Genome-Wide Association Study Meta-Analysis of the Alcohol Use Disorders Identification Test (AUDIT) in Two Population-Based Cohorts.
paper
Cited
Public
- Authors
- Sanchez-Roige, Sandra; Palmer, Abraham A; Fontanillas, Pierre; Elson, Sarah L; 23andMe Research Team, the Substance Use Disorder Working Group of the Psychiatric Genomics Consortium; Adams, Mark J; Howard, David M; Edenberg, Howard J; Davies, Gail; Crist, Richard C; Deary, Ian J; McIntosh, Andrew M; Clarke, Toni-Kim
- Year
- 2019
- Journal
- The American journal of psychiatry
- PMID
- 30336701
- DOI
- 10.1176/appi.ajp.2018.18040369
- PMCID
- PMC6365681
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 (r=0.76-0.92) and DSM-IV alcohol dependence (r=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 (r=0.22), major depressive disorder (r=0.26), and attention deficit hyperactivity disorder (r=0.23), whereas AUDIT-C score was significantly negatively genetically correlated with major depressive disorder (r=-0.24) and ADHD (r=-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 β€4 as control subjects and those with scores β₯12 as case subjects produced a significant high genetic correlation with DSM-IV alcohol dependence (r=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.
Manhattan and QQ plots for the SNP-based GWAS meta-analysis of AUDIT total score (N = 141,932)
Genetic correlations between the three AUDIT phenotypes (total score, AUDIT-C, AUDIT-P) and several traits measured in independent cohorts as described in the Supplementary Tables 3β5: alcohol-related traits, tobacco and cannabis use, neuropsychiatric, personality, cognition, anthropomorphic and blood lipids. ADHD, attention-deο¬cit/hyper-activity disorder; BMI, body mass index; SE, standard error; IQ, intelligence quotient; HDL, high-density lipoprotein. * p < 0.05, ** p < 0.01, *** p < 0.0001; # AUDIT-P vs AUDIT-C, p < 0.01 FDR 5%, (#) AUDIT-P vs AUDIT-C, p < 0.05
Genetic correlations between AUDIT cases (8 [N = 25,423], 10 [N = 15,151], 12 [N = 9,130], 15 [N = 4,471], 18 [N = 2,099], 20 [N = 1,290]) vs controls (2, 3, 4) in the UK Biobank and DSM-IV derived alcohol dependence from the Psychiatric Genetics Consortium. The orange line is a visualization of the number of cases used at each threshold, corresponding to the N on the right hand y-axis.
β Prev
41β48 of 48
| Name | Type |
|---|---|
| 17q21.31 local | variant |
| 23andMe | cohort |
| 4q23 local | variant |
| ABO blood group antigens local | phenotype |
| ADH1B | gene |
| ADH1C | gene |
| ADH5 | gene |
| ADH6 | gene |
| ADHD | phenotype |
| age | phenotype |
| age at first use | phenotype |
| alcohol | phenotype |
| alcohol and substance use traits local | phenotype |
| alcohol dependence | phenotype |
| alcohol metabolism genes | gene |
| Alcohol Problems | phenotype |
| Alcohol related mortality local | phenotype |
| alcohol-related phenotypes | phenotype |
| Alcohol Use | phenotype |
| Alcohol Use Disorder | phenotype |
| Alcohol Use Disorder Identification Test local | phenotype |
| alcohol use disorders | phenotype |
| Alcohol Use Disorders Identification Test local | drug |
| ALDH2 | gene |
| ANNOVAR categories local | drug |
| anterior cingulate cortex | anatomy |
| AUD | phenotype |
| AUDIT | phenotype |
| AUDIT-C | phenotype |
| AUDIT-P | phenotype |
| binge drinking | phenotype |
| bipolar disorder | phenotype |
| blood lipids local | phenotype |
| Blood lipid traits local | phenotype |
| brain | anatomy |
| brain structure | anatomy |
| brain tissue | anatomy |
| CADD scores local | drug |
| Cadm2 | gene |
| cannabis use | phenotype |
| caudate nucleus | anatomy |
| cerebellum | anatomy |
| cerebral hemispheres | anatomy |
| chromatin states | drug |
| cigarettes | phenotype |
| cognitive ability | phenotype |
| college attainment local | phenotype |
| coronary heart disease | phenotype |
| cortex | anatomy |
| credible set SNPs local | variant |
| CRHR1 | gene |
| CRHR1-IT1 local | gene |
| Dependence symptoms | phenotype |
| depressive symptoms | phenotype |
| DRD2 | gene |
| DSM-IV alcohol dependence | phenotype |
| education | phenotype |
