Genome wide association joint analysis reveals 99 risk loci for pain susceptibility and pleiotropic relationships with psychiatric, metabolic, and immunological traits

• Published in: PLoS genetics Vol. 19; no. 10; p. e1010977
• Main Authors: Mocci, Evelina, Ward, Kathryn, Perry, James A., Starkweather, Angela, Stone, Laura S., Schabrun, Siobhan M., Renn, Cynthia, Dorsey, Susan G., Ament, Seth A.
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 16.10.2023; Public Library of Science (PLoS)
• Subjects: Analysis; Arthritis; Back pain; Biobanks; Biology and Life Sciences; Chromatin; Chronic pain; Chronic Pain - genetics; Estimates; Genetic Predisposition to Disease; Genetic relationship; Genome; Genome-wide association studies; Genome-Wide Association Study; Genomes; Genomic analysis; Genomics; Headaches; Humans; Identification and classification; Inflammation; Medicine and Health Sciences; Migraine; Osteoarthritis; Phenotype; Pleiotropy; Polymorphism, Single Nucleotide - genetics; Public health; Quantitative trait loci; Shoulder; Statistical analysis; Statistical power; United Kingdom; United Kingdom > UK
• ISSN: 1553-7404; 1553-7390; 1553-7404
• DOI: 10.1371/journal.pgen.1010977

Chronic pain is at epidemic proportions in the United States, represents a significant burden on our public health system, and is coincident with a growing opioid crisis. While numerous genome-wide association studies have been reported for specific pain-related traits, many of these studies were underpowered, and the genetic relationship among these traits remains poorly understood. Here, we conducted a joint analysis of genome-wide association study summary statistics from seventeen pain susceptibility traits in the UK Biobank. This analysis revealed 99 genome-wide significant risk loci, 65 of which overlap loci identified in earlier studies. The remaining 34 loci are novel. We applied leave-one-trait-out meta-analyses to evaluate the influence of each trait on the joint analysis, which suggested that loci fall into four categories: loci associated with nearly all pain-related traits; loci primarily associated with a single trait; loci associated with multiple forms of skeletomuscular pain; and loci associated with headache-related pain. Overall, 664 genes were mapped to the 99 loci by genomic proximity, eQTLs, and chromatin interaction and ~15% of these genes showed differential expression in individuals with acute or chronic pain compared to healthy controls. Risk loci were enriched for genes involved in neurological and inflammatory pathways. Genetic correlation and two-sample Mendelian randomization indicated that psychiatric, metabolic, and immunological traits mediate some of these effects.