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Horwitz TB, Zorina-Lichtenwalter K, Gustavson DE, Grotzinger AD, Stallings MC. Partitioning the Genomic Components of Behavioral Disinhibition and Substance Use (Disorder) Using Genomic Structural Equation Modeling. Behav Genet 2024:10.1007/s10519-024-10188-9. [PMID: 38981971 DOI: 10.1007/s10519-024-10188-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2024] [Accepted: 06/02/2024] [Indexed: 07/11/2024]
Abstract
Externalizing behaviors encompass manifestations of risk-taking, self-regulation, aggression, sensation-/reward-seeking, and impulsivity. Externalizing research often includes substance use (SUB), substance use disorder (SUD), and other (non-SUB/SUD) "behavioral disinhibition" (BD) traits. Genome-wide and twin research have pointed to overlapping genetic architecture within and across SUB, SUD, and BD. We created single-factor measurement models-each describing SUB, SUD, or BD traits-based on mutually exclusive sets of European ancestry genome-wide association study (GWAS) statistics exploring externalizing variables. We then assessed the partitioning of genetic covariance among the three facets using correlated factors models and Cholesky decomposition. Even when the residuals for indicators relating to the same substance were correlated across the SUB and SUD factors, the two factors yielded a large correlation (rg = 0.803). BD correlated strongly with the SUD (rg = 0.774) and SUB (rg = 0.778) factors. In our initial decompositions, 33% of total BD variance remained after partialing out SUD and SUB. The majority of covariance between BD and SUB and between BD and SUD was shared across all factors, and, within these models, only a small fraction of the total variation in BD operated via an independent pathway with SUD or SUB outside of the other factor. When only nicotine/tobacco, cannabis, and alcohol were included for the SUB/SUD factors, their correlation increased to rg = 0.861; in corresponding decompositions, BD-specific variance decreased to 27%. Further research can better elucidate the properties of BD-specific variation by exploring its genetic/molecular correlates.
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Affiliation(s)
- Tanya B Horwitz
- Institute for Behavioral Genetics, University of Colorado Boulder, 1480 30th St., Boulder, CO, 80303, USA.
| | | | - Daniel E Gustavson
- Institute for Behavioral Genetics, University of Colorado Boulder, 1480 30th St., Boulder, CO, 80303, USA
| | - Andrew D Grotzinger
- Institute for Behavioral Genetics, University of Colorado Boulder, 1480 30th St., Boulder, CO, 80303, USA
- Psychology and Neuroscience, University of Colorado Boulder, Meunzinger D244, 345 UCB, Boulder, CO, 80309, USA
| | - Michael C Stallings
- Institute for Behavioral Genetics, University of Colorado Boulder, 1480 30th St., Boulder, CO, 80303, USA
- Psychology and Neuroscience, University of Colorado Boulder, Meunzinger D244, 345 UCB, Boulder, CO, 80309, USA
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2
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Brasher MS, Grotzinger AD, Friedman NP, Smolker HR, Evans LM. Disentangling differing relationships between internalizing disorders and alcohol use. Am J Med Genet B Neuropsychiatr Genet 2024; 195:e32975. [PMID: 38375614 PMCID: PMC11147714 DOI: 10.1002/ajmg.b.32975] [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: 07/17/2023] [Revised: 12/14/2023] [Accepted: 02/08/2024] [Indexed: 02/21/2024]
Abstract
Both internalizing disorders and alcohol use have dramatic, wide-spread implications for global health. Previous work has established common phenotypic comorbidity among these disorders, as well as shared genetic variation underlying them both. We used genomic structural equation modeling to investigate the shared genetics of internalizing, externalizing, and alcohol use traits, as well as to explore whether specific domains of internalizing symptoms mediate the contrasting relationships with problematic alcohol use compared to alcohol consumption. We also examined patterns of genetic correlations between similar traits within additional Finnish and East Asian ancestry groups. When the shared genetic influence of externalizing psychopathology was accounted for, the genetic effect of internalizing traits on alcohol use was reduced, suggesting the important role of common genetic factors underlying multiple psychiatric disorders and their genetic influences on comorbidity of internalizing and alcohol use traits. Individual internalizing domains had contrasting effects on frequency of alcohol consumption, which demonstrate the complex system of pleiotropy that exists, even within similar disorders, and can be missed when evaluating only relationships among formal diagnoses. Future work must consider the broad effects of shared psychopathology along with the fine-scale effects of heterogeneity within disorders to more fully understand the biology underlying complex traits.
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Affiliation(s)
- Maizy S Brasher
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
- Department of Ecology and Evolutionary Biology, Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
| | - Andrew D Grotzinger
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
- Department of Psychology and Neuroscience, Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
| | - Naomi P Friedman
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
- Department of Psychology and Neuroscience, Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
| | - Harry R Smolker
- Institute of Cognitive Science, University of Colorado Boulder, Boulder, Colorado, USA
| | - Luke M Evans
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
- Department of Ecology and Evolutionary Biology, Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
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3
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Thorpe HHA, Fontanillas P, Meredith JJ, Jennings MV, Cupertino RB, Pakala S, Elson SL, Khokhar JY, Davis LK, Johnson EC, Palmer AA, Sanchez-Roige S. Genome-wide association studies of lifetime and frequency cannabis use in 131,895 individuals. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.06.14.24308946. [PMID: 38947071 PMCID: PMC11213095 DOI: 10.1101/2024.06.14.24308946] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
Cannabis is one of the most widely used drugs globally. Decriminalization of cannabis is further increasing cannabis consumption. We performed genome-wide association studies (GWASs) of lifetime (N=131,895) and frequency (N=73,374) of cannabis use. Lifetime cannabis use GWAS identified two loci, one near CADM2 (rs11922956, p=2.40E-11) and another near GRM3 (rs12673181, p=6.90E-09). Frequency of use GWAS identified one locus near CADM2 (rs4856591, p=8.10E-09; r2 =0.76 with rs11922956). Both traits were heritable and genetically correlated with previous GWASs of lifetime use and cannabis use disorder (CUD), as well as other substance use and cognitive traits. Polygenic scores (PGSs) for lifetime and frequency of cannabis use associated cannabis use phenotypes in AllofUs participants. Phenome-wide association study of lifetime cannabis use PGS in a hospital cohort replicated associations with substance use and mood disorders, and uncovered associations with celiac and infectious diseases. This work demonstrates the value of GWASs of CUD transition risk factors.
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Affiliation(s)
- Hayley H A Thorpe
- Department of Anatomy and Cell Biology, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | | | - John J Meredith
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Mariela V Jennings
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Renata B Cupertino
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Shreya Pakala
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | | | | | - Jibran Y Khokhar
- Department of Anatomy and Cell Biology, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Lea K Davis
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Emma C Johnson
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 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
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
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4
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Miller AP, Gizer IR. Dual-systems models of the genetic architecture of impulsive personality traits: neurogenetic evidence of distinct but related factors. Psychol Med 2024; 54:1533-1543. [PMID: 38016992 PMCID: PMC11132950 DOI: 10.1017/s0033291723003367] [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: 11/30/2023]
Abstract
BACKGROUND Dual-systems models, positing an interaction between two distinct and competing systems (i.e. top-down self-control, and bottom-up reward- or emotion-based drive), provide a parsimonious framework for investigating the interplay between cortical and subcortical brain regions relevant to impulsive personality traits (IPTs) and their associations with psychopathology. Despite recent developments in multivariate analysis of genome-wide association studies (GWAS), molecular genetic investigations of these models have not been conducted. METHODS Using IPT GWAS, we conducted confirmatory genomic structural equation models (GenomicSEM) to empirically evaluate dual-systems models of the genetic architecture of IPTs. Genetic correlations between dual-systems factors and relevant cortical and subcortical neuroimaging phenotypes (regional/structural volume, cortical surface area, cortical thickness) were estimated and compared. RESULTS GenomicSEM dual-systems models underscored important sources of shared and unique genetic variance between top-down and bottom-up constructs. Specifically, a dual-systems genomic model consisting of sensation seeking and lack of self-control factors demonstrated distinct but related sources of genetic influences (rg = 0.60). Genetic correlation analyses provided evidence of differential associations between dual-systems factors and cortical neuroimaging phenotypes (e.g. lack of self-control negatively associated with cortical thickness, sensation seeking positively associated with cortical surface area). No significant associations were observed with subcortical phenotypes. CONCLUSIONS Dual-systems models of the genetic architecture of IPTs tested were consistent with study hypotheses, but associations with relevant neuroimaging phenotypes were mixed (e.g. no associations with subcortical volumes). Findings demonstrate the utility of dual-systems models for studying IPT genetic influences, but also highlight potential limitations as a framework for interpreting IPTs as endophenotypes for psychopathology.
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Affiliation(s)
- Alex P. Miller
- Department of Psychiatry, School of Medicine, Washington University in St. Louis, St. Louis, MO, United States
| | - Ian R. Gizer
- Department of Psychological Sciences, University of Missouri, Columbia, MO, United States
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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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6
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Paul SE, Baranger DAA, Johnson EC, Jackson JJ, Gorelik AJ, Miller AP, Hatoum AS, Thompson WK, Strube M, Dick DM, Kamarajan C, Kramer JR, Plawecki MH, Chan G, Anokhin AP, Chorlian DB, Kinreich S, Meyers JL, Porjesz B, Edenberg HJ, Agrawal A, Bucholz KK, Bogdan R. Alcohol milestones and internalizing, externalizing, and executive function: longitudinal and polygenic score associations. Psychol Med 2024:1-14. [PMID: 38721768 DOI: 10.1017/s003329172400076x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
BACKGROUND Although the link between alcohol involvement and behavioral phenotypes (e.g. impulsivity, negative affect, executive function [EF]) is well-established, the directionality of these associations, specificity to stages of alcohol involvement, and extent of shared genetic liability remain unclear. We estimate longitudinal associations between transitions among alcohol milestones, behavioral phenotypes, and indices of genetic risk. METHODS Data came from the Collaborative Study on the Genetics of Alcoholism (n = 3681; ages 11-36). Alcohol transitions (first: drink, intoxication, alcohol use disorder [AUD] symptom, AUD diagnosis), internalizing, and externalizing phenotypes came from the Semi-Structured Assessment for the Genetics of Alcoholism. EF was measured with the Tower of London and Visual Span Tasks. Polygenic scores (PGS) were computed for alcohol-related and behavioral phenotypes. Cox models estimated associations among PGS, behavior, and alcohol milestones. RESULTS Externalizing phenotypes (e.g. conduct disorder symptoms) were associated with future initiation and drinking problems (hazard ratio (HR)⩾1.16). Internalizing (e.g. social anxiety) was associated with hazards for progression from first drink to severe AUD (HR⩾1.55). Initiation and AUD were associated with increased hazards for later depressive symptoms and suicidal ideation (HR⩾1.38), and initiation was associated with increased hazards for future conduct symptoms (HR = 1.60). EF was not associated with alcohol transitions. Drinks per week PGS was linked with increased hazards for alcohol transitions (HR⩾1.06). Problematic alcohol use PGS increased hazards for suicidal ideation (HR = 1.20). CONCLUSIONS Behavioral markers of addiction vulnerability precede and follow alcohol transitions, highlighting dynamic, bidirectional relationships between behavior and emerging addiction.
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Affiliation(s)
- Sarah E Paul
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - David A A Baranger
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Emma C Johnson
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Joshua J Jackson
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Aaron J Gorelik
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Alex P Miller
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Alexander S Hatoum
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Wesley K Thompson
- Population Neuroscience and Genetics (PNG) Center, Laureate Institute for Brain Research, Tulsa, OK, USA
| | - Michael Strube
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Danielle M Dick
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ, USA
- Rutgers Addiction Research Center, Rutgers University, Piscataway, NJ, USA
| | - Chella Kamarajan
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
| | - John R Kramer
- Department of Psychiatry, Carver College of Medicine, The University of Iowa, Iowa City, IA, USA
| | - Martin H Plawecki
- Department of Psychiatry, School of Medicine, Indiana University, Indianapolis, IN, USA
| | - Grace Chan
- Department of Psychiatry, Carver College of Medicine, The University of Iowa, Iowa City, IA, USA
- Department of Psychiatry, School of Medicine, University of Connecticut, Farmington, CT, USA
| | - Andrey P Anokhin
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - David B Chorlian
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
| | - Sivan Kinreich
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
| | - Jacquelyn L Meyers
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
| | - Bernice Porjesz
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
| | - Howard J Edenberg
- Department of Medical and Molecular Genetics, School of Medicine, Indiana University, Indianapolis, IN, USA
- Department of Biochemistry and Molecular Biology, School of Medicine, Indiana University, Indianapolis, IN, USA
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Kathleen K Bucholz
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Ryan Bogdan
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
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7
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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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8
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Mathes Winnicki BM, Lee DJ, Hawn SE, Livingston NA, Marx BP, Keane TM. Alcohol consumption and dependence risk among male and female Veterans: Trajectories and predictors. Drug Alcohol Depend 2024; 257:111138. [PMID: 38430789 DOI: 10.1016/j.drugalcdep.2024.111138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 02/15/2024] [Accepted: 02/17/2024] [Indexed: 03/05/2024]
Abstract
BACKGROUND With few exceptions, previously conducted research on hazardous drinking among Veterans has employed samples in which the majority of participants identify as male. In addition, past studies have solely focused on alcohol consumption, rather than associated risk for dependence. In this study, we expanded upon the extant literature by investigating sex differences in trajectories and predictors of change in alcohol consumption and dependence risk among post-9/11 Veterans. METHODS A national sample of 1649 Veterans (50.0% female) were recruited in a five-wave longitudinal study that followed Veterans for up to 16 years after deployment. We used growth curve modeling to investigate trajectories of change in alcohol consumption and dependence risk among men and women Veterans. We examined predictors of growth, including demographics, support and resources, psychiatric symptoms, and trauma exposure. RESULTS Among male Veterans, alcohol consumption and dependence risk remained stagnant, which is in contrast to past work using non-Veteran samples. For female Veterans, consumption exhibited initial reductions that decelerated, and dependence risk reduced at a continuous rate. PTSD diagnosis was a significant predictor of individual differences in growth for men. Psychiatric symptoms (i.e., PTSD diagnosis, probable depression diagnosis, suicidal ideation) and psychosocial functioning were significant predictors of decreasing alcohol use for women. CONCLUSIONS Results highlight important sex differences in patterns and predictors of change in alcohol consumption and dependence risk among post-9/11 Veterans. Findings are discussed in relation to screening for hazardous alcohol use and intervention strategies in this at-risk population.
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Affiliation(s)
- Brittany M Mathes Winnicki
- US Department of Veteran Affairs, VA Boston Healthcare System, Boston, MA, United States; Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States.
| | - Daniel J Lee
- US Department of Veteran Affairs, VA Boston Healthcare System, Boston, MA, United States; Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States; Behavioral Science Division, National Center for PTSD, VA Boston Healthcare System, Boston, MA, United States
| | - Sage E Hawn
- Department of Psychology, Old Dominion University, Norfolk, VA, United States
| | - Nicholas A Livingston
- US Department of Veteran Affairs, VA Boston Healthcare System, Boston, MA, United States; Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States; Behavioral Science Division, National Center for PTSD, VA Boston Healthcare System, Boston, MA, United States
| | - Brian P Marx
- US Department of Veteran Affairs, VA Boston Healthcare System, Boston, MA, United States; Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States; Behavioral Science Division, National Center for PTSD, VA Boston Healthcare System, Boston, MA, United States
| | - Terence M Keane
- US Department of Veteran Affairs, VA Boston Healthcare System, Boston, MA, United States; Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States; Behavioral Science Division, National Center for PTSD, VA Boston Healthcare System, Boston, MA, United States
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9
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Thomas NS, Gillespie NA, Chan G, Edenberg HJ, Kamarajan C, Kuo SIC, Miller AP, Nurnberger JI, Tischfield J, Dick DM, Salvatore JE. A Developmentally-Informative Genome-wide Association Study of Alcohol Use Frequency. Behav Genet 2024; 54:151-168. [PMID: 38108996 PMCID: PMC10913412 DOI: 10.1007/s10519-023-10170-x] [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: 06/27/2023] [Accepted: 12/01/2023] [Indexed: 12/19/2023]
Abstract
Contemporary genome-wide association study (GWAS) methods typically do not account for variability in genetic effects throughout development. We applied genomic structural equation modeling to combine developmentally-informative phenotype data and GWAS to create polygenic scores (PGS) for alcohol use frequency that are specific to developmental stage. Longitudinal cohort studies targeted for gene-identification analyses include the Collaborative Study on the Genetics of Alcoholism (adolescence n = 1,118, early adulthood n = 2,762, adulthood n = 5,255), the National Longitudinal Study of Adolescent to Adult Health (adolescence n = 3,089, early adulthood n = 3,993, adulthood n = 5,149), and the Avon Longitudinal Study of Parents and Children (ALSPAC; adolescence n = 5,382, early adulthood n = 3,613). PGS validation analyses were conducted in the COGA sample using an alternate version of the discovery analysis with COGA removed. Results suggest that genetic liability for alcohol use frequency in adolescence may be distinct from genetic liability for alcohol use frequency later in developmental periods. The age-specific PGS predicts an increase of 4 drinking days per year per PGS standard deviation when modeled separately from the common factor PGS in adulthood. The current work was underpowered at all steps of the analysis plan. Though small sample sizes and low statistical power limit the substantive conclusions that can be drawn regarding these research questions, this work provides a foundation for future genetic studies of developmental variability in the genetic underpinnings of alcohol use behaviors and genetically-informed, age-matched phenotype prediction.
