1
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Zhou H, Gelernter J. Human genetics and epigenetics of alcohol use disorder. J Clin Invest 2024; 134:e172885. [PMID: 39145449 PMCID: PMC11324314 DOI: 10.1172/jci172885] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/16/2024] Open
Abstract
Alcohol use disorder (AUD) is a prominent contributor to global morbidity and mortality. Its complex etiology involves genetics, epigenetics, and environmental factors. We review progress in understanding the genetics and epigenetics of AUD, summarizing the key findings. Advancements in technology over the decades have elevated research from early candidate gene studies to present-day genome-wide scans, unveiling numerous genetic and epigenetic risk factors for AUD. The latest GWAS on more than one million participants identified more than 100 genetic variants, and the largest epigenome-wide association studies (EWAS) in blood and brain samples have revealed tissue-specific epigenetic changes. Downstream analyses revealed enriched pathways, genetic correlations with other traits, transcriptome-wide association in brain tissues, and drug-gene interactions for AUD. We also discuss limitations and future directions, including increasing the power of GWAS and EWAS studies as well as expanding the diversity of populations included in these analyses. Larger samples, novel technologies, and analytic approaches are essential; these include whole-genome sequencing, multiomics, single-cell sequencing, spatial transcriptomics, deep-learning prediction of variant function, and integrated methods for disease risk prediction.
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Affiliation(s)
- Hang Zhou
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut, USA
- Department of Biomedical Informatics and Data Science
- Center for Brain and Mind Health
| | - Joel Gelernter
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut, USA
- Department of Genetics, and
- Department of Neuroscience, Yale School of Medicine, New Haven, Connecticut, USA
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2
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Bountress KE, Cusack SE, Hawn SE, Grotzinger A, Bustamante D, Kirkpatrick RM, Edenberg HJ, Amstadter AB. Genetic associations between alcohol phenotypes and life satisfaction: a genomic structural equation modelling approach. Sci Rep 2023; 13:13443. [PMID: 37596344 PMCID: PMC10439217 DOI: 10.1038/s41598-023-40199-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 08/07/2023] [Indexed: 08/20/2023] Open
Abstract
Alcohol use (i.e., quantity, frequency) and alcohol use disorder (AUD) are common, associated with adverse outcomes, and genetically-influenced. Genome-wide association studies (GWAS) identified genetic loci associated with both. AUD is positively genetically associated with psychopathology, while alcohol use (e.g., drinks per week) is negatively associated or NS related to psychopathology. We wanted to test if these genetic associations extended to life satisfaction, as there is an interest in understanding the associations between psychopathology-related traits and constructs that are not just the absence of psychopathology, but positive outcomes (e.g., well-being variables). Thus, we used Genomic Structural Equation Modeling (gSEM) to analyze summary-level genomic data (i.e., effects of genetic variants on constructs of interest) from large-scale GWAS of European ancestry individuals. Results suggest that the best-fitting model is a Bifactor Model, in which unique alcohol use, unique AUD, and common alcohol factors are extracted. The genetic correlation (rg) between life satisfaction-AUD specific factor was near zero, the rg with the alcohol use specific factor was positive and significant, and the rg with the common alcohol factor was negative and significant. Findings indicate that life satisfaction shares genetic etiology with typical alcohol use and life dissatisfaction shares genetic etiology with heavy alcohol use.
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Affiliation(s)
- Kaitlin E Bountress
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, 800 E. Leigh St. Biotech One Suite 101, Richmond, VA, 23219, USA.
| | - Shannon E Cusack
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, 800 E. Leigh St. Biotech One Suite 101, Richmond, VA, 23219, USA
| | - Sage E Hawn
- Department of Psychology, Old Dominion University, Norfolk, USA
| | - Andrew Grotzinger
- Institute for Behavior Genetics, Behavioral, Psychiatric, and Statistical Genetics, University of Colorado Boulder, Boulder, USA
| | - Daniel Bustamante
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, 800 E. Leigh St. Biotech One Suite 101, Richmond, VA, 23219, USA
| | - Robert M Kirkpatrick
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, 800 E. Leigh St. Biotech One Suite 101, Richmond, VA, 23219, USA
| | | | - Ananda B Amstadter
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, 800 E. Leigh St. Biotech One Suite 101, Richmond, VA, 23219, USA
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3
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Interplay between genetic risk and the parent environment in adolescence and substance use in young adulthood: A TRAILS study. Dev Psychopathol 2023; 35:396-409. [PMID: 36914285 DOI: 10.1017/s095457942100081x] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Many adolescents start using tobacco, alcohol, and cannabis. Genetic vulnerability, parent characteristics in young adolescence, and interaction (GxE) and correlation (rGE) between these factors could contribute to the development of substance use. Using prospective data from the TRacking Adolescent Individuals' Lives Survey (TRAILS; N = 1,645), we model latent parent characteristics in young adolescence to predict young adult substance use. Polygenic scores (PGS) are created based on genome-wide association studies (GWAS) for smoking, alcohol use, and cannabis use. Using structural equation modeling we model the direct, GxE, and rGE effects of parent factors and PGS on young adult smoking, alcohol use, and cannabis initiation. The PGS, parental involvement, parental substance use, and parent-child relationship quality predicted smoking. There was GxE such that the PGS amplified the effect of parental substance use on smoking. There was rGE between all parent factors and the smoking PGS. Alcohol use was not predicted by genetic or parent factors, nor by interplay. Cannabis initiation was predicted by the PGS and parental substance use, but there was no GxE or rGE. Genetic risk and parent factors are important predictors of substance use and show GxE and rGE in smoking. These findings can act as a starting point for identifying people at risk.
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4
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Chang XW, Sun Y, Muhai JN, Li YY, Chen Y, Lu L, Chang SH, Shi J. Common and distinguishing genetic factors for substance use behavior and disorder: an integrated analysis of genomic and transcriptomic studies from both human and animal studies. Addiction 2022; 117:2515-2529. [PMID: 35491750 DOI: 10.1111/add.15908] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/30/2021] [Accepted: 04/04/2022] [Indexed: 11/30/2022]
Abstract
BACKGROUND AND AIMS Genomic and transcriptomic findings greatly broaden the biological knowledge regarding substance use. However, systematic convergence and comparison evidence of genome-wide findings is lacking for substance use. Here, we combined all the genome-wide findings from both substance use behavior and disorder (SUBD) and identified common and distinguishing genetic factors for different SUBDs. METHODS Systemic literature search for genome-wide association (GWAS) and RNA-seq studies of alcohol/nicotine/drug use behavior (partially meets or not reported diagnostic criteria) and alcohol use behavior and disorder (AUBD), nicotine use behavior and disorder (NUBD) and drug use behavior and disorder (DUBD) was performed using PubMed and the GWAS catalog. Drug use was focused upon cannabis, opioid, cocaine and methamphetamine use. GWAS studies required case-control or case/cohort samples. RNA-seq studies were based on brain tissues. The genes which contained significant single nucleotide polymorphism (P ≤ 1 × 10-6 ) in GWAS and reported as significant in RNA-seq studies were extracted. Pathway enrichment was performed by using Metascape. Gene interaction networks were identified by using the Protein Interaction Network Analysis database. RESULTS Total SUBD-related 2910 genes were extracted from 75 GWAS studies (2 773 889 participants) and 17 RNA-seq studies. By overlapping the genes and pathways of AUBD, NUBD and DUBD, four shared genes (CACNB2, GRIN2B, PLXDC2 and PKNOX2), four shared pathways [two Gene Ontology (GO) terms of 'modulation of chemical synaptic transmission', 'regulation of trans-synaptic signaling', two Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of 'dopaminergic synapse', 'cocaine addiction'] were identified (significantly higher than random, P < 1 × 10-5 ). The top shared KEGG pathways (Benjamini-Hochberg-corrected P-value < 0.05) in the pairwise comparison of AUBD versus DUBD, NUBD versus DUBD, AUBD versus NUBD were 'Epstein-Barr virus infection', 'protein processing in endoplasmic reticulum' and 'neuroactive ligand-receptor interaction', respectively. We also identified substance-specific genetic factors: i.e. ADH1B and ALDH2 were unique for AUBD, while CHRNA3 and CHRNA4 were unique for NUBD. CONCLUSIONS This systematic review identifies the shared and unique genes and pathways for alcohol, nicotine and drug use behaviors and disorders at the genome-wide level and highlights critical biological processes for the common and distinguishing vulnerability of substance use behaviors and disorders.
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Affiliation(s)
- Xiang-Wen Chang
- Department of Pharmacology, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China.,National Institute on Drug Dependence, Peking University, Beijing, China
| | - Yan Sun
- Department of Pharmacology, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China.,National Institute on Drug Dependence, Peking University, Beijing, China
| | - Jia-Na Muhai
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Yang-Yang Li
- Department of Pharmacology, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China.,National Institute on Drug Dependence, Peking University, Beijing, China
| | - Yun Chen
- Department of Pharmacology, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China.,National Institute on Drug Dependence, Peking University, Beijing, China
| | - Lin Lu
- National Institute on Drug Dependence, Peking University, Beijing, China.,Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Su-Hua Chang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Jie Shi
- National Institute on Drug Dependence, Peking University, Beijing, China.,Beijing Key Laboratory of Drug Dependence Research, Peking University, Beijing, China.,The State Key Laboratory of Natural and Biomimetic Drugs, Peking University, Beijing, China.,The Key Laboratory for Neuroscience of the Ministry of Education and Health, Peking University, Beijing, China
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Parker CC, Philip VM, Gatti DM, Kasparek S, Kreuzman AM, Kuffler L, Mansky B, Masneuf S, Sharif K, Sluys E, Taterra D, Taylor WM, Thomas M, Polesskaya O, Palmer AA, Holmes A, Chesler EJ. Genome-wide association mapping of ethanol sensitivity in the Diversity Outbred mouse population. Alcohol Clin Exp Res 2022; 46:941-960. [PMID: 35383961 DOI: 10.1111/acer.14825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Revised: 03/04/2022] [Accepted: 03/30/2022] [Indexed: 12/01/2022]
Abstract
BACKGROUND A strong predictor for the development of alcohol use disorder (AUD) is altered sensitivity to the intoxicating effects of alcohol. Individual differences in the initial sensitivity to alcohol are controlled in part by genetic factors. Mice offer a powerful tool to elucidate the genetic basis of behavioral and physiological traits relevant to AUD, but conventional experimental crosses have only been able to identify large chromosomal regions rather than specific genes. Genetically diverse, highly recombinant mouse populations make it possible to observe a wider range of phenotypic variation, offer greater mapping precision, and thus increase the potential for efficient gene identification. METHODS We have taken advantage of the Diversity Outbred (DO) mouse population to identify and precisely map quantitative trait loci (QTL) associated with ethanol sensitivity. We phenotyped 798 male J:DO mice for three measures of ethanol sensitivity: ataxia, hypothermia, and loss of the righting response. We used high-density MegaMUGA and GigaMUGA to obtain genotypes ranging from 77,808 to 143,259 SNPs. We also performed RNA sequencing in striatum to map expression QTLs and identify gene expression-trait correlations. We then applied a systems genetic strategy to identify narrow QTLs and construct the network of correlations that exists between DNA sequence, gene expression values, and ethanol-related phenotypes to prioritize our list of positional candidate genes. RESULTS We observed large amounts of phenotypic variation with the DO population and identified suggestive and significant QTLs associated with ethanol sensitivity on chromosomes 1, 2, and 16. The implicated regions were narrow (4.5-6.9 Mb in size) and each QTL explained ~4-5% of the variance. CONCLUSIONS Our results can be used to identify alleles that contribute to AUD in humans, elucidate causative biological mechanisms, or assist in the development of novel therapeutic interventions.
