GWAS of Extended Prescription Analgesic Use Identifies Novel Genetic Loci in Chronic Pain
Harlow, C. E.; Uzochukwu, E.; Fernando, H. A.; Mordaunt, C. E.; Hughey, J. M.; Eicher, J. D.; Robinson, L.; Bowker, N.; Howe, L.; Liu, J.; Cortes, A.; Wilson, P.; Gungabissoon, U.; Tribble, V.; Nash, A.; Young, G.; Addis, L.; Xu, C.-F.; Webber, C.; Davitte, J. M.; Cader, M. Z.
Show abstract
Pain-related conditions are the leading cause of disability worldwide. Current genome-wide association studies (GWAS) for chronic pain have mainly focused on individual pain-related disorders, which may not optimally capture the phenotype. Here, we applied a novel method of defining chronic pain based on prescription analgesic use ([≥]90 days) in two large biobanks (UK Biobank and FinnGen). GWAS meta-analyses of 11 prescription-based pain phenotypes identified 140 associations with chronic pain--78 novel (e.g. ARPP21, CNTNAP2) and 62 previously reported (e.g. SLC39A8, DCC, TRPM8). Integrating these genetic associations with functional data including transcriptome-wide association studies, cell-type and pathway enrichment, and gene enrichment in mouse phenotypes identified novel potential mechanisms involved in chronic pain, implicating oligodendrocyte differentiation, neuronal guidance, endolysosomal function and post-synaptic endosome recycling. Our study showcases how the use of prescription data to identify and characterize pain provides new insights into pain genetics and its underlying biology.
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