College of Public Health, Zhengzhou University, Zhengzhou, No. 100 Kexue Road, High-Tech Development Zone Of States, PR China.
College of Public Health, Zhengzhou University, Zhengzhou, No. 100 Kexue Road, High-Tech Development Zone Of States, PR China; Center for Bioinformatics and Genomics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA 70112, USA.
J Diabetes Complications. 2018 Dec;32(12):1105-1112. doi: 10.1016/j.jdiacomp.2018.09.003. Epub 2018 Sep 9.
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 coronary artery disease (CARD) are generally performed as single-trait studies, rather than analyzing the related traits simultaneously. Despite the extensive evidence suggesting that these two phenotypes share both genetic and environmental risk factors, the shared overlapping genetic biological mechanisms between these traits remain largely unexplored. Here, we adopted a recently developed genetic pleiotropic conditional false discovery rate (cFDR) approach to discover novel loci associated with T2D and CARD by incorporating the summary statistics from existing GWASs of these two traits. Applying the cFDR level of 0.05, 33 loci were identified for T2D and 34 loci for CARD, 9 of which for both. By incorporating pleiotropic effects into a conditional analysis framework, we observed that there is significant pleiotropic enrichment between T2D and CARD. These findings may provide novel insights into the etiology of T2D and CARD, as well as the processes that may influence disease development both individually and jointly.
全基因组关联研究(GWAS)在不同人群中广泛开展,以鉴定与复杂疾病或特征相关的单核苷酸多态性(SNPs)。然而,迄今为止,所鉴定的 SNPs 未能解释特征/疾病的很大一部分方差。2 型糖尿病(T2D)和冠状动脉疾病(CARD)的 GWAS 通常作为单特征研究进行,而不是同时分析相关特征。尽管有大量证据表明这两种表型共享遗传和环境风险因素,但这些特征之间共享的重叠遗传生物学机制在很大程度上仍未得到探索。在这里,我们采用了最近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,发现与 T2D 和 CARD 相关的新基因座。应用 cFDR 水平为 0.05,鉴定出 33 个与 T2D 相关的基因座和 34 个与 CARD 相关的基因座,其中 9 个同时与两者相关。通过将多效性效应纳入条件分析框架,我们观察到 T2D 和 CARD 之间存在显著的多效性富集。这些发现可能为 T2D 和 CARD 的病因学以及可能单独和共同影响疾病发展的过程提供新的见解。