Pividori Milton, Rajagopal Padma S, Barbeira Alvaro, Liang Yanyu, Melia Owen, Bastarache Lisa, Park YoSon, Consortium GTEx, Wen Xiaoquan, Im Hae K
Section of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL, USA.
Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA.
Sci Adv. 2020 Sep 10;6(37). doi: 10.1126/sciadv.aba2083. Print 2020 Sep.
Large-scale genomic and transcriptomic initiatives offer unprecedented insight into complex traits, but clinical translation remains limited by variant-level associations without biological context and lack of analytic resources. Our resource, PhenomeXcan, synthesizes 8.87 million variants from genome-wide association study summary statistics on 4091 traits with transcriptomic data from 49 tissues in Genotype-Tissue Expression v8 into a gene-based, queryable platform including 22,515 genes. We developed a novel Bayesian colocalization method, fast enrichment estimation aided colocalization analysis (fastENLOC), to prioritize likely causal gene-trait associations. We successfully replicate associations from the phenome-wide association studies (PheWAS) catalog Online Mendelian Inheritance in Man, and an evidence-based curated gene list. Using PhenomeXcan results, we provide examples of novel and underreported genome-to-phenome associations, complex gene-trait clusters, shared causal genes between common and rare diseases via further integration of PhenomeXcan with ClinVar, and potential therapeutic targets. PhenomeXcan (phenomexcan.org) provides broad, user-friendly access to complex data for translational researchers.
大规模的基因组和转录组计划为深入了解复杂性状提供了前所未有的视角,但临床转化仍受限于缺乏生物学背景的变异水平关联以及分析资源的匮乏。我们的资源PhenomeXcan,将来自全基因组关联研究汇总统计数据中的887万个变异(涉及4091个性状)与基因型-组织表达v8中49个组织的转录组数据整合到一个基于基因的、可查询的平台中,该平台包含22,515个基因。我们开发了一种新颖的贝叶斯共定位方法,即快速富集估计辅助共定位分析(fastENLOC),以确定可能的因果基因-性状关联的优先级。我们成功地复制了全表型组关联研究(PheWAS)目录《人类孟德尔遗传在线》以及一份基于证据精心策划的基因列表中的关联。利用PhenomeXcan的结果,我们通过将PhenomeXcan与ClinVar进一步整合,提供了新的和未充分报道的基因组到表型组关联、复杂基因-性状簇、常见疾病和罕见疾病之间共享的因果基因以及潜在治疗靶点的实例。PhenomeXcan(phenomexcan.org)为转化研究人员提供了广泛且用户友好的复杂数据访问途径。