PhenomeXcan: Mapping the genome to the phenome through the transcriptome

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.
Funding Information
  • National Institutes of Health (UL1TR000430)
  • National Institutes of Health (HHSN268201000029C)
  • National Institutes of Health (R01DA006227-17)
  • National Institutes of Health (DA006227)
  • National Institutes of Health (HHSN261200800001E)
  • National Institutes of Health (R01MH101814)
  • National Institutes of Health (U01HG007598)
  • National Institutes of Health (R01MH106842)
  • National Institutes of Health (UM1HG008901)
  • National Institutes of Health (R01GM124486)
  • National Institutes of Health (R01HG002585)
  • National Institutes of Health (R01HG006855)
  • National Institutes of Health (UL1TR002550-01)
  • National Institutes of Health (R01MH109905)
  • National Institutes of Health (R01HG008150)
  • National Institutes of Health (DK110919)
  • National Institutes of Health (F32HG009987)
  • U.S. Department of Health and Human Services (10XS170)
  • U.S. Department of Health and Human Services (10XS171)
  • U.S. Department of Health and Human Services (10ST1035)
  • National Institute of Mental Health (R01MH107666)
  • National Institute of Mental Health (R01MH101822)
  • National Institute of Mental Health (R01MH107666)
  • National Heart, Lung, and Blood Institute (R01HL142028)
  • National Human Genome Research Institute (5U41HG009494)
  • National Human Genome Research Institute (U01HG007593)
  • National Human Genome Research Institute (R01HG010067)
  • National Human Genome Research Institute (1K99HG009916-01)
  • National Human Genome Research Institute (R35HG010718)
  • National Human Genome Research Institute (1R01HG010480)
  • National Human Genome Research Institute (5T32HG000044-22)
  • National Human Genome Research Institute (5U41HG002371-19)
  • National Institute of General Medical Sciences (R01GM122924)
  • National Institute of Diabetes and Digestive and Kidney Diseases (P30DK020595)
  • National Institute of Diabetes and Digestive and Kidney Diseases (P30DK020595)
  • Gordon and Betty Moore Foundation (4559)
  • H2020 Marie SkÅodowska-Curie Actions (706636)
  • Swiss National Science Foundation (31003A_149984)
  • Ministerio de Educación, Cultura y Deporte (FPU15/03635)
  • Ministerio de Economía y Competitividad (BIO2015-70777-P)
  • Innovative Medicines Initiative (UE7-DIRECT-115317-1)
  • leidos biomedical research (BOA No. 10XS1035)