| educational attainment | phenotype |
| eQTLGen Consortium | cohort |
| Fgf21 | gene |
| FNBP4 local | gene |
| FUT2 | gene |
| GCKR | gene |
| GTEx v7 | cohort |
| GWAS meta-analysis of AUDIT total score local | cohort |
| Haplotype Reference Consortium | cohort |
| hazardous drinking | phenotype |
| HDL cholesterol local | other |
| HDL cholesterol | phenotype |
| heavy drinking | phenotype |
| hippocampus | anatomy |
| human alcoholics | phenotype |
| hypothalamus | anatomy |
| independent SNPs | cohort |
| index SNP | cohort |
| index SNP on 19q13.3 local | variant |
| JACD local | gene |
| JCAD | gene |
| Klb | gene |
| lifetime smoking | phenotype |
| LINC01833 local | gene |
| MAGMA | drug |
| major depressive disorder | phenotype |
| Mapt | gene |
| Mbarek et al. local | cohort |
| mood disorders | phenotype |
| neurodegenerative tauopathies local | phenotype |
| neuroticism | phenotype |
| nucleus accumbens | anatomy |
| obesity | phenotype |
| Parkinsonβs disease | phenotype |
| personality and behavioral traits local | phenotype |
| problematic alcohol use | phenotype |
| problematic use | phenotype |
| problem use | phenotype |
| Psychiatric co-morbidities local | phenotype |
| psychiatric disorders | phenotype |
| psychopathology | phenotype |
| putamen | anatomy |
| Regional brain volumes local | phenotype |
| RegulomeDB scores local | drug |
| RFC1 local | gene |
| RN7SL728P local | gene |
| rs11733695 local | variant |
| rs11940694 | variant |
| rs1229984 | variant |
| rs1260326 | variant |
| rs13107325 | variant |
| rs13135092 | variant |
| rs141973904 local | variant |
| rs146788033 local | variant |
| rs17651549 local | variant |
| rs2046330 local | variant |
| rs2293576 local | variant |
| rs3114045 local | variant |
| rs4975012 local | variant |
| rs601338 local | variant |
| schizophrenia | phenotype |
| sex | phenotype |
| SLC39A13 | gene |
| SLC39A8 | gene |
| SNP | cohort |
| SNX17 local | gene |
| socioeconomic status | phenotype |
| subcortical regions | anatomy |
| subjective well-being | phenotype |
| substance use phenotypes | phenotype |
| tobacco use | phenotype |
| triglycerides | phenotype |
| Triglycerides local | other |
| UKB | cohort |
| UKB cohort | cohort |
| UK Biobank | cohort |
| UKB White British local | cohort |
| UKB White British sample local | cohort |
| Variant Effect Predictor (VEP) local | drug |
| White British local | cohort |
| White British sample local | cohort |
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| Partitioning the Genomic Components of Behavioral Disinhibition and Substance Use (Disorder) Using Genomic Structural Equation Modeling. | Horwitz TB et al. | β | 2024 | β |
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| What Are the Genetic Building Blocks of Alcohol-Related Behaviors? | Gelernter J et al. | β | 2024 | β |
| What Risks Do Offspring of Parents With Alcohol Use Disorder Face? | Edenberg HJ | β | 2024 | β |
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| Assessing the associations between known genetic variants and substance use in people with HIV in the United States. | Haas CB et al. | β | 2023 | β |
| CADM2 is implicated in impulsive personality and numerous other traits by genome- and phenome-wide association studies in humans and mice. | Sanchez-Roige S et al. | β | 2023 | β |
| Comparative neurogenetics of dog behavior complements efforts towards human neuropsychiatric genetics. | Morrill K et al. | β | 2023 | β |
| Deconstructing the heterogeneity of alcohol use disorder: lifetime comorbid non-alcohol substance use disorder as a distinct behavioral phenotype? | Farmer RF et al. | β | 2023 | β |
| Differences in genetic correlations between posttraumatic stress disorder and alcohol-related problems phenotypes compared to alcohol consumption-related phenotypes. | Bountress KE et al. | β | 2023 | β |
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| Genetic Risk, Neighborhood Characteristics, and Behavioral Difficulties Among African American Adolescents Living in Very Low-Income Neighborhoods. | Sterrett-Hong EM et al. | β | 2023 | β |
