The genetic architecture of pain intensity in the million veteran program

Chronic pain is a common problem, with more than one-fifth of adult Americans reporting pain daily or on most days. It adversely affects quality of life and imposes substantial personal and economic costs. Efforts to treat chronic pain using opioids played a central role in precipitating the U.S. opioid crisis. Despite an estimated heritability of 25-50%, the genetic architecture of chronic pain is not well characterized, in part because study samples have largely been limited to individuals of European ancestry. To help address this knowledge gap, we conducted a cross-ancestry meta-analysis of pain intensity in the Million Veteran Program. We assessed pain intensity in 598,339 participants of African American (AA = 112,968), European American (EA = 436,683), and Hispanic American (HA = 48,688) ancestries using an 11-point ordinal numerical rating scale. Genome-wide association testing was performed in PLINK, adjusting for sex, age at enrollment, and the first 10 PCs. Genetic correlations and causal relationships between pain intensity and other complex traits were determined using linkage disequilibrium score regression and Mendelian Randomization analyses, respectively. Gene-based annotation and enrichment were performed in FUMA. To prioritize druggable genes, transcriptome- and proteome-wide associations were performed using FUSION. Drug repurposing analysis was conducted using druggable genome and drug-gene interaction databases. In the cross-ancestry meta-analysis, we identified 125 independent genetic loci, 82 of which are novel. Ancestry-specific GWASs identified 86 independent loci in EA, 1 independent locus (nearest gene PPARD; chr 6) in AA and 2 independent loci (nearest genes RNU6-461P; chr 3 and RNU6-741P; chr 15) in HA. Pain intensity was genetically correlated with other pain phenotypes, level of substance use, substance use disorders, other psychiatric traits, education level, and cognitive traits. Pain intensity had a significant positive bidirectional causal effect with genetically predicted opioid use, depressed affect subcluster, major depressive disorder, neuroticism, use of drugs to treat peptic ulcer, and smoking cessation. GWAS results showed enrichment for putatively causal genes (n = 142) and proteins (n = 14) expressed in brain tissues, specifically in GABAergic neurons. Drug repurposing analysis identified anticonvulsants, beta-blockers, and calcium-channel blockers, among other drug groups, as having potential analgesic effects. Our results prioritize novel genetic variants for chronic pain, provide insights into key molecular contributors to the experience of pain, and highlight potential drug targets.