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Functional Relevance for Associations between Genetic Variants and Systemic Lupus Erythematosus
Authors:Fei-Yan Deng  Shu-Feng Lei  Yong-Hong Zhang  Zeng-Li Zhang  Yu-Fan Guo
Affiliation:1. Center for Genetic Epidemiology and Genomics, Soochow University, Suzhou, Jiangsu, P. R. China.; 2. Department of Epidemiology, School of Public Health, Soochow University, Suzhou, Jiangsu, P. R. China.; 3. Department of Rheumatology, the First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, P. R. China.; University of Michigan Medical School, United States of America,
Abstract:Systemic lupus erythematosus (SLE) is a serious prototype autoimmune disease characterized by chronic inflammation, auto-antibody production and multi-organ damage. Recent association studies have identified a long list of loci that were associated with SLE with relatively high statistical power. However, most of them only established the statistical associations of genetic markers and SLE at the DNA level without supporting evidence of functional relevance. Here, using publically available datasets, we performed integrative analyses (gene relationship across implicated loci analysis, differential gene expression analysis and functional annotation clustering analysis) and combined with expression quantitative trait loci (eQTLs) results to dissect functional mechanisms underlying the associations for SLE. We found that 14 SNPs, which were significantly associated with SLE in previous studies, have cis-regulation effects on four eQTL genes (HLA-DQA1, HLA-DQB1, HLA-DQB2, and IRF5) that were also differentially expressed in SLE-related cell groups. The functional evidence, taken together, suggested the functional mechanisms underlying the associations of 14 SNPs and SLE. The study may serve as an example of mining publically available datasets and results in validation of significant disease-association results. Utilization of public data resources for integrative analyses may provide novel insights into the molecular genetic mechanisms underlying human diseases.
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