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Affiliation(s)
- Clarissa C Parker
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, Vermont, USA
| | - Vivek M Philip
- Center for Computational Sciences, The Jackson Laboratory, Bar Harbor, Maine, USA
| | - Daniel M Gatti
- Center for Computational Sciences, The Jackson Laboratory, Bar Harbor, Maine, USA
| | - Steven Kasparek
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, Vermont, USA
| | - Andrew M Kreuzman
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, Vermont, USA
| | - Lauren Kuffler
- Center for Mammalian Genetics, The Jackson Laboratory, Bar Harbor, Maine, USA
| | - Benjamin Mansky
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, Vermont, USA
| | - Sophie Masneuf
- Laboratory of Behavioral and Genomic Neuroscience, NIAAA, NIH, Rockville, MD, USA
| | - Kayvon Sharif
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, Vermont, USA
| | - Erica Sluys
- Laboratory of Behavioral and Genomic Neuroscience, NIAAA, NIH, Rockville, MD, USA
| | - Dominik Taterra
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, Vermont, USA
| | - Walter M Taylor
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, Vermont, USA
| | - Mary Thomas
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, Vermont, USA
| | - Oksana Polesskaya
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,Institute for Genomic Medicine, University of California San Diego, La Jolla, California, USA
| | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,Institute for Genomic Medicine, University of California San Diego, La Jolla, California, USA
| | - Andrew Holmes
- Laboratory of Behavioral and Genomic Neuroscience, NIAAA, NIH, Rockville, MD, USA
| | - Elissa J Chesler
- Center for Mammalian Genetics, The Jackson Laboratory, Bar Harbor, Maine, USA
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Ye J, Cheng S, Chu X, Wen Y, Cheng B, Liu L, Liang C, Kafle OP, Jia Y, Wu C, Wang S, Wang X, Ning Y, Zhang F. Associations between electronic devices use and common mental traits: A gene-environment interaction model using the UK Biobank data. Addict Biol 2022; 27:e13111. [PMID: 34877740 DOI: 10.1111/adb.13111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Revised: 08/11/2021] [Accepted: 10/21/2021] [Indexed: 11/29/2022]
Abstract
BACKGROUND Electronic devices use has been reported to be associated with depression. However, limited effort has been provided to elucidate the associations between electronic devices use and mental traits in interaction with genetic factors. METHODS We first conducted an observational study consisting of 138 976-383 742 participants for TV watching, 29 636-38 599 participants for computer using and 118 61-330 985 participants for computer playing in the UK Biobank cohort. A linear regression model was used to evaluate the associations between common mental traits and electronic devices use. Subsequently, a genome-wide gene-environment interaction study (GWEIS) was performed by PLINK2.0 to estimate the interaction effects of genes and electronic devices use on the risks of the four mental traits. RESULTS In the UK Biobank cohort, significant associations were observed between electronic devices use and mental traits (all P < 1.0 × 10-9 ), including depression score (B = 0.094 for TV watching), anxiety score (B = 0.051 for TV watching), cigarette smoking (B = 0.046 for computer using) and alcohol drinking (B = 0.010 for computer playing). GWEIS identified multiple mental traits associated loci, interacting with electronic devices use, such as DCDC2 (rs115986722, P = 4.10 × 10-10 ) for anxiety score and TV watching, PRKCE (rs56181965, P = 9.64 × 10-10 ) for smoking and computer using and FRMD4A (rs56227933, P = 7.42 × 10-11 ) for depression score and computer playing. CONCLUSIONS Our findings suggested that electronic devices use was associated with common mental traits and provided new clues for understanding genetic architecture of mental traits.
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Affiliation(s)
- Jing Ye
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center Xi'an Jiaotong University Xi'an China
| | - Shiqiang Cheng
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center Xi'an Jiaotong University Xi'an China
| | - Xiaomeng Chu
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center Xi'an Jiaotong University Xi'an China
| | - Yan Wen
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center Xi'an Jiaotong University Xi'an China
| | - Bolun Cheng
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center Xi'an Jiaotong University Xi'an China
| | - Li Liu
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center Xi'an Jiaotong University Xi'an China
| | - Chujun Liang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center Xi'an Jiaotong University Xi'an China
| | - Om Prakash Kafle
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center Xi'an Jiaotong University Xi'an China
| | - Yumeng Jia
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center Xi'an Jiaotong University Xi'an China
| | - Cuiyan Wu
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center Xi'an Jiaotong University Xi'an China
| | - Sen Wang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center Xi'an Jiaotong University Xi'an China
| | - Xi Wang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center Xi'an Jiaotong University Xi'an China
| | - Yujie Ning
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center Xi'an Jiaotong University Xi'an China
| | - Feng Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center Xi'an Jiaotong University Xi'an China
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The Aldehyde Dehydrogenase ALDH2*2 Allele, Associated with Alcohol Drinking Behavior, Dates Back to Prehistoric Times. Biomolecules 2021; 11:biom11091376. [PMID: 34572589 PMCID: PMC8465343 DOI: 10.3390/biom11091376] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Revised: 09/11/2021] [Accepted: 09/15/2021] [Indexed: 01/02/2023] Open
Abstract
Human alcohol-consumption behavior is partly genetically encoded. The alcohol consumption of 987 residents in Keelung, Taiwan, was evaluated by using the Alcohol Use Disorder Identification Test (AUDIT). We assessed ~750,000 genomic variants of 71 residents who drank hazardously (AUDIT score ≥ 8) and 126 residents who did not drink in their daily lives (AUDIT score = 0), using high-density single nucleotide polymorphism (SNP) arrays. The rs671 G > A manifests the highest significance of the association with drinking behavior (Fisher’s exact P = 8.75 × 10−9). It is a pleiotropic, non-synonymous variant in the aldehyde dehydrogenase 2 (ALDH2) gene. The minor allele “A”, commonly known as ALDH2*2, is associated with non-drinkers. Intriguingly, identity-by-descent haplotypes encompassing genomic regions with a median length of 1.6 (0.6–2.0) million nucleotide bases were found in all study participants with either heterozygous or homozygous ALDH2*2 (n = 81 and 13, respectively). We also analyzed a public-domain dataset with genome-wide genotypes of 2000 participants in Guangzhou, a coastal city in Southern China. Among them, 175 participants have homozygous ALDH2*2 genotype, and again, long ALDH2*2-carrying haplotypes were found in all 175 participants without exceptions. The median length of the ALDH2*2-carrying haplotype is 1.7 (0.5–2.8) million nucleotide bases. The haplotype lengths in the Keelung and Guangzhou cohorts combined indicate that the origin of the ALDH2*2 allele dates back to 7935 (7014–9381) years ago. In conclusion, the rs671 G > A is the leading genomic variant associated with the long-term drinking behavior among residents of Keelung, Taiwan. The ALDH2*2 allele has been in Asian populations since prehistoric times.
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Clarke TK, Adams MJ, Howard DM, Xia C, Davies G, Hayward C, Campbell A, Padmanabhan S, Smith BH, Murray A, Porteous D, Deary IJ, McIntosh AM. Genetic and shared couple environmental contributions to smoking and alcohol use in the UK population. Mol Psychiatry 2021; 26:4344-4354. [PMID: 31767999 PMCID: PMC8550945 DOI: 10.1038/s41380-019-0607-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/20/2019] [Revised: 11/07/2019] [Accepted: 11/13/2019] [Indexed: 11/22/2022]
Abstract
Alcohol use and smoking are leading causes of death and disability worldwide. Both genetic and environmental factors have been shown to influence individual differences in the use of these substances. In the present study we tested whether genetic factors, modelled alongside common family environment, explained phenotypic variance in alcohol use and smoking behaviour in the Generation Scotland (GS) family sample of up to 19,377 individuals. SNP and pedigree-associated effects combined explained between 18 and 41% of the variance in substance use. Shared couple effects explained a significant amount of variance across all substance use traits, particularly alcohol intake, for which 38% of the phenotypic variance was explained. We tested whether the within-couple substance use associations were due to assortative mating by testing the association between partner polygenic risk scores in 34,987 couple pairs from the UK Biobank (UKB). No significant association between partner polygenic risk scores were observed. Associations between an individual's alcohol PRS (b = 0.05, S.E. = 0.006, p < 2 × 10-16) and smoking status PRS (b = 0.05, S.E. = 0.005, p < 2 × 10-16) were found with their partner's phenotype. In support of this, G carriers of a functional ADH1B polymorphism (rs1229984), known to be associated with greater alcohol intake, were found to consume less alcohol if they had a partner who carried an A allele at this SNP. Together these results show that the shared couple environment contributes significantly to patterns of substance use. It is unclear whether this is due to shared environmental factors, assortative mating, or indirect genetic effects. Future studies would benefit from longitudinal data and larger sample sizes to assess this further.
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Affiliation(s)
- Toni-Kim Clarke
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK.
| | - Mark J Adams
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - David M Howard
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - Charley Xia
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Gail Davies
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Archie Campbell
- Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
- Centre for Genomic and Experimental Medicine, Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Sandosh Padmanabhan
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Blair H Smith
- Division of Population and Health Genomics, University of Dundee, Dundee, UK
| | - Alison Murray
- The Institute of Medical Sciences, Aberdeen Biomedical Imaging Centre, University of Aberdeen, Aberdeen, UK
| | - David Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Ian J Deary
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Andrew M McIntosh
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
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Corpas M, Megy K, Mistry V, Metastasio A, Lehmann E. Whole Genome Interpretation for a Family of Five. Front Genet 2021; 12:535123. [PMID: 33763108 PMCID: PMC7982663 DOI: 10.3389/fgene.2021.535123] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Accepted: 02/15/2021] [Indexed: 12/19/2022] Open
Abstract
Although best practices have emerged on how to analyse and interpret personal genomes, the utility of whole genome screening remains underdeveloped. A large amount of information can be gathered from various types of analyses via whole genome sequencing including pathogenicity screening, genetic risk scoring, fitness, nutrition, and pharmacogenomic analysis. We recognize different levels of confidence when assessing the validity of genetic markers and apply rigorous standards for evaluation of phenotype associations. We illustrate the application of this approach on a family of five. By applying analyses of whole genomes from different methodological perspectives, we are able to build a more comprehensive picture to assist decision making in preventative healthcare and well-being management. Our interpretation and reporting outputs provide input for a clinician to develop a healthcare plan for the individual, based on genetic and other healthcare data.
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Affiliation(s)
- Manuel Corpas
- Cambridge Precision Medicine Limited, ideaSpace, University of Cambridge Biomedical Innovation Hub, Cambridge, United Kingdom.,Institute of Continuing Education Madingley Hall Madingley, University of Cambridge, Cambridge, United Kingdom.,Facultad de Ciencias de la Salud, Universidad Internacional de La Rioja, Madrid, Spain
| | - Karyn Megy
- Cambridge Precision Medicine Limited, ideaSpace, University of Cambridge Biomedical Innovation Hub, Cambridge, United Kingdom.,Department of Haematology, University of Cambridge & National Health Service (NHS) Blood and Transplant, Cambridge, United Kingdom
| | | | - Antonio Metastasio
- Cambridge Precision Medicine Limited, ideaSpace, University of Cambridge Biomedical Innovation Hub, Cambridge, United Kingdom.,Camden and Islington NHS Foundation Trust, London, United Kingdom
| | - Edmund Lehmann
- Cambridge Precision Medicine Limited, ideaSpace, University of Cambridge Biomedical Innovation Hub, Cambridge, United Kingdom
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10
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Oliveira PRS, de Matos LO, Araujo NM, Sant Anna HP, da Silva E Silva DA, Damasceno AKA, Martins de Carvalho L, Horta BL, Lima-Costa MF, Barreto ML, Wiers CE, Volkow ND, Brunialti Godard AL. LRRK2 Gene Variants Associated With a Higher Risk for Alcohol Dependence in Multiethnic Populations. Front Psychiatry 2021; 12:665257. [PMID: 34135785 PMCID: PMC8202767 DOI: 10.3389/fpsyt.2021.665257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Accepted: 04/12/2021] [Indexed: 11/22/2022] Open
Abstract
Background: Genetics influence the vulnerability to alcohol use disorders, and among the implicated genes, three previous studies have provided evidences for the involvement of LRRK2 in alcohol dependence (AD). LRRK2 expression is broadly dysregulated in postmortem brain from AD humans, as well as in the brain of mice with alcohol dependent-like behaviors and in a zebrafish model of alcohol preference. The aim of the present study was to evaluate the association of variants in the LRRK2 gene with AD in multiethnic populations from South and North America. Methods: Alcohol-screening questionnaires [such as CAGE and Alcohol Use Disorders Identification Test (AUDIT)] were used to determine individual risk of AD. Multivariate logistic regression analyses were done in three independent populations (898 individuals from Bambuí, Brazil; 3,015 individuals from Pelotas, Brazil; and 1,316 from the United States). Linkage disequilibrium and conditional analyses, as well as in silico functional analyses, were also conducted. Results: Four LRRK2 variants were significantly associated with AD in our discovery cohort (Bambuí): rs4768231, rs4767971, rs7307310, and rs1465527. Two of these variants (rs4768231 and rs4767971) were replicated in both Pelotas and US cohorts. The consistent association signal (at the LRRK2 locus) found in populations with different genetic backgrounds reinforces the relevance of our findings. Conclusion: Taken together, these results support the notion that genetic variants in the LRRK2 locus are risk factors for AD in humans.
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Affiliation(s)
- Pablo Rafael Silveira Oliveira
- Instituto de Biologia, Universidade Federal da Bahia, Salvador, Brazil.,Centro de Integração de Dados e Conhecimentos para Saúde, Fundação Oswaldo Cruz, Salvador, Brazil
| | - Lorena Oliveira de Matos
- Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Nathalia Matta Araujo
- Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Hanaísa P Sant Anna
- Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | | | - Andresa K Andrade Damasceno
- Instituto de Biologia, Universidade Federal da Bahia, Salvador, Brazil.,Centro de Integração de Dados e Conhecimentos para Saúde, Fundação Oswaldo Cruz, Salvador, Brazil
| | - Luana Martins de Carvalho
- Department of Psychiatry, Center for Alcohol Research in Epigenetics, University of Illinois, Chicago, IL, United States
| | - Bernardo L Horta
- Programa de Pos-Graduação em Epidemiologia, Universidade Federal de Pelotas, Pelotas, Brazil
| | | | - Mauricio Lima Barreto
- Centro de Integração de Dados e Conhecimentos para Saúde, Fundação Oswaldo Cruz, Salvador, Brazil
| | - Corinde E Wiers
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, United States
| | - Nora D Volkow
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, United States
| | - Ana Lúcia Brunialti Godard
- Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
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11
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Parker CC, Lusk R, Saba LM. Alcohol Sensitivity as an Endophenotype of Alcohol Use Disorder: Exploring Its Translational Utility between Rodents and Humans. Brain Sci 2020; 10:E725. [PMID: 33066036 PMCID: PMC7600833 DOI: 10.3390/brainsci10100725] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Revised: 10/06/2020] [Accepted: 10/09/2020] [Indexed: 12/21/2022] Open
Abstract
Alcohol use disorder (AUD) is a complex, chronic, relapsing disorder with multiple interacting genetic and environmental influences. Numerous studies have verified the influence of genetics on AUD, yet the underlying biological pathways remain unknown. One strategy to interrogate complex diseases is the use of endophenotypes, which deconstruct current diagnostic categories into component traits that may be more amenable to genetic research. In this review, we explore how an endophenotype such as sensitivity to alcohol can be used in conjunction with rodent models to provide mechanistic insights into AUD. We evaluate three alcohol sensitivity endophenotypes (stimulation, intoxication, and aversion) for their translatability across human and rodent research by examining the underlying neurobiology and its relationship to consumption and AUD. We show examples in which results gleaned from rodents are successfully integrated with information from human studies to gain insight in the genetic underpinnings of AUD and AUD-related endophenotypes. Finally, we identify areas for future translational research that could greatly expand our knowledge of the biological and molecular aspects of the transition to AUD with the broad hope of finding better ways to treat this devastating disorder.