| Genetic Underpinnings of the Transition From Alcohol Consumption to Alcohol Use Disorder: Shared and Unique Genetic Architectures in a Cross-Ancestry Sample. | Kember RL et al. | β | 2023 | β |
| Genome-wide association study of chronic sputum production implicates loci involved in mucus production and infection. | Packer RJ et al. | β | 2023 | β |
| Guidelines for Evaluating the Comparability of Down-Sampled GWAS Summary Statistics. | Williams CM et al. | β | 2023 | β |
| GWAS meta-analysis of 16 790 patients with Barrett's oesophagus and oesophageal adenocarcinoma identifies 16 novel genetic risk loci and provides insights into disease aetiology beyond the single marker level. | SchrΓΆder J et al. | β | 2023 | β |
| Identifying potential risk genes and pathways for neuropsychiatric and substance use disorders using intermediate molecular mediator information. | Gedik H et al. | β | 2023 | β |
| Initial Validation of a Behavioral Phenotyping Model for Substance Use Disorder. | Keyser-Marcus L et al. | β | 2023 | β |
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| Investigation of convergent and divergent genetic influences underlying schizophrenia and alcohol use disorder. | Johnson EC et al. | β | 2023 | β |
| Large registry-based analysis of genetic predisposition to tuberculosis identifies genetic risk factors at HLA. | Tervi A et al. | β | 2023 | β |
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| Multi-ancestry study of the genetics of problematic alcohol use in over 1 million individuals. | Zhou H et al. | β | 2023 | β |
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| Ocular and neural genes jointly regulate the visuospatial working memory in ADHD children. | Zhao Y et al. | β | 2023 | β |
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| Polygenic risk score for problematic alcohol use predicts heavy drinking and alcohol use disorder symptoms in young adulthood after accounting for adolescent alcohol use and parental alcohol use disorder. | Wang FL et al. | β | 2023 | β |
| Polygenic scores for psychiatric disorders in a diverse postmortem brain tissue cohort. | Duncan L et al. | β | 2023 | β |
| Prioritizing genes associated with brain disorders by leveraging enhancer-promoter interactions in diverse neural cells and tissues. | Zhao X et al. | β | 2023 | β |
| PRSet: Pathway-based polygenic risk score analyses and software. | Choi SW et al. | β | 2023 | β |
| Psychoactive substance use in patients diagnosed with attention-deficit/hyperactivity disorder: an exploratory study. | WiΔckiewicz G et al. | β | 2023 | β |
| Regulating Direct-to-Consumer Polygenic Risk Scores. | Sherkow JS et al. | β | 2023 | β |
| Risk Factors for Binge Drinking in Young Adulthood: The Roles of Aggregate Genetic Liability and Impulsivity-Related Processes. | Lannoy S et al. | β | 2023 | β |
| RNA alternative splicing impacts the risk for alcohol use disorder. | Li R et al. | β | 2023 | β |
| Scalable mixed model methods for set-based association studies on large-scale categorical data analysis and its application to exome-sequencing data in UK Biobank. | Bi W et al. | β | 2023 | β |
| Serum uric acid and risk of diabetic neuropathy: a genetic correlation and mendelian randomization study. | Zhang Y et al. | β | 2023 | β |
| Sleep Health at the Genomic Level: Six Distinct Factors and Their Relationships With Psychopathology. | Morrison CL et al. | β | 2023 | β |
| The effect of antioxidant dietary supplements and diet-derived circulating antioxidants on vitiligo outcome: evidence from genetic association and comprehensive Mendelian randomization. | Ni Y et al. | β | 2023 | β |
| The evolution of Big Data in neuroscience and neurology. | Dipietro L et al. | β | 2023 | β |
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| The role of nicotinic receptors in alcohol consumption. | Kamens HM et al. | β | 2023 | β |
| Transcriptional signatures of heroin intake and relapse throughout the brain reward circuitry in male mice. | Browne CJ et al. | β | 2023 | β |
| Unraveling shared susceptibility loci and Mendelian genetic associations linking educational attainment with multiple neuropsychiatric disorders. | Chen D et al. | β | 2023 | β |
