Using genome-wide association results to identify drug repurposing candidates

Abstract

Drug repurposing may provide a solution to the substantial challenges facing de novo drug development. Given that 66% of FDA-approved drugs in 2021 were supported by human genetic evidence, drug repurposing methods based on genome-wide association studies (GWAS), such as drug gene-set analysis, may prove an efficient way to identify new treatments. However, to our knowledge, drug gene-set analysis has not been tested in non-psychiatric phenotypes, and previous implementations may have contained statistical biases when testing groups of drugs. Here, 1201 drugs were tested for association with hypercholesterolemia, type 2 diabetes, coronary artery disease, asthma, schizophrenia, bipolar disorder, Alzheimer's disease, and Parkinson's disease. We show that drug gene-set analysis can identify clinically relevant drugs (e.g., simvastatin for hypercholesterolemia [p = 2.82E-06]; mitiglinide for type 2 diabetes [p = 2.66E-07]) and drug groups (e.g., C10A for coronary artery disease [p = 2.31E-05]; insulin secretagogues for type 2 diabetes [p = 1.09E-11]) for non-psychiatric phenotypes. Additionally, we demonstrate that when the overlap of genes between drug-gene sets is considered we find no groups containing approved drugs for the psychiatric phenotypes tested. However, several drug groups were identified for psychiatric phenotypes that may contain possible repurposing candidates, such as ATC codes J02A (p = 2.99E-09) and N07B (p = 0.0001) for schizophrenia. Our results demonstrate that clinically relevant drugs and groups of drugs can be identified using drug gene-set analysis for a number of phenotypes. These findings have implications for quickly identifying novel treatments based on the genetic mechanisms underlying diseases.

Psychiatric Genome-wide Association Study Enrichment Shows Promise for Future Psychopharmaceutical Discoveries

“…Gene-Drug pairings were defined using the Drug Gene Interaction Database (DGldb; which uses a dense literature search to assign drug targets 30 ) and Connectivity Map (CMAP; which uses differential expression from human cell lines 31 ), both of which have been previously used to study psychiatric drug repurposing (N Drug = 1,201 32 ).…”

Multivariate, Multi-omic Analysis in 799,429 Individuals Identifies 134 Loci Associated with Somatoform Traits

“…We also used a second genetically informed drug repurposing method, druggene set analysis (DRUGSETS), 63 with data sourced from the Drug Repurposing Hub 61 and the Drug Gene Interaction Database. 64 For this method, drug-gene sets were created for 1,201 drugs, consisting of genes whose protein products are targeted by or interact with each drug.…”

“…Similarly, the somatoform factor and internalizing psychopathology were significantly genetically correlated (r g =0. 63, SD = 0.01) and shared 79% of their causal variants (SD = 0.12). Estimates were also similar for the polygenic overlap between general psychopathology and the somatoform factor (r g = 0.69, SD = 0.01, Dice = 0.83, SD = 0.07).…”

Multi-ancestry meta-analysis of tobacco use disorder prioritizes novel candidate risk genes and reveals associations with numerous health outcomes

“…We applied an additional drug repositioning method, DRUGSETS. 104 Data were drawn from the Clue Repurposing Hub and the Drug Gene Interaction Database. Drug gene-sets were created for 1,201 drugs with genes whose protein products are targeted by or interact with that specific drug.…”