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Yousefi PD, Richmond R, Langdon R, Ness A, Liu C, Levy D, Relton C, Suderman M, Zuccolo L. Validation and characterisation of a DNA methylation alcohol biomarker across the life course. Clin Epigenetics 2019; 11:163. [PMID: 31775873 PMCID: PMC6880546 DOI: 10.1186/s13148-019-0753-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2019] [Accepted: 09/23/2019] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Recently, an alcohol predictor was developed using DNA methylation at 144 CpG sites (DNAm-Alc) as a biomarker for improved clinical or epidemiologic assessment of alcohol-related ill health. We validate the performance and characterise the drivers of this DNAm-Alc for the first time in independent populations. RESULTS In N = 1049 parents from the Avon Longitudinal Study of Parents and Children (ALSPAC) Accessible Resource for Integrated Epigenomic Studies (ARIES) at midlife, we found DNAm-Alc explained 7.6% of the variation in alcohol intake, roughly half of what had been reported previously, and interestingly explained a larger 9.8% of Alcohol Use Disorders Identification Test (AUDIT) score, a scale of alcohol use disorder. Explanatory capacity in participants from the offspring generation of ARIES measured during adolescence was much lower. However, DNAm-Alc explained 14.3% of the variation in replication using the Head and Neck 5000 (HN5000) clinical cohort that had higher average alcohol consumption. To investigate whether this relationship was being driven by genetic and/or earlier environment confounding, we examined how earlier versus concurrent DNAm-Alc measures predicted AUDIT scores. In both ARIES parental and offspring generations, we observed associations between AUDIT and concurrent, but not earlier DNAm-Alc, suggesting independence from genetic and stable environmental contributions. CONCLUSIONS The stronger relationship between DNAm-Alcs and AUDIT in parents at midlife compared to adolescents despite similar levels of consumption suggests that DNAm-Alc likely reflects long-term patterns of alcohol abuse. Such biomarkers may have potential applications for biomonitoring and risk prediction, especially in cases where reporting bias is a concern.
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Affiliation(s)
- Paul Darius Yousefi
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS82BN, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
| | - Rebecca Richmond
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS82BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Ryan Langdon
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS82BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Andrew Ness
- National Institute of Health Bristol Biomedical Research Centre, University of Bristol, Bristol, UK
- Bristol Dental School, University of Bristol, Bristol, UK
| | - Chunyu Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Daniel Levy
- The Framingham Heart Study, Framingham, MA, USA
- The Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Bethesda, MD, USA
| | - Caroline Relton
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS82BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Matthew Suderman
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS82BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Luisa Zuccolo
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS82BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
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Translational Molecular Approaches in Substance Abuse Research. Handb Exp Pharmacol 2019; 258:31-60. [PMID: 31628598 DOI: 10.1007/164_2019_259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2023]
Abstract
Excessive abuse of psychoactive substances is one of the leading contributors to morbidity and mortality worldwide. In this book chapter, we review translational research strategies that are applied in the pursuit of new and more effective therapeutics for substance use disorder (SUD). The complex, multidimensional nature of psychiatric disorders like SUD presents difficult challenges to investigators. While animal models are critical for outlining the mechanistic relationships between defined behaviors and genetic and/or molecular changes, the heterogeneous pathophysiology of brain diseases is uniquely human, necessitating the use of human studies and translational research schemes. Translational research describes a cross-species approach in which findings from human patient-based data can be used to guide molecular genetic investigations in preclinical animal models in order to delineate the mechanisms of reward circuitry changes in the addicted state. Results from animal studies can then inform clinical investigations toward the development of novel treatments for SUD. Here we describe the strategies that are used to identify and functionally validate genetic variants in the human genome which may contribute to increased risk for SUD, starting from early candidate gene approaches to more recent genome-wide association studies. We will next examine studies aimed at understanding how transcriptional and epigenetic dysregulation in SUD can persistently alter cellular function in the disease state. In our discussion, we then focus on examples from the literature illustrating molecular genetic methodologies that have been applied to studies of different substances of abuse - from alcohol and nicotine to stimulants and opioids - in order to exemplify how these approaches can both delineate the underlying molecular systems driving drug addiction and provide insights into the genetic basis of SUD.
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Meyers JL, Chorlian DB, Johnson EC, Pandey AK, Kamarajan C, Salvatore JE, Aliev F, Subbie-Saenz de Viteri S, Zhang J, Chao M, Kapoor M, Hesselbrock V, Kramer J, Kuperman S, Nurnberger J, Tischfield J, Goate A, Foroud T, Dick DM, Edenberg HJ, Agrawal A, Porjesz B. Association of Polygenic Liability for Alcohol Dependence and EEG Connectivity in Adolescence and Young Adulthood. Brain Sci 2019; 9:E280. [PMID: 31627376 PMCID: PMC6826735 DOI: 10.3390/brainsci9100280] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Revised: 09/27/2019] [Accepted: 10/04/2019] [Indexed: 12/13/2022] Open
Abstract
Differences in the connectivity of large-scale functional brain networks among individuals with alcohol use disorders (AUD), as well as those at risk for AUD, point to dysfunctional neural communication and related cognitive impairments. In this study, we examined how polygenic risk scores (PRS), derived from a recent GWAS of DSM-IV Alcohol Dependence (AD) conducted by the Psychiatric Genomics Consortium, relate to longitudinal measures of interhemispheric and intrahemispheric EEG connectivity (alpha, theta, and beta frequencies) in adolescent and young adult offspring from the Collaborative Study on the Genetics of Alcoholism (COGA) assessed between ages 12 and 31. Our findings indicate that AD PRS (p-threshold < 0.001) was associated with increased fronto-central, tempo-parietal, centro-parietal, and parietal-occipital interhemispheric theta and alpha connectivity in males only from ages 18-31 (beta coefficients ranged from 0.02-0.06, p-values ranged from 10-6-10-12), but not in females. Individuals with higher AD PRS also demonstrated more performance deficits on neuropsychological tasks (Tower of London task, visual span test) as well as increased risk for lifetime DSM-5 alcohol and opioid use disorders. We conclude that measures of neural connectivity, together with neurocognitive performance and substance use behavior, can be used to further understanding of how genetic risk variants from large GWAS of AUD may influence brain function. In addition, these data indicate the importance of examining sex and developmental effects, which otherwise may be masked. Understanding of neural mechanisms linking genetic variants emerging from GWAS to risk for AUD throughout development may help to identify specific points when neurocognitive prevention and intervention efforts may be most effective.
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Affiliation(s)
- Jacquelyn L Meyers
- Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, NY 11203, USA.
| | - David B Chorlian
- Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, NY 11203, USA.
| | - Emma C Johnson
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA.
| | - Ashwini K Pandey
- Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, NY 11203, USA.
| | - Chella Kamarajan
- Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, NY 11203, USA.
| | - Jessica E Salvatore
- Department of Psychology, Virginia Commonwealth University, Richmond, VA 23284, USA.
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA 23284, USA.
| | - Fazil Aliev
- Department of Psychology, Virginia Commonwealth University, Richmond, VA 23284, USA.
| | | | - Jian Zhang
- Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, NY 11203, USA.
| | - Michael Chao
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
| | - Manav Kapoor
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
| | - Victor Hesselbrock
- Department of Psychiatry, University of Connecticut School of Medicine, Farmington, CT 06030, USA.
| | - John Kramer
- Department of Psychiatry, Roy J and Lucille A Carver College of Medicine, University of Iowa, Iowa City, IA 52242, USA.
| | - Samuel Kuperman
- Department of Psychiatry, Roy J and Lucille A Carver College of Medicine, University of Iowa, Iowa City, IA 52242, USA.
| | - John Nurnberger
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
| | - Jay Tischfield
- Department of Genetics and the Human Genetics Institute of New Jersey, Rutgers University, Newark, NJ 08901, USA.
| | - Alison Goate
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
| | - Tatiana Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
| | - Danielle M Dick
- Department of Psychology, Virginia Commonwealth University, Richmond, VA 23284, USA.
| | - Howard J Edenberg
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, 46202, USA.
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA.
| | - Bernice Porjesz
- Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, NY 11203, USA.
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Gelernter J, Sun N, Polimanti R, Pietrzak RH, Levey DF, Lu Q, Hu Y, Li B, Radhakrishnan K, Aslan M, Cheung KH, Li Y, Rajeevan N, Sayward F, Harrington K, Chen Q, Cho K, Honerlaw J, Pyarajan S, Lencz T, Quaden R, Shi Y, Hunter-Zinck H, Gaziano JM, Kranzler HR, Concato J, Zhao H, Stein MB. Genome-wide Association Study of Maximum Habitual Alcohol Intake in >140,000 U.S. European and African American Veterans Yields Novel Risk Loci. Biol Psychiatry 2019; 86:365-376. [PMID: 31151762 PMCID: PMC6919570 DOI: 10.1016/j.biopsych.2019.03.984] [Citation(s) in RCA: 63] [Impact Index Per Article: 12.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/12/2018] [Revised: 03/16/2019] [Accepted: 03/18/2019] [Indexed: 12/20/2022]
Abstract
BACKGROUND Habitual alcohol use can be an indicator of alcohol dependence, which is associated with a wide range of serious health problems. METHODS We completed a genome-wide association study in 126,936 European American and 17,029 African American subjects in the Veterans Affairs Million Veteran Program for a quantitative phenotype based on maximum habitual alcohol consumption. RESULTS ADH1B, on chromosome 4, was the lead locus for both populations: for the European American sample, rs1229984 (p = 4.9 × 10-47); for African American, rs2066702 (p = 2.3 × 10-12). In the European American sample, we identified three additional genome-wide-significant maximum habitual alcohol consumption loci: on chromosome 17, rs77804065 (p = 1.5 × 10-12), at CRHR1 (corticotropin-releasing hormone receptor 1); the protein product of this gene is involved in stress and immune responses; and on chromosomes 8 and 10. European American and African American samples were then meta-analyzed; the associated region at CRHR1 increased in significance to 1.02 × 10-13, and we identified two additional genome-wide significant loci, FGF14 (p = 9.86 × 10-9) (chromosome 13) and a locus on chromosome 11. Besides ADH1B, none of the five loci have prior genome-wide significant support. Post-genome-wide association study analysis identified genetic correlation to other alcohol-related traits, smoking-related traits, and many others. Replications were observed in UK Biobank data. Genetic correlation between maximum habitual alcohol consumption and alcohol dependence was 0.87 (p = 4.78 × 10-9). Enrichment for cell types included dopaminergic and gamma-aminobutyric acidergic neurons in midbrain, and pancreatic delta cells. CONCLUSIONS The present study supports five novel alcohol-use risk loci, with particularly strong statistical support for CRHR1. Additionally, we provide novel insight regarding the biology of harmful alcohol use.
