多效性
特质
生物
进化生物学
计算生物学
遗传学
基因组
比例(比率)
全基因组关联研究
数量性状位点
表型
计算机科学
基因
基因型
地理
单核苷酸多态性
地图学
程序设计语言
作者
Guanghao Qi,Surya B. Chhetri,Debashree Ray,Diptavo Dutta,Alexis Battle,Samsiddhi Bhattacharjee,Nilanjan Chatterjee
标识
DOI:10.1038/s41467-024-51075-5
摘要
Genome-wide association studies (GWAS) have found widespread evidence of pleiotropy, but characterization of global patterns of pleiotropy remain highly incomplete due to insufficient power of current approaches. We develop fastASSET, a method that allows efficient detection of variant-level pleiotropic association across many traits. We analyze GWAS summary statistics of 116 complex traits of diverse types collected from the GRASP repository and large GWAS Consortia. We identify 2293 independent loci and find that the lead variants in nearly all these loci (~99%) to be associated with $$\ge 2$$ traits (median = 6). We observe that degree of pleiotropy estimated from our study predicts that observed in the UK Biobank for a much larger number of traits (K = 4114) (correlation = 0.43, p-value $$ < 2.2\times {10}^{-16}$$ ). Follow-up analyzes of 21 trait-specific variants indicate their link to the expression in trait-related tissues for a small number of genes involved in relevant biological processes. Our findings provide deeper insight into the nature of pleiotropy and leads to identification of highly trait-specific susceptibility variants. Here, the authors develop fastASSET, a method for efficient detection of variant-level pleiotropic association across many traits. Using this method, they characterize genome-wide pleiotropy and links to genomic features, identifying 21 trait-specific SNPs.
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