PhenomeXcan: Mapping the genome to the phenome through the transcriptome

• Published in: Science advances Vol. 6; no. 37
• Main Authors: Pividori, Milton, Rajagopal, Padma S, Barbeira, Alvaro, Liang, Yanyu, Melia, Owen, Bastarache, Lisa, Park, YoSon, Consortium, GTEx, Wen, Xiaoquan, Im, Hae K
• Format: Journal Article
• Language: English
• Published: United States American Association for the Advancement of Science 01.09.2020
• Subjects: Computer Science; Genetics; SciAdv r-articles
• ISSN: 2375-2548; 2375-2548
• DOI: 10.1126/sciadv.aba2083

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.