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Affiliation(s)
- Clarissa C. Parker
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, VT 05753, USA
| | - Ryan Lusk
- Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA;
| | - Laura M. Saba
- Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA;
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12
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Mbarek H, van Beijsterveldt CEM, Jan Hottenga J, Dolan CV, Boomsma DI, Willemsen G, Vink JM. Association Between rs1051730 and Smoking During Pregnancy in Dutch Women. Nicotine Tob Res 2020; 21:835-840. [PMID: 29228387 DOI: 10.1093/ntr/ntx267] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2016] [Accepted: 12/05/2017] [Indexed: 01/09/2023]
Abstract
INTRODUCTION The common genetic variant (rs1051730) in the 15q24 nicotinic acetylcholine receptor gene cluster CHRNA5-CHRNA3-CHRNB4 was associated with smoking quantity and has been reported to be associated also with reduced ability to quit smoking in pregnant women but results were inconsistent in nonpregnant women. The aim of this study was to explore the association between rs1051730 and smoking cessation during pregnancy in a sample of Dutch women. METHODS Data on smoking during pregnancy were available from 1337 women, who ever smoked, registered at the Netherlands Twin Register (NTR). Logistic regression was used to assess evidence for the association of rs1051730 genotype on smoking during pregnancy. In a subsample of 561 women, we investigated the influence of partner's smoking. Educational attainment and year of birth were used as covariates in both analyses. RESULTS There was evidence for a significant association between having one or more T alleles of the rs1051730 polymorphism and the likelihood of smoking during pregnancy (p = .03, odds ratio = 1.28, 95% CI = 1.02 to 1.61). However, this association attenuated when adjusting for birth cohort and educational attainment (p = .37, odds ratio = 1.12, 95% CI = 0.87 to 1.43). In the subsample, smoking spouse was highly associated with smoking during pregnancy, even when educational attainment and birth cohort were included in the model. CONCLUSIONS Our results did not support a strong association between this genetic variant and smoking during pregnancy. However, a strong association was observed with the smoking behavior of the partner, regardless of the genotype of the women. IMPLICATIONS The present study emphasizes the importance of social influences like spousal smoking on the smoking behavior of pregnant women. Further research is needed to address the role of rs1051730 genetic variant in influencing smoking cessation and the interaction with important environmental factors like the smoking behavior of the partner.
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Affiliation(s)
- Hamdi Mbarek
- Department of Biological Psychology, Amsterdam Public Health research institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Catharina E M van Beijsterveldt
- Department of Biological Psychology, Amsterdam Public Health research institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Jouke Jan Hottenga
- Department of Biological Psychology, Amsterdam Public Health research institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Conor V Dolan
- Department of Biological Psychology, Amsterdam Public Health research institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Amsterdam Public Health research institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Gonneke Willemsen
- Department of Biological Psychology, Amsterdam Public Health research institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Jacqueline M Vink
- Department of Biological Psychology, Amsterdam Public Health research institute, Vrije Universiteit, Amsterdam, The Netherlands.,Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
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13
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Substance use: Interplay between polygenic risk and neighborhood environment. Drug Alcohol Depend 2020; 209:107948. [PMID: 32151880 DOI: 10.1016/j.drugalcdep.2020.107948] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/23/2019] [Revised: 02/14/2020] [Accepted: 02/26/2020] [Indexed: 11/23/2022]
Abstract
BACKGROUND Tobacco, alcohol, and cannabis use are prevalent behaviors that pose considerable health risks. Genetic vulnerability and characteristics of the neighborhood of residence form important risk factors for substance use. Possibly, these factors do not act in isolation. This study tested the interaction between neighborhood characteristics and genetic risk (gene-environment interaction, GxE) and the association between these classes of risk factors (gene-environment correlation, rGE) in substance use. METHODS Two polygenic scores (PGS) each (based on different discovery datasets) were created for smoking initiation, cigarettes per day, and glasses of alcohol per week based on summary statistics of different genome-wide association studies (GWAS). For cannabis initiation one PGS was created. These PGS were used to predict their respective phenotype in a large population-based sample from the Netherlands Twin Register (N = 6,567). Neighborhood characteristics as retrieved from governmental registration systems were factor analyzed and resulting measures of socioeconomic status (SES) and metropolitanism were used as predictors. RESULTS There were (small) main effects of neighborhood characteristics and PGS on substance use. One of the 14 tested GxE effects was significant, such that the PGS was more strongly associated with alcohol use in individuals with high SES. This was effect was only significant for one out of two PGS. There were weak indications of rGE, mainly with age and cohort covariates. CONCLUSION We conclude that both genetic and neighborhood-level factors are predictors for substance use. More research is needed to establish the robustness of the findings on the interplay between these factors.
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14
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Marees AT, Smit DJA, Ong JS, MacGregor S, An J, Denys D, Vorspan F, van den Brink W, Derks EM. Potential influence of socioeconomic status on genetic correlations between alcohol consumption measures and mental health. Psychol Med 2020; 50:484-498. [PMID: 30874500 PMCID: PMC7083578 DOI: 10.1017/s0033291719000357] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/25/2018] [Revised: 02/01/2019] [Accepted: 02/12/2019] [Indexed: 11/06/2022]
Abstract
BACKGROUND Frequency and quantity of alcohol consumption are metrics commonly used to measure alcohol consumption behaviors. Epidemiological studies indicate that these alcohol consumption measures are differentially associated with (mental) health outcomes and socioeconomic status (SES). The current study aims to elucidate to what extent genetic risk factors are shared between frequency and quantity of alcohol consumption, and how these alcohol consumption measures are genetically associated with four broad phenotypic categories: (i) SES; (ii) substance use disorders; (iii) other psychiatric disorders; and (iv) psychological/personality traits. METHODS Genome-Wide Association analyses were conducted to test genetic associations with alcohol consumption frequency (N = 438 308) and alcohol consumption quantity (N = 307 098 regular alcohol drinkers) within UK Biobank. For the other phenotypes, we used genome-wide association studies summary statistics. Genetic correlations (rg) between the alcohol measures and other phenotypes were estimated using LD score regression. RESULTS We found a substantial genetic correlation between the frequency and quantity of alcohol consumption (rg = 0.52). Nevertheless, both measures consistently showed opposite genetic correlations with SES traits, and many substance use, psychiatric, and psychological/personality traits. High alcohol consumption frequency was genetically associated with high SES and low risk of substance use disorders and other psychiatric disorders, whereas the opposite applies for high alcohol consumption quantity. CONCLUSIONS Although the frequency and quantity of alcohol consumption show substantial genetic overlap, they consistently show opposite patterns of genetic associations with SES-related phenotypes. Future studies should carefully consider the potential influence of SES on the shared genetic etiology between alcohol and adverse (mental) health outcomes.
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Affiliation(s)
- Andries T. Marees
- Department of Psychiatry, Amsterdam UMC, Amsterdam Neuroscience, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands
- Translational Neurogenomics Group, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Dirk J. A. Smit
- Department of Psychiatry, Amsterdam UMC, Amsterdam Neuroscience, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands
| | - Jue-Sheng Ong
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Stuart MacGregor
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Jiyuan An
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Damiaan Denys
- Department of Psychiatry, Amsterdam UMC, Amsterdam Neuroscience, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands
| | - Florence Vorspan
- Assistance Publique – Hôpitaux de Paris, Hôpital Fernand Widal, Département de Psychiatrie et de Médecine Addictologique, 200 rue du Faubourg Saint Denis, 75010Paris, France
- Inserm umr-s 1144, Université Paris Descartes, Université Paris Diderot, 4 avenue de l'Observatoire, 75006Paris, France
| | - Wim van den Brink
- Department of Psychiatry, Amsterdam UMC, Amsterdam Neuroscience, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands
| | - Eske M. Derks
- Department of Psychiatry, Amsterdam UMC, Amsterdam Neuroscience, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands
- Translational Neurogenomics Group, QIMR Berghofer Medical Research Institute, Brisbane, Australia
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15
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Booher WC, Reyes Martínez GJ, Ehringer MA. Behavioral and neuronal interactions between exercise and alcohol: Sex and genetic differences. GENES BRAIN AND BEHAVIOR 2020; 19:e12632. [DOI: 10.1111/gbb.12632] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Revised: 12/18/2019] [Accepted: 12/18/2019] [Indexed: 12/12/2022]
Affiliation(s)
- Winona C. Booher
- Institute for Behavioral GeneticsUniversity of Colorado Boulder Colorado
- Department of Integrative PhysiologyUniversity of Colorado Boulder Colorado
| | - Guillermo J. Reyes Martínez
- Institute for Behavioral GeneticsUniversity of Colorado Boulder Colorado
- Department of Integrative PhysiologyUniversity of Colorado Boulder Colorado
| | - Marissa A. Ehringer
- Institute for Behavioral GeneticsUniversity of Colorado Boulder Colorado
- Department of Integrative PhysiologyUniversity of Colorado Boulder Colorado
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16
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Rhew IC, Fleming CB, Tsang S, Horn E, Kosterman R, Duncan GE. Neighborhood Deprivation Moderates Shared and Unique Environmental Influences on Hazardous Drinking: Findings from a Cross-Sectional Co-Twin Study. Subst Use Misuse 2020; 55:1625-1632. [PMID: 32326868 PMCID: PMC7485221 DOI: 10.1080/10826084.2020.1756332] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
Background: There has been increased interest in the interplay of genetic and environmental factors in the development of problematic alcohol use, including socioeconomic conditions of the neighborhood. Using a co-twin design, we examined the extent to which contributions of genetic, shared environmental, and unique environmental influences on hazardous drinking differed according to levels of neighborhood socioeconomic deprivation. Method: Data came from 1,521 monozygotic (MZ) and 609 dizygotic (DZ) twin pairs surveyed in Washington State. A measure of neighborhood deprivation was created based on census-tract-level variables and the Alcohol Use Disorders Identification Test 3-item instrument was used to assess level of hazardous drinking. We tested a series of nested structural equation models to examine associations among hazardous drinking, neighborhood deprivation, and the variance components (genetic [A], shared [C] and unique environmental [E] influences) of these two constructs, testing for both main effects and moderation by neighborhood deprivation. Results: Neighborhood deprivation was significantly associated with increased hazardous drinking, after accounting for A and C variance common to both phenotypes. Adjusting for within-pair differences in income and education, neighborhood deprivation moderated the magnitude of variance components of hazardous drinking, with the variance attributable to shared environment and non-shared environment increasing in more deprived neighborhoods. Conclusions: Findings point to amplification of early childhood as well as unique adulthood environmental risk on hazardous drinking in areas of greater deprivation.
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Affiliation(s)
- Isaac C Rhew
- Department of Psychiatry and Behavioral Sciences, Center for the Study of Health and Risk Behaviors, University of Washington, Seattle, Washington, USA
| | - Charles B Fleming
- Department of Psychiatry and Behavioral Sciences, Center for the Study of Health and Risk Behaviors, University of Washington, Seattle, Washington, USA
| | - Siny Tsang
- Health Education and Research Building, Washington State University, Washington State Twin Registry, Spokane, Washington, USA
| | - Erin Horn
- Department of Psychology, University of Virginia, Charlottesville, Virginia, USA
| | - Rick Kosterman
- Social Development Research Group, University of Washington, Seattle, Washington, USA
| | - Glen E Duncan
- Health Education and Research Building, Washington State University, Washington State Twin Registry, Spokane, Washington, USA
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17
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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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18
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Cabana-Domínguez J, Shivalikanjli A, Fernàndez-Castillo N, Cormand B. Genome-wide association meta-analysis of cocaine dependence: Shared genetics with comorbid conditions. Prog Neuropsychopharmacol Biol Psychiatry 2019; 94:109667. [PMID: 31212010 DOI: 10.1016/j.pnpbp.2019.109667] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2019] [Revised: 05/07/2019] [Accepted: 06/07/2019] [Indexed: 12/23/2022]
Abstract
Cocaine dependence is a complex psychiatric disorder that is highly comorbid with other psychiatric traits. Twin and adoption studies suggest that genetic variants contribute substantially to cocaine dependence susceptibility, which has an estimated heritability of 65-79%. Here we performed a meta-analysis of genome-wide association studies of cocaine dependence using four datasets from the dbGaP repository (2085 cases and 4293 controls, all of them selected by their European ancestry). Although no genome-wide significant hits were found in the SNP-based analysis, the gene-based analysis identified HIST1H2BD as associated with cocaine-dependence (10% FDR). This gene is located in a region on chromosome 6 enriched in histone-related genes, previously associated with schizophrenia (SCZ). Furthermore, we performed LD Score regression analysis with comorbid conditions and found significant genetic correlations between cocaine dependence and SCZ, ADHD, major depressive disorder (MDD) and risk taking. We also found, through polygenic risk score analysis, that all tested phenotypes are significantly associated with cocaine dependence status: SCZ (R2 = 2.28%; P = 1.21e-26), ADHD (R2 = 1.39%; P = 4.5e-17), risk taking (R2 = 0.60%; P = 2.7e-08), MDD (R2 = 1.21%; P = 4.35e-15), children's aggressive behavior (R2 = 0.3%; P = 8.8e-05) and antisocial behavior (R2 = 1.33%; P = 2.2e-16). To our knowledge, this is the largest reported cocaine dependence GWAS meta-analysis in European-ancestry individuals. We identified suggestive associations in regions that may be related to cocaine dependence and found evidence for shared genetic risk factors between cocaine dependence and several comorbid psychiatric traits. However, the sample size is limited and further studies are needed to confirm these results.
