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Palmer RHC, Brick LA, Chou YL, Agrawal A, McGeary JE, Heath AC, Bierut L, Keller MC, Johnson E, Hartz SM, Schuckit MA, Knopik VS. The etiology of DSM-5 alcohol use disorder: Evidence of shared and non-shared additive genetic effects. Drug Alcohol Depend 2019; 201:147-154. [PMID: 31229702 PMCID: PMC6929687 DOI: 10.1016/j.drugalcdep.2018.12.034] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2018] [Revised: 11/29/2018] [Accepted: 12/06/2018] [Indexed: 12/20/2022]
Abstract
BACKGROUND Alcoholism is a multifactorial disorder influenced by multiple gene loci, each with small effect. Studies suggest shared genetic influences across DSM-IV alcohol dependence symptoms, but shared effects across DSM-5 alcohol use disorder remains unknown. We aimed to test the assumption of genetic homogeneity across the 11 criteria of DSM-5 alcohol use disorder (AUD). METHODS Data from 2596 alcohol using individuals of European ancestry from the Study of Addiction: Genetics and Environment were used to examine the genomewide SNP-heritability (h2SNP) and SNP-covariance (rGSNP) between 11 DSM-5 AUD symptoms. Phenotypic relationships between symptoms were examined to confirm an underlying liability of AUD and the SNP-heritability of the observed latent trait and the co-heritabilityamong AUD symptoms was assessed using Genomic-Relatedness-Matrix-Restricted-Maximum-Likelihood. Genetic covariance among symptoms was examined using factor analysis. RESULTS Phenotypic relationships confirmed a unidimensional underlying liability to AUD. Factor and parallel analyses of the observed genetic variance/covariance provided evidence of genetic homogeneity. Additive genetic effects on DSM-5 AUD symptoms varied from 0.10 to 0.37 and largely overlapped (rG-SNP across symptoms ranged from 0.49 - 0.92). The additive genetic effect on the DSM-5 AUD factor was 0.36, 0.14 for DSM-5 AUD diagnosis, and was 0.22 for DSM-5 AUD severity. CONCLUSIONS Common genetic variants influence DSM-5 AUD symptoms. Despite evidence for a common AUD factor, the evidence of only partially overlapping genetic effects across AUD symptoms further substantiates the need to simultaneously model common and symptom-specific genetic effects in molecular genetic studies in order to best characterize the genetic liability.
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Affiliation(s)
- Rohan H C Palmer
- Behavioral Genetics of Addiction Laboratory, Department of Psychology, Emory University, USA.
| | - Leslie A Brick
- Department of Psychiatry and Human Behavior, Brown University, USA; Division of Behavior Genetics, Department of Psychiatry, Rhode Island Hospital, USA
| | - Yi-Ling Chou
- Washington University in St. Louis, St. Louis, Missouri, USA
| | - Arpana Agrawal
- Washington University in St. Louis, St. Louis, Missouri, USA
| | - John E McGeary
- Department of Psychiatry and Human Behavior, Brown University, USA; Division of Behavior Genetics, Department of Psychiatry, Rhode Island Hospital, USA; Providence Veterans Affairs Medical Center, USA
| | - Andrew C Heath
- Washington University in St. Louis, St. Louis, Missouri, USA
| | - Laura Bierut
- Washington University in St. Louis, St. Louis, Missouri, USA
| | - Matthew C Keller
- Department of Psychology and Neuroscience, University of Colorado at Boulder, USA
| | | | - Sarah M Hartz
- Washington University in St. Louis, St. Louis, Missouri, USA
| | | | - Valerie S Knopik
- Department of Human Development and Family Studies, Purdue University, USA
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102
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Wetherill L, Lai D, Johnson EC, Anokhin A, Bauer L, Bucholz KK, Dick DM, Hariri AR, Hesselbrock V, Kamarajan C, Kramer J, Kuperman S, Meyers JL, Nurnberger JI, Schuckit M, Scott DM, Taylor RE, Tischfield J, Porjesz B, Goate AM, Edenberg HJ, Foroud T, Bogdan R, Agrawal A. Genome-wide association study identifies loci associated with liability to alcohol and drug dependence that is associated with variability in reward-related ventral striatum activity in African- and European-Americans. GENES, BRAIN, AND BEHAVIOR 2019; 18:e12580. [PMID: 31099175 PMCID: PMC6726116 DOI: 10.1111/gbb.12580] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Revised: 04/19/2019] [Accepted: 05/11/2019] [Indexed: 02/07/2023]
Abstract
Genetic influences on alcohol and drug dependence partially overlap, however, specific loci underlying this overlap remain unclear. We conducted a genome-wide association study (GWAS) of a phenotype representing alcohol or illicit drug dependence (ANYDEP) among 7291 European-Americans (EA; 2927 cases) and 3132 African-Americans (AA: 1315 cases) participating in the family-based Collaborative Study on the Genetics of Alcoholism. ANYDEP was heritable (h 2 in EA = 0.60, AA = 0.37). The AA GWAS identified three regions with genome-wide significant (GWS; P < 5E-08) single nucleotide polymorphisms (SNPs) on chromosomes 3 (rs34066662, rs58801820) and 13 (rs75168521, rs78886294), and an insertion-deletion on chromosome 5 (chr5:141988181). No polymorphisms reached GWS in the EA. One GWS region (chromosome 1: rs1890881) emerged from a trans-ancestral meta-analysis (EA + AA) of ANYDEP, and was attributable to alcohol dependence in both samples. Four genes (AA: CRKL, DZIP3, SBK3; EA: P2RX6) and four sets of genes were significantly enriched within biological pathways for hemostasis and signal transduction. GWS signals did not replicate in two independent samples but there was weak evidence for association between rs1890881 and alcohol intake in the UK Biobank. Among 118 AA and 481 EA individuals from the Duke Neurogenetics Study, rs75168521 and rs1890881 genotypes were associated with variability in reward-related ventral striatum activation. This study identified novel loci for substance dependence and provides preliminary evidence that these variants are also associated with individual differences in neural reward reactivity. Gene discovery efforts in non-European samples with distinct patterns of substance use may lead to the identification of novel ancestry-specific genetic markers of risk.
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Affiliation(s)
- Leah Wetherill
- Indiana University. Department of Medical and Molecular Genetics, Indiana University School of Medicine. Indianapolis, IN
| | - Dongbing Lai
- Indiana University. Department of Medical and Molecular Genetics, Indiana University School of Medicine. Indianapolis, IN
| | - Emma C. Johnson
- Washington University. Washington University School of Medicine, Department of Psychiatry. Saint Louis, MO. USA
| | - Andrey Anokhin
- Washington University. Washington University School of Medicine, Department of Psychiatry. Saint Louis, MO. USA
| | - Lance Bauer
- University of Connecticut. University of Connecticut School of Medicine, Department of Psychiatry. Farmington, CT
| | - Kathleen K. Bucholz
- Washington University. Washington University School of Medicine, Department of Psychiatry. Saint Louis, MO. USA
| | - Danielle M. Dick
- Virginia Commonwealth University. Department of Psychology & College Behavioral and Emotional Health Institute, Virginia Commonwealth University. Richmond, VA
| | - Ahmad R. Hariri
- Duke Institute for Brain Sciences, Dept. of Psychology, Duke University, Durham, NC
| | - Victor Hesselbrock
- University of Connecticut. University of Connecticut School of Medicine, Department of Psychiatry. Farmington, CT
| | - Chella Kamarajan
- SUNY. Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center. Brooklyn, NY
| | - John Kramer
- University of Iowa. University of Iowa Roy J and Lucille A Carver College of Medicine, Department of Psychiatry. Iowa City, IA
| | - Samuel Kuperman
- University of Iowa. University of Iowa Roy J and Lucille A Carver College of Medicine, Department of Psychiatry. Iowa City, IA
| | - Jacquelyn L. Meyers
- SUNY. Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center. Brooklyn, NY
| | - John I. Nurnberger
- Indiana University. Department of Psychiatry, Indiana University School of Medicine. Indianapolis, IN
| | - Marc Schuckit
- University of California San Diego. University of California San Diego, Department of Psychiatry. San Diego, CA
| | - Denise M. Scott
- Howard University, Departments of Pediatrics and Human Genetics, Washington, DC
| | | | | | - Bernice Porjesz
- SUNY. Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center. Brooklyn, NY
| | - Alison M. Goate
- Department of Neuroscience, Icahn School of Medicine at Mt. Sinai, New York, NY
| | - Howard J. Edenberg
- Indiana University. Department of Medical and Molecular Genetics, Indiana University School of Medicine. Indianapolis, IN
- Indiana University. Department of Biochemistry and Molecular Biology, Indiana University School of Medicine. Indianapolis, IN
| | - Tatiana Foroud
- Indiana University. Department of Medical and Molecular Genetics, Indiana University School of Medicine. Indianapolis, IN
| | - Ryan Bogdan
- Washington University in Saint Louis, Department of Psychological and Brain Sciences, Saint Louis, MO, USA
| | - Arpana Agrawal
- Washington University. Washington University School of Medicine, Department of Psychiatry. Saint Louis, MO. USA
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103
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Lai D, Wetherill L, Bertelsen S, Carey CE, Kamarajan C, Kapoor M, Meyers JL, Anokhin AP, Bennett DA, Bucholz KK, Chang KK, De Jager PL, Dick DM, Hesselbrock V, Kramer J, Kuperman S, Nurnberger JI, Raj T, Schuckit M, Scott DM, Taylor RE, Tischfield J, Hariri AR, Edenberg HJ, Agrawal A, Bogdan R, Porjesz B, Goate AM, Foroud T. Genome-wide association studies of alcohol dependence, DSM-IV criterion count and individual criteria. GENES, BRAIN, AND BEHAVIOR 2019; 18:e12579. [PMID: 31090166 PMCID: PMC6612573 DOI: 10.1111/gbb.12579] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Revised: 04/19/2019] [Accepted: 05/11/2019] [Indexed: 01/04/2023]
Abstract
Genome-wide association studies (GWAS) of alcohol dependence (AD) have reliably identified variation within alcohol metabolizing genes (eg, ADH1B) but have inconsistently located other signals, which may be partially attributable to symptom heterogeneity underlying the disorder. We conducted GWAS of DSM-IV AD (primary analysis), DSM-IV AD criterion count (secondary analysis), and individual dependence criteria (tertiary analysis) among 7418 (1121 families) European American (EA) individuals from the Collaborative Study on the Genetics of Alcoholism (COGA). Trans-ancestral meta-analyses combined these results with data from 3175 (585 families) African-American (AA) individuals from COGA. In the EA GWAS, three loci were genome-wide significant: rs1229984 in ADH1B for AD criterion count (P = 4.16E-11) and Desire to cut drinking (P = 1.21E-11); rs188227250 (chromosome 8, Drinking more than intended, P = 6.72E-09); rs1912461 (chromosome 15, Time spent drinking, P = 1.77E-08). In the trans-ancestral meta-analysis, rs1229984 was associated with multiple phenotypes and two additional loci were genome-wide significant: rs61826952 (chromosome 1, DSM-IV AD, P = 8.42E-11); rs7597960 (chromosome 2, Time spent drinking, P = 1.22E-08). Associations with rs1229984 and rs18822750 were replicated in independent datasets. Polygenic risk scores derived from the EA GWAS of AD predicted AD in two EA datasets (P < .01; 0.61%-1.82% of variance). Identified novel variants (ie, rs1912461, rs61826952) were associated with differential central evoked theta power (loss - gain; P = .0037) and reward-related ventral striatum reactivity (P = .008), respectively. This study suggests that studying individual criteria may unveil new insights into the genetic etiology of AD liability.
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Affiliation(s)
- Dongbing Lai
- Department of Medical and Molecular Genetics, Indiana
University School of Medicine, Indianapolis, IN
| | - Leah Wetherill
- Department of Medical and Molecular Genetics, Indiana
University School of Medicine, Indianapolis, IN
| | - Sarah Bertelsen
- Department of Neuroscience, Icahn School of Medicine at Mt.
Sinai, New York, NY
| | - Caitlin E. Carey
- BRAIN Lab, Department of Psychological and Brain Sciences,
Washington University School of Medicine, St. Louis, MO
| | - Chella Kamarajan
- Henri Begleiter Neurodynamics Lab, Department of
Psychiatry, State University of New York, Downstate Medical Center, Brooklyn,
NY
| | - Manav Kapoor
- Department of Neuroscience, Icahn School of Medicine at Mt.
Sinai, New York, NY
| | - Jacquelyn L. Meyers
- Henri Begleiter Neurodynamics Lab, Department of
Psychiatry, State University of New York, Downstate Medical Center, Brooklyn,
NY
| | - Andrey P. Anokhin
- Department of Psychiatry, Washington University School of
Medicine, St. Louis, MO
| | - David A. Bennett
- Rush Alzheimer's Disease Center, Rush University
Medical Center, Chicago, IL
| | - Kathleen K. Bucholz
- Department of Psychiatry, Washington University School of
Medicine, St. Louis, MO
| | - Katharine K. Chang
- BRAIN Lab, Department of Psychological and Brain Sciences,
Washington University School of Medicine, St. Louis, MO
| | - Philip L. De Jager
- Departments of Neurology and Psychiatry, Brigham and
Women's Hospital, Boston, MA
| | - Danielle M. Dick
- Department of Psychology, Virginia Commonwealth University,
Richmond, VA
| | | | - John Kramer
- Department of Psychiatry, Roy Carver College of Medicine,
University of Iowa, Iowa City, IA
| | - Samuel Kuperman
- Department of Psychiatry, Roy Carver College of Medicine,
University of Iowa, Iowa City, IA
| | - John I. Nurnberger
- Department of Medical and Molecular Genetics, Indiana
University School of Medicine, Indianapolis, IN
- Department of Psychiatry, Indiana University School of
Medicine, Indianapolis, IN
| | - Towfique Raj
- Department of Neuroscience, Icahn School of Medicine at Mt.
Sinai, New York, NY
| | - Marc Schuckit
- Department of Psychiatry, University of California, San
Diego Medical School, San Diego, CA
| | - Denise M. Scott
- Departments of Pediatrics and Human Genetics, Howard
University, Washington, DC
| | | | | | - Ahmad R. Hariri
- Laboratory of NeuroGenetics, Department of Psychology and
Neuroscience, Duke University, Durham, NC, USA
| | - Howard J. Edenberg
- Department of Medical and Molecular Genetics, Indiana
University School of Medicine, Indianapolis, IN
- Department of Biochemistry and Molecular Biology, Indiana
University School of Medicine, Indianapolis, IN
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of
Medicine, St. Louis, MO
| | - Ryan Bogdan
- BRAIN Lab, Department of Psychological and Brain Sciences,
Washington University School of Medicine, St. Louis, MO
| | - Bernice Porjesz
- Henri Begleiter Neurodynamics Lab, Department of
Psychiatry, State University of New York, Downstate Medical Center, Brooklyn,
NY
| | - Alison M. Goate
- Department of Neuroscience, Icahn School of Medicine at Mt.
Sinai, New York, NY
| | - Tatiana Foroud
- Department of Medical and Molecular Genetics, Indiana
University School of Medicine, Indianapolis, IN
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104
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Hartwell EE, Kranzler HR. Pharmacogenetics of alcohol use disorder treatments: an update. Expert Opin Drug Metab Toxicol 2019; 15:553-564. [PMID: 31162983 DOI: 10.1080/17425255.2019.1628218] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
Introduction: Alcohol use disorder (AUD) is highly prevalent; costly economically, socially, and interpersonally; and grossly undertreated. The low rate of utilization of medications with demonstrated (albeit modest) efficacy is particularly noteworthy. One approach to increasing the utility and safety of available medications is to use a precision medicine approach, which seeks to identify patients for whom specific medications are likely to be most efficacious and have the fewest adverse effects. Areas Covered: We review the literature on the pharmacogenetics of AUD treatment using both approved and off-label medications. We cover both laboratory studies and clinical trials, highlighting valuable mechanistic insights and underscoring the potential value of precision-based care for AUD. Expert Opinion: Pharmacotherapy can be a useful component of AUD treatment. Currently, the evidence regarding genetic predictors of medication efficacy is very limited. Thus, a precision medicine approach is not yet ready for widespread clinical implementation. Further research is needed to identify candidate genetic variants that moderate the response to both established and novel medications. The growing availability of large-scale, longitudinal datasets that enable the synthesis of genetic and electronic health record data provides important opportunities to develop this area of research.
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Affiliation(s)
- Emily E Hartwell
- a Mental Illness Research, Education and Clinical Center , Crescenz VAMC , Philadelphia , PA , USA.,b Center for Studies of Addiction, Department of Psychiatry , University of Pennsylvania Perelman School of Medicine , Philadelphia , PA , USA
| | - Henry R Kranzler
- a Mental Illness Research, Education and Clinical Center , Crescenz VAMC , Philadelphia , PA , USA.,b Center for Studies of Addiction, Department of Psychiatry , University of Pennsylvania Perelman School of Medicine , Philadelphia , PA , USA
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105
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Rosato AJ, Chen X, Tanaka Y, Farrer LA, Kranzler HR, Nunez YZ, Henderson DC, Gelernter J, Zhang H. Salivary microRNAs identified by small RNA sequencing and machine learning as potential biomarkers of alcohol dependence. Epigenomics 2019; 11:739-749. [PMID: 31140863 DOI: 10.2217/epi-2018-0177] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Aim: Salivary miRNA can be easily accessible biomarkers of alcohol dependence (AD). Materials & methods: The miRNA transcriptome in the saliva of 56 African-Americans (AAs; 28 AD patients/28 controls) and 64 European-Americans (EAs; 32 AD patients/32 controls) was profiled using small RNA sequencing. Differentially expressed miRNAs were identified. Salivary miRNAs were used to predict the AD presence using machine learning with Random Forests. Results: Seven miRNAs were differentially expressed in AA AD patients, and five miRNAs were differentially expressed in EA AD patients. The AD prediction accuracy based on top five miRNAs (ranked by Gini index) was 79.1 and 72.2% in AAs and EAs, respectively. Conclusion: This study provided the first evidence that salivary miRNAs are AD biomarkers.
