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Leveraging genome-wide data to investigate differences between opioid use vs. opioid dependence in 41,176 individuals from the Psychiatric Genomics Consortium.

Polimanti R, Walters RK, Johnson EC, McClintick JN, Adkins AE, Adkins DE, Bacanu SA, Bierut LJ, Bigdeli TB, Brown S, Bucholz KK, Copeland WE, Costello EJ, Degenhardt L, Farrer LA, Foroud TM, Fox L, Goate AM, Grucza R, Hack LM, Hancock DB, Hartz SM, Heath AC, Hewitt JK, Hopfer CJ, Johnson EO, Kendler KS, Kranzler HR, Krauter K, Lai D, Madden PAF, Martin NG, Maes HH, Nelson EC, Peterson RE, Porjesz B, Riley BP, Saccone N, Stallings M, Wall TL, Webb BT, Wetherill L, Psychiatric Genomics Consortium Substance Use Disorders Workgroup, Edenberg HJ, Agrawal A, Gelernter J. Leveraging genome-wide data to investigate differences between opioid use vs. opioid dependence in 41,176 individuals from the Psychiatric Genomics Consortium. Molecular Psychiatry. 2020 Aug 1; 25(8):1673-1687.

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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). 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). With respect to the same OE phenotype in the gene-based analysis, we identified SDCCAG8 (EUR?+?AFR z? = 4.69, p? = 10), 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) and a significant association with musculoskeletal disorders in the UK Biobank (p? = 4.88?×?10). 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; OD cases vs. exposed controls, p? = 0.054) and OE (exposed vs. unexposed controls, p? = 3.6?×?10). A PRS based on a GWAS of neuroticism (n? = 390,278) was positively associated with OD (OD vs. unexposed controls, p? = 3.2?×?10; 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.





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