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Zhou H, Gelernter J. Human genetics and epigenetics of alcohol use disorder. J Clin Invest 2024; 134:e172885. [PMID: 39145449 DOI: 10.1172/jci172885] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/16/2024] Open
Abstract
Alcohol use disorder (AUD) is a prominent contributor to global morbidity and mortality. Its complex etiology involves genetics, epigenetics, and environmental factors. We review progress in understanding the genetics and epigenetics of AUD, summarizing the key findings. Advancements in technology over the decades have elevated research from early candidate gene studies to present-day genome-wide scans, unveiling numerous genetic and epigenetic risk factors for AUD. The latest GWAS on more than one million participants identified more than 100 genetic variants, and the largest epigenome-wide association studies (EWAS) in blood and brain samples have revealed tissue-specific epigenetic changes. Downstream analyses revealed enriched pathways, genetic correlations with other traits, transcriptome-wide association in brain tissues, and drug-gene interactions for AUD. We also discuss limitations and future directions, including increasing the power of GWAS and EWAS studies as well as expanding the diversity of populations included in these analyses. Larger samples, novel technologies, and analytic approaches are essential; these include whole-genome sequencing, multiomics, single-cell sequencing, spatial transcriptomics, deep-learning prediction of variant function, and integrated methods for disease risk prediction.
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Affiliation(s)
- Hang Zhou
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut, USA
- Department of Biomedical Informatics and Data Science
- Center for Brain and Mind Health
| | - Joel Gelernter
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut, USA
- Department of Genetics, and
- Department of Neuroscience, Yale School of Medicine, New Haven, Connecticut, USA
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2
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Trang KB, Chesi A, Toikumo S, Pippin JA, Pahl MC, O’Brien JM, Amundadottir LT, Brown KM, Yang W, Welles J, Santoleri D, Titchenell PM, Seale P, Zemel BS, Wagley Y, Hankenson KD, Kaestner KH, Anderson SA, Kayser MS, Wells AD, Kranzler HR, Kember RL, Grant SF. Shared and unique 3D genomic features of substance use disorders across multiple cell types. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.07.18.24310649. [PMID: 39072016 PMCID: PMC11275669 DOI: 10.1101/2024.07.18.24310649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/30/2024]
Abstract
Recent genome-wide association studies (GWAS) have revealed shared genetic components among alcohol, opioid, tobacco and cannabis use disorders. However, the extent of the underlying shared causal variants and effector genes, along with their cellular context, remain unclear. We leveraged our existing 3D genomic datasets comprising high-resolution promoter-focused Capture-C/Hi-C, ATAC-seq and RNA-seq across >50 diverse human cell types to focus on genomic regions that coincide with GWAS loci. Using stratified LD regression, we determined the proportion of genomewide SNP heritability attributable to the features assayed across our cell types by integrating recent GWAS summary statistics for the relevant traits: alcohol use disorder (AUD), tobacco use disorder (TUD), opioid use disorder (OUD) and cannabis use disorder (CanUD). Statistically significant enrichments (P<0.05) were observed in 14 specific cell types, with heritability reaching 9.2-fold for iPSC-derived cortical neurons and neural progenitors, confirming that they are crucial cell types for further functional exploration. Additionally, several pancreatic cell types, notably pancreatic beta cells, showed enrichment for TUD, with heritability enrichments up to 4.8-fold, suggesting genomic overlap with metabolic processes. Further investigation revealed significant positive genetic correlations between T2D with both TUD and CanUD (FDR<0.05) and a significant negative genetic correlation with AUD. Interestingly, after partitioning the heritability for each cell type's cis-regulatory elements, the correlation between T2D and TUD for pancreatic beta cells was greater (r=0.2) than the global genetic correlation value. Our study provides new genomic insights into substance use disorders and implicates cell types where functional follow-up studies could reveal causal variant-gene mechanisms underpinning these disorders.
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Affiliation(s)
- Khanh B. Trang
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Alessandra Chesi
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Sylvanus Toikumo
- Mental Illness Research, Education and Clinical Center, Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - James A. Pippin
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Matthew C. Pahl
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Joan M. O’Brien
- Scheie Eye Institute, Department of Ophthalmology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, PA, USA
- Penn Medicine Center for Ophthalmic Genetics in Complex Disease, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, PA, USA
| | - Laufey T. Amundadottir
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Kevin M. Brown
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Wenli Yang
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jaclyn Welles
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Physiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Dominic Santoleri
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Physiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Paul M. Titchenell
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Physiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Patrick Seale
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Babette S. Zemel
- Division of Gastroenterology, Hepatology, and Nutrition, Children’s Hospital of Philadelphia, PA, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Yadav Wagley
- Department of Orthopedic Surgery, University of Michigan Medical School Ann Arbor, MI, USA
| | - Kurt D. Hankenson
- Department of Orthopedic Surgery, University of Michigan Medical School Ann Arbor, MI, USA
| | - Klaus H. Kaestner
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Stewart A. Anderson
- Department of Child and Adolescent Psychiatry, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Matthew S. Kayser
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Chronobiology Sleep Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Andrew D. Wells
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Institute for Immunology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Henry R. Kranzler
- Mental Illness Research, Education and Clinical Center, Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Rachel L. Kember
- Mental Illness Research, Education and Clinical Center, Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Struan F.A. Grant
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Division of Endocrinology and Diabetes, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
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Toikumo S, Jennings MV, Pham BK, Lee H, Mallard TT, Bianchi SB, Meredith JJ, Vilar-Ribó L, Xu H, Hatoum AS, Johnson EC, Pazdernik VK, Jinwala Z, Pakala SR, Leger BS, Niarchou M, Ehinmowo M, Jenkins GD, Batzler A, Pendegraft R, Palmer AA, Zhou H, Biernacka JM, Coombes BJ, Gelernter J, Xu K, Hancock DB, Cox NJ, Smoller JW, Davis LK, Justice AC, Kranzler HR, Kember RL, Sanchez-Roige S. Multi-ancestry meta-analysis of tobacco use disorder identifies 461 potential risk genes and reveals associations with multiple health outcomes. Nat Hum Behav 2024; 8:1177-1193. [PMID: 38632388 PMCID: PMC11199106 DOI: 10.1038/s41562-024-01851-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 02/21/2024] [Indexed: 04/19/2024]
Abstract
Tobacco use disorder (TUD) is the most prevalent substance use disorder in the world. Genetic factors influence smoking behaviours and although strides have been made using genome-wide association studies to identify risk variants, most variants identified have been for nicotine consumption, rather than TUD. Here we leveraged four US biobanks to perform a multi-ancestral meta-analysis of TUD (derived via electronic health records) in 653,790 individuals (495,005 European, 114,420 African American and 44,365 Latin American) and data from UK Biobank (ncombined = 898,680). We identified 88 independent risk loci; integration with functional genomic tools uncovered 461 potential risk genes, primarily expressed in the brain. TUD was genetically correlated with smoking and psychiatric traits from traditionally ascertained cohorts, externalizing behaviours in children and hundreds of medical outcomes, including HIV infection, heart disease and pain. This work furthers our biological understanding of TUD and establishes electronic health records as a source of phenotypic information for studying the genetics of TUD.
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Affiliation(s)
- Sylvanus Toikumo
- Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Mariela V Jennings
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Benjamin K Pham
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Hyunjoon Lee
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Travis T Mallard
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Center for Precision Psychiatry, Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, MA, USA
| | - Sevim B Bianchi
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - John J Meredith
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Laura Vilar-Ribó
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Heng Xu
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Alexander S Hatoum
- Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Emma C Johnson
- Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | | | - Zeal Jinwala
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Shreya R Pakala
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Brittany S Leger
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Program in Biomedical Sciences, University of California San Diego, La Jolla, CA, USA
| | - Maria Niarchou
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University, Nashville, TN, USA
| | | | - Greg D Jenkins
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Anthony Batzler
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Richard Pendegraft
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Hang Zhou
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Joanna M Biernacka
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - Brandon J Coombes
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Joel Gelernter
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Ke Xu
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | | | - Nancy J Cox
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jordan W Smoller
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Center for Precision Psychiatry, Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, MA, USA
| | - Lea K Davis
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University, Nashville, TN, USA
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Amy C Justice
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
- Yale University School of Public Health, New Haven, CT, USA
- Yale University School of Medicine, New Haven, CT, USA
| | - Henry R Kranzler
- Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Rachel L Kember
- Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Sandra Sanchez-Roige
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA.
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University, Nashville, TN, USA.
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA.
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Jennings MV, Martínez-Magaña JJ, Courchesne-Krak NS, Cupertino RB, Vilar-Ribó L, Bianchi SB, Hatoum AS, Atkinson EG, Giusti-Rodriguez P, Montalvo-Ortiz JL, Gelernter J, Artigas MS, Elson SL, Edenberg HJ, Fontanillas P, Palmer AA, Sanchez-Roige S. A phenome-wide association and Mendelian randomisation study of alcohol use variants in a diverse cohort comprising over 3 million individuals. EBioMedicine 2024; 103:105086. [PMID: 38580523 PMCID: PMC11121167 DOI: 10.1016/j.ebiom.2024.105086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 03/01/2024] [Accepted: 03/11/2024] [Indexed: 04/07/2024] Open
Abstract
BACKGROUND Alcohol consumption is associated with numerous negative social and health outcomes. These associations may be direct consequences of drinking, or they may reflect common genetic factors that influence both alcohol consumption and other outcomes. METHODS We performed exploratory phenome-wide association studies (PheWAS) of three of the best studied protective single nucleotide polymorphisms (SNPs) in genes encoding ethanol metabolising enzymes (ADH1B: rs1229984-T, rs2066702-A; ADH1C: rs698-T) using up to 1109 health outcomes across 28 phenotypic categories (e.g., substance-use, mental health, sleep, immune, cardiovascular, metabolic) from a diverse 23andMe cohort, including European (N ≤ 2,619,939), Latin American (N ≤ 446,646) and African American (N ≤ 146,776) populations to uncover new and perhaps unexpected associations. These SNPs have been consistently implicated by both candidate gene studies and genome-wide association studies of alcohol-related behaviours but have not been investigated in detail for other relevant phenotypes in a hypothesis-free approach in such a large cohort of multiple ancestries. To provide insight into potential causal effects of alcohol consumption on the outcomes significant in the PheWAS, we performed univariable two-sample and one-sample Mendelian randomisation (MR) analyses. FINDINGS The minor allele rs1229984-T, which is protective against alcohol behaviours, showed the highest number of PheWAS associations across the three cohorts (N = 232, European; N = 29, Latin American; N = 7, African American). rs1229984-T influenced multiple domains of health. We replicated associations with alcohol-related behaviours, mental and sleep conditions, and cardio-metabolic health. We also found associations with understudied traits related to neurological (migraines, epilepsy), immune (allergies), musculoskeletal (fibromyalgia), and reproductive health (preeclampsia). MR analyses identified evidence of causal effects of alcohol consumption on liability for 35 of these outcomes in the European cohort. INTERPRETATION Our work demonstrates that polymorphisms in genes encoding alcohol metabolising enzymes affect multiple domains of health beyond alcohol-related behaviours. Understanding the underlying mechanisms of these effects could have implications for treatments and preventative medicine. FUNDING MVJ, NCK, SBB, SSR and AAP were supported by T32IR5226 and 28IR-0070. SSR was also supported by NIDA DP1DA054394. NCK and RBC were also supported by R25MH081482. ASH was supported by funds from NIAAA K01AA030083. JLMO was supported by VA 1IK2CX002095. JLMO and JJMM were also supported by NIDA R21DA050160. JJMM was also supported by the Kavli Postdoctoral Award for Academic Diversity. EGA was supported by K01MH121659 from the NIMH/NIH, the Caroline Wiess Law Fund for Research in Molecular Medicine and the ARCO Foundation Young Teacher-Investigator Fund at Baylor College of Medicine. MSA was supported by the Instituto de Salud Carlos III and co-funded by the European Union Found: Fondo Social Europeo Plus (FSE+) (P19/01224, PI22/00464 and CP22/00128).
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Affiliation(s)
- Mariela V Jennings
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - José Jaime Martínez-Magaña
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, Orange, West Haven, CT, USA
| | | | - Renata B Cupertino
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Laura Vilar-Ribó
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain; Department of Mental Health, Hospital Universitari Vall d'Hebron, Barcelona, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Madrid, Spain
| | - Sevim B Bianchi
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Alexander S Hatoum
- Department of Psychology & Brain Sciences, Washington University in St. Louis, St Louis, MO, USA
| | - Elizabeth G Atkinson
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Paola Giusti-Rodriguez
- Department of Psychiatry, University of Florida College of Medicine, Gainesville, FL, USA
| | - Janitza L Montalvo-Ortiz
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, Orange, West Haven, CT, USA; National Center of Posttraumatic Stress Disorder, VA CT Healthcare Center, West Haven, CT, USA
| | - Joel Gelernter
- VA CT Healthcare Center, Department Psychiatry, West Haven, CT, USA; Departments Psychiatry, Genetics, and Neuroscience, Yale Univ. School of Medicine, New Haven, CT, USA
| | - María Soler Artigas
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain; Department of Mental Health, Hospital Universitari Vall d'Hebron, Barcelona, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Madrid, Spain; Department of Genetics, Microbiology, and Statistics, Faculty of Biology, Universitat de Barcelona, Barcelona, Spain
| | | | - Howard J Edenberg
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, USA
| | | | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Sandra Sanchez-Roige
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA; Division of Genetic Medicine, Department of Medicine, Vanderbilt University, Nashville, TN, USA.
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Popova D, Sun J, Chow HM, Hart RP. A critical review of ethanol effects on neuronal firing: A metabolic perspective. ALCOHOL, CLINICAL & EXPERIMENTAL RESEARCH 2024; 48:450-458. [PMID: 38217065 DOI: 10.1111/acer.15266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 12/22/2023] [Accepted: 01/02/2024] [Indexed: 01/14/2024]
Abstract
Ethanol metabolism is relatively understudied in neurons, even though changes in neuronal metabolism are known to affect their activity. Recent work demonstrates that ethanol is preferentially metabolized over glucose as a source of carbon and energy, and it reprograms neurons to a state of reduced energy potential and diminished capacity to utilize glucose once ethanol is exhausted. Ethanol intake has been associated with changes in neuronal firing and specific brain activity (EEG) patterns have been linked with risk for alcohol use disorder (AUD). Furthermore, a haplotype of the inwardly rectifying potassium channel subunit, GIRK2, which plays a critical role in regulating excitability of neurons, has been linked with AUD and shown to be directly regulated by ethanol. At the same time, overexpression of GIRK2 prevents ethanol-induced metabolic changes. Based on the available evidence, we conclude that the mechanisms underlying the effects of ethanol on neuronal metabolism are a novel target for developing therapies for AUD.
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Affiliation(s)
- Dina Popova
- Department of Cell Biology and Neuroscience, Rutgers University, Piscataway, New Jersey, USA
| | - Jacquelyne Sun
- School of Life Sciences, Faculty of Science, The Chinese University of Hong Kong, Hong Kong, Hong Kong
| | - Hei-Man Chow
- School of Life Sciences, Faculty of Science, The Chinese University of Hong Kong, Hong Kong, Hong Kong
- Gerald Choa Neuroscience Institute, The Chinese University of Hong Kong, Hong Kong, Hong Kong
| | - Ronald P Hart
- Department of Cell Biology and Neuroscience, Rutgers University, Piscataway, New Jersey, USA
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6
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Deng WQ, Belisario K, Gray JC, Levitt EE, MacKillop J. A high-resolution PheWAS approach to alcohol-related polygenic risk scores reveals mechanistic influences of alcohol reinforcing value and drinking motives. Alcohol Alcohol 2024; 59:agad093. [PMID: 38261344 DOI: 10.1093/alcalc/agad093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 11/08/2023] [Accepted: 12/16/2023] [Indexed: 01/24/2024] Open
Abstract
AIMS This study uses a high-resolution phenome-wide approach to evaluate the motivational mechanisms of polygenic risk scores (PRSs) that have been robustly associated with coarse alcohol phenotypes in large-scale studies. METHODS In a community-based sample of 1534 Europeans, we examined genome-wide PRSs for the Alcohol Use Disorders Identification Test (AUDIT), drinks per week, alcohol use disorder (AUD), problematic alcohol use (PAU), and general addiction, in relation to 42 curated phenotypes. The curated phenotypes were in seven categories: alcohol consumption, alcohol reinforcing value, drinking motives, other addictive behaviors, commonly comorbid psychiatric syndromes, impulsivity, and personality traits. RESULTS The PRS for each alcohol phenotype was validated via its within-sample association with the corresponding phenotype (adjusted R2s = 0.35-1.68%, Ps = 0.012-3.6 × 10-7) with the exception of AUD. All PRSs were positively associated with alcohol reinforcing value and drinking motives, with the strongest effects from AUDIT-consumption (adjusted R2s = 0.45-1.33%, Ps = 0.006-3.6 × 10-5) and drinks per week PRSs (adjusted R2s = 0.52-2.28%, Ps = 0.004-6.6 × 10-9). Furthermore, the PAU and drinks per week PRSs were positively associated with adverse childhood experiences (adjusted R2s = 0.6-0.7%, Ps = 0.0001-4.8 × 10-4). CONCLUSIONS These results implicate alcohol reinforcing value and drinking motives as genetically-influenced mechanisms using PRSs for the first time. The findings also highlight the value of dissecting genetic influence on alcohol involvement through diverse phenotypic risk pathways but also the need for future studies with both phenotypic richness and larger samples.
