@article {Mountjoy2020.09.16.299271, author = {Edward Mountjoy and Ellen M. Schmidt and Miguel Carmona and Gareth Peat and Alfredo Miranda and Luca Fumis and James Hayhurst and Annalisa Buniello and Jeremy Schwartzentruber and Mohd Anisul Karim and Daniel Wright and Andrew Hercules and Eliseo Papa and Eric Fauman and Jeffrey C. Barrett and John A. Todd and David Ochoa and Ian Dunham and Maya Ghoussaini}, title = {Open Targets Genetics: An open approach to systematically prioritize causal variants and genes at all published GWAS trait-associated loci}, elocation-id = {2020.09.16.299271}, year = {2020}, doi = {10.1101/2020.09.16.299271}, publisher = {Cold Spring Harbor Laboratory}, abstract = {Genome-wide association studies (GWAS) have identified many variants robustly associated with complex traits but identifying the gene(s) mediating such associations is a major challenge. Here we present an open resource that provides systematic fine-mapping and protein-coding gene prioritization across 133,441 published GWAS loci. We integrate diverse data sources, including genetics (from GWAS Catalog and UK Biobank) as well as transcriptomic, proteomic and epigenomic data across many tissues and cell types. We also provide systematic disease-disease and disease-molecular trait colocalization results across 92 cell types and tissues and identify 729 loci fine-mapped to a single coding causal variant and colocalized with a single gene. We trained a machine learning model using the fine mapped genetics and functional genomics data using 445 gold standard curated GWAS loci to distinguish causal genes from background genes at the same loci, outperforming a naive distance based model. Genes prioritized by our model are enriched for known approved drug targets (OR = 8.1, 95\% CI: [5.7, 11.5]). These results will be regularly updated and are publicly available through a web portal, Open Targets Genetics (OTG, http://genetics.opentargets.org), enabling users to easily prioritize genes at disease-associated loci and assess their potential as drug targets.Competing Interest StatementThe authors have declared no competing interest.}, URL = {https://www.biorxiv.org/content/early/2020/09/17/2020.09.16.299271}, eprint = {https://www.biorxiv.org/content/early/2020/09/17/2020.09.16.299271.full.pdf}, journal = {bioRxiv} }