Polygenic contributions to alcohol use and alcohol use disorders across population-based and clinically ascertained samples.
paper
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Public
- Authors
- Johnson, Emma C; Sanchez-Roige, Sandra; Acion, Laura; Adams, Mark J; Bucholz, Kathleen K; Chan, Grace; Chao, Michael J; Chorlian, David B; Dick, Danielle M; Edenberg, Howard J; Foroud, Tatiana; Hayward, Caroline; Heron, Jon; Hesselbrock, Victor; Hickman, Matthew; Kendler, Kenneth S; Kinreich, Sivan; Kramer, John; Kuo, Sally I-Chun; Kuperman, Samuel; Lai, Dongbing; McIntosh, Andrew M; Meyers, Jacquelyn L; Plawecki, Martin H; Porjesz, Bernice; Porteous, David; Schuckit, Marc A; Su, Jinni; Zang, Yong; Palmer, Abraham A; Agrawal, Arpana; Clarke, Toni-Kim; Edwards, Alexis C
- Year
- 2021
- Journal
- Psychological medicine
- PMID
- 31955720
- DOI
- 10.1017/S0033291719004045
- PMCID
- PMC7405725
BACKGROUND: Studies suggest that alcohol consumption and alcohol use disorders have distinct genetic backgrounds. METHODS: We examined whether polygenic risk scores (PRS) for consumption and problem subscales of the Alcohol Use Disorders Identification Test (AUDIT-C, AUDIT-P) in the UK Biobank (UKB; N = 121 630) correlate with alcohol outcomes in four independent samples: an ascertained cohort, the Collaborative Study on the Genetics of Alcoholism (COGA; N = 6850), and population-based cohorts: Avon Longitudinal Study of Parents and Children (ALSPAC; N = 5911), Generation Scotland (GS; N = 17 461), and an independent subset of UKB (N = 245 947). Regression models and survival analyses tested whether the PRS were associated with the alcohol-related outcomes. RESULTS: In COGA, AUDIT-P PRS was associated with alcohol dependence, AUD symptom count, maximum drinks (R2 = 0.47-0.68%, p = 2.0 × 10-8-1.0 × 10-10), and increased likelihood of onset of alcohol dependence (hazard ratio = 1.15, p = 4.7 × 10-8); AUDIT-C PRS was not an independent predictor of any phenotype. In ALSPAC, the AUDIT-C PRS was associated with alcohol dependence (R2 = 0.96%, p = 4.8 × 10-6). In GS, AUDIT-C PRS was a better predictor of weekly alcohol use (R2 = 0.27%, p = 5.5 × 10-11), while AUDIT-P PRS was more associated with problem drinking (R2 = 0.40%, p = 9.0 × 10-7). Lastly, AUDIT-P PRS was associated with ICD-based alcohol-related disorders in the UKB subset (R2 = 0.18%, p < 2.0 × 10-16). CONCLUSIONS: AUDIT-P PRS was associated with a range of alcohol-related phenotypes across population-based and ascertained cohorts, while AUDIT-C PRS showed less utility in the ascertained cohort. We show that AUDIT-P is genetically correlated with both use and misuse and demonstrate the influence of ascertainment schemes on PRS analyses.
Odds Ratios (OR) and 95% confidence interval for alcohol dependence diagnosis by PRS quartiles in ALSPAC, COGA, and UKB.PRS were split into quartiles and odds ratios calculated for case status for each quartile of risk compared to quartile 1 (lowest). A. Alcohol dependence in ALSPAC was coded by DSM-IV diagnosis (484 cases, 3,837 controls). B. Alcohol dependence was coded via DSM-IV diagnosis in the COGA sample (2,318 cases, 4,532 controls). C. A sample of European ancestry, unrelated British individuals who had ever drank, had ICD9 and ICD-10 codes available, and were not included in the discovery GWAS were used (4,141 cases, 241,806 controls).
Overview of the magnitude of predicted variance (R2, %) across the alcohol-related phenotypes probed in the four independent samples (Generation Scotland, GS; ALSPAC at age 23, A23; Collaborative Study on the Genetics of Alcoholism, COGA; and UK Biobank, UKB).The color of the dots denotes AUDIT-C (light gray) or AUDIT-P (dark gray) PRS. Only the significant (p < 0.0004) associations are shown. C, AUDIT-C; P, AUDIT-P.
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