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Affiliation(s)
- Judit Cabana-Domínguez
- Departament de Genètica, Microbiologia i Estadística, Facultat de Biologia, Universitat de Barcelona, Barcelona, Catalonia, Spain; Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Instituto de Salud Carlos III, Spain; Institut de Biomedicina de la Universitat de Barcelona (IBUB), Barcelona, Catalonia, Spain; Institut de Recerca Sant Joan de Déu (IR-SJD), Esplugues de Llobregat, Catalonia, Spain
| | - Anu Shivalikanjli
- Departament de Genètica, Microbiologia i Estadística, Facultat de Biologia, Universitat de Barcelona, Barcelona, Catalonia, Spain; Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Instituto de Salud Carlos III, Spain; Institut de Biomedicina de la Universitat de Barcelona (IBUB), Barcelona, Catalonia, Spain; Institut de Recerca Sant Joan de Déu (IR-SJD), Esplugues de Llobregat, Catalonia, Spain
| | - Noèlia Fernàndez-Castillo
- Departament de Genètica, Microbiologia i Estadística, Facultat de Biologia, Universitat de Barcelona, Barcelona, Catalonia, Spain; Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Instituto de Salud Carlos III, Spain; Institut de Biomedicina de la Universitat de Barcelona (IBUB), Barcelona, Catalonia, Spain; Institut de Recerca Sant Joan de Déu (IR-SJD), Esplugues de Llobregat, Catalonia, Spain.
| | - Bru Cormand
- Departament de Genètica, Microbiologia i Estadística, Facultat de Biologia, Universitat de Barcelona, Barcelona, Catalonia, Spain; Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Instituto de Salud Carlos III, Spain; Institut de Biomedicina de la Universitat de Barcelona (IBUB), Barcelona, Catalonia, Spain; Institut de Recerca Sant Joan de Déu (IR-SJD), Esplugues de Llobregat, Catalonia, Spain.
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19
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Booher WC, Hoft NR, Ehringer MA. The effect of voluntary wheel running on 129/SvEvTac and C3H/Ibg alcohol consumption. Alcohol 2019; 77:91-99. [PMID: 30616894 DOI: 10.1016/j.alcohol.2018.10.007] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2018] [Revised: 09/24/2018] [Accepted: 10/20/2018] [Indexed: 12/15/2022]
Abstract
The mesolimbic dopaminergic reward pathway is activated by both alcohol and exercise, suggesting exercise as a possible treatment or preventative method for alcohol-use disorders (AUDs). Prior studies conducted in our lab have demonstrated the hedonic substitution of voluntary alcohol consumption for voluntary wheel running in female C57Bl/6Ibg mice, and a trend in male C57Bl/6Ibg mice. Given the important contribution of genetic background on AUDs, this study aims to assess the effects of voluntary wheel running on voluntary alcohol consumption in two moderate alcohol-consuming strains of mice, C3H/Ibg and 129/SvEvTac. Contrary to our previous studies conducted in C57Bl/6Ibg mice, 129/SvEvTac and male C3H/Ibg mice housed without a wheel consumed significantly more alcohol than mice housed with a free or locked wheel. This suggests that 129/SvEvTac and male C3H/Ibg mice are reducing their alcohol consumption due to an enriched environment and not exercise. Interestingly, the three groups of female C3H/Ibg mice (free wheel, locked wheel, no wheel) did not significantly differ in alcohol consumption, suggesting sex-specific differences in C3H/Ibg mice. In addition, genetic and sex effects were observed for running phenotypes in the presence of alcohol. Female 129/SvEvTac and C57Bl/6Ibg mice ran longer distances than male mice, whereas male and female C3H/Ibg mice did not differ in distance run. C3H/Ibg and female 129/SvEvTav mice with access only to water ran longer distances than mice with access to both alcohol and water. However, this effect was not observed in C57Bl/6Ibg or male 129/SvEvTac mice. The results of this mouse model highlight the importance of genetic background and sex on an animal's response to exercise as an enrichment to reduce voluntary alcohol consumption.
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20
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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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21
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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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22
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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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23
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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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24
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Sanchez-Roige S, Fontanillas P, Elson SL, Gray JC, de Wit H, Davis LK, MacKillop J, Palmer AA. Genome-wide association study of alcohol use disorder identification test (AUDIT) scores in 20 328 research participants of European ancestry. Addict Biol 2019; 24:121-131. [PMID: 29058377 PMCID: PMC6988186 DOI: 10.1111/adb.12574] [Citation(s) in RCA: 66] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2017] [Revised: 09/11/2017] [Accepted: 09/25/2017] [Indexed: 12/26/2022]
Abstract
Genetic factors contribute to the risk for developing alcohol use disorder (AUD). In collaboration with the genetics company 23andMe, Inc., we performed a genome-wide association study of the alcohol use disorder identification test (AUDIT), an instrument designed to screen for alcohol misuse over the past year. Our final sample consisted of 20 328 research participants of European ancestry (55.3% females; mean age = 53.8, SD = 16.1) who reported ever using alcohol. Our results showed that the 'chip-heritability' of AUDIT score, when treated as a continuous phenotype, was 12%. No loci reached genome-wide significance. The gene ADH1C, which has been previously implicated in AUD, was among our most significant associations (4.4 × 10-7 ; rs141973904). We also detected a suggestive association on chromosome 1 (2.1 × 10-7 ; rs182344113) near the gene KCNJ9, which has been implicated in mouse models of high ethanol drinking. Using linkage disequilibrium score regression, we identified positive genetic correlations between AUDIT score, high alcohol consumption and cigarette smoking. We also observed an unexpected positive genetic correlation between AUDIT and educational attainment and additional unexpected negative correlations with body mass index/obesity and attention-deficit/hyperactivity disorder. We conclude that conducting a genetic study using responses to an online questionnaire in a population not ascertained for AUD may represent a cost-effective strategy for elucidating aspects of the etiology of AUD.
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Affiliation(s)
- Sandra Sanchez-Roige
- Department of Psychiatry, University of California San Diego, La Jolla, CA, 92093, USA
| | | | | | | | - Joshua C. Gray
- Center for Deployment Psychology, Uniformed Services University, Bethesda, MD, 20814
| | - Harriet de Wit
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL 60637, USA
| | - Lea K. Davis
- Vanderbilt Genetics Institute; Division of Genetic Medicine, Department of Medicine, Vanderbilt University, Nashville, TN, USA
| | - James MacKillop
- Peter Boris Centre for Addictions Research, McMaster University/St. Joseph’s Healthcare Hamilton, Hamilton, ON L8N 3K7, Canada; Homewood Research Institute, Guelph, ON N1E 6K9, Canada
| | - 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
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25
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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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Clark SL, Costin BN, Chan RF, Johnson AW, Xie L, Jurmain JL, Kumar G, Shabalin AA, Pandey AK, Aberg KA, Miles MF, van den Oord E. A Whole Methylome Study of Ethanol Exposure in Brain and Blood: An Exploration of the Utility of Peripheral Blood as Proxy Tissue for Brain in Alcohol Methylation Studies. Alcohol Clin Exp Res 2018; 42:2360-2368. [PMID: 30320886 DOI: 10.1111/acer.13905] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2018] [Accepted: 10/06/2018] [Indexed: 01/04/2023]
Abstract
BACKGROUND Recent reviews have highlighted the potential use of blood-based methylation biomarkers as diagnostic and prognostic tools of current and future alcohol use and addiction. Due to the substantial overlap that often exists between methylation patterns across different tissues, including blood and brain, blood-based methylation may track methylation changes in brain; however, little work has explored the overlap in alcohol-related methylation in these tissues. METHODS To study the effects of alcohol on the brain methylome and identify possible biomarkers of these changes in blood, we performed a methylome-wide association study in brain and blood from 40 male DBA/2J mice that received either an acute ethanol (EtOH) or saline intraperitoneal injection. To investigate all 22 million CpGs in the mouse genome, we enriched for the methylated genomic fraction using methyl-CpG binding domain (MBD) protein capture followed by next-generation sequencing (MBD-seq). We performed association tests in blood and brain separately followed by enrichment testing to determine whether there was overlapping alcohol-related methylation in the 2 tissues. RESULTS The top result for brain was a CpG located in an intron of Ttc39b (p = 5.65 × 10-08 ), and for blood, the top result was located in Espnl (p = 5.11 × 10-08 ). Analyses implicated pathways involved in inflammation and neuronal differentiation, such as CXCR4, IL-7, and Wnt signaling. Enrichment tests indicated significant overlap among the top results in brain and blood. Pathway analyses of the overlapping genes converge on MAPKinase signaling (p = 5.6 × 10-05 ) which plays a central role in acute and chronic responses to alcohol and glutamate receptor pathways, which can regulate neuroplastic changes underlying addictive behavior. CONCLUSIONS Overall, we have shown some methylation changes in brain and blood after acute EtOH administration and that the changes in blood partly mirror the changes in brain suggesting the potential for DNA methylation in blood to be biomarkers of alcohol use.
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Affiliation(s)
- Shaunna L Clark
- Department of Psychology , Michigan State University, East Lansing, Michigan.,Center for Biomarker Research and Precision Medicine , Virginia Commonwealth University, Richmond, Virginia
| | - Blair N Costin
- Department of Pharmacology and Toxicology , Virginia Commonwealth University, Richmond, Virginia
| | - Robin F Chan
- Center for Biomarker Research and Precision Medicine , Virginia Commonwealth University, Richmond, Virginia
| | - Alexander W Johnson
- Department of Psychology , Michigan State University, East Lansing, Michigan
| | - Linying Xie
- Center for Biomarker Research and Precision Medicine , Virginia Commonwealth University, Richmond, Virginia
| | - Jessica L Jurmain
- Department of Pharmacology and Toxicology , Virginia Commonwealth University, Richmond, Virginia
| | - Gaurav Kumar
- Center for Biomarker Research and Precision Medicine , Virginia Commonwealth University, Richmond, Virginia
| | - Andrey A Shabalin
- Center for Biomarker Research and Precision Medicine , Virginia Commonwealth University, Richmond, Virginia
| | - Ashutosh K Pandey
- Department of Anatomy and Neurobiology , Center for Integrative and Translational Genomics, University of Tennessee Health Science Center, Memphis, Tennessee
| | - Karolina A Aberg
- Center for Biomarker Research and Precision Medicine , Virginia Commonwealth University, Richmond, Virginia
| | - Michael F Miles
- Department of Pharmacology and Toxicology , Virginia Commonwealth University, Richmond, Virginia
| | - Edwin van den Oord
- Center for Biomarker Research and Precision Medicine , Virginia Commonwealth University, Richmond, Virginia
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27
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Stolf AR, Cupertino RB, Müller D, Sanvicente-Vieira B, Roman T, Vitola ES, Grevet EH, von Diemen L, Kessler FHP, Grassi-Oliveira R, Bau CHD, Rovaris DL, Pechansky F, Schuch JB. Effects of DRD2 splicing-regulatory polymorphism and DRD4 48 bp VNTR on crack cocaine addiction. J Neural Transm (Vienna) 2018; 126:193-199. [PMID: 30367264 DOI: 10.1007/s00702-018-1946-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2018] [Accepted: 10/17/2018] [Indexed: 11/24/2022]
Abstract
There is evidence that dopamine receptors D2 (DRD2) and D4 (DRD4) polymorphisms may influence substance use disorders (SUD) susceptibility both individually and through their influence in the formation of DRD2-DRD4 heteromers. The dopaminergic role on the vulnerability to addiction appears to be influenced by sex. A cross-sectional study with 307 crack cocaine addicts and 770 controls was conducted. The influence of DRD2 rs2283265 and DRD4 48 bp VNTR in exon 3 variants, as well as their interaction on crack cocaine addiction susceptibility and severity were evaluated in women and men separately. An association between the DRD2 T allele and crack cocaine addiction was found in women. In this same group, interaction analysis demonstrated that the presence of DRD2-T allele and concomitant absence of DRD4-7R allele were associated with risk for crack cocaine addiction. No influence of DRD2 and DRD4 variants was observed in men regarding addiction severity. This study reinforces the role of dopaminergic genes in externalizing behaviors, especially the influence of DRD2-DRD4 interaction on SUD. This is the fourth sample that independently associated the DRD2-DRD4 interaction with SUD itself or related disorders. In addition, our findings point out to a potential difference of dopaminergic neurotransmission across sex influencing addiction susceptibility.
