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.
Autozygosity is associated with rare Mendelian disorders and clinically-relevant quantitative traits. We investigated associations between FROH(fraction of the genome in runs of homozygosity) and common diseases in Genes & Health (N=23,978 British South Asians), UK Biobank (N=397,184), and 23andMe, Inc. We show that restricting analysis to offspring of first cousins is an effective way of removing confounding due to social/environmental correlates of FROH. Within this group in G&H+UK Biobank, we found experiment-wide significant associations between FROHand twelve common diseases. We replicated the associations with type 2 diabetes (T2D) and post-traumatic stress disorder via between-sibling analysis in 23andMe (median N=480,282). We estimated that autozygosity due to consanguinity accounts for 5-18% of T2D cases amongst British Pakistanis. Our work highlights the possibility of widespread non-additive effects on common diseases and has important implications for global populations with high rates of consanguinity.
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