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Affiliation(s)
- Nathaniel S Thomas
- Department of Psychology, Virginia Commonwealth University, Box 842018, Richmond, VA, 23284-2018, USA.
| | - Nathan A Gillespie
- Virginia Institute for Psychiatric and Behavioral Genetics, Richmond, VA, USA
| | - Grace Chan
- Department of Psychiatry, University of Connecticut School of Medicine, Farmington, CT, USA
- Department of Psychiatry, University of Iowa, Carver College of Medicine, Iowa City, IA, 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
| | - Chella Kamarajan
- Department of Psychiatry & Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
| | - Sally I-Chun Kuo
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ, USA
| | - Alex P Miller
- Department of Psychiatry, School of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | | | - Jay Tischfield
- Department of Genetics, Human Genetics Institute of New Jersey, Rutgers University, Piscataway, NJ, USA
| | - Danielle M Dick
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ, USA
| | - Jessica E Salvatore
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ, USA
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10
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Horwitz TB, Zorina-Lichtenwalter K, Gustavson DE, Grotzinger AD, Stallings MC. Partitioning the Genomic Components of Behavioral Disinhibition and Substance Use (Disorder) Using Genomic Structural Equation Modeling. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.02.20.24303036. [PMID: 38464249 PMCID: PMC10925358 DOI: 10.1101/2024.02.20.24303036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Externalizing behaviors encompass manifestations of risk-taking, self-regulation, aggression, sensation-/reward-seeking, and impulsivity. Externalizing research often includes substance use (SU), substance use disorder (SUD), and other (non-SU/SUD) "behavioral disinhibition" (BD) traits. Genome-wide and twin research have pointed to overlapping genetic architecture within and across SUB, SUD, and BD. We created single-factor measurement models-each describing SUB, SUD, or BD traits--based on mutually exclusive sets of European ancestry genome-wide association study (GWAS) statistics exploring externalizing variables. We then applied trivariate Cholesky decomposition to these factors in order to identify BD-specific genomic variation and assess the partitioning of BD's genetic covariance with each of the other facets. Even when the residuals for indicators relating to the same substance were correlated across the SUB and SUD factors, the two factors yielded a large zero-order correlation (rg=.803). BD correlated strongly with the SUD (rg=.774) and SUB factors (rg=.778). In our initial decompositions, 33% of total BD variance remained after removing variance associated with SUD and SUB. The majority of covariance between BD and SU and between BD and SUD was shared across all factors. When only nicotine/tobacco, cannabis, and alcohol were included for the SUB/SUD factors, their zero-order correlation increased to rg=.861; in corresponding decompositions, BD-specific variance decreased to 27%. In summary, BD, SU, and SUD were highly genetically correlated at the latent factor level, and a significant minority of genomic BD variation was not shared with SU and/or SUD. Further research can better elucidate the properties of BD-specific variation by exploring its genetic/molecular correlates.
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Affiliation(s)
- Tanya B. Horwitz
- Institute for Behavioral Genetics, University of Colorado Boulder, 1480 30 St, Boulder, CO, United States of America 80303
- Psychology and Neuroscience, University of Colorado Boulder, Meunzinger D244, 345 UCB, Boulder, CO, United States of America 80303
| | - Katerina Zorina-Lichtenwalter
- Institute for Behavioral Genetics, University of Colorado Boulder, 1480 30 St, Boulder, CO, United States of America 80303
| | - Daniel E. Gustavson
- Institute for Behavioral Genetics, University of Colorado Boulder, 1480 30 St, Boulder, CO, United States of America 80303
| | - Andrew D. Grotzinger
- Institute for Behavioral Genetics, University of Colorado Boulder, 1480 30 St, Boulder, CO, United States of America 80303
- Psychology and Neuroscience, University of Colorado Boulder, Meunzinger D244, 345 UCB, Boulder, CO, United States of America 80303
| | - Michael C. Stallings
- Institute for Behavioral Genetics, University of Colorado Boulder, 1480 30 St, Boulder, CO, United States of America 80303
- Psychology and Neuroscience, University of Colorado Boulder, Meunzinger D244, 345 UCB, Boulder, CO, United States of America 80303
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11
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Chen AB, Yu X, Thapa KS, Gao H, Reiter JL, Xuei X, Tsai AP, Landreth GE, Lai D, Wang Y, Foroud TM, Tischfield JA, Edenberg HJ, Liu Y. Functional 3'-UTR Variants Identify Regulatory Mechanisms Impacting Alcohol Use Disorder and Related Traits. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.31.578270. [PMID: 38370821 PMCID: PMC10871301 DOI: 10.1101/2024.01.31.578270] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
Although genome-wide association studies (GWAS) have identified loci associated with alcohol consumption and alcohol use disorder (AUD), they do not identify which variants are functional. To approach this, we evaluated the impact of variants in 3' untranslated regions (3'-UTRs) of genes in loci associated with substance use and neurological disorders using a massively parallel reporter assay (MPRA) in neuroblastoma and microglia cells. Functionally impactful variants explained a higher proportion of heritability of alcohol traits than non-functional variants. We identified genes whose 3'UTR activities are associated with AUD and alcohol consumption by combining variant effects from MPRA with GWAS results. We examined their effects by evaluating gene expression after CRISPR inhibition of neuronal cells and stratifying brain tissue samples by MPRA-derived 3'-UTR activity. A pathway analysis of differentially expressed genes identified inflammation response pathways. These analyses suggest that variation in response to inflammation contributes to the propensity to increase alcohol consumption.
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Affiliation(s)
- Andy B. Chen
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana
| | - Xuhong Yu
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
| | - Kriti S. Thapa
- Department of Biochemistry & Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana
| | - Hongyu Gao
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana
- Center for Medical Genomics, Indiana University School of Medicine, Indianapolis, Indiana
| | - Jill L Reiter
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana
| | - Xiaoling Xuei
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
- Center for Medical Genomics, Indiana University School of Medicine, Indianapolis, Indiana
| | - Andy P. Tsai
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, Indiana
| | - Gary E. Landreth
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, Indiana
- Department of Anatomy and Cell Biology, Indiana University School of Medicine, Indianapolis, Indiana
| | - Dongbing Lai
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
| | - Yue Wang
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
| | - Tatiana M. Foroud
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
| | | | - Howard J. Edenberg
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
- Department of Biochemistry & Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana
| | - Yunlong Liu
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana
- Center for Medical Genomics, Indiana University School of Medicine, Indianapolis, Indiana
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12
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Miller AP, Gizer IR. Neurogenetic and multi-omic sources of overlap among sensation seeking, alcohol consumption, and alcohol use disorder. Addict Biol 2024; 29:e13365. [PMID: 38380706 PMCID: PMC10882188 DOI: 10.1111/adb.13365] [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: 05/30/2023] [Revised: 09/26/2023] [Accepted: 11/26/2023] [Indexed: 02/22/2024]
Abstract
Sensation seeking is bidirectionally associated with levels of alcohol consumption in both adult and adolescent samples, and shared neurobiological and genetic influences may in part explain these associations. Links between sensation seeking and alcohol use disorder (AUD) may primarily manifest via increased alcohol consumption rather than through direct effects on increasing problems and consequences. Here the overlap among sensation seeking, alcohol consumption, and AUD was examined using multivariate modelling approaches for genome-wide association study (GWAS) summary statistics in conjunction with neurobiologically informed analyses at multiple levels of investigation. Meta-analytic and genomic structural equation modelling (GenomicSEM) approaches were used to conduct GWAS of sensation seeking, alcohol consumption, and AUD. Resulting summary statistics were used in downstream analyses to examine shared brain tissue enrichment of heritability and genome-wide evidence of overlap (e.g., stratified GenomicSEM, RRHO, genetic correlations with neuroimaging phenotypes), and to identify genomic regions likely contributing to observed genetic overlap across traits (e.g., H-MAGMA and LAVA). Across approaches, results supported shared neurogenetic architecture between sensation seeking and alcohol consumption characterised by overlapping enrichment of genes expressed in midbrain and striatal tissues and variants associated with increased cortical surface area. Alcohol consumption and AUD evidenced overlap in relation to variants associated with decreased frontocortical thickness. Finally, genetic mediation models provided evidence of alcohol consumption mediating associations between sensation seeking and AUD. This study extends previous research by examining critical sources of neurogenetic and multi-omic overlap among sensation seeking, alcohol consumption, and AUD which may underlie observed phenotypic associations.
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Affiliation(s)
- Alex P. Miller
- Department of PsychiatryWashington University School of MedicineSt. LouisMissouriUSA
| | - Ian R. Gizer
- Department of Psychological SciencesUniversity of MissouriColumbiaMissouriUSA
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13
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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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14
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Icick R, Shadrin A, Holen B, Karadag N, Parker N, O'Connell K, Frei O, Bahrami S, Høegh M, Lagerberg T, Cheng W, Seibert T, Djurovic S, Dale A, Zhou H, Edenberg H, Gelernter J, Smeland O, Hindley G, Andreassen O. Identification of Novel Loci and Cross-Disorder Pleiotropy Through Multi-Ancestry Genome-Wide Analysis of Alcohol Use Disorder in Over One Million Individuals. RESEARCH SQUARE 2023:rs.3.rs-3755915. [PMID: 38196616 PMCID: PMC10775504 DOI: 10.21203/rs.3.rs-3755915/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/11/2024]
Abstract
Alcohol use disorder (AUD) is highly heritable and burdensome worldwide. Genome-wide association studies (GWASs) can provide new evidence regarding the aetiology of AUD. We report a multi-ancestry GWASs across diverse ancestries focusing on a narrow AUD phenotype, using novel statistical tools in a total sample of 1,041,450 individuals [102,079 cases; European, 75,583; African, 20,689 (mostly African-American); Hispanic American, 3,449; East Asian, 2,254; South Asian, 104; descent]. Cross-ancestry functional analyses were performed with European and African samples. Thirty-seven genome-wide significant loci were identified, of which seven were novel for AUD and six for other alcohol phenotypes. Loci were mapped to genes enriched for brain regions relevant for AUD (striatum, hypothalamus, and prefrontal cortex) and potential drug targets (GABAergic, dopaminergic and serotonergic neurons). African-specific analysis yielded a unique pattern of immune-related gene sets. Polygenic overlap and positive genetic correlations showed extensive shared genetic architecture between AUD and both mental and general medical phenotypes, suggesting they are not only complications of alcohol use but also share genetic liability with AUD. Leveraging a cross-ancestry approach allowed identification of novel genetic loci for AUD and underscores the value of multi-ancestry genetic studies. These findings advance our understanding of AUD risk and clinically-relevant comorbidities.
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Affiliation(s)
| | | | - Børge Holen
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407 Oslo
| | - Naz Karadag
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407 Oslo
| | - Nadine Parker
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407 Oslo
| | - Kevin O'Connell
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407 Oslo
| | | | - Shahram Bahrami
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407 Oslo
| | - Margrethe Høegh
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407 Oslo
| | - Trine Lagerberg
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407 Oslo
| | - Weiqiu Cheng
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407 Oslo
| | - Tyler Seibert
- Department of Radiation Medicine and Applied Sciences, Department of Radiology, Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo; NORMENT Centre, Department of Clinical Science, University of Bergen, Bergen
| | - Anders Dale
- Department of Neurosciences, University of California San Diego
| | | | | | | | - Olav Smeland
- NORMENT Centre for Mental Disorders Research, University of Oslo and Oslo University Hospital
| | - Guy Hindley
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407 Oslo
| | - Ole Andreassen
- Oslo University Hospital & Institute of Clinical Medicine, University of Oslo
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15
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Zhou H, Kember RL, Deak JD, Xu H, Toikumo S, Yuan K, Lind PA, Farajzadeh L, Wang L, Hatoum AS, Johnson J, Lee H, Mallard TT, Xu J, Johnston KJA, Johnson EC, Nielsen TT, Galimberti M, Dao C, Levey DF, Overstreet C, Byrne EM, Gillespie NA, Gordon S, Hickie IB, Whitfield JB, Xu K, Zhao H, Huckins LM, Davis LK, Sanchez-Roige S, Madden PAF, Heath AC, Medland SE, Martin NG, Ge T, Smoller JW, Hougaard DM, Børglum AD, Demontis D, Krystal JH, Gaziano JM, Edenberg HJ, Agrawal A, Justice AC, Stein MB, Kranzler HR, Gelernter J. Multi-ancestry study of the genetics of problematic alcohol use in over 1 million individuals. Nat Med 2023; 29:3184-3192. [PMID: 38062264 PMCID: PMC10719093 DOI: 10.1038/s41591-023-02653-5] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Accepted: 10/18/2023] [Indexed: 12/17/2023]
Abstract
Problematic alcohol use (PAU), a trait that combines alcohol use disorder and alcohol-related problems assessed with a questionnaire, is a leading cause of death and morbidity worldwide. Here we conducted a large cross-ancestry meta-analysis of PAU in 1,079,947 individuals (European, N = 903,147; African, N = 122,571; Latin American, N = 38,962; East Asian, N = 13,551; and South Asian, N = 1,716 ancestries). We observed a high degree of cross-ancestral similarity in the genetic architecture of PAU and identified 110 independent risk variants in within- and cross-ancestry analyses. Cross-ancestry fine mapping improved the identification of likely causal variants. Prioritizing genes through gene expression and chromatin interaction in brain tissues identified multiple genes associated with PAU. We identified existing medications for potential pharmacological studies by a computational drug repurposing analysis. Cross-ancestry polygenic risk scores showed better performance of association in independent samples than single-ancestry polygenic risk scores. Genetic correlations between PAU and other traits were observed in multiple ancestries, with other substance use traits having the highest correlations. This study advances our knowledge of the genetic etiology of PAU, and these findings may bring possible clinical applicability of genetics insights-together with neuroscience, biology and data science-closer.
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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.