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Affiliation(s)
- Anderson R Stolf
- Center for Drug and Alcohol Research, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Renata B Cupertino
- Department of Genetics, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Diana Müller
- Department of Genetics, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Breno Sanvicente-Vieira
- Developmental Cognitive Neuroscience Lab (DCNL), Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre, Brazil
| | - Tatiana Roman
- Department of Genetics, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Eduardo S Vitola
- ADHD Outpatient Program, Adult Division, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
| | - Eugenio H Grevet
- ADHD Outpatient Program, Adult Division, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
| | - Lisia von Diemen
- Center for Drug and Alcohol Research, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Felix H P Kessler
- Center for Drug and Alcohol Research, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Rodrigo Grassi-Oliveira
- Developmental Cognitive Neuroscience Lab (DCNL), Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre, Brazil
| | - Claiton H D Bau
- Center for Drug and Alcohol Research, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.,ADHD Outpatient Program, Adult Division, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
| | - Diego L Rovaris
- Department of Genetics, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Flavio Pechansky
- Center for Drug and Alcohol Research, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Jaqueline B Schuch
- Department of Genetics, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil. .,Laboratory of Immunosenescence, Graduate Program in Biomedical Gerontology, Pontifícia Universidade Católica do Rio Grande do Sul, Av. Ipiranga, 6681, prédio 81, Porto Alegre, Rio Grande do Sul, CEP 90619-900, Brazil.
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28
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Xu R, Wu H, Zhang S, Zhou H, Liang L. Lack of association between MTHFR C677T Gene polymorphism with alcohol dependence: A meta-analysis of case-control studies. Neurosci Lett 2018; 683:69-74. [PMID: 29953924 DOI: 10.1016/j.neulet.2018.06.044] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2018] [Revised: 06/21/2018] [Accepted: 06/24/2018] [Indexed: 01/08/2023]
Abstract
Many studies have reported that MTHFR C677T (rs 1801133) polymorphism is associated with the risk of alcohol dependence(AD). However, there are conflicting results regarding this relationship. In this article, we performed a meta-analysis of case-control studies to assess synthetically the influence of MTHFR C677T polymorphism on the risk of AD. All relevant studies were searched from Cochrane Library, EmBase, PubMed, and Web of science. 7 studies were included to evaluate the strength of associations between the MTHFR C677T polymorphism and AD by pooled odds ratios (ORs) and 95% confidence intervals (CIs). The present meta-analysis evaluated a total of 1066 AD patients and 1049 controls and showed that MTHFR C677T polymorphism was not significantly associated with AD susceptibility in all five genetic models (Allelic, T vs C: OR = 1.04,95% CI: 0.83-1.31, P = 0.73; Homozygous, TT vs CC: OR = 0.98,95% CI: 0.57-1.68, P = 0.94; Heterozygous, TT vs CT: OR = 0.87,95% CI: 0.64-1.19, P = 0.39; Dominant, TT + CT vs CC: OR = 1.12,95% CI: 0.92-1.35, P = 0.26; Recessive, TT vs CT + CC: OR = 0.93,95% CI: 0.58-1.47, P = 0.74). On subgroup analysis by ethnicity, there was still insignificant association was detected in the Caucasians and Asians under the five genetic models respectively. In conclusion, the present data revealed that MTHFR C677T polymorphism may not be associated with AD susceptibility. Further well designed studies in a larger population and biological functional analysis of MTHFR are needed to elucidate the role of MTHFR C677T Gene polymorphism in AD.
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Affiliation(s)
- Rong Xu
- Department of Medical Oncology, People's Hospital of Xinjiang Uygur, Urumqi, China
| | - Hao Wu
- Department of Pathology, Renmin Hospital of Wuhan University, Hubei Zhang Road (formerly Ziyang Road) Wuchang District No. 99 Jiefang Road 238, Wuhan, Hubei province, China
| | - Shiying Zhang
- Department of Pathology, Renmin Hospital of Wuhan University, Hubei Zhang Road (formerly Ziyang Road) Wuchang District No. 99 Jiefang Road 238, Wuhan, Hubei province, China
| | - Heng Zhou
- Department of Pathology, Renmin Hospital of Wuhan University, Hubei Zhang Road (formerly Ziyang Road) Wuchang District No. 99 Jiefang Road 238, Wuhan, Hubei province, China
| | - Liang Liang
- Department of Pathology, Renmin Hospital of Wuhan University, Hubei Zhang Road (formerly Ziyang Road) Wuchang District No. 99 Jiefang Road 238, Wuhan, Hubei province, China.
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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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Almli LM, Lori A, Meyers JL, Shin J, Fani N, Maihofer AX, Nievergelt CM, Smith AK, Mercer KB, Kerley K, Leveille JM, Feng H, Abu‐Amara D, Flory JD, Yehuda R, Marmar CR, Baker DG, Bradley B, Koenen KC, Conneely KN, Ressler KJ. Problematic alcohol use associates with sodium channel and clathrin linker 1 (SCLT1) in trauma-exposed populations. Addict Biol 2018; 23:1145-1159. [PMID: 29082582 DOI: 10.1111/adb.12569] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2016] [Revised: 08/05/2017] [Accepted: 08/29/2017] [Indexed: 12/15/2022]
Abstract
Excessive alcohol use is extremely prevalent in the United States, particularly among trauma-exposed individuals. While several studies have examined genetic influences on alcohol use and related problems, this has not been studied in the context of trauma-exposed populations. We report results from a genome-wide association study of alcohol consumption and associated problems as measured by the alcohol use disorders identification test (AUDIT) in a trauma-exposed cohort. Results indicate a genome-wide significant association between total AUDIT score and rs1433375 [N = 1036, P = 2.61 × 10-8 (dominant model), P = 7.76 × 10-8 (additive model)], an intergenic single-nucleotide polymorphism located 323 kb upstream of the sodium channel and clathrin linker 1 (SCLT1) at 4q28. rs1433375 was also significant in a meta-analysis of two similar, but independent, cohorts (N = 1394, P = 0.0004), the Marine Resiliency Study and Systems Biology PTSD Biomarkers Consortium. Functional analysis indicated that rs1433375 was associated with SCLT1 gene expression and cortical-cerebellar functional connectivity measured via resting state functional magnetic resonance imaging. Together, findings suggest a role for sodium channel regulation and cerebellar functioning in alcohol use behavior. Identifying mechanisms underlying risk for problematic alcohol use in trauma-exposed populations is critical for future treatment and prevention efforts.
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Affiliation(s)
- Lynn M. Almli
- Department of Psychiatry and Behavioral Sciences Emory University Atlanta GA USA
| | - Adriana Lori
- Department of Psychiatry and Behavioral Sciences Emory University Atlanta GA USA
| | - Jacquelyn L. Meyers
- Department of Psychiatry State University of New York Downstate Medical Center Brooklyn NY USA
| | - Jaemin Shin
- Center for Advanced Brain Imaging Georgia State University/Georgia Institute of Technology Atlanta GA USA
| | - Negar Fani
- Department of Psychiatry and Behavioral Sciences Emory University Atlanta GA USA
| | - Adam X. Maihofer
- Department of Psychiatry University of California San Diego San Diego CA USA
- Veterans Affairs Center of Excellence for Stress and Mental Health San Diego USA
| | - Caroline M. Nievergelt
- Department of Psychiatry University of California San Diego San Diego CA USA
- Veterans Affairs Center of Excellence for Stress and Mental Health San Diego USA
| | - Alicia K. Smith
- Department of Psychiatry and Behavioral Sciences Emory University Atlanta GA USA
- Department of Gynecology and Obstetrics Emory University Atlanta GA USA
| | | | - Kimberly Kerley
- Department of Psychiatry and Behavioral Sciences Emory University Atlanta GA USA
| | - Jennifer M. Leveille
- Department of Psychiatry and Behavioral Sciences Emory University Atlanta GA USA
| | - Hao Feng
- Department of Human Genetics Emory University Atlanta GA USA
| | - Duna Abu‐Amara
- Steven and Alexandra Cohen Veterans Center for Posttraumatic Stress and Traumatic Brain Injury Department of Psychiatry, New York University New York NY USA
| | - Janine D. Flory
- Steven and Alexandra Cohen Veterans Center for Posttraumatic Stress and Traumatic Brain Injury Department of Psychiatry, New York University New York NY USA
- Department of Psychiatry MSSM/James J. Peters Veterans Administration Medical Center New York NY USA
| | - Rachel Yehuda
- Steven and Alexandra Cohen Veterans Center for Posttraumatic Stress and Traumatic Brain Injury Department of Psychiatry, New York University New York NY USA
- Department of Psychiatry MSSM/James J. Peters Veterans Administration Medical Center New York NY USA
| | - Charles R. Marmar
- Steven and Alexandra Cohen Veterans Center for Posttraumatic Stress and Traumatic Brain Injury Department of Psychiatry, New York University New York NY USA
| | - Dewleen G. Baker
- Department of Psychiatry University of California San Diego San Diego CA USA
- Veterans Affairs Center of Excellence for Stress and Mental Health San Diego USA
- Psychiatry Services VA San Diego Healthcare System San Diego CA USA
| | - Bekh Bradley
- Department of Psychiatry and Behavioral Sciences Emory University Atlanta GA USA
- Mental Health Service Line Department of Veterans Affairs Medical Center Atlanta GA USA
| | - Karestan C. Koenen
- Department of Epidemiology Harvard TH Chan School of Public Health Boston MA USA
| | | | - Kerry J. Ressler
- Department of Psychiatry and Behavioral Sciences Emory University Atlanta GA USA
- McLean Hospital Harvard Medical School Belmont MA USA
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Marees AT, Hammerschlag AR, Bastarache L, de Kluiver H, Vorspan F, van den Brink W, Smit DJ, Denys D, Gamazon ER, Li-Gao R, Breetvelt EJ, de Groot MCH, Galesloot TE, Vermeulen SH, Poppelaars JL, Souverein PC, Keeman R, de Mutsert R, Noordam R, Rosendaal FR, Stringa N, Mook-Kanamori DO, Vaartjes I, Kiemeney LA, den Heijer M, van Schoor NM, Klungel OH, Maitland-Van der Zee AH, Schmidt MK, Polderman TJC, van der Leij AR, Posthuma D, Derks EM. Exploring the role of low-frequency and rare exonic variants in alcohol and tobacco use. Drug Alcohol Depend 2018; 188:94-101. [PMID: 29758381 DOI: 10.1016/j.drugalcdep.2018.03.026] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/04/2017] [Revised: 03/22/2018] [Accepted: 03/24/2018] [Indexed: 02/07/2023]
Abstract
BACKGROUND Alcohol and tobacco use are heritable phenotypes. However, only a small number of common genetic variants have been identified, and common variants account for a modest proportion of the heritability. Therefore, this study aims to investigate the role of low-frequency and rare variants in alcohol and tobacco use. METHODS We meta-analyzed ExomeChip association results from eight discovery cohorts and included 12,466 subjects and 7432 smokers in the analysis of alcohol consumption and tobacco use, respectively. The ExomeChip interrogates low-frequency and rare exonic variants, and in addition a small pool of common variants. We investigated top variants in an independent sample in which ICD-9 diagnoses of "alcoholism" (N = 25,508) and "tobacco use disorder" (N = 27,068) had been assessed. In addition to the single variant analysis, we performed gene-based, polygenic risk score (PRS), and pathway analyses. RESULTS The meta-analysis did not yield exome-wide significant results. When we jointly analyzed our top results with the independent sample, no low-frequency or rare variants reached significance for alcohol consumption or tobacco use. However, two common variants that were present on the ExomeChip, rs16969968 (p = 2.39 × 10-7) and rs8034191 (p = 6.31 × 10-7) located in CHRNA5 and AGPHD1 at 15q25.1, showed evidence for association with tobacco use. DISCUSSION Low-frequency and rare exonic variants with large effects do not play a major role in alcohol and tobacco use, nor does the aggregate effect of ExomeChip variants. However, our results confirmed the role of the CHRNA5-CHRNA3-CHRNB4 cluster of nicotinic acetylcholine receptor subunit genes in tobacco use.
