Sibling comparisons elucidate the associations between educational attainment polygenic scores and alcohol, nicotine and cannabis

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dc.authoridStephenson, Mallory/0000-0002-1498-4333
dc.authoridSalvatore, Jessica/0000-0001-5504-5087
dc.authoridBucholz, Kathleen/0000-0003-3794-0736
dc.authoridWetherill, Leah/0000-0003-2888-9051
dc.contributor.authorSalvatore, Jessica E.
dc.contributor.authorBarr, Peter B.
dc.contributor.authorStephenson, Mallory
dc.contributor.authorAliev, Fazil
dc.contributor.authorKuo, Sally I-Chun
dc.contributor.authorSu, Jinni
dc.contributor.authorAgrawal, Arpana
dc.date.accessioned2024-09-29T16:04:34Z
dc.date.available2024-09-29T16:04:34Z
dc.date.issued2020
dc.departmentKarabük Üniversitesien_US
dc.description.abstractBackground and Aims The associations between low educational attainment and substance use disorders (SUDs) may be related to a common genetic vulnerability. We aimed to elucidate the associations between polygenic scores for educational attainment and clinical criterion counts for three SUDs (alcohol, nicotine and cannabis). Design Polygenic association and sibling comparison methods. The latter strengthens inferences in observational research by controlling for confounding factors that differ between families. Setting Six sites in the United States. Participants European ancestry participants aged 25 years and older from the Collaborative Study on the Genetics of Alcoholism (COGA). Polygenic association analyses included 5582 (54% female) participants. Sibling comparisons included 3098 (52% female) participants from 1226 sibling groups nested within the overall sample. Measurements Outcomes included criterion counts for DSM-5 alcohol use disorder (AUDSX), Fagerstrom nicotine dependence (NDSX) and DSM-5 cannabis use disorder (CUDSX). We derived polygenic scores for educational attainment (EduYears-GPS) using summary statistics from a large (> 1 million) genome-wide association study of educational attainment. Findings In polygenic association analyses, higher EduYears-GPS predicted lower AUDSX, NDSX and CUDSX [P < 0.01, effect sizes (R-2) ranging from 0.30 to 1.84%]. These effects were robust in sibling comparisons, where sibling differences in EduYears-GPS predicted all three SUDs (P < 0.05, R-2 0.13-0.20%). Conclusions Individuals who carry more alleles associated with educational attainment tend to meet fewer clinical criteria for alcohol, nicotine and cannabis use disorders, and these effects are robust to rigorous controls for potentially confounding factors that differ between families (e.g. socio-economic status, urban-rural residency and parental education).en_US
dc.description.sponsorshipNIH from the National Institute on Alcohol Abuse and Alcoholism (NIAAA) [U10AA008401]; National Institute on Drug Abuse (NIDA); National Institute on Alcohol Abuse and Alcoholism; NIH GEI [U01HG004438]; NIH contract 'High throughput genotyping for studying the genetic contributions to human disease' [HHSN268200782096C]; NCI Cancer Center Support Grant [P30 CA91842]; ICTS/CTSA from the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH) [UL1RR024992]; NIH Roadmap for Medical Research; [K01AA024152]; [K02DA032573]; [R01DA040411]en_US
dc.description.sponsorshipThe Collaborative Study on the Genetics of Alcoholism (COGA), Principal Investigators (PI) B. Porjesz, V. Hesselbrock, H. Edenberg and L. Bierut, includes 11 different centers: University of Connecticut (V. Hesselbrock); Indiana University (H. J. Edenberg, J. Nurnberger Jr, T. Foroud); University of Iowa (S. Kuperman, J. Kramer); SUNY Downstate (B. Porjesz); Washington University in St Louis (L. Bierut, J. Rice, K. Bucholz, A. Agrawal); University of California at San Diego (M. Schuckit); Rutgers University (J. Tischfield, A. Brooks); Department of Biomedical and Health Informatics, The Children's Hospital of Philadelphia; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia PA (L. Almasy), Virginia Commonwealth University (D. Dick), Icahn School of Medicine at Mount Sinai (A. Goate) and Howard University (R. Taylor). Other COGA collaborators include: L. Bauer (University of Connecticut); J. McClintick, L. Wetherill, X. Xuei, Y. Liu, D. Lai, S. O'Connor, M. Plawecki, S. Lourens (Indiana University); G. Chan (University of Iowa; University of Connecticut); J. Meyers, D. Chorlian, C. Kamarajan, A. Pandey, J. Zhang (SUNY Downstate); J.-C. Wang, M. Kapoor, S. Bertelsen (Icahn School of Medicine at Mount Sinai); A. Anokhin, V. McCutcheon, S. Saccone (Washington University); J. Salvatore, F. Aliev, B. Cho (Virginia Commonwealth University); and Mark Kos (University of Texas Rio Grande Valley). A. Parsian and M. Reilly are the NIAAA Staff Collaborators. We continue to be inspired by our memories of Henri Begleiter and Theodore Reich, founding PI and Co-PI of COGA, and also owe a debt of gratitude to other past organizers of COGA, including Ting-Kai Li, P. Michael Conneally, Raymond Crowe and Wendy Reich for their critical contributions. This national collaborative study is supported by NIH Grant U10AA008401 from the National Institute on Alcohol Abuse and Alcoholism (NIAAA) and the National Institute on Drug Abuse (NIDA). Additional support for this project comes from K01AA024152 (J.E.S.); K02DA032573 (A.A.); and R01DA040411 (E.C.J.). Funding support for GWAS genotyping performed at the Johns Hopkins University Center for Inherited Disease Research was provided by the National Institute on Alcohol Abuse and Alcoholism, the NIH GEI (U01HG004438), and the NIH contract 'High throughput genotyping for studying the genetic contributions to human disease' (HHSN268200782096C). GWAS genotyping was also performed at the Genome Technology Access Center in the Department of Genetics at Washington University School of Medicine, which is partially supported by NCI Cancer Center Support Grant no. P30 CA91842 to the Siteman Cancer Center and by ICTS/CTSA Grant# UL1RR024992 from the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH), and NIH Roadmap for Medical Research.en_US
dc.identifier.doi10.1111/add.14815
dc.identifier.endpage346en_US
dc.identifier.issn0965-2140
dc.identifier.issn1360-0443
dc.identifier.issue2en_US
dc.identifier.pmid31659820en_US
dc.identifier.scopus2-s2.0-85074732119en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage337en_US
dc.identifier.urihttps://doi.org/10.1111/add.14815
dc.identifier.urihttps://hdl.handle.net/20.500.14619/6206
dc.identifier.volume115en_US
dc.identifier.wosWOS:000492870800001en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.publisherWileyen_US
dc.relation.ispartofAddictionen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectAlcoholen_US
dc.subjectcannabisen_US
dc.subjectCollaborative Study on the Genetics of Alcoholismen_US
dc.subjectnicotineen_US
dc.subjectpolygenic risk scoreen_US
dc.subjectsibling comparisonsen_US
dc.titleSibling comparisons elucidate the associations between educational attainment polygenic scores and alcohol, nicotine and cannabisen_US
dc.typeArticleen_US

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