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Affiliation(s)
- Andrew J Rosato
- Department of Psychiatry, Boston University School of Medicine, Boston, MA 02118, USA
| | - Xiaochun Chen
- Department of Psychiatry, Boston University School of Medicine, Boston, MA 02118, USA
| | - Yoshiaki Tanaka
- Department of Genetics, Yale University School of Medicine, New Haven, CT 06520, USA
| | - Lindsay A Farrer
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA 02118, USA.,Department of Neurology, Boston University School of Medicine, Boston, MA 02118, USA.,Department of Ophthalmology, Boston University School of Medicine, Boston, MA 02118, USA.,Department of Epidemiology & Boston University School of Public Health, Boston, MA 02118, USA.,Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Henry R Kranzler
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania & VISN4 MIRECC, Crescenz VAMC, Philadelphia, PA 19104, USA
| | - Yaira Z Nunez
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - David C Henderson
- Department of Psychiatry, Boston University School of Medicine, Boston, MA 02118, USA
| | - Joel Gelernter
- Department of Genetics, Yale University School of Medicine, New Haven, CT 06520, USA.,Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06511, USA.,Department of Neuroscience, Yale University School of Medicine, New Haven, CT 06510, USA.,VA Connecticut Healthcare System, West Haven, CT 06516, USA
| | - Huiping Zhang
- Department of Psychiatry, Boston University School of Medicine, Boston, MA 02118, USA.,Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA 02118, USA
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106
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Mignogna KM, Bacanu SA, Riley BP, Wolen AR, Miles MF. Cross-species alcohol dependence-associated gene networks: Co-analysis of mouse brain gene expression and human genome-wide association data. PLoS One 2019; 14:e0202063. [PMID: 31017905 PMCID: PMC6481773 DOI: 10.1371/journal.pone.0202063] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2018] [Accepted: 04/07/2019] [Indexed: 01/06/2023] Open
Abstract
Genome-wide association studies on alcohol dependence, by themselves, have yet to account for the estimated heritability of the disorder and provide incomplete mechanistic understanding of this complex trait. Integrating brain ethanol-responsive gene expression networks from model organisms with human genetic data on alcohol dependence could aid in identifying dependence-associated genes and functional networks in which they are involved. This study used a modification of the Edge-Weighted Dense Module Searching for genome-wide association studies (EW-dmGWAS) approach to co-analyze whole-genome gene expression data from ethanol-exposed mouse brain tissue, human protein-protein interaction databases and alcohol dependence-related genome-wide association studies. Results revealed novel ethanol-responsive and alcohol dependence-associated gene networks in prefrontal cortex, nucleus accumbens, and ventral tegmental area. Three of these networks were overrepresented with genome-wide association signals from an independent dataset. These networks were significantly overrepresented for gene ontology categories involving several mechanisms, including actin filament-based activity, transcript regulation, Wnt and Syndecan-mediated signaling, and ubiquitination. Together, these studies provide novel insight for brain mechanisms contributing to alcohol dependence.
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Affiliation(s)
- Kristin M. Mignogna
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, United States of America
- VCU Alcohol Research Center, Virginia Commonwealth University, Richmond, Virginia, United States of America
- VCU Center for Clinical & Translational Research, Virginia Commonwealth University, Richmond, Virginia, United States of America
| | - Silviu A. Bacanu
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, United States of America
- VCU Alcohol Research Center, Virginia Commonwealth University, Richmond, Virginia, United States of America
| | - Brien P. Riley
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, United States of America
- VCU Alcohol Research Center, Virginia Commonwealth University, Richmond, Virginia, United States of America
| | - Aaron R. Wolen
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, Virginia, United States of America
| | - Michael F. Miles
- VCU Alcohol Research Center, Virginia Commonwealth University, Richmond, Virginia, United States of America
- Department of Pharmacology and Toxicology, Virginia Commonwealth University, Richmond, Virginia, United States of America
- * E-mail:
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107
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Meda SA, Narayanan B, Chorlian D, Meyers JL, Gelernter J, Hesselbrock V, Bauer L, Calhoun VD, Porjesz B, Pearlson GD. Multivariate Analyses Reveal Biological Components Related to Neuronal Signaling and Immunity Mediating Electroencephalograms Abnormalities in Alcohol-Dependent Individuals from the Collaborative Study on the Genetics of Alcoholism Cohort. Alcohol Clin Exp Res 2019; 43:1462-1477. [PMID: 31009096 DOI: 10.1111/acer.14063] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2018] [Revised: 04/08/2019] [Accepted: 04/11/2019] [Indexed: 12/22/2022]
Abstract
BACKGROUND The underlying molecular mechanisms associated with alcohol use disorder (AUD) risk have only been partially revealed using traditional approaches such as univariate genomewide association and linkage-based analyses. We therefore aimed to identify gene clusters related to Electroencephalograms (EEG) neurobiological phenotypes distinctive to individuals with AUD using a multivariate approach. METHODS The current project adopted a bimultivariate data-driven approach, parallel independent component analysis (para-ICA), to derive and explore significant genotype-phenotype associations in a case-control subset of the Collaborative Study on the Genetics of Alcoholism (COGA) dataset. Para-ICA subjects comprised N = 799 self-reported European Americans (367 controls and 432 AUD cases), recruited from COGA, who had undergone resting EEG and genotyping. Both EEG and genomewide single nucleotide polymorphism (SNP) data were preprocessed prior to being subjected to para-ICA in order to derive genotype-phenotype relationships. RESULTS From the data, 4 EEG frequency and 4 SNP components were estimated, with 2 significantly correlated EEG-genetic relationship pairs. The first such pair primarily represented theta activity, negatively correlated with a genetic cluster enriched for (but not limited to) ontologies/disease processes representing cell signaling, neurogenesis, transmembrane drug transportation, alcoholism, and lipid/cholesterol metabolism. The second component pair represented mainly alpha activity, positively correlated with a genetic cluster with ontologies similarly enriched as the first component. Disease-related enrichments for this component revealed heart and autoimmune disorders as top hits. Loading coefficients for both the alpha and theta components were significantly reduced in cases compared to controls. CONCLUSIONS Our data suggest plausible multifactorial genetic components, primarily enriched for neuronal/synaptic signaling/transmission, immunity, and neurogenesis, mediating low-frequency alpha and theta abnormalities in alcohol addiction.
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Affiliation(s)
- Shashwath A Meda
- Olin Neuropsychiatry Research Center, Hartford Hospital/IOL, Hartford, Connecticut
| | - Balaji Narayanan
- Olin Neuropsychiatry Research Center, Hartford Hospital/IOL, Hartford, Connecticut
| | - David Chorlian
- Department of Psychiatry, SUNY Downstate Medical Center, Brooklyn, New York
| | - Jacquelyn L Meyers
- Department of Psychiatry, SUNY Downstate Medical Center, Brooklyn, New York
| | - Joel Gelernter
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
| | | | - Lance Bauer
- Department of Psychiatry, UConn Health, Farmington, Connecticut
| | | | - Bernice Porjesz
- Department of Psychiatry, SUNY Downstate Medical Center, Brooklyn, New York
| | - Godfrey D Pearlson
- Olin Neuropsychiatry Research Center, Hartford Hospital/IOL, Hartford, Connecticut.,Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut
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108
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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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109
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Kim J, Marciano MA, Ninham S, Zaso MJ, Park A. Interaction Effects between the Cumulative Genetic Score and Psychosocial Stressor on Self-Reported Drinking Urge and Implicit Attentional Bias for Alcohol: A Human Laboratory Study. Alcohol Alcohol 2019; 54:30-37. [PMID: 30192917 DOI: 10.1093/alcalc/agy065] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2018] [Accepted: 08/22/2018] [Indexed: 01/27/2023] Open
Abstract
Aims The current candidate gene and environment interaction (cGxE) study examined whether the effects of an experimentally manipulated psychosocial stressor on self-reported drinking urge and implicit attentional bias for alcohol cues differ as a function of a cumulative genetic score of 5-HTTLPR, MAO-A, DRD4, DAT1 and DRD2 genotypes. The current study also examined whether salivary alpha-amylase level or self-reported anxiety state mediate these cGxE effects. Short Summary Individuals with high cumulative genetic risk score of the five monoamergic genotypes showed greater attentional bias toward alcohol cues when exposed to a psychosocial stressor than when not exposed. Methods Frequent binge-drinking Caucasian young adults (N = 105; mean age = 19; 61% male) completed both the control condition and stress condition (using the Trier Social Stress Test) in order. Results Regarding attentional bias, individuals with high and medium cumulative genetic risk scores showed greater attentional bias toward alcohol stimuli in the stress condition than in the control condition, whereas, those with low genetic risk scores showed greater attentional bias toward alcohol stimuli in the control condition than in the stress condition. No mediating roles of salivary alpha-amylase and anxiety state in the cGxE effect were found. Regarding self-reported drinking urge, individuals with high cumulative genetic score reported greater drinking urge than those with low genetic score regardless of experimental conditions. Conclusions Although replication is necessary, the findings suggest that the association of a psychosocial stressor on implicit (but not explicit, self-reported) alcohol outcomes may differ as a function of the collective effects of five monoamine genes.
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Affiliation(s)
- Jueun Kim
- Department of Psychology, Handong Global University, Pohang, South Korea
| | - Michael A Marciano
- Forensic and National Security Sciences Institute, College of Arts and Sciences, Syracuse University, Syracuse, NY, USA
| | - Shyanne Ninham
- Department of Psychology, Syracuse University, Syracuse, NY, USA
| | - Michelle J Zaso
- Department of Psychology, Syracuse University, Syracuse, NY, USA
| | - Aesoon Park
- Department of Psychology, Syracuse University, Syracuse, NY, USA
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110
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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: 272] [Impact Index Per Article: 54.4] [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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111
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Montalvo-Ortiz JL, Cheng Z, Kranzler HR, Zhang H, Gelernter J. Genomewide Study of Epigenetic Biomarkers of Opioid Dependence in European- American Women. Sci Rep 2019; 9:4660. [PMID: 30874594 PMCID: PMC6420601 DOI: 10.1038/s41598-019-41110-7] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2018] [Accepted: 03/04/2019] [Indexed: 12/14/2022] Open
Abstract
There is currently an epidemic of opioid use, overdose, and dependence in the United States. Although opioid dependence (OD) is more prevalent in men, opioid relapse and fatal opioid overdoses have recently increased at a higher rate among women. Epigenetic mechanisms have been implicated in the etiology of OD, though most studies to date have used candidate gene approaches. We conducted the first epigenome-wide association study (EWAS) of OD in a sample of 220 European-American (EA) women (140 OD cases, 80 opioid-exposed controls). DNA was derived from whole blood samples and EWAS was implemented using the Illumina Infinium HumanMethylationEPIC array. To identify differentially methylated CpG sites, we performed an association analysis adjusting for age, estimates of cell proportions, smoking status, and the first three principal components to correct for population stratification. After correction for multiple testing, association analysis identified three genome-wide significant differentially methylated CpG sites mapping to the PARG, RERE, and CFAP77 genes. These genes are involved in chromatin remodeling, DNA binding, cell survival, and cell projection. Previous genome-wide association studies have identified RERE risk variants in association with psychiatric disorders and educational attainment. DNA methylation age in the peripheral blood did not differ between OD subjects and opioid-exposed controls. Our findings implicate epigenetic mechanisms in OD and, if replicated, identify possible novel peripheral biomarkers of OD that could inform the prevention and treatment of the disorder.
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Affiliation(s)
- Janitza L Montalvo-Ortiz
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- VA CT Healthcare Center, West Haven, CT, USA
| | - Zhongshan Cheng
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- VA CT Healthcare Center, West Haven, CT, USA
| | - Henry R Kranzler
- University of Pennsylvania Perelman School of Medicine, Department of Psychiatry, Center for Studies of Addiction and Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
| | - Huiping Zhang
- Departments of Psychiatry and Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA
| | - Joel Gelernter
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA.
- VA CT Healthcare Center, West Haven, CT, USA.
- Departments of Genetics and Neuroscience, Yale University School of Medicine, New Haven, USA.
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112
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Abstract
PURPOSE OF REVIEW We review the search for genetic variants that affect the risk for alcohol dependence and alcohol consumption. RECENT FINDINGS Variations in genes affecting alcohol metabolism (ADH1B, ALDH2) are protective against both alcohol dependence and excessive consumption, but different variants are found in different populations. There are different patterns of risk variants for alcohol dependence vs. consumption. Variants for alcohol dependence, but not consumption, are associated with risk for other psychiatric illnesses. ADH1B and ALDH2 strongly affect both consumption and dependence. Variations in many other genes affect both consumption and dependence-or one or the other of these traits-but individual effect sizes are small. Evidence for other specific genes that affect dependence is not yet strong. Most current knowledge derives from studies of European-ancestry populations, and large studies of carefully phenotyped subjects from different populations are needed to understand the genetic contributions to alcohol consumption and alcohol use disorders.
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113
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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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114
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Analysis of whole genome-transcriptomic organization in brain to identify genes associated with alcoholism. Transl Psychiatry 2019; 9:89. [PMID: 30765688 PMCID: PMC6376002 DOI: 10.1038/s41398-019-0384-y] [Citation(s) in RCA: 54] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/06/2018] [Accepted: 01/02/2019] [Indexed: 02/07/2023] Open
Abstract
Alcohol exposure triggers changes in gene expression and biological pathways in human brain. We explored alterations in gene expression in the Pre-Frontal Cortex (PFC) of 65 alcoholics and 73 controls of European descent, and identified 129 genes that showed altered expression (FDR < 0.05) in subjects with alcohol dependence. Differentially expressed genes were enriched for pathways related to interferon signaling and Growth Arrest and DNA Damage-inducible 45 (GADD45) signaling. A coexpression module (thistle2) identified by weighted gene co-expression network analysis (WGCNA) was significantly correlated with alcohol dependence, alcohol consumption, and AUDIT scores. Genes in the thistle2 module were enriched with genes related to calcium signaling pathways and showed significant downregulation of these pathways, as well as enrichment for biological processes related to nicotine response and opioid signaling. A second module (brown4) showed significant upregulation of pathways related to immune signaling. Expression quantitative trait loci (eQTLs) for genes in the brown4 module were also enriched for genetic associations with alcohol dependence and alcohol consumption in large genome-wide studies included in the Psychiatric Genetic Consortium and the UK Biobank's alcohol consumption dataset. By leveraging multi-omics data, this transcriptome analysis has identified genes and biological pathways that could provide insight for identifying therapeutic targets for alcohol dependence.
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115
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Genetic loci for alcohol-related life events and substance-induced affective symptoms: indexing the "dark side" of addiction. Transl Psychiatry 2019; 9:71. [PMID: 30718457 PMCID: PMC6362044 DOI: 10.1038/s41398-019-0397-6] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/03/2018] [Accepted: 01/17/2019] [Indexed: 12/24/2022] Open
Abstract
A limited number of genetic variants have been identified in traditional GWAS as risk or protective factors for alcohol use disorders (AUD) and related phenotypes. We herein report whole-genome association and rare-variant analyses on AUD traits in American Indians (AI) and European Americans (EA). We evaluated 742 AIs and 1711 EAs using low-coverage whole-genome sequencing. Phenotypes included: (1) a metric based on the occurrence of 36 alcohol-related life events that reflect AUD severity; (2) two alcohol-induced affective symptoms that accompany severe AUDs. We identified two new loci for alcohol-related life events with converging evidence from both cohorts: rare variants of K2P channel gene KCNK2, and rare missense and splice-site variants in pro-inflammatory mediator gene PDE4C. A NAF1-FSTL5 intergenic variant and an FSTL5 variant were respectively associated with alcohol-related life events in AI and EA. PRKG2 of serine/threonine protein kinase family, and rare variants in interleukin subunit gene EBI3 (IL-27B) were uniquely associated with alcohol-induced affective symptoms in AI. LncRNA LINC02347 on 12q24.32 was uniquely associated with alcohol-induced depression in EA. The top GWAS findings were primarily rare/low-frequency variants in AI, and common variants in EA. Adrenal gland was the most enriched in tissue-specific gene expression analysis for alcohol-related life events, and nucleus accumbens was the most enriched for alcohol-induced affective states in AI. Prefrontal cortex was the most enriched in EA for both traits. These studies suggest that whole-genome sequencing can identify novel, especially uncommon, variants associated with severe AUD phenotypes although the findings may be population specific.