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Affiliation(s)
- Wei Q Deng
- Peter Boris Centre for Addictions Research, St. Joseph's Healthcare Hamilton, Hamilton, Ontario L8N 3K7, Canada
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario L8N 3K7, Canada
| | - Kyla Belisario
- Peter Boris Centre for Addictions Research, St. Joseph's Healthcare Hamilton, Hamilton, Ontario L8N 3K7, Canada
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario L8N 3K7, Canada
| | - Joshua C Gray
- Department of Medical and Clinical Psychology, Uniformed Services University, Bethesda, MD 20814, United States
| | - Emily E Levitt
- Peter Boris Centre for Addictions Research, St. Joseph's Healthcare Hamilton, Hamilton, Ontario L8N 3K7, Canada
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario L8N 3K7, Canada
| | - James MacKillop
- Peter Boris Centre for Addictions Research, St. Joseph's Healthcare Hamilton, Hamilton, Ontario L8N 3K7, Canada
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario L8N 3K7, Canada
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7
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Koellinger PD, Okbay A, Kweon H, Schweinert A, Linnér RK, Goebel J, Richter D, Reiber L, Zweck BM, Belsky DW, Biroli P, Mata R, Tucker-Drob EM, Harden KP, Wagner G, Hertwig R. Cohort profile: Genetic data in the German Socio-Economic Panel Innovation Sample (SOEP-G). PLoS One 2023; 18:e0294896. [PMID: 38019829 PMCID: PMC10686514 DOI: 10.1371/journal.pone.0294896] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Accepted: 11/12/2023] [Indexed: 12/01/2023] Open
Abstract
The German Socio-Economic Panel (SOEP) serves a global research community by providing representative annual longitudinal data of respondents living in private households in Germany. The dataset offers a valuable life course panorama, encompassing living conditions, socioeconomic status, familial connections, personality traits, values, preferences, health, and well-being. To amplify research opportunities further, we have extended the SOEP Innovation Sample (SOEP-IS) by collecting genetic data from 2,598 participants, yielding the first genotyped dataset for Germany based on a representative population sample (SOEP-G). The sample includes 107 full-sibling pairs, 501 parent-offspring pairs, and 152 triads, which overlap with the parent-offspring pairs. Leveraging the results from well-powered genome-wide association studies, we created a repository comprising 66 polygenic indices (PGIs) in the SOEP-G sample. We show that the PGIs for height, BMI, and educational attainment capture 22∼24%, 12∼13%, and 9% of the variance in the respective phenotypes. Using the PGIs for height and BMI, we demonstrate that the considerable increase in average height and the decrease in average BMI in more recent birth cohorts cannot be attributed to genetic shifts within the German population or to age effects alone. These findings suggest an important role of improved environmental conditions in driving these changes. Furthermore, we show that higher values in the PGIs for educational attainment and the highest math class are associated with better self-rated health, illustrating complex relationships between genetics, cognition, behavior, socio-economic status, and health. In summary, the SOEP-G data and the PGI repository we created provide a valuable resource for studying individual differences, inequalities, life-course development, health, and interactions between genetic predispositions and the environment.
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Affiliation(s)
- Philipp D. Koellinger
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Aysu Okbay
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Hyeokmoon Kweon
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Annemarie Schweinert
- Department of Economics, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Richard Karlsson Linnér
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Department of Economics, Leiden Law School, Leiden University, Leiden, The Netherlands
| | - Jan Goebel
- German Socio-Economic Panel Study, Deutsches Institut für Wirtschaftsforschung (DIW Berlin), Berlin, Germany
| | - David Richter
- Educational Science and Psychology, Freie Universität Berlin, Berlin, Germany
- SHARE Berlin, Berlin, Germany
| | - Lisa Reiber
- Center for Adaptive Rationality, Max-Planck Institute for Human Development, Berlin, Germany
| | | | - Daniel W. Belsky
- Department of Epidemiology and Butler Columbia Aging Center, Mailman School of Public Health, Columbia University, New York, New York, United States of America
- PROMENTA Center, University of Oslo, Oslo, Norway
| | - Pietro Biroli
- Department of Economics, University of Bologna, Bologna, Italy
| | - Rui Mata
- Center for Adaptive Rationality, Max-Planck Institute for Human Development, Berlin, Germany
- Faculty of Psychology, University of Basel, Basel, Switzerland
| | - Elliot M. Tucker-Drob
- Department of Psychology and Population Research Center, University of Texas at Austin, Austin, Texas, United States of America
| | - K. Paige Harden
- Department of Psychology and Population Research Center, University of Texas at Austin, Austin, Texas, United States of America
| | - Gert Wagner
- Educational Science and Psychology, Freie Universität Berlin, Berlin, Germany
- Center for Adaptive Rationality, Max-Planck Institute for Human Development, Berlin, Germany
- Federal Institute for Population Research, Wiesbaden, Germany
| | - Ralph Hertwig
- Center for Adaptive Rationality, Max-Planck Institute for Human Development, Berlin, Germany
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8
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Toikumo S, Jennings MV, Pham BK, Lee H, Mallard TT, Bianchi SB, Meredith JJ, Vilar-Ribó L, Xu H, Hatoum AS, Johnson EC, Pazdernik V, Jinwala Z, Pakala SR, Leger BS, Niarchou M, Ehinmowo M, Jenkins GD, Batzler A, Pendegraft R, Palmer AA, Zhou H, Biernacka JM, Coombes BJ, Gelernter J, Xu K, Hancock DB, Cox NJ, Smoller JW, Davis LK, Justice AC, Kranzler HR, Kember RL, Sanchez-Roige S. Multi-ancestry meta-analysis of tobacco use disorder prioritizes novel candidate risk genes and reveals associations with numerous health outcomes. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.03.27.23287713. [PMID: 37034728 PMCID: PMC10081388 DOI: 10.1101/2023.03.27.23287713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/29/2023]
Abstract
Tobacco use disorder (TUD) is the most prevalent substance use disorder in the world. Genetic factors influence smoking behaviors, and although strides have been made using genome-wide association studies (GWAS) to identify risk variants, the majority of variants identified have been for nicotine consumption, rather than TUD. We leveraged five biobanks to perform a multi-ancestral meta-analysis of TUD (derived via electronic health records, EHR) in 898,680 individuals (739,895 European, 114,420 African American, 44,365 Latin American). We identified 88 independent risk loci; integration with functional genomic tools uncovered 461 potential risk genes, primarily expressed in the brain. TUD was genetically correlated with smoking and psychiatric traits from traditionally ascertained cohorts, externalizing behaviors in children, and hundreds of medical outcomes, including HIV infection, heart disease, and pain. This work furthers our biological understanding of TUD and establishes EHR as a source of phenotypic information for studying the genetics of TUD.
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Affiliation(s)
- Sylvanus Toikumo
- Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Mariela V Jennings
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Benjamin K Pham
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Hyunjoon Lee
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Travis T Mallard
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Sevim B Bianchi
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - John J Meredith
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Laura Vilar-Ribó
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d’Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Heng Xu
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Alexander S Hatoum
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, Missouri, USA
| | - Emma C Johnson
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, Missouri, USA
| | - Vanessa Pazdernik
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Zeal Jinwala
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Shreya R Pakala
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Brittany S Leger
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
- Program in Biomedical Sciences, University of California San Diego, La Jolla, CA, USA
| | - Maria Niarchou
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | | | - Greg D Jenkins
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Anthony Batzler
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Richard Pendegraft
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Hang Zhou
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Joanna M Biernacka
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA
| | - Brandon J Coombes
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Joel Gelernter
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Ke Xu
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Dana B Hancock
- Behavioral and Urban Health Program, Behavioral Health and Criminal Justice Division, RTI International, Research Triangle Park, NC, USA
| | - Nancy J Cox
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University, Nashville, TN, USA
| | - Jordan W Smoller
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Lea K Davis
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Amy C Justice
- Yale University School of Public Health, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
- Yale University School of Medicine, New Haven, CT, USA
| | - Henry R Kranzler
- Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Rachel L Kember
- Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Sandra Sanchez-Roige
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University, Nashville, TN, USA
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9
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Ahangari M, Gentry AE, Hassan MF, Nguyen TH, Kendler KS, Bacanu SA, Peterson RE, Riley BP, Webb BT. Improving the discovery of rare variants associated with alcohol problems by leveraging machine learning phenotype prediction and functional information. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.11.557163. [PMID: 37745400 PMCID: PMC10515858 DOI: 10.1101/2023.09.11.557163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
Alcohol use disorder (AUD) is moderately heritable with significant social and economic impact. Genome-wide association studies (GWAS) have identified common variants associated with AUD, however, rare variant investigations have yet to achieve well-powered sample sizes. In this study, we conducted an interval-based exome-wide analysis of the Alcohol Use Disorder Identification Test Problems subscale (AUDIT-P) using both machine learning (ML) predicted risk and empirical functional weights. This research has been conducted using the UK Biobank Resource (application number 30782.) Filtering the 200k exome release to unrelated individuals of European ancestry resulted in a sample of 147,386 individuals with 51,357 observed and 96,029 unmeasured but predicted AUDIT-P for exome analysis. Sequence Kernel Association Test (SKAT/SKAT-O) was used for rare variant (Minor Allele Frequency (MAF) < 0.01) interval analyses using default and empirical weights. Empirical weights were constructed using annotations found significant by stratified LD Score Regression analysis of predicted AUDIT-P GWAS, providing prior functional weights specific to AUDIT-P. Using only samples with observed AUDIT-P yielded no significantly associated intervals. In contrast, ADH1C and THRA gene intervals were significant (False discovery rate (FDR) <0.05) using default and empirical weights in the predicted AUDIT-P sample, with the most significant association found using predicted AUDIT-P and empirical weights in the ADH1C gene (SKAT-O P Default = 1.06 x 10 -9 and P Empirical weight = 6.25 x 10 -11 ). These findings provide evidence for rare variant association of the ADH1C gene with the AUDIT-P and highlight the successful leveraging of ML to increase effective sample size and prior empirical functional weights based on common variant GWAS data to refine and increase the statistical significance in underpowered phenotypes.
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10
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Bountress KE, Bustamante D, de Viteri SSS, Chatzinakos C, Sheerin C, Daskalakis NP, Edenberg HJ, Peterson RE, Webb BT, Meyers J, Amstadter A. Differences in genetic correlations between posttraumatic stress disorder and alcohol-related problems phenotypes compared to alcohol consumption-related phenotypes. Psychol Med 2023; 53:5767-5777. [PMID: 36177877 PMCID: PMC10060434 DOI: 10.1017/s0033291722002999] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
BACKGROUND Posttraumatic Stress Disorder (PTSD) tends to co-occur with greater alcohol consumption as well as alcohol use disorder (AUD). However, it is unknown whether the same etiologic factors that underlie PTSD-alcohol-related problems comorbidity also contribute to PTSD- alcohol consumption. METHODS We used summary statistics from large-scale genome-wide association studies (GWAS) of European-ancestry (EA) and African-ancestry (AA) participants to estimate genetic correlations between PTSD and a range of alcohol consumption-related and alcohol-related problems phenotypes. RESULTS In EAs, there were positive genetic correlations between PTSD phenotypes and alcohol-related problems phenotypes (e.g. Alcohol Use Disorders Identification Test (AUDIT) problem score) (rGs: 0.132-0.533, all FDR adjusted p < 0.05). However, the genetic correlations between PTSD phenotypes and alcohol consumption -related phenotypes (e.g. drinks per week) were negatively associated or non-significant (rGs: -0.417 to -0.042, FDR adjusted p: <0.05-NS). For AAs, the direction of correlations was sometimes consistent and sometimes inconsistent with that in EAs, and the ranges were larger (rGs for alcohol-related problems: -0.275 to 0.266, FDR adjusted p: NS, alcohol consumption-related: 0.145-0.699, FDR adjusted p: NS). CONCLUSIONS These findings illustrate that the genetic associations between consumption and problem alcohol phenotypes and PTSD differ in both strength and direction. Thus, the genetic factors that may lead someone to develop PTSD and high levels of alcohol consumption are not the same as those that lead someone to develop PTSD and alcohol-related problems. Discussion around needing improved methods to better estimate heritabilities and genetic correlations in diverse and admixed ancestry samples is provided.
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Affiliation(s)
| | | | | | - Chris Chatzinakos
- VIPBG. VCU, Richmond, VA, USA
- Department of Psychiatry, McLean Hospital, Harvard Medical School, Belmont, MA, USA
| | | | | | | | | | | | - Bradley T. Webb
- GenOmics, Bioinformatics, and Translational Research Center, Biostatistics and Epidemiology Division, RTI International, Research Triangle Park, NC, USA
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11
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Bountress KE, Cusack SE, Hawn SE, Grotzinger A, Bustamante D, Kirkpatrick RM, Edenberg HJ, Amstadter AB. Genetic associations between alcohol phenotypes and life satisfaction: a genomic structural equation modelling approach. Sci Rep 2023; 13:13443. [PMID: 37596344 PMCID: PMC10439217 DOI: 10.1038/s41598-023-40199-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 08/07/2023] [Indexed: 08/20/2023] Open
Abstract
Alcohol use (i.e., quantity, frequency) and alcohol use disorder (AUD) are common, associated with adverse outcomes, and genetically-influenced. Genome-wide association studies (GWAS) identified genetic loci associated with both. AUD is positively genetically associated with psychopathology, while alcohol use (e.g., drinks per week) is negatively associated or NS related to psychopathology. We wanted to test if these genetic associations extended to life satisfaction, as there is an interest in understanding the associations between psychopathology-related traits and constructs that are not just the absence of psychopathology, but positive outcomes (e.g., well-being variables). Thus, we used Genomic Structural Equation Modeling (gSEM) to analyze summary-level genomic data (i.e., effects of genetic variants on constructs of interest) from large-scale GWAS of European ancestry individuals. Results suggest that the best-fitting model is a Bifactor Model, in which unique alcohol use, unique AUD, and common alcohol factors are extracted. The genetic correlation (rg) between life satisfaction-AUD specific factor was near zero, the rg with the alcohol use specific factor was positive and significant, and the rg with the common alcohol factor was negative and significant. Findings indicate that life satisfaction shares genetic etiology with typical alcohol use and life dissatisfaction shares genetic etiology with heavy alcohol use.
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Affiliation(s)
- Kaitlin E Bountress
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, 800 E. Leigh St. Biotech One Suite 101, Richmond, VA, 23219, USA.
| | - Shannon E Cusack
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, 800 E. Leigh St. Biotech One Suite 101, Richmond, VA, 23219, USA
| | - Sage E Hawn
- Department of Psychology, Old Dominion University, Norfolk, USA
| | - Andrew Grotzinger
- Institute for Behavior Genetics, Behavioral, Psychiatric, and Statistical Genetics, University of Colorado Boulder, Boulder, USA
| | - Daniel Bustamante
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, 800 E. Leigh St. Biotech One Suite 101, Richmond, VA, 23219, USA
| | - Robert M Kirkpatrick
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, 800 E. Leigh St. Biotech One Suite 101, Richmond, VA, 23219, USA
| | | | - Ananda B Amstadter
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, 800 E. Leigh St. Biotech One Suite 101, Richmond, VA, 23219, USA
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12
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White JD, Bierut LJ. Alcohol Consumption and Alcohol Use Disorder: Exposing an Increasingly Shared Genetic Architecture. Am J Psychiatry 2023; 180:530-532. [PMID: 37525606 PMCID: PMC10765608 DOI: 10.1176/appi.ajp.20230456] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/02/2023]
Affiliation(s)
- Julie D White
- GenOmics and Translational Research Center, RTI International, Research Triangle Park, N.C. (White); Department of Psychiatry, Washington University School of Medicine, St. Louis (Bierut)
| | - Laura J Bierut
- GenOmics and Translational Research Center, RTI International, Research Triangle Park, N.C. (White); Department of Psychiatry, Washington University School of Medicine, St. Louis (Bierut)
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13
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Gentry AE, Kirkpatrick RM, Peterson RE, Webb BT. Missingness adapted group informed clustered (MAGIC)-LASSO: a novel paradigm for phenotype prediction to improve power for genetic loci discovery. Front Genet 2023; 14:1162690. [PMID: 37547462 PMCID: PMC10399453 DOI: 10.3389/fgene.2023.1162690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 07/03/2023] [Indexed: 08/08/2023] Open
Abstract
Introduction: The availability of large-scale biobanks linking genetic data, rich phenotypes, and biological measures is a powerful opportunity for scientific discovery. However, real-world collections frequently have extensive missingness. While missing data prediction is possible, performance is significantly impaired by block-wise missingness inherent to many biobanks. Methods: To address this, we developed Missingness Adapted Group-wise Informed Clustered (MAGIC)-LASSO which performs hierarchical clustering of variables based on missingness followed by sequential Group LASSO within clusters. Variables are pre-filtered for missingness and balance between training and target sets with final models built using stepwise inclusion of features ranked by completeness. This research has been conducted using the UK Biobank (n > 500 k) to predict unmeasured Alcohol Use Disorders Identification Test (AUDIT) scores. Results: The phenotypic correlation between measured and predicted total score was 0.67 while genetic correlations between independent subjects was high >0.86. Discussion: Phenotypic and genetic correlations in real data application, as well as simulations, demonstrate the method has significant accuracy and utility for increasing power for genetic loci discovery.
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Affiliation(s)
- Amanda Elswick Gentry
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, United States
| | - Robert M. Kirkpatrick
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, United States
| | - Roseann E. Peterson
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, United States
- Department of Psychiatry and Behavioral Sciences, Institute for Genomics in Health, SUNY Downstate Health Sciences University, Brooklyn, NY, United States
| | - Bradley T. Webb
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, United States
- GenOmics and Translational Research Center, RTI International, Research Triangle Park, NC, United States
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14
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Chaudhary S, Chen Y, Zhornitsky S, Le TM, Zhang S, Chao HH, Dominguez JC, Li CSR. The effects of age on the severity of problem drinking: Mediating effects of positive alcohol expectancy and neural correlates. Addict Biol 2023; 28:e13278. [PMID: 37252876 DOI: 10.1111/adb.13278] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 02/24/2023] [Accepted: 03/20/2023] [Indexed: 06/01/2023]
Abstract
Aging is associated with reduction in the severity of alcohol misuse. However, the psychological and neural mechanisms underlying the age-related changes remain unclear. Here, we tested the hypothesis that age-related diminution of positive alcohol expectancy (AE) mediated the effects of age on problem drinking and investigated the neural correlates of the mediating effects. Ninety-six drinkers 21-85 years of age, including social drinkers and those with mild/moderate alcohol use disorder (AUD), were assessed for global positive (GP) AE and problem drinking, each with the Alcohol Expectancy Questionnaire and Alcohol Use Disorders Identification Test (AUDIT), and with brain imaging during alcohol cue exposure. We processed imaging data with published routines; identified the correlates shared between whole-brain regression against age, GP and AUDIT scores; and performed mediation and path analyses to explore the interrelationships between the clinical and neural variables. The results showed that age was negatively correlated with both GP and AUDIT scores, with GP score completely mediating the correlation between age and AUDIT score. Lower age and higher GP correlated with shared cue responses in bilateral parahippocampal gyrus and left middle occipital cortex (PHG/OC). Further, higher GP and AUDIT scores were associated with shared cue responses in bilateral rostral anterior cingulate cortex and caudate head (ACC/caudate). Path analyses demonstrated models with significant statistical fit and PHG/OC and ACC/caudate each interrelating age to GP and GP to AUDIT scores. These findings confirmed change in positive AE as a psychological mechanism mitigating alcohol misuse as individuals age and highlighted the neural processes of cue-reactivity interrelating age and alcohol use severity.
