The genetic architecture of pain intensity in a sample of 598,339 U.S. veterans

Abstract

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 opioid crisis. Despite an estimated heritability of 25-50%, the genetic architecture of chronic pain is not well characterized, in part because studies have largely been limited to samples of European ancestry. To help address this knowledge gap, we conducted a cross-ancestry meta-analysis of pain intensity in 598,339 participants in the Million Veteran Program, which identified 125 independent genetic loci, 82 of which are novel. Pain intensity was genetically correlated with other pain phenotypes, level of substance use and substance use disorders, other psychiatric traits, education level, and cognitive traits. Integration of the GWAS findings with functional genomics data shows 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 provide insights into key molecular contributors to the experience of pain and highlight attractive drug targets.

Competing Interest Statement

HRK has been or is a member of advisory boards for Dicerna Pharmaceuticals, Sophrosyne Pharmaceuticals, Enthion Pharmaceuticals, and Clearmind Medicine. HRK has been a consultant to Sobrera Pharmaceuticals. HRK is the recipient of research funding and medication supplies from Alkermes for an investigator-initiated study. HRK is a member of the American Society of Clinical Psychopharmacology's Alcohol Clinical Trials Initiative supported in the last 3 years by Alkermes, Dicerna, Ethypharm, Lundbeck, Mitsubishi, and Otsuka. HRK and JG hold patent #15/878,640 titled "Genotype-guided dosing of opioid agonists" filed January 24, 2018. ES is a full-time employee of Regeneron Pharmaceuticals.

Funding Statement

This work was supported by grants from the US Department of Veterans Affairs Biomedical Laboratory Research and Development Service (no. I01 BX003341 (to A.C.J. and H.R.K.)) and the VISN 4 Mental Illness Research, Education and Clinical Center (to H.R.K.); and NIH grants K01 AA028292 (to R.L.K.); and P30 DA046345 (to H.R.K.).

Author Declarations

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

The protocol and consent were approved by the Central Veterans Affairs Institutional Review Board (IRB) and all site-specific IRBs.

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

Yes

I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

Yes

Data Availability

All genotype data and summary phenotype data from the Million Veteran Program GWAS will be posted on dbGaP upon acceptance of the manuscript in a peer-review journal

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