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Affiliation(s)
- Andries T Marees
- Department of Psychiatry, Amsterdam Neuroscience, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands; QIMR Berghofer, Translational Neurogenomics Group, Brisbane, Australia.
| | - Anke R Hammerschlag
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Lisa Bastarache
- Center for Precision Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, United States
| | - Hilde de Kluiver
- GGZ inGeest and Department of Psychiatry, Amsterdam Public Health Research Institute, VU University Medical Center, Amsterdam, The Netherlands
| | - Florence Vorspan
- Assistance Publique-Hôpitaux de Paris, Hôpital Fernand Widal, Département de Psychiatrie et de Médecine Addictologique, 200 Rue du Faubourg Saint-Denis, Paris, France; Inserm umr-s 1144, Université Paris Descartes, Université Paris Diderot, 4 Avenue de l'Observatoire, Paris, France
| | - Wim van den Brink
- Department of Psychiatry, Amsterdam Neuroscience, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Dirk J Smit
- Department of Psychiatry, Amsterdam Neuroscience, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Damiaan Denys
- Department of Psychiatry, Amsterdam Neuroscience, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Eric R Gamazon
- Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, United States; Clare Hall, University of Cambridge, Cambridge, CB3 9AL, United Kingdom
| | - Ruifang Li-Gao
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Elemi J Breetvelt
- The Dalglish Family 22q Clinic, Toronto General Hospital, University Health Network, Toronto, Canada; Clinical Genetics Research Program, Centre for Addiction and Mental Health, Toronto, Canada
| | - Mark C H de Groot
- Department of Clinical Chemistry and Haematology, Division of Laboratory and Pharmacy, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Tessel E Galesloot
- Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Sita H Vermeulen
- Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jan L Poppelaars
- Department of Sociology, VU University, Amsterdam, The Netherlands; Department of Epidemiology and Biostatistics, Amsterdam Public Health Research Institute, VU University Medical Center, Amsterdam, The Netherlands
| | - Patrick C Souverein
- Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute of Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands
| | - Renske Keeman
- Division of Molecular Pathology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Renée de Mutsert
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Raymond Noordam
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands
| | - Frits R Rosendaal
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Najada Stringa
- Department of Epidemiology and Biostatistics, Amsterdam Public Health Research Institute, VU University Medical Center, Amsterdam, The Netherlands
| | - Dennis O Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands; Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, The Netherlands
| | - Ilonca Vaartjes
- Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Lambertus A Kiemeney
- Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Martin den Heijer
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands; Department of Internal Medicine, VU University Medical Center, Amsterdam, The Netherlands
| | - Natasja M van Schoor
- Department of Epidemiology and Biostatistics, Amsterdam Public Health Research Institute, VU University Medical Center, Amsterdam, The Netherlands
| | - Olaf H Klungel
- Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute of Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands
| | - Anke H Maitland-Van der Zee
- Department of Respiratory Medicine, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Marjanka K Schmidt
- Division of Molecular Pathology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Tinca J C Polderman
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | | | - Danielle Posthuma
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands; Clinical Genetics, Vrije Universiteit Medical Center, Amsterdam, The Netherlands
| | - Eske M Derks
- Department of Psychiatry, Amsterdam Neuroscience, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands; QIMR Berghofer, Translational Neurogenomics Group, Brisbane, Australia
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Gelernter J, Zhou H, Nuñez YZ, Mutirangura A, Malison RT, Kalayasiri R. Genomewide Association Study of Alcohol Dependence and Related Traits in a Thai Population. Alcohol Clin Exp Res 2018; 42:861-868. [PMID: 29460428 DOI: 10.1111/acer.13614] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2017] [Accepted: 02/14/2018] [Indexed: 02/06/2023]
Abstract
BACKGROUND Alcohol use (both quantity and dependence) is moderately heritable, and genomewide association studies (GWAS) have identified risk genes in European, African, and Asian populations. The most reproducibly identified risk genes affect alcohol metabolism. Well-known functional variants at the gene encoding alcohol dehydrogenase B and other alcohol dehydrogenases affect risk in European and African ancestry populations. Similarly, variants mapped to these same genes and a well-known null variant that maps to the gene that encodes aldehyde dehydrogenase 2 (ALDH2) also affect risk in various Asian populations. In this study, we completed the first GWAS for 3 traits related to alcohol use in a Thai population recruited initially for studies of methamphetamine dependence. METHODS All subjects were evaluated with the Thai version of the Semi-Structured Assessment for Drug Dependence and Alcoholism (SSADDA). A total of 1,045 subjects were available for analysis. Three traits were analyzed: flushing, maximum number of alcoholic beverages consumed in any lifetime 24-hour period ("MAXDRINKS"), and DSM-IV alcohol dependence criterion count. We also conducted a pleiotropy analysis with major depression, the only other psychiatric trait where summary statistics from a large-scale Asian-population GWAS are available. RESULTS All 3 traits showed genomewide significant association with variants near ALDH2, with significance ranging from 2.01 × 10-14 (for flushing; lead single nucleotide polymorphism (SNP) PTPN11* rs143894582) to pmeta = 5.80 × 10-10 (for alcohol dependence criterion count; lead SNP rs149212747). These lead SNPs flank rs671 and span a region of over a megabase, illustrating the need for prior biological information in identifying the actual effect SNP, rs671. We also identified significant pleiotropy between major depression and flushing. CONCLUSIONS These results are consistent with prior findings in Asian populations and add new information regarding alcohol use-depression pleiotropy.
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Affiliation(s)
- Joel Gelernter
- Department of Psychiatry , Yale University School of Medicine, New Haven, Connecticut.,Department of Psychiatry , VA Connecticut Healthcare System, West Haven, Connecticut.,Departments of Genetics and Neuroscience , Yale University School of Medicine, New Haven, Connecticut
| | - Hang Zhou
- Department of Psychiatry , Yale University School of Medicine, New Haven, Connecticut.,Department of Psychiatry , VA Connecticut Healthcare System, West Haven, Connecticut
| | - Yaira Z Nuñez
- Department of Psychiatry , Yale University School of Medicine, New Haven, Connecticut.,Department of Psychiatry , VA Connecticut Healthcare System, West Haven, Connecticut
| | - Apiwat Mutirangura
- Department of Anatomy , Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Robert T Malison
- Department of Psychiatry , Yale University School of Medicine, New Haven, Connecticut.,Clinical Neuroscience Research Unit , Connecticut Mental Health Center, New Haven, Connecticut
| | - Rasmon Kalayasiri
- Department of Psychiatry , King Chulalongkorn Memorial Hospital, Bangkok, Thailand.,Department of Psychiatry , Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
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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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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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Salvatore JE, Savage JE, Barr P, Wolen AR, Aliev F, Vuoksimaa E, Latvala A, Pulkkinen L, Rose RJ, Kaprio J, Dick DM. Incorporating Functional Genomic Information to Enhance Polygenic Signal and Identify Variants Involved in Gene-by-Environment Interaction for Young Adult Alcohol Problems. Alcohol Clin Exp Res 2018; 42:413-423. [PMID: 29121402 PMCID: PMC5785466 DOI: 10.1111/acer.13551] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2017] [Accepted: 11/02/2017] [Indexed: 12/18/2022]
Abstract
BACKGROUND Characterizing aggregate genetic risk for alcohol misuse and identifying variants involved in gene-by-environment (G × E) interaction effects has so far been a major challenge. We hypothesized that functional genomic information could be used to enhance detection of polygenic signal underlying alcohol misuse and to prioritize identification of single nucleotide polymorphisms (SNPs) most likely to exhibit G × E effects. METHODS We examined these questions in the young adult FinnTwin12 sample (n = 1,170). We used genomewide association estimates from an independent sample to derive 2 types of polygenic scores for alcohol problems in FinnTwin12. Genomewide polygenic scores included all SNPs surpassing a designated p-value threshold. DNase polygenic scores were a subset of the genomewide polygenic scores including only variants in DNase I hypersensitive sites (DHSs), which are open chromatin marks likely to index regions with a regulatory function. We conducted parallel analyses using height as a nonpsychiatric model phenotype to evaluate the consistency of effects. For the G × E analyses, we examined whether SNPs in DHSs were overrepresented among SNPs demonstrating significant G × E effects in an interaction between romantic relationship status and intoxication frequency. RESULTS Contrary to our expectations, we found that DNase polygenic scores were not more strongly predictive of alcohol problems than conventional polygenic scores. However, variants in DNase polygenic scores had per-SNP effects that were up to 1.4 times larger than variants in conventional polygenic scores. This same pattern of effects was also observed in supplementary analyses with height. In G × E models, SNPs in DHSs were modestly overrepresented among SNPs with significant interaction effects for intoxication frequency. CONCLUSIONS These findings highlight the potential utility of integrating functional genomic annotation information to increase the signal-to-noise ratio in polygenic scores and identify genetic variants that may be most susceptible to environmental modification.
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Affiliation(s)
- Jessica E. Salvatore
- Department of Psychology, Virginia Commonwealth University, PO Box 842018, Richmond, VA 23284-2018, United States
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, PO Box 980126, Richmond, VA 23298, United States
| | - Jeanne E. Savage
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, PO Box 980126, Richmond, VA 23298, United States
| | - Peter Barr
- Department of Psychology, Virginia Commonwealth University, PO Box 842018, Richmond, VA 23284-2018, United States
| | - Aaron R. Wolen
- Center for Clinical and Translational Research, Virginia Commonwealth University, P.O. Box 980261, Richmond, VA 23298-0261, United States
| | - Fazil Aliev
- Department of Psychology, Virginia Commonwealth University, PO Box 842018, Richmond, VA 23284-2018, United States
- Faculty of Business, Karabuk University, 78050 Karabuk, Turkey
| | - Eero Vuoksimaa
- Institute for Molecular Medicine FIMM, University of Helsinki, PO Box 20 (Tukholmankatu 8), FI-00014 Helsinki, Finland
| | - Antti Latvala
- Institute for Molecular Medicine FIMM, University of Helsinki, PO Box 20 (Tukholmankatu 8), FI-00014 Helsinki, Finland
| | - Lea Pulkkinen
- Department of Psychology, University of Jyväskylä, PO Box 35, 40014 University of Jyväskylä, Jyväskylä, Finland
| | - Richard J. Rose
- Department of Psychological & Brain Sciences, Indiana University, 1101 E. 10th St., Bloomington, IN 47405, United States
| | - Jaakko Kaprio
- Institute for Molecular Medicine FIMM, University of Helsinki, PO Box 20 (Tukholmankatu 8), FI-00014 Helsinki, Finland
| | - Danielle M. Dick
- Department of Psychology, Virginia Commonwealth University, PO Box 842018, Richmond, VA 23284-2018, United States
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Mies GW, Verweij KJH, Treur JL, Ligthart L, Fedko IO, Hottenga JJ, Willemsen G, Bartels M, Boomsma DI, Vink JM. Polygenic risk for alcohol consumption and its association with alcohol-related phenotypes: Do stress and life satisfaction moderate these relationships? Drug Alcohol Depend 2018; 183:7-12. [PMID: 29220643 DOI: 10.1016/j.drugalcdep.2017.10.018] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/25/2017] [Revised: 10/15/2017] [Accepted: 10/16/2017] [Indexed: 11/17/2022]
Abstract
BACKGROUND Genetic and environmental factors contribute about equally to alcohol-related phenotypes in adulthood. In the present study, we examined whether more stress at home or low satisfaction with life might be associated with heavier drinking or more alcohol-related problems in individuals with a high genetic susceptibility to alcohol use. METHODS Information on polygenic scores and drinking behavior was available in 6705 adults (65% female; 18-83 years) registered with the Netherlands Twin Register. Polygenic risk scores (PRSs) were constructed for all subjects based on the summary statistics of a large genome-wide association meta-analysis on alcohol consumption (grams per day). Outcome measures were quantity of alcohol consumption and alcohol-related problems assessed with the Alcohol Use Disorders Identification Test (AUDIT). Stress at home and life satisfaction were moderating variables whose significance was tested by Generalized Estimating Equation analyses taking familial relatedness, age and sex into account. RESULTS PRSs for alcohol were significantly associated with quantity of alcohol consumption and alcohol-related problems in the past year (R2=0.11% and 0.10% respectively). Participants who reported to have experienced more stress in the past year and lower life satisfaction, scored higher on alcohol-related problems (R2=0.27% and 0.29 respectively), but not on alcohol consumption. Stress and life satisfaction did not moderate the association between PRSs and the alcohol outcome measures. CONCLUSIONS There were significant main effects of polygenic scores and of stress and life satisfaction on drinking behavior, but there was no support for PRS-by-stress or PRS-by-life satisfaction interactions on alcohol consumption and alcohol-related problems.
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Affiliation(s)
- Gabry W Mies
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
| | - Karin J H Verweij
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
| | - Jorien L Treur
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
| | - Lannie Ligthart
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
| | - Iryna O Fedko
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
| | - Jouke Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
| | - Gonneke Willemsen
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands; Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Meike Bartels
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands; Amsterdam Public Health Research Institute, Amsterdam, The Netherlands; Amsterdam Neuroscience, The Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands; Amsterdam Public Health Research Institute, Amsterdam, The Netherlands; Amsterdam Neuroscience, The Netherlands
| | - Jacqueline M Vink
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands.
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Prom-Wormley EC, Ebejer J, Dick DM, Bowers MS. The genetic epidemiology of substance use disorder: A review. Drug Alcohol Depend 2017; 180:241-259. [PMID: 28938182 PMCID: PMC5911369 DOI: 10.1016/j.drugalcdep.2017.06.040] [Citation(s) in RCA: 82] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/28/2016] [Revised: 06/20/2017] [Accepted: 06/23/2017] [Indexed: 12/15/2022]
Abstract
BACKGROUND Substance use disorder (SUD) remains a significant public health issue. A greater understanding of how genes and environment interact to regulate phenotypes comprising SUD will facilitate directed treatments and prevention. METHODS The literature studying the neurobiological correlates of SUD with a focus on the genetic and environmental influences underlying these mechanisms was reviewed. Results from twin/family, human genetic association, gene-environment interaction, epigenetic literature, phenome-wide association studies are summarized for alcohol, nicotine, cannabinoids, cocaine, and opioids. RESULTS There are substantial genetic influences on SUD that are expected to influence multiple neurotransmission pathways, and these influences are particularly important within the dopaminergic system. Genetic influences involved in other aspects of SUD etiology including drug processing and metabolism are also identified. Studies of gene-environment interaction emphasize the importance of environmental context in SUD. Epigenetic studies indicate drug-specific changes in gene expression as well as differences in gene expression related to the use of multiple substances. Further, gene expression is expected to differ by stage of SUD such as substance initiation versus chronic substance use. While a substantial literature has developed for alcohol and nicotine use disorders, there is comparatively less information for other commonly abused substances. CONCLUSIONS A better understanding of genetically-mediated mechanisms involved in the neurobiology of SUD provides increased opportunity to develop behavioral and biologically based treatment and prevention of SUD.
