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

backgroundChronic pain, defined as pain that persists for greater than three months, is a common, understudied condition that affect an estimated 20-30% of the population. 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 risk.

methodsHere 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 pain. 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.

findingsThis study identifies 894 putative drug candidates across three pain disease signatures, including 210 medications prescribable in the U.S. Drug candidates span both known and novel drug classes, including analgesics, cardiovascular agents, antidepressants, and antipsychotics, among others. Mendelian randomization analysis provides additional suggestive evidence (p < 0.05) for a causal relationships of opioid and antithrombotic agent exposure on chronic pain liability.

interpretationIn this study we establish a novel genetics-informed framework to drug repurposing for chronic pain, leveraging existing genetic and transcriptomic data resources. We identify FDA-approved drugs that we hypothesize may be beneficial for prevention or treatment of chronic pain, detected through reversed transcriptomic impacts to chronic pain and association with reduced chronic pain through causal inference approaches. Future experimental and clinical follow-up is necessary to further our understanding of these alternative drug opportunities.

fundingLMH acknowledges funding from NIMH (R01MH124839, R01MH118278, R01MH125938, RM1MH132648, R01MH136149), NIEHS (R01ES033630), and the Department of Defense (TP220451). CS acknowledges funding from NIH (F30MH132324).