| A Genome-Wide Association Study Reveals a <i>BDNF</i>-Centered Molecular Network Associated with Alcohol Dependence and Related Clinical Measures. | Levchenko A et al. | β | 2022 | β |
| Alcohol and nicotine polygenic scores are associated with the development of alcohol and nicotine use problems from adolescence to young adulthood. | Deak JD et al. | β | 2022 | β |
| Alcohol use and alcohol use disorder differ in their genetic relationships with PTSD: A genomic structural equation modelling approach. | Bountress KE et al. | β | 2022 | β |
| Alcohol Use and Use Disorder and Cancer Risk: Perspective on Causal Inference. | Zhou H et al. | β | 2022 | β |
| Alcohol use disorder, psychiatric comorbidities, marriage and divorce in a high-risk sample. | Thomas NS et al. | β | 2022 | β |
| Association of Alcohol Use Disorder Risk With <i>ADH1B, DRD2, FAAH, SLC39A8, GCKR</i>, and <i>PDYN</i> Genetic Polymorphisms. | Legaki E et al. | β | 2022 | β |
| Associations between cognition and polygenic liability to substance involvement in middle childhood: Results from the ABCD study. | Paul SE et al. | β | 2022 | β |
| A Systematic Review of Genetic Polymorphisms Associated with Bipolar Disorder Comorbid to Substance Abuse. | de Marco A et al. | β | 2022 | β |
| Back-translating GWAS findings to animal models reveals a role for Hgfac and Slc39a8 in alcohol and nicotine consumption. | Banna FKE et al. | β | 2022 | β |
| Binge and high-intensity drinking-Associations with intravenous alcohol self-administration and underlying risk factors. | Plawecki MH et al. | β | 2022 | β |
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| Context-dependant enhancers as a reservoir of functional polymorphisms and epigenetic markers linked to alcohol use disorders and comorbidities. | MacKenzie A et al. | β | 2022 | β |
| Diverse functions associate with non-coding polymorphisms shared between humans and chimpanzees. | Velazquez-Arcelay K et al. | β | 2022 | β |
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| Genes regulating levels of Ο-3 long-chain polyunsaturated fatty acids are associated with alcohol use disorder and consumption, and broader externalizing behavior in humans. | Aliev F et al. | β | 2022 | β |
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| Genome-wide association mapping of ethanol sensitivity in the Diversity Outbred mouse population. | Parker CC et al. | β | 2022 | β |
| Genome-wide imputed differential expression enrichment analysis identifies trait-relevant tissues. | Ghaffar A et al. | β | 2022 | β |
| Genome-Wide Investigation of Maximum Habitual Alcohol Intake in US Veterans in Relation to Alcohol Consumption Traits and Alcohol Use Disorder. | Deak JD et al. | β | 2022 | β |
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| Identifying the Common Genetic Basis of Antidepressant Response. | Pain O et al. | β | 2022 | β |
| Item-Level Genome-Wide Association Study of the Alcohol Use Disorders Identification Test in Three Population-Based Cohorts. | Mallard TT et al. | β | 2022 | β |
| Longitudinal associations between impulsivity and alcohol and cannabis use frequency, quantity, and problems among military veterans. | Kearns NT et al. | β | 2022 | β |
| Multivariate GWAS of psychiatric disorders and their cardinal symptoms reveal two dimensions of cross-cutting genetic liabilities. | Mallard TT et al. | β | 2022 | β |
| Neurosteroids (allopregnanolone) and alcohol use disorder: From mechanisms to potential pharmacotherapy. | Gatta E et al. | β | 2022 | β |
| Pairwise genetic meta-analyses between schizophrenia and substance dependence phenotypes reveals novel association signals with pharmacological significance. | Greco LA et al. | β | 2022 | β |
| Parsing genetically influenced risk pathways: genetic loci impact problematic alcohol use via externalizing and specific risk. | Barr PB et al. | β | 2022 | β |
| Predicting Alcohol Use From Genome-Wide Polygenic Scores, Environmental Factors, and Their Interactions in Young Adulthood. | Kandaswamy R et al. | β | 2022 | β |
