Journal of AutoimmunityBioinformaticsPeer-reviewed journal article
Evidence for a potential role of miR-1908-5p and miR-3614-5p in autoimmune disease risk using genome-wide analyses
Abstract
Genome-wide association studies (GWAS) have identified a large number of genetic risk loci for autoimmune diseases. However, the functional variants underlying these disease associations remain largely unknown. There is evidence that microRNA-mediated regulation may play an important role in this context. Therefore, we assessed whether autoimmune disease loci unfold their effects via altering microRNA expression in relevant immune cells.\n\nTo this end, we performed microRNA expression quantitative trait loci (eQTL) analyses across 115 GWAS regions associated with 12 autoimmune diseases using next-generation sequencing data of 345 lymphoblastoid cell lines. Statistical analyses included the application and extension of a recently proposed framework (joint likelihood mapping), to microRNA expression data and microRNA target gene enrichment analyses of relevant GWAS data.\n\nOverall, only a minority of autoimmune disease risk loci may exert their pathophysiologic effects by altering miRNA expression based on JLIM. However, detailed functional fine-mapping revealed two independent GWAS regions harboring autoimmune disease risk SNPs with significant effects on microRNA expression. These relate to SNPs associated with Crohns disease (CD; rs102275) and rheumatoid arthritis (RA; rs968567), which affect the expression of miR-1908-5p (prs102275=1.44e-20, prs968567=2.54e-14). In addition, an independent CD risk SNP, rs3853824, was found to alter the expression of miR-3614-5p (p=5.70e-7). To support these findings, we demonstrate that GWAS signals for RA and CD were enriched in genes predicted to be targeted by both miRNAs (all with p<0.05).\n\nIn summary, our study points towards a pathophysiological role of miR-1908-5p and miR- 3614-5p in autoimmunity.
- organism: human
- assay: GWAS summary statistics
- research focus: fine-mapping
- approach: statistical model
- Citations
- 25
- FWCI
- 1.69
- Field percentile
- top 16%
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