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Affiliation(s)
- Shefali Chaudhary
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Yu Chen
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Simon Zhornitsky
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Thang M Le
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Sheng Zhang
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Herta H Chao
- VA Connecticut Healthcare System, West Haven, CT, USA
- Department of Medicine, Yale University School of Medicine, New Haven, CT, USA
| | | | - Chiang-Shan R Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT, USA
- Wu Tsai Institute, Yale University, New Haven, CT, USA
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15
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Kuo SIC, Thomas NS, Aliev F, Bucholz KK, Dick DM, McCutcheon VV, Meyers JL, Chan G, Kamarajan C, Kramer JR, Hesselbrock V, Plawecki MH, Porjesz B, Tischfield J, Salvatore JE. Association of parental divorce, discord, and polygenic risk with children's alcohol initiation and lifetime risk for alcohol use disorder. ALCOHOL, CLINICAL & EXPERIMENTAL RESEARCH 2023; 47:724-735. [PMID: 36807915 PMCID: PMC10149624 DOI: 10.1111/acer.15042] [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] [Received: 11/06/2022] [Revised: 01/25/2023] [Accepted: 02/14/2023] [Indexed: 02/21/2023]
Abstract
BACKGROUND Parental divorce and discord are associated with poorer alcohol-related outcomes for offspring. However, not all children exposed to these stressors develop alcohol problems. Our objective was to test gene-by-environment interaction effects whereby children's genetic risk for alcohol problems modifies the effects of parental divorce and discord to predict alcohol outcomes. METHODS The sample included European (EA; N = 5608, 47% male, Mage ~ 36 years) and African (AA; N = 1714, 46% female, Mage ~ 33 years) ancestry participants from the Collaborative Study on the Genetics of Alcoholism. Outcomes included age at initiation of regular drinking and lifetime DSM-5 alcohol use disorder (AUD). Predictors included parental divorce, parental relationship discord, and offspring alcohol problems polygenic risk scores (PRSALC ). Mixed effects Cox proportional hazard models were used to examine alcohol initiation and generalized linear mixed effects models were used to examine lifetime AUD. Tests of PRS moderation of the effects of parental divorce/relationship discord on alcohol outcomes were examined on multiplicative and additive scales. RESULTS Among EA participants, parental divorce, parental discord, and higher PRSALC were associated with earlier alcohol initiation and greater lifetime AUD risk. Among AA participants, parental divorce was associated with earlier alcohol initiation and discord was associated with earlier initiation and AUD. PRSALC was not associated with either. Parental divorce/discord and PRSALC interacted on an additive scale in the EA sample, but no interactions were found in AA participants. CONCLUSIONS Children's genetic risk for alcohol problems modifies the impact of parental divorce/discord, consistent with an additive model of diathesis-stress interaction, with some differences across ancestry.
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Affiliation(s)
- Sally I-Chun Kuo
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, New Jersey, USA
| | - Nathaniel S. Thomas
- Department of Psychology, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Fazil Aliev
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, New Jersey, USA
| | - Kathleen K. Bucholz
- Department of Psychiatry, School of Medicine, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Danielle M. Dick
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, New Jersey, USA
| | - Vivia V. McCutcheon
- Department of Psychiatry, School of Medicine, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Jacquelyn L. Meyers
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, New York, USA
| | - Grace Chan
- Department of Psychiatry, University of Connecticut School of Medicine, Farmington, Connecticut, USA
| | - Chella Kamarajan
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, New York, USA
| | - John R. Kramer
- Department of Psychiatry, University of Iowa, Iowa City, Iowa, USA
| | - Victor Hesselbrock
- Department of Psychiatry, University of Connecticut School of Medicine, Farmington, Connecticut, USA
| | - Martin H. Plawecki
- Department of Psychiatry, Indiana University, Indianapolis, Indiana, USA
| | - Bernice Porjesz
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, New York, USA
| | - Jay Tischfield
- Department of Genetics, Rutgers University, Piscataway, New Jersey, USA
| | - Jessica E. Salvatore
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, New Jersey, USA
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16
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Thomas NS, Salvatore JE, Kuo SIC, Aliev F, McCutcheon VV, Meyers JM, Bucholz KK, Brislin SJ, Chan G, Edenberg HJ, Kamarajan C, Kramer JR, Kuperman S, Pandey G, Plawecki MH, Schuckit MA, Dick DM. Genetic nurture effects for alcohol use disorder. Mol Psychiatry 2023; 28:759-766. [PMID: 36253439 PMCID: PMC10079179 DOI: 10.1038/s41380-022-01816-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 09/19/2022] [Accepted: 09/23/2022] [Indexed: 11/09/2022]
Abstract
We tested whether aspects of the childhood/adolescent home environment mediate genetic risk for alcohol problems within families across generations. Parental relationship discord and parental divorce were the focal environments examined. The sample included participants of European ancestry (N = 4806, 51% female) and African ancestry (N = 1960, 52% female) from the high-risk Collaborative Study on the Genetics of Alcoholism. Alcohol outcomes in the child generation included lifetime criterion counts for DSM-5 Alcohol Use Disorder (AUD), lifetime maximum drinks in 24 h, age at initiation of regular drinking, and age at first alcohol intoxication. Predictors in the parent generation included relationship discord, divorce, alcohol measures parallel to those in the child generation, and polygenic scores for alcohol problems. Parental polygenic scores were partitioned into alleles that were transmitted and non-transmitted to the child. The results from structural equation models were consistent with genetic nurture effects in European ancestry families. Exposure to parental relationship discord and parental divorce mediated, in part, the transmission of genetic risk for alcohol problems from parents to children to predict earlier ages regular drinking (βindirect = -0.018 [-0.026, -0.011]) and intoxication (βindirect = -0.015 [-0.023, -0.008]), greater lifetime maximum drinks (βindirect = 0.006 [0.002, 0.01]) and more lifetime AUD criteria (βindirect = 0.011 [0.006, 0.016]). In contrast, there was no evidence that parental alleles had indirect effects on offspring alcohol outcomes via parental relationship discord or divorce in the smaller number of families of African ancestry. In conclusion, parents transmit genetic risk for alcohol problems to their children not only directly, but also indirectly via genetically influenced aspects of the home environment. Further investigation of genetic nurture in non-European samples is needed.
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Affiliation(s)
- Nathaniel S Thomas
- Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA.
| | - Jessica E Salvatore
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ, USA.
| | - Sally I-Chun Kuo
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ, USA
| | - Fazil Aliev
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ, USA
| | - Vivia V McCutcheon
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Jacquelyn M Meyers
- Department of Psychiatry and Behavioral Sciences, State University of New York Health Sciences University, Brooklyn, NY, USA
| | - Kathleen K Bucholz
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Sarah J Brislin
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ, USA
| | - Grace Chan
- Department of Psychiatry, University of Connecticut School of Medicine, Farmington, CT, USA
- Department of Psychiatry, University of Iowa, Iowa City, IA, USA
| | - Howard J Edenberg
- Department of Biochemistry and Molecular Biology, Indiana University, Indianapolis, IN, USA
| | - Chella Kamarajan
- Department of Psychiatry and Behavioral Sciences, State University of New York Health Sciences University, Brooklyn, NY, USA
| | - John R Kramer
- Department of Psychiatry, University of Iowa, Iowa City, IA, USA
| | - Samuel Kuperman
- Department of Psychiatry, University of Iowa, Iowa City, IA, USA
| | - Gayathri Pandey
- Department of Psychiatry and Behavioral Sciences, State University of New York Health Sciences University, Brooklyn, NY, USA
| | | | - Marc A Schuckit
- Department of Psychiatry, University of California San Diego Medical School, San Diego, CA, USA
| | - Danielle M Dick
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ, USA
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17
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Gentry AE, Alexander JC, Ahangari M, Peterson RE, Miles MF, Bettinger JC, Davies AG, Groteweil M, Bacanu SA, Kendler KS, Riley BP, Webb BT. Case-only exome variation analysis of severe alcohol dependence using a multivariate hierarchical gene clustering approach. PLoS One 2023; 18:e0283985. [PMID: 37098020 PMCID: PMC10128939 DOI: 10.1371/journal.pone.0283985] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 03/21/2023] [Indexed: 04/26/2023] Open
Abstract
BACKGROUND Variation in genes involved in ethanol metabolism has been shown to influence risk for alcohol dependence (AD) including protective loss of function alleles in ethanol metabolizing genes. We therefore hypothesized that people with severe AD would exhibit different patterns of rare functional variation in genes with strong prior evidence for influencing ethanol metabolism and response when compared to genes not meeting these criteria. OBJECTIVE Leverage a novel case only design and Whole Exome Sequencing (WES) of severe AD cases from the island of Ireland to quantify differences in functional variation between genes associated with ethanol metabolism and/or response and their matched control genes. METHODS First, three sets of ethanol related genes were identified including those a) involved in alcohol metabolism in humans b) showing altered expression in mouse brain after alcohol exposure, and altering ethanol behavioral responses in invertebrate models. These genes of interest (GOI) sets were matched to control gene sets using multivariate hierarchical clustering of gene-level summary features from gnomAD. Using WES data from 190 individuals with severe AD, GOI were compared to matched control genes using logistic regression to detect aggregate differences in abundance of loss of function, missense, and synonymous variants, respectively. RESULTS Three non-independent sets of 10, 117, and 359 genes were queried against control gene sets of 139, 1522, and 3360 matched genes, respectively. Significant differences were not detected in the number of functional variants in the primary set of ethanol-metabolizing genes. In both the mouse expression and invertebrate sets, we observed an increased number of synonymous variants in GOI over matched control genes. Post-hoc simulations showed the estimated effects sizes observed are unlikely to be under-estimated. CONCLUSION The proposed method demonstrates a computationally viable and statistically appropriate approach for genetic analysis of case-only data for hypothesized gene sets supported by empirical evidence.
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Affiliation(s)
- Amanda Elswick Gentry
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, United States of America
- Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia, United States of America
| | - Jeffry C Alexander
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, United States of America
| | - Mohammad Ahangari
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, United States of America
- Integrative Life Sciences Ph.D. Program, Virginia Commonwealth University, Richmond, Virginia, United States of America
| | - Roseann E Peterson
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, United States of America
- Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia, United States of America
- Department of Psychiatry and Behavioral Sciences, Institute for Genomics in Health, SUNY Downstate Health Sciences University, Brooklyn, New York, United States of America
- VCU Alcohol Research Center, 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
| | - Jill C Bettinger
- 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
| | - Andrew G Davies
- 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
| | - Mike Groteweil
- VCU Alcohol Research Center, Virginia Commonwealth University, Richmond, Virginia, United States of America
- Department of Human and Molecular Genetics, 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
- Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia, United States of America
- VCU Alcohol Research Center, Virginia Commonwealth University, Richmond, Virginia, United States of America
| | - Kenneth S Kendler
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, United States of America
- Department of Psychiatry, 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
- Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia, United States of America
- VCU Alcohol Research Center, Virginia Commonwealth University, Richmond, Virginia, United States of America
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, Virginia, United States of America
| | - Bradley T Webb
- VCU Alcohol Research Center, Virginia Commonwealth University, Richmond, Virginia, United States of America
- GenOmics, Bioinformatics, and Translational Research Center, Biostatistics and Epidemiology Division, RTI International, Research Triangle Park, North Caroline, United States of America
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18
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Abstract
Alcohol is one of the most widely consumed psychoactive drugs globally. Hazardous drinking, defined by quantity and frequency of consumption, is associated with acute and chronic morbidity. Alcohol use disorders (AUDs) are psychiatric syndromes characterized by impaired control over drinking and other symptoms. Contemporary aetiological perspectives on AUDs apply a biopsychosocial framework that emphasizes the interplay of genetics, neurobiology, psychology, and an individual's social and societal context. There is strong evidence that AUDs are genetically influenced, but with a complex polygenic architecture. Likewise, there is robust evidence for environmental influences, such as adverse childhood exposures and maladaptive developmental trajectories. Well-established biological and psychological determinants of AUDs include neuroadaptive changes following persistent use, differences in brain structure and function, and motivational determinants including overvaluation of alcohol reinforcement, acute effects of environmental triggers and stress, elevations in multiple facets of impulsivity, and lack of alternative reinforcers. Social factors include bidirectional roles of social networks and sociocultural influences, such as public health control strategies and social determinants of health. An array of evidence-based approaches for reducing alcohol harms are available, including screening, pharmacotherapies, psychological interventions and policy strategies, but are substantially underused. Priorities for the field include translating advances in basic biobehavioural research into novel clinical applications and, in turn, promoting widespread implementation of evidence-based clinical approaches in practice and health-care systems.
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19
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Stephenson M, Aliev F, Kuo SIC, Edwards AC, Pandey G, Su J, Kamarajan C, Dick D, Salvatore JE. The role of adolescent social relationships in promoting alcohol resistance: Interrupting the intergenerational transmission of alcohol misuse. Dev Psychopathol 2022; 34:1841-1855. [PMID: 36873306 PMCID: PMC9976711 DOI: 10.1017/s0954579422000785] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Genetic factors contribute to the intergenerational transmission of alcohol misuse, but not all individuals at high genetic risk develop problems. The present study examined adolescent relationships with parents, peers, and romantic partners as predictors of realized resistance, defined as high biological risk for disorder combined with a healthy outcome, to alcohol initiation, heavy episodic drinking, and alcohol use disorder (AUD). Data were from the Collaborative Study on the Genetics of Alcoholism (N = 1,858; 49.9% female; mean age at baseline = 13.91 years). Genetic risk, indexed using family history density and polygenic risk scores for alcohol problems and AUD, was used to define alcohol resistance. Adolescent predictors included parent-child relationship quality, parental monitoring, peer drinking, romantic partner drinking, and social competence. There was little support for the hypothesis that social relationship factors would promote alcohol resistance, with the exception that higher father-child relationship quality was associated with higher resistance to alcohol initiation (β ^ = - 0.19 , 95% CI = -0.35, -0.03). Unexpectedly, social competence was associated with lower resistance to heavy episodic drinking (β ^ = 0.10 , 95% CI = 0.01, 0.20). This pattern of largely null effects underscores how little is known about resistance processes among those at high genetic risk for AUD.
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Affiliation(s)
- Mallory Stephenson
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Fazil Aliev
- Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA
| | - Sally I-Chun Kuo
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, USA
| | - Alexis C. Edwards
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
- Department of Psychiatry, School of Medicine, Virginia Commonwealth University, Richmond, VA, USA
| | - Gayathri Pandey
- Department of Psychiatry and Behavioral Sciences, Downstate Medical Center, State University of New York, Brooklyn, NY, USA
| | - Jinni Su
- Department of Psychology, Arizona State University, Tempe, AZ, USA
| | - Chella Kamarajan
- Department of Psychiatry and Behavioral Sciences, Downstate Medical Center, State University of New York, Brooklyn, NY, USA
| | - Danielle Dick
- Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA
| | - Jessica E. Salvatore
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, USA
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20
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Sanchez-Roige S, Kember RL, Agrawal A. Substance use and common contributors to morbidity: A genetics perspective. EBioMedicine 2022; 83:104212. [PMID: 35970022 PMCID: PMC9399262 DOI: 10.1016/j.ebiom.2022.104212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 07/27/2022] [Accepted: 07/28/2022] [Indexed: 11/23/2022] Open
Abstract
Excessive substance use and substance use disorders (SUDs) are common, serious and relapsing medical conditions. They frequently co-occur with other diseases that are leading contributors to disability worldwide. While heavy substance use may potentiate the course of some of these illnesses, there is accumulating evidence suggesting common genetic architectures. In this narrative review, we focus on four heritable medical conditions - cardiometabolic disease, chronic pain, depression and COVID-19, which are commonly overlapping with, but not necessarily a direct consequence of, SUDs. We find persuasive evidence of underlying genetic liability that predisposes to both SUDs and chronic pain, depression, and COVID-19. For cardiometabolic disease, there is greater support for a potential causal influence of problematic substance use. Our review encourages de-stigmatization of SUDs and the assessment of substance use in clinical settings. We assert that identifying shared pathways of risk has high translational potential, allowing tailoring of treatments for multiple medical conditions. Funding SSR acknowledges T29KT0526, T32IR5226 and DP1DA054394; RLK acknowledges AA028292; AA acknowledges DA054869 & K02DA032573. The funders had no role in the conceptualization or writing of the paper.
