College of Public Health, Zhengzhou University, Zhengzhou, NO.100 Kexue Road, High-Tech Development Zone Of States, Zhengzhou, P.R. China.
Center for Bioinformatics and Genomics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, 70112, USA.
Sci Rep. 2017 Nov 27;7(1):16397. doi: 10.1038/s41598-017-16722-6.
Genome-wide association studies (GWASs) have been performed extensively in diverse populations to identify single nucleotide polymorphisms (SNPs) associated with complex diseases or traits. However, to date, the SNPs identified fail to explain a large proportion of the variance of the traits/diseases. GWASs on type 2 diabetes (T2D) and obesity are generally focused on individual traits independently, and genetic intercommunity (common genetic contributions or the product of over correlated phenotypic world) between them are largely unknown, despite extensive data showing that these two phenotypes share both genetic and environmental risk factors. Here, we applied a recently developed genetic pleiotropic conditional false discovery rate (cFDR) approach to discover novel loci associated with BMI and T2D by incorporating the summary statistics from existing GWASs of these two traits. Conditional Q-Q and fold enrichment plots were used to visually demonstrate the strength of pleiotropic enrichment. Adopting a cFDR nominal significance level of 0.05, 287 loci were identified for BMI and 75 loci for T2D, 23 of which for both traits. By incorporating related traits into a conditional analysis framework, we observed significant pleiotropic enrichment between obesity and T2D. These findings may provide novel insights into the etiology of obesity and T2D, individually and jointly.
全基因组关联研究（GWAS）已经在不同人群中广泛进行，以鉴定与复杂疾病或特征相关的单核苷酸多态性（SNP）。然而，迄今为止，所鉴定的 SNP 未能解释特征/疾病的很大一部分变异。2 型糖尿病（T2D）和肥胖症的 GWAS 通常分别关注个体特征，尽管有大量数据表明这两种表型共享遗传和环境风险因素，但它们之间的遗传共性（常见遗传贡献或过度相关表型世界的产物）在很大程度上是未知的。在这里，我们应用了一种新开发的遗传多效性条件假发现率（cFDR）方法，通过整合这两种特征的现有 GWAS 的汇总统计数据来发现与 BMI 和 T2D 相关的新基因座。条件 Q-Q 和折叠富集图用于直观地展示多效性富集的强度。采用 cFDR 名义显著性水平 0.05，确定了 287 个与 BMI 相关的基因座和 75 个与 T2D 相关的基因座，其中 23 个与两种特征都相关。通过将相关特征纳入条件分析框架，我们观察到肥胖症和 T2D 之间存在显著的多效性富集。这些发现可能为肥胖症和 T2D 的病因学提供新的见解，无论是单独还是联合。