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116
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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: 240] [Impact Index Per Article: 48.0] [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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117
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Levey DF, Polimanti R, Cheng Z, Zhou H, Nuñez YZ, Jain S, He F, Sun X, Ursano RJ, Kessler RC, Smoller JW, Stein MB, Kranzler HR, Gelernter J. Genetic associations with suicide attempt severity and genetic overlap with major depression. Transl Psychiatry 2019; 9:22. [PMID: 30655502 PMCID: PMC6336846 DOI: 10.1038/s41398-018-0340-2] [Citation(s) in RCA: 70] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2018] [Accepted: 11/13/2018] [Indexed: 11/09/2022] Open
Abstract
In 2015, ~800,000 people died by suicide worldwide. For every death by suicide there are as many as 25 suicide attempts, which can result in serious injury even when not fatal. Despite this large impact on morbidity and mortality, the genetic influences on suicide attempt are poorly understood. We performed a genome-wide association study (GWAS) of severity of suicide attempts to investigate genetic influences. A discovery GWAS was performed in Yale-Penn sample cohorts of European Americans (EAs, n = 2,439) and African Americans (AAs, n = 3,881). We found one genome-wide significant (GWS) signal in EAs near the gene LDHB (rs1677091, p = 1.07 × 10-8) and three GWS associations in AAs: ARNTL2 on chromosome 12 (rs683813, p = 2.07 × 10-8), FAH on chromosome 15 (rs72740082, p = 2.36 × 10-8), and on chromosome 18 (rs11876255, p = 4.61 × 10-8) in the Yale-Penn discovery sample. We conducted a limited replication analysis in the completely independent Army-STARRS cohorts. rs1677091 replicated in Latinos (LAT, p = 6.52 × 10-3). A variant in LD with FAH rs72740082 (rs72740088; r2 = 0.68) was replicated in AAs (STARRS AA p = 5.23 × 10-3; AA meta, 1.51 × 10-9). When combined for a trans-population meta-analysis, the final sample size included n = 20,153 individuals. Finally, we found significant genetic overlap with major depressive disorder (MDD) using polygenic risk scores from a large GWAS (r2 = 0.007, p = 6.42 × 10-5). To our knowledge, this is the first GWAS of suicide attempt severity. We identified GWS associations near genes involved in anaerobic energy production (LDHB), circadian clock regulation (ARNTL2), and catabolism of tyrosine (FAH). These findings provide evidence of genetic risk factors for suicide attempt severity, providing new information regarding the molecular mechanisms involved.
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Affiliation(s)
- Daniel F. Levey
- 0000000419368710grid.47100.32Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT USA ,Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT USA
| | - Renato Polimanti
- 0000000419368710grid.47100.32Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT USA ,Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT USA
| | - Zhongshan Cheng
- 0000000419368710grid.47100.32Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT USA ,Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT USA
| | - Hang Zhou
- 0000000419368710grid.47100.32Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT USA ,Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT USA
| | - Yaira Z. Nuñez
- 0000000419368710grid.47100.32Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT USA ,Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT USA
| | - Sonia Jain
- 0000 0001 2107 4242grid.266100.3Department of Family Medicine and Public Health, University of California San Diego, La Jolla, CA USA
| | - Feng He
- 0000 0001 2107 4242grid.266100.3Department of Family Medicine and Public Health, University of California San Diego, La Jolla, CA USA
| | - Xiaoying Sun
- 0000 0001 2107 4242grid.266100.3Department of Family Medicine and Public Health, University of California San Diego, La Jolla, CA USA
| | - Robert J. Ursano
- 0000 0001 0421 5525grid.265436.0Uniformed Services University of the Health Sciences, Bethesda, MD USA
| | - Ronald C. Kessler
- 000000041936754Xgrid.38142.3cDepartment of Health Care Policy, Harvard Medical School, Boston, MA USA
| | - Jordan W. Smoller
- 000000041936754Xgrid.38142.3cDepartment of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA USA ,0000 0004 0386 9924grid.32224.35Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA USA ,grid.66859.34Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Murray B. Stein
- 0000 0001 2107 4242grid.266100.3Department of Family Medicine and Public Health, University of California San Diego, La Jolla, CA USA ,0000 0001 2107 4242grid.266100.3Department of Psychiatry, University of California San Diego, La Jolla, CA USA ,0000 0004 0419 2708grid.410371.0VA San Diego Healthcare System, San Diego, CA USA
| | - Henry R. Kranzler
- 0000 0004 1936 8972grid.25879.31Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA USA ,0000 0004 0420 350Xgrid.410355.6Veterans Integrated Service Network 4 Mental Illness Research, Education and Clinical Center, Crescenz Veterans Affairs Medical Center, Philadelphia, PA USA
| | - Joel Gelernter
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA. .,Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA. .,Department of Genetics, Yale University School of Medicine, New Haven, CT, USA. .,Department of Neuroscience, Yale University School of Medicine, New Haven, CT, USA.
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Dingel MJ, Ostergren J, Koenig BA, McCormick J. "Why did I get that part of you?" Understanding addiction genetics through family history. PUBLIC UNDERSTANDING OF SCIENCE (BRISTOL, ENGLAND) 2019; 28:53-67. [PMID: 29947292 PMCID: PMC6342673 DOI: 10.1177/0963662518785350] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Scientists have sought to uncover the genetic bases of many diseases and disorders. In response, scholars defined "geneticization" to describe genetic infiltration of understandings of health and illness. In our research, we interviewed 63 individuals in addiction treatment programs to identify what form of geneticization best fits individuals' description of their own addiction. Individuals' narratives of their lives, which include family history and are influenced by cultural and structural factors, affect respondents' reactions to a potential genetic basis of addiction. Most who had a family history of addiction subscribed to a notion that addiction "runs in families," while most who lacked a family history of addiction used this fact to reject the notion of genetic inheritance of addiction. We conclude that though we see elements of several different versions of geneticization, Nikolas Rose's version, that genetics affects peoples' perceptions of addiction in small but important ways, best describes our respondents' views.
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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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Xiang B, Yang BZ, Zhou H, Kranzler HR, Gelernter J. GWAS and network analysis of co-occurring nicotine and alcohol dependence identifies significantly associated alleles and network. Am J Med Genet B Neuropsychiatr Genet 2019; 180:3-11. [PMID: 30488612 PMCID: PMC6918694 DOI: 10.1002/ajmg.b.32692] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2017] [Revised: 08/02/2018] [Accepted: 09/26/2018] [Indexed: 12/11/2022]
Abstract
Alcohol dependence (AD) and nicotine dependence (ND) co-occur frequently (AD+ND). We integrated SNP-based, gene-based, and protein-protein interaction network analyses to identify shared risk genes or gene subnetworks for AD+ND in African Americans (AAs, N = 2,094) and European Americans (EAs, N = 1,207). The DSM-IV criterion counts for AD and ND were modeled as two dependent variables in a multivariate linear mixed model, and analyzed separately for the two populations. The most significant SNP was rs6579845 in EAs (p < 1.29 × 10-8 ) in GM2A, which encodes GM2 ganglioside activator, and is a cis-expression quantitative locus that affects GM2A expression in blood and brain tissues. However, this SNP was not replicated in our another small sample (N = 678). We identified a subnetwork of 24 genes that contributed to the AD+ND criterion counts. In the gene-set analysis for the subnetwork in an independent sample, the Study of Addiction: Genetics and Environment project (predominately EAs), these 24 genes as a set differed in AD+ND versus control subjects in EAs (p = .041). Functional enrichment analysis for this subnetwork revealed that the gene enrichment involved primarily nerve growth factor pathways, and cocaine and amphetamine addiction. In conclusion, we identified a genome-wide significant variant at GM2A and a gene subnetwork underlying the genetic trait of shared AD+ND. These results increase our understanding of the shared (pleiotropic) genetic risk that underlies AD+ND.
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Affiliation(s)
- Bo Xiang
- Department of Psychiatry, Yale University School of Medicine, New Haven, and VA CT Healthcare Center, West Haven, CT, USA,Department of Psychiatry, Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan Province, China
| | - Bao-Zhu Yang
- Department of Psychiatry, Yale University School of Medicine, New Haven, and VA CT Healthcare Center, West Haven, CT, USA
| | - Hang Zhou
- Department of Psychiatry, Yale University School of Medicine, New Haven, and VA CT Healthcare Center, West Haven, CT, USA
| | - Henry R. Kranzler
- Department of Psychiatry, Center for Studies of Addiction, University of Pennsylvania and VISN 4 MIRECC, Crescenz VAMC, Philadelphia, PA, USA
| | - Joel Gelernter
- Department of Psychiatry, Yale University School of Medicine, New Haven, and VA CT Healthcare Center, West Haven, CT, USA,Departments of Genetics and Neuroscience, Yale University School of Medicine, New Haven, CT, USA
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121
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Bach P, Zois E, Vollstädt-Klein S, Kirsch M, Hoffmann S, Jorde A, Frank J, Charlet K, Treutlein J, Beck A, Heinz A, Walter H, Rietschel M, Kiefer F. Association of the alcohol dehydrogenase gene polymorphism rs1789891 with gray matter brain volume, alcohol consumption, alcohol craving and relapse risk. Addict Biol 2019; 24:110-120. [PMID: 29058369 DOI: 10.1111/adb.12571] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2017] [Revised: 07/27/2017] [Accepted: 09/12/2017] [Indexed: 11/27/2022]
Abstract
Alcohol metabolizing enzymes, such as the alcohol dehydrogenases and the aldehyde dehydrogenases, regulate the levels of acetaldehyde in the blood and play an important role in the development and maintenance of alcohol addiction. Recent genome-wide systematic searches found associations between a single nucleotide polymorphism (rs1789891, risk allele: A, protective allele: C) in the alcohol dehydrogenase gene cluster and the risk of alcohol dependence. The current study investigated the effect of this single nucleotide polymorphism on alcohol consumption, craving for alcohol, relapse risk and brain gray matter volume. Alcohol-dependent patients (n = 74) and controls (n = 43) were screened, genotyped and underwent magnetic resonance imaging scanning, and relapse data were collected during 3 months following the experiment. Alcohol-dependent A allele carriers reported increased alcohol craving and higher alcohol consumption compared with the group of alcohol-dependent individuals homozygous for the C allele, which displayed craving values similar to the control group. Further, follow-up data indicated that A allele carriers relapsed earlier to heavy drinking compared with individuals with two C alleles. Analyses of gray matter volume indicated a significant genotype difference in the patient group: individuals with two C alleles had reduced gray matter volume in the left and right superior, middle and inferior temporal gyri. Findings of the current study further support the relevance of genetic variants in alcohol metabolizing enzymes to addictive behavior, brain tissue volume and relapse risk. Genotype-dependent differences in acetaldehyde formation, implicated by earlier studies, might be the biological substrate of the genotype differences.
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Affiliation(s)
- Patrick Bach
- Department of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim; University of Heidelberg; Germany
| | - Evangelos Zois
- Department of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim; University of Heidelberg; Germany
| | - Sabine Vollstädt-Klein
- Department of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim; University of Heidelberg; Germany
| | - Martina Kirsch
- Department of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim; University of Heidelberg; Germany
| | - Sabine Hoffmann
- Department of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim; University of Heidelberg; Germany
| | - Anne Jorde
- Department of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim; University of Heidelberg; Germany
| | - Josef Frank
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim; University of Heidelberg; Germany
| | - Katrin Charlet
- Department of Psychiatry and Psychotherapy; Charité-Universitätsmedizin Berlin; Germany
| | - Jens Treutlein
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim; University of Heidelberg; Germany
| | - Anne Beck
- Department of Psychiatry and Psychotherapy; Charité-Universitätsmedizin Berlin; Germany
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy; Charité-Universitätsmedizin Berlin; Germany
| | - Henrik Walter
- Division of Mind and Brain Research, Department of Psychiatry and Psychotherapy; Charité-Universitätsmedizin Berlin; Germany
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim; University of Heidelberg; Germany
| | - Falk Kiefer
- Department of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim; University of Heidelberg; Germany
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122
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Brick LA, Keller MC, Knopik VS, McGeary JE, Palmer RHC. Shared additive genetic variation for alcohol dependence among subjects of African and European ancestry. Addict Biol 2019; 24:132-144. [PMID: 29178570 PMCID: PMC6312725 DOI: 10.1111/adb.12578] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2017] [Revised: 09/05/2017] [Accepted: 10/15/2017] [Indexed: 02/01/2023]
Abstract
Alcohol dependence (AD) affects individuals from all racial/ethnic groups, and previous research suggests that there is considerable variation in AD risk between and among various ancestrally defined groups in the United States. Although the reasons for these differences are likely due in part to contributions of complex sociocultural factors, limited research has attempted to examine whether similar genetic variation plays a role across ancestral groups. Using a pooled sample of individuals of African and European ancestry (AA/EA) obtained through data shared within the Database for Genotypes and Phenotypes, we estimated the extent to which additive genetic similarity for AD between AA and EAs using common single nucleotide polymorphisms overlapped across the two populations. AD was represented as a factor score by using Diagnostic and Statistical Manual dependence criteria, and genetic data were imputed by using the 1000 Genomes Reference Panel. Analyses revealed a significant single nucleotide polymorphism-based heritability of 17 percent (SE = 5) in EAs and 24 percent (SE = 15) in AAs. Further, a significant genetic correlation of 0.77 (SE = 0.46) suggests that the allelic architecture influencing the AD factor for EAs and AAs is largely similar across the two populations. Analyses indicated that investigating the genetic underpinnings of alcohol dependence in different ethnic groups may serve to highlight core etiological factors common to both groups and unique etiological factors specific to each ethnic group.
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Affiliation(s)
- Leslie A. Brick
- Division of Behavioral Genetics, Department of Psychiatry, Rhode Island Hospital, Providence, Rhode Island
- Department of Psychiatry and Human Behavior, Alpert Medical School, Brown University, Providence, Rhode Island
| | - Matthew C. Keller
- Institute for Behavior Genetics, department of Psychology and Neuroscience, University of Colorado at Boulder, Boulder, Colorado
| | - Valerie S. Knopik
- Division of Behavioral Genetics, Department of Psychiatry, Rhode Island Hospital, Providence, Rhode Island
- Department of Psychiatry and Human Behavior, Alpert Medical School, Brown University, Providence, Rhode Island
| | - John E. McGeary
- Division of Behavioral Genetics, Department of Psychiatry, Rhode Island Hospital, Providence, Rhode Island
- Department of Psychiatry and Human Behavior, Alpert Medical School, Brown University, Providence, Rhode Island
- Providence Veterans Affairs Medical Center, Providence, Rhode Island
| | - Rohan H. C. Palmer
- Division of Behavioral Genetics, Department of Psychiatry, Rhode Island Hospital, Providence, Rhode Island
- Department of Psychiatry and Human Behavior, Alpert Medical School, Brown University, Providence, Rhode Island
- Behavior Genetics of Addiction Laboratory, Department of Psychology, Emory University, Atlanta, Georgia
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123
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Mehta D, Czamara D. GWAS of Behavioral Traits. Curr Top Behav Neurosci 2019; 42:1-34. [PMID: 31407241 DOI: 10.1007/7854_2019_105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Over the past decade, genome-wide association studies (GWAS) have evolved into a powerful tool to investigate genetic risk factors for human diseases via a hypothesis-free scan of the genome. The success of GWAS for psychiatric disorders and behavioral traits have been somewhat mixed, partly owing to the complexity and heterogeneity of these traits. Significant progress has been made in the last few years in the development and implementation of complex statistical methods and algorithms incorporating GWAS. Such advanced statistical methods applied to GWAS hits in combination with incorporation of different layers of genomics data have catapulted the search for novel genes for behavioral traits and improved our understanding of the complex polygenic architecture of these traits.This chapter will give a brief overview on GWAS and statistical methods currently used in GWAS. The chapter will focus on reviewing the current literature and highlight some of the most important GWAS on psychiatric and other behavioral traits and will conclude with a discussion on future directions.
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Affiliation(s)
- Divya Mehta
- School of Psychology and Counselling, Faculty of Health, Institute of Health and Biomedical Innovation, Queensland University of Technology, Kelvin Grove, QLD, Australia.
| | - Darina Czamara
- Department of Translational Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany
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124
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Abstract
Supplemental Digital Content is available in the text. The clinical comorbidity of alcohol dependence (AD) and major depressive disorder (MDD) is well established, whereas genetic factors influencing co-occurrence remain unclear. A recent study using polygenic risk scores (PRS) calculated based on the first-wave Psychiatric Genomics Consortium MDD meta-analysis (PGC-MDD1) suggests a modest shared genetic contribution to MDD and AD. Using a (∼10 fold) larger discovery sample, we calculated PRS based on the second wave (PGC-MDD2) of results, in a severe AD case–control target sample. We found significant associations between AD disease status and MDD-PRS derived from both PGC-MDD2 (most informative P-threshold=1.0, P=0.00063, R2=0.533%) and PGC-MDD1 (P-threshold=0.2, P=0.00014, R2=0.663%) meta-analyses; the larger discovery sample did not yield additional predictive power. In contrast, calculating PRS in a MDD target sample yielded increased power when using PGC-MDD2 (P-threshold=1.0, P=0.000038, R2=1.34%) versus PGC-MDD1 (P-threshold=1.0, P=0.0013, R2=0.81%). Furthermore, when calculating PGC-MDD2 PRS in a subsample of patients with AD recruited explicitly excluding comorbid MDD, significant associations were still found (n=331; P-threshold=1.0, P=0.042, R2=0.398%). Meanwhile, in the subset of patients in which MDD was not the explicit exclusion criteria, PRS predicted more variance (n=999; P-threshold=1.0, P=0.0003, R2=0.693%). Our findings replicate the reported genetic overlap between AD and MDD and also suggest the need for improved, rigorous phenotyping to identify true shared cross-disorder genetic factors. Larger target samples are needed to reduce noise and take advantage of increasing discovery sample size.
