Identifying therapeutic drug targets using bidirectional effect genes

Prioritizing genes for translation to therapeutics for common diseases has been challenging. Here, we propose an approach to identify drug targets with high probability of success by focusing on genes with both gain of function (GoF) and loss of function (LoF) mutations associated with opposing effects on phenotype (Bidirectional Effect Selected Targets, BEST). We find 98 BEST genes for a variety of indications. Drugs targeting those genes are 3.8-fold more likely to be approved than non-BEST genes. We focus on five genes ( IGF1R, NPPC, NPR2, FGFR3 , and SHOX ) with evidence for bidirectional effects on stature. Rare protein-altering variants in those genes result in significantly increased risk for idiopathic short stature (ISS) (OR = 2.75, p = 3.99 × 10 −8 ). Finally, using functional experiments, we demonstrate that adding an exogenous CNP analog (encoded by NPPC ) rescues the phenotype, thus validating its potential as a therapeutic treatment for ISS. Our results show the value of looking for bidirectional effects to identify and validate drug targets. Prioritising genes as potential drug targets is challenging and often unsuccessful once testing efficacy in humans. Here, the authors propose an approach to identifying drug targets that uses evidence from gain- or loss-of-function mutations associated with bidirectional effects on phenotypes.