- Section of Biomedical Informatics and Data Science, Yale School of Medicine, New Haven, CT, USA.
| | - Rachel L Kember
- Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Joseph D Deak
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Heng Xu
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Sylvanus Toikumo
- Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Kai Yuan
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Penelope A Lind
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- School of Biomedical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
- Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia
| | - Leila Farajzadeh
- Department of Biomedicine - Human Genetics, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - Lu Wang
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Alexander S Hatoum
- Department of Psychological and Brain Sciences, Washington University in St. Louis, Saint Louis, MO, USA
| | - Jessica Johnson
- Pamela Sklar Division of Psychiatric Genomics, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Hyunjoon Lee
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Travis T Mallard
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Jiayi Xu
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | | | - Emma C Johnson
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Trine Tollerup Nielsen
- Department of Biomedicine - Human Genetics, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - Marco Galimberti
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Cecilia Dao
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Daniel F Levey
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Cassie Overstreet
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Enda M Byrne
- Child Health Research Centre, The University of Queensland, Brisbane, Queensland, Australia
| | - Nathan A Gillespie
- Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Scott Gordon
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Ian B Hickie
- Brain and Mind Centre, University of Sydney, Camperdown, New South Wales, Australia
| | - John B Whitfield
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Ke Xu
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Hongyu Zhao
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
| | - Laura M Huckins
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Lea K Davis
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Medicine, Division of Medical Genetics, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Sandra Sanchez-Roige
- Department of Medicine, Division of Medical Genetics, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Pamela A F Madden
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Andrew C Heath
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Sarah E Medland
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia
- School of Psychology, University of Queensland, Brisbane, Queensland, Australia
| | - Nicholas G Martin
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Tian Ge
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Center for Precision Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Jordan W Smoller
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Center for Precision Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - David M Hougaard
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Neonatal Screening, Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark
| | - Anders D Børglum
- Department of Biomedicine - Human Genetics, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - Ditte Demontis
- Department of Biomedicine - Human Genetics, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
- The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - John H Krystal
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA
- National Center for PTSD, US Department of Veterans Affairs, West Haven, CT, USA
- Department of Psychology, Yale University, New Haven, CT, USA
- Psychiatry and Behavioral Health Services, Yale-New Haven Hospital, New Haven, CT, USA
| | - J Michael Gaziano
- Massachusetts Veterans Epidemiology and Research Information Center (MAVERIC), Boston Veterans Affairs Healthcare System, Boston, MA, USA
- Department of Medicine, Divisions of Aging and Preventative Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Howard J Edenberg
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Amy C Justice
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
- 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
| | - Murray B Stein
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Psychiatry Service, VA San Diego Healthcare System, San Diego, CA, USA
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Henry R Kranzler
- Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Joel Gelernter
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA.
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA.
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA.
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA.
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16
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Waszczuk MA, Jonas KG, Bornovalova M, Breen G, Bulik CM, Docherty AR, Eley TC, Hettema JM, Kotov R, Krueger RF, Lencz T, Li JJ, Vassos E, Waldman ID. Dimensional and transdiagnostic phenotypes in psychiatric genome-wide association studies. Mol Psychiatry 2023; 28:4943-4953. [PMID: 37402851 PMCID: PMC10764644 DOI: 10.1038/s41380-023-02142-8] [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: 01/17/2023] [Revised: 05/17/2023] [Accepted: 06/16/2023] [Indexed: 07/06/2023]
Abstract
Genome-wide association studies (GWAS) provide biological insights into disease onset and progression and have potential to produce clinically useful biomarkers. A growing body of GWAS focuses on quantitative and transdiagnostic phenotypic targets, such as symptom severity or biological markers, to enhance gene discovery and the translational utility of genetic findings. The current review discusses such phenotypic approaches in GWAS across major psychiatric disorders. We identify themes and recommendations that emerge from the literature to date, including issues of sample size, reliability, convergent validity, sources of phenotypic information, phenotypes based on biological and behavioral markers such as neuroimaging and chronotype, and longitudinal phenotypes. We also discuss insights from multi-trait methods such as genomic structural equation modelling. These provide insight into how hierarchical 'splitting' and 'lumping' approaches can be applied to both diagnostic and dimensional phenotypes to model clinical heterogeneity and comorbidity. Overall, dimensional and transdiagnostic phenotypes have enhanced gene discovery in many psychiatric conditions and promises to yield fruitful GWAS targets in the years to come.
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Affiliation(s)
- Monika A Waszczuk
- Department of Psychology, Rosalind Franklin University of Medicine and Science, North Chicago, IL, USA.
| | - Katherine G Jonas
- Department of Psychiatry, Stony Brook University School of Medicine, Stony Brook, NY, USA
| | | | - Gerome Breen
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- UK National Institute for Health and Care Research (NIHR) Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
| | - Cynthia M Bulik
- Department of Psychiatry, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Anna R Docherty
- Huntsman Mental Health Institute, Department of Psychiatry, University of Utah School of Medicine, Salt Lake City, UT, USA
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
| | - Thalia C Eley
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- UK National Institute for Health and Care Research (NIHR) Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
| | - John M Hettema
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
- Department of Psychiatry, Texas A&M Health Sciences Center, Bryan, TX, USA
| | - Roman Kotov
- Department of Psychiatry, Stony Brook University School of Medicine, Stony Brook, NY, USA
| | - Robert F Krueger
- Psychology Department, University of Minnesota, Minneapolis, MN, USA
| | - Todd Lencz
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Department of Psychiatry, Division of Research, The Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, USA
- Institute for Behavioral Science, The Feinstein Institutes for Medical Research, Manhasset, NY, USA
| | - James J Li
- Department of Psychology, University of Wisconsin, Madison, WI, USA
- Waisman Center, University of Wisconsin, Madison, WI, USA
| | - Evangelos Vassos
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- UK National Institute for Health and Care Research (NIHR) Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
| | - Irwin D Waldman
- Department of Psychology, Emory University, Atlanta, GA, USA
- Center for Computational and Quantitative Genetics, Emory University, Atlanta, GA, USA
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17
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Miller AP, Kuo SIC, Johnson EC, Tillman R, Brislin SJ, Dick DM, Kamarajan C, Kinreich S, Kramer J, McCutcheon VV, Plawecki MH, Porjesz B, Schuckit MA, Salvatore JE, Edenberg HJ, Bucholz KK, Meyers JL, Agrawal A. Diagnostic Criteria for Identifying Individuals at High Risk of Progression From Mild or Moderate to Severe Alcohol Use Disorder. JAMA Netw Open 2023; 6:e2337192. [PMID: 37815828 PMCID: PMC10565602 DOI: 10.1001/jamanetworkopen.2023.37192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Accepted: 08/22/2023] [Indexed: 10/11/2023] Open
Abstract
Importance Current Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) (DSM-5) diagnoses of substance use disorders rely on criterion count-based approaches, disregarding severity grading indexed by individual criteria. Objective To examine correlates of alcohol use disorder (AUD) across count-based severity groups (ie, mild, moderate, mild-to-moderate, severe), identify specific diagnostic criteria indicative of greater severity, and evaluate whether specific criteria within mild-to-moderate AUD differentiate across relevant correlates and manifest in greater hazards of severe AUD development. Design, Setting, and Participants This cohort study involved 2 cohorts from the family-based Collaborative Study on the Genetics of Alcoholism (COGA) with 7 sites across the United States: cross-sectional (assessed 1991-2005) and longitudinal (assessed 2004-2019). Statistical analyses were conducted from December 2022 to June 2023. Main Outcomes and Measures Sociodemographic, alcohol-related, psychiatric comorbidity, brain electroencephalography (EEG), and AUD polygenic score measures as correlates of DSM-5 AUD levels (ie, mild, moderate, severe) and criterion severity-defined mild-to-moderate AUD diagnostic groups (ie, low-risk vs high-risk mild-to-moderate). Results A total of 13 110 individuals from the cross-sectional COGA cohort (mean [SD] age, 37.8 [14.2] years) and 2818 individuals from the longitudinal COGA cohort (mean baseline [SD] age, 16.1 [3.2] years) were included. Associations with alcohol-related, psychiatric, EEG, and AUD polygenic score measures reinforced the role of increasing criterion counts as indexing severity. Yet within mild-to-moderate AUD (2-5 criteria), the presence of specific high-risk criteria (eg, withdrawal) identified a group reporting heavier drinking and greater psychiatric comorbidity even after accounting for criterion count differences. In longitudinal analyses, prior mild-to-moderate AUD characterized by endorsement of at least 1 high-risk criterion was associated with more accelerated progression to severe AUD (adjusted hazard ratio [aHR], 11.62; 95% CI, 7.54-17.92) compared with prior mild-to-moderate AUD without endorsement of high-risk criteria (aHR, 5.64; 95% CI, 3.28-9.70), independent of criterion count. Conclusions and Relevance In this cohort study of a combined 15 928 individuals, findings suggested that simple count-based AUD diagnostic approaches to estimating severe AUD vulnerability, which ignore heterogeneity among criteria, may be improved by emphasizing specific high-risk criteria. Such emphasis may allow better focus on individuals at the greatest risk and improve understanding of the development of AUD.
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Affiliation(s)
- Alex P. Miller
- Department of Psychiatry, Washington University School of Medicine, St Louis, Missouri
| | - Sally I-Chun Kuo
- Department of Psychiatry, Rutgers Robert Wood Johnson Medical School, Piscataway, New Jersey
| | - Emma C. Johnson
- Department of Psychiatry, Washington University School of Medicine, St Louis, Missouri
| | - Rebecca Tillman
- Department of Psychiatry, Washington University School of Medicine, St Louis, Missouri
| | - Sarah J. Brislin
- Department of Psychiatry, Rutgers Robert Wood Johnson Medical School, Piscataway, New Jersey
| | - Danielle M. Dick
- Department of Psychiatry, Rutgers Robert Wood Johnson Medical School, Piscataway, New Jersey
| | - Chella Kamarajan
- Department of Psychiatry and Behavioral Sciences, State University of New York Health Sciences University, Brooklyn
| | - Sivan Kinreich
- Department of Psychiatry and Behavioral Sciences, State University of New York Health Sciences University, Brooklyn
| | - John Kramer
- Department of Psychiatry, University of Iowa, Iowa City
| | - Vivia V. McCutcheon
- Department of Psychiatry, Washington University School of Medicine, St Louis, Missouri
| | | | - Bernice Porjesz
- Department of Psychiatry and Behavioral Sciences, State University of New York Health Sciences University, Brooklyn
| | - Marc A. Schuckit
- Department of Psychiatry, University of California San Diego Medical School, San Diego
| | - Jessica E. Salvatore
- Department of Psychiatry, Rutgers Robert Wood Johnson Medical School, Piscataway, New Jersey
| | - Howard J. Edenberg
- Department of Biochemistry and Molecular Biology, Indiana University, Indianapolis
| | - Kathleen K. Bucholz
- Department of Psychiatry, Washington University School of Medicine, St Louis, Missouri
| | - Jaquelyn L. Meyers
- Department of Psychiatry and Behavioral Sciences, State University of New York Health Sciences University, Brooklyn
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of Medicine, St Louis, Missouri
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18
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Thijssen AB, Dick DM, Posthuma D, Savage JE. Investigating genetically stratified subgroups to better understand the etiology of alcohol misuse. Mol Psychiatry 2023; 28:4225-4233. [PMID: 37488169 PMCID: PMC10827662 DOI: 10.1038/s41380-023-02174-0] [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: 02/28/2023] [Revised: 06/15/2023] [Accepted: 06/28/2023] [Indexed: 07/26/2023]
Abstract
Alcohol misuse (AM) is highly prevalent and harmful, with theorized subgroups differing on internalizing and externalizing dimensions. Despite known heterogeneity, genome-wide association studies (GWAS) are usually conducted on unidimensional phenotypes. These approaches have identified important genes related to AM but fail to capture a large part of the heritability, even with recent increases in sample sizes. This study aimed to address phenotypic heterogeneity in GWAS to aid gene finding and to uncover the etiology of different types of AM. Genetic and phenotypic data from 410,414 unrelated individuals of multiple ancestry groups (primarily European) in the UK Biobank were obtained. Mixture modeling was applied to measures of alcohol misuse and internalizing/externalizing psychopathology to uncover phenotypically homogenous subclasses, which were carried forward to GWAS and functional annotation. A four-class model emerged with "low risk", "internalizing-light/non-drinkers", "heavy alcohol use-low impairment", and "broad high risk" classes. SNP heritability ranged from 3 to 18% and both known AM signals and novel signals were captured by genomic risk loci. Class comparisons showed distinct patterns of regional brain tissue enrichment and genetic correlations with internalizing and externalizing phenotypes. Despite some limitations, this study demonstrated the utility of genetic research on homogenous subclasses. Not only were novel genetic signals identified that might be used for follow-up studies, but addressing phenotypic heterogeneity allows for the discovery and investigation of differential genetic vulnerabilities in the development of AM, which is an important step towards the goal of personalized medicine.
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Affiliation(s)
- Anaïs B Thijssen
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Danielle M Dick
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers-The State University of New Jersey, Piscataway, NJ, USA
| | - Danielle Posthuma
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Department of Clinical Genetics, Section Complex Trait Genetics, Amsterdam Neuroscience, Vrije Universiteit Medical Center, Amsterdam, The Netherlands
| | - Jeanne E Savage
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands.
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19
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Gameiro‐Ros I, Popova D, Prytkova I, Pang ZP, Liu Y, Dick D, Bucholz KK, Agrawal A, Porjesz B, Goate AM, Xuei X, Kamarajan C, Tischfield JA, Edenberg HJ, Slesinger PA, Hart RP. 5. Collaborative Study on the Genetics of Alcoholism: Functional genomics. GENES, BRAIN, AND BEHAVIOR 2023; 22:e12855. [PMID: 37533187 PMCID: PMC10550792 DOI: 10.1111/gbb.12855] [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: 03/07/2023] [Revised: 05/31/2023] [Accepted: 06/17/2023] [Indexed: 08/04/2023]
Abstract
Alcohol Use Disorder is a complex genetic disorder, involving genetic, neural, and environmental factors, and their interactions. The Collaborative Study on the Genetics of Alcoholism (COGA) has been investigating these factors and identified putative alcohol use disorder risk genes through genome-wide association studies. In this review, we describe advances made by COGA in elucidating the functional changes induced by alcohol use disorder risk genes using multimodal approaches with human cell lines and brain tissue. These studies involve investigating gene regulation in lymphoblastoid cells from COGA participants and in post-mortem brain tissues. High throughput reporter assays are being used to identify single nucleotide polymorphisms in which alternate alleles differ in driving gene expression. Specific single nucleotide polymorphisms (both coding or noncoding) have been modeled using induced pluripotent stem cells derived from COGA participants to evaluate the effects of genetic variants on transcriptomics, neuronal excitability, synaptic physiology, and the response to ethanol in human neurons from individuals with and without alcohol use disorder. We provide a perspective on future studies, such as using polygenic risk scores and populations of induced pluripotent stem cell-derived neurons to identify signaling pathways related with responses to alcohol. Starting with genes or loci associated with alcohol use disorder, COGA has demonstrated that integration of multimodal data within COGA participants and functional studies can reveal mechanisms linking genomic variants with alcohol use disorder, and potential targets for future treatments.