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21
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Zhou H, Kalayasiri R, Sun Y, Nuñez YZ, Deng HW, Chen XD, Justice AC, Kranzler HR, Chang S, Lu L, Shi J, Sanichwankul K, Mutirangura A, Malison RT, Gelernter J. Genome-wide meta-analysis of alcohol use disorder in East Asians. Neuropsychopharmacology 2022; 47:1791-1797. [PMID: 35094024 PMCID: PMC9372033 DOI: 10.1038/s41386-022-01265-w] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Revised: 12/22/2021] [Accepted: 12/29/2021] [Indexed: 12/14/2022]
Abstract
Alcohol use disorder (AUD) is a leading cause of death and disability worldwide. Genome-wide association studies (GWAS) have identified ~30 AUD risk genes in European populations, but many fewer in East Asians. We conducted GWAS and genome-wide meta-analysis of AUD in 13,551 subjects with East Asian ancestry, using published summary data and newly genotyped data from five cohorts: (1) electronic health record (EHR)-diagnosed AUD in the Million Veteran Program (MVP) sample; (2) DSM-IV diagnosed alcohol dependence (AD) in a Han Chinese-GSA (array) cohort; (3) AD in a Han Chinese-Cyto (array) cohort; and (4) two AD Thai cohorts. The MVP and Thai samples included newly genotyped subjects from ongoing recruitment. In total, 2254 cases and 11,297 controls were analyzed. An AUD polygenic risk score was analyzed in an independent sample with 4464 East Asians (Genetic Epidemiology Research in Adult Health and Aging (GERA)). Phenotypes from survey data and ICD-9-CM diagnoses were tested for association with the AUD PRS. Two risk loci were detected: the well-known functional variant rs1229984 in ADH1B and rs3782886 in BRAP (near the ALDH2 gene locus) are the lead variants. AUD PRS was significantly associated with days per week of alcohol consumption (beta = 0.43, SE = 0.067, p = 2.47 × 10-10) and nominally associated with pack years of smoking (beta = 0.09, SE = 0.05, p = 4.52 × 10-2) and ever vs. never smoking (beta = 0.06, SE = 0.02, p = 1.14 × 10-2). This is the largest GWAS of AUD in East Asians to date. Building on previous findings, we were able to analyze pleiotropy, but did not identify any new risk regions, underscoring the importance of recruiting additional East Asian subjects for alcohol GWAS.
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Affiliation(s)
- Hang Zhou
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Rasmon Kalayasiri
- Department of Psychiatry, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Department of Psychiatry, King Chulalongkorn Memorial Hospital, Bangkok, Thailand
- Center for Excellence in Molecular Genetics of Cancer and Human Diseases, Department of Anatomy, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Yan Sun
- National Institute on Drug Dependence, Peking University, Beijing, China
| | - Yaira Z Nuñez
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Hong-Wen Deng
- Center for Biomedical Informatics and Genomics, School of Medicine, Tulane University, New Orleans, LA, USA
| | - Xiang-Ding Chen
- Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan, China
| | - Amy C Justice
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
- Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT, USA
| | - Henry R Kranzler
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
| | - Suhua Chang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Lin Lu
- National Institute on Drug Dependence, Peking University, Beijing, China
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Jie Shi
- National Institute on Drug Dependence, Peking University, Beijing, China
| | | | - Apiwat Mutirangura
- Center for Excellence in Molecular Genetics of Cancer and Human Diseases, Department of Anatomy, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Robert T Malison
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Joel Gelernter
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA.
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA.
- Departments of Genetics and Neuroscience, Yale University School of Medicine, New Haven, CT, USA.
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22
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Chang XW, Sun Y, Muhai JN, Li YY, Chen Y, Lu L, Chang SH, Shi J. Common and distinguishing genetic factors for substance use behavior and disorder: an integrated analysis of genomic and transcriptomic studies from both human and animal studies. Addiction 2022; 117:2515-2529. [PMID: 35491750 DOI: 10.1111/add.15908] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/30/2021] [Accepted: 04/04/2022] [Indexed: 11/30/2022]
Abstract
BACKGROUND AND AIMS Genomic and transcriptomic findings greatly broaden the biological knowledge regarding substance use. However, systematic convergence and comparison evidence of genome-wide findings is lacking for substance use. Here, we combined all the genome-wide findings from both substance use behavior and disorder (SUBD) and identified common and distinguishing genetic factors for different SUBDs. METHODS Systemic literature search for genome-wide association (GWAS) and RNA-seq studies of alcohol/nicotine/drug use behavior (partially meets or not reported diagnostic criteria) and alcohol use behavior and disorder (AUBD), nicotine use behavior and disorder (NUBD) and drug use behavior and disorder (DUBD) was performed using PubMed and the GWAS catalog. Drug use was focused upon cannabis, opioid, cocaine and methamphetamine use. GWAS studies required case-control or case/cohort samples. RNA-seq studies were based on brain tissues. The genes which contained significant single nucleotide polymorphism (P ≤ 1 × 10-6 ) in GWAS and reported as significant in RNA-seq studies were extracted. Pathway enrichment was performed by using Metascape. Gene interaction networks were identified by using the Protein Interaction Network Analysis database. RESULTS Total SUBD-related 2910 genes were extracted from 75 GWAS studies (2 773 889 participants) and 17 RNA-seq studies. By overlapping the genes and pathways of AUBD, NUBD and DUBD, four shared genes (CACNB2, GRIN2B, PLXDC2 and PKNOX2), four shared pathways [two Gene Ontology (GO) terms of 'modulation of chemical synaptic transmission', 'regulation of trans-synaptic signaling', two Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of 'dopaminergic synapse', 'cocaine addiction'] were identified (significantly higher than random, P < 1 × 10-5 ). The top shared KEGG pathways (Benjamini-Hochberg-corrected P-value < 0.05) in the pairwise comparison of AUBD versus DUBD, NUBD versus DUBD, AUBD versus NUBD were 'Epstein-Barr virus infection', 'protein processing in endoplasmic reticulum' and 'neuroactive ligand-receptor interaction', respectively. We also identified substance-specific genetic factors: i.e. ADH1B and ALDH2 were unique for AUBD, while CHRNA3 and CHRNA4 were unique for NUBD. CONCLUSIONS This systematic review identifies the shared and unique genes and pathways for alcohol, nicotine and drug use behaviors and disorders at the genome-wide level and highlights critical biological processes for the common and distinguishing vulnerability of substance use behaviors and disorders.
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Affiliation(s)
- Xiang-Wen Chang
- Department of Pharmacology, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China.,National Institute on Drug Dependence, Peking University, Beijing, China
| | - Yan Sun
- Department of Pharmacology, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China.,National Institute on Drug Dependence, Peking University, Beijing, China
| | - Jia-Na Muhai
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Yang-Yang Li
- Department of Pharmacology, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China.,National Institute on Drug Dependence, Peking University, Beijing, China
| | - Yun Chen
- Department of Pharmacology, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China.,National Institute on Drug Dependence, Peking University, Beijing, China
| | - Lin Lu
- National Institute on Drug Dependence, Peking University, Beijing, China.,Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Su-Hua Chang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Jie Shi
- National Institute on Drug Dependence, Peking University, Beijing, China.,Beijing Key Laboratory of Drug Dependence Research, Peking University, Beijing, China.,The State Key Laboratory of Natural and Biomimetic Drugs, Peking University, Beijing, China.,The Key Laboratory for Neuroscience of the Ministry of Education and Health, Peking University, Beijing, China
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23
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de Marco A, Scozia G, Manfredi L, Conversi D. A Systematic Review of Genetic Polymorphisms Associated with Bipolar Disorder Comorbid to Substance Abuse. Genes (Basel) 2022; 13:genes13081303. [PMID: 35893041 PMCID: PMC9330731 DOI: 10.3390/genes13081303] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Revised: 07/20/2022] [Accepted: 07/21/2022] [Indexed: 01/09/2023] Open
Abstract
It is currently unknown which genetic polymorphisms are involved in substance use disorder (SUD) comorbid with bipolar disorder (BD). The research on polymorphisms in BD comorbid with SUD (BD + SUD) is summarized in this systematic review. We looked for case-control studies that genetically compared adults and adolescents with BD and SUD, healthy controls, and BD without SUD. PRISMA was used to create our protocol, which is PROSPERO-registered (identification: CRD4221270818). The following bibliographic databases were searched indefinitely until December 2021 to identify potentially relevant articles: PubMed, PsycINFO, Scopus, and Web of Science. This systematic review, after the qualitative analysis of the study selection, included 17 eligible articles. In the selected studies, 66 polymorphisms in 29 genes were investigated. The present work delivers a group of potentially valuable genetic polymorphisms associated with BD + SUD: rs11600996 (ARNTL), rs228642/rs228682/rs2640909 (PER3), PONQ192R (PON1), rs945032 (BDKRB2), rs1131339 (NR4A3), and rs6971 (TSPO). It is important to note that none of those findings have been confirmed by two or more studies; thus, we believe that all the polymorphisms identified in this review require additional evidence to be confirmed.
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Affiliation(s)
- Adriano de Marco
- Department of Psychology, Università degli Studi di Roma ‘La Sapienza’, 00185 Rome, Italy; (A.d.M.); (G.S.); (L.M.)
| | - Gabriele Scozia
- Department of Psychology, Università degli Studi di Roma ‘La Sapienza’, 00185 Rome, Italy; (A.d.M.); (G.S.); (L.M.)
- PhD Program in Behavioral Neuroscience, Università degli Studi di Roma ‘La Sapienza’, 00185 Rome, Italy
| | - Lucia Manfredi
- Department of Psychology, Università degli Studi di Roma ‘La Sapienza’, 00185 Rome, Italy; (A.d.M.); (G.S.); (L.M.)
| | - David Conversi
- Department of Psychology, Università degli Studi di Roma ‘La Sapienza’, 00185 Rome, Italy; (A.d.M.); (G.S.); (L.M.)
- Correspondence:
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24
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Alcohol-Induced Oxidative Stress and the Role of Antioxidants in Alcohol Use Disorder: A Systematic Review. Antioxidants (Basel) 2022; 11:antiox11071374. [PMID: 35883865 PMCID: PMC9311529 DOI: 10.3390/antiox11071374] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 07/06/2022] [Accepted: 07/11/2022] [Indexed: 12/12/2022] Open
Abstract
Alcohol use disorder (AUD) is a highly prevalent, comorbid, and disabling disorder. The underlying mechanism of ethanol neurotoxicity and the involvement of oxidative stress is still not fully elucidated. However, ethanol metabolism has been associated with increased oxidative stress through alcohol dehydrogenase, the microsomal ethanol oxidation system, and catalase metabolic pathways. We searched the PubMed and genome-wide association studies (GWAS) catalog databases to review the literature systematically and summarized the findings focusing on AUD and alcohol abstinence in relation to oxidative stress. In addition, we reviewed the ClinicalTrials.gov resource of the US National Library of Medicine to identify all ongoing and completed clinical trials that include therapeutic interventions based on antioxidants. The retrieved clinical and preclinical studies show that oxidative stress impacts AUD through genetics, alcohol metabolism, inflammation, and neurodegeneration.
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25
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Parker CC, Philip VM, Gatti DM, Kasparek S, Kreuzman AM, Kuffler L, Mansky B, Masneuf S, Sharif K, Sluys E, Taterra D, Taylor WM, Thomas M, Polesskaya O, Palmer AA, Holmes A, Chesler EJ. Genome-wide association mapping of ethanol sensitivity in the Diversity Outbred mouse population. Alcohol Clin Exp Res 2022; 46:941-960. [PMID: 35383961 DOI: 10.1111/acer.14825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Revised: 03/04/2022] [Accepted: 03/30/2022] [Indexed: 12/01/2022]
Abstract
BACKGROUND A strong predictor for the development of alcohol use disorder (AUD) is altered sensitivity to the intoxicating effects of alcohol. Individual differences in the initial sensitivity to alcohol are controlled in part by genetic factors. Mice offer a powerful tool to elucidate the genetic basis of behavioral and physiological traits relevant to AUD, but conventional experimental crosses have only been able to identify large chromosomal regions rather than specific genes. Genetically diverse, highly recombinant mouse populations make it possible to observe a wider range of phenotypic variation, offer greater mapping precision, and thus increase the potential for efficient gene identification. METHODS We have taken advantage of the Diversity Outbred (DO) mouse population to identify and precisely map quantitative trait loci (QTL) associated with ethanol sensitivity. We phenotyped 798 male J:DO mice for three measures of ethanol sensitivity: ataxia, hypothermia, and loss of the righting response. We used high-density MegaMUGA and GigaMUGA to obtain genotypes ranging from 77,808 to 143,259 SNPs. We also performed RNA sequencing in striatum to map expression QTLs and identify gene expression-trait correlations. We then applied a systems genetic strategy to identify narrow QTLs and construct the network of correlations that exists between DNA sequence, gene expression values, and ethanol-related phenotypes to prioritize our list of positional candidate genes. RESULTS We observed large amounts of phenotypic variation with the DO population and identified suggestive and significant QTLs associated with ethanol sensitivity on chromosomes 1, 2, and 16. The implicated regions were narrow (4.5-6.9 Mb in size) and each QTL explained ~4-5% of the variance. CONCLUSIONS Our results can be used to identify alleles that contribute to AUD in humans, elucidate causative biological mechanisms, or assist in the development of novel therapeutic interventions.
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Affiliation(s)
- Clarissa C Parker
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, Vermont, USA
| | - Vivek M Philip
- Center for Computational Sciences, The Jackson Laboratory, Bar Harbor, Maine, USA
| | - Daniel M Gatti
- Center for Computational Sciences, The Jackson Laboratory, Bar Harbor, Maine, USA
| | - Steven Kasparek
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, Vermont, USA
| | - Andrew M Kreuzman
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, Vermont, USA
| | - Lauren Kuffler
- Center for Mammalian Genetics, The Jackson Laboratory, Bar Harbor, Maine, USA
| | - Benjamin Mansky
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, Vermont, USA
| | - Sophie Masneuf
- Laboratory of Behavioral and Genomic Neuroscience, NIAAA, NIH, Rockville, MD, USA
| | - Kayvon Sharif
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, Vermont, USA
| | - Erica Sluys
- Laboratory of Behavioral and Genomic Neuroscience, NIAAA, NIH, Rockville, MD, USA
| | - Dominik Taterra
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, Vermont, USA
| | - Walter M Taylor
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, Vermont, USA
| | - Mary Thomas
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, Vermont, USA
| | - Oksana Polesskaya
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,Institute for Genomic Medicine, University of California San Diego, La Jolla, California, USA
| | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,Institute for Genomic Medicine, University of California San Diego, La Jolla, California, USA
| | - Andrew Holmes
- Laboratory of Behavioral and Genomic Neuroscience, NIAAA, NIH, Rockville, MD, USA
| | - Elissa J Chesler
- Center for Mammalian Genetics, The Jackson Laboratory, Bar Harbor, Maine, USA
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26
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Bountress KE, Brick LA, Sheerin C, Grotzinger A, Bustamante D, Hawn SE, Gillespie N, Kirkpatrick RM, Kranzler H, Morey R, Edenberg HJ, Maihofer AX, Disner S, Ashley-Koch A, Peterson R, Lori A, Stein DJ, Kimbrel N, Nievergelt C, Andreassen OA, Luykx J, Javanbakht A, Youssef NA, Amstadter AB. Alcohol use and alcohol use disorder differ in their genetic relationships with PTSD: A genomic structural equation modelling approach. Drug Alcohol Depend 2022; 234:109430. [PMID: 35367939 PMCID: PMC9018560 DOI: 10.1016/j.drugalcdep.2022.109430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 03/09/2022] [Accepted: 03/21/2022] [Indexed: 11/20/2022]
Abstract
PURPOSE Posttraumatic Stress Disorder (PTSD) is associated with increased alcohol use and alcohol use disorder (AUD), which are all moderately heritable. Studies suggest the genetic association between PTSD and alcohol use differs from that of PTSD and AUD, but further analysis is needed. BASIC PROCEDURES We used genomic Structural Equation Modeling (genomicSEM) to analyze summary statistics from large-scale genome-wide association studies (GWAS) of European Ancestry participants to investigate the genetic relationships between PTSD (both diagnosis and re-experiencing symptom severity) and a range of alcohol use and AUD phenotypes. MAIN FINDINGS When we differentiated genetic factors for alcohol use and AUD we observed improved model fit relative to models with all alcohol-related indicators loading onto a single factor. The genetic correlations (rG) of PTSD were quite discrepant for the alcohol use and AUD factors. This was true when modeled as a three-correlated-factor model (PTSD-AUD rG:.36, p < .001; PTSD-alcohol use rG: -0.17, p < .001) and as a Bifactor model, in which the common and unique portions of alcohol phenotypes were pulled out into an AUD-specific factor (rG with PTSD:.40, p < .001), AU-specific factor (rG with PTSD: -0.57, p < .001), and a common alcohol factor (rG with PTSD:.16, NS). PRINCIPAL CONCLUSIONS These results indicate the genetic architecture of alcohol use and AUD are differentially associated with PTSD. When the portions of variance unique to alcohol use and AUD are extracted, their genetic associations with PTSD vary substantially, suggesting different genetic architectures of alcohol phenotypes in people with PTSD.
