biostudies-literatureFang HEuropean Research CouncilVersus ArthritisNational Institute for Health Research (NIHR)Wellcome Trust1082-1091https://www.ebi.ac.uk/biostudies/studies/S-EPMC7124888biostudies-literatureUnknown51(7)Most candidate drugs currently fail later-stage clinical trials, largely due to poor prediction of efficacy on early target selection¹. Drug targets with genetic support are more likely to be therapeutically valid^2,3, but the translational use of genome-scale data such as from genome-wide association studies for drug target discovery in complex diseases remains challenging^4-6. Here, we show that integration of functional genomic and immune-related annotations, together with knowledge of network connectivity, maximizes the informativeness of genetics for target validation, defining the target prioritization landscape for 30 immune traits at the gene and pathway level. We demonstrate how our genetics-led drug target prioritization approach (the priority indexNature geneticsA genetics-led approach defines the drug target landscape of 30 immune-related traits.PMC712488820773204969/Z/16/Z106169106169/ZZ14/Z204969201488/Z/16/Z201488090532203141/Z/16/Z281824203141ACF-2016-13-005090532/Z/09/Z106169/Z/14/ZCarpenter LEgner UFang HPaez-Cortez JRKasela SMatthias GHandunnetthi LPeeters PJBountra CBeckmann GFujii RPrinz FGohlmann HWSekine TDe Cesco SOsgood JBurgess-Brown NBrennan PEMcVean GHowe TMcCann FEYabuki CJakobsson PJBerg LKnezevic BKnight JCOstermann NLledo Lara AMilani LChen LDe Wolf HSundstrom MDe Martino JWegner JKMalarstig AKatopodis AVlach JSanniti AMueller-Fahrnow ASoulard PMarsden BDFairfax BPBurnham KLULTRA-DD ConsortiumBowness PO'Callaghan CADamerell DSundstrom YfalseA genetics-led approach defines the drug target landscape of 30 immune-related traits.Most candidate drugs currently fail later-stage clinical trials, largely due to poor prediction of efficacy on early target selection¹. Drug targets with genetic support are more likely to be therapeutically valid^2,3, but the translational use of genome-scale data such as from genome-wide association studies for drug target discovery in complex diseases remains challenging^4-6. Here, we show that integration of functional genomic and immune-related annotations, together with knowledge of network connectivity, maximizes the informativeness of genetics for target validation, defining the target prioritization landscape for 30 immune traits at the gene and pathway level. We demonstrate how our genetics-led drug target prioritization approach (the priority index2019-01-01T00:00:00Z2019 Jul2026-04-28T22:01:57.278Z2020-10-04T07:07:02ZS-EPMC71248883125398010.1038/s41588-019-0456-1