Risk variants disrupting enhancers of TH1 and TREG cells in type 1 diabetes

Significance Functional interpretation of noncoding genetic variants identified by genome-wide association studies is a major challenge in human genetics and gene regulation. We generated epigenomics data using primary cells from type 1 diabetes patients. Using these data, we identified and validated multiple novel risk variants for this disease. In addition, our ranked list of candidate risk SNPs represents the most comprehensive annotation based on T1D-specific T-cell data. Because many autoimmune diseases share some genetic underpinnings, our dataset may be used to understand causal noncoding mutations in related autoimmune diseases. Genome-wide association studies (GWASs) have revealed 59 genomic loci associated with type 1 diabetes (T1D). Functional interpretation of the SNPs located in the noncoding region of these loci remains challenging. We perform epigenomic profiling of two enhancer marks, H3K4me1 and H3K27ac, using primary TH1 and TREG cells isolated from healthy and T1D subjects. We uncover a large number of deregulated enhancers and altered transcriptional circuitries in both cell types of T1D patients. We identify four SNPs (rs10772119, rs10772120, rs3176792, rs883868) in linkage disequilibrium (LD) with T1D-associated GWAS lead SNPs that alter enhancer activity and expression of immune genes. Among them, rs10772119 and rs883868 disrupt the binding of retinoic acid receptor α (RARA) and Yin and Yang 1 (YY1), respectively. Loss of binding by YY1 also results in the loss of long-range enhancer–promoter interaction. These findings provide insights into how noncoding variants affect the transcriptomes of two T-cell subtypes that play critical roles in T1D pathogenesis.

• Publication year

  2019

• Venue

  Proceedings of the National Academy of Sciences of the United States of America

• Publication date

  2019-03-25

• Fields of study

  Biology, Medicine

• Identifiers
  DOI 10.1073/pnas.1815336116PMID 30910956PMCID 6462079
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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