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Affiliation(s)
- Kaitlin E Bountress
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, USA.
| | - Leslie A Brick
- Department of Psychiatry and Human Behavior, Quantitative Sciences Program, Alpert Medical School at Brown University, USA
| | - Christina Sheerin
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, USA
| | - Andrew Grotzinger
- Behavioral, Psychiatric, and Statistical Genetics, Institute for Behavior Genetics, University of Colorado Boulder, USA
| | - Daniel Bustamante
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, USA; Integrative Life Sciences Doctoral Program, Virginia Commonwealth University, USA
| | - Sage E Hawn
- National Center for PTSD at VA Boston Healthcare System, Boston, MA, USA; Boston University School of Medicine, Department of Psychiatry, Boston, MA, USA
| | - Nathan Gillespie
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, USA
| | - Robert M Kirkpatrick
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, USA
| | - Henry Kranzler
- University of Pennsylvania Perelman School of Medicine, Department of Psychiatry, Philadelphia, PA, USA; Mental Illness Research, Education and Clinical Center, Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
| | - Rajendra Morey
- VA Mid-Atlantic Mental Illness Research Education and Clinical Center, Durham VAMC, Durham, NC, USA; Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA; Duke-UNC Brain Imaging and Analysis Center, Duke University, Durham, NC, USA
| | - Howard J Edenberg
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, USA; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, USA
| | - Adam X Maihofer
- Department of Psychiatry, University of California, San Diego, USA; Center of Excellence for Stress and Mental Health, Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
| | - Seth Disner
- Minneapolis VA Health Care System, Minneapolis, MN, USA; Department of Psychiatry and Behavioral Sciences, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Allison Ashley-Koch
- Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC, USA
| | - Roseann Peterson
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, USA
| | - Adriana Lori
- Department of Psychiatry and Behavioral Sciences, Emory University, USA
| | - Dan J Stein
- Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Nathan Kimbrel
- VA Mid-Atlantic Mental Illness Research Education and Clinical Center, Durham VAMC, Durham, NC, USA; Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
| | - Caroline Nievergelt
- Department of Psychiatry, University of California, San Diego, USA; Center of Excellence for Stress and Mental Health, Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
| | - Ole A Andreassen
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Jurjen Luykx
- School for Mental Health and Neuroscience, Maastricht University Medical Centre, Department of Psychiatry and Neuropsychology Maastricht, The Netherlands; UMC Utrecht Brain Center, University Medical Center Utrecht, Department of Psychiatry Utrecht, University, Utrecht, The Netherlands; Outpatient second opinion clinic, GGNet Mental Health, Warnsveld, The Netherlands
| | - Arash Javanbakht
- Stress, Trauma, and Anxiety Research Clinic (STARC), Department of Psychiatry and Behavioral Neurosciences, Wayne State University, Detroit, MI, USA
| | - Nagy A Youssef
- Department of Psychiatry and Behavioral Health, Ohio State University, Columbus, OH, USA
| | - Ananda B Amstadter
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, USA
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27
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Flippo KH, Trammell SAJ, Gillum MP, Aklan I, Perez MB, Yavuz Y, Smith NK, Jensen-Cody SO, Zhou B, Claflin KE, Beierschmitt A, Fink-Jensen A, Knop FK, Palmour RM, Grueter BA, Atasoy D, Potthoff MJ. FGF21 suppresses alcohol consumption through an amygdalo-striatal circuit. Cell Metab 2022; 34:317-328.e6. [PMID: 35108517 PMCID: PMC9093612 DOI: 10.1016/j.cmet.2021.12.024] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 11/11/2021] [Accepted: 12/23/2021] [Indexed: 02/08/2023]
Abstract
Excessive alcohol consumption is a major health and social issue in our society. Pharmacologic administration of the endocrine hormone fibroblast growth factor 21 (FGF21) suppresses alcohol consumption through actions in the brain in rodents, and genome-wide association studies have identified single nucleotide polymorphisms in genes involved with FGF21 signaling as being associated with increased alcohol consumption in humans. However, the neural circuit(s) through which FGF21 signals to suppress alcohol consumption are unknown, as are its effects on alcohol consumption in higher organisms. Here, we demonstrate that administration of an FGF21 analog to alcohol-preferring non-human primates reduces alcohol intake by 50%. Further, we reveal that FGF21 suppresses alcohol consumption through a projection-specific subpopulation of KLB-expressing neurons in the basolateral amygdala. Our results illustrate how FGF21 suppresses alcohol consumption through a specific population of neurons in the brain and demonstrate its therapeutic potential in non-human primate models of excessive alcohol consumption.
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Affiliation(s)
- Kyle H Flippo
- Department of Neuroscience and Pharmacology, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA; Fraternal Order of Eagles Diabetes Research Center, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA; Iowa Neuroscience Institute, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA.
| | - Samuel A J Trammell
- Section for Nutrient and Metabolite Sensing, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Matthew P Gillum
- Section for Nutrient and Metabolite Sensing, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Iltan Aklan
- Department of Neuroscience and Pharmacology, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA; Fraternal Order of Eagles Diabetes Research Center, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA; Iowa Neuroscience Institute, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA
| | - Misty B Perez
- Department of Neuroscience and Pharmacology, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA; Fraternal Order of Eagles Diabetes Research Center, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA; Iowa Neuroscience Institute, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA
| | - Yavuz Yavuz
- Department of Neuroscience and Pharmacology, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA; Fraternal Order of Eagles Diabetes Research Center, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA; Iowa Neuroscience Institute, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA
| | - Nicholas K Smith
- Department of Anesthesiology, Vanderbilt University, Nashville, TN 37323, USA
| | - Sharon O Jensen-Cody
- Department of Neuroscience and Pharmacology, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA; Fraternal Order of Eagles Diabetes Research Center, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA; Iowa Neuroscience Institute, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA
| | - Bolu Zhou
- Department of Neuroscience and Pharmacology, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA; Fraternal Order of Eagles Diabetes Research Center, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA; Iowa Neuroscience Institute, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA
| | - Kristin E Claflin
- Department of Neuroscience and Pharmacology, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA; Fraternal Order of Eagles Diabetes Research Center, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA; Iowa Neuroscience Institute, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA
| | - Amy Beierschmitt
- School of Veterinary Medicine, Ross University, Basseterre KN 0101, Saint Kitts and Nevis; Behavioral Science Foundation, Basseterre KN 0101, Saint Kitts and Nevis
| | - Anders Fink-Jensen
- Laboratory of Neuropsychiatry, Psychiatric Centre Copenhagen and University Hospital of Copenhagen, Edel Sauntes Allé 10, DK-2100 Copenhagen, Denmark
| | - Filip K Knop
- Center for Clinical Metabolic Research, Gentofte Hospital, University of Copenhagen, Gentofte Hospitalsvej 7, 3rd floor, DK-2900 Hellerup, Denmark; Steno Diabetes Center Copenhagen, 2820 Gentofte, Denmark
| | - Roberta M Palmour
- Behavioral Science Foundation, Basseterre KN 0101, Saint Kitts and Nevis; Departments of Psychiatry and Human Genetics, McGill University, Montreal, QC, Canada
| | - Brad A Grueter
- Department of Anesthesiology, Vanderbilt University, Nashville, TN 37323, USA
| | - Deniz Atasoy
- Department of Neuroscience and Pharmacology, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA; Fraternal Order of Eagles Diabetes Research Center, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA; Iowa Neuroscience Institute, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA
| | - Matthew J Potthoff
- Department of Neuroscience and Pharmacology, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA; Fraternal Order of Eagles Diabetes Research Center, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA; Iowa Neuroscience Institute, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA; Department of Veterans Affairs Medical Center, Iowa City, IA 52242, USA.
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28
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Gunturkun MH, Wang T, Chitre AS, Garcia Martinez A, Holl K, St Pierre C, Bimschleger H, Gao J, Cheng R, Polesskaya O, Solberg Woods LC, Palmer AA, Chen H. Genome-Wide Association Study on Three Behaviors Tested in an Open Field in Heterogeneous Stock Rats Identifies Multiple Loci Implicated in Psychiatric Disorders. Front Psychiatry 2022; 13:790566. [PMID: 35237186 PMCID: PMC8882588 DOI: 10.3389/fpsyt.2022.790566] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Accepted: 01/18/2022] [Indexed: 12/05/2022] Open
Abstract
Many personality traits are influenced by genetic factors. Rodents models provide an efficient system for analyzing genetic contribution to these traits. Using 1,246 adolescent heterogeneous stock (HS) male and female rats, we conducted a genome-wide association study (GWAS) of behaviors measured in an open field, including locomotion, novel object interaction, and social interaction. We identified 30 genome-wide significant quantitative trait loci (QTL). Using multiple criteria, including the presence of high impact genomic variants and co-localization of cis-eQTL, we identified 17 candidate genes (Adarb2, Ankrd26, Cacna1c, Cacng4, Clock, Ctu2, Cyp26b1, Dnah9, Gda, Grxcr1, Eva1a, Fam114a1, Kcnj9, Mlf2, Rab27b, Sec11a, and Ube2h) for these traits. Many of these genes have been implicated by human GWAS of various psychiatric or drug abuse related traits. In addition, there are other candidate genes that likely represent novel findings that can be the catalyst for future molecular and genetic insights into human psychiatric diseases. Together, these findings provide strong support for the use of the HS population to study psychiatric disorders.
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Affiliation(s)
- Mustafa Hakan Gunturkun
- Department of Pharmacology, Addiction Science and Toxicology, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Tengfei Wang
- Department of Pharmacology, Addiction Science and Toxicology, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Apurva S Chitre
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
| | - Angel Garcia Martinez
- Department of Pharmacology, Addiction Science and Toxicology, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Katie Holl
- Department of Internal Medicine, Wake Forest School of Medicine, Winston Salem, NC, United States
| | - Celine St Pierre
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
| | - Hannah Bimschleger
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
| | - Jianjun Gao
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
| | - Riyan Cheng
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
| | - Oksana Polesskaya
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
| | - Leah C Solberg Woods
- Department of Internal Medicine, Wake Forest School of Medicine, Winston Salem, NC, United States
| | - Abraham A Palmer
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States.,Institute for Genomic Medicine, University of California, San Diego, La Jolla, CA, United States
| | - Hao Chen
- Department of Pharmacology, Addiction Science and Toxicology, University of Tennessee Health Science Center, Memphis, TN, United States
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29
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Becker J, Burik CAP, Goldman G, Wang N, Jayashankar H, Bennett M, Belsky DW, Karlsson Linnér R, Ahlskog R, Kleinman A, Hinds DA, Caspi A, Corcoran DL, Moffitt TE, Poulton R, Sugden K, Williams BS, Harris KM, Steptoe A, Ajnakina O, Milani L, Esko T, Iacono WG, McGue M, Magnusson PKE, Mallard TT, Harden KP, Tucker-Drob EM, Herd P, Freese J, Young A, Beauchamp JP, Koellinger PD, Oskarsson S, Johannesson M, Visscher PM, Meyer MN, Laibson D, Cesarini D, Benjamin DJ, Turley P, Okbay A. Resource profile and user guide of the Polygenic Index Repository. Nat Hum Behav 2021; 5:1744-1758. [PMID: 34140656 PMCID: PMC8678380 DOI: 10.1038/s41562-021-01119-3] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Accepted: 04/16/2021] [Indexed: 02/05/2023]
Abstract
Polygenic indexes (PGIs) are DNA-based predictors. Their value for research in many scientific disciplines is growing rapidly. As a resource for researchers, we used a consistent methodology to construct PGIs for 47 phenotypes in 11 datasets. To maximize the PGIs' prediction accuracies, we constructed them using genome-wide association studies-some not previously published-from multiple data sources, including 23andMe and UK Biobank. We present a theoretical framework to help interpret analyses involving PGIs. A key insight is that a PGI can be understood as an unbiased but noisy measure of a latent variable we call the 'additive SNP factor'. Regressions in which the true regressor is this factor but the PGI is used as its proxy therefore suffer from errors-in-variables bias. We derive an estimator that corrects for the bias, illustrate the correction, and make a Python tool for implementing it publicly available.
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Affiliation(s)
- Joel Becker
- Department of Economics, New York University, New York, NY, USA
| | - Casper A P Burik
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Grant Goldman
- National Bureau of Economic Research, Cambridge, MA, USA
| | - Nancy Wang
- National Bureau of Economic Research, Cambridge, MA, USA
| | | | | | - Daniel W Belsky
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA
- Robert N. Butler Columbia Aging Center, Columbia University, New York, NY, USA
| | - Richard Karlsson Linnér
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Rafael Ahlskog
- Department of Government, Uppsala University, Uppsala, Sweden
| | | | | | - Avshalom Caspi
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
- Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
| | - David L Corcoran
- Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
| | - Terrie E Moffitt
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
- Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
| | - Richie Poulton
- Dunedin Multidisciplinary Health and Development Research Unit, University of Otago, Dunedin, New Zealand
| | - Karen Sugden
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | | | - Kathleen Mullan Harris
- Department of Sociology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Andrew Steptoe
- Department of Behavioural Science and Health, University College London, London, UK
| | - Olesya Ajnakina
- Department of Behavioural Science and Health, University College London, London, UK
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Lili Milani
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Tõnu Esko
- Institute of Genomics, University of Tartu, Tartu, Estonia
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - William G Iacono
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Matt McGue
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Patrik K E Magnusson
- Swedish Twin Registry, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Travis T Mallard
- Department of Psychology, The University of Texas at Austin, Austin, TX, USA
| | - K Paige Harden
- Department of Psychology, The University of Texas at Austin, Austin, TX, USA
- Population Research Center, The University of Texas at Austin, Austin, TX, USA
| | - Elliot M Tucker-Drob
- Department of Psychology, The University of Texas at Austin, Austin, TX, USA
- Population Research Center, The University of Texas at Austin, Austin, TX, USA
| | - Pamela Herd
- McCourt School of Public Policy, Georgetown University, Washington, DC, USA
| | - Jeremy Freese
- Department of Sociology, Stanford University, Stanford, CA, USA
| | - Alexander Young
- UCLA Anderson School of Management, Los Angeles, CA, USA
- Human Genetics Department, UCLA David Geffen School of Medicine, Los Angeles, CA, USA
| | - Jonathan P Beauchamp
- Interdisciplinary Center for Economic Science and Department of Economics, George Mason University, Fairfax, VA, USA
| | - Philipp D Koellinger
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Robert M. La Follette School of Public Affairs, University of Wisconsin-Madison, Madison, WI, USA
| | - Sven Oskarsson
- Department of Government, Uppsala University, Uppsala, Sweden
| | - Magnus Johannesson
- Department of Economics, Stockholm School of Economics, Stockholm, Sweden
| | - Peter M Visscher
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Michelle N Meyer
- Center for Translational Bioethics and Health Care Policy, Geisinger Health System, Danville, PA, USA
| | - David Laibson
- National Bureau of Economic Research, Cambridge, MA, USA
- Department of Economics, Harvard University, Cambridge, MA, USA
| | - David Cesarini
- Department of Economics, New York University, New York, NY, USA.
- National Bureau of Economic Research, Cambridge, MA, USA.
| | - Daniel J Benjamin
- National Bureau of Economic Research, Cambridge, MA, USA.
- UCLA Anderson School of Management, Los Angeles, CA, USA.
- Human Genetics Department, UCLA David Geffen School of Medicine, Los Angeles, CA, USA.
| | - Patrick Turley
- Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA.
- Department of Economics, University of Southern California, Los Angeles, CA, USA.
| | - Aysu Okbay
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
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30
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Mallard TT, Sanchez-Roige S. Dimensional Phenotypes in Psychiatric Genetics: Lessons from Genome-Wide Association Studies of Alcohol Use Phenotypes. Complex Psychiatry 2021; 7:45-48. [PMID: 35083441 PMCID: PMC8739983 DOI: 10.1159/000518863] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Accepted: 07/08/2021] [Indexed: 12/14/2022] Open
Affiliation(s)
- Travis T. Mallard
- Department of Psychology, University of Texas at Austin, Austin, Texas, USA
| | - Sandra Sanchez-Roige
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
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31
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Dao C, Zhou H, Small A, Gordon KS, Li B, Kember RL, Ye Y, Gelernter J, Xu K, Kranzler HR, Zhao H, Justice AC. The impact of removing former drinkers from genome-wide association studies of AUDIT-C. Addiction 2021; 116:3044-3054. [PMID: 33861876 PMCID: PMC9377185 DOI: 10.1111/add.15511] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Revised: 11/27/2020] [Accepted: 03/24/2021] [Indexed: 11/30/2022]
Abstract
BACKGROUND AND AIMS The Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) questionnaire screens for harmful drinking using a 12-month timeframe. A score of 0 is assigned to individuals who report abstaining from alcohol in the past year. However, many middle-age individuals reporting current abstinence are former drinkers (FDs). Because FDs may be more genetically prone to harmful alcohol use than lifelong abstainers (LAs) and are often combined with LAs, we evaluated the impact of differentiating them on the identification of genetic association. DESIGN AND SETTING The United Kingdom Biobank (UKBB) includes AUDIT-C and alcohol drinker status. PARTICIPANTS 131 510 Europeans, including 5135 FDs. MEASUREMENTS We compared three genome-wide association (GWAS) analyses to explore the effects of removing FDs: the full AUDIT-C data, AUDIT-C data without FDs, and data from a random sample numerically matched to the data without FDs. Because prior studies show a consistent association of the ADH1B polymorphism rs1229984 with both alcohol consumption and alcohol use disorder, we compared allele frequencies for rs1229984 stratified by AUDIT-C value and FD versus LA status. Additionally, we calculated polygenic risk scores (PRS) of related diseases. FINDINGS The rs1229984 allele frequencies among FDs were numerically comparable to those with high AUDIT-C scores and very different from those of LAs. Removing FDs from GWAS yielded a stronger association with rs1229984 (P value after removal: 1.9 × 10-70 vs 1.7 × 10-65 and 2.5 × 10-62 ), more statistically significant single nucleotide polymorphisms (SNPs) (after removal: 11 vs 9 and 8), and genomic loci (after removal: 11 vs 9 and 7). Additional independent SNPs were identified after removal of FDs: rs2817866 (PTGER3), rs7105867 (ANO3), and rs17601612 (DRD2). For PRS of alcohol use disorder and major depressive disorder, there are statistically significant differences between FDs and LAs. CONCLUSIONS Differentiating between former drinkers and lifelong abstainers can improve Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) genome-wide association results.
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Affiliation(s)
- Cecilia Dao
- Yale University School of Public Health, New Haven, CT, USA,Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Hang Zhou
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA,Yale University School of Medicine, New Haven, CT, USA
| | - Aeron Small
- Yale University School of Medicine, New Haven, CT, USA
| | - Kirsha S. Gordon
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA,Yale University School of Medicine, New Haven, CT, USA
| | - Boyang Li
- Yale University School of Public Health, New Haven, CT, USA,Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Rachel L. Kember
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA,Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
| | - Yixuan Ye
- Yale University School of Public Health, New Haven, CT, USA
| | - Joel Gelernter
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA,Yale University School of Medicine, New Haven, CT, USA
| | - Ke Xu
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA,Yale University School of Medicine, New Haven, CT, USA
| | - Henry R. Kranzler
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA,Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
| | - Hongyu Zhao
- Yale University School of Public Health, New Haven, CT, USA,Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA,Yale University School of Medicine, New Haven, CT, USA
| | - Amy C. Justice
- Yale University School of Public Health, New Haven, CT, USA,Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA,Yale University School of Medicine, New Haven, CT, USA
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Abstract
Substance use disorders (SUDs) are prevalent and result in an array of negative consequences. They are influenced by genetic factors (h2 = ~50%). Recent years have brought substantial progress in our understanding of the genetic etiology of SUDs and related traits. The present review covers the current state of the field for SUD genetics, including the epidemiology and genetic epidemiology of SUDs, findings from the first-generation of SUD genome-wide association studies (GWAS), cautions about translating GWAS findings to clinical settings, and suggested prioritizations for the next wave of SUD genetics efforts. Recent advances in SUD genetics have been facilitated by the assembly of large GWAS samples, and the development of state-of-the-art methods modeling the aggregate effect of genome-wide variation. These advances have confirmed that SUDs are highly polygenic with many variants across the genome conferring risk, the vast majority of which are of small effect. Downstream analyses have enabled finer resolution of the genetic architecture of SUDs and revealed insights into their genetic relationship with other psychiatric disorders. Recent efforts have also prioritized a closer examination of GWAS findings that have suggested non-uniform genetic influences across measures of substance use (e.g. consumption) and problematic use (e.g. SUD). Additional highlights from recent SUD GWAS include the robust confirmation of loci in alcohol metabolizing genes (e.g. ADH1B and ALDH2) affecting alcohol-related traits, and loci within the CHRNA5-CHRNA3-CHRNB4 gene cluster influencing nicotine-related traits. Similar successes are expected for cannabis, opioid, and cocaine use disorders as sample sizes approach those assembled for alcohol and nicotine.
