PhenomeXcan: Mapping the genome to the phenome through the transcriptome.
Milton PividoriPadma Sheila RajagopalAlvaro N BarbeiraYanyu LiangOwen J MeliaLisa BastaracheYoSon ParkGTEx ConsortiumXiaoquan WenHae Kyung ImPublished in: Science advances (2020)
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.
Keyphrases
- human health
- genome wide
- copy number
- risk assessment
- dna methylation
- climate change
- mitochondrial dna
- genome wide identification
- genome wide association study
- single cell
- poor prognosis
- electronic health record
- big data
- genome wide analysis
- healthcare
- social media
- binding protein
- low cost
- high density
- quality improvement
- data analysis