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Affiliation(s)
- Joel Gelernter
- Psychiatry Service, VA Connecticut Healthcare System, West Haven, Connecticut; Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut.
| | - Ning Sun
- Veterans Affairs (VA) Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut; Department of Biostatistics, Yale University School of Medicine, New Haven, Connecticut
| | - Renato Polimanti
- Psychiatry Service, VA Connecticut Healthcare System, West Haven, Connecticut; Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Robert H Pietrzak
- Psychiatry Service, VA Connecticut Healthcare System, West Haven, Connecticut; Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Daniel F Levey
- Psychiatry Service, VA Connecticut Healthcare System, West Haven, Connecticut; Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Qiongshi Lu
- Department of Biostatistics, Yale University School of Medicine, New Haven, Connecticut
| | - Yiming Hu
- Department of Biostatistics, Yale University School of Medicine, New Haven, Connecticut
| | - Boyang Li
- Department of Biostatistics, Yale University School of Medicine, New Haven, Connecticut
| | - Krishnan Radhakrishnan
- Veterans Affairs (VA) Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut
| | - Mihaela Aslan
- Veterans Affairs (VA) Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut; Department of Medicine, Yale University School of Medicine, New Haven, Connecticut
| | - Kei-Hoi Cheung
- Veterans Affairs (VA) Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut; Department of Emergency Medicine, Yale University School of Medicine, New Haven, Connecticut
| | - Yuli Li
- Veterans Affairs (VA) Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut; Yale Center for Medical Informatics, Yale University School of Medicine, New Haven, Connecticut
| | - Nallakkandi Rajeevan
- Veterans Affairs (VA) Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut; Yale Center for Medical Informatics, Yale University School of Medicine, New Haven, Connecticut
| | - Fred Sayward
- Veterans Affairs (VA) Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut; Yale Center for Medical Informatics, Yale University School of Medicine, New Haven, Connecticut
| | - Kelly Harrington
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, Massachusetts; Department of Psychiatry, Boston University School of Medicine, Boston, Massachusetts
| | - Quan Chen
- Veterans Affairs (VA) Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut; Department of Biostatistics, Yale University School of Medicine, New Haven, Connecticut
| | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, Massachusetts; Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Jacqueline Honerlaw
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, Massachusetts
| | - Saiju Pyarajan
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, Massachusetts; Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Todd Lencz
- Department of Psychiatry, Hofstra Northwell School of Medicine, Hempstead, New York; Department of Molecular Medicine, Hofstra Northwell School of Medicine, Hempstead, New York; Department of Psychiatry, Division of Research, The Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, New York; Center for Psychiatric Neuroscience, The Feinstein Institute for Medical Research, Manhasset, New York
| | - Rachel Quaden
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, Massachusetts
| | - Yunling Shi
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, Massachusetts
| | - Haley Hunter-Zinck
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, Massachusetts
| | - J Michael Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, Massachusetts; Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Henry R Kranzler
- Veterans Integrated Services Networks (VISN) 4 Mental Illness Research, Education and Clinical Center, Crescenz VA Medical Center, Philadelphia, Pennsylvania; Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania
| | - John Concato
- Veterans Affairs (VA) Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut; Department of Medicine, Yale University School of Medicine, New Haven, Connecticut
| | - Hongyu Zhao
- Veterans Affairs (VA) Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut; Department of Biostatistics, Yale University School of Medicine, New Haven, Connecticut
| | - Murray B Stein
- Psychiatry Service, VA San Diego Healthcare System, San Diego, California; Department of Psychiatry, University of California San Diego, La Jolla, California.
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McGinnis KA, Justice AC, Tate JP, Kranzler HR, Tindle HA, Becker WC, Concato J, Gelernter J, Li B, Zhang X, Zhao H, Crothers K, Xu K. Using DNA methylation to validate an electronic medical record phenotype for smoking. Addict Biol 2019; 24:1056-1065. [PMID: 30284751 DOI: 10.1111/adb.12670] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2018] [Revised: 05/22/2018] [Accepted: 07/22/2018] [Indexed: 12/14/2022]
Abstract
A validated, scalable approach to characterizing (phenotyping) smoking status is needed to facilitate genetic discovery. Using established DNA methylation sites from blood samples as a criterion standard for smoking behavior, we compare three candidate electronic medical record (EMR) smoking metrics based on longitudinal EMR text notes. With data from the Veterans Aging Cohort Study (VACS), we employed a validated algorithm to translate each smoking-related text note into current, past or never categories. We compared three alternative summary characterizations of smoking: most recent, modal and trajectories using descriptive statistics and Spearman's correlation coefficients. Logistic regression and area under the curve analyses were used to compare the associations of these phenotypes with the DNA methylation sites, cg05575921 and cg03636183, which are known to have strong associations with current smoking. DNA methylation data were available from the VACS Biomarker Cohort (VACS-BC), a sub-study of VACS. We also considered whether the associations differed by the certainty of trajectory group assignment (<0.80/≥0.80). Among 140 152 VACS participants, EMR summary smoking phenotypes varied in frequency by the metric chosen: current from 33 to 53 percent; past from 16 to 24 percent and never from 24 to 33 percent. The association between the EMR smoking pairs was highest for modal and trajectories (rho = 0.89). Among 728 individuals in the VACS-BC, both DNA methylation sites were associated with all three EMR summary metrics (p < 0.001), but the strongest association with both methylation sites was observed for trajectories (p < 0.001). Longitudinal EMR smoking data support using a summary phenotype, the validity of which is enhanced when data are integrated into statistical trajectories.
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Affiliation(s)
| | - Amy C. Justice
- Veterans Affairs Connecticut Healthcare System; West Haven CT USA
- Yale School of Medicine; New Haven CT USA
- Yale School of Public Health; New Haven CT USA
| | - Janet P. Tate
- Veterans Affairs Connecticut Healthcare System; West Haven CT USA
- Yale School of Medicine; New Haven CT USA
| | - Henry R. Kranzler
- VISN 4 MIRECC; Crescenz VAMC; Philadelphia PA USA
- University of Pennsylvania Perelman School of Medicine; Philadelphia PA USA
| | - Hilary A. Tindle
- Vanderbilt University Medical Center; Nashville TN USA
- Geriatric Research Education and Clinical Centers (GRECC), Veterans Affairs Tennessee Valley Healthcare System; Nashville TN USA
| | - William C. Becker
- Veterans Affairs Connecticut Healthcare System; West Haven CT USA
- Yale School of Medicine; New Haven CT USA
| | - John Concato
- Veterans Affairs Connecticut Healthcare System; West Haven CT USA
- Yale School of Medicine; New Haven CT USA
| | - Joel Gelernter
- Veterans Affairs Connecticut Healthcare System; West Haven CT USA
- Yale School of Medicine; New Haven CT USA
| | - Boyang Li
- Yale School of Medicine; New Haven CT USA
| | | | - Hongyu Zhao
- Yale School of Medicine; New Haven CT USA
- Yale School of Public Health; New Haven CT USA
| | | | - Ke Xu
- Veterans Affairs Connecticut Healthcare System; West Haven CT USA
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Johnson EC, St Pierre CL, Meyers JL, Aliev F, McCutcheon VV, Lai D, Dick DM, Goate AM, Kramer J, Kuperman S, Nurnberger JI, Schuckit MA, Porjesz B, Edenberg HJ, Bucholz KK, Agrawal A. The Genetic Relationship Between Alcohol Consumption and Aspects of Problem Drinking in an Ascertained Sample. Alcohol Clin Exp Res 2019; 43:1113-1125. [PMID: 30994927 PMCID: PMC6560626 DOI: 10.1111/acer.14064] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2018] [Accepted: 04/04/2019] [Indexed: 12/12/2022]
Abstract
BACKGROUND Genomewide association studies (GWAS) have begun to identify loci related to alcohol consumption, but little is known about whether this genetic propensity overlaps with specific indices of problem drinking in ascertained samples. METHODS In 6,731 European Americans who had been exposed to alcohol, we examined whether polygenic risk scores (PRS) from a GWAS of weekly alcohol consumption in the UK Biobank predicted variance in 6 alcohol-related phenotypes: alcohol use, maximum drinks within 24 hours (MAXD), total score on the Self-Rating of the Effects of Ethanol Questionnaire (SRE-T), DSM-IV alcohol dependence (DSM4AD), DSM-5 alcohol use disorder symptom counts (DSM5AUDSX), and reduction/cessation of problematic drinking. We also examined the extent to which an single nucleotide polymorphism (rs1229984) in ADH1B, which is strongly associated with both alcohol consumption and dependence, contributed to the polygenic association with these phenotypes and whether PRS interacted with sex, age, or family history of alcoholism to predict alcohol-related outcomes. We performed mixed-effect regression analyses, with family membership and recruitment site included as random effects, as well as survival modeling of age of onset of DSM4AD. RESULTS PRS for alcohol consumption significantly predicted variance in 5 of the 6 outcomes: alcohol use (Δmarginal R2 = 1.39%, Δ area under the curve [AUC] = 0.011), DSM4AD (Δmarginal R2 = 0.56%; ΔAUC = 0.003), DSM5AUDSX (Δmarginal R2 = 0.49%), MAXD (Δmarginal R2 = 0.31%), and SRE-T (Δmarginal R2 = 0.22%). PRS were also associated with onset of DSM4AD (hazard ratio = 1.11, p = 2.08e-5). The inclusion of rs1229984 attenuated the effects of the alcohol consumption PRS, particularly for DSM4AD and DSM5AUDSX, but the PRS continued to exert an independent effect for all 5 alcohol measures (Δmarginal R2 after controlling for ADH1B = 0.14 to 1.22%). Interactions between PRS and sex, age, or family history were nonsignificant. CONCLUSIONS Genetic propensity for typical alcohol consumption was associated with alcohol use and was also associated with 4 of the additional 5 outcomes, though the variance explained in this sample was modest. Future GWAS that focus on the multifaceted nature of AUD, which goes beyond consumption, might reveal additional information regarding the polygenic underpinnings of problem drinking.
