PopTradeOff: a database for exploring population-specific trade-offs between adaptive evolution, disease susceptibility, and drug responsiveness

Abstract

The influence of adaptive evolution on disease susceptibility has drawn attention, but the extent of the influence, whether favored mutations also influence drug responses, and whether the associations between the three are population specific remain little known. Using a deep learning network to integrate seven statistical tests for detecting selection signals, we predicted favored mutations in the genomes of 17 human populations. We integrate these favored mutations with GWAS sites and drug response-related variants into the database PopTradeOff. The database also contains genome annotation information on the SNP, sequence, gene, and pathway levels. The preliminary data analyses suggest that substantial associations exist between adaptive evolution, disease susceptibility, and drug responses. The database may be valuable for disease studies, drug development, and personalized medicine.