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Affiliation(s)
- Joseph D. Deak
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Emma C. Johnson
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
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Kapoor M, Chao MJ, Johnson EC, Novikova G, Lai D, Meyers JL, Schulman J, Nurnberger JI, Porjesz B, Liu Y, Foroud T, Edenberg HJ, Marcora E, Agrawal A, Goate A. Multi-omics integration analysis identifies novel genes for alcoholism with potential overlap with neurodegenerative diseases. Nat Commun 2021; 12:5071. [PMID: 34417470 PMCID: PMC8379159 DOI: 10.1038/s41467-021-25392-y] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Accepted: 08/03/2021] [Indexed: 11/27/2022] Open
Abstract
Identification of causal variants and genes underlying genome-wide association study (GWAS) loci is essential to understand the biology of alcohol use disorder (AUD) and drinks per week (DPW). Multi-omics integration approaches have shown potential for fine mapping complex loci to obtain biological insights to disease mechanisms. In this study, we use multi-omics approaches, to fine-map AUD and DPW associations at single SNP resolution to demonstrate that rs56030824 on chromosome 11 significantly reduces SPI1 mRNA expression in myeloid cells and lowers risk for AUD and DPW. Our analysis also identifies MAPT as a candidate causal gene specifically associated with DPW. Genes prioritized in this study show overlap with causal genes associated with neurodegenerative disorders. Multi-omics integration analyses highlight, genetic similarities and differences between alcohol intake and disordered drinking, suggesting molecular heterogeneity that might inform future targeted functional and cross-species studies.
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Affiliation(s)
- Manav Kapoor
- Departments of Genetics and Genomic Sciences and Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Michael J Chao
- Departments of Genetics and Genomic Sciences and Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Emma C Johnson
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Gloriia Novikova
- Departments of Genetics and Genomic Sciences and Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Dongbing Lai
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Jacquelyn L Meyers
- Department of Psychiatry, State University of New York, Downstate Medical Center, Brooklyn, NY, USA
| | - Jessica Schulman
- Departments of Genetics and Genomic Sciences and Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - John I Nurnberger
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Bernice Porjesz
- Department of Psychiatry, State University of New York, Downstate Medical Center, Brooklyn, NY, USA
| | - Yunlong Liu
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Tatiana Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Howard J Edenberg
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Edoardo Marcora
- Departments of Genetics and Genomic Sciences and Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Alison Goate
- Departments of Genetics and Genomic Sciences and Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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Clarke TK, Adams MJ, Howard DM, Xia C, Davies G, Hayward C, Campbell A, Padmanabhan S, Smith BH, Murray A, Porteous D, Deary IJ, McIntosh AM. Genetic and shared couple environmental contributions to smoking and alcohol use in the UK population. Mol Psychiatry 2021; 26:4344-4354. [PMID: 31767999 PMCID: PMC8550945 DOI: 10.1038/s41380-019-0607-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/20/2019] [Revised: 11/07/2019] [Accepted: 11/13/2019] [Indexed: 11/22/2022]
Abstract
Alcohol use and smoking are leading causes of death and disability worldwide. Both genetic and environmental factors have been shown to influence individual differences in the use of these substances. In the present study we tested whether genetic factors, modelled alongside common family environment, explained phenotypic variance in alcohol use and smoking behaviour in the Generation Scotland (GS) family sample of up to 19,377 individuals. SNP and pedigree-associated effects combined explained between 18 and 41% of the variance in substance use. Shared couple effects explained a significant amount of variance across all substance use traits, particularly alcohol intake, for which 38% of the phenotypic variance was explained. We tested whether the within-couple substance use associations were due to assortative mating by testing the association between partner polygenic risk scores in 34,987 couple pairs from the UK Biobank (UKB). No significant association between partner polygenic risk scores were observed. Associations between an individual's alcohol PRS (b = 0.05, S.E. = 0.006, p < 2 × 10-16) and smoking status PRS (b = 0.05, S.E. = 0.005, p < 2 × 10-16) were found with their partner's phenotype. In support of this, G carriers of a functional ADH1B polymorphism (rs1229984), known to be associated with greater alcohol intake, were found to consume less alcohol if they had a partner who carried an A allele at this SNP. Together these results show that the shared couple environment contributes significantly to patterns of substance use. It is unclear whether this is due to shared environmental factors, assortative mating, or indirect genetic effects. Future studies would benefit from longitudinal data and larger sample sizes to assess this further.
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Affiliation(s)
- Toni-Kim Clarke
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK.
| | - Mark J Adams
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - David M Howard
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - Charley Xia
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Gail Davies
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Archie Campbell
- Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
- Centre for Genomic and Experimental Medicine, Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Sandosh Padmanabhan
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Blair H Smith
- Division of Population and Health Genomics, University of Dundee, Dundee, UK
| | - Alison Murray
- The Institute of Medical Sciences, Aberdeen Biomedical Imaging Centre, University of Aberdeen, Aberdeen, UK
| | - David Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Ian J Deary
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Andrew M McIntosh
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
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35
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Luderer M, Ramos Quiroga JA, Faraone SV, Zhang James Y, Reif A. Alcohol use disorders and ADHD. Neurosci Biobehav Rev 2021; 128:648-660. [PMID: 34265320 DOI: 10.1016/j.neubiorev.2021.07.010] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 07/05/2021] [Accepted: 07/09/2021] [Indexed: 12/18/2022]
Abstract
Despite a growing literature on the complex bidirectional relationship of ADHD and substance use, reviews specifically focusing on alcohol are scarce. ADHD and AUD show a significant genetic overlap, including genes involved in gluatamatergic and catecholaminergic neurotransmission. ADHD drives risky behavior and negative experiences throughout the lifespan that subsequently enhance a genetically increased risk for Alcohol Use Disorders (AUD). Impulsive decisions and a maladaptive reward system make individuals with ADHD vulnerable for alcohol use and up to 43 % develop an AUD; in adults with AUD, ADHD occurs in about 20 %, but is vastly under-recognized and under-treated. Thus, routine screening and treatment procedures need to be implemented in AUD treatment. Long-acting stimulants or non-stimulants can be used to treat ADHD in individuals with AUD. However, it is crucial to combine medical treatment for ADHD with pharmacotherapy and psychotherapy for AUD, and other comorbid disorders. Identification of individuals at risk for AUD, especially those with ADHD and conduct disorder or oppositional defiant disorder, is a key factor to prevent negative outcomes.
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Affiliation(s)
- Mathias Luderer
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital, Goethe University, Frankfurt, Frankfurt am Main, Germany.
| | - Josep Antoni Ramos Quiroga
- Department of Psychiatry, Hospital Universitari Vall d'Hebron, Barcelona, Catalonia, Spain; Department of Psychiatryand Forensic Medicine, Universitat Autònoma deBarcelona, Bellaterra, Catalonia, Spain; Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Institut de Recerca (VHIR), Barcelona, Catalonia, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Barcelona, Catalonia, Spain
| | - Stephen V Faraone
- Department of Psychiatry and Behavioral Sciences, SUNY Upstate Medical University, Syracuse, NY, USA; Department of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Yanli Zhang James
- Department of Psychiatry and Behavioral Sciences, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Andreas Reif
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital, Goethe University, Frankfurt, Frankfurt am Main, Germany
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36
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The Cocaine and Oxycodone Biobanks, Two Repositories from Genetically Diverse and Behaviorally Characterized Rats for the Study of Addiction. eNeuro 2021; 8:ENEURO.0033-21.2021. [PMID: 33875455 PMCID: PMC8213442 DOI: 10.1523/eneuro.0033-21.2021] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 03/26/2021] [Accepted: 03/31/2021] [Indexed: 11/21/2022] Open
Abstract
The rat oxycodone and cocaine biobanks contain samples that vary by genotypes (by using genetically diverse genotyped HS rats), phenotypes (by measuring addiction-like behaviors in an advanced SA model), timepoints (samples are collected longitudinally before, during, and after SA, and terminally at three different timepoints in the addiction cycle: intoxication, withdrawal, and abstinence or without exposure to drugs through age-matched naive rats), samples collected (organs, cells, biofluids, feces), preservation (paraformaldehyde-fixed, snap-frozen, or cryopreserved) and application (proteomics, transcriptomics, microbiomics, metabolomics, epigenetics, anatomy, circuitry analysis, biomarker discovery, etc.Substance use disorders (SUDs) are pervasive in our society and have substantial personal and socioeconomical costs. A critical hurdle in identifying biomarkers and novel targets for medication development is the lack of resources for obtaining biological samples with a detailed behavioral characterization of SUD. Moreover, it is nearly impossible to find longitudinal samples. As part of two ongoing large-scale behavioral genetic studies in heterogeneous stock (HS) rats, we have created two preclinical biobanks using well-validated long access (LgA) models of intravenous cocaine and oxycodone self-administration (SA) and comprehensive characterization of addiction-related behaviors. The genetic diversity in HS rats mimics diversity in the human population and includes individuals that are vulnerable or resilient to compulsive-like responding for cocaine or oxycodone. Longitudinal samples are collected throughout the experiment, before exposure to the drug, during intoxication, acute withdrawal, and protracted abstinence, and include naive, age-matched controls. Samples include, but are not limited to, blood plasma, feces and urine, whole brains, brain slices and punches, kidney, liver, spleen, ovary, testis, and adrenal glands. Three preservation methods (fixed in formaldehyde, snap-frozen, or cryopreserved) are used to facilitate diverse downstream applications such as proteomics, metabolomics, transcriptomics, epigenomics, microbiomics, neuroanatomy, biomarker discovery, and other cellular and molecular approaches. To date, >20,000 samples have been collected from over 1000 unique animals and made available free of charge to non-profit institutions through https://www.cocainebiobank.org/ and https://www.oxycodonebiobank.org/.
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37
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Johnson EC, Sanchez-Roige S, Acion L, Adams MJ, Bucholz KK, Chan G, Chao MJ, Chorlian DB, Dick DM, Edenberg HJ, Foroud T, Hayward C, Heron J, Hesselbrock V, Hickman M, Kendler KS, Kinreich S, Kramer J, Kuo SIC, Kuperman S, Lai D, McIntosh AM, Meyers JL, Plawecki MH, Porjesz B, Porteous D, Schuckit MA, Su J, Zang Y, Palmer AA, Agrawal A, Clarke TK, Edwards AC. Polygenic contributions to alcohol use and alcohol use disorders across population-based and clinically ascertained samples. Psychol Med 2021; 51:1147-1156. [PMID: 31955720 PMCID: PMC7405725 DOI: 10.1017/s0033291719004045] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
BACKGROUND Studies suggest that alcohol consumption and alcohol use disorders have distinct genetic backgrounds. METHODS We examined whether polygenic risk scores (PRS) for consumption and problem subscales of the Alcohol Use Disorders Identification Test (AUDIT-C, AUDIT-P) in the UK Biobank (UKB; N = 121 630) correlate with alcohol outcomes in four independent samples: an ascertained cohort, the Collaborative Study on the Genetics of Alcoholism (COGA; N = 6850), and population-based cohorts: Avon Longitudinal Study of Parents and Children (ALSPAC; N = 5911), Generation Scotland (GS; N = 17 461), and an independent subset of UKB (N = 245 947). Regression models and survival analyses tested whether the PRS were associated with the alcohol-related outcomes. RESULTS In COGA, AUDIT-P PRS was associated with alcohol dependence, AUD symptom count, maximum drinks (R2 = 0.47-0.68%, p = 2.0 × 10-8-1.0 × 10-10), and increased likelihood of onset of alcohol dependence (hazard ratio = 1.15, p = 4.7 × 10-8); AUDIT-C PRS was not an independent predictor of any phenotype. In ALSPAC, the AUDIT-C PRS was associated with alcohol dependence (R2 = 0.96%, p = 4.8 × 10-6). In GS, AUDIT-C PRS was a better predictor of weekly alcohol use (R2 = 0.27%, p = 5.5 × 10-11), while AUDIT-P PRS was more associated with problem drinking (R2 = 0.40%, p = 9.0 × 10-7). Lastly, AUDIT-P PRS was associated with ICD-based alcohol-related disorders in the UKB subset (R2 = 0.18%, p < 2.0 × 10-16). CONCLUSIONS AUDIT-P PRS was associated with a range of alcohol-related phenotypes across population-based and ascertained cohorts, while AUDIT-C PRS showed less utility in the ascertained cohort. We show that AUDIT-P is genetically correlated with both use and misuse and demonstrate the influence of ascertainment schemes on PRS analyses.
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Affiliation(s)
- Emma C Johnson
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Sandra Sanchez-Roige
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Laura Acion
- Department of Psychiatry, University of Iowa, Carver College of Medicine, Iowa City, IA, USA
| | - Mark J Adams
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Kathleen K Bucholz
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Grace Chan
- Department of Psychiatry, University of Connecticut School of Medicine, Farmington, CT, USA
| | - Michael J Chao
- Department of Neuroscience, Icahn School of Medicine at Mt. Sinai, New York, NY, USA
| | - David B Chorlian
- Department of Psychiatry, Suny Downstate Medical Center, Brooklyn, NY, USA
| | - Danielle M Dick
- Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Howard J Edenberg
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Tatiana Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Caroline Hayward
- MRC Human Genetics Unit, University of Edinburgh, Institute of Genetics and Molecular Medicine, Edinburgh, UK
| | - Jon Heron
- University of Bristol, Bristol Medical School, Population Health Sciences, Bristol, UK
| | - Victor Hesselbrock
- Department of Psychiatry, University of Connecticut School of Medicine, Farmington, CT, USA
| | - Matthew Hickman
- University of Bristol, Bristol Medical School, Population Health Sciences, Bristol, UK
| | - Kenneth S Kendler
- Department of Psychiatry, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
| | - Sivan Kinreich
- Department of Psychiatry, Suny Downstate Medical Center, Brooklyn, NY, USA
| | - John Kramer
- Department of Psychiatry, University of Iowa, Carver College of Medicine, Iowa City, IA, USA
| | - Sally I-Chun Kuo
- Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA
| | - Samuel Kuperman
- Department of Psychiatry, University of Iowa, Carver College of Medicine, Iowa City, IA, USA
| | - Dongbing Lai
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | | | - Jacquelyn L Meyers
- Department of Psychiatry, Suny Downstate Medical Center, Brooklyn, NY, USA
| | - Martin H Plawecki
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Bernice Porjesz
- Department of Psychiatry, Suny Downstate Medical Center, Brooklyn, NY, USA
| | - David Porteous
- University of Edinburgh, Institute of Genetics & Molecular Medicine, Centre for Genomic and Experimental Medicine, Edinburgh, UK
| | - Marc A Schuckit
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Jinni Su
- Department of Psychology, Arizona State University, Tempe, AZ, USA
| | - Yong Zang
- Department of Biostatistics, Indiana University School of Medicine, Bloomington, IN, USA
| | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
- University of California San Diego, Institute for Genomic Medicine, San Diego, CA, USA
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Toni-Kim Clarke
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Alexis C Edwards
- Department of Psychiatry, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
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Palmer RHC, Johnson EC, Won H, Polimanti R, Kapoor M, Chitre A, Bogue MA, Benca‐Bachman CE, Parker CC, Verma A, Reynolds T, Ernst J, Bray M, Kwon SB, Lai D, Quach BC, Gaddis NC, Saba L, Chen H, Hawrylycz M, Zhang S, Zhou Y, Mahaffey S, Fischer C, Sanchez‐Roige S, Bandrowski A, Lu Q, Shen L, Philip V, Gelernter J, Bierut LJ, Hancock DB, Edenberg HJ, Johnson EO, Nestler EJ, Barr PB, Prins P, Smith DJ, Akbarian S, Thorgeirsson T, Walton D, Baker E, Jacobson D, Palmer AA, Miles M, Chesler EJ, Emerson J, Agrawal A, Martone M, Williams RW. Integration of evidence across human and model organism studies: A meeting report. GENES, BRAIN, AND BEHAVIOR 2021; 20:e12738. [PMID: 33893716 PMCID: PMC8365690 DOI: 10.1111/gbb.12738] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/20/2021] [Revised: 04/11/2021] [Accepted: 04/21/2021] [Indexed: 12/13/2022]
Abstract
The National Institute on Drug Abuse and Joint Institute for Biological Sciences at the Oak Ridge National Laboratory hosted a meeting attended by a diverse group of scientists with expertise in substance use disorders (SUDs), computational biology, and FAIR (Findability, Accessibility, Interoperability, and Reusability) data sharing. The meeting's objective was to discuss and evaluate better strategies to integrate genetic, epigenetic, and 'omics data across human and model organisms to achieve deeper mechanistic insight into SUDs. Specific topics were to (a) evaluate the current state of substance use genetics and genomics research and fundamental gaps, (b) identify opportunities and challenges of integration and sharing across species and data types, (c) identify current tools and resources for integration of genetic, epigenetic, and phenotypic data, (d) discuss steps and impediment related to data integration, and (e) outline future steps to support more effective collaboration-particularly between animal model research communities and human genetics and clinical research teams. This review summarizes key facets of this catalytic discussion with a focus on new opportunities and gaps in resources and knowledge on SUDs.
