Leveraging genome-wide data to investigate differences between opioid use vs. opioid dependence in 41,176 individuals from the Psychiatric Genomics Consortium
dc.contributor.author | Polimanti, Renato | |
dc.contributor.author | Walters, Raymond K. | |
dc.contributor.author | Johnson, Emma C. | |
dc.contributor.author | McClintick, Jeanette N. | |
dc.contributor.author | Adkins, Amy E. | |
dc.contributor.author | Adkins, Daniel E. | |
dc.contributor.author | Bacanu, Silviu-Alin | |
dc.contributor.author | Bierut, Laura J. | |
dc.contributor.author | Bigdeli, Tim B. | |
dc.contributor.author | Brown, Sandra | |
dc.contributor.author | Bucholz, Kathleen K. | |
dc.contributor.author | Copeland, William E. | |
dc.contributor.author | Costello, E. Jane | |
dc.contributor.author | Degenhardt, Louisa | |
dc.contributor.author | Farrer, Lindsay A. | |
dc.contributor.author | Foroud, Tatiana M. | |
dc.contributor.author | Fox, Louis | |
dc.contributor.author | Goate, Alison M. | |
dc.contributor.author | Grucza, Richard | |
dc.contributor.author | Hack, Laura M. | |
dc.contributor.author | Hancock, Dana B. | |
dc.contributor.author | Hartz, Sarah M. | |
dc.contributor.author | Heath, Andrew C. | |
dc.contributor.author | Hewitt, John K. | |
dc.contributor.author | Hopfer, Christian J. | |
dc.contributor.author | Johnson, Eric O. | |
dc.contributor.author | Kendler, Kenneth S. | |
dc.contributor.author | Kranzler, Henry R. | |
dc.contributor.author | Krauter, Kenneth | |
dc.contributor.author | Lai, Dongbing | |
dc.contributor.author | Madden, Pamela A.F. | |
dc.contributor.author | Martin, Nicholas G. | |
dc.contributor.author | Maes, Hermine H. | |
dc.contributor.author | Nelson, Elliot C. | |
dc.contributor.author | Peterson, Roseann E. | |
dc.contributor.author | Porjesz, Bernice | |
dc.contributor.author | Riley, Brien P. | |
dc.contributor.author | Saccone, Nancy | |
dc.contributor.author | Stallings, Michael | |
dc.contributor.author | Wall, Tamara L. | |
dc.contributor.author | Webb, Bradley T. | |
dc.contributor.author | Wetherill, Leah | |
dc.contributor.department | Biochemistry and Molecular Biology, School of Medicine | en_US |
dc.date.accessioned | 2023-03-01T18:40:07Z | |
dc.date.available | 2023-03-01T18:40:07Z | |
dc.date.issued | 2020-08 | |
dc.description.abstract | To provide insights into the biology of opioid dependence (OD) and opioid use (i.e., exposure, OE), we completed a genome-wide analysis comparing 4503 OD cases, 4173 opioid-exposed controls, and 32,500 opioid-unexposed controls, including participants of European and African descent (EUR and AFR, respectively). Among the variants identified, rs9291211 was associated with OE (exposed vs. unexposed controls; EUR z = -5.39, p = 7.2 × 10-8). This variant regulates the transcriptomic profiles of SLC30A9 and BEND4 in multiple brain tissues and was previously associated with depression, alcohol consumption, and neuroticism. A phenome-wide scan of rs9291211 in the UK Biobank (N > 360,000) found association of this variant with propensity to use dietary supplements (p = 1.68 × 10-8). With respect to the same OE phenotype in the gene-based analysis, we identified SDCCAG8 (EUR + AFR z = 4.69, p = 10-6), which was previously associated with educational attainment, risk-taking behaviors, and schizophrenia. In addition, rs201123820 showed a genome-wide significant difference between OD cases and unexposed controls (AFR z = 5.55, p = 2.9 × 10-8) and a significant association with musculoskeletal disorders in the UK Biobank (p = 4.88 × 10-7). A polygenic risk score (PRS) based on a GWAS of risk-tolerance (n = 466,571) was positively associated with OD (OD vs. unexposed controls, p = 8.1 × 10-5; OD cases vs. exposed controls, p = 0.054) and OE (exposed vs. unexposed controls, p = 3.6 × 10-5). A PRS based on a GWAS of neuroticism (n = 390,278) was positively associated with OD (OD vs. unexposed controls, p = 3.2 × 10-5; OD vs. exposed controls, p = 0.002) but not with OE (p = 0.67). Our analyses highlight the difference between dependence and exposure and the importance of considering the definition of controls in studies of addiction. | en_US |
dc.eprint.version | Author's manuscript | en_US |
dc.identifier.citation | Polimanti R, Walters RK, Johnson EC, et al. Leveraging genome-wide data to investigate differences between opioid use vs. opioid dependence in 41,176 individuals from the Psychiatric Genomics Consortium. Mol Psychiatry. 2020;25(8):1673-1687. doi:10.1038/s41380-020-0677-9 | en_US |
dc.identifier.uri | https://hdl.handle.net/1805/31556 | |
dc.language.iso | en_US | en_US |
dc.publisher | Springer Nature | en_US |
dc.relation.isversionof | 10.1038/s41380-020-0677-9 | en_US |
dc.relation.journal | Molecular Psychiatry | en_US |
dc.rights | Publisher Policy | en_US |
dc.source | PMC | en_US |
dc.subject | Opioids | en_US |
dc.subject | Substance | en_US |
dc.subject | Abuse | en_US |
dc.subject | Genetics | en_US |
dc.subject | Genome-wide association study | en_US |
dc.title | Leveraging genome-wide data to investigate differences between opioid use vs. opioid dependence in 41,176 individuals from the Psychiatric Genomics Consortium | en_US |
dc.type | Article | en_US |