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Polygenic contributions to alcohol use and alcohol use disorders across population-based and clinically ascertained samples

Published online by Cambridge University Press:  20 January 2020

Emma C. Johnson Open the ORCID record for Emma C. Johnson [Opens in a new window] ,
Sandra Sanchez-Roige ,
Laura Acion ,
Mark J. Adams ,
Kathleen K. Bucholz ,
Grace Chan ,
Michael J. Chao ,
David B. Chorlian ,
Danielle M. Dick  and
Howard J. Edenberg
...Show all authors
Emma C. Johnson*
Affiliation:
Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
Sandra Sanchez-Roige
Affiliation:
Department of Psychiatry, University of California San Diego, San Diego, CA, USA
Laura Acion
Affiliation:
Department of Psychiatry, University of Iowa, Carver College of Medicine, Iowa City, IA, USA
Mark J. Adams
Affiliation:
Division of Psychiatry, University of Edinburgh, Edinburgh, UK
Kathleen K. Bucholz
Affiliation:
Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
Grace Chan
Affiliation:
Department of Psychiatry, University of Connecticut School of Medicine, Farmington, CT, USA
Michael J. Chao
Affiliation:
Department of Neuroscience, Icahn School of Medicine at Mt. Sinai, New York, NY, USA
David B. Chorlian
Affiliation:
Department of Psychiatry, Suny Downstate Medical Center, Brooklyn, NY, USA
Danielle M. Dick
Affiliation:
Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA
Howard J. Edenberg
Affiliation:
Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, USA Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
Tatiana Foroud
Affiliation:
Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
Caroline Hayward
Affiliation:
MRC Human Genetics Unit, University of Edinburgh, Institute of Genetics and Molecular Medicine, Edinburgh, UK
Jon Heron
Affiliation:
University of Bristol, Bristol Medical School, Population Health Sciences, Bristol, UK
Victor Hesselbrock
Affiliation:
Department of Psychiatry, University of Connecticut School of Medicine, Farmington, CT, USA
Matthew Hickman
Affiliation:
University of Bristol, Bristol Medical School, Population Health Sciences, Bristol, UK
Kenneth S. Kendler
Affiliation:
Department of Psychiatry, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
Sivan Kinreich
Affiliation:
Department of Psychiatry, Suny Downstate Medical Center, Brooklyn, NY, USA
John Kramer
Affiliation:
Department of Psychiatry, University of Iowa, Carver College of Medicine, Iowa City, IA, USA
Sally I-Chun Kuo
Affiliation:
Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA
Samuel Kuperman
Affiliation:
Department of Psychiatry, University of Iowa, Carver College of Medicine, Iowa City, IA, USA
Dongbing Lai
Affiliation:
Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
Andrew M. McIntosh
Affiliation:
Division of Psychiatry, University of Edinburgh, Edinburgh, UK
Jacquelyn L. Meyers
Affiliation:
Department of Psychiatry, Suny Downstate Medical Center, Brooklyn, NY, USA
Martin H. Plawecki
Affiliation:
Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA
Bernice Porjesz
Affiliation:
Department of Psychiatry, Suny Downstate Medical Center, Brooklyn, NY, USA
David Porteous
Affiliation:
University of Edinburgh, Institute of Genetics & Molecular Medicine, Centre for Genomic and Experimental Medicine, Edinburgh, UK
Marc A. Schuckit
Affiliation:
Department of Psychiatry, University of California San Diego, San Diego, CA, USA
Jinni Su
Affiliation:
Department of Psychology, Arizona State University, Tempe, AZ, USA
Yong Zang
Affiliation:
Department of Biostatistics, Indiana University School of Medicine, Bloomington, IN, USA
Abraham A. Palmer
Affiliation:
Department of Psychiatry, University of California San Diego, San Diego, CA, USA University of California San Diego, Institute for Genomic Medicine, San Diego, CA, USA
Arpana Agrawal
Affiliation:
Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
Toni-Kim Clarke
Affiliation:
Division of Psychiatry, University of Edinburgh, Edinburgh, UK
Alexis C. Edwards
Affiliation:
Department of Psychiatry, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
*
Author for correspondence: Emma C. Johnson, E-mail: [email protected]
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Abstract

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.

Keywords

Alcohol consumptionalcohol dependencealcohol use disorderAUDITgeneticsGWASpolygenic risk score
Type
Original Article
Information
Psychological Medicine , Volume 51 , Issue 7 , May 2021 , pp. 1147 - 1156
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Copyright
Copyright © The Author(s) 2020. Published by Cambridge University Press

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Footnotes

*

Joint first authors.

†

Joint senior authors.

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