Abstract
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.
Highlights
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
We found lower than expected number of mCpGs in transcription start sites (TSS), transcribed regions, and CpG islands
We provide a new resource: a genome-wide cis-methylation QTL (mQTL) map for primary CD4+ T cells which is more extensive than the existing map due to a greater number of DNA methylation sites being assessed
Summary
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. We establish a genome-wide map of DNA methylation quantitative trait loci in CD4+ T-cells isolated from multiple sclerosis patients. We (1) provide a genome-wide cis- DNA methylation QTL (mQTL) map of CD4+ T cells in MS patients, which can be utilized in future studies of MS and other inflammatory diseases, (2) identify cis- effects of MS genetic susceptibility variants on nearby CpG dinucleotide methylation, (3) discover and validate a trans-mQTL effect of an MS variant, and (4) demonstrate that polygenic scores of MS susceptibility influence DNA methylation at specific CpG dinucleotides and suggest the convergence of the effects of multiple variants on methylation levels in distal CpG sites
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