Lun-Hsien Chang1, Baptiste Couvy-Duchesne2, Mengzhen Liu3, Sarah E Medland4, Brad Verhulst5, Eric G Benotsch6, Ian B Hickie7, Nicholas G Martin4, Nathan A Gillespie8. 1. Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia; Faculty of Medicine, the University of Queensland, Brisbane, Australia. Electronic address: Lun-Hsien.Chang@qimrberghofer.edu.au. 2. Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia; Institute for Molecular Bioscience, the University of Queensland, Brisbane, Australia. 3. Department of Psychology, University of Minnesota Twin Cities, Minneapolis, MN, USA. 4. Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia. 5. Department of Psychology, Michigan State University, East Lansing, MI, USA. 6. Psychology Department, Virginia Commonwealth University, VA, USA. 7. Brain and Mind Centre, University of Sydney, Sydney, New South Wales, Australia. 8. Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia; Department of Psychology, Michigan State University, East Lansing, MI, USA.
Abstract
BACKGROUND: Co-morbid substance use is very common. Despite a historical focus using genetic epidemiology to investigate comorbid substance use and misuse, few studies have examined substance-substance associations using polygenic risk score (PRS) methods. METHODS: Using summary statistics from the largest substance use GWAS to date (258,797- 632,802 subjects), GWAS and Sequencing Consortium of Alcohol and Nicotine use (GSCAN), we constructed PRSs for smoking initiation (PRS-SI), age of initiation of regular smoking (PRS-AI), cigarettes per day (PRS-CPD), smoking cessation (PRS-SC), and drinks per week (PRS-DPW). We then estimated the fixed effect of individual PRSs on 22 lifetime substance use and substance use disorder phenotypes collected in an independent sample of 2463 young Australian adults using genetic restricted maximal likelihood (GREML) in Genome-wide Complex Trait Analysis (GCTA), separately in females, males and both sexes together. RESULTS: After accounting for multiple testing, PRS-SI significantly explained variation in the risk of cocaine (0.67%), amphetamine (1.54%), hallucinogens (0.72%), ecstasy (1.66%) and cannabis initiation (0.97%), as well as DSM-5 alcohol use disorder (0.72%). PRS-DPW explained 0.75%, 0.59% and 0.90% of the variation of cocaine, amphetamine and ecstasy initiation respectively. None of the 22 phenotypes including emergent classes of substance use were significantly predicted by PRS-AI, PRS-CPD, and PRS-SC. CONCLUSIONS: To our knowledge, this is the first study to report significant genetic overlap between the polygenic risks for smoking initiation and alcohol consumption and the risk of initiating major classes of illicit substances. PRSs constructed from large discovery GWASs allows the detection of novel genetic associations.
BACKGROUND: Co-morbid substance use is very common. Despite a historical focus using genetic epidemiology to investigate comorbid substance use and misuse, few studies have examined substance-substance associations using polygenic risk score (PRS) methods. METHODS: Using summary statistics from the largest substance use GWAS to date (258,797- 632,802 subjects), GWAS and Sequencing Consortium of Alcohol and Nicotine use (GSCAN), we constructed PRSs for smoking initiation (PRS-SI), age of initiation of regular smoking (PRS-AI), cigarettes per day (PRS-CPD), smoking cessation (PRS-SC), and drinks per week (PRS-DPW). We then estimated the fixed effect of individual PRSs on 22 lifetime substance use and substance use disorder phenotypes collected in an independent sample of 2463 young Australian adults using genetic restricted maximal likelihood (GREML) in Genome-wide Complex Trait Analysis (GCTA), separately in females, males and both sexes together. RESULTS: After accounting for multiple testing, PRS-SI significantly explained variation in the risk of cocaine (0.67%), amphetamine (1.54%), hallucinogens (0.72%), ecstasy (1.66%) and cannabis initiation (0.97%), as well as DSM-5 alcohol use disorder (0.72%). PRS-DPW explained 0.75%, 0.59% and 0.90% of the variation of cocaine, amphetamine and ecstasy initiation respectively. None of the 22 phenotypes including emergent classes of substance use were significantly predicted by PRS-AI, PRS-CPD, and PRS-SC. CONCLUSIONS: To our knowledge, this is the first study to report significant genetic overlap between the polygenic risks for smoking initiation and alcohol consumption and the risk of initiating major classes of illicit substances. PRSs constructed from large discovery GWASs allows the detection of novel genetic associations.
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