| Literature DB >> 32917697 |
Milton Pividori1,2, Padma S Rajagopal3, Alvaro Barbeira1, Yanyu Liang1, Owen Melia1, Lisa Bastarache4,5, YoSon Park2, GTEx Consortium, Xiaoquan Wen6, Hae K Im7.
Abstract
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.Entities:
Year: 2020 PMID: 32917697 DOI: 10.1126/sciadv.aba2083
Source DB: PubMed Journal: Sci Adv ISSN: 2375-2548 Impact factor: 14.136