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Affiliation(s)
- Emma C Johnson
- Department of Psychiatry, Washington University School of Medicine, St Louis, Missouri
| | - Celine L St Pierre
- Division of Biological and Biomedical Sciences, Washington University School of Medicine, Saint Louis, Missouri
| | - Jacquelyn L Meyers
- Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, New York
| | - Fazil Aliev
- Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia
- Department of Actuarial and Risk Management, Faculty of Business, Karabuk University, Karabük, Turkey
| | - Vivia V McCutcheon
- Department of Psychiatry, Washington University School of Medicine, St Louis, Missouri
| | - Dongbing Lai
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
| | - Danielle M Dick
- Department of Psychology and Human and Molecular Genetics, Virginia Commonwealth University, Richmond, Virginia
| | - Alison M Goate
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York
| | - John Kramer
- Department of Psychiatry, Roy J and Lucille A Carver College of Medicine, University of Iowa, Iowa City, Iowa
| | - Samuel Kuperman
- Department of Psychiatry, Roy J and Lucille A Carver College of Medicine, University of Iowa, Iowa City, Iowa
| | - John I Nurnberger
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, Indiana
| | - Marc A Schuckit
- Department of Psychiatry, University of California San Diego, San Diego, California
| | - Bernice Porjesz
- Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, New York
| | - Howard J Edenberg
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana
| | - Kathleen K Bucholz
- Department of Psychiatry, Washington University School of Medicine, St Louis, Missouri
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of Medicine, St Louis, Missouri
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Cornelis MC. Genetic determinants of beverage consumption: Implications for nutrition and health. ADVANCES IN FOOD AND NUTRITION RESEARCH 2019; 89:1-52. [PMID: 31351524 PMCID: PMC7047661 DOI: 10.1016/bs.afnr.2019.03.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Beverages make important contributions to nutritional intake and their role in health has received much attention. This review focuses on the genetic determinants of common beverage consumption and how research in this field is contributing insight to what and how much we consume and why this genetic knowledge matters from a research and public health perspective. The earliest efforts in gene-beverage behavior mapping involved genetic linkage and candidate gene analysis but these approaches have been largely replaced by genome-wide association studies (GWAS). GWAS have identified biologically plausible loci underlying alcohol and coffee drinking behavior. No GWAS has identified variants specifically associated with consumption of tea, juice, soda, wine, beer, milk or any other common beverage. Thus far, GWAS highlight an important behavior-reward component (as opposed to taste) to beverage consumption which may serve as a potential barrier to dietary interventions. Loci identified have been used in Mendelian randomization and gene×beverage interaction analysis of disease but results have been mixed. This research is necessary as it informs the clinical relevance of SNP-beverage associations and thus genotype-based personalized nutrition, which is gaining interest in the commercial and public health sectors.
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Affiliation(s)
- Marilyn C Cornelis
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, United States.
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58
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Kranzler HR, Zhou H, Kember RL, Vickers Smith R, Justice AC, Damrauer S, Tsao PS, Klarin D, Baras A, Reid J, Overton J, Rader DJ, Cheng Z, Tate JP, Becker WC, Concato J, Xu K, Polimanti R, Zhao H, Gelernter J. Genome-wide association study of alcohol consumption and use disorder in 274,424 individuals from multiple populations. Nat Commun 2019; 10:1499. [PMID: 30940813 PMCID: PMC6445072 DOI: 10.1038/s41467-019-09480-8] [Citation(s) in RCA: 285] [Impact Index Per Article: 57.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Accepted: 03/06/2019] [Indexed: 12/21/2022] Open
Abstract
Alcohol consumption level and alcohol use disorder (AUD) diagnosis are moderately heritable traits. We conduct genome-wide association studies of these traits using longitudinal Alcohol Use Disorder Identification Test-Consumption (AUDIT-C) scores and AUD diagnoses in a multi-ancestry Million Veteran Program sample (N = 274,424). We identify 18 genome-wide significant loci: 5 associated with both traits, 8 associated with AUDIT-C only, and 5 associated with AUD diagnosis only. Polygenic Risk Scores (PRS) for both traits are associated with alcohol-related disorders in two independent samples. Although a significant genetic correlation reflects the overlap between the traits, genetic correlations for 188 non-alcohol-related traits differ significantly for the two traits, as do the phenotypes associated with the traits' PRS. Cell type group partitioning heritability enrichment analyses also differentiate the two traits. We conclude that, although heavy drinking is a key risk factor for AUD, it is not a sufficient cause of the disorder.
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Affiliation(s)
- Henry R Kranzler
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.
- Crescenz Veterans Affairs Medical Center, Philadelphia, PA, 19104, USA.
| | - Hang Zhou
- Yale School of Medicine, New Haven, CT, 06511, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - Rachel L Kember
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Crescenz Veterans Affairs Medical Center, Philadelphia, PA, 19104, USA
| | - Rachel Vickers Smith
- Crescenz Veterans Affairs Medical Center, Philadelphia, PA, 19104, USA
- University of Louisville School of Nursing, Louisville, KY, 40202, USA
| | - Amy C Justice
- Yale School of Medicine, New Haven, CT, 06511, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
- Yale School of Public Health, New Haven, CT, 06511, USA
| | - Scott Damrauer
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Crescenz Veterans Affairs Medical Center, Philadelphia, PA, 19104, USA
| | - Philip S Tsao
- VA Palo Alto Health Care System, Palo Alto, CA, 94304, USA
- Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Derek Klarin
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
| | - Aris Baras
- Regeneron Genetics Center, Tarrytown, NY, 10591, USA
| | - Jeffrey Reid
- Regeneron Genetics Center, Tarrytown, NY, 10591, USA
| | - John Overton
- Regeneron Genetics Center, Tarrytown, NY, 10591, USA
| | - Daniel J Rader
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Zhongshan Cheng
- Yale School of Medicine, New Haven, CT, 06511, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - Janet P Tate
- Yale School of Medicine, New Haven, CT, 06511, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - William C Becker
- Yale School of Medicine, New Haven, CT, 06511, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - John Concato
- Yale School of Medicine, New Haven, CT, 06511, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - Ke Xu
- Yale School of Medicine, New Haven, CT, 06511, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - Renato Polimanti
- Yale School of Medicine, New Haven, CT, 06511, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - Hongyu Zhao
- Yale School of Medicine, New Haven, CT, 06511, USA
- Yale School of Public Health, New Haven, CT, 06511, USA
| | - Joel Gelernter
- Yale School of Medicine, New Haven, CT, 06511, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
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59
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Salvatore JE, Han S, Farris SP, Mignogna KM, Miles MF, Agrawal A. Beyond genome-wide significance: integrative approaches to the interpretation and extension of GWAS findings for alcohol use disorder. Addict Biol 2019; 24:275-289. [PMID: 29316088 PMCID: PMC6037617 DOI: 10.1111/adb.12591] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2017] [Revised: 11/20/2017] [Accepted: 11/26/2017] [Indexed: 12/16/2022]
Abstract
Alcohol use disorder (AUD) is a heritable complex behavior. Due to the highly polygenic nature of AUD, identifying genetic variants that comprise this heritable variation has proved to be challenging. With the exception of functional variants in alcohol metabolizing genes (e.g. ADH1B and ALDH2), few other candidate loci have been confidently linked to AUD. Genome-wide association studies (GWAS) of AUD and other alcohol-related phenotypes have either produced few hits with genome-wide significance or have failed to replicate on further study. These issues reinforce the complex nature of the genetic underpinnings for AUD and suggest that both GWAS studies with larger samples and additional analysis approaches that better harness the nominally significant loci in existing GWAS are needed. Here, we review approaches of interest in the post-GWAS era, including in silico functional analyses; functional partitioning of single nucleotide polymorphism heritability; aggregation of signal into genes and gene networks; and validation of identified loci, genes and gene networks in postmortem brain tissue and across species. These integrative approaches hold promise to illuminate our understanding of the biological basis of AUD; however, we recognize that the main challenge continues to be the extremely polygenic nature of AUD, which necessitates large samples to identify multiple loci associated with AUD liability.
