Association of OPRM1 Functional Coding Variant With Opioid Use Disorder: A Genome-Wide Association Study
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Abstract
Importance: With the current opioid crisis, it is important to improve understanding of the biological mechanisms of opioid use disorder (OUD). Objectives: To detect genetic risk variants for OUD and determine genetic correlations and causal association with OUD and other traits. Design, Setting, and Participants: A genome-wide association study of electronic health record-defined OUD in the Million Veteran Program sample was conducted, comprising 8529 affected European American individuals and 71 200 opioid-exposed European American controls (defined by electronic health record trajectory analysis) and 4032 affected African American individuals and 26 029 opioid-exposed African American controls. Participants were enrolled from January 10, 2011, to May 21, 2018, with electronic health record data for OUD diagnosis from October 1, 1999, to February 7, 2018. Million Veteran Program results and additional OUD case-control genome-wide association study results from the Yale-Penn and Study of Addiction: Genetics and Environment samples were meta-analyzed (total numbers: European American individuals, 10 544 OUD cases and 72 163 opioid-exposed controls; African American individuals, 5212 cases and 26 876 controls). Data on Yale-Penn participants were collected from February 14, 1999, to April 1, 2017, and data on Study of Addiction: Genetics and Environment participants were collected from 1990 to 2007. The key result was replicated in 2 independent cohorts: proxy-phenotype buprenorphine treatment in the UK Biobank and newly genotyped Yale-Penn participants. Genetic correlations between OUD and other traits were tested, and mendelian randomization analysis was conducted to identify potential causal associations. Main Outcomes and Measures: Main outcomes were International Classification of Diseases, Ninth Revision-diagnosed OUD or International Statistical Classification of Diseases and Related Health Problems, Tenth Revision-diagnosed OUD (Million Veteran Program), and DSM-IV-defined opioid dependence (Yale-Penn and Study of Addiction: Genetics and Environment). Results: A total of 114 759 individuals (101 016 men [88%]; mean [SD] age, 60.1 [12.8] years) were included. In 82 707 European American individuals, a functional coding variant (rs1799971, encoding Asn40Asp) in OPRM1 (μ-opioid receptor gene, the main biological target for opioid drugs; OMIM 600018) reached genome-wide significance (G allele: β = -0.066 [SE = 0.012]; P = 1.51 × 10-8). The finding was replicated in 2 independent samples. Single-nucleotide polymorphism-based heritability of OUD was 11.3% (SE = 1.8%). Opioid use disorder was genetically correlated with 83 traits, including multiple substance use traits, psychiatric illnesses, cognitive performance, and others. Mendelian randomization analysis revealed the following associations with OUD: risk of tobacco smoking, depression, neuroticism, worry neuroticism subcluster, and cognitive performance. No genome-wide significant association was detected for African American individuals or in transpopulation meta-analysis. Conclusions and Relevance: This genome-wide meta-analysis identified a significant association of OUD with an OPRM1 variant, which was replicated in 2 independent samples. Post-genome-wide association study analysis revealed associated pleiotropic characteristics. Recruitment of additional individuals with OUD for future studies-especially those of non-European ancestry-is a crucial next step in identifying additional significant risk loci.
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For many high-cost, high-risk externalizing behaviors, such as opioid use disorder and suicide attempts, limited genotyped cases are available for gene discovery.
“For many high-cost, high-risk behaviors with an externalizing component – opioid use disorder and suicide attempts7 being salient examples – there are limited genotyped cases available for gene discovery8,9.”
From Multivariate analysis of 1.5 million people identifies genetic associations with traits related to self-regulation and addiction. (2021) · cites this paper as [8]
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- Authors
- Zhou, H., Rentsch, C. T., Cheng, Z., Kember, R. L., Nunez, Y. Z., Sherva, R. M., Tate, J. P., Dao, C., Xu, K., Polimanti, R., Farrer, L. A., Justice, A. C., Kranzler, H. R., Gelernter, J., & Program, V. A. M. V.
- Affiliations
- Yale University (US)
- Philadelphia VA Medical Center (US)
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
- Boston University (US)
- Corresponding author
- Gelernter, Joel
- ORCID
- Venue
- JAMA Psychiatry
- Publisher
- American Medical Association (AMA)
- Published
- 2020-10-01
- Volume
- 77
- Issue
- 10
- Pages
- 1072
- ISSN
- 2168-622X (ISSN-L)
- PMC
- PMC7270886
- OpenAlex
- W3031982843
- Semantic Scholar
- 1cdbebff41b591db0c2d3cb09eca9c8734cf2a81
- Cited by
- 186
- References
- 41
- Citations by year
- 2026: 20 · 2025: 26 · 2024: 22 · 2023: 29 · 2022: 38 · 2021: 41 · 2020: 10
- FWCI
- 22.06
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- JAMA Psychiatry (publishedVersion)
- medRxiv (acceptedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- LSHTM Research Online (London School of Hygiene and Tropical Medicine) (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion, cc-by-nc-nd)
- Funders
- U.S. Department of Veterans Affairs (I01BX003341, #I01 BX004820)
- Yale University
- University of Pennsylvania
- National Institutes of Health (UL1TR001863)
- National Institute on Drug Abuse (R01DA047063, R01DA042691)
- National Center for Advancing Translational Sciences
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Opioid Use Disorder Treatment
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
- Keywords
- opioid use disorder, OPRM1, mu-opioid receptor, rs1799971, genetic risk variants, opioid epidemic, genetic correlation, causal relationship, buprenorphine treatment, opioid exposure, electronic health records, Million Veteran Program
- MeSH terms
- Aged, Female, Humans, Male, Middle Aged, Opioid-Related Disorders, United States, United States Department of Veterans Affairs, Receptors, Opioid, mu, Genome-Wide Association Study
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