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Affiliation(s)
- Isabel Gameiro‐Ros
- Nash Family Department of NeuroscienceIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Dina Popova
- Human Genetics Institute of New JerseyRutgers UniversityPiscatawayNew JerseyUSA
| | - Iya Prytkova
- Nash Family Department of NeuroscienceIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Zhiping P. Pang
- Human Genetics Institute of New JerseyRutgers UniversityPiscatawayNew JerseyUSA
- Child Health Institute of New Jersey and Department of Neuroscience and Cell Biology, Robert Wood Johnson Medical SchoolRutgers UniversityNew BrunswickNew JerseyUSA
| | - Yunlong Liu
- Department of Medical and Molecular GeneticsIndiana University School of MedicineIndianapolisIndianaUSA
| | - Danielle Dick
- Rutgers Addiction Research Center, Robert Wood Johnson Medical SchoolRutgers UniversityPiscatawayNew JerseyUSA
| | - Kathleen K. Bucholz
- Department of PsychiatryWashington University School of MedicineSt. LouisMissouriUSA
| | - Arpana Agrawal
- Department of PsychiatryWashington University School of MedicineSt. LouisMissouriUSA
| | - Bernice Porjesz
- Department of Psychiatry and Behavioral SciencesSUNY Downstate Health Sciences UniversityBrooklynNew YorkUSA
| | - Alison M. Goate
- Nash Family Department of NeuroscienceIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Xiaoling Xuei
- Department of Medical and Molecular GeneticsIndiana University School of MedicineIndianapolisIndianaUSA
| | - Chella Kamarajan
- Department of Psychiatry and Behavioral SciencesSUNY Downstate Health Sciences UniversityBrooklynNew YorkUSA
| | | | - Jay A. Tischfield
- Human Genetics Institute of New JerseyRutgers UniversityPiscatawayNew JerseyUSA
- Department of GeneticsRutgers UniversityPiscatawayNew JerseyUSA
| | - Howard J. Edenberg
- Department of Biochemistry and Molecular BiologyIndiana University School of MedicineIndianapolisIndianaUSA
- Department of Medical and Molecular GeneticsIndiana UniversityIndianapolisIndianaUSA
| | - Paul A. Slesinger
- Nash Family Department of NeuroscienceIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Ronald P. Hart
- Human Genetics Institute of New JerseyRutgers UniversityPiscatawayNew JerseyUSA
- Department of Cell Biology and NeuroscienceRutgers UniversityPiscatawayNew JerseyUSA
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20
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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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Kendler KS, Ohlsson H, Sundquist J, Sundquist K. Contagious Transmission in a Swedish National Sample of Alcohol Use Disorders as a Function of Geographical Proximity Among Siblings and Propinquity-of-Rearing Defined Acquaintances. J Stud Alcohol Drugs 2023; 84:670-679. [PMID: 37219029 PMCID: PMC10600968 DOI: 10.15288/jsad.23-00003] [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: 01/04/2023] [Accepted: 05/09/2023] [Indexed: 05/24/2023] Open
Abstract
OBJECTIVE The purpose of this study was to determine whether alcohol use disorder (AUD) can be transmitted contagiously in siblings and likely acquaintances growing up close to one another (Propinquity-of-Rearing Defined Acquaintances [PRDAs]). METHOD PRDAs were pairs of same-age subjects growing up within 1 km of each other and sharing the same school class, where one of whom (PRDA1) was first registered for AUD at age 15 or older. Using adult residential location, we predicted proximity-dependent risk for an AUD first registration in a second PRDA within 3 years of PRDA1's registration. RESULTS In 150,195 informative siblings, cohabitation status (hazard ratio [HR] = 1.22, 95% confidence interval [CI] [1.08, 1.37]), but not proximity, predicted risk for AUD onset. In 114,375 informative PRDA pairs, a log model fit best, predicting lower risk the greater the distance (HR = 0.88, 95% CI [0.84, 0.92]) with risks for AUD at 10, 50, and 100 km from affected PRDA1 cases equaling, respectively: 0.73 [0.66, 0.82], 0.60 [0.51, 0.72], and 0.55 [0.45, 0.68]. Within PRDA acquaintanceships, results resembled those found among PRDA pairs. The proximity-dependent contagious risk for AUD among PRDA pairs was attenuated by increasing age, lower genetic risk, and higher educational attainment. CONCLUSIONS Cohabitation but not distance predicted transmission of AUD between siblings. However, contagious transmission of AUD among acquaintances growing up and attending school together was present and attenuated by increasing distance in adulthood. The impact of adult proximity on transmission was moderated by age, educational attainment, and genetic risk for AUD. Our results provide support for the validity of contagion models for AUD.
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Affiliation(s)
- Kenneth S. Kendler
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia
- Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia
| | - Henrik Ohlsson
- Center for Primary Health Care Research, Lund University, Malmö, Sweden
| | - Jan Sundquist
- Center for Primary Health Care Research, Lund University, Malmö, Sweden
- Department of Family Medicine and Community Health, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Kristina Sundquist
- Center for Primary Health Care Research, Lund University, Malmö, Sweden
- Department of Family Medicine and Community Health, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, New York
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Poore HE, Hatoum A, Mallard TT, Sanchez-Roige S, Waldman ID, Palmer AA, Paige Harden K, Barr PB, Dick DM. A multivariate approach to understanding the genetic overlap between externalizing phenotypes and substance use disorders. Addict Biol 2023; 28:e13319. [PMID: 37644899 PMCID: PMC11010459 DOI: 10.1111/adb.13319] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 05/24/2023] [Accepted: 07/17/2023] [Indexed: 08/31/2023]
Abstract
Substance use disorders (SUDs) are phenotypically and genetically correlated with each other and with other psychological traits characterized by behavioural under-control, termed externalizing phenotypes. In this study, we used genomic structural equation modelling to explore the shared genetic architecture among six externalizing phenotypes and four SUDs used in two previous multivariate genome-wide association studies of an externalizing and an addiction risk factor, respectively. We first evaluated five confirmatory factor analytic models, including a common factor model, alternative parameterizations of two-factor structures and a bifactor model. We next explored the genetic correlations between factors identified in these models and other relevant psychological traits. Finally, we quantified the degree of polygenic overlap between externalizing and addiction risk using MiXeR. We found that the common and two-factor structures provided the best fit to the data, evidenced by high factor loadings, good factor reliability and no evidence of concerning model characteristics. The two-factor models yielded high genetic correlations between factors (rg s ≥ 0.87), and between the effect sizes of genetic correlations with external traits (rg ≥ 0.95). Nevertheless, 21 of the 84 correlations with external criteria showed small, significant differences between externalizing and addiction risk factors. MiXer results showed that approximately 81% of influential externalizing variants were shared with addiction risk, whereas addiction risk shared 56% of its influential variants with externalizing. These results suggest that externalizing and addiction genetic risk are largely shared, though both constructs also retain meaningful unshared genetic variance. These results can inform future efforts to identify specific genetic influences on externalizing and SUDs.
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Affiliation(s)
- Holly E. Poore
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, New Jersey, USA
| | - Alexander Hatoum
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Travis T. Mallard
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Sandra Sanchez-Roige
- Department of Psychiatry, University of California, San Diego, San Diego, California, USA
- Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Irwin D. Waldman
- Department of Psychology, Emory University, Atlanta, Georgia, USA
| | - Abraham A. Palmer
- Department of Psychiatry, University of California, San Diego, San Diego, California, USA
- Institute for Genomic Medicine, University of California, San Diego, San Diego, California, USA
| | - K. Paige Harden
- Department of Psychology, University of Texas at Austin, Austin, Texas, USA
- Population Research Center, University of Texas at Austin, Austin, Texas, USA
| | - Peter B. Barr
- Department of Psychiatry & Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, New York, USA
- VA New York Harbor Healthcare System, Brooklyn, New York, USA
| | - Danielle M. Dick
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, New Jersey, USA
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23
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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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Rosoff DB, Mavromatis LA, Bell AS, Wagner J, Jung J, Marioni RE, Davey Smith G, Horvath S, Lohoff FW. Multivariate genome-wide analysis of aging-related traits identifies novel loci and new drug targets for healthy aging. NATURE AGING 2023; 3:1020-1035. [PMID: 37550455 PMCID: PMC10432278 DOI: 10.1038/s43587-023-00455-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 06/07/2023] [Indexed: 08/09/2023]
Abstract
The concept of aging is complex, including many related phenotypes such as healthspan, lifespan, extreme longevity, frailty and epigenetic aging, suggesting shared biological underpinnings; however, aging-related endpoints have been primarily assessed individually. Using data from these traits and multivariate genome-wide association study methods, we modeled their underlying genetic factor ('mvAge'). mvAge (effective n = ~1.9 million participants of European ancestry) identified 52 independent variants in 38 genomic loci. Twenty variants were novel (not reported in input genome-wide association studies). Transcriptomic imputation identified age-relevant genes, including VEGFA and PHB1. Drug-target Mendelian randomization with metformin target genes showed a beneficial impact on mvAge (P value = 8.41 × 10-5). Similarly, genetically proxied thiazolidinediones (P value = 3.50 × 10-10), proprotein convertase subtilisin/kexin 9 inhibition (P value = 1.62 × 10-6), angiopoietin-like protein 4, beta blockers and calcium channel blockers also had beneficial Mendelian randomization estimates. Extending the drug-target Mendelian randomization framework to 3,947 protein-coding genes prioritized 122 targets. Together, these findings will inform future studies aimed at improving healthy aging.
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Affiliation(s)
- Daniel B Rosoff
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
- NIH-Oxford-Cambridge Scholars Program; Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
| | - Lucas A Mavromatis
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Andrew S Bell
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Josephin Wagner
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Jeesun Jung
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
| | - Steve Horvath
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- San Diego Institute of Science, Alto Labs, San Diego, CA, USA
| | - Falk W Lohoff
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA.
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25
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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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26
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Kember RL, Vickers-Smith R, Zhou H, Xu H, Jennings M, Dao C, Davis L, Sanchez-Roige S, Justice AC, Gelernter J, Vujkovic M, Kranzler HR. Genetic Underpinnings of the Transition From Alcohol Consumption to Alcohol Use Disorder: Shared and Unique Genetic Architectures in a Cross-Ancestry Sample. Am J Psychiatry 2023; 180:584-593. [PMID: 37282553 PMCID: PMC10731616 DOI: 10.1176/appi.ajp.21090892] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
OBJECTIVE Recent genome-wide association studies (GWASs) of alcohol-related phenotypes have uncovered key differences in the underlying genetic architectures of alcohol consumption and alcohol use disorder (AUD), with the two traits having opposite genetic correlations with psychiatric disorders. Understanding the genetic factors that underlie the transition from heavy drinking to AUD has important theoretical and clinical implications. METHODS The authors used longitudinal data from the cross-ancestry Million Veteran Program sample to identify 1) novel loci associated with AUD and alcohol consumption (measured by the score on the consumption subscale of the Alcohol Use Disorders Identification Test [AUDIT-C]), 2) the impact of phenotypic variation on genetic discovery, and 3) genetic variants with direct effects on AUD that are not mediated through alcohol consumption. RESULTS The authors identified 26 loci associated with AUD and 22 loci associated with AUDIT-C score, including ancestry-specific and novel loci. In secondary GWASs that excluded individuals who report abstinence, the authors identified seven additional loci for AUD and eight additional loci for AUDIT-C score. Although the heterogeneity of the abstinent group biases the GWAS findings, unique variance between alcohol consumption and disorder remained after the abstinent group was excluded. Finally, using mediation analysis, the authors identified a set of variants with effects on AUD that are not mediated through alcohol consumption. CONCLUSIONS Differences in genetic architecture between alcohol consumption and AUD are consistent with their having different biological contributions. Genetic variants with direct effects on AUD are potentially relevant to understanding the transition from heavy alcohol consumption to AUD and may be targets for translational prevention and treatment efforts.
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Affiliation(s)
- Rachel L Kember
- Mental Illness Research, Education, and Clinical Center, Veterans Integrated Service Network 4, Crescenz Veterans Affairs Medical Center, Philadelphia (Kember, Vickers-Smith, Kranzler); Center for Studies of Addiction, Department of Psychiatry (Kember, Xu, Kranzler) and Department of Epidemiology, University of Kentucky College of Public Health, Lexington (Vickers-Smith); Center on Drug and Alcohol Research, Department of Behavioral Science, University of Kentucky College of Medicine, Lexington (Vickers-Smith); VA Connecticut Healthcare System, West Haven (Zhou, Dao, Justice, Gelernter); Department of Psychiatry (Zhou, Gelernter), Department of Genetics (Gelernter), Department of Neuroscience (Gelernter), and Department of Internal Medicine (Justice), Yale School of Medicine, New Haven, Conn.; School of Public Health, Yale University, New Haven, Conn. (Dao, Justice); Department of Psychiatry, University of California San Diego, San Diego (Jennings, Sanchez-Roige); Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tenn. (Davis, Sanchez-Roige)
| | - Rachel Vickers-Smith
- Mental Illness Research, Education, and Clinical Center, Veterans Integrated Service Network 4, Crescenz Veterans Affairs Medical Center, Philadelphia (Kember, Vickers-Smith, Kranzler); Center for Studies of Addiction, Department of Psychiatry (Kember, Xu, Kranzler) and Department of Epidemiology, University of Kentucky College of Public Health, Lexington (Vickers-Smith); Center on Drug and Alcohol Research, Department of Behavioral Science, University of Kentucky College of Medicine, Lexington (Vickers-Smith); VA Connecticut Healthcare System, West Haven (Zhou, Dao, Justice, Gelernter); Department of Psychiatry (Zhou, Gelernter), Department of Genetics (Gelernter), Department of Neuroscience (Gelernter), and Department of Internal Medicine (Justice), Yale School of Medicine, New Haven, Conn.; School of Public Health, Yale University, New Haven, Conn. (Dao, Justice); Department of Psychiatry, University of California San Diego, San Diego (Jennings, Sanchez-Roige); Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tenn. (Davis, Sanchez-Roige)
| | - Hang Zhou
- Mental Illness Research, Education, and Clinical Center, Veterans Integrated Service Network 4, Crescenz Veterans Affairs Medical Center, Philadelphia (Kember, Vickers-Smith, Kranzler); Center for Studies of Addiction, Department of Psychiatry (Kember, Xu, Kranzler) and Department of Epidemiology, University of Kentucky College of Public Health, Lexington (Vickers-Smith); Center on Drug and Alcohol Research, Department of Behavioral Science, University of Kentucky College of Medicine, Lexington (Vickers-Smith); VA Connecticut Healthcare System, West Haven (Zhou, Dao, Justice, Gelernter); Department of Psychiatry (Zhou, Gelernter), Department of Genetics (Gelernter), Department of Neuroscience (Gelernter), and Department of Internal Medicine (Justice), Yale School of Medicine, New Haven, Conn.; School of Public Health, Yale University, New Haven, Conn. (Dao, Justice); Department of Psychiatry, University of California San Diego, San Diego (Jennings, Sanchez-Roige); Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tenn. (Davis, Sanchez-Roige)
| | - Heng Xu
- Mental Illness Research, Education, and Clinical Center, Veterans Integrated Service Network 4, Crescenz Veterans Affairs Medical Center, Philadelphia (Kember, Vickers-Smith, Kranzler); Center for Studies of Addiction, Department of Psychiatry (Kember, Xu, Kranzler) and Department of Epidemiology, University of Kentucky College of Public Health, Lexington (Vickers-Smith); Center on Drug and Alcohol Research, Department of Behavioral Science, University of Kentucky College of Medicine, Lexington (Vickers-Smith); VA Connecticut Healthcare System, West Haven (Zhou, Dao, Justice, Gelernter); Department of Psychiatry (Zhou, Gelernter), Department of Genetics (Gelernter), Department of Neuroscience (Gelernter), and Department of Internal Medicine (Justice), Yale School of Medicine, New Haven, Conn.; School of Public Health, Yale University, New Haven, Conn. (Dao, Justice); Department of Psychiatry, University of California San Diego, San Diego (Jennings, Sanchez-Roige); Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tenn. (Davis, Sanchez-Roige)
| | - Mariela Jennings
- Mental Illness Research, Education, and Clinical Center, Veterans Integrated Service Network 4, Crescenz Veterans Affairs Medical Center, Philadelphia (Kember, Vickers-Smith, Kranzler); Center for Studies of Addiction, Department of Psychiatry (Kember, Xu, Kranzler) and Department of Epidemiology, University of Kentucky College of Public Health, Lexington (Vickers-Smith); Center on Drug and Alcohol Research, Department of Behavioral Science, University of Kentucky College of Medicine, Lexington (Vickers-Smith); VA Connecticut Healthcare System, West Haven (Zhou, Dao, Justice, Gelernter); Department of Psychiatry (Zhou, Gelernter), Department of Genetics (Gelernter), Department of Neuroscience (Gelernter), and Department of Internal Medicine (Justice), Yale School of Medicine, New Haven, Conn.; School of Public Health, Yale University, New Haven, Conn. (Dao, Justice); Department of Psychiatry, University of California San Diego, San Diego (Jennings, Sanchez-Roige); Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tenn. (Davis, Sanchez-Roige)
| | - Cecilia Dao
