Identifying the effects of genetic variation on the epigenome in disease-relevant cell types can help advance our understanding of the first molecular contributions of genetic susceptibility to disease onset. Here, we establish a genome-wide map of DNA methylation quantitative trait loci in CD4+ T-cells isolated from multiple sclerosis patients. Utilizing this map in a colocalization analysis, we identify 19 loci where the same haplotype drives both multiple sclerosis susceptibility and local DNA methylation. We also identify two distant methylation effects of multiple sclerosis susceptibility loci: a chromosome 16 locus affects PRDM8 methylation (a chromosome 4 region not previously associated with multiple sclerosis), and the aggregate effect of multiple sclerosis-associated variants in the major histocompatibility complex influences DNA methylation near PRKCA (chromosome 17). Overall, we present a new resource for a key cell type in inflammatory disease research and uncover new gene targets for the study of predisposition to multiple sclerosis.
Digital Object Identifier (DOI)
The study was funded by a grant to PLD from the Massachusetts Life Sciences Center.
The genotyping and DNA methylation data from our MS CD4+ T cell dataset have been deposited in the Synapse database under accession codes syn26340457 [https://doi.org/10.7303/syn26340457] and syn26339303 [https://doi.org/10.7303/syn26339303], respectively. As sensitive human data, these data can be accessed upon request, following the establishment of a Data Use Agreement with the Brigham and Women’s Hospital. The initial request can be sent to the corresponding author, and the applicants will be contacted within a week. The complete set of summary statistics from the cis-mQTL analysis are available for download from the Synapse database under accession code syn26339302 [https://doi.org/10.7303/syn26339302]. The genome-wide significant cis-mQTL effects can be found in Supplementary Data 1. Data from the Genetics of Lipid-lowering Drugs and Diet Network (GOLDN) study used for the cis-mQTL replication analyses can be obtained from dbGaP under accession code phs000741.v2.p1 [https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000741.v2.p1]. BLUEPRINT Epigenome Project’s9 publicly available cis-mQTL summary statistics were downloaded from ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/. BLUEPRINT genetic data were accessed from the European Genome-phenome Archive under accession code EGAD00001002663.
Roostaei, Tina; Klein, Hans-Ulrich; Ma, Yiyi; Felsky, Daniel; Kivisäkk, Pia; Connor, Sarah M.; Kroshilina, Alexandra; Yung, Christina; Kaskow, Belinda J.; Shao, Xiaorong; Rhead, Brooke; Ordovás, José M.; Absher, Devin M.; Arnett, Donna K.; Liu, Jia; Patsopoulos, Nikolaos; Barcellos, Lisa F.; Weiner, Howard L.; and De Jager, Philip L., "Proximal and Distal Effects of Genetic Susceptibility to Multiple Sclerosis on the T Cell Epigenome" (2021). Epidemiology and Environmental Health Faculty Publications. 87.
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Description of additional supplementary files
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