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Affiliation(s)
- Jessica E. Salvatore
- Department of Psychology; Virginia Commonwealth University; Richmond VA USA
- Virginia Institute for Psychiatric and Behavioral Genetics; Virginia Commonwealth University; Richmond VA USA
| | - Shizhong Han
- Department of Psychiatry; University of Iowa; Iowa City IA USA
- Department of Psychiatry and Behavioral Sciences; Johns Hopkins School of Medicine; Baltimore MD USA
| | - Sean P. Farris
- Waggoner Center for Alcohol and Addiction Research; The University of Texas at Austin; Austin TX USA
| | - Kristin M. Mignogna
- Virginia Institute for Psychiatric and Behavioral Genetics; Virginia Commonwealth University; Richmond VA USA
| | - Michael F. Miles
- Department of Pharmacology and Toxicology; Virginia Commonwealth University; Richmond VA USA
| | - Arpana Agrawal
- Department of Psychiatry; Washington University School of Medicine; Saint Louis MO USA
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60
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Genome-Wide Association Studies of Impulsive Personality Traits (BIS-11 and UPPS-P) and Drug Experimentation in up to 22,861 Adult Research Participants Identify Loci in the CACNA1I and CADM2 genes. J Neurosci 2019; 39:2562-2572. [PMID: 30718321 DOI: 10.1523/jneurosci.2662-18.2019] [Citation(s) in RCA: 53] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2018] [Revised: 12/14/2018] [Accepted: 01/10/2019] [Indexed: 12/12/2022] Open
Abstract
Impulsive personality traits are complex heritable traits that are governed by frontal-subcortical circuits and are associated with numerous neuropsychiatric disorders, particularly drug abuse and attention-deficit/hyperactivity disorder (ADHD). In collaboration with the genetics company 23andMe, we performed 10 genome-wide association studies on measures of impulsive personality traits [the short version of the UPPS-P Impulsive Behavior Scale, and the Barratt Impulsiveness Scale (BIS-11)] and drug experimentation (the number of drug classes an individual had tried in their lifetime) in up to 22,861 male and female adult human research participants of European ancestry. Impulsive personality traits and drug experimentation showed single nucleotide polymorphism heritabilities that ranged from 5 to 11%. Genetic variants in the CADM2 locus were significantly associated with UPPS-P Sensation Seeking (p = 8.3 × 10-9, rs139528938) and showed a suggestive association with Drug Experimentation (p = 3.0 × 10-7, rs2163971; r 2 = 0.68 with rs139528938). Furthermore, genetic variants in the CACNA1I locus were significantly associated with UPPS-P Negative Urgency (p = 3.8 × 10-8; rs199694726). The role of these genes was supported by single variant, gene- and transcriptome-based analyses. Multiple subscales from both UPPS-P and BIS showed strong genetic correlations (>0.5) with Drug Experimentation and other substance use traits measured in independent cohorts, including smoking initiation, and lifetime cannabis use. Several UPPS-P and BIS subscales were genetically correlated with ADHD (r g = 0.30-0.51), supporting their validity as endophenotypes. Our findings demonstrate a role for common genetic contributions to individual differences in impulsivity. Furthermore, our study is the first to provide a genetic dissection of the relationship between different types of impulsive personality traits and various psychiatric disorders.SIGNIFICANCE STATEMENT Impulsive personality traits (IPTs) are heritable traits that are governed by frontal-subcortical circuits and are associated with neuropsychiatric disorders, particularly substance use disorders. We have performed genome-wide association studies of IPTs to identify regions and genes that account for this heritable variation. IPTs and drug experimentation were modestly heritable (5-11%). We identified an association between single nucleotide polymorphisms in CADM2 and both sensation seeking and drug experimentation; and between variants in CACNA1I and negative urgency. The role of these genes was supported by single variant, gene- and transcriptome-based analyses. This study provides evidence that impulsivity can be genetically separated into distinct components. We showed that IPT are genetically associated with substance use and ADHD, suggesting impulsivity is an endophenotype contributing to these psychiatric conditions.
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61
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Sanchez-Roige S, Palmer AA, Fontanillas P, Elson SL, Adams MJ, Howard DM, Edenberg HJ, Davies G, Crist RC, Deary IJ, McIntosh AM, Clarke TK. Genome-Wide Association Study Meta-Analysis of the Alcohol Use Disorders Identification Test (AUDIT) in Two Population-Based Cohorts. Am J Psychiatry 2019; 176:107-118. [PMID: 30336701 PMCID: PMC6365681 DOI: 10.1176/appi.ajp.2018.18040369] [Citation(s) in RCA: 243] [Impact Index Per Article: 48.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
OBJECTIVE Alcohol use disorders are common conditions that have enormous social and economic consequences. Genome-wide association analyses were performed to identify genetic variants associated with a proxy measure of alcohol consumption and alcohol misuse and to explore the shared genetic basis between these measures and other substance use, psychiatric, and behavioral traits. METHOD This study used quantitative measures from the Alcohol Use Disorders Identification Test (AUDIT) from two population-based cohorts of European ancestry (UK Biobank [N=121,604] and 23andMe [N=20,328]) and performed a genome-wide association study (GWAS) meta-analysis. Two additional GWAS analyses were performed, a GWAS for AUDIT scores on items 1-3, which focus on consumption (AUDIT-C), and for scores on items 4-10, which focus on the problematic consequences of drinking (AUDIT-P). RESULTS The GWAS meta-analysis of AUDIT total score identified 10 associated risk loci. Novel associations localized to genes including JCAD and SLC39A13; this study also replicated previously identified signals in the genes ADH1B, ADH1C, KLB, and GCKR. The dimensions of AUDIT showed positive genetic correlations with alcohol consumption (rg=0.76-0.92) and DSM-IV alcohol dependence (rg=0.33-0.63). AUDIT-P and AUDIT-C scores showed significantly different patterns of association across a number of traits, including psychiatric disorders. AUDIT-P score was significantly positively genetically correlated with schizophrenia (rg=0.22), major depressive disorder (rg=0.26), and attention deficit hyperactivity disorder (rg=0.23), whereas AUDIT-C score was significantly negatively genetically correlated with major depressive disorder (rg=-0.24) and ADHD (rg=-0.10). This study also used the AUDIT data in the UK Biobank to identify thresholds for dichotomizing AUDIT total score that optimize genetic correlations with DSM-IV alcohol dependence. Coding individuals with AUDIT total scores ≤4 as control subjects and those with scores ≥12 as case subjects produced a significant high genetic correlation with DSM-IV alcohol dependence (rg=0.82) while retaining most subjects. CONCLUSIONS AUDIT scores ascertained in population-based cohorts can be used to explore the genetic basis of both alcohol consumption and alcohol use disorders.
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Affiliation(s)
- Sandra Sanchez-Roige
- Department of Psychiatry, University of California San
Diego, La Jolla, CA, 92093, USA
| | - Abraham A. Palmer
- Department of Psychiatry, University of California San
Diego, La Jolla, CA, 92093, USA
- Institute for Genomic Medicine, University of California
San Diego, La Jolla, CA, USA
| | - Pierre Fontanillas
- Collaborator List for the 23andMe Research Team: Michelle
Agee, Babak Alipanahi, Adam Auton, Robert K. Bell, Katarzyna Bryc, Sarah L. Elson,
Pierre Fontanillas, Nicholas A. Furlotte, David A. Hinds, Karen E. Huber, Aaron
Kleinman, Nadia K. Litterman, Jennifer C. McCreight, Matthew H. McIntyre, Joanna L.
Mountain, Elizabeth S. Noblin, Carrie A.M. Northover, Steven J. Pitts, J. Fah
Sathirapongsasuti, Olga V. Sazonova, Janie F. Shelton, Suyash Shringarpure, Chao
Tian, Joyce Y. Tung, Vladimir Vacic, and Catherine H. Wilson
| | - Sarah L. Elson
- Collaborator List for the 23andMe Research Team: Michelle
Agee, Babak Alipanahi, Adam Auton, Robert K. Bell, Katarzyna Bryc, Sarah L. Elson,
Pierre Fontanillas, Nicholas A. Furlotte, David A. Hinds, Karen E. Huber, Aaron
Kleinman, Nadia K. Litterman, Jennifer C. McCreight, Matthew H. McIntyre, Joanna L.
Mountain, Elizabeth S. Noblin, Carrie A.M. Northover, Steven J. Pitts, J. Fah
Sathirapongsasuti, Olga V. Sazonova, Janie F. Shelton, Suyash Shringarpure, Chao
Tian, Joyce Y. Tung, Vladimir Vacic, and Catherine H. Wilson
| | - The 23andMe Research Team
- Collaborator List for the 23andMe Research Team: Michelle
Agee, Babak Alipanahi, Adam Auton, Robert K. Bell, Katarzyna Bryc, Sarah L. Elson,
Pierre Fontanillas, Nicholas A. Furlotte, David A. Hinds, Karen E. Huber, Aaron
Kleinman, Nadia K. Litterman, Jennifer C. McCreight, Matthew H. McIntyre, Joanna L.
Mountain, Elizabeth S. Noblin, Carrie A.M. Northover, Steven J. Pitts, J. Fah
Sathirapongsasuti, Olga V. Sazonova, Janie F. Shelton, Suyash Shringarpure, Chao
Tian, Joyce Y. Tung, Vladimir Vacic, and Catherine H. Wilson
| | | | - Mark J. Adams
- Division of Psychiatry, University of Edinburgh, Edinburgh,
UK
| | - David M. Howard
- Division of Psychiatry, University of Edinburgh, Edinburgh,
UK
| | - Howard J. Edenberg
- Department of Biochemistry and Molecular Biology, Indiana
University School of Medicine, Indianapolis, IN, USA
| | - Gail Davies
- Centre for Cognitive Ageing and Cognitive Epidemiology,
University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh,
Edinburgh, UK
| | - Richard C. Crist
- Translational Research Laboratories, Center for
Neurobiology and Behavior, Department of Psychiatry, University of Pennsylvania
Perelman School of Medicine, Philadelphia, PA, USA
| | - Ian J. Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology,
University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh,
Edinburgh, UK
| | - Andrew M. McIntosh
- Division of Psychiatry, University of Edinburgh, Edinburgh,
UK
- Centre for Cognitive Ageing and Cognitive Epidemiology,
University of Edinburgh, Edinburgh, UK
| | - Toni-Kim Clarke
- Division of Psychiatry, University of Edinburgh, Edinburgh,
UK
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Edenberg HJ, McClintick JN. Alcohol Dehydrogenases, Aldehyde Dehydrogenases, and Alcohol Use Disorders: A Critical Review. Alcohol Clin Exp Res 2018; 42:2281-2297. [PMID: 30320893 PMCID: PMC6286250 DOI: 10.1111/acer.13904] [Citation(s) in RCA: 146] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2018] [Accepted: 10/07/2018] [Indexed: 12/20/2022]
Abstract
Alcohol use disorders (AUDs) are complex traits, meaning that variations in many genes contribute to the risk, as does the environment. Although the total genetic contribution to risk is substantial, most individual variations make only very small contributions. By far the strongest contributors are functional variations in 2 genes involved in alcohol (ethanol [EtOH]) metabolism. A functional variant in alcohol dehydrogenase 1B (ADH1B) is protective in people of European and Asian descent, and a different functional variant in the same gene is protective in those of African descent. A strongly protective variant in aldehyde dehydrogenase 2 (ALDH2) is essentially only found in Asians. This highlights the need to study a wide range of populations. The likely mechanism of protection against heavy drinking and AUDs in both cases is alteration in the rate of metabolism of EtOH that at least transiently elevates acetaldehyde. Other ADH and ALDH variants, including functional variations in ADH1C, have also been implicated in affecting drinking behavior and risk for alcoholism. The pattern of linkage disequilibrium in the ADH region and the differences among populations complicate analyses, particularly of regulatory variants. This critical review focuses upon the ADH and ALDH genes as they affect AUDs.