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125
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Edenberg HJ, McClintick JN. Alcohol Dehydrogenases, Aldehyde Dehydrogenases, and Alcohol Use Disorders: A Critical Review. Alcohol Clin Exp Res 2018; 42:2281-2297. [PMID: 30320893 PMCID: PMC6286250 DOI: 10.1111/acer.13904] [Citation(s) in RCA: 139] [Impact Index Per Article: 23.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2018] [Accepted: 10/07/2018] [Indexed: 12/20/2022]
Abstract
Alcohol use disorders (AUDs) are complex traits, meaning that variations in many genes contribute to the risk, as does the environment. Although the total genetic contribution to risk is substantial, most individual variations make only very small contributions. By far the strongest contributors are functional variations in 2 genes involved in alcohol (ethanol [EtOH]) metabolism. A functional variant in alcohol dehydrogenase 1B (ADH1B) is protective in people of European and Asian descent, and a different functional variant in the same gene is protective in those of African descent. A strongly protective variant in aldehyde dehydrogenase 2 (ALDH2) is essentially only found in Asians. This highlights the need to study a wide range of populations. The likely mechanism of protection against heavy drinking and AUDs in both cases is alteration in the rate of metabolism of EtOH that at least transiently elevates acetaldehyde. Other ADH and ALDH variants, including functional variations in ADH1C, have also been implicated in affecting drinking behavior and risk for alcoholism. The pattern of linkage disequilibrium in the ADH region and the differences among populations complicate analyses, particularly of regulatory variants. This critical review focuses upon the ADH and ALDH genes as they affect AUDs.
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Affiliation(s)
- Howard J. Edenberg
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN
| | - Jeanette N. McClintick
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN
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126
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Justice AC, Smith RV, Tate JP, McGinnis K, Xu K, Becker WC, Lee KY, Lynch K, Sun N, Concato J, Fiellin DA, Zhao H, Gelernter J, Kranzler HR. AUDIT-C and ICD codes as phenotypes for harmful alcohol use: association with ADH1B polymorphisms in two US populations. Addiction 2018; 113:2214-2224. [PMID: 29972609 PMCID: PMC6226338 DOI: 10.1111/add.14374] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2017] [Revised: 01/31/2018] [Accepted: 06/28/2018] [Indexed: 01/28/2023]
Abstract
BACKGROUND AND AIMS Longitudinal electronic health record (EHR) data offer a large-scale, untapped source of phenotypical information on harmful alcohol use. Using established, alcohol-associated variants in the gene that encodes the enzyme alcohol dehydrogenase 1B (ADH1B) as criterion standards, we compared the individual and combined validity of three longitudinal EHR-based phenotypes of harmful alcohol use: Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) trajectories; mean age-adjusted AUDIT-C; and diagnoses of alcohol use disorder (AUD). DESIGN With longitudinal EHR data from the Million Veteran Program (MVP) linked to genetic data, we used two population-specific polymorphisms in ADH1B that are associated strongly with AUD in African Americans (AAs) and European Americans (EAs): rs2066702 (Arg369Cys, AAs) and rs1229984 (Arg48His, EAs) as criterion measures. SETTING United States Department of Veterans Affairs Healthcare System. PARTICIPANTS A total of 167 721 veterans (57 677 AAs and 110 044 EAs; 92% male, mean age = 63 years) took part in this study. Data were collected from 1 October 2007 to 1 May 2017. MEASUREMENTS Using all AUDIT-C scores and AUD diagnostic codes recorded in the EHR, we calculated age-adjusted mean AUDIT-C values, longitudinal statistical trajectories of AUDIT-C scores and ICD-9/10 diagnostic groupings for AUD. FINDINGS A total of 19 793 AAs (34.3%) had one or two minor alleles at rs2066702 [minor allele frequency (MAF) = 0.190] and 6933 EAs (6.3%) had one or two minor alleles at rs1229984 (MAF = 0.032). In both populations, trajectories and age-adjusted mean AUDIT-C were correlated (r = 0.90) but, when considered separately, highest score (8+ versus 0) of age-adjusted mean AUDIT-C demonstrated a stronger association with the ADH1B variants [adjusted odds ratio (aOR) 0.54 in AAs and 0.37 in AAs] than did the highest trajectory (aOR 0.71 in AAs and 0.53 in EAs); combining AUDIT-C metrics did not improve discrimination. When age-adjusted mean AUDIT-C score and AUD diagnoses were considered together, age-adjusted mean AUDIT-C (8+ versus 0) was associated with lower odds of having the ADH1B minor allele than were AUD diagnostic codes: aOR = 0.59 versus 0.86 in AAs and 0.48 versus 0.68 in EAs. These independent associations combine to yield an even lower aOR of 0.51 for AAs and 0.33 for EAs. CONCLUSIONS The age-adjusted mean AUDIT-C score is associated more strongly with genetic polymorphisms of known risk for alcohol use disorder than are longitudinal trajectories of AUDIT-C or AUD diagnostic codes. AUD diagnostic codes modestly enhance this association.
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Affiliation(s)
- Amy C. Justice
- Yale School of Medicine, New Haven CT 06515,Veterans Affairs Connecticut Healthcare System, West Haven, CT 06516,Yale School of Public Health, New Haven CT 06515
| | - Rachel V. Smith
- University of Louisville School of Nursing, Louisville, KY 40202
| | | | - Kathleen McGinnis
- Veterans Affairs Connecticut Healthcare System, West Haven, CT 06516
| | - Ke Xu
- Yale School of Medicine, New Haven CT 06515,Veterans Affairs Connecticut Healthcare System, West Haven, CT 06516
| | - William C. Becker
- Yale School of Medicine, New Haven CT 06515,Veterans Affairs Connecticut Healthcare System, West Haven, CT 06516
| | - Kuang-Yao Lee
- Department of Statistical Science, Temple University, Philadelphia, PA 19122
| | - Kevin Lynch
- VISN 4 MIRECC, Crescenz VAMC, Philadelphia, PA 19104,University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104
| | - Ning Sun
- Yale School of Medicine, New Haven CT 06515,Yale School of Public Health, New Haven CT 06515
| | - John Concato
- Yale School of Medicine, New Haven CT 06515,Veterans Affairs Connecticut Healthcare System, West Haven, CT 06516
| | - David A. Fiellin
- Yale School of Medicine, New Haven CT 06515,Yale School of Public Health, New Haven CT 06515
| | - Hongyu Zhao
- Yale School of Medicine, New Haven CT 06515,Yale School of Public Health, New Haven CT 06515
| | - Joel Gelernter
- Yale School of Medicine, New Haven CT 06515,Veterans Affairs Connecticut Healthcare System, West Haven, CT 06516
| | - Henry R. Kranzler
- VISN 4 MIRECC, Crescenz VAMC, Philadelphia, PA 19104,University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104
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127
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Smith AH, Ovesen PL, Skeldal S, Yeo S, Jensen KP, Olsen D, Diazgranados N, Zhao H, Farrer LA, Goldman D, Glerup S, Kranzler HR, Nykjær A, Gelernter J. Risk Locus Identification Ties Alcohol Withdrawal Symptoms to SORCS2. Alcohol Clin Exp Res 2018; 42:2337-2348. [PMID: 30252935 PMCID: PMC6317871 DOI: 10.1111/acer.13890] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2018] [Accepted: 09/06/2018] [Indexed: 01/11/2023]
Abstract
BACKGROUND Efforts to promote the cessation of harmful alcohol use are hindered by the affective and physiological components of alcohol withdrawal (AW), which can include life-threatening seizures. Although previous studies of AW and relapse have highlighted the detrimental role of stress, little is known about genetic risk factors. METHODS We conducted a genome-wide association study of AW symptom count in uniformly assessed subjects with histories of serious AW, followed by additional genotyping in independent AW subjects. RESULTS The top association signal for AW severity was in sortilin family neurotrophin receptor gene SORCS2 on chromosome 4 (European American meta-analysis n = 1,478, p = 4.3 × 10-9 ). There were no genome-wide significant findings in African Americans (n = 1,231). Bioinformatic analyses were conducted using publicly available high-throughput transcriptomic and epigenomic data sets, showing that in humans SORCS2 is most highly expressed in the nervous system. The identified SORCS2 risk haplotype is predicted to disrupt a stress hormone-modulated regulatory element that has tissue-specific activity in human hippocampus. We used human neural lineage cells to demonstrate in vitro a causal relationship between stress hormone levels and SORCS2 expression, and show that SORCS2 levels in culture are increased upon ethanol exposure and withdrawal. CONCLUSIONS Taken together, these findings indicate that the pathophysiology of withdrawal may involve the effects of stress hormones on neurotrophic factor signaling. Further investigation of these pathways could produce new approaches to managing the aversive consequences of abrupt alcohol cessation.
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Affiliation(s)
- Andrew H. Smith
- Interdepartmental Neuroscience Program and Medical Scientist Training Program, Yale School of Medicine
- Division of Human Genetics, Department of Psychiatry, VA CT Healthcare Center and Yale School of Medicine
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029
| | - Peter L. Ovesen
- The Lundbeck Foundation Research Center MIND, Danish Research Institute of Translational Neuroscience DANDRITE - Nordic EMBL Partnership for Molecular Medicine, Department of Biomedicine, Aarhus University, DK-8000 Aarhus C, Denmark
| | - Sune Skeldal
- The Lundbeck Foundation Research Center MIND, Danish Research Institute of Translational Neuroscience DANDRITE - Nordic EMBL Partnership for Molecular Medicine, Department of Biomedicine, Aarhus University, DK-8000 Aarhus C, Denmark
| | - Seungeun Yeo
- Laboratory of Neurogenetics, National Institute on Alcohol Abuse and Alcoholism
| | - Kevin P. Jensen
- Division of Human Genetics, Department of Psychiatry, VA CT Healthcare Center and Yale School of Medicine
| | - Ditte Olsen
- The Lundbeck Foundation Research Center MIND, Danish Research Institute of Translational Neuroscience DANDRITE - Nordic EMBL Partnership for Molecular Medicine, Department of Biomedicine, Aarhus University, DK-8000 Aarhus C, Denmark
| | - Nancy Diazgranados
- Office of the Clinical Director, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD 20892, USA
| | - Hongyu Zhao
- Department of Biostatistics, Yale School of Public Health
| | - Lindsay A. Farrer
- Departments of Medicine (Biomedical Genetics), Neurology, and Ophthalmology, School of Medicine, and Departments of Biostatistics and Epidemiology, School of Public Health, Boston University, Boston, MA 02118, USA
| | - David Goldman
- Laboratory of Neurogenetics, National Institute on Alcohol Abuse and Alcoholism
- Office of the Clinical Director, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD 20892, USA
| | - Simon Glerup
- The Lundbeck Foundation Research Center MIND, Danish Research Institute of Translational Neuroscience DANDRITE - Nordic EMBL Partnership for Molecular Medicine, Department of Biomedicine, Aarhus University, DK-8000 Aarhus C, Denmark
| | - Henry R. Kranzler
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania and Corporal Michael J. Crescenz VAMC, Philadelphia, Pennsylvania 19104, USA
| | - Anders Nykjær
- The Lundbeck Foundation Research Center MIND, Danish Research Institute of Translational Neuroscience DANDRITE - Nordic EMBL Partnership for Molecular Medicine, Department of Biomedicine, Aarhus University, DK-8000 Aarhus C, Denmark
- Department of Neuroscience, Mayo Clinic, Jacksonville 32224, Florida, USA
| | - Joel Gelernter
- Division of Human Genetics, Department of Psychiatry, VA CT Healthcare Center and Yale School of Medicine
- Departments of Genetics and Neuroscience, Yale School of Medicine, Yale University, New Haven, Connecticut 06510, USA
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128
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Montalvo-Ortiz JL, Zhou H, D'Andrea I, Maroteaux L, Lori A, Smith A, Ressler KJ, Nuñez YZ, Farrer LA, Zhao H, Kranzler HR, Gelernter J. Translational studies support a role for serotonin 2B receptor (HTR2B) gene in aggression-related cannabis response. Mol Psychiatry 2018; 23:2277-2286. [PMID: 29875475 PMCID: PMC6281782 DOI: 10.1038/s41380-018-0077-6] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2017] [Revised: 04/17/2018] [Accepted: 04/23/2018] [Indexed: 12/18/2022]
Abstract
Cannabis use is increasing in the United States, as are its adverse effects. We investigated the genetics of an adverse consequence of cannabis use: cannabis-related aggression (CRA) using a genome-wide association study (GWAS) design. Our GWAS sample included 3269 African Americans (AAs) and 2546 European Americans (EAs). An additional 89 AA subjects from the Grady Trauma Project (GTP) were also examined using a proxy-phenotype replication approach. We identified genome-wide significant risk loci contributing to CRA in AAs at the serotonin receptor 2B receptor gene (HTR2B), and the lead SNP, HTR2B*rs17440378, showed nominal association to aggression in the GTP cohort of cannabis-exposed subjects. A priori evidence linked HTR2B to impulsivity/aggression but not to cannabis response. Human functional data regarding the HTR2B variant further supported our finding. Treating an Htr2b-/- knockout mouse with THC resulted in increased aggressive behavior, whereas wild-type mice following THC administration showed decreased aggression in the resident-intruder paradigm, demonstrating that HTR2B variation moderates the effects of cannabis on aggression. These concordant findings in mice and humans implicate HTR2B as a major locus associated with cannabis-induced aggression.
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Affiliation(s)
- Janitza L Montalvo-Ortiz
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- VA CT Healthcare Center, West Haven, CT, USA
| | - Hang Zhou
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Ivana D'Andrea
- INSERM UMR-S 839, F-75005, Paris, France
- Sorbonne Universités, UPMC Univ Paris 6, F-75005, Paris, France
- Institut du Fer à Moulin, F-75005, Paris, France
| | - Luc Maroteaux
- INSERM UMR-S 839, F-75005, Paris, France
- Sorbonne Universités, UPMC Univ Paris 6, F-75005, Paris, France
- Institut du Fer à Moulin, F-75005, Paris, France
| | - Adriana Lori
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Alicia Smith
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Kerry J Ressler
- Department of Psychiatry, Harvard Medical School and McLean Hospital, Belmont, MA, USA
| | - Yaira Z Nuñez
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- VA CT Healthcare Center, West Haven, CT, USA
| | - Lindsay A Farrer
- Departments of Medicine (Biomedical Genetics), Neurology, Ophthalmology, Epidemiology, and Biostatistics, Boston University Schools of Medicine and Public Health, Boston, MA, USA
| | - Hongyu Zhao
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
| | - Henry R Kranzler
- Department of Psychiatry, Center for Studies of Addiction and Crescenz Veterans Affairs Medical Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Joel Gelernter
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA.
- VA CT Healthcare Center, West Haven, CT, USA.
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA.
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA.
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129
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RETRACTED ARTICLE: Multi-view Sparse Vector Decomposition to Deal with Missing Values in Alcohol Dependence Study. Neural Process Lett 2018. [DOI: 10.1007/s11063-018-9847-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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130
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Nurnberger JI, Austin J, Berrettini WH, Besterman AD, DeLisi LE, Grice DE, Kennedy JL, Moreno-De-Luca D, Potash JB, Ross DA, Schulze TG, Zai G. What Should a Psychiatrist Know About Genetics? Review and Recommendations From the Residency Education Committee of the International Society of Psychiatric Genetics. J Clin Psychiatry 2018; 80:17nr12046. [PMID: 30549495 PMCID: PMC6480395 DOI: 10.4088/jcp.17nr12046] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2017] [Accepted: 06/01/2018] [Indexed: 01/23/2023]
Abstract
The International Society of Psychiatric Genetics (ISPG) created a Residency Education Committee with the purpose of identifying key genetic knowledge that should be taught in psychiatric training programs. Thirteen committee members were appointed by the ISPG Board of Directors, based on varied training, expertise, gender, and national origin. The Committee has met quarterly for the past 2 years, with periodic reports to the Board and to the members of the Society. The information summarized includes the existing literature in the field of psychiatric genetics and the output of ongoing large genomics consortia. An outline of clinically relevant areas of genetic knowledge was developed, circulated, and approved. This document was expanded and annotated with appropriate references, and the manuscript was developed. Specific information regarding the contribution of common and rare genetic variants to major psychiatric disorders and treatment response is now available. Current challenges include the following: (1) Genetic testing is recommended in the evaluation of autism and intellectual disability, but its use is limited in current clinical practice. (2) Commercial pharmacogenomic testing is widely available, but its utility has not yet been clearly established. (3) Other methods, such as whole exome and whole genome sequencing, will soon be clinically applicable. The need for informed genetic counseling in psychiatry is greater than ever before, knowledge in the field is rapidly growing, and genetic education should become an integral part of psychiatric training.
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Affiliation(s)
- John I Nurnberger
- 320 W 15th St, Indianapolis, IN 46202.
- Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Jehannine Austin
- University of British Columbia, Vancouver, British Columbia, Canada
| | - Wade H Berrettini
- University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, USA
| | - Aaron D Besterman
- University of California Los Angeles Semel Institute of Neuroscience and Human Behavior, Los Angeles, California, USA
| | - Lynn E DeLisi
- VA Boston Healthcare System and Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, USA
| | | | - James L Kennedy
- Centre for Addiction and Mental Health and University of Toronto, Toronto, Ontario, Canada
| | | | - James B Potash
- Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - David A Ross
- Yale University School of Medicine, Hartford, Connecticut, USA
| | - Thomas G Schulze
- Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich, Munich, Germany
| | - Gwyneth Zai
- Centre for Addiction and Mental Health and University of Toronto, Toronto, Ontario, Canada
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131
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Farris SP, Riley BP, Williams RW, Mulligan MK, Miles MF, Lopez MF, Hitzemann R, Iancu OD, Colville A, Walter NAR, Darakjian P, Oberbeck DL, Daunais JB, Zheng CL, Searles RP, McWeeney SK, Grant KA, Mayfield RD. Cross-species molecular dissection across alcohol behavioral domains. Alcohol 2018; 72:19-31. [PMID: 30213503 PMCID: PMC6309876 DOI: 10.1016/j.alcohol.2017.11.036] [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: 10/14/2017] [Revised: 11/17/2017] [Accepted: 11/28/2017] [Indexed: 12/14/2022]
Abstract
This review summarizes the proceedings of a symposium presented at the "Alcoholism and Stress: A Framework for Future Treatment Strategies" conference held in Volterra, Italy on May 9-12, 2017. Psychiatric diseases, including alcohol-use disorders (AUDs), are influenced through complex interactions of genes, neurobiological pathways, and environmental influences. A better understanding of the common neurobiological mechanisms underlying an AUD necessitates an integrative approach, involving a systematic assessment of diverse species and phenotype measures. As part of the World Congress on Stress and Alcoholism, this symposium provided a detailed account of current strategies to identify mechanisms underlying the development and progression of AUDs. Dr. Sean Farris discussed the integration and organization of transcriptome and postmortem human brain data to identify brain regional- and cell type-specific differences related to excessive alcohol consumption that are conserved across species. Dr. Brien Riley presented the results of a genome-wide association study of DSM-IV alcohol dependence; although replication of genetic associations with alcohol phenotypes in humans remains challenging, model organism studies show that COL6A3, KLF12, and RYR3 affect behavioral responses to ethanol, and provide substantial evidence for their role in human alcohol-related traits. Dr. Rob Williams expanded upon the systematic characterization of extensive genetic-genomic resources for quantifying and clarifying phenotypes across species that are relevant to precision medicine in human disease. The symposium concluded with Dr. Robert Hitzemann's description of transcriptome studies in a mouse model selectively bred for high alcohol ("binge-like") consumption and a non-human primate model of long-term alcohol consumption. Together, the different components of this session provided an overview of systems-based approaches that are pioneering the experimental prioritization and validation of novel genes and gene networks linked with a range of behavioral phenotypes associated with stress and AUDs.
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Affiliation(s)
- Sean P Farris
- University of Texas at Austin, Austin, TX, United States
| | - Brien P Riley
- Virginia Commonwealth University, Richmond, VA, United States
| | - Robert W Williams
- University of Tennessee Health Science Center, Memphis, TN, United States
| | - Megan K Mulligan
- University of Tennessee Health Science Center, Memphis, TN, United States
| | - Michael F Miles
- University of Tennessee Health Science Center, Memphis, TN, United States
| | - Marcelo F Lopez
- University of Tennessee Health Science Center, Memphis, TN, United States
| | - Robert Hitzemann
- Oregon Health and Science University, Portland, OR, United States
| | - Ovidiu D Iancu
- Oregon Health and Science University, Portland, OR, United States
| | | | | | | | | | - James B Daunais
- Wake Forest School of Medicine, Winston-Salem, NC, United States
| | | | - Robert P Searles
- Oregon Health and Science University, Portland, OR, United States
| | | | - Kathleen A Grant
- Oregon Health and Science University, Portland, OR, United States
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132
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Bradbury C, Köttgen A, Staubach F. Off-target phenotypes in forensic DNA phenotyping and biogeographic ancestry inference: A resource. Forensic Sci Int Genet 2018; 38:93-104. [PMID: 30391626 DOI: 10.1016/j.fsigen.2018.10.010] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2018] [Revised: 08/27/2018] [Accepted: 10/13/2018] [Indexed: 01/04/2023]
Abstract
With recent advances in DNA sequencing technologies it has become feasible and cost effective to genotype larger marker sets for forensic purposes. Two technologies that make use of the larger marker sets have come into focus in forensic research and applications; inference of biogeographic ancestry (BGA) and forensic DNA phenotyping (FDP). These methods hold the promise to reveal information about a yet unknown perpetrator from a DNA sample. In contrast, DNA-profiling, that is a standard practice in case work, relies on matching DNA-profiles between crime scene material and suspects on a database of DNA-profiles. Markers for DNA-profiling were developed under the premise to reveal as little additional information about the human source of the profile as possible, the rationale being that personal privacy rights have to be balanced against the public interest in solving a crime. The same argument holds for markers used in BGA and FDP; these markers might also reveal information on off-target phenotypes (OTPs), that go beyond BGA and the phenotypes targeted in FDP. In particular, health related OTPs might shift the balance between privacy protection and public interest. However, to our knowledge, there is currently no convenient resource available to incorporate knowledge on OTPs in BGA and FDP assay design and application. In order to provide such a resource, we performed a systematic search for OTPs associated with a comprehensive set of markers (1766 SNPs) used or suggested to be used for BGA inference and FDP. In this set, we identified a relatively small number of 27 SNPs (1.53%) that convey information on diverse health related OTPs such as cancer risk, induced asthma, or risk of alcoholism. Some of these SNPs are commonly used for FDP and BGA across different marker sets. We conclude that the effects of SNP markers used in FDP and BGA on OTPs are currently limited, with few exceptions that should be considered in a balanced decision on assay design and application.
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Affiliation(s)
- Cedric Bradbury
- University College Freiburg, Albert-Ludwigs-University Freiburg, Freiburg, Germany
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Dept. of Biometry, Epidemiology and Medical Bioinformatics, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Fabian Staubach
- Institute of Biology I, Dept. of Evolutionary Biology and Ecology, Albert-Ludwigs-University Freiburg, Freiburg, Germany.
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133
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Harper J, Malone SM, Iacono WG. Conflict-related medial frontal theta as an endophenotype for alcohol use disorder. Biol Psychol 2018; 139:25-38. [PMID: 30300674 DOI: 10.1016/j.biopsycho.2018.10.002] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2018] [Revised: 09/19/2018] [Accepted: 10/01/2018] [Indexed: 12/28/2022]
Abstract
Diminished cognitive control in alcohol use disorder (AUD) is thought to be mediated by prefrontal cortex circuitry dysregulation. Research testing the relationship between AUD and specific cognitive control psychophysiological correlates, such as medial frontal (MF) theta-band EEG power, is scarce, and the etiology of this relationship is largely unknown. The current report tested relationship between pathological alcohol use through young adulthood and reduced conflict-related theta at age 29 in a large prospective population-based twin sample. Greater lifetime AUD symptomatology was associated with reduced MF theta power during response conflict, but not alpha-band visual attention processing. Follow-up analyses using cotwin control analysis and biometric modeling suggested that genetic influences, and not the consequences of sustained AUD symptomatology, explained the theta-AUD association. Results provide strong evidence that AUD is genetically related to diminished conflict-related MF theta, and advance MF theta as a promising electrophysiological correlate of AUD-related dysfunctional frontal circuitry.
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Affiliation(s)
- Jeremy Harper
- Department of Psychology, University of Minnesota, USA.
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134
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Rabinowitz JA, Musci RJ, Milam AJ, Benke K, Uhl GR, Sisto DY, Ialongo NS, Maher BS. The interplay between externalizing disorders polygenic risk scores and contextual factors on the development of marijuana use disorders. Drug Alcohol Depend 2018; 191:365-373. [PMID: 30195949 PMCID: PMC8005265 DOI: 10.1016/j.drugalcdep.2018.07.016] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2018] [Revised: 07/13/2018] [Accepted: 07/18/2018] [Indexed: 12/28/2022]
Abstract
Externalizing disorders have been extensively linked to substance use problems. However, less is known about whether genetic factors underpinning externalizing disorders and environmental features interact to predict substance use disorders (i.e., marijuana abuse and dependence) among urban African Americans. We examined whether polygenic risk scores (PRS) for conduct disorder (CD) and attention-deficit hyperactivity disorder (ADHD) interacted with contextual factors (i.e., parental monitoring, community disadvantage) to influence risk for marijuana use disorders in a sample of African American youth. Participants (N=1,050; 44.2% male) were initially recruited for an elementary school-based universal prevention trial in a Mid-Atlantic city and followed through age 20. Participants reported on their parental monitoring in sixth grade and whether they were diagnosed with marijuana abuse or dependence at age 20. Blood or saliva samples were genotyped using the Affymetrix 6.0 microarrays. The CD and ADHD PRS were created based on genome-wide association studies conducted by Dick et al. (2010) and Demontis et al. (2017), respectively. Community disadvantage was calculated based on census data when participants were in sixth grade. There was an interaction between the CD PRS and community disadvantage such that a higher CD PRS was associated with greater risk for a marijuana use disorder at higher levels of neighborhood disadvantage. This finding should be interpreted with caution owing to the number of significance tests performed. Implications for etiological models and future research directions are presented.
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Affiliation(s)
- Jill A Rabinowitz
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, 624 N. Broadway, Baltimore, MD 21205, United States.
| | - Rashelle J Musci
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, 624 N. Broadway, Baltimore, MD 21205, United States
| | - Adam J Milam
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, 624 N. Broadway, Baltimore, MD 21205, United States
| | - Kelly Benke
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, 624 N. Broadway, Baltimore, MD 21205, United States
| | - George R Uhl
- New Mexico VA Healthcare System, 1501 San Pedro Drive, SE, Albuquerque, NM, 87108 United States
| | - Danielle Y Sisto
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, 624 N. Broadway, Baltimore, MD 21205, United States
| | - Nicholas S Ialongo
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, 624 N. Broadway, Baltimore, MD 21205, United States
| | - Brion S Maher
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, 624 N. Broadway, Baltimore, MD 21205, United States
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135
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Tylee DS, Sun J, Hess JL, Tahir MA, Sharma E, Malik R, Worrall BB, Levine AJ, Martinson JJ, Nejentsev S, Speed D, Fischer A, Mick E, Walker BR, Crawford A, Grant SF, Polychronakos C, Bradfield JP, Sleiman PMA, Hakonarson H, Ellinghaus E, Elder JT, Tsoi LC, Trembath RC, Barker JN, Franke A, Dehghan A, Faraone SV, Glatt. SJ. Genetic correlations among psychiatric and immune-related phenotypes based on genome-wide association data. Am J Med Genet B Neuropsychiatr Genet 2018; 177:641-657. [PMID: 30325587 PMCID: PMC6230304 DOI: 10.1002/ajmg.b.32652] [Citation(s) in RCA: 133] [Impact Index Per Article: 22.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/17/2017] [Revised: 02/21/2018] [Accepted: 05/22/2018] [Indexed: 12/18/2022]
Abstract
Individuals with psychiatric disorders have elevated rates of autoimmune comorbidity and altered immune signaling. It is unclear whether these altered immunological states have a shared genetic basis with those psychiatric disorders. The present study sought to use existing summary-level data from previous genome-wide association studies to determine if commonly varying single nucleotide polymorphisms are shared between psychiatric and immune-related phenotypes. We estimated heritability and examined pair-wise genetic correlations using the linkage disequilibrium score regression (LDSC) and heritability estimation from summary statistics methods. Using LDSC, we observed significant genetic correlations between immune-related disorders and several psychiatric disorders, including anorexia nervosa, attention deficit-hyperactivity disorder, bipolar disorder, major depression, obsessive compulsive disorder, schizophrenia, smoking behavior, and Tourette syndrome. Loci significantly mediating genetic correlations were identified for schizophrenia when analytically paired with Crohn's disease, primary biliary cirrhosis, systemic lupus erythematosus, and ulcerative colitis. We report significantly correlated loci and highlight those containing genome-wide associations and candidate genes for respective disorders. We also used the LDSC method to characterize genetic correlations among the immune-related phenotypes. We discuss our findings in the context of relevant genetic and epidemiological literature, as well as the limitations and caveats of the study.
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Affiliation(s)
- Daniel S. Tylee
- Psychiatric Genetic Epidemiology & Neurobiology Laboratory (PsychGENe Lab); Departments of Psychiatry and Behavioral Sciences & Neuroscience and Physiology; SUNY Upstate Medical University; Syracuse, NY, U.S.A
| | - Jiayin Sun
- Psychiatric Genetic Epidemiology & Neurobiology Laboratory (PsychGENe Lab); Departments of Psychiatry and Behavioral Sciences & Neuroscience and Physiology; SUNY Upstate Medical University; Syracuse, NY, U.S.A
| | - Jonathan L. Hess
- Psychiatric Genetic Epidemiology & Neurobiology Laboratory (PsychGENe Lab); Departments of Psychiatry and Behavioral Sciences & Neuroscience and Physiology; SUNY Upstate Medical University; Syracuse, NY, U.S.A
| | - Muhammad A. Tahir
- Psychiatric Genetic Epidemiology & Neurobiology Laboratory (PsychGENe Lab); Departments of Psychiatry and Behavioral Sciences & Neuroscience and Physiology; SUNY Upstate Medical University; Syracuse, NY, U.S.A
| | - Esha Sharma
- Psychiatric Genetic Epidemiology & Neurobiology Laboratory (PsychGENe Lab); Departments of Psychiatry and Behavioral Sciences & Neuroscience and Physiology; SUNY Upstate Medical University; Syracuse, NY, U.S.A
| | - Rainer Malik
- Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-University (LMU), Munich, Germany
| | - Bradford B. Worrall
- Departments of Neurology and Public Health Sciences, University of Virginia School of Medicine, Charlottesville, VA, U.S.A
| | - Andrew J. Levine
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, U.S.A
| | - Jeremy J. Martinson
- Department of Infectious Diseases and Microbiology, Graduate School of Public Health, University of Pittsburgh, PA, U.S.A
| | | | - Doug Speed
- Aarhus Institute for Advanced Studies and University College London, London, U.K
| | - Annegret Fischer
- Institute of Clinical Molecular Biology, Christian Albrechts University of Kiel, Kiel, Germany
| | - Eric Mick
- Department of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA, U.S.A
| | - Brian R. Walker
- BHF Centre for Cardiovascular Science, Queen’s Medical Research Institute, University of Edinburgh, Edinburgh, EH16 4TJ, U.K
| | - Andrew Crawford
- School of Social and Community Medicine, MRC Integrated Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, UK
- Center for Applied Genomics, Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, U.S.A
| | - Struan F.A. Grant
- Center for Applied Genomics, Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, U.S.A
- Division of Endocrinology and Diabetes, The Children’s Hospital of Philadelphia, Philadelphia, PA, U.S.A
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, U.S.A
- Institute of Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, U.S.A
| | - Constantin Polychronakos
- Endocrine Genetics Laboratory, Department of Pediatrics and the Child Health Program of the Research Institute, McGill University Health Centre, Montreal, Quebec, Canada
| | - Jonathan P. Bradfield
- Center for Applied Genomics, Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, U.S.A
- Quantinuum Research LLC, San Diego, CA, U.S.A
| | - Patrick M. A. Sleiman
- Center for Applied Genomics, Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, U.S.A
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, U.S.A
| | - Hakon Hakonarson
- Center for Applied Genomics, Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, U.S.A
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, U.S.A
| | - Eva Ellinghaus
- Institute of Clinical Molecular Biology, Christian Albrechts University of Kiel, Kiel, Germany
| | - James T. Elder
- Department of Dermatology, Veterans Affairs Hospital, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Lam C. Tsoi
- Department of Dermatology, Veterans Affairs Hospital, University of Michigan, Ann Arbor, Michigan, United States of America
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Richard C. Trembath
- Division of Genetics and Molecular Medicine, King’s College London, London, UK
| | - Jonathan N. Barker
- Department of Biostatistics and Epidemiology, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London
| | - Andre Franke
- Institute of Clinical Molecular Biology, Christian Albrechts University of Kiel, Kiel, Germany
| | - Abbas Dehghan
- Department of Biostatistics and Epidemiology, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London
| | | | | | - Stephen V. Faraone
- Psychiatric Genetic Epidemiology & Neurobiology Laboratory (PsychGENe Lab); Departments of Psychiatry and Behavioral Sciences & Neuroscience and Physiology; SUNY Upstate Medical University; Syracuse, NY, U.S.A
- K.G. Jebsen Centre for Research on Neuropsychiatric Disorders, University of Bergen, Bergen, Norway
| | - Stephen J. Glatt.