- Mental Illness Research, Education, and Clinical Center, Veterans Integrated Service Network 4, Crescenz Veterans Affairs Medical Center, Philadelphia (Kember, Vickers-Smith, Kranzler); Center for Studies of Addiction, Department of Psychiatry (Kember, Xu, Kranzler) and Department of Epidemiology, University of Kentucky College of Public Health, Lexington (Vickers-Smith); Center on Drug and Alcohol Research, Department of Behavioral Science, University of Kentucky College of Medicine, Lexington (Vickers-Smith); VA Connecticut Healthcare System, West Haven (Zhou, Dao, Justice, Gelernter); Department of Psychiatry (Zhou, Gelernter), Department of Genetics (Gelernter), Department of Neuroscience (Gelernter), and Department of Internal Medicine (Justice), Yale School of Medicine, New Haven, Conn.; School of Public Health, Yale University, New Haven, Conn. (Dao, Justice); Department of Psychiatry, University of California San Diego, San Diego (Jennings, Sanchez-Roige); Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tenn. (Davis, Sanchez-Roige)
| | - Lea Davis
- Mental Illness Research, Education, and Clinical Center, Veterans Integrated Service Network 4, Crescenz Veterans Affairs Medical Center, Philadelphia (Kember, Vickers-Smith, Kranzler); Center for Studies of Addiction, Department of Psychiatry (Kember, Xu, Kranzler) and Department of Epidemiology, University of Kentucky College of Public Health, Lexington (Vickers-Smith); Center on Drug and Alcohol Research, Department of Behavioral Science, University of Kentucky College of Medicine, Lexington (Vickers-Smith); VA Connecticut Healthcare System, West Haven (Zhou, Dao, Justice, Gelernter); Department of Psychiatry (Zhou, Gelernter), Department of Genetics (Gelernter), Department of Neuroscience (Gelernter), and Department of Internal Medicine (Justice), Yale School of Medicine, New Haven, Conn.; School of Public Health, Yale University, New Haven, Conn. (Dao, Justice); Department of Psychiatry, University of California San Diego, San Diego (Jennings, Sanchez-Roige); Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tenn. (Davis, Sanchez-Roige)
| | - Sandra Sanchez-Roige
- Mental Illness Research, Education, and Clinical Center, Veterans Integrated Service Network 4, Crescenz Veterans Affairs Medical Center, Philadelphia (Kember, Vickers-Smith, Kranzler); Center for Studies of Addiction, Department of Psychiatry (Kember, Xu, Kranzler) and Department of Epidemiology, University of Kentucky College of Public Health, Lexington (Vickers-Smith); Center on Drug and Alcohol Research, Department of Behavioral Science, University of Kentucky College of Medicine, Lexington (Vickers-Smith); VA Connecticut Healthcare System, West Haven (Zhou, Dao, Justice, Gelernter); Department of Psychiatry (Zhou, Gelernter), Department of Genetics (Gelernter), Department of Neuroscience (Gelernter), and Department of Internal Medicine (Justice), Yale School of Medicine, New Haven, Conn.; School of Public Health, Yale University, New Haven, Conn. (Dao, Justice); Department of Psychiatry, University of California San Diego, San Diego (Jennings, Sanchez-Roige); Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tenn. (Davis, Sanchez-Roige)
| | - Amy C Justice
- Mental Illness Research, Education, and Clinical Center, Veterans Integrated Service Network 4, Crescenz Veterans Affairs Medical Center, Philadelphia (Kember, Vickers-Smith, Kranzler); Center for Studies of Addiction, Department of Psychiatry (Kember, Xu, Kranzler) and Department of Epidemiology, University of Kentucky College of Public Health, Lexington (Vickers-Smith); Center on Drug and Alcohol Research, Department of Behavioral Science, University of Kentucky College of Medicine, Lexington (Vickers-Smith); VA Connecticut Healthcare System, West Haven (Zhou, Dao, Justice, Gelernter); Department of Psychiatry (Zhou, Gelernter), Department of Genetics (Gelernter), Department of Neuroscience (Gelernter), and Department of Internal Medicine (Justice), Yale School of Medicine, New Haven, Conn.; School of Public Health, Yale University, New Haven, Conn. (Dao, Justice); Department of Psychiatry, University of California San Diego, San Diego (Jennings, Sanchez-Roige); Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tenn. (Davis, Sanchez-Roige)
| | - Joel Gelernter
- Mental Illness Research, Education, and Clinical Center, Veterans Integrated Service Network 4, Crescenz Veterans Affairs Medical Center, Philadelphia (Kember, Vickers-Smith, Kranzler); Center for Studies of Addiction, Department of Psychiatry (Kember, Xu, Kranzler) and Department of Epidemiology, University of Kentucky College of Public Health, Lexington (Vickers-Smith); Center on Drug and Alcohol Research, Department of Behavioral Science, University of Kentucky College of Medicine, Lexington (Vickers-Smith); VA Connecticut Healthcare System, West Haven (Zhou, Dao, Justice, Gelernter); Department of Psychiatry (Zhou, Gelernter), Department of Genetics (Gelernter), Department of Neuroscience (Gelernter), and Department of Internal Medicine (Justice), Yale School of Medicine, New Haven, Conn.; School of Public Health, Yale University, New Haven, Conn. (Dao, Justice); Department of Psychiatry, University of California San Diego, San Diego (Jennings, Sanchez-Roige); Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tenn. (Davis, Sanchez-Roige)
| | - Marijana Vujkovic
- Mental Illness Research, Education, and Clinical Center, Veterans Integrated Service Network 4, Crescenz Veterans Affairs Medical Center, Philadelphia (Kember, Vickers-Smith, Kranzler); Center for Studies of Addiction, Department of Psychiatry (Kember, Xu, Kranzler) and Department of Epidemiology, University of Kentucky College of Public Health, Lexington (Vickers-Smith); Center on Drug and Alcohol Research, Department of Behavioral Science, University of Kentucky College of Medicine, Lexington (Vickers-Smith); VA Connecticut Healthcare System, West Haven (Zhou, Dao, Justice, Gelernter); Department of Psychiatry (Zhou, Gelernter), Department of Genetics (Gelernter), Department of Neuroscience (Gelernter), and Department of Internal Medicine (Justice), Yale School of Medicine, New Haven, Conn.; School of Public Health, Yale University, New Haven, Conn. (Dao, Justice); Department of Psychiatry, University of California San Diego, San Diego (Jennings, Sanchez-Roige); Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tenn. (Davis, Sanchez-Roige)
| | - Henry R Kranzler
- Mental Illness Research, Education, and Clinical Center, Veterans Integrated Service Network 4, Crescenz Veterans Affairs Medical Center, Philadelphia (Kember, Vickers-Smith, Kranzler); Center for Studies of Addiction, Department of Psychiatry (Kember, Xu, Kranzler) and Department of Epidemiology, University of Kentucky College of Public Health, Lexington (Vickers-Smith); Center on Drug and Alcohol Research, Department of Behavioral Science, University of Kentucky College of Medicine, Lexington (Vickers-Smith); VA Connecticut Healthcare System, West Haven (Zhou, Dao, Justice, Gelernter); Department of Psychiatry (Zhou, Gelernter), Department of Genetics (Gelernter), Department of Neuroscience (Gelernter), and Department of Internal Medicine (Justice), Yale School of Medicine, New Haven, Conn.; School of Public Health, Yale University, New Haven, Conn. (Dao, Justice); Department of Psychiatry, University of California San Diego, San Diego (Jennings, Sanchez-Roige); Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tenn. (Davis, Sanchez-Roige)
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Lannoy S, Heron J, Hickman M, Edwards AC. Risk Factors for Binge Drinking in Young Adulthood: The Roles of Aggregate Genetic Liability and Impulsivity-Related Processes. J Stud Alcohol Drugs 2023; 84:499-507. [PMID: 36971764 PMCID: PMC10488311 DOI: 10.15288/jsad.22-00420] [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: 12/12/2022] [Accepted: 02/17/2023] [Indexed: 08/29/2023] Open
Abstract
OBJECTIVE Binge drinking is characterized by excessive alcohol use and is widespread in youth. We explore the relationship between binge drinking's risk factors by considering (a) aggregate genetic liability (polygenic risk score [PGS]) for alcohol use and problems and (b) impulsivity-related processes. We examined whether the associations between PGS and binge drinking were mediated by impulsivity, with a possible shared genetic liability between alcohol phenotypes and impulsivity. METHOD Participants were from the Avon Longitudinal Study of Parents and Children (N = 2,545). We evaluated PGS for alcohol use and problems and impulsivity-related processes (sensation seeking at age 18 and inhibition at age 24) and measured binge drinking frequency (24 years old) as the outcome. Correlations and structural equation models were used to test a hypothesized model of the relationships among these variables. RESULTS Higher binge drinking frequency was related to higher aggregate genetic liability for alcohol use and problems in both models (standardized betas = .055-.064, all ps < .009). We found an association between binge drinking and sensation seeking (standardized beta = .224, p < .0001) but not inhibition (standardized beta = -.015, p = .437). Although the association between binge drinking and PGS for alcohol use and problems was mainly direct, a proportion of the association with alcohol problems was mediated by sensation seeking (14.61%). CONCLUSIONS Targeting sensation seeking at the end of adolescence may be means to prevent binge drinking in adulthood, whereas considering the role of genetic factors may improve our understanding of at-risk youth.
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Affiliation(s)
- Séverine Lannoy
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, Virginia
| | - Jon Heron
- Population Health Sciences, University of Bristol, Bristol, United Kingdom
| | - Matthew Hickman
- Population Health Sciences, University of Bristol, Bristol, United Kingdom
| | - Alexis C. Edwards
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, Virginia
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Miller AP, Gizer IR. Neurogenetic and multi-omic sources of overlap among sensation seeking, alcohol consumption, and alcohol use disorder. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.05.30.23290733. [PMID: 37333128 PMCID: PMC10274973 DOI: 10.1101/2023.05.30.23290733] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Sensation seeking is bidirectionally associated with levels of alcohol consumption in both adult and adolescent samples and shared neurobiological and genetic influences may in part explain this association. Links between sensation seeking and alcohol use disorder (AUD) may primarily manifest via increased alcohol consumption rather than through direct effects on increasing problems and consequences. Here the overlap between sensation seeking, alcohol consumption, and AUD was examined using multivariate modeling approaches for genome-wide association study (GWAS) summary statistics in conjunction with neurobiologically-informed analyses at multiple levels of investigation. Meta-analytic and genomic structural equation modeling (GenomicSEM) approaches were used to conduct GWAS of sensation seeking, alcohol consumption, and AUD. Resulting summary statistics were used in downstream analyses to examine shared brain tissue enrichment of heritability and genome-wide evidence of overlap (e.g., stratified GenomicSEM, RRHO, genetic correlations with neuroimaging phenotypes) and to identify genomic regions likely contributing to observed genetic overlap across traits (e.g., HMAGMA, LAVA). Across approaches, results supported shared neurogenetic architecture between sensation seeking and alcohol consumption characterized by overlapping enrichment of genes expressed in midbrain and striatal tissues and variants associated with increased cortical surface area. Alcohol consumption and AUD evidenced overlap in relation to variants associated with decreased frontocortical thickness. Finally, genetic mediation models provided evidence of alcohol consumption mediating associations between sensation seeking and AUD. This study extends previous research by examining critical sources of neurogenetic and multi-omic overlap among sensation seeking, alcohol consumption, and AUD which may underlie observed phenotypic associations.
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Affiliation(s)
- Alex P. Miller
- Department of Psychiatry, School of Medicine, Washington University in St. Louis, St. Louis, MO, United States
| | - Ian R. Gizer
- Department of Psychological Sciences, University of Missouri, Columbia, MO, United States
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Mallard TT, Grotzinger AD, Smoller JW. Examining the shared etiology of psychopathology with genome-wide association studies. Physiol Rev 2023; 103:1645-1665. [PMID: 36634217 PMCID: PMC9988537 DOI: 10.1152/physrev.00016.2022] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 12/19/2022] [Accepted: 01/03/2023] [Indexed: 01/13/2023] Open
Abstract
Genome-wide association studies (GWASs) have ushered in a new era of reproducible discovery in psychiatric genetics. The field has now identified hundreds of common genetic variants that are associated with mental disorders, and many of them influence more than one disorder. By advancing the understanding of causal biology underlying psychopathology, GWAS results are poised to inform the development of novel therapeutics, stratification of at-risk patients, and perhaps even the revision of top-down classification systems in psychiatry. Here, we provide a concise review of GWAS findings with an emphasis on findings that have elucidated the shared genetic etiology of psychopathology, summarizing insights at three levels of analysis: 1) genome-wide architecture; 2) networks, pathways, and gene sets; and 3) individual variants/genes. Three themes emerge from these efforts. First, all psychiatric phenotypes are heritable, highly polygenic, and influenced by many pleiotropic variants with incomplete penetrance. Second, GWAS results highlight the broad etiological roles of neuronal biology, system-wide effects over localized effects, and early neurodevelopment as a critical period. Third, many loci that are robustly associated with multiple forms of psychopathology harbor genes that are involved in synaptic structure and function. Finally, we conclude our review by discussing the implications that GWAS results hold for the field of psychiatry, as well as expected challenges and future directions in the next stage of psychiatric genetics.
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Affiliation(s)
- Travis T Mallard
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, United States
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, Massachusetts, United States
| | - Andrew D Grotzinger
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, United States
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, Colorado, United States
| | - Jordan W Smoller
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, United States
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, Massachusetts, United States
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Stephenson M, Lannoy S, Edwards AC. Shared genetic liability for alcohol consumption, alcohol problems, and suicide attempt: Evaluating the role of impulsivity. Transl Psychiatry 2023; 13:87. [PMID: 36899000 PMCID: PMC10006209 DOI: 10.1038/s41398-023-02389-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Revised: 02/24/2023] [Accepted: 02/28/2023] [Indexed: 03/12/2023] Open
Abstract
Heavy drinking and diagnosis with alcohol use disorder (AUD) are consistently associated with risk for suicide attempt (SA). Though the shared genetic architecture among alcohol consumption and problems (ACP) and SA remains largely uncharacterized, impulsivity has been proposed as a heritable, intermediate phenotype for both alcohol problems and suicidal behavior. The present study investigated the extent to which shared liability for ACP and SA is genetically related to five dimensions of impulsivity. Analyses incorporated summary statistics from genome-wide association studies of alcohol consumption (N = 160,824), problems (N = 160,824), and dependence (N = 46,568), alcoholic drinks per week (N = 537,349), suicide attempt (N = 513,497), impulsivity (N = 22,861), and extraversion (N = 63,030). We used genomic structural equation modeling (Genomic SEM) to, first, estimate a common factor model with alcohol consumption, problems, and dependence, drinks per week, and SA included as indicators. Next, we evaluated the correlations between this common genetic factor and five factors representing genetic liability to negative urgency, positive urgency, lack of premeditation, sensation-seeking, and lack of perseverance. Common genetic liability to ACP and SA was significantly correlated with all five impulsive personality traits examined (rs = 0.24-0.53, ps < 0.002), and the largest correlation was with lack of premeditation, though supplementary analyses suggested that these findings were potentially more strongly influenced by ACP than SA. These analyses have potential implications for screening and prevention: Impulsivity can be comprehensively assessed in childhood, whereas heavy drinking and suicide attempt are quite rare prior to adolescence. Our findings provide preliminary evidence that features of impulsivity may serve as early indicators of genetic risk for alcohol problems and suicidality.
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Affiliation(s)
- Mallory Stephenson
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA.
| | - Séverine Lannoy
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Alexis C Edwards
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
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Quintero Reis A, Newton BA, Kessler R, Polimanti R, Wendt FR. Functional and molecular characterization of suicidality factors using phenotypic and genome-wide data. Mol Psychiatry 2023; 28:1064-1071. [PMID: 36604601 PMCID: PMC10005939 DOI: 10.1038/s41380-022-01929-5] [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: 08/29/2022] [Revised: 12/09/2022] [Accepted: 12/14/2022] [Indexed: 01/07/2023]
Abstract
Genome-wide association studies (GWAS) of suicidal thoughts and behaviors support the existence of genetic contributions. Continuous measures of psychiatric disorder symptom severity can sometimes model polygenic risk better than binarized definitions. We compared two severity measures of suicidal thoughts and behaviors at the molecular and functional levels using genome-wide data. We used summary association data from GWAS of four traits analyzed in 122,935 individuals of European ancestry: thought life was not worth living (TLNWL), thoughts of self-harm, actual self-harm, and attempted suicide. A new trait for suicidal thoughts and behaviors was constructed first, phenotypically, by aggregating the previous four traits (termed "suicidality") and second, genetically, by using genomic structural equation modeling (gSEM; termed S-factor). Suicidality and S-factor were compared using SNP-heritability (h2) estimates, genetic correlation (rg), partitioned h2, effect size distribution, transcriptomic correlations (ρGE) in the brain, and cross-population polygenic scoring (PGS). The S-factor had good model fit (χ2 = 0.21, AIC = 16.21, CFI = 1.00, SRMR = 0.024). Suicidality (h2 = 7.6%) had higher h2 than the S-factor (h2 = 2.54, Pdiff = 4.78 × 10-13). Although the S-factor had a larger number of non-null susceptibility loci (πc = 0.010), these loci had small effect sizes compared to those influencing suicidality (πc = 0.005, Pdiff = 0.045). The h2 of both traits was enriched for conserved biological pathways. The rg and ρGE support highly overlapping genetic and transcriptomic features between suicidality and the S-factor. PGS using European-ancestry SNP effect sizes strongly associated with TLNWL in Admixed Americans: Nagelkerke's R2 = 8.56%, P = 0.009 (PGSsuicidality) and Nagelkerke's R2 = 7.48%, P = 0.045 (PGSS-factor). An aggregate suicidality phenotype was statistically more heritable than the S-factor across all analyses and may be more informative for future genetic study designs interested in common genetic factors among different suicide related phenotypes.