| Principal Component Analysis Reduces Collider Bias in Polygenic Score Effect Size Estimation. | Thomas NS et al. | β | 2022 | β |
| Sex-heterogeneous SNPs disproportionately influence gene expression and health. | Traglia M et al. | β | 2022 | β |
| Shared genetic links between frontotemporal dementia and psychiatric disorders. | Li C et al. | β | 2022 | β |
| Shared Genetics and Causality Between Decaffeinated Coffee Consumption and Neuropsychiatric Diseases: A Large-Scale Genome-Wide Cross-Trait Analysis and Mendelian Randomization Analysis. | Yin B et al. | β | 2022 | β |
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| Structural differences in adolescent brains can predict alcohol misuse. | Rane RP et al. | β | 2022 | β |
| Substance abuse and the risk of severe COVID-19: Mendelian randomization confirms the causal role of opioids but hints a negative causal effect for cannabinoids. | Jabalameli MR et al. | β | 2022 | β |
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| Ten challenges for clinical translation in psychiatric genetics. | Derks EM et al. | β | 2022 | β |
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| The dopamine transporter gene SLC6A3: multidisease risks. | Reith MEA et al. | β | 2022 | β |
| The proarrhythmic conundrum of alcohol intake. | Manolis TA et al. | β | 2022 | β |
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| A comprehensive gene-centric pleiotropic association analysis for 14 psychiatric disorders with GWAS summary statistics. | Lu H et al. | β | 2021 | β |
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| Alcohol Consumption Is Associated with Poor Prognosis in Obese Patients with COVID-19: A Mendelian Randomization Study Using UK Biobank. | Fan X et al. | β | 2021 | β |
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| Causal Associations Between Modifiable Risk Factors and the Alzheimer's Phenome. | Andrews SJ et al. | β | 2021 | β |
| Chronic Alcohol Use Induces Molecular Genetic Changes in the Dorsomedial Thalamus of People with Alcohol-Related Disorders. | Hade AC et al. | β | 2021 | β |
| Common genetic variation influencing human white matter microstructure. | Zhao B et al. | β | 2021 | β |
| CRISPR disruption and UK Biobank analysis of a highly conserved polymorphic enhancer suggests a role in male anxiety and ethanol intake. | McEwan AR et al. | β | 2021 | β |
| Differential expression and transcription factor binding associated with genotype at a pharmacogenetic variant in <i>OPRD1</i>. | Crist RC et al. | β | 2021 | β |
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| Educational attainment impacts drinking behaviors and risk for alcohol dependence: results from a two-sample Mendelian randomization study with ~780,000 participants. | Rosoff DB et al. | β | 2021 | β |
| Functional and clinical implications of genetic structure in 1686 Italian exomes. | Birolo G et al. | β | 2021 | β |
| Functional validation of a finding from a mouse genome-wide association study shows that Azi2 influences the acute locomotor stimulant response to methamphetamine. | Zhou X et al. | β | 2021 | β |
| Genes identified in rodent studies of alcohol intake are enriched for heritability of human substance use. | Huggett SB et al. | β | 2021 | β |
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| Genetic and shared couple environmental contributions to smoking and alcohol use in the UK population. | Clarke TK et al. | β | 2021 | β |
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| Genome-wide analyses of behavioural traits are subject to bias by misreports and longitudinal changes. | Xue A et al. | β | 2021 | β |
| Genome-Wide Association Studies of Schizophrenia and Bipolar Disorder in a Diverse Cohort of US Veterans. | Bigdeli TB et al. | β | 2021 | β |
| Gut Microbiota and Psychiatric Disorders: A Two-Sample Mendelian Randomization Study. | Ni JJ et al. | β | 2021 | β |
| Integration of evidence across human and model organism studies: A meeting report. | Palmer RHC et al. | β | 2021 | β |