- Psychiatric Genetic Epidemiology & Neurobiology Laboratory (PsychGENe Lab); Departments of Psychiatry and Behavioral Sciences & Neuroscience and Physiology; SUNY Upstate Medical University; Syracuse, NY, U.S.A
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136
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Gorwood P, Le Strat Y, Ramoz N. Genetics of addictive behavior: the example of nicotine dependence. DIALOGUES IN CLINICAL NEUROSCIENCE 2018. [PMID: 29302221 PMCID: PMC5741107 DOI: 10.31887/dcns.2017.19.3/pgorwood] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
The majority of addictive disorders have a significant heritability—roughly around 50%. Surprisingly, the most convincing association (a nicotinic acetylcholine receptor CHRNA5-A3-B4 gene cluster in nicotine dependence), with a unique attributable risk of 14%, was detected through a genome-wide association study (GWAS) on lung cancer, although lung cancer has a low heritability. We propose some explanations of this finding, potentially helping to understand how a GWAS strategy can be successful. Many endophenotypes were also assessed as potentially modulating the effect of nicotine, indirectly facilitating the development of nicotine dependence. Challenging the involved phenotype led to the demonstration that other potentially overlapping disorders, such as schizophrenia and Parkinson disease, could also be involved, and further modulated by parent monitoring or the existence of a smoking partner. Such a complex mechanism of action is compatible with a gene-environment interaction, most clearly explained by epigenetic factors, especially as such factors were shown to be, at least partly, genetically driven.
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Affiliation(s)
- Philip Gorwood
- INSERM U894, Center of Psychiatry and Neuroscience, Paris, France; University Paris-Descartes; Paris, France; Sainte-Anne Hospital (CMME), Paris, France
| | - Yann Le Strat
- INSERM U894, Center of Psychiatry and Neuroscience, Paris, France; Hopital Louis Mourier (AP-HP), Colombes, France
| | - Nicolas Ramoz
- INSERM U894, Center of Psychiatry and Neuroscience, Paris, France; University Paris-Descartes
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137
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Examining interactions between genetic risk for alcohol problems, peer deviance, and interpersonal traumatic events on trajectories of alcohol use disorder symptoms among African American college students. Dev Psychopathol 2018; 30:1749-1761. [DOI: 10.1017/s0954579418000962] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
AbstractNumerous studies have demonstrated that genetic and environmental factors interact to influence alcohol problems. Yet prior research has primarily focused on samples of European descent and little is known about gene–environment interactions in relation to alcohol problems in non-European populations. In this study, we examined whether and how genetic risk for alcohol problems and peer deviance and interpersonal traumatic events independently and interactively influence trajectories of alcohol use disorder symptoms in a sample of African American students across the college years (N = 1,119; Mage= 18.44 years). Data were drawn from the Spit for Science study where participants completed multiple online surveys throughout college and provided a saliva sample for genotyping. Multilevel growth curve analyses indicated that alcohol dependence genome-wide polygenic risk scores did not predict trajectory of alcohol use disorder symptoms, while family history of alcohol problems was associated with alcohol use disorder symptoms at the start of college but not with the rate of change in symptoms over time. Peer deviance and interpersonal traumatic events were associated with more alcohol use disorder symptoms across college years. Neither alcohol dependence genome-wide polygenic risk scores nor family history of alcohol problems moderated the effects of these environmental risk factors on alcohol use disorder symptoms. Our findings indicated that peer deviance and experience of interpersonal traumatic events are salient risk factors that elevate risk for alcohol problems among African American college students. Family history of alcohol problems could be a useful indicator of genetic risk for alcohol problems. Gene identification efforts with much larger samples of African descent are needed to better characterize genetic risk for alcohol use disorders, in order to better understand gene–environment interaction processes in this understudied population.
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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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139
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Trajanoska K, Morris JA, Oei L, Zheng HF, Evans DM, Kiel DP, Ohlsson C, Richards JB, Rivadeneira F. Assessment of the genetic and clinical determinants of fracture risk: genome wide association and mendelian randomisation study. BMJ 2018; 362:k3225. [PMID: 30158200 PMCID: PMC6113773 DOI: 10.1136/bmj.k3225] [Citation(s) in RCA: 163] [Impact Index Per Article: 27.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 07/02/2018] [Indexed: 12/19/2022]
Abstract
OBJECTIVES To identify the genetic determinants of fracture risk and assess the role of 15 clinical risk factors on osteoporotic fracture risk. DESIGN Meta-analysis of genome wide association studies (GWAS) and a two-sample mendelian randomisation approach. SETTING 25 cohorts from Europe, United States, east Asia, and Australia with genome wide genotyping and fracture data. PARTICIPANTS A discovery set of 37 857 fracture cases and 227 116 controls; with replication in up to 147 200 fracture cases and 150 085 controls. Fracture cases were defined as individuals (>18 years old) who had fractures at any skeletal site confirmed by medical, radiological, or questionnaire reports. Instrumental variable analyses were performed to estimate effects of 15 selected clinical risk factors for fracture in a two-sample mendelian randomisation framework, using the largest previously published GWAS meta-analysis of each risk factor. RESULTS Of 15 fracture associated loci identified, all were also associated with bone mineral density and mapped to genes clustering in pathways known to be critical to bone biology (eg, SOST, WNT16, and ESR1) or novel pathways (FAM210A, GRB10, and ETS2). Mendelian randomisation analyses showed a clear effect of bone mineral density on fracture risk. One standard deviation decrease in genetically determined bone mineral density of the femoral neck was associated with a 55% increase in fracture risk (odds ratio 1.55 (95% confidence interval 1.48 to 1.63; P=1.5×10-68). Hand grip strength was inversely associated with fracture risk, but this result was not significant after multiple testing correction. The remaining clinical risk factors (including vitamin D levels) showed no evidence for an effect on fracture. CONCLUSIONS This large scale GWAS meta-analysis for fracture identified 15 genetic determinants of fracture, all of which also influenced bone mineral density. Among the clinical risk factors for fracture assessed, only bone mineral density showed a major causal effect on fracture. Genetic predisposition to lower levels of vitamin D and estimated calcium intake from dairy sources were not associated with fracture risk.
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Affiliation(s)
- Katerina Trajanoska
- Department of Internal Medicine, Erasmus MC, University Medical Center, Rotterdam, Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, Netherlands
| | - John A Morris
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Québec, Canada
- Department of Human Genetics, McGill University, Montréal, Québec, Canada
| | - Ling Oei
- Department of Internal Medicine, Erasmus MC, University Medical Center, Rotterdam, Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, Netherlands
| | - Hou-Feng Zheng
- DaP Lab, School of Life Sciences, Westlake University and Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
- Institute of Aging Research and the Affiliated Hospital, School of Medicine, Hangzhou Normal University, Hangzhou, Zhejiang, China
| | - David M Evans
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- University of Queensland Diamantina Institute, University of Queensland, Translational Research Institute, Brisbane, Australia
| | - Douglas P Kiel
- Institute for Aging Research, Hebrew SeniorLife, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Claes Ohlsson
- Centre for Bone and Arthritis Research, Department of Internal Medicine, Institute of Medicine, Sahlgrenska, Gothenburg, Sweden
| | - J Brent Richards
- Lady Davis Institute, Jewish General Hospital, McGill University, Montréal, Québec, Canada
- Department of Human Genetics, McGill University, Montréal, Québec, Canada
| | - Fernando Rivadeneira
- Department of Internal Medicine, Erasmus MC, University Medical Center, Rotterdam, Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, Netherlands
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140
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Deak JD, Miller AP, Gizer IR. Genetics of alcohol use disorder: a review. Curr Opin Psychol 2018; 27:56-61. [PMID: 30170251 DOI: 10.1016/j.copsyc.2018.07.012] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2018] [Revised: 07/25/2018] [Accepted: 07/31/2018] [Indexed: 01/13/2023]
Abstract
Alcohol use disorder (AUD) represents a significant and ongoing public health concern with 12-month prevalence estimates of ∼5.6%. Quantitative genetic studies suggest a heritability of approximately 50% for AUD, and as a result, significant efforts have been made to identify specific variation within the genome related to the etiology of AUD. Given the limited number of replicable findings that have emerged from genome-wide linkage and candidate gene association studies, more recent efforts have focused on the use of genome-wide association studies (GWAS). These studies have suggested that hundreds of variants across the genome, most of small effect (R2 < 0.002), contribute to the genetic etiology of AUD. The present review describes the initial, though limited, successes of GWAS to identify loci related to risk for AUD as well as other etiologically relevant traits (e.g. alcohol consumption). In addition, 'Post-GWAS' approaches that rely on GWAS data to estimate the heritability and co-heritability of traits, test causal relations between traits, and aid in gene discovery are described. Together, the described research findings illustrate the importance of molecular genetic research on AUD as we seek to better understand the mechanisms through which genetic variation leads to increased risk for AUD.
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Affiliation(s)
- Joseph D Deak
- Department of Psychological Sciences, University of Missouri, 210 McAlester Hall, Columbia, MO 65211, USA
| | - Alex P Miller
- Department of Psychological Sciences, University of Missouri, 210 McAlester Hall, Columbia, MO 65211, USA
| | - Ian R Gizer
- Department of Psychological Sciences, University of Missouri, 210 McAlester Hall, Columbia, MO 65211, USA.
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141
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Salvatore JE, Dick DM. Genetic influences on conduct disorder. Neurosci Biobehav Rev 2018; 91:91-101. [PMID: 27350097 PMCID: PMC5183514 DOI: 10.1016/j.neubiorev.2016.06.034] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2016] [Revised: 05/22/2016] [Accepted: 06/22/2016] [Indexed: 01/08/2023]
Abstract
Conduct disorder (CD) is a moderately heritable psychiatric disorder of childhood and adolescence characterized by aggression toward people and animals, destruction of property, deceitfulness or theft, and serious violation of rules. Genome-wide scans using linkage and association methods have identified a number of suggestive genomic regions that are pending replication. A small number of candidate genes (e.g., GABRA2, MAOA, SLC6A4, AVPR1A) are associated with CD related phenotypes across independent studies; however, failures to replicate also exist. Studies of gene-environment interplay show that CD genetic predispositions also contribute to selection into higher-risk environments, and that environmental factors can alter the importance of CD genetic factors and differentially methylate CD candidate genes. The field's understanding of CD etiology will benefit from larger, adequately powered studies in gene identification efforts; the incorporation of polygenic approaches in gene-environment interplay studies; attention to the mechanisms of risk from genes to brain to behavior; and the use of genetically informative data to test quasi-causal hypotheses about purported risk factors.
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Affiliation(s)
- Jessica E Salvatore
- Department of Psychology and the Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, VCU PO Box 842018, 806 West Franklin Street, Richmond, VA 23284-2018, USA.
| | - Danielle M Dick
- Department of Psychology, African American Studies, and Human & Molecular Genetics, VCU PO Box 842509, Richmond, VA 23284-2509, USA
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142
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Chi YC, Lee SL, Lee YP, Lai CL, Yin SJ. Modeling of Human Hepatic and Gastrointestinal Ethanol Metabolism with Kinetic-Mechanism-Based Full-Rate Equations of the Component Alcohol Dehydrogenase Isozymes and Allozymes. Chem Res Toxicol 2018; 31:556-569. [PMID: 29847918 DOI: 10.1021/acs.chemrestox.8b00003] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Alcohol dehydrogenase (ADH) is the principal enzyme responsible for the metabolism of ethanol. Human ADH constitutes a complex family of isozymes and allozymes with striking variation in kinetic properties and tissue distribution. The liver and the gastrointestinal tract are the major sites for first-pass metabolism (FPM). The quantitative contributions of ADH isozymes and ethnically distinct allozymes to cellular ethanol metabolism remain poorly understood. To address this issue, kinetic mechanism and the steady-state full-rate equations for recombinant human class I ADH1A, ADH1B (including allozymes ADH1B1, ADH1B2, and ADH1B3), ADH1C (including allozymes ADH1C1 and ADH1C2), class II ADH2, and class IV ADH4 were determined by initial velocity, product inhibition, and dead-end inhibition experiments in 0.1 M sodium phosphate at pH 7.5 and 25 °C. Models of the hepatic and gastrointestinal metabolisms of ethanol were constructed by linear combination of the numerical full-rate equations of the component isozymes and allozymes in target organs. The organ simulations indicate that in homozygous ADH1B*1/*1 livers, a representative genotype among ethnically distinct populations due to high prevalence of the allele, major contributors at 1 to 10 mM ethanol are ADH1B1 (45% to 24%) and the ADH1C allozymes (54% to 40%). The simulated activities at 1 to 50 mM ethanol for the gastrointestinal tract (total mucosae of ADH1C*1/*1-ADH4 stomach and the ADH1C*1/*1-ADH2 duodenum and jejunum) account for 0.68%-0.76% of that for the ADH1B*1/*1-ADH1C*1/*1 liver, suggesting gastrointestinal tract plays a relatively minor role in the human FPM of ethanol. Based on the flow-limited sinusoidal perfusion model, the simulated hepatic Kmapp, Vmaxapp, and Ci at a 95% clearance of ethanol for ADH1B*1/*1-ADH1C*1/*1 livers are compatible to that documented in hepatic vein catheterization and pharmacokinetic studies with humans that controlled for the genotypes. The model simulations suggest that slightly higher or similar ethanol elimination rates for ADH1B*2/*2 and ADH1B*3/*3 individuals compared with those for ADH1B*1/*1 individuals may result from higher hepatocellular acetaldehyde.
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Affiliation(s)
- Yu-Chou Chi
- Department of Biochemistry , National Defense Medical Center , 161 Minchuan East Road Section 6 , Taipei 11490 , Taiwan
| | - Shou-Lun Lee
- Department of Biological Science and Technology , China Medical University , 91 Hsueh-Shih Road , Taichung 40402 , Taiwan
| | - Yung-Ping Lee
- Department of Biochemistry , National Defense Medical Center , 161 Minchuan East Road Section 6 , Taipei 11490 , Taiwan
| | - Ching-Long Lai
- Department of Nursing , Chang Gung University of Science and Technology , 261 Wenhwa First Road , Taoyuan City 33303 , Taiwan
| | - Shih-Jiun Yin
- Department of Biochemistry , National Defense Medical Center , 161 Minchuan East Road Section 6 , Taipei 11490 , Taiwan
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143
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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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Thomas NS, Adkins A, Aliev F, Edwards AC, Webb BT, Tiarsmith EC, Kendler KS, Dick DM, Chartier KG. Alcohol Metabolizing Polygenic Risk for Alcohol Consumption in European American College Students. J Stud Alcohol Drugs 2018; 79:627-634. [PMID: 30079879 PMCID: PMC6090104 DOI: 10.15288/jsad.2018.79.627] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2017] [Accepted: 11/16/2017] [Indexed: 12/30/2023] Open
Abstract
OBJECTIVE Evidence suggests that the nature and magnitude of some genetic effects on alcohol use vary by age. We tested for moderation in the effect of an alcohol metabolizing polygenic score by time across the college years. METHOD Participants (total n = 2,214) were drawn from three cohorts of undergraduate college students, who were assessed annually for up to 4 years starting in their freshman year. Polygenic risk scores (PRSs) were calculated from genes involved in the metabolism of alcohol, as many of these markers are among the best replicated in association studies examining alcohol use phenotypes. Linear mixed effects models were fit by maximum likelihood to test the main effects of time and the PRS on alcohol consumption, as well as moderation of the PRS effect on alcohol consumption by time. RESULTS In the main effects model, the fixed effects for time and the PRS were positively associated with alcohol consumption. The interaction term testing moderation of the PRS effect by time reached statistical significance and remained statistically significant after other relevant interaction effects were controlled for. The main effect of the PRS accounted for 0.2% of the variance in alcohol consumption, whereas the interaction of PRS effect and time accounted for 0.05%. CONCLUSIONS Alcohol metabolizing genetic effects on alcohol use appear to be more influential in later years of college than in earlier years. Shifting environmental contexts, such as increased access to alcohol as individuals approach the legal age to purchase alcohol, may account for this association.
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Affiliation(s)
- Nathaniel S. Thomas
- College Behavioral and Emotional Health Institute, Virginia Commonwealth University, Richmond, Virginia
- Department of Psychology, Virginia Commonwealth University, Richmond, Virginia
| | - Amy Adkins
- College Behavioral and Emotional Health Institute, Virginia Commonwealth University, Richmond, Virginia
- Department of Psychology, Virginia Commonwealth University, Richmond, Virginia
| | - Fazil Aliev
- College Behavioral and Emotional Health Institute, Virginia Commonwealth University, Richmond, Virginia
- Department of Psychology, Virginia Commonwealth University, Richmond, Virginia
- Faculty of Business, Karabuk University, Turkey
| | - Alexis C. Edwards
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia
- Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia
| | - Bradley T. Webb
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia
- Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia
| | - E. Clare Tiarsmith
- School of Social Work, Virginia Commonwealth University, Richmond, Virginia
| | - Kenneth S. Kendler
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia
- Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, Virginia
| | - Danielle M. Dick
- College Behavioral and Emotional Health Institute, Virginia Commonwealth University, Richmond, Virginia
- Department of Psychology, Virginia Commonwealth University, Richmond, Virginia
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, Virginia
| | - Karen G. Chartier
- Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia
- School of Social Work, Virginia Commonwealth University, Richmond, Virginia
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145
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Levran O, Correa da Rosa J, Randesi M, Rotrosen J, Adelson M, Kreek MJ. A non-coding CRHR2 SNP rs255105, a cis-eQTL for a downstream lincRNA AC005154.6, is associated with heroin addiction. PLoS One 2018; 13:e0199951. [PMID: 29953524 PMCID: PMC6023117 DOI: 10.1371/journal.pone.0199951] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2018] [Accepted: 06/15/2018] [Indexed: 02/02/2023] Open
Abstract
Dysregulation of the stress response is implicated in drug addiction; therefore, polymorphisms in stress-related genes may be involved in this disease. An analysis was performed to identify associations between variants in 11 stress-related genes, selected a priori, and heroin addiction. Two discovery samples of American subjects of European descent (EA, n = 601) and of African Americans (AA, n = 400) were analyzed separately. Ancestry was verified by principal component analysis. Final sets of 414 (EA) and 562 (AA) variants were analyzed after filtering of 846 high-quality variants. The main result was an association of a non-coding SNP rs255105 in the CRH (CRF) receptor 2 gene (CRHR2), in the discovery EA sample (Pnominal = .00006; OR = 2.1; 95% CI 1.4-3.1). The association signal remained significant after permutation-based multiple testing correction. The result was corroborated by an independent EA case sample (n = 364). Bioinformatics analysis revealed that SNP rs255105 is associated with the expression of a downstream long intergenic non-coding RNA (lincRNA) gene AC005154.6. AC005154.6 is highly expressed in the pituitary but its functions are unknown. LincRNAs have been previously associated with adaptive behavior, PTSD, and alcohol addiction. Further studies are warranted to corroborate the association results and to assess the potential relevance of this lincRNA to addiction and other stress-related disorders.