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Affiliation(s)
- Elizabeth C Prom-Wormley
- Dvision of Epidemiology, Department of Family Medicine and Population Health, Virginia Commonwealth University, PO Box 980212, Richmond, VA 23298-0212, USA.
| | - Jane Ebejer
- School of Cognitive Behavioural and Social Sciences, University of New England, Armidale, NSW 2350, Australia
| | - Danielle M Dick
- Department of Psychology, Virginia Commonwealth University, PO Box 842509, Richmond, VA 23284-2509, USA
| | - M Scott Bowers
- Faulk Center for Molecular Therapeutics, Biomedical Engeneering, Northwestern University, Evanston, IL 60201, USA
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Kong X, Deng H, Gong S, Alston T, Kong Y, Wang J. Lack of associations of the opioid receptor mu 1 (OPRM1) A118G polymorphism (rs1799971) with alcohol dependence: review and meta-analysis of retrospective controlled studies. BMC MEDICAL GENETICS 2017; 18:120. [PMID: 29070014 PMCID: PMC5657079 DOI: 10.1186/s12881-017-0478-4] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/27/2017] [Accepted: 10/12/2017] [Indexed: 12/13/2022]
Abstract
Background Studies have sought associations of the opioid receptor mu 1 (OPRM1) A118G polymorphism (rs1799971) with alcohol-dependence, but findings are inconsistent. We summarize the information as to associations of rs1799971 (A > G) and the alcohol-dependence. Methods Systematically, we reviewed related literatures using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline. Embase, PubMed, Web of Knowledge, and Chinese National Knowledge Infrastructure (CNKI) databases were searched using select medical subject heading (MeSH) terms to identify all researches focusing on the present topic up to September 2016. Odds ratios (ORs) along with the 95% confidence interval (95% CI) were estimated in allele model, homozygote model, heterozygote model, dominant model and recessive model. Ethnicity-specific subgroup-analysis, sensitivity analysis, heterogeneity description, and publication-bias assessment were also analyzed. Results There were 17 studies, including 9613 patients in the present meta-analysis. The ORs in the 5 genetic-models were 1.037 (95% CI: 0.890, 1.210; p = 0.64), 1.074 (95% CI: 0.831, 1.387; p = 0.586), 1.155 (95% CI: 0.935, 1.427; p = 0.181), 1.261 (95% CI: 1.008, 1.578; p = 0.042), 0.968 (95% CI: 0.758, 1.236; p = 0.793), respectively. An association is significant in the dominant model, but there is no statistical significance upon ethnicity-specific subgroup analysis. Conclusion The rs1799971 (A > G) is not strongly associated with alcohol-dependence. However, there are study heterogeneities and limited sample sizes.
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Affiliation(s)
- Xiangyi Kong
- Department of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, No. 1 Shuaifuyuan Hutong, Dongcheng District, Beijing, 100730, People's Republic of China.,Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Harvard University, 55 Fruit Street, Boston, MA, 02114-3117, USA.,Department of Breast Surgical Oncology, China National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Chaoyangqu, Panjiayuan, Beijing, People's Republic of China
| | - Hao Deng
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Harvard University, 55 Fruit Street, Boston, MA, 02114-3117, USA
| | - Shun Gong
- Department of Neurosurgery, Shanghai Institute of Neurosurgery, PLA Institute of Neurosurgery, Shanghai Changzheng Hospital, Second Military Medical University, 415 Fengyang Road, Shanghai, 200003, People's Republic of China.,Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, 1249 Boylston St, Boston, MA, 02215, USA
| | - Theodore Alston
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Harvard University, 55 Fruit Street, Boston, MA, 02114-3117, USA
| | - Yanguo Kong
- Department of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, No. 1 Shuaifuyuan Hutong, Dongcheng District, Beijing, 100730, People's Republic of China.
| | - Jingping Wang
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Harvard University, 55 Fruit Street, Boston, MA, 02114-3117, USA.
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Yeung EW, Craggs JG, Gizer IR. Comorbidity of Alcohol Use Disorder and Chronic Pain: Genetic Influences on Brain Reward and Stress Systems. Alcohol Clin Exp Res 2017; 41:1831-1848. [PMID: 29048744 DOI: 10.1111/acer.13491] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2017] [Accepted: 08/25/2017] [Indexed: 01/10/2023]
Abstract
Alcohol use disorder (AUD) is highly comorbid with chronic pain (CP). Evidence has suggested that neuroadaptive processes characterized by reward deficit and stress surfeit are involved in the development of AUD and pain chronification. Neurological data suggest that shared genetic architecture associated with the reward and stress systems may contribute to the comorbidity of AUD and CP. This monograph first delineates the prevailing theories of the development of AUD and pain chronification focusing on the reward and stress systems. It then provides a brief summary of relevant neurological findings followed by an evaluation of evidence documented by molecular genetic studies. Candidate gene association studies have provided some initial support for the genetic overlap between AUD and CP; however, these results must be interpreted with caution until studies with sufficient statistical power are conducted and replications obtained. Genomewide association studies have suggested a number of genes (e.g., TBX19, HTR7, and ADRA1A) that are either directly or indirectly related to the reward and stress systems in the AUD and CP literature. Evidence reviewed in this monograph suggests that shared genetic liability underlying the comorbidity between AUD and CP, if present, is likely to be complex. As the advancement in molecular genetic methods continues, future studies may show broader central nervous system involvement in AUD-CP comorbidity.
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Affiliation(s)
- Ellen W Yeung
- Department of Psychological Sciences, University of Missouri, Columbia, Missouri.,Institute for Interdisciplinary Salivary Bioscience Research, University of California at Irvine, Irvine, California
| | - Jason G Craggs
- Department of Psychological Sciences, University of Missouri, Columbia, Missouri.,School of Health Professions, University of Missouri, Columbia, Missouri
| | - Ian R Gizer
- Department of Psychological Sciences, University of Missouri, Columbia, Missouri
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Genome-wide association study of alcohol consumption and genetic overlap with other health-related traits in UK Biobank (N=112 117). Mol Psychiatry 2017; 22:1376-1384. [PMID: 28937693 PMCID: PMC5622124 DOI: 10.1038/mp.2017.153] [Citation(s) in RCA: 284] [Impact Index Per Article: 40.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2017] [Revised: 05/02/2017] [Accepted: 05/08/2017] [Indexed: 11/19/2022]
Abstract
Alcohol consumption has been linked to over 200 diseases and is responsible for over 5% of the global disease burden. Well-known genetic variants in alcohol metabolizing genes, for example, ALDH2 and ADH1B, are strongly associated with alcohol consumption but have limited impact in European populations where they are found at low frequency. We performed a genome-wide association study (GWAS) of self-reported alcohol consumption in 112 117 individuals in the UK Biobank (UKB) sample of white British individuals. We report significant genome-wide associations at 14 loci. These include single-nucleotide polymorphisms (SNPs) in alcohol metabolizing genes (ADH1B/ADH1C/ADH5) and two loci in KLB, a gene recently associated with alcohol consumption. We also identify SNPs at novel loci including GCKR, CADM2 and FAM69C. Gene-based analyses found significant associations with genes implicated in the neurobiology of substance use (DRD2, PDE4B). GCTA analyses found a significant SNP-based heritability of self-reported alcohol consumption of 13% (se=0.01). Sex-specific analyses found largely overlapping GWAS loci and the genetic correlation (rG) between male and female alcohol consumption was 0.90 (s.e.=0.09, P-value=7.16 × 10-23). Using LD score regression, genetic overlap was found between alcohol consumption and years of schooling (rG=0.18, s.e.=0.03), high-density lipoprotein cholesterol (rG=0.28, s.e.=0.05), smoking (rG=0.40, s.e.=0.06) and various anthropometric traits (for example, overweight, rG=-0.19, s.e.=0.05). This study replicates the association between alcohol consumption and alcohol metabolizing genes and KLB, and identifies novel gene associations that should be the focus of future studies investigating the neurobiology of alcohol consumption.
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Tollenaar MS, Molendijk ML, Penninx BWJH, Milaneschi Y, Antypa N. The association of childhood maltreatment with depression and anxiety is not moderated by the oxytocin receptor gene. Eur Arch Psychiatry Clin Neurosci 2017; 267:517-526. [PMID: 28353027 PMCID: PMC5561157 DOI: 10.1007/s00406-017-0784-z] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2016] [Accepted: 03/13/2017] [Indexed: 12/31/2022]
Abstract
BACKGROUND The oxytocin receptor (OXTR) gene may be involved in resilience or vulnerability towards stress, and hence in the development of stress-related disorders. There are indications that OXTR single nucleotide polymorphisms (SNPs) interact with early life stressors in predicting levels of depression and anxiety. To replicate and extend these findings, we examined whether three literature-based OXTR SNPs (rs2254298, rs53576, rs2268498) interact with childhood maltreatment in the development of clinically diagnosed depression and anxiety disorders. METHODS We included 2567 individuals from the Netherlands Study of Depression and Anxiety. This sample consisted of 387 healthy controls, 428 people with a current or past depressive disorder, 243 people with a current or past anxiety disorder, and 1509 people with both lifetime depression and anxiety diagnoses. Childhood maltreatment was measured with both an interview and via self-report. Additional questionnaires measured depression and anxiety sensitivity. RESULTS Childhood maltreatment was strongly associated with both lifetime depression and anxiety diagnoses, as well as with depression and anxiety sensitivity. However, the OXTR SNPs did not moderate these associations nor had main effects on outcomes. CONCLUSIONS The three OXTR gene SNPs did not interact with childhood maltreatment in predicting lifetime depression and anxiety diagnoses or sensitivity. This stresses the importance of replication studies with regard to OXTR gene variants in general populations as well as in clearly established clinical samples.
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Affiliation(s)
- Marieke S Tollenaar
- Department of Clinical Psychology, Institute of Psychology, Leiden Institute for Brain and Cognition, Leiden University, P.O. Box 9555, 2300 RB, Leiden, The Netherlands.
| | - Marc L Molendijk
- Department of Clinical Psychology, Institute of Psychology, Leiden Institute for Brain and Cognition, Leiden University, P.O. Box 9555, 2300 RB, Leiden, The Netherlands
| | - Brenda W J H Penninx
- Department of Psychiatry, EMGO Institute for Health and Care Research and Neuroscience Campus Amsterdam, VU University Medical Center/GGZ inGeest, Amsterdam, The Netherlands
| | - Yuri Milaneschi
- Department of Psychiatry, EMGO Institute for Health and Care Research and Neuroscience Campus Amsterdam, VU University Medical Center/GGZ inGeest, Amsterdam, The Netherlands
| | - Niki Antypa
- Department of Clinical Psychology, Institute of Psychology, Leiden Institute for Brain and Cognition, Leiden University, P.O. Box 9555, 2300 RB, Leiden, The Netherlands.
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Jorgenson E, Thai KK, Hoffmann TJ, Sakoda LC, Kvale MN, Banda Y, Schaefer C, Risch N, Mertens J, Weisner C, Choquet H. Genetic contributors to variation in alcohol consumption vary by race/ethnicity in a large multi-ethnic genome-wide association study. Mol Psychiatry 2017; 22:1359-1367. [PMID: 28485404 PMCID: PMC5568932 DOI: 10.1038/mp.2017.101] [Citation(s) in RCA: 95] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2016] [Revised: 03/03/2017] [Accepted: 03/27/2017] [Indexed: 01/08/2023]
Abstract
Alcohol consumption is a complex trait determined by both genetic and environmental factors, and is correlated with the risk of alcohol use disorders. Although a small number of genetic loci have been reported to be associated with variation in alcohol consumption, genetic factors are estimated to explain about half of the variance in alcohol consumption, suggesting that additional loci remain to be discovered. We conducted a genome-wide association study (GWAS) of alcohol consumption in the large Genetic Epidemiology Research in Adult Health and Aging (GERA) cohort, in four race/ethnicity groups: non-Hispanic whites, Hispanic/Latinos, East Asians and African Americans. We examined two statistically independent phenotypes reflecting subjects' alcohol consumption during the past year, based on self-reported information: any alcohol intake (drinker/non-drinker status) and the regular quantity of drinks consumed per week (drinks/week) among drinkers. We assessed these two alcohol consumption phenotypes in each race/ethnicity group, and in a combined trans-ethnic meta-analysis comprising a total of 86 627 individuals. We observed the strongest association between the previously reported single nucleotide polymorphism (SNP) rs671 in ALDH2 and alcohol drinker status (odd ratio (OR)=0.40, P=2.28 × 10-72) in East Asians, and also an effect on drinks/week (beta=-0.17, P=5.42 × 10-4) in the same group. We also observed a genome-wide significant association in non-Hispanic whites between the previously reported SNP rs1229984 in ADH1B and both alcohol consumption phenotypes (OR=0.79, P=2.47 × 10-20 for drinker status and beta=-0.19, P=1.91 × 10-35 for drinks/week), which replicated in Hispanic/Latinos (OR=0.72, P=4.35 × 10-7 and beta=-0.21, P=2.58 × 10-6, respectively). Although prior studies reported effects of ADH1B and ALDH2 on lifetime measures, such as risk of alcohol dependence, our study adds further evidence of the effect of the same genes on a cross-sectional measure of average drinking. Our trans-ethnic meta-analysis confirmed recent findings implicating the KLB and GCKR loci in alcohol consumption, with strongest associations observed for rs7686419 (beta=-0.04, P=3.41 × 10-10 for drinks/week and OR=0.96, P=4.08 × 10-5 for drinker status), and rs4665985 (beta=0.04, P=2.26 × 10-8 for drinks/week and OR=1.04, P=5 × 10-4 for drinker status), respectively. Finally, we also obtained confirmatory results extending previous findings implicating AUTS2, SGOL1 and SERPINC1 genes in alcohol consumption traits in non-Hispanic whites.