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| Investigating causality between liability to ADHD and substance use, and liability to substance use and ADHD risk, using Mendelian randomization. | Treur JL et al. | β | 2021 | β |
| Large-scale GWAS reveals genetic architecture of brain white matter microstructure and genetic overlap with cognitive and mental health traits (nβ=β17,706). | Zhao B et al. | β | 2021 | β |
| Long tracks of homozygosity predict the severity of alcohol use disorders in an American Indian population. | Peng Q et al. | β | 2021 | β |
| Looking for Sunshine: Genetic Predisposition to Sun Seeking in 265,000 Individuals of European Ancestry. | Sanna M et al. | β | 2021 | β |
| Mediational Pathways From Genetic Risk to Alcohol Use Disorder in Swedish Men and Women. | Kendler KS et al. | β | 2021 | β |
| Multi-Polygenic Analysis of Nicotine Dependence in Individuals of European Ancestry. | Risner VA et al. | β | 2021 | β |
| Multivariate analysis of 1.5 million people identifies genetic associations with traits related to self-regulation and addiction. | Karlsson LinnΓ©r R et al. | β | 2021 | β |
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| Polygenic risk scores for alcohol involvement relate to brain structure in substance-naΓ―ve children: Results from the ABCD study. | Hatoum AS et al. | β | 2021 | β |
| Potential causal effect of posttraumatic stress disorder on alcohol use disorder and alcohol consumption in individuals of European descent: A Mendelian Randomization Study. | Bountress KE et al. | β | 2021 | β |
| Prospective randomized pharmacogenetic study of topiramate for treating alcohol use disorder. | Kranzler HR et al. | β | 2021 | β |
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| The Aldehyde Dehydrogenase ALDH2*2 Allele, Associated with Alcohol Drinking Behavior, Dates Back to Prehistoric Times. | Lin CL et al. | β | 2021 | β |
| The Cocaine and Oxycodone Biobanks, Two Repositories from Genetically Diverse and Behaviorally Characterized Rats for the Study of Addiction. | Carrette LLG et al. | β | 2021 | β |
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| The Nuanced Metabolic Functions of Endogenous FGF21 Depend on the Nature of the Stimulus, Tissue Source, and Experimental Model. | Spann RA et al. | β | 2021 | β |
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| Differentiating Types of Self-Reported Alcohol Abstinence. | Gordon KS et al. | β | 2020 | β |
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| Epigenetic changes on rat chromosome 4 contribute to disparate alcohol drinking behavior in alcohol-preferring and -nonpreferring rats. | Spence JP et al. | β | 2020 | β |
| Epistatic evidence for gender-dependant slow neurotransmission signalling in substance use disorders: PPP1R12B versus PPP1R1B. | Liu K et al. | β | 2020 | β |
| FGF21 and the Physiological Regulation of Macronutrient Preference. | Hill CM et al. | β | 2020 | β |
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| Leveraging genome-wide data to investigate differences between opioid use vs. opioid dependence in 41,176 individuals from the Psychiatric Genomics Consortium. | Polimanti R et al. | β | 2020 | β |
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| Alcohol use disorders. | Carvalho AF et al. | β | 2019 | β |
| Assessment of the Association of D2 Dopamine Receptor Gene and Reported Allele Frequencies With Alcohol Use Disorders: A Systematic Review and Meta-analysis. | Jung Y et al. | β | 2019 | β |
| Association of Polygenic Liability for Alcohol Dependence and EEG Connectivity in Adolescence and Young Adulthood. | Meyers JL et al. | β | 2019 | β |
| Cross-species alcohol dependence-associated gene networks: Co-analysis of mouse brain gene expression and human genome-wide association data. | Mignogna KM et al. | β | 2019 | β |
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| Genome-Wide Association Studies of Impulsive Personality Traits (BIS-11 and UPPS-P) and Drug Experimentation in up to 22,861 Adult Research Participants Identify Loci in the <i>CACNA1I</i> and <i>CADM2</i> genes. | Sanchez-Roige S et al. | β | 2019 | β |
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