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Affiliation(s)
- Orna Levran
- The Laboratory of the Biology of Addictive Diseases, The Rockefeller University, New York, New York, United States of America
| | - Joel Correa da Rosa
- Center for Clinical and Translational Science, The Rockefeller University, New York, New York, United States of America
| | - Matthew Randesi
- The Laboratory of the Biology of Addictive Diseases, The Rockefeller University, New York, New York, United States of America
| | - John Rotrosen
- NYU School of Medicine, New York, New York, United States of America
| | - Miriam Adelson
- Dr. Miriam and Sheldon G. Adelson Clinic for Drug Abuse Treatment and Research, Las Vegas, Nevada, United States of America
| | - Mary Jeanne Kreek
- The Laboratory of the Biology of Addictive Diseases, The Rockefeller University, New York, New York, United States of America
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Feitosa MF, Kraja AT, Chasman DI, Sung YJ, Winkler TW, Ntalla I, Guo X, Franceschini N, Cheng CY, Sim X, Vojinovic D, Marten J, Musani SK, Li C, Bentley AR, Brown MR, Schwander K, Richard MA, Noordam R, Aschard H, Bartz TM, Bielak LF, Dorajoo R, Fisher V, Hartwig FP, Horimoto ARVR, Lohman KK, Manning AK, Rankinen T, Smith AV, Tajuddin SM, Wojczynski MK, Alver M, Boissel M, Cai Q, Campbell A, Chai JF, Chen X, Divers J, Gao C, Goel A, Hagemeijer Y, Harris SE, He M, Hsu FC, Jackson AU, Kähönen M, Kasturiratne A, Komulainen P, Kühnel B, Laguzzi F, Luan J, Matoba N, Nolte IM, Padmanabhan S, Riaz M, Rueedi R, Robino A, Said MA, Scott RA, Sofer T, Stančáková A, Takeuchi F, Tayo BO, van der Most PJ, Varga TV, Vitart V, Wang Y, Ware EB, Warren HR, Weiss S, Wen W, Yanek LR, Zhang W, Zhao JH, Afaq S, Amin N, Amini M, Arking DE, Aung T, Boerwinkle E, Borecki I, Broeckel U, Brown M, Brumat M, Burke GL, Canouil M, Chakravarti A, Charumathi S, Ida Chen YD, Connell JM, Correa A, de las Fuentes L, de Mutsert R, de Silva HJ, Deng X, Ding J, Duan Q, Eaton CB, Ehret G, Eppinga RN, Evangelou E, Faul JD, Felix SB, Forouhi NG, Forrester T, Franco OH, Friedlander Y, Gandin I, Gao H, Ghanbari M, Gigante B, Gu CC, Gu D, Hagenaars SP, Hallmans G, Harris TB, He J, Heikkinen S, Heng CK, Hirata M, Howard BV, Ikram MA, John U, Katsuya T, Khor CC, Kilpeläinen TO, Koh WP, Krieger JE, Kritchevsky SB, Kubo M, Kuusisto J, Lakka TA, Langefeld CD, Langenberg C, Launer LJ, Lehne B, Lewis CE, Li Y, Lin S, Liu J, Liu J, Loh M, Louie T, Mägi R, McKenzie CA, Meitinger T, Metspalu A, Milaneschi Y, Milani L, Mohlke KL, Momozawa Y, Nalls MA, Nelson CP, Sotoodehnia N, Norris JM, O'Connell JR, Palmer ND, Perls T, Pedersen NL, Peters A, Peyser PA, Poulter N, Raffel LJ, Raitakari OT, Roll K, Rose LM, Rosendaal FR, Rotter JI, Schmidt CO, Schreiner PJ, Schupf N, Scott WR, Sever PS, Shi Y, Sidney S, Sims M, Sitlani CM, Smith JA, Snieder H, Starr JM, Strauch K, Stringham HM, Tan NYQ, Tang H, Taylor KD, Teo YY, Tham YC, Turner ST, Uitterlinden AG, Vollenweider P, Waldenberger M, Wang L, Wang YX, Wei WB, Williams C, Yao J, Yu C, Yuan JM, Zhao W, Zonderman AB, Becker DM, Boehnke M, Bowden DW, Chambers JC, Deary IJ, Esko T, Farrall M, Franks PW, Freedman BI, Froguel P, Gasparini P, Gieger C, Jonas JB, Kamatani Y, Kato N, Kooner JS, Kutalik Z, Laakso M, Laurie CC, Leander K, Lehtimäki T, Study LC, Magnusson PKE, Oldehinkel AJ, Penninx BWJH, Polasek O, Porteous DJ, Rauramaa R, Samani NJ, Scott J, Shu XO, van der Harst P, Wagenknecht LE, Wareham NJ, Watkins H, Weir DR, Wickremasinghe AR, Wu T, Zheng W, Bouchard C, Christensen K, Evans MK, Gudnason V, Horta BL, Kardia SLR, Liu Y, Pereira AC, Psaty BM, Ridker PM, van Dam RM, Gauderman WJ, Zhu X, Mook-Kanamori DO, Fornage M, Rotimi CN, Cupples LA, Kelly TN, Fox ER, Hayward C, van Duijn CM, Tai ES, Wong TY, Kooperberg C, Palmas W, Rice K, Morrison AC, Elliott P, Caulfield MJ, Munroe PB, Rao DC, Province MA, Levy D. Novel genetic associations for blood pressure identified via gene-alcohol interaction in up to 570K individuals across multiple ancestries. PLoS One 2018; 13:e0198166. [PMID: 29912962 PMCID: PMC6005576 DOI: 10.1371/journal.pone.0198166] [Citation(s) in RCA: 60] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2018] [Accepted: 05/15/2018] [Indexed: 01/01/2023] Open
Abstract
Heavy alcohol consumption is an established risk factor for hypertension; the mechanism by which alcohol consumption impact blood pressure (BP) regulation remains unknown. We hypothesized that a genome-wide association study accounting for gene-alcohol consumption interaction for BP might identify additional BP loci and contribute to the understanding of alcohol-related BP regulation. We conducted a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions. In Stage 1, genome-wide discovery meta-analyses in ≈131K individuals across several ancestry groups yielded 3,514 SNVs (245 loci) with suggestive evidence of association (P < 1.0 x 10-5). In Stage 2, these SNVs were tested for independent external replication in ≈440K individuals across multiple ancestries. We identified and replicated (at Bonferroni correction threshold) five novel BP loci (380 SNVs in 21 genes) and 49 previously reported BP loci (2,159 SNVs in 109 genes) in European ancestry, and in multi-ancestry meta-analyses (P < 5.0 x 10-8). For African ancestry samples, we detected 18 potentially novel BP loci (P < 5.0 x 10-8) in Stage 1 that warrant further replication. Additionally, correlated meta-analysis identified eight novel BP loci (11 genes). Several genes in these loci (e.g., PINX1, GATA4, BLK, FTO and GABBR2) have been previously reported to be associated with alcohol consumption. These findings provide insights into the role of alcohol consumption in the genetic architecture of hypertension.
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Affiliation(s)
- Mary F. Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Aldi T. Kraja
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Daniel I. Chasman
- Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
| | - Yun J. Sung
- Division of Biostatistics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Thomas W. Winkler
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Ioanna Ntalla
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Xiuqing Guo
- Genomic Outcomes, Pediatrics, Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Nora Franceschini
- Epidemiology, University of North Carolina Gilling School of Global Public Health, Chapel Hill, North Carolina, United States of America
| | - Ching-Yu Cheng
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University Health System and National University of Singapore, Singapore, Singapore
| | - Dina Vojinovic
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Jonathan Marten
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Solomon K. Musani
- Jackson Heart Study, Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi, United States of America
| | - Changwei Li
- Epidemiology and Biostatistics, University of Georgia at Athens College of Public Health, Athens, Georgia, United States of America
| | - Amy R. Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Michael R. Brown
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, The University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Karen Schwander
- Division of Biostatistics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Melissa A. Richard
- Brown Foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Raymond Noordam
- Internal Medicine, Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands
| | - Hugues Aschard
- Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America
- Centre de Bioinformatique, Biostatistique et Biologie Intégrative (C3BI), Institut Pasteur, Paris, France
| | - Traci M. Bartz
- Cardiovascular Health Research Unit, Biostatistics and Medicine, University of Washington, Seattle, Washington, United States of America
| | - Lawrence F. Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Rajkumar Dorajoo
- Genome Institute of Singapore, Agency for Science Technology and Research, Singapore, Singapore
| | - Virginia Fisher
- Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
| | - Fernando P. Hartwig
- Postgraduate Programme in Epidemiology, Federal University of Pelotas, Pelotas, RS, Brazil
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
| | - Andrea R. V. R. Horimoto
- Laboratory of Genetics and Molecular Cardiology, Heart Institute (InCor), University of São Paulo Medical School, São Paulo, SP, Brazil
| | - Kurt K. Lohman
- Biostatistical Sciences, Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Alisa K. Manning
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Tuomo Rankinen
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, Louisiana, United States of America
| | - Albert V. Smith
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Salman M. Tajuddin
- Health Disparities Research Section, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, United States of America
| | - Mary K. Wojczynski
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Maris Alver
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Mathilde Boissel
- CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, University of Lille, Lille, France
| | - Qiuyin Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America
| | - Archie Campbell
- Centre for Genomic & Experimental Medicine, Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Jin Fang Chai
- Saw Swee Hock School of Public Health, National University Health System and National University of Singapore, Singapore, Singapore
| | - Xu Chen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Stockholm, Sweden
| | - Jasmin Divers
- Biostatistical Sciences, Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Chuan Gao
- Molecular Genetics and Genomics Program, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Anuj Goel
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, Oxfordshire, United Kingdom
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, Oxfordshire, United Kingdom
| | - Yanick Hagemeijer
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Sarah E. Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, United Kingdom
- Medical Genetics Section, Centre for Genomic and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, The University of Edinburgh, Edinburgh, United Kingdom
| | - Meian He
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health for Incubating, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Fang-Chi Hsu
- Biostatistical Sciences, Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Anne U. Jackson
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, Tampere, Finland
- University of Tampere, Tampere, Finland
| | | | - Pirjo Komulainen
- Foundation for Research in Health Exercise and Nutrition, Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - Brigitte Kühnel
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Federica Laguzzi
- Unit of Cardiovascular Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Jian'an Luan
- MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
| | - Nana Matoba
- Laboratory for Statistical Analysis, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
| | - Ilja M. Nolte
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Sandosh Padmanabhan
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom
| | - Muhammad Riaz
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, United Kingdom
| | - Rico Rueedi
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Instititute of Bioinformatics, Lausanne, Switzerland
| | - Antonietta Robino
- Institute for Maternal and Child Health—IRCCS "Burlo Garofolo", Trieste, Italy
| | - M. Abdullah Said
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Robert A. Scott
- MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
| | - Tamar Sofer
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, United States of America
| | - Alena Stančáková
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Fumihiko Takeuchi
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Bamidele O. Tayo
- Department of Public Health Sciences, Loyola University Chicago, Maywood, Illinois, United States of America
| | - Peter J. van der Most
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Tibor V. Varga
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Skåne University Hospital, Malmö, Sweden
| | - Veronique Vitart
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Yajuan Wang
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Erin B. Ware
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Helen R. Warren
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
- NIHR Barts Cardiovascular Biomedical Research Unit, Queen Mary University of London, London, London, United Kingdom
| | - Stefan Weiss
- Interfaculty Institute for Genetics and Functional genomics, University Medicine Ernst Moritz Arndt University Greifsald, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
| | - Wanqing Wen
- Division of Epidemiology, Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America
| | - Lisa R. Yanek
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Weihua Zhang
- Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
- Department of Cardiology, Ealing Hospital, Middlesex, United Kingdom
| | - Jing Hua Zhao
- MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
| | - Saima Afaq
- Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
| | - Najaf Amin
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Marzyeh Amini
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Dan E. Arking
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Tin Aung
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Eric Boerwinkle
- Department of Epidemiology, Human Genetics, and Environmental Sciences, The University of Texas School of Public Health, Houston, Texas, United States of America
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas, United States of America
| | - Ingrid Borecki
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Ulrich Broeckel
- Section of Genomic Pediatrics, Department of Pediatrics, Medicine and Physiology, Medical College of Wisconsin, Milwaukee, Wisconsin, United States of America
| | - Morris Brown
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
- NIHR Barts Cardiovascular Biomedical Research Unit, Queen Mary University of London, London, London, United Kingdom
| | - Marco Brumat
- Department of Medical Sciences, University of Trieste, Trieste, Italy
| | - Gregory L. Burke
- Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Mickaël Canouil
- CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, University of Lille, Lille, France
| | - Aravinda Chakravarti
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Sabanayagam Charumathi
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
| | - Yii-Der Ida Chen
- Genomic Outcomes, Pediatrics, Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - John M. Connell
- Ninewells Hospital & Medical School, University of Dundee, Dundee, Scotland, United Kingdom
| | - Adolfo Correa
- Jackson Heart Study, Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi, United States of America
| | - Lisa de las Fuentes
- Division of Biostatistics, Washington University School of Medicine, St. Louis, Missouri, United States of America
- Cardiovascular Division, Department of Medicine, Washington University, St. Louis, Missouri, United States of America
| | - Renée de Mutsert
- Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - H. Janaka de Silva
- Department of Medicine, Faculty of Medicine, University of Kelaniya, Ragama, Sri Lanka
| | - Xuan Deng
- Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
| | - Jingzhong Ding
- Center on Diabetes, Obesity, and Metabolism, Gerontology and Geriatric Medicine, Wake Forest University Health Sciences, Winston-Salem, North Carolina, United States of America
| | - Qing Duan
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Charles B. Eaton
- Department of Family Medicine and Epidemiology, Alpert Medical School of Brown University, Providence, Rhode Island, United States of America
| | - Georg Ehret
- Cardiology, Geneva University Hospital, Geneva, Switzerland
| | - Ruben N. Eppinga
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Evangelos Evangelou
- Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece
| | - Jessica D. Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Stephan B. Felix
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
| | - Nita G. Forouhi
- MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
| | - Terrence Forrester
- The Caribbean Institute for Health Research (CAIHR), University of the West Indies, Mona, Jamaica
| | - Oscar H. Franco
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Yechiel Friedlander
- Braun School of Public Health, Hebrew University-Hadassah Medical Center, Jerusalem, Israel
| | - Ilaria Gandin
- Department of Medical Sciences, University of Trieste, Trieste, Italy
| | - He Gao
- Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
- Department of Genetics, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Bruna Gigante
- Unit of Cardiovascular Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - C. Charles Gu
- Division of Biostatistics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Dongfeng Gu
- Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center of Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Saskia P. Hagenaars
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, United Kingdom
- Psychology, The University of Edinburgh, Edinburgh, United Kingdom
| | - Göran Hallmans
- Department of Public Health and Clinical Medicine, Nutritional Research, Umeå University, Umeå, Västerbotten, Sweden
| | - Tamara B. Harris
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Jiang He
- Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, United States of America
- Medicine, Tulane University School of Medicine, New Orleans, Louisiana, United States of America
| | - Sami Heikkinen
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio Campus, Finland
| | - Chew-Kiat Heng
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Khoo Teck Puat–National University Children's Medical Institute, National University Health System, Singapore
| | - Makoto Hirata
- Laboratory of Genome Technology, Human Genome Center, Institute of Medical Science, The University of Tokyo, Minato-ku, Japan
| | - Barbara V. Howard
- MedStar Health Research Institute, Hyattsville, Maryland, United States of America
- Center for Clinical and Translational Sciences and Department of Medicine, Georgetown-Howard Universities, Washington, DC, United States of America
| | - M. Arfan Ikram
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
- Department of Neurology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | | | - Ulrich John
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Institute of Social Medicine and Prevention, University Medicine Greifswald, Greifswald, Germany
| | - Tomohiro Katsuya
- Department of Clinical Gene Therapy, Osaka University Graduate School of Medicine, Suita, Japan
- Department of Geriatric Medicine and Nephrology, Osaka University Graduate School of Medicine, Suita, Japan
| | - Chiea Chuen Khor
- Genome Institute of Singapore, Agency for Science Technology and Research, Singapore, Singapore
- Department of Biochemistry, National University of Singapore, Singapore, Singapore
| | - Tuomas O. Kilpeläinen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Environmental Medicine and Public Health, The Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Woon-Puay Koh
- Saw Swee Hock School of Public Health, National University Health System and National University of Singapore, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - José E. Krieger
- Laboratory of Genetics and Molecular Cardiology, Heart Institute (InCor), University of São Paulo Medical School, São Paulo, SP, Brazil
| | - Stephen B. Kritchevsky
- Sticht Center for Healthy Aging and Alzheimer's Prevention, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Michiaki Kubo
- Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
| | - Johanna Kuusisto
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Timo A. Lakka
- Foundation for Research in Health Exercise and Nutrition, Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio Campus, Finland
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland
| | - Carl D. Langefeld
- Biostatistical Sciences, Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
| | - Lenore J. Launer
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Benjamin Lehne
- Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
| | - Cora E. Lewis
- Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States of America
| | - Yize Li
- Division of Biostatistics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Shiow Lin
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Jianjun Liu
- Saw Swee Hock School of Public Health, National University Health System and National University of Singapore, Singapore, Singapore
- Genome Institute of Singapore, Agency for Science Technology and Research, Singapore, Singapore
| | - Jingmin Liu
- WHI CCC, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Marie Loh
- Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
- Translational Laboratory in Genetic Medicine, Agency for Science, Technology and Research, Singapore
| | - Tin Louie
- Department of Biostatistics, University of Washington, Seattle, Washington, United States of America
| | - Reedik Mägi
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Colin A. McKenzie
