A computational genetic- and transcriptomics-based study nominates drug repurposing candidates for the treatment of chronic pain

Abstract

Chronic pain, defined as pain that persists for greater than three months, is a common, understudied condition that affect an estimated 20-30% of the population1,2. Despite a high prevalence and distressing physical and psychological symptoms, research is lacking in appropriate long-term pharmaceutical treatment for chronic pain, and chronic pain persists at high rates even with intervention. Recent genome-wide association studies (GWAS) of chronic pain indicate that chronic pain can be studied as a distinct neuropsychiatric illness with genetic risk3,4. Here we develop a genetics-informed framework to identify new drug repurposing candidates for chronic pain. We first use a functional genomics approach to drug repurposing, called signature mapping, to identify drug repurposing candidates for chronic pain5. In a signature mapping analysis, the transcriptomic effects of disease and drug perturbations are compared, and drugs with opposite effects on gene expression as the disease are nominated as therapeutic candidates. Then we further investigate therapeutic avenues through causal inference using two-sample Mendelian randomization analysis, leveraging GWAS of chronic pain and GWAS of medication use across 23 drug classes. This approach, driven by information from genome- and transcriptome-wide associations with chronic pain, can yield additional insights beyond the single receptor- or molecule-level drug discovery investigation in traditional drug development pipelines.