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Affiliation(s)
- Andrea Quintero Reis
- American University of Antigua College of Medicine, Osbourn, Antigua and Barbuda
| | - Brendan A Newton
- Forensic Science Program, University of Toronto, Mississauga, ON, Canada
| | - Ronald Kessler
- Department of Health Care Policy, Harvard Medical School, Boston, MA, USA
| | - Renato Polimanti
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- VA CT Healthcare System, West Haven, CT, USA
| | - Frank R Wendt
- Forensic Science Program, University of Toronto, Mississauga, ON, Canada.
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA.
- VA CT Healthcare System, West Haven, CT, USA.
- Department of Anthropology, University of Toronto, Mississauga, ON, Canada.
- Biostatistics Division, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
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Miller AP, Gizer IR. Dual-systems models of the genetic architecture of impulsive personality traits: Neurogenetic evidence of distinct but related factors. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.02.10.23285725. [PMID: 36824800 PMCID: PMC9949186 DOI: 10.1101/2023.02.10.23285725] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/16/2023]
Abstract
Background Dual-systems models provide a parsimonious framework for understanding the interplay between cortical and subcortical brain regions relevant to impulsive personality traits (IPTs) and their associations with psychiatric disorders. Despite recent developments in multivariate analysis of genome-wide association studies (GWAS), molecular genetic investigations of these models have not been conducted. Methods Using extant IPT GWAS, we conducted confirmatory genomic structural equation models (GenomicSEM) to empirically evaluate dual-systems models of the genetic architecture of IPTs. Genetic correlations between results of multivariate GWAS of dual-systems factors and GWAS of relevant cortical and subcortical neuroimaging phenotypes (regional/structural volume, cortical surface area, cortical thickness) were calculated and compared. Results Evaluation of GenomicSEM model fit indices for dual-systems models suggested that these models highlight important sources of shared and unique genetic variance between top-down and bottom-up constructs. Specifically, a dual-systems genomic model consisting of sensation seeking and lack of self-control factors demonstrated distinct but related sources of genetic influences ( r g =.60). Genetic correlation analyses provided evidence of differential associations between dual-systems factors and cortical neuroimaging phenotypes (e.g., lack of self-control negatively associated with cortical thickness, sensation seeking positively associated with cortical surface area). However, no significant associations were observed for subcortical phenotypes inconsistent with hypothesized functional localization of dual-systems constructs. Conclusions Dual-systems models of the genetic architecture of IPTs tested here demonstrate evidence of shared and unique genetic influences and associations with relevant neuroimaging phenotypes. These findings emphasize potential advantages in utilizing dual-systems models to study genetic influences for IPTs and transdiagnostic associations with psychiatric disorders.
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Zhou H, Kember RL, Deak JD, Xu H, Toikumo S, Yuan K, Lind PA, Farajzadeh L, Wang L, Hatoum AS, Johnson J, Lee H, Mallard TT, Xu J, Johnston KJ, Johnson EC, Galimberti M, Dao C, Levey DF, Overstreet C, Byrne EM, Gillespie NA, Gordon S, Hickie IB, Whitfield JB, Xu K, Zhao H, Huckins LM, Davis LK, Sanchez-Roige S, Madden PAF, Heath AC, Medland SE, Martin NG, Ge T, Smoller JW, Hougaard DM, Børglum AD, Demontis D, Krystal JH, Gaziano JM, Edenberg HJ, Agrawal A, Justice AC, Stein MB, Kranzler HR, Gelernter J. Multi-ancestry study of the genetics of problematic alcohol use in >1 million individuals. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.01.24.23284960. [PMID: 36747741 PMCID: PMC9901058 DOI: 10.1101/2023.01.24.23284960] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
Problematic alcohol use (PAU) is a leading cause of death and disability worldwide. To improve our understanding of the genetics of PAU, we conducted a large cross-ancestry meta-analysis of PAU in 1,079,947 individuals. We observed a high degree of cross-ancestral similarity in the genetic architecture of PAU and identified 110 independent risk variants in within- and cross-ancestry analyses. Cross-ancestry fine-mapping improved the identification of likely causal variants. Prioritizing genes through gene expression and/or chromatin interaction in brain tissues identified multiple genes associated with PAU. We identified existing medications for potential pharmacological studies by drug repurposing analysis. Cross-ancestry polygenic risk scores (PRS) showed better performance in independent sample than single-ancestry PRS. Genetic correlations between PAU and other traits were observed in multiple ancestries, with other substance use traits having the highest correlations. The analysis of diverse ancestries contributed significantly to the findings, and fills an important gap in the literature.
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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
- These authors contributed equally
| | - Rachel L. Kember
- Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- These authors contributed equally
| | - Joseph D. Deak
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Heng Xu
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Sylvanus Toikumo
- Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Kai Yuan
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Penelope A. Lind
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, Queensland University of Technology, Brisbane, QLD, Australia
- Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
| | - Leila Farajzadeh
- Department of Biomedicine - Human Genetics, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - Lu Wang
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Alexander S. Hatoum
- Department of Psychological and Brain Sciences, Washington University in St. Louis, Saint Louis, MO, USA
| | - Jessica Johnson
- Pamela Sklar Division of Psychiatric Genomics, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Hyunjoon Lee
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Travis T. Mallard
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Jiayi Xu
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | | | - Emma C. Johnson
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Marco Galimberti
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Cecilia Dao
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
- Department of Chronic Disease Epidemiology, Yale University School of Public Health, New Haven, CT, USA
| | - Daniel F. Levey
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Cassie Overstreet
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Enda M. Byrne
- Child Health Research Centre, The University of Queensland, Brisbane, QLD, Australia
| | - Nathan A. Gillespie
- Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Scott Gordon
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Ian B. Hickie
- Brain and Mind Centre, University of Sydney, Camperdown, NSW, Australia
| | - John B. Whitfield
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Ke Xu
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Hongyu Zhao
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
| | - Laura M. Huckins
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Lea K. Davis
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Medicine, Division of Medical Genetics, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Sandra Sanchez-Roige
- Department of Medicine, Division of Medical Genetics, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Pamela A. F. Madden
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Andrew C. Heath
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Sarah E. Medland
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
- School of Psychology, University of Queensland, Brisbane, QLD, Australia
| | - Nicholas G. Martin
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Tian Ge
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Center for Precision Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Jordan W. Smoller
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - David M. Hougaard
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark
- Center for Neonatal Screening, Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark
| | - Anders D. Børglum
- Department of Biomedicine - Human Genetics, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - Ditte Demontis
- Department of Biomedicine - Human Genetics, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - John H. Krystal
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT, USA
- National Center for PTSD, US Department of Veterans Affairs, West Haven, CT, USA
| | - J. Michael Gaziano
- Massachusetts Veterans Epidemiology and Research Information Center (MAVERIC), Boston Veterans Affairs Healthcare System, Boston, MA, USA
- Department of Medicine, Divisions of Aging and Preventative Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Howard J. Edenberg
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | | | - Amy C. Justice
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
- 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
| | - Murray B. Stein
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- VA San Diego Healthcare System, Psychiatry Service, San Diego, CA, USA
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Henry R. Kranzler
- Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- These authors jointly supervised this work
| | - Joel Gelernter
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT, USA
- These authors jointly supervised this work
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Clites BL, Hofmann HA, Pierce JT. The Promise of an Evolutionary Perspective of Alcohol Consumption. Neurosci Insights 2023; 18:26331055231163589. [PMID: 37051560 PMCID: PMC10084549 DOI: 10.1177/26331055231163589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2022] [Accepted: 02/27/2023] [Indexed: 04/07/2023] Open
Abstract
The urgent need for medical treatments of alcohol use disorders has motivated the search for novel molecular targets of alcohol response. Most studies exploit the strengths of lab animals without considering how these and other species may have adapted to respond to alcohol in an ecological context. Here, we provide an evolutionary perspective on the molecular and genetic underpinnings of alcohol consumption by reviewing evidence that alcohol metabolic enzymes have undergone adaptive evolution at 2 evolutionary junctures: first, to enable alcohol consumption accompanying the advent of a frugivorous diet in a primate ancestor, and second, to decrease the likelihood of excessive alcohol consumption concurrent with the spread of agriculture and fermentation in East Asia. By similarly considering how diverse vertebrate and invertebrate species have undergone natural selection for alcohol responses, novel conserved molecular targets of alcohol are likely be discovered that may represent promising therapeutic targets.
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Affiliation(s)
- Benjamin L Clites
- Department of Neuroscience, University of Texas at Austin, Austin, TX, USA
- Waggoner Center for Alcohol and Addiction Research, University of Texas at Austin, Austin, TX, USA
- Institute for Cellular & Molecular Biology, University of Texas at Austin, Austin, TX, USA
- Institute for Neuroscience, University of Texas at Austin, Austin, TX, USA
| | - Hans A Hofmann
- Institute for Cellular & Molecular Biology, University of Texas at Austin, Austin, TX, USA
- Institute for Neuroscience, University of Texas at Austin, Austin, TX, USA
- Department of Integrative Biology, University of Texas at Austin, Austin, TX, USA
| | - Jonathan T Pierce
- Department of Neuroscience, University of Texas at Austin, Austin, TX, USA
- Waggoner Center for Alcohol and Addiction Research, University of Texas at Austin, Austin, TX, USA
- Institute for Cellular & Molecular Biology, University of Texas at Austin, Austin, TX, USA
- Institute for Neuroscience, University of Texas at Austin, Austin, TX, USA
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35
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Bogdan R, Hatoum AS, Johnson EC, Agrawal A. The Genetically Informed Neurobiology of Addiction (GINA) model. Nat Rev Neurosci 2023; 24:40-57. [PMID: 36446900 PMCID: PMC10041646 DOI: 10.1038/s41583-022-00656-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/19/2022] [Indexed: 11/30/2022]
Abstract
Addictions are heritable and unfold dynamically across the lifespan. One prominent neurobiological theory proposes that substance-induced changes in neural circuitry promote the progression of addiction. Genome-wide association studies have begun to characterize the polygenic architecture undergirding addiction liability and revealed that genetic loci associated with risk can be divided into those associated with a general broad-spectrum liability to addiction and those associated with drug-specific addiction risk. In this Perspective, we integrate these genomic findings with our current understanding of the neurobiology of addiction to propose a new Genetically Informed Neurobiology of Addiction (GINA) model.
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Affiliation(s)
- Ryan Bogdan
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA.
| | - Alexander S Hatoum
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Emma C Johnson
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA.
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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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Dick DM. The Promise and Peril of Genetics. CURRENT DIRECTIONS IN PSYCHOLOGICAL SCIENCE 2022; 31:480-485. [PMID: 36591341 PMCID: PMC9802013 DOI: 10.1177/09637214221112041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Human genetics is advancing at an unprecedented pace. Improvements in genotyping technology and rapidly falling costs have accelerated gene discovery. We can now comprehensively scan the genome, testing variation across millions of genetic markers, to identify specific variants associated with any outcome of interest. Large consortia consisting of hundreds of scientists are analyzing data from hundreds of thousands to millions of individuals. Multivariate methods now enable us to identify genes involved in underlying processes, to complement studies focused on specific disorders or traits. There has been an exponential increase in use of direct-to-consumer genetic feedback platforms. These advances are poised to have a widespread effect on medicine and society. However, with such rapid progress will come ethical, social, and legal challenges. Among those challenges is the need for increased efforts to enhance public understanding of the ways genes contribute to complex behavioral outcomes, and for increased diversity in the field of genetics to ensure that all people benefit from advances. Psychologists can play an important role in addressing the inevitable questions that will arise as genetics increasingly becomes mainstream.
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Affiliation(s)
- Danielle M. Dick
- Department of Psychiatry, Rutgers Robert Wood Johnson Medical School, Rutgers University
- Rutgers Addiction Research Center, Rutgers University
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Saunders GRB, Wang X, Chen F, Jang SK, Liu M, Wang C, Gao S, Jiang Y, Khunsriraksakul C, Otto JM, Addison C, Akiyama M, Albert CM, Aliev F, Alonso A, Arnett DK, Ashley-Koch AE, Ashrani AA, Barnes KC, Barr RG, Bartz TM, Becker DM, Bielak LF, Benjamin EJ, Bis JC, Bjornsdottir G, Blangero J, Bleecker ER, Boardman JD, Boerwinkle E, Boomsma DI, Boorgula MP, Bowden DW, Brody JA, Cade BE, Chasman DI, Chavan S, Chen YDI, Chen Z, Cheng I, Cho MH, Choquet H, Cole JW, Cornelis MC, Cucca F, Curran JE, de Andrade M, Dick DM, Docherty AR, Duggirala R, Eaton CB, Ehringer MA, Esko T, Faul JD, Fernandes Silva L, Fiorillo E, Fornage M, Freedman BI, Gabrielsen ME, Garrett ME, Gharib SA, Gieger C, Gillespie N, Glahn DC, Gordon SD, Gu CC, Gu D, Gudbjartsson DF, Guo X, Haessler J, Hall ME, Haller T, Harris KM, He J, Herd P, Hewitt JK, Hickie I, Hidalgo B, Hokanson JE, Hopfer C, Hottenga J, Hou L, Huang H, Hung YJ, Hunter DJ, Hveem K, Hwang SJ, Hwu CM, Iacono W, Irvin MR, Jee YH, Johnson EO, Joo YY, Jorgenson E, Justice AE, Kamatani Y, Kaplan RC, Kaprio J, Kardia SLR, Keller MC, Kelly TN, Kooperberg C, Korhonen T, Kraft P, Krauter K, Kuusisto J, Laakso M, Lasky-Su J, Lee WJ, Lee JJ, Levy D, Li L, Li K, Li Y, Lin K, Lind PA, Liu C, Lloyd-Jones DM, Lutz SM, Ma J, Mägi R, Manichaikul A, Martin NG, Mathur R, Matoba N, McArdle PF, McGue M, McQueen MB, Medland SE, Metspalu A, Meyers DA, Millwood IY, Mitchell BD, Mohlke KL, Moll M, Montasser ME, Morrison AC, Mulas A, Nielsen JB, North KE, Oelsner EC, Okada Y, Orrù V, Palmer ND, Palviainen T, Pandit A, Park SL, Peters U, Peters A, Peyser PA, Polderman TJC, Rafaels N, Redline S, Reed RM, Reiner AP, Rice JP, Rich SS, Richmond NE, Roan C, Rotter JI, Rueschman MN, Runarsdottir V, Saccone NL, Schwartz DA, Shadyab AH, Shi J, Shringarpure SS, Sicinski K, Skogholt AH, Smith JA, Smith NL, Sotoodehnia N, Stallings MC, Stefansson H, Stefansson K, Stitzel JA, Sun X, Syed M, Tal-Singer R, Taylor AE, Taylor KD, Telen MJ, Thai KK, Tiwari H, Turman C, Tyrfingsson T, Wall TL, Walters RG, Weir DR, Weiss ST, White WB, Whitfield JB, Wiggins KL, Willemsen G, Willer CJ, Winsvold BS, Xu H, Yanek LR, Yin J, Young KL, Young KA, Yu B, Zhao W, Zhou W, Zöllner S, Zuccolo L, Batini C, Bergen AW, Bierut LJ, David SP, Gagliano Taliun SA, Hancock DB, Jiang B, Munafò MR, Thorgeirsson TE, Liu DJ, Vrieze S. Genetic diversity fuels gene discovery for tobacco and alcohol use. Nature 2022; 612:720-724. [PMID: 36477530 PMCID: PMC9771818 DOI: 10.1038/s41586-022-05477-4] [Citation(s) in RCA: 115] [Impact Index Per Article: 57.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Accepted: 10/25/2022] [Indexed: 12/12/2022]
Abstract
Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury1-4. These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries5. Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction.