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Affiliation(s)
- Eric Jorgenson
- Kaiser Permanente Division of Research, Oakland, CA, USA
| | - Khanh K. Thai
- Kaiser Permanente Division of Research, Oakland, CA, USA
| | - Thomas J. Hoffmann
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA,Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - Lori C. Sakoda
- Kaiser Permanente Division of Research, Oakland, CA, USA
| | - Mark N. Kvale
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - Yambazi Banda
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | | | - Neil Risch
- Kaiser Permanente Division of Research, Oakland, CA, USA,Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA,Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | | | - Constance Weisner
- Kaiser Permanente Division of Research, Oakland, CA, USA,Department of Psychiatry, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Hélène Choquet
- Kaiser Permanente Division of Research, Oakland, CA, USA
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Webb BT, Edwards AC, Wolen AR, Salvatore JE, Aliev F, Riley BP, Sun C, Williamson VS, Kitchens JN, Pedersen K, Adkins A, Cooke ME, Savage JE, Neale Z, Cho SB, Dick DM, Kendler KS. Molecular Genetic Influences on Normative and Problematic Alcohol Use in a Population-Based Sample of College Students. Front Genet 2017; 8:30. [PMID: 28360924 PMCID: PMC5350109 DOI: 10.3389/fgene.2017.00030] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2016] [Accepted: 02/27/2017] [Indexed: 11/13/2022] Open
Abstract
Background: Genetic factors impact alcohol use behaviors and these factors may become increasingly evident during emerging adulthood. Examination of the effects of individual variants as well as aggregate genetic variation can clarify mechanisms underlying risk. Methods: We conducted genome-wide association studies (GWAS) in an ethnically diverse sample of college students for three quantitative outcomes including typical monthly alcohol consumption, alcohol problems, and maximum number of drinks in 24 h. Heritability based on common genetic variants (h2SNP) was assessed. We also evaluated whether risk variants in aggregate were associated with alcohol use outcomes in an independent sample of young adults. Results: Two genome-wide significant markers were observed: rs11201929 in GRID1 for maximum drinks in 24 h, with supportive evidence across all ancestry groups; and rs73317305 in SAMD12 (alcohol problems), tested only in the African ancestry group. The h2SNP estimate was 0.19 (SE = 0.11) for consumption, and was non-significant for other outcomes. Genome-wide polygenic scores were significantly associated with alcohol outcomes in an independent sample. Conclusions: These results robustly identify genetic risk for alcohol use outcomes at the variant level and in aggregate. We confirm prior evidence that genetic variation in GRID1 impacts alcohol use, and identify novel loci of interest for multiple alcohol outcomes in emerging adults. These findings indicate that genetic variation influencing normative and problematic alcohol use is, to some extent, convergent across ancestry groups. Studying college populations represents a promising avenue by which to obtain large, diverse samples for gene identification.
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Affiliation(s)
- Bradley T Webb
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth UniversityRichmond, VA, USA; Department of Psychiatry, Virginia Commonwealth UniversityRichmond, VA, USA; Department of Human and Molecular Genetics, Virginia Commonwealth UniversityRichmond, VA, USA
| | - Alexis C Edwards
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth UniversityRichmond, VA, USA; Department of Psychiatry, Virginia Commonwealth UniversityRichmond, VA, USA
| | - Aaron R Wolen
- Center for Clinical and Translational Research, Virginia Commonwealth University Richmond, VA, USA
| | - Jessica E Salvatore
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth UniversityRichmond, VA, USA; Department of Psychology, Virginia Commonwealth UniversityRichmond, VA, USA
| | - Fazil Aliev
- Department of African-American Studies, Virginia Commonwealth UniversityRichmond, VA, USA; Faculty of Business, Karabuk UniversityKarabuk, Turkey; College Behavioral and Emotional Health Institute, Virginia Commonwealth UniversityRichmond, VA, USA
| | - Brien P Riley
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth UniversityRichmond, VA, USA; Department of Psychiatry, Virginia Commonwealth UniversityRichmond, VA, USA; Department of Human and Molecular Genetics, Virginia Commonwealth UniversityRichmond, VA, USA
| | - Cuie Sun
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth UniversityRichmond, VA, USA; Department of Psychiatry, Virginia Commonwealth UniversityRichmond, VA, USA
| | - Vernell S Williamson
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University Richmond, VA, USA
| | - James N Kitchens
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University Richmond, VA, USA
| | - Kimberly Pedersen
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth UniversityRichmond, VA, USA; Department of Psychiatry, Virginia Commonwealth UniversityRichmond, VA, USA; College Behavioral and Emotional Health Institute, Virginia Commonwealth UniversityRichmond, VA, USA
| | - Amy Adkins
- Department of Psychology, Virginia Commonwealth UniversityRichmond, VA, USA; College Behavioral and Emotional Health Institute, Virginia Commonwealth UniversityRichmond, VA, USA
| | - Megan E Cooke
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth UniversityRichmond, VA, USA; College Behavioral and Emotional Health Institute, Virginia Commonwealth UniversityRichmond, VA, USA
| | - Jeanne E Savage
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth UniversityRichmond, VA, USA; College Behavioral and Emotional Health Institute, Virginia Commonwealth UniversityRichmond, VA, USA
| | - Zoe Neale
- Department of Psychology, Virginia Commonwealth UniversityRichmond, VA, USA; College Behavioral and Emotional Health Institute, Virginia Commonwealth UniversityRichmond, VA, USA
| | - Seung B Cho
- Department of Psychology, Virginia Commonwealth UniversityRichmond, VA, USA; College Behavioral and Emotional Health Institute, Virginia Commonwealth UniversityRichmond, VA, USA
| | - Danielle M Dick
- Department of Human and Molecular Genetics, Virginia Commonwealth UniversityRichmond, VA, USA; Department of Psychology, Virginia Commonwealth UniversityRichmond, VA, USA; Department of African-American Studies, Virginia Commonwealth UniversityRichmond, VA, USA; College Behavioral and Emotional Health Institute, Virginia Commonwealth UniversityRichmond, VA, USA
| | - Kenneth S Kendler
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth UniversityRichmond, VA, USA; Department of Psychiatry, Virginia Commonwealth UniversityRichmond, VA, USA
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Li JJ, Cho SB, Salvatore JE, Edenberg HJ, Agrawal A, Chorlian DB, Porjesz B, Hesselbrock V, Dick DM. The Impact of Peer Substance Use and Polygenic Risk on Trajectories of Heavy Episodic Drinking Across Adolescence and Emerging Adulthood. Alcohol Clin Exp Res 2017; 41:65-75. [PMID: 27991676 PMCID: PMC5205549 DOI: 10.1111/acer.13282] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2016] [Accepted: 10/27/2016] [Indexed: 01/01/2023]
Abstract
BACKGROUND Heavy episodic drinking is developmentally normative among adolescents and young adults, but is linked to adverse consequences in later life, such as drug and alcohol dependence. Genetic and peer influences are robust predictors of heavy episodic drinking in youth, but little is known about the interplay between polygenic risk and peer influences as they impact developmental patterns of heavy episodic drinking. METHODS Data were from a multisite prospective study of alcohol use among adolescents and young adults with genome-wide association data (n = 412). Generalized linear mixed models were used to characterize the initial status and slopes of heavy episodic drinking between age 15 and 28. Polygenic risk scores (PRS) were derived from a separate genome-wide association study for alcohol dependence and examined for their interaction with substance use among the adolescents' closest friends in predicting the initial status and slopes of heavy episodic drinking. RESULTS Close friend substance use was a robust predictor of adolescent heavy episodic drinking, even after controlling for parental knowledge and peer substance use in the school. PRS were predictive of the initial status and early patterns of heavy episodic drinking in males, but not in females. No interaction was detected between PRS and close friend substance use for heavy episodic drinking trajectories in either males or females. CONCLUSIONS Although substance use among close friends and genetic influences play an important role in predicting heavy episodic drinking trajectories, particularly during the late adolescent to early adult years, we found no evidence of interaction between these influences after controlling for other social processes, such as parental knowledge and broader substance use among other peers outside of close friends. The use of longitudinal models and accounting for multiple social influences may be crucial for future studies focused on uncovering gene-environment interplay. Clinical implications are also discussed.
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Affiliation(s)
- James J. Li
- Department of Psychology and Waisman Center, University of Wisconsin-Madison, Madison, WI
| | - Seung Bin Cho
- Department of Psychology, Virginia Commonwealth University, Richmond, VA
| | - Jessica E. Salvatore
- Department of Psychology, Virginia Commonwealth University, Richmond, VA
- Virginia Institute for Psychiatric and Behavioral Genetics, Richmond, VA
| | - Howard J. Edenberg
- Departments of Biochemistry and Molecular Biology and Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO
| | - David B. Chorlian
- Department of Psychiatry, State University of New York, Health Science Center at Brooklyn, New York, USA
| | - Bernice Porjesz
- Department of Psychiatry, State University of New York, Health Science Center at Brooklyn, New York, USA
| | - Victor Hesselbrock
- Department of Psychiatry, University of Connecticut, Farmington, CT, USA
| | | | - Danielle M. Dick
- Department of Psychology, Virginia Commonwealth University, Richmond, VA
- Virginia Institute for Psychiatric and Behavioral Genetics, Richmond, VA
- Department of African-American Studies, Virginia Commonwealth University, Richmond, VA
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Treur JL, Boomsma DI, Ligthart L, Willemsen G, Vink JM. Heritability of high sugar consumption through drinks and the genetic correlation with substance use. Am J Clin Nutr 2016; 104:1144-1150. [PMID: 27581476 DOI: 10.3945/ajcn.115.127324] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2015] [Accepted: 07/22/2016] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND High sugar consumption contributes to the rising prevalence of obesity. Sugar can have rewarding effects that are similar to, but less strong than, the effects of addictive substances. People who consume large amounts of sugar also tend to use more addictive substances, but it is unclear whether this is due to shared genetic or environmental risk factors. OBJECTIVE We examined whether there are genetic influences on the consumption of sugar-containing drinks and whether genetic factors can explain the association with substance use. DESIGN The frequency of consumption of sugar-containing drinks (e.g., cola, soft drinks, and energy drinks) and addictive substances (nicotine, caffeine, alcohol, cannabis, and illicit drugs) was obtained for 8586 twins who were registered at the Netherlands Twin Register (women: 68.7%; mean ± SD age: 33.5 ± 15.3 y). Participants were categorized as high or low sugar consumers (>1 compared with ≤1 SD above daily consumption in grams) and as high or low substance users (≥2 compared with <2 substances). Through bivariate genetic modeling, genetic and environmental influences on sugar consumption, substance use, and their association were estimated. RESULTS Genetic factors explained 48% of the variation in high sugar consumption, whereas unique environmental factors explained 52%. For high substance use, these values were 62% and 38%, respectively. There was a moderate phenotypic association between high sugar consumption and high substance use (r = 0.2), which was explained by genetic factors (59%) and unique environmental factors (41%). CONCLUSIONS The positive association between high sugar consumption and high substance use was partly due to unique environmental factors (e.g., social situations). Genetic factors were also of influence, suggesting that neuronal circuits underlying the development of addiction and obesity are related. Further research is needed to identify genes that influence sugar consumption and those that overlap with substance use.
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Affiliation(s)
- Jorien L Treur
- Department of Biological Psychology, Vrije University (VU) Amsterdam, Amsterdam, Netherlands; EMGO+ Institute for Health and Care Research and
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije University (VU) Amsterdam, Amsterdam, Netherlands; EMGO+ Institute for Health and Care Research and Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, Netherlands; and
| | - Lannie Ligthart
- Department of Biological Psychology, Vrije University (VU) Amsterdam, Amsterdam, Netherlands; EMGO+ Institute for Health and Care Research and
| | - Gonneke Willemsen
- Department of Biological Psychology, Vrije University (VU) Amsterdam, Amsterdam, Netherlands; EMGO+ Institute for Health and Care Research and
| | - Jacqueline M Vink
- Department of Biological Psychology, Vrije University (VU) Amsterdam, Amsterdam, Netherlands; EMGO+ Institute for Health and Care Research and Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, Netherlands; and Behavioral Science Institute, Radboud University, Nijmegen, Netherlands
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