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

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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.
Molecular Psychiatry ( IF 11.0 ) Pub Date : 2020-02-26 , DOI: 10.1038/s41380-020-0677-9
Renato Polimanti ₁ , Raymond K Walters ₂ , Emma C Johnson ₃ , Jeanette N McClintick ₄ , Amy E Adkins ₅ , Daniel E Adkins ₆ , Silviu-Alin Bacanu ₇ , Laura J Bierut ₃ , Tim B Bigdeli ₈ , Sandra Brown ₉ , Kathleen K Bucholz ₃ , William E Copeland ₁₀ , E Jane Costello ₁₁ , Louisa Degenhardt ₁₂ , Lindsay A Farrer ₁₃ , Tatiana M Foroud ₁₄ , Louis Fox ₃ , Alison M Goate ₁₅ , Richard Grucza ₃ , Laura M Hack ₁₆ , Dana B Hancock ₁₇ , Sarah M Hartz ₃ , Andrew C Heath ₃ , John K Hewitt ₁₈ , Christian J Hopfer ₁₉ , Eric O Johnson ₁₇ , Kenneth S Kendler ₂₀ , Henry R Kranzler ₂₁ , Kenneth Krauter ₂₂ , Dongbing Lai ₁₄ , Pamela A F Madden ₃ , Nicholas G Martin ₂₃ , Hermine H Maes ₂₀ , Elliot C Nelson ₃ , Roseann E Peterson ₂₄ , Bernice Porjesz ₈ , Brien P Riley ₇ , Nancy Saccone ₂₅ , Michael Stallings ₁₈ , Tamara L Wall ₉ , Bradley T Webb ₇ , Leah Wetherill ₁₄ , , Howard J Edenberg ₄ , Arpana Agrawal ₃ , Joel Gelernter ₁

Affiliation

Department of Psychiatry, Yale University School of Medicine, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA.
Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA.
Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, USA.
Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA.
Department of Psychiatry, University of Utah, Salt Lake City, UT, USA.
Virginia Commonwealth University Alcohol Research Center, Virginia Institute for Psychiatric and Behavioral Genetics, Richmond, VA, USA.
Department of Psychiatry and Behavioral Sciences, State University of New York Downstate Medical Center, Brooklyn, NY, USA.
Department of Psychiatry, University of California San Diego, San Diego, CA, USA.
Department of Psychiatry, University of Vermont Medical Center, Burlington, VT, USA.
Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, USA.
National Drug and Alcohol Research Centre, University of New South Wales, Sydney, NSW, Australia.
Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA.
Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA.
Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA.
Center for Omics Discovery and Epidemiology, RTI International, Research Triangle Park, NC, USA.
Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA.
Department of Psychiatry, University of Colorado Denver, Aurora, CO, USA.
Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA.
Center for Studies of Addiction, University of Pennsylvania Perelman School of Medicine, VISN 4 MIRECC, Crescenz VAMC, Philadelphia, PA, USA.
Department of Molecular, Cellular, and Developmental Biology, University of Colorado Boulder, Boulder, CO, USA.
QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA.
Department of Genetics, Washington University School of Medicine, Saint Louis, MO, USA.

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.

中文翻译：

利用全基因组数据研究来自精神病基因组学联盟的 41,176 名个体的阿片类药物使用与阿片类药物依赖之间的差异。

为了深入了解阿片类药物依赖 (OD) 和阿片类药物使用（即暴露，OE）的生物学，我们完成了一项全基因组分析，比较了 4503 例 OD 病例、4173 例阿片类药物暴露对照和 32,500 例阿片类药物未暴露对照，包括参与者欧洲和非洲人后裔（分别为 EUR 和 AFR）。在确定的变体中，rs9291211 与 OE 相关（暴露与未暴露对照；EUR z = -5.39，p = 7.2 × 10-8）。该变体调节多个脑组织中 SLC30A9 和 BEND4 的转录组谱，以前与抑郁症、饮酒和神经质有关。在英国生物库 (N > 360,000) 中对 rs9291211 进行的全表型扫描发现该变体与使用膳食补充剂的倾向有关 (p = 1.68 × 10-8)。对于基于基因的分析中相同的 OE 表型，我们确定了 SDCCAG8 (EUR + AFR z = 4.69, p = 10-6)，它以前与教育程度、冒险行为和精神分裂症有关。此外，rs201123820 显示 OD 病例和未暴露对照之间存在全基因组显着差异（AFR z = 5.55，p = 2.9 × 10-8），并且与英国生物库中的肌肉骨骼疾病显着相关（p = 4.88 × 10-7 ）。基于风险耐受性 GWAS (n = 466,571) 的多基因风险评分 (PRS) 与 OD 呈正相关（OD 与未暴露的对照，p = 8.1 × 10-5；OD 病例与暴露的对照，p = 0.054 ) 和 OE（曝光与未曝光对照，p = 3.6 × 10-5）。基于神经质的 GWAS (n = 390,278) 的 PRS 与 OD 呈正相关（OD 与未暴露的对照，p = 3.2 × 10-5；OD 与暴露的对照，p = 0.002）但与 OE 无关（p = 0.67)。

更新日期：2020-02-26

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