Polygenic Risk Score Prediction of Alcohol Dependence Symptoms Across Population-Based and Clinically Ascertained Samples

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dc.authoridLoukola, Anu-Maria/0000-0003-0542-5967
dc.authoridWebb, Bradley/0000-0002-0576-5366
dc.authoridKaprio, Jaakko/0000-0002-3716-2455
dc.authoridEdwards, Alexis/0000-0002-4006-9710
dc.authoridSalvatore, Jessica/0000-0001-5504-5087
dc.authoridHickman, Matthew/0000-0001-9864-459X
dc.authoridLatvala, Antti/0000-0001-5695-117X
dc.contributor.authorSavage, Jeanne E.
dc.contributor.authorSalvatore, Jessica E.
dc.contributor.authorAliev, Fazil
dc.contributor.authorEdwards, Alexis C.
dc.contributor.authorHickman, Matthew
dc.contributor.authorKendler, Kenneth S.
dc.contributor.authorMacleod, John
dc.date.accessioned2024-09-29T16:04:33Z
dc.date.available2024-09-29T16:04:33Z
dc.date.issued2018
dc.departmentKarabük Üniversitesien_US
dc.description.abstractBackgroundDespite consistent evidence of the heritability of alcohol use disorders (AUDs), few specific genes with an etiological role have been identified. It is likely that AUDs are highly polygenic; however, the etiological pathways and genetic variants involved may differ between populations. The aim of this study was thus to evaluate whether aggregate genetic risk for AUDs differed between clinically ascertained and population-based epidemiological samples. MethodsFour independent samples were obtained: 2 from unselected birth cohorts (Avon Longitudinal Study of Parents and Children [ALSPAC], N=4,304; FinnTwin12 [FT12], N=1,135) and 2 from families densely affected with AUDs, identified from treatment-seeking patients (Collaborative Study on the Genetics of Alcoholism, N=2,097; Irish Affected Sib Pair Study of Alcohol Dependence, N=706). AUD symptoms were assessed with clinical interviews, and participants of European ancestry were genotyped. Genomewide association was conducted separately in each sample, and the resulting association weights were used to create polygenic risk scores in each of the other samples (12 total discovery-validation pairs), and from meta-analyses within sample type. We then tested how well these aggregate genetic scores predicted AUD outcomes within and across sample types. ResultsPolygenic scores derived from 1 population-based sample (ALSPAC) significantly predicted AUD symptoms in another population-based sample (FT12), but not in either clinically ascertained sample. Trend-level associations (uncorrected p<0.05) were found for polygenic score predictions within sample types but no or negative predictions across sample types. Polygenic scores accounted for 0 to 1% of the variance in AUD symptoms. ConclusionsThough preliminary, these results provide suggestive evidence of differences in the genetic etiology of AUDs based on sample characteristics such as treatment-seeking status, which may index other important clinical or demographic factors that moderate genetic influences. Although the variance accounted for by genomewide polygenic scores remains low, future studies could improve gene identification efforts by amassing very large samples, or reducing genetic heterogeneity by informing analyses with other phenotypic information such as sample characteristics. Multiple complementary approaches may be needed to make progress in gene identification for this complex disorder.en_US
dc.description.sponsorshipNIMH [T32MH020030]; NIAAA [F31AA024378, K01AA024152, K01AA021399, R01AA018333, K01AA018755, AA015416, AA015416-S1, AA12502, AA00145, AA09203, R01AA11408]; UK Medical Research Council; Wellcome [102215/2/13/2]; University of Bristol; Academy of Finland [100499, 205585, 141054, 118555, 265240, 263278, 264146]; Academy of Finland Centre of Excellence Programme; NIH from NIAAA [U10AA008401]; NIDA; NCI Cancer Center Support grant [P30 CA91842]; ICTS/CTSA grant from the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH) [UL1RR024992]; NIH Roadmap for Medical Research; [K02AA018755]; MRC [G0800612, MR/L022206/1, G0802736] Funding Source: UKRIen_US
dc.description.sponsorshipData analysis and manuscript preparation for this project were supported by grants T32MH020030 from the NIMH and F31AA024378 from the NIAAA (JESav) and K01AA024152 from the NIAAA (JESal). Data collection and genotyping for each of the parent studies were supported by multiple sources. ALSPAC: We are extremely grateful to all the families who took part in this study, the midwives for their help in recruiting them, and the whole ALSPAC team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists, and nurses. The UK Medical Research Council and Wellcome (grant ref: 102215/2/13/2) and the University of Bristol provide core support for ALSPAC. This research was specifically funded by grants K01AA021399 and R01AA018333 from the NIAAA. GWAS data were generated by Sample Logistics and Genotyping Facilities at Wellcome Sanger Institute and LabCorp (Laboratory Corporation of America) using support from 23andMe. FinnTwin12: Funding for this study was provided by grants K01AA018755, AA015416, and AA015416-S1 (DMD) and grants AA12502, AA00145, and AA09203 (RJR) from the NIAAA, grants 100499, 205585, 141054, 118555, 265240, 263278, and 264146 from the Academy of Finland (JK), and the Academy of Finland Centre of Excellence Programme (JK). COGA: The Collaborative Study on the Genetics of Alcoholism (COGA), Principal Investigators B. Porjesz, V. Hesselbrock, H. Edenberg, 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 and 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. This national collaborative study is supported by NIH grant U10AA008401 from NIAAA and NIDA. We thank the Genome Technology Access Center in the Department of Genetics at Washington University School of Medicine for help with genomic analysis. The Center is partially supported by NCI Cancer Center Support grant #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. This work was also supported by K02AA018755 (DMD). IASPSAD: Data collection was funded by grant R01AA11408 from the NIAAA.We thank the Irish Health Research Board and Shaftsbury Square Hospital for their support of data collection. We thank Margaret Devitt, Lisa Halberstadt, and Victor Robinson for supervising the field work. This publication is the work of the authors, and Jeanne E. Savage and Danielle M. Dick will serve as guarantors for the contents of this study. The funding sources had no further role in the study design, data analysis, writing of the report, or decision to submit this article for publication. The contents of the study are solely the responsibility of the authors and do not necessarily represent the official views of the funders. The authors report no conflict of interests.en_US
dc.identifier.doi10.1111/acer.13589
dc.identifier.endpage530en_US
dc.identifier.issn0145-6008
dc.identifier.issn1530-0277
dc.identifier.issue3en_US
dc.identifier.pmid29405378en_US
dc.identifier.scopus2-s2.0-85041636062en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage520en_US
dc.identifier.urihttps://doi.org/10.1111/acer.13589
dc.identifier.urihttps://hdl.handle.net/20.500.14619/6196
dc.identifier.volume42en_US
dc.identifier.wosWOS:000426489600006en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.publisherWileyen_US
dc.relation.ispartofAlcoholism-Clinical and Experimental Researchen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectALSPACen_US
dc.subjectCOGAen_US
dc.subjectFinnTwinen_US
dc.subjectIASPSADen_US
dc.subjectGenetic Heterogeneityen_US
dc.titlePolygenic Risk Score Prediction of Alcohol Dependence Symptoms Across Population-Based and Clinically Ascertained Samplesen_US
dc.typeArticleen_US

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