Center for Genetic Epidemiology and Genomics, Soochow University, Suzhou, Jiangsu, PR China.
PLoS One. 2013;8(1):e53037. doi: 10.1371/journal.pone.0053037. Epub 2013 Jan 14.
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.
系统性红斑狼疮(SLE)是一种严重的自身免疫性疾病原型,其特征为慢性炎症、自身抗体产生和多器官损伤。最近的关联研究已经确定了一长串与 SLE 相关的基因座,这些基因座具有相对较高的统计功效。然而,其中大多数只是在 DNA 水平上建立了遗传标记与 SLE 的统计关联,而没有支持功能相关性的证据。在这里,我们使用公开可用的数据集进行综合分析(跨受累基因座的基因关系分析、差异基因表达分析和功能注释聚类分析),并结合表达数量性状基因座(eQTL)的结果来剖析 SLE 关联的功能机制。我们发现,先前研究中与 SLE 显著相关的 14 个 SNP 对四个 eQTL 基因(HLA-DQA1、HLA-DQB1、HLA-DQB2 和 IRF5)具有顺式调控作用,这些基因在 SLE 相关细胞群中也存在差异表达。综合这些功能证据,提示了 14 个 SNP 与 SLE 关联的功能机制。该研究可能为挖掘公开可用数据集和验证显著疾病关联结果提供范例。综合分析利用公共数据资源可能为人类疾病的分子遗传机制提供新的见解。