- The Caribbean Institute for Health Research (CAIHR), University of the West Indies, Mona, Jamaica
| | - Thomas Meitinger
- Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Human Genetics, Technische Universität München, Munich, Germany
| | | | - Yuri Milaneschi
- Department of Psychiatry, Amsterdam Neuroscience and Amsterdam Public Health Research Institute, VU University Medical Center, Amsterdam, The Netherlands
| | - Lili Milani
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Karen L. Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
| | - Mike A. Nalls
- Data Tecnica International, Glen Echo, Maryland, United States of America
- Laboratory of Neurogenetics, National Institute on Aging, Bethesda, Maryland, United States of America
| | - Christopher P. Nelson
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, United Kingdom
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Division of Cardiology, University of Washington, Seattle, Washington, United States of America
| | - Jill M. Norris
- Department of Epidemiology, Colorado School of Public Health, Aurora, Colorado, United States of America
| | - Jeff R. O'Connell
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
- Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - Nicholette D. Palmer
- Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Thomas Perls
- Geriatrics Section, Boston University Medical Center, Boston, Massachusetts, United States of America
| | - Nancy L. Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Stockholm, Sweden
| | - Annette Peters
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- DZHK (German Centre for Cardiovascular Research), partner site Munich Heart Alliance, Neuherberg, Germany
| | - Patricia A. Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Neil Poulter
- School of Public Health, Imperial College London, London, London, United Kingdom
| | - Leslie J. Raffel
- Division of Genetic and Genomic Medicine, Department of Pediatrics, University of California, Irvine, California, United States of America
| | - Olli T. Raitakari
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Kathryn Roll
- Genomic Outcomes, Pediatrics, Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Lynda M. Rose
- Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America
| | - Frits R. Rosendaal
- Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Jerome I. Rotter
- Genomic Outcomes, Pediatrics, Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Carsten O. Schmidt
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Pamela J. Schreiner
- Epidemiology & Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Nicole Schupf
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University Medical Center, New York, New York, United States of America
| | - William R. Scott
- Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Peter S. Sever
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Yuan Shi
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Stephen Sidney
- Division of Research, Kaiser Permanente of Northern California, Oakland, California, United States of America
| | - Mario Sims
- Jackson Heart Study, Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi, United States of America
| | - Colleen M. Sitlani
- Cardiovascular Health Research Unit, Medicine, University of Washington, Seattle, Washington, United States of America
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - John M. Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, United Kingdom
- Alzheimer Scotland Dementia Research Centre, The University of Edinburgh, Edinburgh, United Kingdom
| | - Konstantin Strauch
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Chair of Genetic Epidemiology, IBE, Faculty of Medicine, LMU, Munich, Germany
| | - Heather M. Stringham
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Nicholas Y. Q. Tan
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Hua Tang
- Department of Genetics, Stanford University, Stanford, California, United States of America
| | - Kent D. Taylor
- Genomic Outcomes, Pediatrics, Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Yik Ying Teo
- Saw Swee Hock School of Public Health, National University Health System and National University of Singapore, Singapore, Singapore
- Genome Institute of Singapore, Agency for Science Technology and Research, Singapore, Singapore
- Life Sciences Institute, National University of Singapore, Singapore, Singapore
- NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore, Singapore
- Department of Statistics and Applied Probability, National University of Singapore, Singapore, Singapore
| | - Yih Chung Tham
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Stephen T. Turner
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota, United States of America
| | - André G. Uitterlinden
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Peter Vollenweider
- Service of Internal Medicine, Department of Internal Medicine, University Hospital, Lausanne, Switzerland
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Lihua Wang
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Ya Xing Wang
- Beijing Institute of Ophthalmology, Beijing Ophthalmology and Visual Science Key Lab, Beijing Tongren Eye Center, Capital Medical University, Beijing, China
- Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Wen Bin Wei
- Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Christine Williams
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Jie Yao
- Genomic Outcomes, Pediatrics, Institute for Translational Genomics and Population Sciences, LABioMed at Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Caizheng Yu
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health for Incubating, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jian-Min Yuan
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- Division of Cancer Control and Population Sciences, UPMC Hillman Cancer, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Alan B. Zonderman
- Behavioral Epidemiology Section, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, United States of America
| | - Diane M. Becker
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Donald W. Bowden
- Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - John C. Chambers
- Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
- Department of Cardiology, Ealing Hospital, Middlesex, United Kingdom
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
- Imperial College Healthcare NHS Trust, London, United Kingdom
- MRC-PHE Centre for Environment and Health, Department of Epidemiology & Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - Ian J. Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, United Kingdom
- Psychology, The University of Edinburgh, Edinburgh, United Kingdom
| | - Tõnu Esko
- Estonian Genome Center, University of Tartu, Tartu, Estonia
- Broad Institute of the Massachusetts Institute of Technology and Harvard University, Boston, Massachusetts, United States of America
| | - Martin Farrall
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, Oxfordshire, United Kingdom
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, Oxfordshire, United Kingdom
| | - Paul W. Franks
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Skåne University Hospital, Malmö, Sweden
- Harvard T. H. Chan School of Public Health, Department of Nutrition, Harvard University, Boston, Massachusetts, United States of America
| | - Barry I. Freedman
- Nephrology, Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Philippe Froguel
- CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, University of Lille, Lille, France
- Department of Genomics of Common Disease, Imperial College London, London, United Kingdom
| | - Paolo Gasparini
- Institute for Maternal and Child Health—IRCCS "Burlo Garofolo", Trieste, Italy
- Department of Medical Sciences, University of Trieste, Trieste, Italy
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD e.V.), Neuherberg, Germany
| | - Jost Bruno Jonas
- Beijing Institute of Ophthalmology, Beijing Ophthalmology and Visual Science Key Lab, Beijing Tongren Eye Center, Capital Medical University, Beijing, China
- Department of Ophthalmology, Medical Faculty Mannheim, University Heidelberg, Mannheim, Germany, Germany
| | - Yoichiro Kamatani
- Laboratory for Statistical Analysis, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
| | - Norihiro Kato
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Jaspal S. Kooner
- Department of Cardiology, Ealing Hospital, Middlesex, United Kingdom
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Imperial College Healthcare NHS Trust, London, United Kingdom
- MRC-PHE Centre for Environment and Health, Department of Epidemiology & Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - Zoltán Kutalik
- Swiss Instititute of Bioinformatics, Lausanne, Switzerland
- Institute of Social and Preventive Medicine, Lausanne University Hospital, Lausanne, Switzerland
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Cathy C. Laurie
- Department of Biostatistics, University of Washington, Seattle, Washington, United States of America
| | - Karin Leander
- Unit of Cardiovascular Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center—Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland
| | | | - Patrik K. E. Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Stockholm, Sweden
| | - Albertine J. Oldehinkel
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Brenda W. J. H. Penninx
- Department of Psychiatry, Amsterdam Neuroscience and Amsterdam Public Health Research Institute, VU University Medical Center, Amsterdam, The Netherlands
| | - Ozren Polasek
- Department of Public Health, Department of Medicine, University of Split, Split, Croatia
- Psychiatric Hospital "Sveti Ivan", Zagreb, Croatia
- Gen-info Ltd, Zagreb, Croatia
| | - David J. Porteous
- Centre for Genomic & Experimental Medicine, Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Rainer Rauramaa
- Foundation for Research in Health Exercise and Nutrition, Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - Nilesh J. Samani
- Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, United Kingdom
| | - James Scott
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America
| | - Pim van der Harst
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Lynne E. Wagenknecht
- Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | | | - Hugh Watkins
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, Oxfordshire, United Kingdom
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, Oxfordshire, United Kingdom
| | - David R. Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan, United States of America
| | | | - Tangchun Wu
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health for Incubating, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America
| | - Claude Bouchard
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, Louisiana, United States of America
| | - Kaare Christensen
- The Danish Aging Research Center, Institute of Public Health, University of Southern Denmark, Odense, Denmark
| | - Michele K. Evans
- Health Disparities Research Section, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, United States of America
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Bernardo L. Horta
- Postgraduate Programme in Epidemiology, Federal University of Pelotas, Pelotas, RS, Brazil
| | - Sharon L. R. Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Yongmei Liu
- Public Health Sciences, Epidemiology and Prevention, Wake Forest University Health Sciences, Winston-Salem, North Carolina, United States of America
| | - Alexandre C. Pereira
- Laboratory of Genetics and Molecular Cardiology, Heart Institute (InCor), University of São Paulo Medical School, São Paulo, SP, Brazil
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Epidemiology, Medicine and Health Services, University of Washington, Seattle, Washington, United States of America
- Kaiser Permanente Washington, Health Research Institute, Seattle, Washington, United States of America
| | - Paul M. Ridker
- Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
| | - Rob M. van Dam
- Saw Swee Hock School of Public Health, National University Health System and National University of Singapore, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - W. James Gauderman
- Biostatistics, Preventive Medicine, University of Southern California, Los Angeles, California, United States of America
| | - Xiaofeng Zhu
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Dennis O. Mook-Kanamori
- Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
- Public Health and Primary Care, Leiden University Medical Center, Leiden, The Netherlands
| | - Myriam Fornage
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, The University of Texas Health Science Center at Houston, Houston, Texas, United States of America
- Brown Foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Charles N. Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - L. Adrienne Cupples
- Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
- The Framingham Heart Study, Framingham, Massachusetts, United States of America
| | - Tanika N. Kelly
- Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, United States of America
| | - Ervin R. Fox
- Cardiology, Medicine, University of Mississippi Medical Center, Jackson, Mississippi, United States of America
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Cornelia M. van Duijn
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - E Shyong Tai
- Saw Swee Hock School of Public Health, National University Health System and National University of Singapore, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Tien Yin Wong
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Charles Kooperberg
- Fred Hutchinson Cancer Research Center, University of Washington School of Public Health, Seattle, Washington, United States of America
| | - Walter Palmas
- Medicine, Columbia University Medical Center, New York, New York, United States of America
| | - Kenneth Rice
- Department of Biostatistics, University of Washington, Seattle, Washington, United States of America
| | - Alanna C. Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, The University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Paul Elliott
- MRC-PHE Centre for Environment and Health, Department of Epidemiology & Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - Mark J. Caulfield
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
- NIHR Barts Cardiovascular Biomedical Research Unit, Queen Mary University of London, London, London, United Kingdom
| | - Patricia B. Munroe
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
- NIHR Barts Cardiovascular Biomedical Research Unit, Queen Mary University of London, London, London, United Kingdom
| | - Dabeeru C. Rao
- Division of Biostatistics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Michael A. Province
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Daniel Levy
- The Framingham Heart Study, Framingham, Massachusetts, United States of America
- The Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, United States of America
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Koulentaki M, Kouroumalis E. GABA A receptor polymorphisms in alcohol use disorder in the GWAS era. Psychopharmacology (Berl) 2018; 235:1845-1865. [PMID: 29721579 DOI: 10.1007/s00213-018-4918-4] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/04/2017] [Accepted: 04/18/2018] [Indexed: 12/11/2022]
Abstract
Alcohol use disorder (AUD) is a chronic, relapsing, neuro-psychiatric illness of high prevalence and with a serious public health impact worldwide. It is complex and polygenic, with a heritability of about 50%, and influenced by environmental causal heterogeneity. Risk factors associated with its etiology have a genetic component. GABA (γ-aminobutyric acid) is a major inhibitory neurotransmitter in mammalian brain. GABAA receptors are believed to mediate some of the physiological and behavioral actions of alcohol. In this critical review, relevant genetic terms and type and methodology of the genetic studies are briefly explained. Postulated candidate genes that encode subunits of GABAA receptors, with all the reported SNPs, are presented. Genetic studies and meta-analyses examining polymorphisms of the GABAA receptor and their association with AUD predisposition are presented. The data are critically examined with reference to recent GWAS studies that failed to show relations between GABAA receptors and AUD. Restrictions and perspectives of the different findings are discussed.
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Affiliation(s)
- Mairi Koulentaki
- Alcohology Research Laboratory, Medical School, University of Crete, 71500, Heraklion, Crete, Greece.,Department of Gastroenterology, University Hospital Heraklion, 71500, Heraklion, Crete, Greece
| | - Elias Kouroumalis
- Department of Gastroenterology, University Hospital Heraklion, 71500, Heraklion, Crete, Greece.
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148
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The OPRM1 A118G polymorphism: converging evidence against associations with alcohol sensitivity and consumption. Neuropsychopharmacology 2018; 43:1530-1538. [PMID: 29497164 PMCID: PMC5983535 DOI: 10.1038/s41386-017-0002-8] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2017] [Revised: 10/28/2017] [Accepted: 12/07/2017] [Indexed: 12/31/2022]
Abstract
The endogenous opioid system may be involved in the development and maintenance of alcohol use disorder (AUD) and is a target for existing AUD pharmacotherapies. A functional polymorphism of the mu-opioid receptor gene (OPRM1 A118G, rs1799971) may alter the risk of developing AUD. Human laboratory studies have demonstrated that minor allele carriers self-administer more alcohol, show greater sensitivity to alcohol's effects, and exhibit increased alcohol-induced dopamine release. On the other hand, large genome-wide association studies and meta-analyses of candidate gene studies have not found an association between this genotype and alcohol dependence diagnosis. Given this discrepancy, the present study sought to verify whether OPRM1 A118G was associated with alcohol self-administration, subjective response to alcohol, and craving in a sample of 106 social drinkers of European ancestry who completed an intravenous alcohol self-administration session. We found no relationship between OPRM1 rs1799971 genotype and subjective response to alcohol or craving. OPRM1 genotype was not associated with total alcohol exposure or likelihood of attaining a binge-level exposure (80 mg%) during the intravenous alcohol self-administration session. Analysis of 90-day Timeline Followback interview data in a larger sample of 965 participants of European ancestry found no relationship between OPRM1 genotype and alcohol consumption in either alcohol dependent or non-dependent participants. These findings suggest that there may not be an association between OPRM1 rs1799971 genotype and alcohol consumption or sensitivity in individuals of European ancestry.
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149
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Chen G, Xue WD, Zhu J. Full genetic analysis for genome-wide association study of Fangji: a powerful approach for effectively dissecting the molecular architecture of personalized traditional Chinese medicine. Acta Pharmacol Sin 2018; 39:906-911. [PMID: 29417942 DOI: 10.1038/aps.2017.137] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2017] [Accepted: 08/29/2017] [Indexed: 12/24/2022] Open
Abstract
Elucidation of the systems biology foundation underlying the effect of Fangji, which are multi-herbal traditional Chinese medicine (TCM) formulas, is one of the major aims in the field. The numerous bioactive ingredients of a Fangji deal with the multiple targets of a complex disease, which is influenced by a number of genes and their interactions with the environment. Genome-wide association study (GWAS) is an unbiased approach for dissecting the genetic variants underlying complex diseases and individual response to a given treatment. GWAS has great potential for the study of systems biology from the point of view of genomics, but the capacity using current analysis models is largely handicapped, as evidenced by missing heritability. Recent development of a full genetic model, in which gene-gene interactions (dominance and epistasis) and gene-environment interactions are all considered, has addressed these problems. This approach has been demonstrated to substantially increase model power, remarkably improving the detection of association of GWAS and the construction of the molecular architecture. This analysis does not require a very large sample size, which is often difficult to meet for a GWAS of treatment response. Furthermore, this analysis can integrate other omic information and allow for variations of Fangji, which is very promising for Fangjiomic study and detection of the sophisticated molecular architecture of the function of Fangji, as well as for the delineation of the systems biology of personalized medicine in TCM in an unbiased and comprehensive manner.
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150
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Ramoz N, Gorwood P. Aspects génétiques de l’alcoolo-dépendance. Presse Med 2018; 47:547-553. [DOI: 10.1016/j.lpm.2017.07.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2017] [Accepted: 07/12/2017] [Indexed: 12/31/2022] Open
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