arrays retrieved from GEO. See Methylation data for 27,720 Illumina 450K arrays retrieved from GEO

• mQTLdb: mQTL database based on single UK cohort: “Large-scale genome-wide DNA methylation analysis of 1,000 mother-child pairs at serial time points across the life-course (ARIES)”“, maintained by MRC-IEU at University of Bristol

• GoDMC Database: Database of DNA methylation quantitative trait loci (mQTL) in a large set of samples, developed and maintained by Genetics of DNA Methylation Consortium across several European universities (Exeter, Bristol, Kings College London, Leiden), website is occationally down

  • Genomic and phenotypic insights from an atlas of genetic effects on DNA methylation, Nature Genetics, 2021

• eQTM-Catalog: eQTM database developed using GTEx and other public data resources. Created and maintained by Aditya Sriram, currently at University of Pittsburgh.

• Human Kidney meQTL Atlas: Summary Statistics of Human Kidney meQTLs and eQTMs by Susztak Lab at UPenn

• EPIGEN MeQTL Database: The EPIGEN MeQTL Database compiles results from multiple meQTL studies conducted by the Epigenomics Research Group at the Department of Twin Research at King’s College London, under the leadership of Dr Jordana Bell.

• GTEx cis-mQTLs: Characterization of multi-tissue DNA methylation and DNA methylation local quantitative trait loci (cis mQTLs) datasets based on 987 GTEx samples derived from 9 tissues: breast mammary tissue, colon transverse, kidney cortex, lung, muscle skeletal, ovary, prostate, testis and whole blood. Methods and dataset information are described in http://dx.doi.org/10.1038/s41588-022-01248-z, including preprocessing, filtering, normalization and mQTL mapping steps. For additional GTEx sample metadata, consult DOI:10.1126/science.aaz1776.

• Framingham Heart Study EWAS: Expression quantitative trait methylation (eQTM) analysis identifies DNA CpG sites at which methylation is associated with gene expression. The present study describes an eQTM resource of CpG-transcript pairs derived from whole blood DNA methylation and RNA sequencing gene expression data in 2115 Framingham Heart Study participants. We identified 70,047 significant cis CpG-transcript pairs at p < 1E−7 where the top most significant eGenes (i.e., gene transcripts associated with a CpG) were enriched in biological pathways related to cell signaling, and for 1208 clinical traits (enrichment false discovery rate [FDR] ≤ 0.05). We also identified 246,667 significant trans CpG-transcript pairs at p < 1E−14 where the top most significant eGenes were enriched in biological pathways related to activation of the immune response, and for 1191 clinical traits (enrichment FDR ≤ 0.05). Independent and external replication of the top 1000 significant cis and trans CpG-transcript pairs was completed in the Women’s Health Initiative and Jackson Heart Study cohorts. Using significant cis CpG-transcript pairs, we identified significant mediation of the association between CpG sites and cardiometabolic traits through gene expression and identified shared genetic regulation between CpGs and transcripts associated with cardiometabolic traits. In conclusion, we developed a robust and powerful resource of whole blood eQTM CpG-transcript pairs that can help inform future functional studies that seek to understand the molecular basis of disease.

3 Other Resources

• IHEC Data Portal: The International Human Epigenome Consortium (IHEC) provides comprehensive sets of reference epigenomes relevant to health and disease. This IHEC Data Portal can be used to view, search and download the data already released by the different IHEC-associated projects. The main IHEC website describes the consortium’s goals and research. Primarily dense methylation data from Whole Genome or Reduced Representation Bisulfite Sequencing.