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Affiliation(s)
- Rohan H. C. Palmer
- Behavioral Genetics of Addiction Laboratory, Department of PsychologyEmory UniversityAtlantaGeorgiaUSA
| | - Emma C. Johnson
- Department of PsychiatryWashington University School of MedicineSt. LouisMissouriUSA
| | - Hyejung Won
- Department of Genetics and Neuroscience CenterUniversity of North Carolina at Chapel HillChapel HillNorth CarolinaUSA
| | - Renato Polimanti
- Department of PsychiatryYale University School of MedicineWest HavenConnecticutUSA
| | - Manav Kapoor
- Nash Family Department of Neuroscience and Friedman Brain InstituteIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Apurva Chitre
- Department of PsychiatryUniversity of California, San DiegoLa JollaCaliforniaUSA
| | | | - Chelsie E. Benca‐Bachman
- Behavioral Genetics of Addiction Laboratory, Department of PsychologyEmory UniversityAtlantaGeorgiaUSA
| | - Clarissa C. Parker
- Department of Psychology and Program in NeuroscienceMiddlebury CollegeMiddleburyVermontUSA
| | - Anurag Verma
- Biomedical and Translational Informatics LaboratoryUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | | | - Jason Ernst
- Department of Biological ChemistryUniversity of California Los AngelesLos AngelesCaliforniaUSA
| | - Michael Bray
- Department of PsychiatryWashington University School of MedicineSt. LouisMissouriUSA
| | - Soo Bin Kwon
- Department of Biological ChemistryUniversity of California Los AngelesLos AngelesCaliforniaUSA
| | - Dongbing Lai
- Department of Medical and Molecular GeneticsIndiana University School of MedicineIndianapolisIndianaUSA
| | - Bryan C. Quach
- GenOmics, Bioinformatics, and Translational Research Center, Biostatistics and Epidemiology DivisionRTI InternationalResearch Triangle ParkNorth CarolinaUSA
| | - Nathan C. Gaddis
- GenOmics, Bioinformatics, and Translational Research Center, Biostatistics and Epidemiology DivisionRTI InternationalResearch Triangle ParkNorth CarolinaUSA
| | - Laura Saba
- Department of Pharmaceutical SciencesUniversity of Colorado, Anschutz Medical CampusAuroraColoradoUSA
| | - Hao Chen
- Department of Pharmacology, Addiction Science, and ToxicologyUniversity of Tennessee Health Science CenterMemphisTennesseeUSA
| | | | - Shan Zhang
- Department of Statistics and ProbabilityMichigan State UniversityEast LansingMichiganUSA
| | - Yuan Zhou
- Department of Department of BiostatisticsUniversity of FloridaGainesvilleFloridaUSA
| | - Spencer Mahaffey
- Department of Pharmaceutical Sciences, School of PharmacyUniversity of Colorado DenverAuroraColoradoUSA
| | - Christian Fischer
- Department of Genetics, Genomics and InformaticsUniversity of Tennessee Health Science CenterMemphisTennesseeUSA
| | - Sandra Sanchez‐Roige
- Department of PsychiatryUniversity of California, San DiegoLa JollaCaliforniaUSA
| | - Anita Bandrowski
- Department of NeuroscienceUniversity of California, San DiegoLa JollaCaliforniaUSA
| | - Qing Lu
- Department of Department of BiostatisticsUniversity of FloridaGainesvilleFloridaUSA
| | - Li Shen
- Nash Family Department of Neuroscience and Friedman Brain InstituteIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | | | - Joel Gelernter
- Department of PsychiatryYale University School of MedicineWest HavenConnecticutUSA
| | - Laura J. Bierut
- Department of PsychiatryWashington University School of MedicineSt. LouisMissouriUSA
| | - Dana B. Hancock
- GenOmics, Bioinformatics, and Translational Research Center, Biostatistics and Epidemiology DivisionRTI InternationalResearch Triangle ParkNorth CarolinaUSA
| | - Howard J. Edenberg
- Department of Medical and Molecular GeneticsIndiana University School of MedicineIndianapolisIndianaUSA
- Department of Biochemistry and Molecular BiologyIndiana University School of MedicineIndianapolisIndianaUSA
| | - Eric O. Johnson
- GenOmics, Bioinformatics, and Translational Research Center, Biostatistics and Epidemiology DivisionRTI InternationalResearch Triangle ParkNorth CarolinaUSA
| | - Eric J. Nestler
- Nash Family Department of Neuroscience and Friedman Brain InstituteIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Peter B. Barr
- Department of PsychologyVirginia Commonwealth UniversityRichmondVirginiaUSA
| | - Pjotr Prins
- Department of Genetics, Genomics and InformaticsUniversity of Tennessee Health Science CenterMemphisTennesseeUSA
| | - Desmond J. Smith
- Department of Molecular and Medical PharmacologyDavid Geffen School of Medicine, UCLALos AngelesCaliforniaUSA
| | - Schahram Akbarian
- Friedman Brain Institute and Departments of Psychiatry and NeuroscienceIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | | | | | - Erich Baker
- Department of Computer ScienceBaylor UniversityWacoTexasUSA
| | - Daniel Jacobson
- Computational and Predictive Biology, BiosciencesOak Ridge National LaboratoryOak RidgeTennesseeUSA
- Department of PsychologyUniversity of Tennessee KnoxvilleKnoxvilleTennesseeUSA
| | - Abraham A. Palmer
- Department of PsychiatryUniversity of California, San DiegoLa JollaCaliforniaUSA
- Institute for Genomic Medicine, University of California San DiegoLa JollaCaliforniaUSA
| | - Michael Miles
- Department of Pharmacology and ToxicologyVirginia Commonwealth UniversityRichmondVirginiaUSA
| | | | | | - Arpana Agrawal
- Department of PsychiatryWashington University School of MedicineSt. LouisMissouriUSA
| | - Maryann Martone
- Department of NeuroscienceUniversity of California, San DiegoLa JollaCaliforniaUSA
| | - Robert W. Williams
- Department of Genetics, Genomics and InformaticsUniversity of Tennessee Health Science CenterMemphisTennesseeUSA
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Xue A, Jiang L, Zhu Z, Wray NR, Visscher PM, Zeng J, Yang J. Genome-wide analyses of behavioural traits are subject to bias by misreports and longitudinal changes. Nat Commun 2021; 12:20211. [PMID: 33436567 PMCID: PMC7804181 DOI: 10.1038/s41467-020-20237-6] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Accepted: 11/20/2020] [Indexed: 01/28/2023] Open
Abstract
Genome-wide association studies (GWAS) have discovered numerous genetic variants associated with human behavioural traits. However, behavioural traits are subject to misreports and longitudinal changes (MLC) which can cause biases in GWAS and follow-up analyses. Here, we demonstrate that individuals with higher disease burden in the UK Biobank (n = 455,607) are more likely to misreport or reduce their alcohol consumption levels, and propose a correction procedure to mitigate the MLC-induced biases. The alcohol consumption GWAS signals removed by the MLC corrections are enriched in metabolic/cardiovascular traits. Almost all the previously reported negative estimates of genetic correlations between alcohol consumption and common diseases become positive/non-significant after the MLC corrections. We also observe MLC biases for smoking and physical activities in the UK Biobank. Our findings provide a plausible explanation of the controversy about the effects of alcohol consumption on health outcomes and a caution for future analyses of self-reported behavioural traits in biobank data.
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Affiliation(s)
- Angli Xue
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Longda Jiang
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Zhihong Zhu
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Naomi R Wray
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Peter M Visscher
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Jian Zeng
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Jian Yang
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.
- School of Life Sciences, Westlake University, Hangzhou, Zhejiang, 310024, China.
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, 310024, China.
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40
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Oliveira PRS, de Matos LO, Araujo NM, Sant Anna HP, da Silva E Silva DA, Damasceno AKA, Martins de Carvalho L, Horta BL, Lima-Costa MF, Barreto ML, Wiers CE, Volkow ND, Brunialti Godard AL. LRRK2 Gene Variants Associated With a Higher Risk for Alcohol Dependence in Multiethnic Populations. Front Psychiatry 2021; 12:665257. [PMID: 34135785 PMCID: PMC8202767 DOI: 10.3389/fpsyt.2021.665257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Accepted: 04/12/2021] [Indexed: 11/22/2022] Open
Abstract
Background: Genetics influence the vulnerability to alcohol use disorders, and among the implicated genes, three previous studies have provided evidences for the involvement of LRRK2 in alcohol dependence (AD). LRRK2 expression is broadly dysregulated in postmortem brain from AD humans, as well as in the brain of mice with alcohol dependent-like behaviors and in a zebrafish model of alcohol preference. The aim of the present study was to evaluate the association of variants in the LRRK2 gene with AD in multiethnic populations from South and North America. Methods: Alcohol-screening questionnaires [such as CAGE and Alcohol Use Disorders Identification Test (AUDIT)] were used to determine individual risk of AD. Multivariate logistic regression analyses were done in three independent populations (898 individuals from Bambuí, Brazil; 3,015 individuals from Pelotas, Brazil; and 1,316 from the United States). Linkage disequilibrium and conditional analyses, as well as in silico functional analyses, were also conducted. Results: Four LRRK2 variants were significantly associated with AD in our discovery cohort (Bambuí): rs4768231, rs4767971, rs7307310, and rs1465527. Two of these variants (rs4768231 and rs4767971) were replicated in both Pelotas and US cohorts. The consistent association signal (at the LRRK2 locus) found in populations with different genetic backgrounds reinforces the relevance of our findings. Conclusion: Taken together, these results support the notion that genetic variants in the LRRK2 locus are risk factors for AD in humans.
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Affiliation(s)
- Pablo Rafael Silveira Oliveira
- Instituto de Biologia, Universidade Federal da Bahia, Salvador, Brazil.,Centro de Integração de Dados e Conhecimentos para Saúde, Fundação Oswaldo Cruz, Salvador, Brazil
| | - Lorena Oliveira de Matos
- Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Nathalia Matta Araujo
- Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Hanaísa P Sant Anna
- Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | | | - Andresa K Andrade Damasceno
- Instituto de Biologia, Universidade Federal da Bahia, Salvador, Brazil.,Centro de Integração de Dados e Conhecimentos para Saúde, Fundação Oswaldo Cruz, Salvador, Brazil
| | - Luana Martins de Carvalho
- Department of Psychiatry, Center for Alcohol Research in Epigenetics, University of Illinois, Chicago, IL, United States
| | - Bernardo L Horta
- Programa de Pos-Graduação em Epidemiologia, Universidade Federal de Pelotas, Pelotas, Brazil
| | | | - Mauricio Lima Barreto
- Centro de Integração de Dados e Conhecimentos para Saúde, Fundação Oswaldo Cruz, Salvador, Brazil
| | - Corinde E Wiers
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, United States
| | - Nora D Volkow
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, United States
| | - Ana Lúcia Brunialti Godard
- Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
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41
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Spence JP, Lai D, Reiter JL, Cao S, Bell RL, Williams KE, Liang T. Epigenetic changes on rat chromosome 4 contribute to disparate alcohol drinking behavior in alcohol-preferring and -nonpreferring rats. Alcohol 2020; 89:103-112. [PMID: 32798691 PMCID: PMC7722131 DOI: 10.1016/j.alcohol.2020.08.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2020] [Revised: 07/24/2020] [Accepted: 08/09/2020] [Indexed: 12/22/2022]
Abstract
BACKGROUND Paternal alcohol abuse is a well-recognized risk factor for the development of an alcohol use disorder (AUD). In addition to genetic and environmental risk factors, heritable epigenetic factors also have been proposed to play a key role in the development of AUD. However, it is not clear whether epigenetic factors contribute to the genetic inheritance in families affected by AUD. We used reciprocal crosses of the alcohol-preferring (P) and -nonpreferring (NP) rat lines to test whether epigenetic factors also impacted alcohol drinking in up to two generations of offspring. METHODS F1 offspring derived by reciprocal breeding of P and NP rats were tested for differences in alcohol consumption using a free-choice protocol of 10% ethanol, 20% ethanol, and water that were available concurrently. In a separate experiment, an F2 population was tested for alcohol consumption not only due to genetic differences. These rats were generated from inbred P (iP) and iNP rat lines that were reciprocally bred to produce genetically identical F1 offspring that remained alcohol-naïve. Intercrosses of the F1 generation animals produced the F2 generation. Alcohol consumption was then assessed in the F2 generation using a standard two-bottle choice protocol, and was analyzed using genome-wide linkage analysis. Alcohol consumption measures were also analyzed for sex differences. RESULTS Average alcohol consumption was higher in the F1 offspring of P vs. NP sires and in the F2 offspring of F0 iP vs. iNP grandsires. Linkage analyses showed the maximum LOD scores for alcohol consumption in both male and female offspring were on chromosome 4 (Chr 4). The LOD score for both sexes considered together was higher when the grandsire was iP vs. iNP (5.0 vs. 3.35, respectively). Furthermore, the F2 population displayed enhanced alcohol consumption when the P alleles from the F0 sire were present. CONCLUSIONS These results demonstrate that epigenetic and/or non-genetic factors mapping to rat chromosome 4 contribute to a transgenerational paternal effect on alcohol consumption in the P and NP rat model of AUD.
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Affiliation(s)
- John Paul Spence
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, 46202, United States
| | - Dongbing Lai
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, 46202, United States
| | - Jill L Reiter
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, 46202, United States
| | - Sha Cao
- Department of Biostatistics, Indiana University School of Medicine, Indianapolis, IN, 46202, United States
| | - Richard L Bell
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, 46202, United States
| | - Kent E Williams
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, 46202, United States
| | - Tiebing Liang
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, 46202, United States.
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42
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Cheng H, Sewda A, Marquez-Luna C, White SR, Whitney BM, Williams-Nguyen J, Nance RM, Lee WJ, Kitahata MM, Saag MS, Willig A, Eron JJ, Mathews WC, Hunt PW, Moore RD, Webel A, Mayer KH, Delaney JA, Crane PK, Crane HM, Hao K, Peter I. Genetic architecture of cardiometabolic risks in people living with HIV. BMC Med 2020; 18:288. [PMID: 33109212 PMCID: PMC7592520 DOI: 10.1186/s12916-020-01762-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Accepted: 08/24/2020] [Indexed: 01/16/2023] Open
Abstract
BACKGROUND Advances in antiretroviral therapies have greatly improved the survival of people living with human immunodeficiency virus (HIV) infection (PLWH); yet, PLWH have a higher risk of cardiovascular disease than those without HIV. While numerous genetic loci have been linked to cardiometabolic risk in the general population, genetic predictors of the excessive risk in PLWH are largely unknown. METHODS We screened for common and HIV-specific genetic variants associated with variation in lipid levels in 6284 PLWH (3095 European Americans [EA] and 3189 African Americans [AA]), from the Centers for AIDS Research Network of Integrated Clinical Systems cohort. Genetic hits found exclusively in the PLWH cohort were tested for association with other traits. We then assessed the predictive value of a series of polygenic risk scores (PRS) recapitulating the genetic burden for lipid levels, type 2 diabetes (T2D), and myocardial infarction (MI) in EA and AA PLWH. RESULTS We confirmed the impact of previously reported lipid-related susceptibility loci in PLWH. Furthermore, we identified PLWH-specific variants in genes involved in immune cell regulation and previously linked to HIV control, body composition, smoking, and alcohol consumption. Moreover, PLWH at the top of European-based PRS for T2D distribution demonstrated a > 2-fold increased risk of T2D compared to the remaining 95% in EA PLWH but to a much lesser degree in AA. Importantly, while PRS for MI was not predictive of MI risk in AA PLWH, multiethnic PRS significantly improved risk stratification for T2D and MI. CONCLUSIONS Our findings suggest that genetic loci involved in the regulation of the immune system and predisposition to risky behaviors contribute to dyslipidemia in the presence of HIV infection. Moreover, we demonstrate the utility of the European-based and multiethnic PRS for stratification of PLWH at a high risk of cardiometabolic diseases who may benefit from preventive therapies.
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Affiliation(s)
- Haoxiang Cheng
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY, 10029, United States of America
| | - Anshuman Sewda
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY, 10029, United States of America.,Institute of Health Management Research, IIHMR University, Jaipur, Rajasthan, India
| | - Carla Marquez-Luna
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Sierra R White
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY, 10029, United States of America
| | - Bridget M Whitney
- Department of Epidemiology, University of Washington School of Public Health, Seattle, WA, United States of America
| | - Jessica Williams-Nguyen
- Department of Epidemiology, University of Washington School of Public Health, Seattle, WA, United States of America
| | - Robin M Nance
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY, 10029, United States of America.,Department of Medicine, University of Washington School of Medicine, Seattle, WA, United States of America
| | - Won Jun Lee
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY, 10029, United States of America
| | - Mari M Kitahata
- Department of Medicine, University of Washington School of Medicine, Seattle, WA, United States of America.,Center for AIDS Research, University of Washington, Seattle, WA, United States of America
| | - Michael S Saag
- School of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States of America
| | - Amanda Willig
- School of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States of America
| | - Joseph J Eron
- Department of Medicine, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27514, United States of America
| | - W Christopher Mathews
- Department of Medicine, University of California San Diego, San Diego, CA, United States of America
| | - Peter W Hunt
- Division of Experimental Medicine, University of California San Francisco, San Francisco, CA, United States of America
| | - Richard D Moore
- Department of Medicine, Johns Hopkins University, Baltimore, MD, United States of America.,Department of Epidemiology,
- Johns Hopkins University, Baltimore, MD, United States of America
| | - Allison Webel
- Frances Payne Bolton School of Nursing, Case Western Reserve University, Cleveland, OH, United States of America
| | - Kenneth H Mayer
- The Fenway Institute at Fenway Health, Boston, MA, United States of America
| | - Joseph A Delaney
- Department of Epidemiology, University of Washington School of Public Health, Seattle, WA, United States of America
| | - Paul K Crane
- Department of Medicine, University of Washington School of Medicine, Seattle, WA, United States of America
| | - Heidi M Crane
- Department of Medicine, University of Washington School of Medicine, Seattle, WA, United States of America.,Center for AIDS Research, University of Washington, Seattle, WA, United States of America
| | - Ke Hao
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY, 10029, United States of America
| | - Inga Peter
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1425 Madison Avenue, New York, NY, 10029, United States of America.
