多效性
孟德尔随机化
全基因组关联研究
单核苷酸多态性
遗传关联
遗传建筑学
遗传学
生物
基因
候选基因
计算生物学
生物信息学
数量性状位点
表型
遗传变异
基因型
作者
Zeye Liu,Jianming Xu,Jiang-Shan Tan,Xiaofei Li,Fengwen Zhang,Wenbin Ouyang,Shouzheng Wang,Yuan Huang,Shoujun Li,Xiangbin Pan
出处
期刊:iScience
[Elsevier]
日期:2023-11-01
卷期号:26 (11): 108150-108150
被引量:1
标识
DOI:10.1016/j.isci.2023.108150
摘要
Recent studies suggest that pleiotropic effects may explain the genetic architecture of cardiovascular diseases (CVDs). We conducted a comprehensive gene-centric pleiotropic association analysis for ten CVDs using genome-wide association study (GWAS) summary statistics to identify pleiotropic genes and pathways that may underlie multiple CVDs. We found shared genetic mechanisms underlying the pathophysiology of CVDs, with over two-thirds of the diseases exhibiting common genes and single-nucleotide polymorphisms (SNPs). Significant positive genetic correlations were observed in more than half of paired CVDs. Additionally, we investigated the pleiotropic genes shared between different CVDs, as well as their functional pathways and distribution in different tissues. Moreover, six hub genes, including ALDH2, XPO1, HSPA1L, ESR2, WDR12, and RAB1A, as well as 26 targeted potential drugs, were identified. Our study provides further evidence for the pleiotropic effects of genetic variants on CVDs and highlights the importance of considering pleiotropy in genetic association studies.
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