Genetic similarity among 178 disease phenotypes predicts therapeutic and side effects for 1,711 drugs
Panagiotis Nikolaos Lalagkas, Rachel Dania Melamed · medRxiv · 2025
Abstract Human genetics demonstrates great potential for drug discovery, but challenges in identifying causal genes limit its clinical translation. Pleiotropy, the phenomenon where genetic variants or genes influence multiple traits, has been previously used to identify drug targets shared between phenotypically similar diseases. Here, we expand the use of pleiotropy to develop and evaluate a gene-agnostic method that predicts novel drug therapeutic and side effects across the phenome. We hypothesize that diseases with high genetic similarity to a drug’s known indications can point to new drug uses. To test this, we develop five metrics to quantify the genetic similarity between pairs of 178 diseases integrating genome-wide genetic correlation, gene-level associations and tissue-specific gene regulation. Comparing these metrics with data on indications and side effects of 1,711 common drugs, we find that more genetically similar diseases tend to share more drugs. We then use genetic similarity to predict drug therapeutic effects: our predictions with probability >0.1 show a 2.03-fold increased likelihood of progressing from Phase I clinical trials to regulatory approval. As well, predictions with probability >0.2 are 1.42 times more likely to correspond to true adverse effects. Notably, the indications model predicts side effects better than expected by chance, and vice-versa, implying a shared genetic basis for therapeutic and adverse drug effects. Together, our results suggest that genetic similarity can reveal new drug-disease links, putting forward a new use of genetics that bypasses the need for disease and drug target identification.