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43
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Parker CC, Lusk R, Saba LM. Alcohol Sensitivity as an Endophenotype of Alcohol Use Disorder: Exploring Its Translational Utility between Rodents and Humans. Brain Sci 2020; 10:E725. [PMID: 33066036 PMCID: PMC7600833 DOI: 10.3390/brainsci10100725] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Revised: 10/06/2020] [Accepted: 10/09/2020] [Indexed: 12/21/2022] Open
Abstract
Alcohol use disorder (AUD) is a complex, chronic, relapsing disorder with multiple interacting genetic and environmental influences. Numerous studies have verified the influence of genetics on AUD, yet the underlying biological pathways remain unknown. One strategy to interrogate complex diseases is the use of endophenotypes, which deconstruct current diagnostic categories into component traits that may be more amenable to genetic research. In this review, we explore how an endophenotype such as sensitivity to alcohol can be used in conjunction with rodent models to provide mechanistic insights into AUD. We evaluate three alcohol sensitivity endophenotypes (stimulation, intoxication, and aversion) for their translatability across human and rodent research by examining the underlying neurobiology and its relationship to consumption and AUD. We show examples in which results gleaned from rodents are successfully integrated with information from human studies to gain insight in the genetic underpinnings of AUD and AUD-related endophenotypes. Finally, we identify areas for future translational research that could greatly expand our knowledge of the biological and molecular aspects of the transition to AUD with the broad hope of finding better ways to treat this devastating disorder.
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Affiliation(s)
- Clarissa C. Parker
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, VT 05753, USA
| | - Ryan Lusk
- Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA;
| | - Laura M. Saba
- Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA;
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44
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Anker E, Haavik J, Heir T. Alcohol and drug use disorders in adult attention-deficit/hyperactivity disorder: Prevalence and associations with attention-deficit/hyperactivity disorder symptom severity and emotional dysregulation. World J Psychiatry 2020; 10:202-211. [PMID: 33014721 PMCID: PMC7515748 DOI: 10.5498/wjp.v10.i9.202] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Revised: 07/11/2020] [Accepted: 08/15/2020] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND High risk of alcohol and drug use disorders in people with attention-deficit/hyperactivity disorder (ADHD) calls for exploratory research of relationships with clinical features of ADHD. AIM To estimate prevalence of alcohol/drug use disorders and associations with ADHD symptom severity and emotional dysregulation, in adults with ADHD. METHODS This observational cross-sectional clinical study consisted of patients admitted to a private psychiatric outpatient clinic in Oslo, Norway (2014-2018). Five-hundred and fifty-eight eligible patients diagnosed with ADHD (Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) criteria) agreed to participate. Alcohol and drug use disorders were diagnosed using the Mini International Neuropsychiatric Interview (MINI). Dependence and abuse were merged into "use" disorder as in MINI version 7.0/DSM-5. Questions were related both to lifetime and the past 12-mo. ADHD severity was assessed by the Adult ADHD Self Report Scale (ASRS). Subdivisions of the ASRS questionnaire as inattentive items and hyperactive/impulsivity items were recorded separately. Emotional dysregulation was assessed by the eight-item version of Barkley's Current Behavior Scale - Self Report. RESULTS The 12-mo prevalence was 5.3% for alcohol use disorder and 13.7% for drug use disorder. The lifetime prevalence was 12.0% for alcohol use disorder and 27.7% for drug use disorder. Men had higher rates of both alcohol use disorder and drug use disorder compared to women. The prevalence of drug use disorder was more than twice that of alcohol use disorder for both sexes. The drugs most participants reported having used were (in descending order): Amphetamine (19.1%), cannabis (17.1%), cocaine or ecstasy (7.4%), benzodiazepines (7.4%), and heroin or other opioids (2.9%). Lifetime drug use disorder was significantly associated with both hyperactivity-impulsivity symptoms and emotional dysregulation symptom severity. Lifetime alcohol use disorder, on the other hand, was not significantly associated with ADHD symptoms or emotional dysregulation when adjusted for gender and age. CONCLUSION Patients with ADHD have a high lifetime prevalence of drug use disorder, which is associated with higher levels of hyperactivity-impulsivity symptoms and emotional dysregulation.
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Affiliation(s)
| | - Jan Haavik
- Department of Biomedicine, University of Bergen, Bergen 5007, Norway
- Division of Psychiatry, Haukeland University Hospital, Bergen 5021, Norway
| | - Trond Heir
- Institute of Clinical Medicine, University of Oslo, Oslo 0316, Norway
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45
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Huggett SB, Bubier JA, Chesler EJ, Palmer RHC. Do gene expression findings from mouse models of cocaine use recapitulate human cocaine use disorder in reward circuitry? GENES BRAIN AND BEHAVIOR 2020; 20:e12689. [PMID: 32720468 DOI: 10.1111/gbb.12689] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Revised: 07/15/2020] [Accepted: 07/23/2020] [Indexed: 11/29/2022]
Abstract
Animal models of drug use have investigated possible mechanisms governing human substance use traits for over 100 years. Most cross-species research on drug use/addiction examines behavioral overlap, but studies assessing neuromolecular (e.g. RNA) correspondence are lacking. Our study utilized transcriptome-wide data from the hippocampus and ventral tegmental area (VTA)/midbrain from a total of 35 human males with cocaine use disorder/controls and 49 male C57BL/6J cocaine/saline administering/exposed mice. We hypothesized differential expressed genes and systems of co-expressed genes (gene networks) would show appreciable overlap across mouse cocaine self-administration and human cocaine use disorder. We found modest, but significant relationships between differentially expressed genes associated with cocaine self-administration (short access) and cocaine use disorder within reward circuitry. Differentially expressed genes underlying models of acute cocaine exposure (cocaine), context re-exposure and cocaine + context re-exposure were not consistently associated with human CUD across brain regions. Investigating systems of co-expressed genes, we found several validated gene networks with weak to moderate conservation between cocaine/saline self-administering mice and disordered cocaine users/controls. The most conserved hippocampal and VTA gene networks demonstrated substantial overlap (2029 common genes) and included both novel and previously implicated targets for cocaine use/addiction. Lastly, we conducted (expression-based) phenome-wide association studies of the nine common hub genes across conserved gene networks. Common hub genes were associated with dopamine/serotonin function, cocaine self-administration and other relevant mouse traits. Overall, our study pinpointed and characterized conserved brain-related RNA patterns across mouse cocaine self-administration and human cocaine use disorder. We offer recommendations for future research and add to the dialogue surrounding pre-clinical animal research for human disease.
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Affiliation(s)
- Spencer B Huggett
- Behavioral Genetics of Addiction Laboratory, Department of Psychology at Emory University, Atlanta, Georgia, USA
| | - Jason A Bubier
- Center for Systems Neurogenetics of Addiction, The Jackson Laboratory, Bar Harbor, Maine, USA
| | - Elissa J Chesler
- Center for Systems Neurogenetics of Addiction, The Jackson Laboratory, Bar Harbor, Maine, USA
| | - Rohan H C Palmer
- Behavioral Genetics of Addiction Laboratory, Department of Psychology at Emory University, Atlanta, Georgia, USA
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46
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Sanchez-Roige S, Palmer AA, Clarke TK. Recent Efforts to Dissect the Genetic Basis of Alcohol Use and Abuse. Biol Psychiatry 2020; 87:609-618. [PMID: 31733789 PMCID: PMC7071963 DOI: 10.1016/j.biopsych.2019.09.011] [Citation(s) in RCA: 51] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/21/2019] [Revised: 08/14/2019] [Accepted: 09/13/2019] [Indexed: 01/29/2023]
Abstract
Alcohol use disorder (AUD) is defined by several symptom criteria, which can be dissected further at the genetic level. Over the past several years, our understanding of the genetic factors influencing alcohol use and abuse has progressed tremendously; numerous loci have been implicated in different aspects of alcohol use. Previously known associations with alcohol-metabolizing enzymes (ADH1B, ALDH2) have been replicated definitively. In addition, novel associations with loci containing the genes KLB, GCKR, CRHR1, and CADM2 have been reported. Downstream analyses have leveraged these genetic findings to reveal important relationships between alcohol use behaviors and both physical and mental health. AUD and aspects of alcohol misuse have been shown to overlap strongly with psychiatric disorders, whereas aspects of alcohol consumption have shown stronger links to metabolism. These results demonstrate that the genetic architecture of alcohol consumption only partially overlaps with the genetics of clinically defined AUD. We discuss the limitations of using quantitative measures of alcohol use as proxy measures for AUD, and we outline how future studies will require careful phenotype harmonization to properly capture the genetic liability to AUD.
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Affiliation(s)
- Sandra Sanchez-Roige
- Department of Psychiatry, University of California San Diego, La Jolla, California.
| | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, California; Institute for Genomic Medicine, University of California San Diego, La Jolla, California
| | - Toni-Kim Clarke
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
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47
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Lee JY, Kim W, Brook JS, Finch SJ, Brook DW. Adolescent risk and protective factors predicting triple trajectories of substance use from adolescence into adulthood. JOURNAL OF CHILD AND FAMILY STUDIES 2020; 29:403-412. [PMID: 33311966 PMCID: PMC7731617 DOI: 10.1007/s10826-019-01629-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
OBJECTIVES Since the number of individuals who use substances in the United States has markedly increased every year, substance use is a significant public health concern. The current study examines the possible risk and protective factors associated with triple comorbid trajectories of longitudinal alcohol, tobacco, and cannabis use from age 14 to 36. METHODS A community sample of 674 participants (53% African Americans and 47% Puerto Ricans; 60% females) were recruited from the Harlem Longitudinal Development Study. Multinomial logistic regression analyses were conducted to examine the associations between the risk (low self-control, peer drug use) and protective (parent-child attachment, family church attendance) factors at age 14 and membership in the triple trajectory groups derived from a multivariate growth mixture model. RESULTS Low self-control and peer drug use were associated with an increased likelihood of being a member in the triple comorbid trajectory groups compared to the reference group (i.e., low alcohol, no tobacco, and no cannabis use). On the other hand, parent-child attachment and family church attendance were associated with a decreased likelihood of being a member in the triple comorbid trajectory groups compared to the reference group. CONCLUSIONS Treatment programs for adolescents who use substances may be more helpful if their parents and/or friends could also participate together with the adolescent, rather than only the adolescent participates in the treatment programs. Further research is needed to gain a greater understanding of the conceptual nature of the relationship between earlier risk and protective factors and later substance use patterns.
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Affiliation(s)
- Jung Yeon Lee
- New York University School of Medicine, Department of Psychiatry, New York, NY 10016, USA
| | - Wonkuk Kim
- Chung-Ang University, Department of Applied Statistics, Seoul 06974, Republic of Korea
| | - Judith S. Brook
- New York University School of Medicine, Department of Psychiatry, New York, NY 10016, USA
| | - Stephen J. Finch
- Stony Brook University, Department of Applied Mathematics and Statistics, Stony Brook, NY 11794, USA
| | - David W. Brook
- New York University School of Medicine, Department of Psychiatry, New York, NY 10016, USA
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Gordon KS, McGinnis K, Dao C, Rentsch CT, Small A, Smith RV, Kember RL, Gelernter J, Kranzler HR, Bryant KJ, Tate JP, Justice AC. Differentiating Types of Self-Reported Alcohol Abstinence. AIDS Behav 2020; 24:655-665. [PMID: 31435887 DOI: 10.1007/s10461-019-02638-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
We contrast three types of abstinence: quit after alcohol associated problems (Q-AP), quit for other reasons (Q-OR), and lifetime abstainer (LTA). We summarized the characteristics of people living with HIV (PLWH), and matched uninfected individuals, by levels of alcohol use and types of abstinence. We then identified factors that differentiate abstinence and determined whether the association with an alcohol biomarker or a genetic polymorphism is improved by differentiating abstinence. Among abstainers, 34% of PLWH and 38% of uninfected were Q-AP; 53% and 53% were Q-OR; and 12% and 10% were LTA. Logistic regression models found smoking, alcohol, cocaine, and hepatitis C increased odds of Q-AP, whereas smoking and marijuana decreased odds of LTA. Differentiating types of abstinence improved association. Q-APs and LTAs can be readily differentiated by an alcohol biomarker and genetic polymorphism. Differentiating type of abstinence may enhance understanding of alcohol health effects.
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Affiliation(s)
- Kirsha S Gordon
- VA Connecticut Healthcare System, 11ACSL-G, 950 Campbell Avenue, West Haven, CT, 06516, USA.
- Yale University School of Medicine, New Haven, CT, 06510, USA.
| | - Kathleen McGinnis
- VA Connecticut Healthcare System, 11ACSL-G, 950 Campbell Avenue, West Haven, CT, 06516, USA
| | - Cecilia Dao
- Yale University School of Medicine, New Haven, CT, 06510, USA
| | - Christopher T Rentsch
- VA Connecticut Healthcare System, 11ACSL-G, 950 Campbell Avenue, West Haven, CT, 06516, USA
- Epidemiology & Population Health, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK
| | - Aeron Small
- Yale University School of Medicine, New Haven, CT, 06510, USA
| | | | - Rachel L Kember
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Corporal Michael J. Crescenz Veterans Affairs Medical Center VISN4 MIRECC, Philadelphia, PA, 19104, USA
| | - Joel Gelernter
- VA Connecticut Healthcare System, 11ACSL-G, 950 Campbell Avenue, West Haven, CT, 06516, USA
- Yale University School of Medicine, New Haven, CT, 06510, USA
| | - Henry R Kranzler
- Corporal Michael J. Crescenz Veterans Affairs Medical Center VISN4 MIRECC, Philadelphia, PA, 19104, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Kendall J Bryant
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD, 20892, USA
| | - Janet P Tate
- VA Connecticut Healthcare System, 11ACSL-G, 950 Campbell Avenue, West Haven, CT, 06516, USA
- Yale University School of Medicine, New Haven, CT, 06510, USA
| | - Amy C Justice
- VA Connecticut Healthcare System, 11ACSL-G, 950 Campbell Avenue, West Haven, CT, 06516, USA
- Yale University School of Medicine, New Haven, CT, 06510, USA
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Nieto SJ, Grodin EN, Ray LA. On the path towards personalized medicine: Implications of pharmacogenetic studies of alcohol use disorder medications. EXPERT REVIEW OF PRECISION MEDICINE AND DRUG DEVELOPMENT 2020; 5:43-54. [PMID: 34291172 DOI: 10.1080/23808993.2020.1724510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
Introduction The heritability of alcohol use disorder (AUD) is estimated to be ~50%; however, the genetic basis of the disease is still poorly understood. The genetic variants identified thus far only explain a small percentage of AUD phenotypic variability. While genome-wide association studies (GWAS) are impacted by technical and methodological limitations, genetic variants that have been identified independently of GWAS findings can moderate the efficacy of AUD medications. Areas Covered This review discusses findings from clinical pharmacogenetic studies of AUD medications. While the pharmacogenetic studies reviewed involve several genetic variants in the major neurotransmitter systems, genetic loci in the opioid system have garnered the most attention. Expert Opinion The clinical utility of pharmacogenetics in AUD populations is uncertain at this time. There are several ongoing prospective clinical trials that will enhance knowledge regarding the applicability of pharmacogenetics in clinical populations. We recommend that future work in this area consider reverse translating from genotype to phenotype, mapping genes to stages of the addiction cycle, mapping genes to neural circuits, and harnessing large population-based cohorts.
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Affiliation(s)
- Steven J Nieto
- University of California Los Angeles, Department of Psychology, Los Angeles, CA, USA
| | - Erica N Grodin
- University of California Los Angeles, Department of Psychology, Los Angeles, CA, USA
| | - Lara A Ray
- University of California Los Angeles, Department of Psychology, Los Angeles, CA, USA.,University of California, Los Angeles, Department of Psychiatry and Biobehavioral Sciences, Los Angeles, CA, USA.,University of California Los Angeles, Brain Research Institute, Los Angeles, CA, USA
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Yousefi PD, Richmond R, Langdon R, Ness A, Liu C, Levy D, Relton C, Suderman M, Zuccolo L. Validation and characterisation of a DNA methylation alcohol biomarker across the life course. Clin Epigenetics 2019; 11:163. [PMID: 31775873 PMCID: PMC6880546 DOI: 10.1186/s13148-019-0753-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2019] [Accepted: 09/23/2019] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Recently, an alcohol predictor was developed using DNA methylation at 144 CpG sites (DNAm-Alc) as a biomarker for improved clinical or epidemiologic assessment of alcohol-related ill health. We validate the performance and characterise the drivers of this DNAm-Alc for the first time in independent populations. RESULTS In N = 1049 parents from the Avon Longitudinal Study of Parents and Children (ALSPAC) Accessible Resource for Integrated Epigenomic Studies (ARIES) at midlife, we found DNAm-Alc explained 7.6% of the variation in alcohol intake, roughly half of what had been reported previously, and interestingly explained a larger 9.8% of Alcohol Use Disorders Identification Test (AUDIT) score, a scale of alcohol use disorder. Explanatory capacity in participants from the offspring generation of ARIES measured during adolescence was much lower. However, DNAm-Alc explained 14.3% of the variation in replication using the Head and Neck 5000 (HN5000) clinical cohort that had higher average alcohol consumption. To investigate whether this relationship was being driven by genetic and/or earlier environment confounding, we examined how earlier versus concurrent DNAm-Alc measures predicted AUDIT scores. In both ARIES parental and offspring generations, we observed associations between AUDIT and concurrent, but not earlier DNAm-Alc, suggesting independence from genetic and stable environmental contributions. CONCLUSIONS The stronger relationship between DNAm-Alcs and AUDIT in parents at midlife compared to adolescents despite similar levels of consumption suggests that DNAm-Alc likely reflects long-term patterns of alcohol abuse. Such biomarkers may have potential applications for biomonitoring and risk prediction, especially in cases where reporting bias is a concern.
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Affiliation(s)
- Paul Darius Yousefi
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS82BN, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
| | - Rebecca Richmond
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS82BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Ryan Langdon
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS82BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Andrew Ness
- National Institute of Health Bristol Biomedical Research Centre, University of Bristol, Bristol, UK
- Bristol Dental School, University of Bristol, Bristol, UK
| | - Chunyu Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Daniel Levy
- The Framingham Heart Study, Framingham, MA, USA
- The Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Bethesda, MD, USA
| | - Caroline Relton
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS82BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Matthew Suderman
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS82BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Luisa Zuccolo
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS82BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
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