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Affiliation(s)
- Howard J. Edenberg
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN
| | - Jeanette N. McClintick
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN
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63
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Walters RK, Polimanti R, Johnson EC, McClintick JN, Adams MJ, Adkins AE, Aliev F, Bacanu SA, Batzler A, Bertelsen S, Biernacka JM, Bigdeli TB, Chen LS, Clarke TK, Chou YL, Degenhardt F, Docherty AR, Edwards AC, Fontanillas P, Foo JC, Fox L, Frank J, Giegling I, Gordon S, Hack LM, Hartmann AM, Hartz SM, Heilmann-Heimbach S, Herms S, Hodgkinson C, Hoffmann P, Jan Hottenga J, Kennedy MA, Alanne-Kinnunen M, Konte B, Lahti J, Lahti-Pulkkinen M, Lai D, Ligthart L, Loukola A, Maher BS, Mbarek H, McIntosh AM, McQueen MB, Meyers JL, Milaneschi Y, Palviainen T, Pearson JF, Peterson RE, Ripatti S, Ryu E, Saccone NL, Salvatore JE, Sanchez-Roige S, Schwandt M, Sherva R, Streit F, Strohmaier J, Thomas N, Wang JC, Webb BT, Wedow R, Wetherill L, Wills AG, Boardman JD, Chen D, Choi DS, Copeland WE, Culverhouse RC, Dahmen N, Degenhardt L, Domingue BW, Elson SL, Frye MA, Gäbel W, Hayward C, Ising M, Keyes M, Kiefer F, Kramer J, Kuperman S, Lucae S, Lynskey MT, Maier W, Mann K, Männistö S, Müller-Myhsok B, Murray AD, Nurnberger JI, Palotie A, Preuss U, Räikkönen K, Reynolds MD, Ridinger M, Scherbaum N, Schuckit MA, Soyka M, Treutlein J, Witt S, Wodarz N, Zill P, Adkins DE, Boden JM, Boomsma DI, Bierut LJ, Brown SA, Bucholz KK, Cichon S, Costello EJ, de Wit H, Diazgranados N, Dick DM, Eriksson JG, Farrer LA, Foroud TM, Gillespie NA, Goate AM, Goldman D, Grucza RA, Hancock DB, Harris KM, Heath AC, Hesselbrock V, Hewitt JK, Hopfer CJ, Horwood J, Iacono W, Johnson EO, Kaprio JA, Karpyak VM, Kendler KS, Kranzler HR, Krauter K, Lichtenstein P, Lind PA, McGue M, MacKillop J, Madden PAF, Maes HH, Magnusson P, Martin NG, Medland SE, Montgomery GW, Nelson EC, Nöthen MM, Palmer AA, Pedersen NL, Penninx BWJH, Porjesz B, Rice JP, Rietschel M, Riley BP, Rose R, Rujescu D, Shen PH, Silberg J, Stallings MC, Tarter RE, Vanyukov MM, Vrieze S, Wall TL, Whitfield JB, Zhao H, Neale BM, Gelernter J, Edenberg HJ, Agrawal A. Transancestral GWAS of alcohol dependence reveals common genetic underpinnings with psychiatric disorders. Nat Neurosci 2018; 21:1656-1669. [PMID: 30482948 PMCID: PMC6430207 DOI: 10.1038/s41593-018-0275-1] [Citation(s) in RCA: 403] [Impact Index Per Article: 67.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2018] [Accepted: 10/12/2018] [Indexed: 01/21/2023]
Abstract
Liability to alcohol dependence (AD) is heritable, but little is known about its complex polygenic architecture or its genetic relationship with other disorders. To discover loci associated with AD and characterize the relationship between AD and other psychiatric and behavioral outcomes, we carried out the largest genome-wide association study to date of DSM-IV-diagnosed AD. Genome-wide data on 14,904 individuals with AD and 37,944 controls from 28 case-control and family-based studies were meta-analyzed, stratified by genetic ancestry (European, n = 46,568; African, n = 6,280). Independent, genome-wide significant effects of different ADH1B variants were identified in European (rs1229984; P = 9.8 × 10-13) and African ancestries (rs2066702; P = 2.2 × 10-9). Significant genetic correlations were observed with 17 phenotypes, including schizophrenia, attention deficit-hyperactivity disorder, depression, and use of cigarettes and cannabis. The genetic underpinnings of AD only partially overlap with those for alcohol consumption, underscoring the genetic distinction between pathological and nonpathological drinking behaviors.
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Affiliation(s)
- Raymond K Walters
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Renato Polimanti
- Department of Psychiatry, Yale School of Medicine and Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Emma C Johnson
- Washington University School of Medicine, Department of Psychiatry, St. Louis, MO, USA
| | - Jeanette N McClintick
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Mark J Adams
- University of Edinburgh, Division of Psychiatry, Edinburgh, UK
| | - Amy E Adkins
- Department of Psychology & College Behavioral and Emotional Health Institute, Virginia Commonwealth University, Richmond, VA, USA
| | - Fazil Aliev
- Virginia Commonwealth University, Department of Psychology, Richmond, VA, USA
| | - Silviu-Alin Bacanu
- Virginia Commonwealth University Alcohol Research Center; Virginia Institute for Psychiatric and Behavioral Genetics; Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Anthony Batzler
- Mayo Clinic, Psychiatric Genomics and Pharmacogenomics Program, Rochester, MN, USA
| | - Sarah Bertelsen
- Icahn School of Medicine at Mount Sinai, Department of Neuroscience, New York, NY, USA
| | - Joanna M Biernacka
- Mayo Clinic, Department of Health Sciences Research, and Department of Psychiatry and Psychology, Rochester, MN, USA
| | - Tim B Bigdeli
- Department of Psychiatry and Behavioral Sciences, State University of New York Downstate Medical Center, Brooklyn, NY, USA
| | - Li-Shiun Chen
- Washington University School of Medicine, Department of Psychiatry, St. Louis, MO, USA
| | - Toni-Kim Clarke
- University of Edinburgh, Division of Psychiatry, Edinburgh, UK
| | - Yi-Ling Chou
- Washington University School of Medicine, Department of Psychiatry, St. Louis, MO, USA
| | - Franziska Degenhardt
- Institute of Human Genetics, University of Bonn; and Department of Genomics, Life & Brain Center, University of Bonn, Bonn, Germany
| | - Anna R Docherty
- University of Utah, Department of Psychiatry, Salt Lake City, UT, USA
| | - Alexis C Edwards
- Virginia Commonwealth University, Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Richmond, VA, USA
| | | | - Jerome C Foo
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Louis Fox
- Washington University School of Medicine, Department of Psychiatry, St. Louis, MO, USA
| | - Josef Frank
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Ina Giegling
- Martin-Luther-University Halle-Wittenberg, Department of Psychiatry, Psychotherapy and Psychosomatics, Halle, Germany
| | - Scott Gordon
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Laura M Hack
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Annette M Hartmann
- Martin-Luther-University Halle-Wittenberg, Department of Psychiatry, Psychotherapy and Psychosomatics, Halle, Germany
| | - Sarah M Hartz
- Washington University School of Medicine, Department of Psychiatry, St. Louis, MO, USA
| | - Stefanie Heilmann-Heimbach
- Institute of Human Genetics, University of Bonn; and Department of Genomics, Life & Brain Center, University of Bonn, Bonn, Germany
| | - Stefan Herms
- Institute of Human Genetics, University of Bonn; and Department of Genomics, Life & Brain Center, University of Bonn, Bonn, Germany
- Human Genomics Research Group, Department of Biomedicine, University of Basel Institute of Medical Genetics and Pathology, University Hospital Basel, Basel, Switzerland
| | | | - Per Hoffmann
- Institute of Human Genetics, University of Bonn; and Department of Genomics, Life & Brain Center, University of Bonn, Bonn, Germany
- Human Genomics Research Group, Department of Biomedicine, University of Basel Institute of Medical Genetics and Pathology, University Hospital Basel, Basel, Switzerland
| | - Jouke Jan Hottenga
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | | | - Mervi Alanne-Kinnunen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Bettina Konte
- Martin-Luther-University Halle-Wittenberg, Department of Psychiatry, Psychotherapy and Psychosomatics, Halle, Germany
| | - Jari Lahti
- Helsinki Collegium for Advanced Studies, University of Helsinki, Helsinki, Finland
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | | | - Dongbing Lai
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Lannie Ligthart
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Anu Loukola
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Brion S Maher
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Hamdi Mbarek
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Andrew M McIntosh
- University of Edinburgh, Division of Psychiatry, Centre for Cognitive Ageing and Cognitive Epidemiology, Edinburgh, UK
| | - Matthew B McQueen
- Department of Integrative Physiology, University of Colorado Boulder, Boulder, CO, USA
| | - Jacquelyn L Meyers
- Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, NY, USA
| | - Yuri Milaneschi
- Department of Psychiatry, Amsterdam Public Health Research Institute, VU University Medical Center/GGz inGeest, Amsterdam, The Netherlands
| | - Teemu Palviainen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - John F Pearson
- Biostatistics and Computational Biology Unit, University of Otago, Christchurch, New Zealand
| | - Roseann E Peterson
- Virginia Commonwealth University, Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Richmond, VA, USA
| | - Samuli Ripatti
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Euijung Ryu
- Mayo Clinic, Department of Health Sciences Research, Rochester, MN, USA
| | - Nancy L Saccone
- Washington University School of Medicine, Department of Genetics, St. Louis, MO, USA
| | - Jessica E Salvatore
- Virginia Commonwealth University, Department of Psychology, Richmond, VA, USA
- Virginia Commonwealth University, Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Richmond, VA, USA
| | - Sandra Sanchez-Roige
- University of California San Diego, Department of Psychiatry, San Diego, CA, USA
| | | | - Richard Sherva
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA
| | - Fabian Streit
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Jana Strohmaier
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Nathaniel Thomas
- Department of Psychology & College Behavioral and Emotional Health Institute, Virginia Commonwealth University, Richmond, VA, USA
| | - Jen-Chyong Wang
- Icahn School of Medicine at Mount Sinai, Department of Neuroscience, New York, NY, USA
| | - Bradley T Webb
- Virginia Commonwealth University Alcohol Research Center; Virginia Institute for Psychiatric and Behavioral Genetics; Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Robbee Wedow
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Sociology, Harvard University, Cambridge, MA, USA
| | - Leah Wetherill
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Amanda G Wills
