Lun-Hsien Chang1, John B Whitfield2, Mengzhen Liu3, Sarah E Medland4, Ian B Hickie5, Nicholas G Martin6, Brad Verhulst7, Andrew C Heath8, Pamela A Madden9, Dixie J Statham10, Nathan A Gillespie11. 1. Genetic Epidemiology, QIMR Berghofer Medical Research Institute, 300 Herston Road, Herston QLD 4006, Australia; Faculty of Medicine, the University of Queensland, 20 Weightman St, Herston QLD 4006, Australia. Electronic address: lun-hsien.chang@qimrberghofer.edu.au. 2. Genetic Epidemiology, QIMR Berghofer Medical Research Institute, 300 Herston Road, Herston QLD 4006, Australia. Electronic address: John.Whitfield@qimrberghofer.edu.au. 3. Department of Psychology, University of Minnesota Twin Cities, 75 E River Rd, Minneapolis, MN 55455, USA. Electronic address: mengzhen.liu@colorado.edu. 4. Genetic Epidemiology, QIMR Berghofer Medical Research Institute, 300 Herston Road, Herston QLD 4006, Australia. Electronic address: Sarah.Medland@qimrberghofer.edu.au. 5. Brain and Mind Centre, University of Sydney, 94 Mallett St, Camperdown NSW 2050, USA. Electronic address: ian.hickie@sydney.edu.au. 6. Genetic Epidemiology, QIMR Berghofer Medical Research Institute, 300 Herston Road, Herston QLD 4006, Australia. Electronic address: Nick.Martin@qimrberghofer.edu.au. 7. Department of psychology, Michigan State University, 316 Physics Road #262, East Lansing, MI 48824, USA. Electronic address: bverhuls@msu.edu. 8. Department of Psychiatry, Washington University School of Medicine, 660 S Euclid Ave, St. Louis, MO 63110, USA. Electronic address: heatha@psychiatry.wustl.edu. 9. Department of Psychiatry, Washington University School of Medicine, 660 S Euclid Ave, St. Louis, MO 63110, USA. Electronic address: pam@matlock.wustl.edu. 10. School of Health and Life Sciences, Federation University, Federation University Australia, PO Box 663, Ballarat, VIC 3353, Australia. Electronic address: d.statham@federation.edu.au. 11. Virginia Institute for Psychiatric and Behavioural Genetics, Virginia Commonwealth University, Richmond, VA 23298, USA. Electronic address: Nathan.Gillespie@vcuhealth.org.
Abstract
BACKGROUND: Substance use, substance use disorders (SUDs), and psychiatric disorders commonly co-occur. Genetic risk common to these complex traits is an important explanation; however, little is known about how polygenic risk for tobacco or alcohol use overlaps the genetic risk for the comorbid SUDs and psychiatric disorders. METHODS: We constructed polygenic risk scores (PRSs) using GWAS meta-analysis summary statistics from a large discovery sample, GWAS & Sequencing Consortium of Alcohol and Nicotine use (GSCAN), for smoking initiation (SI; N = 631,564), age of initiating regular smoking (AI; N = 258,251), cigarettes per day (CPD; N = 258,999), smoking cessation (SC; N = 312,273), and drinks per week (DPW; N = 527,402). We then estimated the fixed effect of these PRSs on the liability to 15 phenotypes related to tobacco and alcohol use, substance use disorders, and psychiatric disorders in an independent target sample of Australian adults. RESULTS: After adjusting for multiple testing, 10 of 75 combinations of discovery and target phenotypes remained significant. PRS-SI (R2 range: 1.98%-5.09 %) was positively associated with SI, DPW, and with DSM-IV and FTND nicotine dependence, and conduct disorder. PRS-AI (R2: 3.91 %) negatively associated with DPW. PRS-CPD (R2: 1.56 %-1.77 %) positively associated with DSM-IV nicotine dependence and conduct disorder. PRS-DPW (R2: 3.39 %-6.26 %) positively associated with only DPW. The variation of DPW was significantly influenced by sex*PRS-SI, sex*PRS-AI and sex*PRS-DPW. Such interaction effect was not detected in the other 14 phenotypes. CONCLUSIONS: Polygenic risks associated with tobacco use are also associated with liability to alcohol consumption, nicotine dependence, and conduct disorder.
BACKGROUND: Substance use, substance use disorders (SUDs), and psychiatric disorders commonly co-occur. Genetic risk common to these complex traits is an important explanation; however, little is known about how polygenic risk for tobacco or alcohol use overlaps the genetic risk for the comorbid SUDs and psychiatric disorders. METHODS: We constructed polygenic risk scores (PRSs) using GWAS meta-analysis summary statistics from a large discovery sample, GWAS & Sequencing Consortium of Alcohol and Nicotine use (GSCAN), for smoking initiation (SI; N = 631,564), age of initiating regular smoking (AI; N = 258,251), cigarettes per day (CPD; N = 258,999), smoking cessation (SC; N = 312,273), and drinks per week (DPW; N = 527,402). We then estimated the fixed effect of these PRSs on the liability to 15 phenotypes related to tobacco and alcohol use, substance use disorders, and psychiatric disorders in an independent target sample of Australian adults. RESULTS: After adjusting for multiple testing, 10 of 75 combinations of discovery and target phenotypes remained significant. PRS-SI (R2 range: 1.98%-5.09 %) was positively associated with SI, DPW, and with DSM-IV and FTND nicotine dependence, and conduct disorder. PRS-AI (R2: 3.91 %) negatively associated with DPW. PRS-CPD (R2: 1.56 %-1.77 %) positively associated with DSM-IV nicotine dependence and conduct disorder. PRS-DPW (R2: 3.39 %-6.26 %) positively associated with only DPW. The variation of DPW was significantly influenced by sex*PRS-SI, sex*PRS-AI and sex*PRS-DPW. Such interaction effect was not detected in the other 14 phenotypes. CONCLUSIONS: Polygenic risks associated with tobacco use are also associated with liability to alcohol consumption, nicotine dependence, and conduct disorder.
Authors: Emily E Hartwell; Alison K Merikangas; Shefali S Verma; Marylyn D Ritchie; Henry R Kranzler; Rachel L Kember Journal: Addict Biol Date: 2021-10-05 Impact factor: 4.093
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