Computational analyses of obesity associated loci generated by genome-wide association studies

ObjectivesGenome-wide association studies (GWASs) have discovered associations of numerous SNPs and genes with obesity. However, the underlying molecular mechanisms through which these SNPs and genes affect the predisposition to obesity remain not fully understood. Aims of our study are to comprehensively characterize obesity GWAS SNPs and genes through computational approaches.MethodsFor obesity GWAS identified SNPs, functional annotation, effects on miRNAs binding and impact on protein phosphorylation were performed via RegulomeDB and 3DSNP, miRNASNP, and the PhosSNP 1.0 database, respectively. For obesity associated genes, protein-protein interaction network construction, gene ontology and pathway enrichment analyses were performed by STRING, PANTHER and STRING, respectively.ResultsA total of 445 SNPs are significantly associated with obesity related phenotypes at threshold P −8. A number of SNPs were eQTLs for obesity associated genes, some SNPs located at binding sites of obesity related transcription factors. SNPs that might affect miRNAs binding and protein phosphorylation were identified. Protein-protein interaction network analysis identified the highly-interconnected “hub” genes. Obesity associated genes mainly involved in metabolic process and catalytic activity, and significantly enriched in 15 signal pathways.ConclusionsOur results provided the targets for follow-up experimental testing and further shed new light on obesity pathophysiology.研究目标：全基因组关联研究（Genome-wide association studies, GWAS）已发现大量单核苷酸多态性（Single Nucleotide Polymorphism, SNP）与基因和肥胖存在关联，但上述SNPs及基因影响肥胖易感性的潜在分子机制仍未完全阐明。本研究旨在通过计算生物学方法，全面解析肥胖GWAS相关SNPs与基因。研究方法：针对肥胖GWAS鉴定得到的SNPs，本研究分别通过RegulomeDB与3DSNP数据库、miRNASNP数据库以及PhosSNP 1.0数据库，对其开展功能注释、miRNA结合影响分析以及蛋白质磷酸化影响分析。针对肥胖关联基因，本研究分别通过STRING、PANTHER与STRING数据库完成蛋白质相互作用网络构建、基因本体（Gene Ontology, GO）富集分析以及通路富集分析。研究结果：本研究共筛选得到445个在阈值P<10⁻⁸水平下与肥胖相关表型显著关联的SNPs。部分SNPs为肥胖关联基因的表达数量性状位点（expression quantitative trait locus, eQTL），另有部分SNPs位于肥胖相关转录因子的结合位点区域。本研究还鉴定出了可能影响miRNA结合与蛋白质磷酸化的SNPs。蛋白质相互作用网络分析筛选得到了高度互联的枢纽（hub）基因。肥胖关联基因主要参与代谢过程与催化活性，并显著富集于15条信号通路中。研究结论：本研究结果为后续实验验证提供了潜在靶点，并为肥胖的病理生理学研究提供了全新视角。