- University of Colorado School of Medicine, Department of Pharmacology, Aurora, CO, USA
| | - Jason D Boardman
- Institute of Behavioral Science and Department of Sociology, University of Colorado, Boulder, CO, USA
| | - Danfeng Chen
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Doo-Sup Choi
- Mayo Clinic, Department of Molecular Pharmacology and Experimental Therapeutics, Rochester, MN, USA
| | - William E Copeland
- Duke University Medical Center, Department of Psychiatry and Behavioral Sciences, Durham, NC, USA
| | - Robert C Culverhouse
- Washington University School of Medicine, Department of Medicine and Division of Biostatistics, St. Louis, MO, USA
| | - Norbert Dahmen
- Department of Psychiatry, University of Mainz, Mainz, Germany
| | - Louisa Degenhardt
- National Drug and Alcohol Research Centre, University of New South Wales, Sydney, New South Wales, Australia
| | | | | | - Mark A Frye
- Mayo Clinic, Department of Psychiatry and Psychology, Rochester, MN, USA
| | - Wolfgang Gäbel
- Department of Psychiatry and Psychotherapy, University of Düsseldorf, Düsseldorf, Germany
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Marcus Ising
- Max-Planck-Institute of Psychiatry, Munich, Germany
| | - Margaret Keyes
- University of Minnesota, Department of Psychology, Minneapolis, MN, USA
| | - Falk Kiefer
- Department of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - John Kramer
- University of Iowa Roy J and Lucille A Carver College of Medicine, Department of Psychiatry, Iowa City, IA, USA
| | - Samuel Kuperman
- University of Iowa Roy J and Lucille A Carver College of Medicine, Department of Psychiatry, Iowa City, IA, USA
| | | | - Michael T Lynskey
- Addictions Department, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Wolfgang Maier
- Department of Psychiatry, University of Bonn, Bonn, Germany
| | - Karl Mann
- Department of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | | | - Bertram Müller-Myhsok
- Department of Statistical Genetics, Max-Planck-Institute of Psychiatry, Munich, Germany
| | - Alison D Murray
- The Institute of Medical Sciences, Aberdeen Biomedical Imaging Centre, University of Aberdeen, Aberdeen, UK
| | - John I Nurnberger
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Aarno Palotie
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Department of Medicine, Department of Neurology and Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Ulrich Preuss
- Martin-Luther-University Halle-Wittenberg, Department of Psychiatry, Psychotherapy and Psychosomatics, Halle, Germany
- Vitos Hospital Herborn, Department of Psychiatry and Psychotherapy, Herborn, Germany
| | - Katri Räikkönen
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | | | - Monika Ridinger
- Department of Psychiatry and Psychotherapy, University of Regensburg Psychiatric Health Care Aargau, Regensburg, Germany
| | - Norbert Scherbaum
- LVR-Hospital Essen, Department of Psychiatry and Psychotherapy, Department of Addictive Behaviour and Addiction Medicine, Medical Faculty, University of Duisburg-Essen, Duisburg, Germany
| | - Marc A Schuckit
- University of California San Diego, Department of Psychiatry, San Diego, CA, USA
| | - Michael Soyka
- Medical Park Chiemseeblick in Bernau-Felden, Chiemsee, Germany
- Psychiatric Hospital, Ludwig-Maximilians-University, Munich, Germany
| | - Jens Treutlein
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Stephanie Witt
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Norbert Wodarz
- Department of Psychiatry and Psychotherapy, University of Regensburg, Regensburg, Germany
| | - Peter Zill
- Psychiatric Hospital, Ludwig-Maximilians-University, Munich, Germany
| | - Daniel E Adkins
- University of Utah, Department of Psychiatry, Salt Lake City, UT, USA
- University of Utah, Department of Sociology, Salt Lake City, UT, USA
| | | | - Dorret I Boomsma
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Laura J Bierut
- Washington University School of Medicine, Department of Psychiatry, St. Louis, MO, USA
| | - Sandra A Brown
- University of California San Diego, Department of Psychiatry, San Diego, CA, USA
- University of California, San Diego School of Medicine, Department of Psychology, San Diego, CA, USA
| | - Kathleen K Bucholz
- Washington University School of Medicine, Department of Psychiatry, St. Louis, MO, USA
| | - Sven Cichon
- Human Genomics Research Group, Department of Biomedicine, University of Basel Institute of Medical Genetics and Pathology, University Hospital Basel, Basel, Switzerland
| | - E Jane Costello
- Duke University Medical Center, Department of Psychiatry and Behavioral Sciences, Durham, NC, USA
| | | | | | - Danielle M Dick
- Department of Psychology & College Behavioral and Emotional Health Institute, Virginia Commonwealth University, Richmond, VA, USA
- Department of Human & Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Johan G Eriksson
- Department of General Practice and Primary Health Care, University of Helsinki, and National Institute for Health and Welfare, Helsinki, Finland
| | - Lindsay A Farrer
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA
- Departments of Neurology, Ophthalmology, Epidemiology, and Biostatistics, Boston University Schools of Medicine and Public Health, Boston, MA, USA
| | - Tatiana M Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Nathan A Gillespie
- Virginia Commonwealth University, Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Richmond, VA, USA
| | - Alison M Goate
- Icahn School of Medicine at Mount Sinai, Department of Neuroscience, New York, NY, USA
| | - David Goldman
- NIH/NIAAA, Laboratory of Neurogenetics, Bethesda, MD, USA
- NIH/NIAAA, Office of the Clinical Director, Bethesda, MD, USA
| | - Richard A Grucza
- Washington University School of Medicine, Department of Psychiatry, St. Louis, MO, USA
| | - Dana B Hancock
- Center for Omics Discovery and Epidemiology, Behavioral Health Research Division, RTI International, Research Triangle Park, NC, USA
| | - Kathleen Mullan Harris
- Department of Sociology and Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Andrew C Heath
- Washington University School of Medicine, Department of Psychiatry, St. Louis, MO, USA
| | - Victor Hesselbrock
- University of Connecticut School of Medicine, Department of Psychiatry, Farmington, CT, USA
| | - John K Hewitt
- University of Colorado Boulder, Institute for Behavioral Genetics, Boulder, CO, USA
| | | | | | - William Iacono
- University of Minnesota, Department of Psychology, Minneapolis, MN, USA
| | - Eric O Johnson
- RTI International, Fellows Program, Research Triangle Park, NC, USA
| | - Jaakko A Kaprio
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Victor M Karpyak
- Mayo Clinic, Department of Psychiatry and Psychology, Rochester, MN, USA
| | - Kenneth S Kendler
- Virginia Commonwealth University Alcohol Research Center; Virginia Institute for Psychiatric and Behavioral Genetics; Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Henry R Kranzler
- University of Pennsylvania Perelman School of Medicine, Center for Studies of Addiction, Department of Psychiatry and VISN 4 MIRECC, Crescenz VAMC, Philadelphia, PA, USA
| | - Kenneth Krauter
- University of Colorado Boulder, Department of Molecular, Cellular, and Developmental Biology, Boulder, CO, USA
| | - Paul Lichtenstein
- Department of Medical Epidemiology and Biostatistics, Karolinska Instituet, Stockholm, Sweden
| | - Penelope A Lind
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Matt McGue
- University of Minnesota, Department of Psychology, Minneapolis, MN, USA
| | - James MacKillop
- Peter Boris Centre for Addictions Research, McMaster University/St. Joseph's Healthcare Hamilton; Michael G. DeGroote Centre for Medicinal Cannabis Research, Hamilton, Ontario, Canada
| | - Pamela A F Madden
- Washington University School of Medicine, Department of Psychiatry, St. Louis, MO, USA
| | - Hermine H Maes
- Virginia Commonwealth University, Virginia Institute for Psychiatric and Behavioral Genetics, Richmond, VA, USA
| | - Patrik Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Instituet, Stockholm, Sweden
| | - Nicholas G Martin
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Grant W Montgomery
- The Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Elliot C Nelson
- Washington University School of Medicine, Department of Psychiatry, St. Louis, MO, USA
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Abraham A Palmer
- University of California San Diego, Department of Psychiatry, San Diego, CA, USA
- University of California San Diego, Institute for Genomic Medicine, San Diego, CA, USA
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Instituet, Stockholm, Sweden
| | - Brenda W J H Penninx
- Department of Psychiatry, Amsterdam Public Health Research Institute, VU University Medical Center/GGz inGeest, Amsterdam, The Netherlands
| | - Bernice Porjesz
- Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, NY, USA
| | - John P Rice
- Washington University School of Medicine, Department of Psychiatry, St. Louis, MO, USA
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Brien P Riley
- Virginia Commonwealth University Alcohol Research Center; Virginia Institute for Psychiatric and Behavioral Genetics; Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Richard Rose
- Department of Psychological & Brain Sciences, Indiana University Bloomington, Bloomington, IN, USA
| | - Dan Rujescu
- Martin-Luther-University Halle-Wittenberg, Department of Psychiatry, Psychotherapy and Psychosomatics, Halle, Germany
| | - Pei-Hong Shen
- NIH/NIAAA, Laboratory of Neurogenetics, Bethesda, MD, USA
| | - Judy Silberg
- Virginia Commonwealth University, Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Richmond, VA, USA
| | - Michael C Stallings
- University of Colorado Boulder, Institute for Behavioral Genetics, Boulder, CO, USA
| | - Ralph E Tarter
- University of Pittsburgh, School of Pharmacy, Pittsburgh, PA, USA
| | | | - Scott Vrieze
- University of Minnesota, Department of Psychology, Minneapolis, MN, USA
| | - Tamara L Wall
- University of California San Diego, Department of Psychiatry, San Diego, CA, USA
| | - John B Whitfield
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Hongyu Zhao
- Department of Biostatistics, Yale School of Public Health, Yale University, New Haven, CT, USA
| | - Benjamin M Neale
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Joel Gelernter
- Departments of Psychiatry, Genetics, and Neuroscience, Yale University School of Medicine, Veterans Affairs Connecticut Healthcare System, New Haven, CT, USA.
