Polygenic Risk Score Prediction of Alcohol Dependence Symptoms Across Population‐Based and Clinically Ascertained Samples. (5th February 2018)

• Record Type: Journal Article
• Authors: Savage, Jeanne E.; Salvatore, Jessica E.; Aliev, Fazil; Edwards, Alexis C.; Hickman, Matthew; Kendler, Kenneth S.; Macleod, John; Latvala, Antti; Loukola, Anu; Kaprio, Jaakko; Rose, Richard J.; Chan, Grace; Hesselbrock, Victor; Webb, Bradley T.; Adkins, Amy; Bigdeli, Tim B.; Riley, Brien P.; Dick, Danielle M.
• Other Names: Porjesz B. investigator.; Edenberg H. investigator.; Bierut L. investigator.; Nurnberger J. investigator.; Foroud T. investigator.; Kuperman S. investigator.; Kramer J. investigator.; Rice J. investigator.; Bucholz K. investigator.; Agrawal A. investigator.; Schuckit M. investigator.; Tischfield J. investigator.; Brooks A. investigator.; Almasy L. investigator.; Goate A. investigator.; Taylor R. investigator.; Bauer L. investigator.; McClintick J. investigator.; Wetherill L. investigator.; Xuei X. investigator.; Liu Y. investigator.; Lai D. investigator.; O'Connor S. investigator.; Plawecki M. investigator.; Lourens S. investigator.; Meyers J. investigator.; Chorlian D. investigator.; Kamarajan C. investigator.; Pandey A. investigator.; Zhang J. investigator.; Wang J.‐C. investigator.; Kapoor M. investigator.; Bertelsen S. investigator.; Anokhin A. investigator.; McCutcheon V. investigator.; Saccone S. investigator.; Cho B. investigator.; Parsian A. investigator.; Reilly M. investigator.;
• Is Part Of: Alcoholism. Volume 42:Number 3(2018)
• Page Start: 520
• Page End: 530
• Publication Date: 2018-02-05
• Subjects: ALSPAC -- COGA -- FinnTwin -- IASPSAD -- Genetic Heterogeneity; Alcoholism -- Periodicals; Alcoholism -- Periodicals; Alcoolisme; Electronic journals; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.861005
• DOI: 10.1111/acer.13589
• Languages: English
• ISSNs: 0145-6008

Abstract

Abstract : Background: Despite 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. Methods: Four 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. Results: Polygenic 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. Conclusions: Though 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. Abstract : Gene identification efforts for alcohol use disorders are made more complicated by heterogeneity – the existence of different genes and etiological pathways influencing their development between individuals. Using genome‐wide polygenic risk score methods, we found a lack of overlap in genetic influences on alcohol dependence symptoms between independent samples from epidemiological population‐based studies versus studies of clinically‐ascertained families densely affected with alcoholism. Mechanisms underlying alcohol use disorders may differ between these groups, indicating caution when combining them for research or inference.