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Affiliation(s)
| | - Xingyan Wang
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Fang Chen
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Seon-Kyeong Jang
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Mengzhen Liu
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Chen Wang
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Shuang Gao
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Yu Jiang
- Department of Epidemiology & Population Health at Stanford University, Stanford, CA, USA
| | | | - Jacqueline M Otto
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Clifton Addison
- Jackson Heart Study (JHS) Graduate Training and Education Center (GTEC), Department of Epidemiology and Biostatistics, School of Public Health, Jackson State University, Jackson, MS, USA
| | - Masato Akiyama
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Department of Ocular Pathology and Imaging Science, Kyushu University Graduate School of Medical Sciences, Fukuoka, Japan
| | - Christine M Albert
- Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Division of Preventive Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Fazil Aliev
- Department of Psychiatry, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ, USA
| | - Alvaro Alonso
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Donna K Arnett
- Dean's Office and Department of Epidemiology, College of Public Health, University of Kentucky, Lexington, KY, USA
| | - Allison E Ashley-Koch
- Department of Medicine and Duke Comprehensive Sickle Cell Center, Duke University School of Medicine, Durham, NC, USA
- Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC, USA
| | - Aneel A Ashrani
- Division of Hematology, Department of Medicine, Mayo Clinic College of Medicine and Science, Rochester, MN, USA
| | - Kathleen C Barnes
- Division of Biomedical Informatics & Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Tempus, Chicago, IL, USA
| | - R Graham Barr
- Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Traci M Bartz
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Diane M Becker
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Lawrence F Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Emelia J Benjamin
- Department of Medicine, Boston Medical Center, Boston University School of Medicine, Boston, MA, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | | | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | | | - Jason D Boardman
- Institute of Behavioral Science, University of Colorado Boulder, Boulder, CO, USA
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Dorret I Boomsma
- Netherlands Twin Register, Dept Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Meher Preethi Boorgula
- Division of Biomedical Informatics & Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Donald W Bowden
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Brian E Cade
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Sameer Chavan
- Division of Biomedical Informatics & Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Yii-Der Ida Chen
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Iona Cheng
- Department of Epidemiology & Biostatistics, University of California, San Francisco, CA, USA
- UCSF Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA, USA
| | - Michael H Cho
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Hélène Choquet
- Kaiser Permanente Northern California (KPNC), Division of Research, Oakland, CA, USA
| | - John W Cole
- Department of Neurology, Baltimore Veterans Affairs Medical Center, Baltimore, MD, USA
- Division of Vascular Neurology, Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Marilyn C Cornelis
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | | | - Joanne E Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Mariza de Andrade
- Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic College of Medicine and Science, Rochester, MN, USA
| | - Danielle M Dick
- Department of Psychiatry, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ, USA
| | - Anna R Docherty
- Department of Psychiatry, University of Utah School of Medicine, Salt Lake City, UT, USA
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Virginia, USA
- Huntsman Mental Health Institute, Salt Lake City, UT, USA
| | - Ravindranath Duggirala
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Charles B Eaton
- Department of Family Medicine, Brown University, Providence, RI, USA
| | - Marissa A Ehringer
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA
- Department of Integrative Physiology, University of Colorado Boulder, Boulder, CO, USA
| | - Tõnu Esko
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Jessica D Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Lilian Fernandes Silva
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Edoardo Fiorillo
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche (CNR), Monserrato, Italy
| | - Myriam Fornage
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Barry I Freedman
- Department of Internal Medicine-Section on Nephrology, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Maiken E Gabrielsen
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Melanie E Garrett
- Department of Medicine and Duke Comprehensive Sickle Cell Center, Duke University School of Medicine, Durham, NC, USA
- Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC, USA
| | - Sina A Gharib
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, University of Washington, Seattle, WA, USA
- Center for Lung Biology, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Christian Gieger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Nathan Gillespie
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Virginia, USA
| | - David C Glahn
- Department of Psychiatry & Behavioral Sciences, Boston Children's Hospital & Harvard Medical School, Boston, MA, USA
| | - Scott D Gordon
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Charles C Gu
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Dongfeng Gu
- Department of Epidemiology and Key Laboratory of Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Daniel F Gudbjartsson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jeffrey Haessler
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Michael E Hall
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Toomas Haller
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Kathleen Mullan Harris
- Department of Sociology and the Carolina Population Center, University of North Carolina, Chapel Hill, NC, USA
| | - Jiang He
- Department of Epidemiology, Tulane University, New Orleans, LA, USA
- Translational Sciences Institute, Tulane University, New Orleans, LA, USA
| | - Pamela Herd
- McCourt School of Public Policy, Georgetown University, Washington, DC, USA
| | - John K Hewitt
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA
- Department Of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
| | - Ian Hickie
- Youth Mental Health & Technology Team, Brain and Mind Centre, University of Sydney, Sydney, Australia
| | - Bertha Hidalgo
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - John E Hokanson
- Department of Epidemiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Christian Hopfer
- Department of Psychiatry, University of Colorado Anschutz Medical Center, Denver, CO, USA
| | - JoukeJan Hottenga
- Netherlands Twin Register, Dept Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Hongyan Huang
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Yi-Jen Hung
- Institute of Preventive Medicine, National Defense Medical Center, New Taipei City, Taiwan
| | - David J Hunter
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Kristian Hveem
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Center, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Department of Research, Innovation and Education, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Shih-Jen Hwang
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Chii-Min Hwu
- Section of Endocrinology and Metabolism, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
| | - William Iacono
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Marguerite R Irvin
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Yon Ho Jee
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Eric O Johnson
- GenOmics, Bioinformatics, and Translational Research Center, RTI International, Research Triangle Park, NC, USA
- Fellow Program, RTI International, Research Triangle Park, NC, USA
| | - Yoonjung Y Joo
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Institute of Data Science, Korea University, Seoul, South Korea
| | | | - Anne E Justice
- Department of Population Health Sciences, Geisinger, Danville, PA, USA
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Yoichiro Kamatani
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Robert C Kaplan
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland - FIMM, University of Helsinki, Helsinki, Finland
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Matthew C Keller
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA
- Department Of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
| | - Tanika N Kelly
- Department of Epidemiology, Tulane University, New Orleans, LA, USA
- Translational Sciences Institute, Tulane University, New Orleans, LA, USA
| | - Charles Kooperberg
- Department of Biostatistics, University of Washington, Seattle, WA, USA
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Tellervo Korhonen
- Institute for Molecular Medicine Finland - FIMM, University of Helsinki, Helsinki, Finland
| | - Peter Kraft
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Kenneth Krauter
- Department of Molecular, Cellular and Developmental Biology, University of Colorado, Boulder, CO, USA
| | - Johanna Kuusisto
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
- Center for Medicine and Clinical Research, Kuopio University Hospital, Kuopio, Finland
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Jessica Lasky-Su
- Brigham and Women's Hospital, Department of Medicine, Channing Division of Network Medicine, Boston, MA, USA
| | - Wen-Jane Lee
- Department of Medical Research, Taichung Veterans General Hospital, Taichung City, Taiwan
| | - James J Lee
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Daniel Levy
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Kevin Li
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Yuqing Li
- Department of Epidemiology & Biostatistics, University of California, San Francisco, CA, USA
| | - Kuang Lin
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Penelope A Lind
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
- School of Biomedical Sciences, Faculty of Medicine, University of Queensland, Brisbane, Australia
- School of Biomedical Sciences, Queensland University of Technology, Brisbane, Australia
| | - Chunyu Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Donald M Lloyd-Jones
- Departments of Preventive Medicine, Medicine, and Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Sharon M Lutz
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA, USA
- Department of Biostatics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jiantao Ma
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
- Division of Nutrition Epidemiology and Data Science, Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
| | - Reedik Mägi
- Department of Integrative Physiology, University of Colorado Boulder, Boulder, CO, USA
| | - Ani Manichaikul
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Nicholas G Martin
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Ravi Mathur
- GenOmics, Bioinformatics, and Translational Research Center, RTI International, Research Triangle Park, NC, USA
| | - Nana Matoba
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Department of Genetics, UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Patrick F McArdle
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Matt McGue
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Matthew B McQueen
- Department of Integrative Physiology, University of Colorado, Boulder, CO, USA
| | - Sarah E Medland
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | | | | | - Iona Y Millwood
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Braxton D Mitchell
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore, MD, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Matthew Moll
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - May E Montasser
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Antonella Mulas
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche (CNR), Monserrato, Italy
| | - Jonas B Nielsen
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Kari E North
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Elizabeth C Oelsner
- Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Yukinori Okada
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan
- Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan
| | - Valeria Orrù
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche (CNR), Monserrato, Italy
| | - Nicholette D Palmer
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Teemu Palviainen
- Institute for Molecular Medicine Finland - FIMM, University of Helsinki, Helsinki, Finland
| | - Anita Pandit
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - S Lani Park
- Population Sciences of the Pacific Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Ulrike Peters
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig Maximilians University Munich, Munich, Germany
- German Centre for Cardiovascular Research, DZHK, Partner Site Munich, Munich, Germany
| | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Tinca J C Polderman
- Department of Clinical Developmental Psychology, Vrije Universiteit, Amsterdam, The Netherlands
- Department of Child and Adolescent Psychiatry, Amsterdam UMC, Amsterdam, The Netherlands
| | - Nicholas Rafaels
- Division of Biomedical Informatics & Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
- Division of Pulmonary, Critical Care, and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Robert M Reed
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Alex P Reiner
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - John P Rice
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Stephen S Rich
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Nicole E Richmond
- Department of Epidemiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Carol Roan
- Center for Demography of Health and Aging, University of Wisconsin-Madison, Madison, WI, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Michael N Rueschman
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
| | | | - Nancy L Saccone
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - David A Schwartz
- Division of Pulmonary Sciences and Critical Care Medicine; Department of Medicine and Immunology, University of Colorado, Aurora, CO, USA
| | - Aladdin H Shadyab
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla, CA, USA
| | | | | | - Kamil Sicinski
- Center for Demography of Health and Aging, University of Wisconsin-Madison, Madison, WI, USA
| | - Anne Heidi Skogholt
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Nicholas L Smith
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, WA, USA
- Seattle Epidemiologic Research and Information Center, Department of Veterans Affairs Office of Research and Development, Seattle, WA, USA
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Division of Cardiology, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Michael C Stallings
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA
- Department Of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
| | | | - Kari Stefansson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Jerry A Stitzel
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA
| | - Xiao Sun
- Department of Epidemiology, Tulane University, New Orleans, LA, USA
| | - Moin Syed
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | | | - Amy E Taylor
- MRC Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, UK
- National Institute for Health Research Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, UK
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Marilyn J Telen
- Department of Medicine and Duke Comprehensive Sickle Cell Center, Duke University School of Medicine, Durham, NC, USA
| | - Khanh K Thai
- Kaiser Permanente Northern California (KPNC), Division of Research, Oakland, CA, USA
| | - Hemant Tiwari
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Constance Turman
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | | | - Tamara L Wall
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Robin G Walters
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - David R Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Scott T Weiss
- Brigham and Women's Hospital, Department of Medicine, Channing Division of Network Medicine, Boston, MA, USA
| | - Wendy B White
- Jackson Heart Study Undergraduate Training and Education Center, Tougaloo College, Tougaloo, MS, USA
| | - John B Whitfield
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Kerri L Wiggins
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Gonneke Willemsen
- Netherlands Twin Register, Dept Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Cristen J Willer
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Bendik S Winsvold
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Research and Innovation, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
- Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Huichun Xu
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Lisa R Yanek
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jie Yin
- Kaiser Permanente Northern California (KPNC), Division of Research, Oakland, CA, USA
| | - Kristin L Young
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Kendra A Young
- Department of Epidemiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Bing Yu
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Wei Zhou
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Sebastian Zöllner
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Luisa Zuccolo
- MRC Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, UK
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Health Data Science Centre, Fondazione Human Technopole, Milan, Italy
| | - Chiara Batini
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Andrew W Bergen
- Oregon Research Institute, Springfield, OR, USA
- BioRealm, LLC, Walnut, CA, USA
| | - Laura J Bierut
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Sean P David
- Outcomes Research Network & Department of Family Medicine, NorthShore University HealthSystem, Evanston, IL, USA
- Department of Family Medicine, University of Chicago, Chicago, IL, USA
| | - Sarah A Gagliano Taliun
- Department of Medicine, Université de Montréal, Montréal, Québec, Canada
- Department of Neurosciences, Université de Montréal, Montréal, Québec, Canada
- Research Centre, Montréal Heart Institute, Montréal, Québec, Canada
| | - Dana B Hancock
- GenOmics, Bioinformatics, and Translational Research Center, RTI International, Research Triangle Park, NC, USA
| | - Bibo Jiang
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Marcus R Munafò
- MRC Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, UK
- National Institute for Health Research Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, UK
- School of Psychological Science, University of Bristol, Bristol, UK
| | | | - Dajiang J Liu
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA.
| | - Scott Vrieze
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA.
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Whitfield JB, Seth D, Morgan TR, Atkinson SR, Bataller R, Botwin G, Chalasani NP, Cordell HJ, Daly AK, Darlay R, Day CP, Eyer F, Foroud T, Gleeson D, Goldman D, Haber PS, Jacquet J, Liang T, Liangpunsakul S, Masson S, Mathurin P, Moirand R, Moreno C, Morgan TR, Morgan M, Mueller S, Müllhaupt B, Nagy LE, Nahon P, Nalpas B, Naveau S, Perney P, Pirmohamed M, Schwantes‐An T, Seitz HK, Seth D, Soyka M, Stickel F, Thompson A, Thursz MR, Trepo E, Whitfield JB. All-cause and liver-related mortality risk factors in excessive drinkers: Analysis of data from the UK biobank. Alcohol Clin Exp Res 2022; 46:2245-2257. [PMID: 36317527 PMCID: PMC10098765 DOI: 10.1111/acer.14968] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 10/26/2022] [Accepted: 10/27/2022] [Indexed: 11/13/2022]
Abstract
BACKGROUND High alcohol intake is associated with increased mortality. We aimed to identify factors affecting mortality in people drinking extreme amounts of alcohol. METHODS We obtained information from the UK Biobank on approximately 500,000 participants aged 40-70 years at baseline assessment in 2006-2010. Habitual alcohol intake, lifestyle and physiological data, laboratory test results, and hospital diagnoses and death certificate data (to June 2020) for 5136 men (2.20% of male participants) and 1504 women (0.60%) who reported consuming ≥80 or ≥50 g/day, respectively, were used in survival analysis. RESULTS Mortality hazard ratios for these excessive drinkers, compared to all other participants, were 2.02 (95% CI 1.89-2.17) for all causes, 1.89 (1.69-2.12) for any cancer, 1.87 (1.61-2.17) for any circulatory disease, and 9.40 (7.00-12.64) for any liver disease. Liver disease diagnosis or abnormal liver function tests predicted not only deaths attributed to liver disease but also those from cancers or circulatory diseases. Mortality among excessive drinkers was also associated with quantitative alcohol intake; diagnosed alcohol dependence, harmful use, or withdrawal syndrome; and current smoking at assessment. CONCLUSIONS People with chronic excessive alcohol intake experience decreased average survival, but there is substantial variation in their mortality, with liver abnormality and alcohol dependence or other alcohol use disorders associated with a worse prognosis. Clinically, patients with these risk factors and high alcohol intake should be considered for early or intensive management. Research can usefully focus on the factors predisposing to dependence or liver abnormality.