| | - Howard J Edenberg
- 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.
| | - Arpana Agrawal
- Washington University School of Medicine, Department of Psychiatry, St. Louis, MO, USA.
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Justice AC, Smith RV, Tate JP, McGinnis K, Xu K, Becker WC, Lee KY, Lynch K, Sun N, Concato J, Fiellin DA, Zhao H, Gelernter J, Kranzler HR. AUDIT-C and ICD codes as phenotypes for harmful alcohol use: association with ADH1B polymorphisms in two US populations. Addiction 2018; 113:2214-2224. [PMID: 29972609 PMCID: PMC6226338 DOI: 10.1111/add.14374] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2017] [Revised: 01/31/2018] [Accepted: 06/28/2018] [Indexed: 01/28/2023]
Abstract
BACKGROUND AND AIMS Longitudinal electronic health record (EHR) data offer a large-scale, untapped source of phenotypical information on harmful alcohol use. Using established, alcohol-associated variants in the gene that encodes the enzyme alcohol dehydrogenase 1B (ADH1B) as criterion standards, we compared the individual and combined validity of three longitudinal EHR-based phenotypes of harmful alcohol use: Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) trajectories; mean age-adjusted AUDIT-C; and diagnoses of alcohol use disorder (AUD). DESIGN With longitudinal EHR data from the Million Veteran Program (MVP) linked to genetic data, we used two population-specific polymorphisms in ADH1B that are associated strongly with AUD in African Americans (AAs) and European Americans (EAs): rs2066702 (Arg369Cys, AAs) and rs1229984 (Arg48His, EAs) as criterion measures. SETTING United States Department of Veterans Affairs Healthcare System. PARTICIPANTS A total of 167 721 veterans (57 677 AAs and 110 044 EAs; 92% male, mean age = 63 years) took part in this study. Data were collected from 1 October 2007 to 1 May 2017. MEASUREMENTS Using all AUDIT-C scores and AUD diagnostic codes recorded in the EHR, we calculated age-adjusted mean AUDIT-C values, longitudinal statistical trajectories of AUDIT-C scores and ICD-9/10 diagnostic groupings for AUD. FINDINGS A total of 19 793 AAs (34.3%) had one or two minor alleles at rs2066702 [minor allele frequency (MAF) = 0.190] and 6933 EAs (6.3%) had one or two minor alleles at rs1229984 (MAF = 0.032). In both populations, trajectories and age-adjusted mean AUDIT-C were correlated (r = 0.90) but, when considered separately, highest score (8+ versus 0) of age-adjusted mean AUDIT-C demonstrated a stronger association with the ADH1B variants [adjusted odds ratio (aOR) 0.54 in AAs and 0.37 in AAs] than did the highest trajectory (aOR 0.71 in AAs and 0.53 in EAs); combining AUDIT-C metrics did not improve discrimination. When age-adjusted mean AUDIT-C score and AUD diagnoses were considered together, age-adjusted mean AUDIT-C (8+ versus 0) was associated with lower odds of having the ADH1B minor allele than were AUD diagnostic codes: aOR = 0.59 versus 0.86 in AAs and 0.48 versus 0.68 in EAs. These independent associations combine to yield an even lower aOR of 0.51 for AAs and 0.33 for EAs. CONCLUSIONS The age-adjusted mean AUDIT-C score is associated more strongly with genetic polymorphisms of known risk for alcohol use disorder than are longitudinal trajectories of AUDIT-C or AUD diagnostic codes. AUD diagnostic codes modestly enhance this association.
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Affiliation(s)
- Amy C. Justice
- Yale School of Medicine, New Haven CT 06515,Veterans Affairs Connecticut Healthcare System, West Haven, CT 06516,Yale School of Public Health, New Haven CT 06515
| | - Rachel V. Smith
- University of Louisville School of Nursing, Louisville, KY 40202
| | | | - Kathleen McGinnis
- Veterans Affairs Connecticut Healthcare System, West Haven, CT 06516
| | - Ke Xu
- Yale School of Medicine, New Haven CT 06515,Veterans Affairs Connecticut Healthcare System, West Haven, CT 06516
| | - William C. Becker
- Yale School of Medicine, New Haven CT 06515,Veterans Affairs Connecticut Healthcare System, West Haven, CT 06516
| | - Kuang-Yao Lee
- Department of Statistical Science, Temple University, Philadelphia, PA 19122
| | - Kevin Lynch
- VISN 4 MIRECC, Crescenz VAMC, Philadelphia, PA 19104,University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104
| | - Ning Sun
- Yale School of Medicine, New Haven CT 06515,Yale School of Public Health, New Haven CT 06515
| | - John Concato
- Yale School of Medicine, New Haven CT 06515,Veterans Affairs Connecticut Healthcare System, West Haven, CT 06516
| | - David A. Fiellin
- Yale School of Medicine, New Haven CT 06515,Yale School of Public Health, New Haven CT 06515
| | - Hongyu Zhao
- Yale School of Medicine, New Haven CT 06515,Yale School of Public Health, New Haven CT 06515
| | - Joel Gelernter
- Yale School of Medicine, New Haven CT 06515,Veterans Affairs Connecticut Healthcare System, West Haven, CT 06516
| | - Henry R. Kranzler
- VISN 4 MIRECC, Crescenz VAMC, Philadelphia, PA 19104,University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104
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Edwards AC, Deak JD, Gizer IR, Lai D, Chatzinakos C, Wilhelmsen KP, Lindsay J, Heron J, Hickman M, Webb BT, Bacanu SA, Foroud TM, Kendler KS, Dick DM, Schuckit MA. Meta-Analysis of Genetic Influences on Initial Alcohol Sensitivity. Alcohol Clin Exp Res 2018; 42:2349-2359. [PMID: 30276832 PMCID: PMC6286211 DOI: 10.1111/acer.13896] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2018] [Accepted: 09/25/2018] [Indexed: 12/12/2022]
Abstract
BACKGROUND Previous studies indicate that low initial sensitivity to alcohol may be a risk factor for later alcohol misuse. Evidence suggests that initial sensitivity is influenced by genetic factors, but few molecular genetic studies have been reported. METHODS We conducted a meta-analysis of 2 population-based genome-wide association studies of the Self-Rating of the Effects of Alcohol scale. Our final sample consisted of 7,339 individuals (82.3% of European descent; 59.2% female) who reported having used alcohol at least 5 times. In addition, we estimated single nucleotide polymorphism (SNP)-based heritability and conducted a series of secondary aggregate genetic analyses. RESULTS No individual locus reached genome-wide significance. Gene and set based analyses, both overall and using tissue-specific expression data, yielded largely null results, and genes previously implicated in alcohol problems and consumption were overall not associated with initial sensitivity. Only 1 gene set, related to hormone signaling and including core clock genes, survived correction for multiple testing. A meta-analysis of SNP-based heritability resulted in a modest estimate of h SNP 2 = 0.19 (SE = 0.10), though this was driven by 1 sample (N = 3,683, h SNP 2 = 0.36, SE = 0.14, p = 0.04). No significant genetic correlations with other relevant outcomes were observed. CONCLUSIONS Findings yielded only modest support for a genetic component underlying initial alcohol sensitivity. Results suggest that its biological underpinnings may diverge somewhat from that of other alcohol outcomes and may be related to core clock genes or other aspects of hormone signaling. Larger samples, ideally of prospectively assessed samples, are likely necessary to improve gene identification efforts and confirm the current findings.
