Functional Relevance for Associations between Genetic Variants and Systemic Lupus Erythematosus

被引:11
|
作者
Deng, Fei-Yan [1 ]
Lei, Shu-Feng [1 ,2 ]
Zhang, Yong-Hong [1 ,2 ]
Zhang, Zeng-Li [1 ]
Guo, Yu-Fan [3 ]
机构
[1] Soochow Univ, Ctr Genet Epidemiol & Genom, Suzhou, Jiangsu, Peoples R China
[2] Soochow Univ, Sch Publ Hlth, Dept Epidemiol, Suzhou, Jiangsu, Peoples R China
[3] Soochow Univ, Dept Rheumatol, Affiliated Hosp 1, Suzhou, Jiangsu, Peoples R China
来源
PLOS ONE | 2013年 / 8卷 / 01期
基金
加拿大健康研究院;
关键词
GENOME-WIDE ASSOCIATION; INCREASED RISK; IRF5; GENE; POPULATION; EXPRESSION; SUSCEPTIBILITY; AGGREGATION; HAPLOTYPE; CHINESE; ITGAM;
D O I
10.1371/journal.pone.0053037
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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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页数:7
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