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Affiliation(s)
- Alexis C. Edwards
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, US
| | - Joseph D. Deak
- Department of Psychological Sciences, University of Missouri, Columbia, MO, US
| | - Ian R. Gizer
- Department of Psychological Sciences, University of Missouri, Columbia, MO, US
| | - Dongbing Lai
- Department of Medical and Molecular Genetics, Indiana University, Indianapolis, IN, US
| | - Chris Chatzinakos
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, US
| | - Kirk P. Wilhelmsen
- Departments of Neurology and Genetics, University of North Carolina, Chapel Hill, NC, US
| | - Jonathan Lindsay
- Department of Pharmacology and Toxicology, Virginia Commonwealth University, Richmond, VA, US
| | - Jon Heron
- Population Health Sciences, University of Bristol, Bristol, UK
| | - Matthew Hickman
- Population Health Sciences, University of Bristol, Bristol, UK
| | - Bradley T. Webb
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, US
| | - Silviu-Alin Bacanu
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, US
| | - Tatiana M. Foroud
- Department of Medical and Molecular Genetics, Indiana University, Indianapolis, IN, US
| | - Kenneth S. Kendler
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, US
| | - Danielle M. Dick
- Department of Psychology, Virginia Commonwealth University, Richmond, VA, US
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, US
- College Behavioral and Emotional Health Institute, Virginia Commonwealth University, Richmond, VA, US
| | - Marc A. Schuckit
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, US
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Harper J, Malone SM, Iacono WG. Conflict-related medial frontal theta as an endophenotype for alcohol use disorder. Biol Psychol 2018; 139:25-38. [PMID: 30300674 DOI: 10.1016/j.biopsycho.2018.10.002] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2018] [Revised: 09/19/2018] [Accepted: 10/01/2018] [Indexed: 12/28/2022]
Abstract
Diminished cognitive control in alcohol use disorder (AUD) is thought to be mediated by prefrontal cortex circuitry dysregulation. Research testing the relationship between AUD and specific cognitive control psychophysiological correlates, such as medial frontal (MF) theta-band EEG power, is scarce, and the etiology of this relationship is largely unknown. The current report tested relationship between pathological alcohol use through young adulthood and reduced conflict-related theta at age 29 in a large prospective population-based twin sample. Greater lifetime AUD symptomatology was associated with reduced MF theta power during response conflict, but not alpha-band visual attention processing. Follow-up analyses using cotwin control analysis and biometric modeling suggested that genetic influences, and not the consequences of sustained AUD symptomatology, explained the theta-AUD association. Results provide strong evidence that AUD is genetically related to diminished conflict-related MF theta, and advance MF theta as a promising electrophysiological correlate of AUD-related dysfunctional frontal circuitry.
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Affiliation(s)
- Jeremy Harper
- Department of Psychology, University of Minnesota, USA.
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67
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Prytkova I, Goate A, Hart RP, Slesinger PA. Genetics of Alcohol Use Disorder: A Role for Induced Pluripotent Stem Cells? Alcohol Clin Exp Res 2018; 42:1572-1590. [PMID: 29897633 PMCID: PMC6120805 DOI: 10.1111/acer.13811] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2018] [Accepted: 06/04/2018] [Indexed: 12/13/2022]
Abstract
Alcohol use disorder (AUD) affects millions of people and costs nearly 250 billion dollars annually. Few effective FDA-approved treatments exist, and more are needed. AUDs have a strong heritability, but only a few genes have been identified with a large effect size on disease phenotype. Genomewide association studies (GWASs) have identified common variants with low effect sizes, most of which are in noncoding regions of the genome. Animal models frequently fail to recapitulate key molecular features of neuropsychiatric disease due to the polygenic nature of the disease, partial conservation of coding regions, and significant disparity in noncoding regions. By contrast, human induced pluripotent stem cells (hiPSCs) derived from patients provide a powerful platform for evaluating genes identified by GWAS and modeling complex interactions in the human genome. hiPSCs can be differentiated into a wide variety of human cells, including neurons, glia, and hepatic cells, which are compatible with numerous functional assays and genome editing techniques. In this review, we focus on current applications and future directions of patient hiPSC-derived central nervous system cells for modeling AUDs in addition to highlighting successful applications of hiPSCs in polygenic neuropsychiatric diseases.
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Affiliation(s)
- Iya Prytkova
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA
| | - Alison Goate
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA
- Ronald M. Loeb Center for Alzheimer’s disease, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
| | - Ronald P. Hart
- Department of Cell Biology and Neuroscience, Rutgers University, 604 Allison Road, Piscataway NJ 08854, USA
| | - Paul A. Slesinger
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA
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68
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Deak JD, Miller AP, Gizer IR. Genetics of alcohol use disorder: a review. Curr Opin Psychol 2018; 27:56-61. [PMID: 30170251 DOI: 10.1016/j.copsyc.2018.07.012] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2018] [Revised: 07/25/2018] [Accepted: 07/31/2018] [Indexed: 01/13/2023]
Abstract
Alcohol use disorder (AUD) represents a significant and ongoing public health concern with 12-month prevalence estimates of ∼5.6%. Quantitative genetic studies suggest a heritability of approximately 50% for AUD, and as a result, significant efforts have been made to identify specific variation within the genome related to the etiology of AUD. Given the limited number of replicable findings that have emerged from genome-wide linkage and candidate gene association studies, more recent efforts have focused on the use of genome-wide association studies (GWAS). These studies have suggested that hundreds of variants across the genome, most of small effect (R2 < 0.002), contribute to the genetic etiology of AUD. The present review describes the initial, though limited, successes of GWAS to identify loci related to risk for AUD as well as other etiologically relevant traits (e.g. alcohol consumption). In addition, 'Post-GWAS' approaches that rely on GWAS data to estimate the heritability and co-heritability of traits, test causal relations between traits, and aid in gene discovery are described. Together, the described research findings illustrate the importance of molecular genetic research on AUD as we seek to better understand the mechanisms through which genetic variation leads to increased risk for AUD.
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Affiliation(s)
- Joseph D Deak
- Department of Psychological Sciences, University of Missouri, 210 McAlester Hall, Columbia, MO 65211, USA
| | - Alex P Miller
- Department of Psychological Sciences, University of Missouri, 210 McAlester Hall, Columbia, MO 65211, USA
| | - Ian R Gizer
- Department of Psychological Sciences, University of Missouri, 210 McAlester Hall, Columbia, MO 65211, USA.
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Abstract
PURPOSE OF REVIEW With the advent of the genome-wide association study (GWAS), our understanding of the genetics of addiction has made significant strides forward. Here, we summarize genetic loci containing variants identified at genome-wide statistical significance (P < 5 × 10-8) and independently replicated, review evidence of functional or regulatory effects for GWAS-identified variants, and outline multi-omics approaches to enhance discovery and characterize addiction loci. RECENT FINDINGS Replicable GWAS findings span 11 genetic loci for smoking, eight loci for alcohol, and two loci for illicit drugs combined and include missense functional variants and noncoding variants with regulatory effects in human brain tissues traditionally viewed as addiction-relevant (e.g., prefrontal cortex [PFC]) and, more recently, tissues often overlooked (e.g., cerebellum). GWAS analyses have discovered several novel, replicable variants contributing to addiction. Using larger sample sizes from harmonized datasets and new approaches to integrate GWAS with multiple 'omics data across human brain tissues holds great promise to significantly advance our understanding of the biology underlying addiction.
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Affiliation(s)
- Dana B Hancock
- Behavioral and Urban Health Program, Behavioral Health and Criminal Justice Division, RTI International, 3040 East Cornwallis Road, P. O. Box 12194, Research Triangle Park, NC, 27709, USA.
| | - Christina A Markunas
- Behavioral and Urban Health Program, Behavioral Health and Criminal Justice Division, RTI International, 3040 East Cornwallis Road, P. O. Box 12194, Research Triangle Park, NC, 27709, USA
| | - Laura J Bierut
- Department of Psychiatry, Washington University, St. Louis, MO, USA
| | - Eric O Johnson
- Fellow Program and Behavioral Health and Criminal Justice Division, RTI International, Research Triangle Park, NC, USA
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70
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Savage JE, Salvatore JE, Aliev F, Edwards AC, Hickman M, Kendler KS, Macleod J, Latvala A, Loukola A, Kaprio J, Rose RJ, Chan G, Hesselbrock V, Webb BT, Adkins A, Bigdeli TB, Riley BP, Dick DM. Polygenic Risk Score Prediction of Alcohol Dependence Symptoms Across Population-Based and Clinically Ascertained Samples. Alcohol Clin Exp Res 2018; 42:520-530. [PMID: 29405378 PMCID: PMC5832589 DOI: 10.1111/acer.13589] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2017] [Accepted: 12/11/2017] [Indexed: 11/28/2022]
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.
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Affiliation(s)
- Jeanne E. Savage
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University
| | - Jessica E. Salvatore
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University
- Department of Psychology, Virginia Commonwealth University
| | - Fazil Aliev
- Department of Psychology, Virginia Commonwealth University
- Faculty of Business, Karabuk University, Turkey
| | - Alexis C. Edwards
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University
- Department of Psychiatry, Virginia Commonwealth University
| | - Matthew Hickman
- School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Kenneth S. Kendler
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University
- Department of Psychiatry, Virginia Commonwealth University
- Department of Human and Molecular Genetics, Virginia Commonwealth University
| | - John Macleod
- School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Antti Latvala
- Institute for Molecular Medicine FIMM, University of Helsinki
- Department of Public Health, University of Helsinki
| | - Anu Loukola
- Institute for Molecular Medicine FIMM, University of Helsinki
- Department of Public Health, University of Helsinki
| | - Jaakko Kaprio
- Institute for Molecular Medicine FIMM, University of Helsinki
- Department of Public Health, University of Helsinki
| | - Richard J. Rose
- Department of Psychological and Brain Sciences, Indiana University
| | - Grace Chan
- Department of Psychiatry, University of Connecticut Health Center
| | | | - Bradley T. Webb
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University
- Department of Psychiatry, Virginia Commonwealth University
| | - Amy Adkins
- Department of Psychology, Virginia Commonwealth University
- College Behavioral and Emotional Health Institute (COBE), Virginia Commonwealth University
| | - Tim B. Bigdeli
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University
- Department of Psychiatry, Virginia Commonwealth University
| | - Brien P. Riley
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University
- Department of Human and Molecular Genetics, Virginia Commonwealth University
| | - Danielle M. Dick
- Department of Psychology, Virginia Commonwealth University
- Department of Human and Molecular Genetics, Virginia Commonwealth University
- College Behavioral and Emotional Health Institute (COBE), Virginia Commonwealth University
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