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Affiliation(s)
- John B Whitfield
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Devanshi Seth
- Drug Health Services, Royal Prince Alfred Hospital, Camperdown, New South Wales, Australia.,Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia.,Centenary Institute of Cancer Medicine and Cell Biology, University of Sydney, Sydney, New South Wales, Australia
| | - Timothy R Morgan
- Department of Veterans Affairs, VA Long Beach Healthcare System, Long Beach, California, USA.,Department of Medicine, University of California, Irvine, California, USA
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A Genome-Wide Association Study Reveals a BDNF-Centered Molecular Network Associated with Alcohol Dependence and Related Clinical Measures. Biomedicines 2022; 10:biomedicines10123007. [PMID: 36551763 PMCID: PMC9775455 DOI: 10.3390/biomedicines10123007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Revised: 11/15/2022] [Accepted: 11/18/2022] [Indexed: 11/24/2022] Open
Abstract
At least 50% of factors predisposing to alcohol dependence (AD) are genetic and women affected with this disorder present with more psychiatric comorbidities, probably indicating different genetic factors involved. We aimed to run a genome-wide association study (GWAS) followed by a bioinformatic functional annotation of associated genomic regions in patients with AD and eight related clinical measures. A genome-wide significant association of rs220677 with AD (p-value = 1.33 × 10-8 calculated with the Yates-corrected χ2 test under the assumption of dominant inheritance) was discovered in female patients. Associations of AD and related clinical measures with seven other single nucleotide polymorphisms listed in previous GWASs of psychiatric and addiction traits were differently replicated in male and female patients. The bioinformatic analysis showed that regulatory elements in the eight associated linkage disequilibrium blocks define the expression of 80 protein-coding genes. Nearly 68% of these and of 120 previously published coding genes associated with alcohol phenotypes directly interact in a single network, where BDNF is the most significant hub gene. This study indicates that several genes behind the pathogenesis of AD are different in male and female patients, but implicated molecular mechanisms are functionally connected. The study also reveals a central role of BDNF in the pathogenesis of AD.
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41
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Deak JD, Levey DF, Wendt FR, Zhou H, Galimberti M, Kranzler HR, Gaziano JM, Stein MB, Polimanti R, Gelernter J. Genome-Wide Investigation of Maximum Habitual Alcohol Intake in US Veterans in Relation to Alcohol Consumption Traits and Alcohol Use Disorder. JAMA Netw Open 2022; 5:e2238880. [PMID: 36301540 PMCID: PMC9614582 DOI: 10.1001/jamanetworkopen.2022.38880] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Accepted: 08/30/2022] [Indexed: 11/14/2022] Open
Abstract
Importance Alcohol genome-wide association studies (GWASs) have generally focused on alcohol consumption and alcohol use disorder (AUD); few have examined habitual drinking behaviors like maximum habitual alcohol intake (MaxAlc). Objectives To identify genetic loci associated with MaxAlc and to elucidate the genetic architecture across alcohol traits. Design, Setting, and Participants This MaxAlc genetic association study was performed among Million Veteran Program participants enrolled from January 10, 2011, to September 30, 2020. Ancestry-specific GWASs were conducted in participants with European (n = 218 623) and African (n = 29 132) ancestry, then meta-analyzed (N = 247 755). Linkage-disequilibrium score regression was used to estimate single nucleotide variant (SNV)-heritability and genetic correlations (rg) with other alcohol and psychiatric traits. Genomic structural equation modeling (gSEM) was used to evaluate genetic associations between MaxAlc and other alcohol traits. Mendelian randomization was used to examine potential causal relationships between MaxAlc and liver enzyme levels. MTAG (multitrait analysis of GWAS) was used to analyze MaxAlc and problematic alcohol use (PAU) jointly. Exposures Genetic associations. Main Outcomes and Measures MaxAlc was defined from the following survey item: "in a typical month, what is/was the largest number of drinks of alcohol you may have had in one day?" with ordinal responses from 0 to 15 or more drinks. Results GWASs were conducted on sample sizes of as many as 247 455 US veterans. Participants were 92.68% male and had mean (SD) age of 65.92 (11.70) years. The MaxAlc GWAS resulted in 15 genome-wide significant loci. Top associations in European-ancestry and African-ancestry participants were with known functional variants in the ADH1B gene, namely rs1229984 (P = 3.12 × 10-101) and rs2066702 (P = 6.30 × 10-17), respectively. Novel associations were also found. SNV-heritability was 6.65% (SE, 0.41) in European-ancestry participants and 3.42% (SE, 1.46) in African-ancestry participants. MaxAlc was positively correlated with PAU (rg = 0.79; P = 3.95 × 10-149) and AUD (rg = 0.76; P = 1.26 × 10-127) and had negative rg with the UK Biobank "alcohol usually taken with meals" (rg = -0.53; P = 1.40 × 10-50). For psychiatric traits, MaxAlc had the strongest genetic correlation with suicide attempt (rg = 0.40; P = 3.02 × 10-21). gSEM supported a 2-factor model with MaxAlc loading on a factor with PAU and AUD and other alcohol consumption measures loading on a separate factor. Mendelian randomization supported an association between MaxAlc and the liver enzyme gamma-glutamyltransferase (β = 0.012; P = 2.66 × 10-10). MaxAlc MTAG resulted in 31 genome-wide significant loci. Conclusions and Relevance The findings suggest that MaxAlc closely aligns genetically with PAU traits. This study improves understanding of the mechanisms associated with normative alcohol consumption vs problematic habitual use and AUD as well as how MaxAlc relates to psychiatric and medical conditions genetically and biologically.
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Affiliation(s)
- Joseph D. Deak
- Yale School of Medicine, New Haven, Connecticut
- VA Connecticut Healthcare Center, West Haven, Connecticut
| | - Daniel F. Levey
- Yale School of Medicine, New Haven, Connecticut
- VA Connecticut Healthcare Center, West Haven, Connecticut
| | - Frank R. Wendt
- Yale School of Medicine, New Haven, Connecticut
- VA Connecticut Healthcare Center, West Haven, Connecticut
| | - Hang Zhou
- Yale School of Medicine, New Haven, Connecticut
- VA Connecticut Healthcare Center, West Haven, Connecticut
| | - Marco Galimberti
- Yale School of Medicine, New Haven, Connecticut
- VA Connecticut Healthcare Center, West Haven, Connecticut
| | - Henry R. Kranzler
- University of Pennsylvania Perelman School of Medicine, Philadelphia
- Crescenz VA Medical Center, Philadelphia, Pennsylvania
| | - J. Michael Gaziano
- Massachusetts Veterans Epidemiology and Research Information Center (MAVERIC), Boston Veterans Affairs Healthcare System, Boston
- Department of Medicine, Divisions of Aging and Preventative Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Murray B. Stein
- University of California, San Diego, La Jolla
- VA San Diego Healthcare System, San Diego, California
| | - Renato Polimanti
- Yale School of Medicine, New Haven, Connecticut
- VA Connecticut Healthcare Center, West Haven, Connecticut
| | - Joel Gelernter
- Yale School of Medicine, New Haven, Connecticut
- VA Connecticut Healthcare Center, West Haven, Connecticut
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Hatoum AS, Johnson EC, Colbert SMC, Polimanti R, Zhou H, Walters RK, Gelernter J, Edenberg HJ, Bogdan R, Agrawal A. The addiction risk factor: A unitary genetic vulnerability characterizes substance use disorders and their associations with common correlates. Neuropsychopharmacology 2022; 47:1739-1745. [PMID: 34750568 PMCID: PMC9372072 DOI: 10.1038/s41386-021-01209-w] [Citation(s) in RCA: 44] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Revised: 09/27/2021] [Accepted: 10/11/2021] [Indexed: 11/09/2022]
Abstract
Substance use disorders commonly co-occur with one another and with other psychiatric disorders. They share common features including high impulsivity, negative affect, and lower executive function. We tested whether a common genetic factor undergirds liability to problematic alcohol use (PAU), problematic tobacco use (PTU), cannabis use disorder (CUD), and opioid use disorder (OUD) by applying genomic structural equation modeling to genome-wide association study summary statistics for individuals of European ancestry (Total N = 1,019,521; substance-specific Ns range: 82,707-435,563) while adjusting for the genetics of substance use (Ns = 184,765-632,802). We also tested whether shared liability across SUDs is associated with behavioral constructs (risk-taking, executive function, neuroticism; Ns = 328,339-427,037) and non-substance use psychopathology (psychotic, compulsive, and early neurodevelopmental disorders). Shared genetic liability to PAU, PTU, CUD, and OUD was characterized by a unidimensional addiction risk factor (termed The Addiction-Risk-Factor, independent of substance use. OUD and CUD demonstrated the largest loadings, while problematic tobacco use showed the lowest loading. The Addiction-Risk-Factor was associated with risk-taking, neuroticism, executive function, and non-substance psychopathology, but retained specific variance before and after accounting for the genetics of substance use. Thus, a common genetic factor partly explains susceptibility for alcohol, tobacco, cannabis, and opioid use disorder. The Addiction-Risk-Factor has a unique genetic architecture that is not shared with normative substance use or non-substance psychopathology, suggesting that addiction is not the linear combination of substance use and psychopathology.
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Affiliation(s)
- Alexander S Hatoum
- Washington University School of Medicine, Department of Psychiatry, Saint Louis, MO, USA.
| | - Emma C Johnson
- Washington University School of Medicine, Department of Psychiatry, Saint Louis, MO, USA
| | - Sarah M C Colbert
- Washington University School of Medicine, Department of Psychiatry, Saint Louis, MO, USA
| | - Renato Polimanti
- Department of Psychiatry, Division of Human Genetics, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Hang Zhou
- Department of Psychiatry, Division of Human Genetics, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Raymond K Walters
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Joel Gelernter
- Department of Psychiatry, Division of Human Genetics, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA
| | - 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
| | - Ryan Bogdan
- Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Arpana Agrawal
- Washington University School of Medicine, Department of Psychiatry, Saint Louis, MO, USA
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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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44
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Mallard TT. Crossing diagnostic boundaries to understand the genetic etiology of addiction. Neuropsychopharmacology 2022; 47:1735-1736. [PMID: 34873297 PMCID: PMC9372034 DOI: 10.1038/s41386-021-01245-6] [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] [Received: 10/28/2021] [Revised: 11/10/2021] [Accepted: 11/19/2021] [Indexed: 11/09/2022]
Affiliation(s)
- 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.
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45
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Dattani S, Howard DM, Lewis CM, Sham PC. Clarifying the causes of consistent and inconsistent findings in genetics. Genet Epidemiol 2022; 46:372-389. [PMID: 35652173 PMCID: PMC9544854 DOI: 10.1002/gepi.22459] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Revised: 04/12/2022] [Accepted: 04/22/2022] [Indexed: 11/29/2022]
Abstract
As research in genetics has advanced, some findings have been unexpected or shown to be inconsistent between studies or datasets. The reasons these inconsistencies arise are complex. Results from genetic studies can be affected by various factors including statistical power, linkage disequilibrium, quality control, confounding and selection bias, as well as real differences from interactions and effect modifiers, which may be informative about the mechanisms of traits and disease. Statistical artefacts can manifest as differences between results but they can also conceal underlying differences, which implies that their critical examination is important for understanding the underpinnings of traits. In this review, we examine these factors and outline how they can be identified and conceptualised with structural causal models. We explain the consequences they have on genetic estimates, such as genetic associations, polygenic scores, family‐ and genome‐wide heritability, and describe methods to address them to aid in the estimation of true effects of genetic variation. Clarifying these factors can help researchers anticipate when results are likely to diverge and aid researchers' understanding of causal relationships between genes and complex traits.
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Affiliation(s)
- Saloni Dattani
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.,Department of Psychiatry, Li Ka Shing (LKS) Faculty of Medicine, University of Hong Kong, Hong Kong, China
| | - David M Howard
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.,Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - Cathryn M Lewis
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.,Department of Medical and Molecular Genetics, Faculty of Life Sciences and Medicine, King's College London, London, UK
| | - Pak C Sham
- Department of Psychiatry, State Key Laboratory of Brain and Cognitive Sciences, and Centre for Panoromic Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
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46
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Affiliation(s)
- Ned H Kalin
- Department of Psychiatry, University of Wisconsin School of Medicine and Public Health, Madison
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47
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Kranzler HR, Zhou H, Kember RL. Identifying and Reducing Bias in Genome-Wide Association Studies of Alcohol-Related Traits. Am J Psychiatry 2022; 179:14-16. [PMID: 34974756 DOI: 10.1176/appi.ajp.2021.21111107] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
Affiliation(s)
- Henry R Kranzler
- Center for Studies of Addiction, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia (Kranzler, Kember); Mental Illness Research, Education, and Clinical Center, Veterans Integrated Service Network 4, Crescenz Veterans Affairs Medical Center, Philadelphia (Kranzler, Kember); Department of Psychiatry, Yale School of Medicine, New Haven, Conn., and Veterans Affairs Connecticut Healthcare System, West Haven, Conn. (Zhou)
| | - Hang Zhou
- Center for Studies of Addiction, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia (Kranzler, Kember); Mental Illness Research, Education, and Clinical Center, Veterans Integrated Service Network 4, Crescenz Veterans Affairs Medical Center, Philadelphia (Kranzler, Kember); Department of Psychiatry, Yale School of Medicine, New Haven, Conn., and Veterans Affairs Connecticut Healthcare System, West Haven, Conn. (Zhou)
| | - Rachel L Kember
- Center for Studies of Addiction, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia (Kranzler, Kember); Mental Illness Research, Education, and Clinical Center, Veterans Integrated Service Network 4, Crescenz Veterans Affairs Medical Center, Philadelphia (Kranzler, Kember); Department of Psychiatry, Yale School of Medicine, New Haven, Conn., and Veterans Affairs Connecticut Healthcare System, West Haven, Conn. (Zhou)
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Bondy E, Bogdan R. Understanding Anhedonia from a Genomic Perspective. Curr Top Behav Neurosci 2022; 58:61-79. [PMID: 35152374 PMCID: PMC9375777 DOI: 10.1007/7854_2021_293] [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] [Indexed: 06/14/2023]
Abstract
Anhedonia, or the decreased ability to experience pleasure, is a cardinal symptom of major depression that commonly occurs within other forms of psychopathology. Supportive of long-held theory that anhedonia represents a genetically influenced vulnerability marker for depression, evidence from twin studies suggests that it is moderately-largely heritable. However, the genomic sources of this heritability are just beginning to be understood. In this review, we survey what is known about the genomic architecture underlying anhedonia and related constructs. We briefly review twin and initial candidate gene studies before focusing on genome-wide association study (GWAS) and polygenic efforts. As large samples are needed to reliably detect the small effects that typically characterize common genetic variants, the study of anhedonia and related phenotypes conflicts with current genomic research requirements and frameworks that prioritize sample size over precise phenotyping. This has resulted in few and underpowered studies of anhedonia-related constructs that have largely failed to reliably identify individual variants. Nonetheless, the polygenic architecture of anhedonia-related constructs identified in these studies has genetic overlap with depression and schizophrenia as well as related brain structure (e.g., striatal volume), providing important clues to etiology that may usefully guide refinement in nosology. As we await the accumulation of larger samples for more well-powered GWAS of reward-related constructs, novel analytic techniques that leverage GWAS summary statistics (e.g., genomic structural equation modeling) may currently be used to help characterize how the genomic architecture of anhedonia is shared and distinct from that underlying other constructs (e.g., depression, neuroticism, anxiety).
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Affiliation(s)
- Erin Bondy
- Department of Psychological and Brain Sciences, Washington University in Saint Louis, St. Louis, MO, USA
| | - Ryan Bogdan
- Department of Psychological and Brain Sciences, Washington University in Saint Louis, St. Louis, MO, USA.
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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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Mallard TT, Liu S, Seidlitz J, Ma Z, Moraczewski D, Thomas A, Raznahan A. X-chromosome influences on neuroanatomical variation in humans. Nat Neurosci 2021; 24:1216-1224. [PMID: 34294918 DOI: 10.1038/s41593-021-00890-w] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Accepted: 06/14/2021] [Indexed: 02/06/2023]
Abstract
The X-chromosome has long been hypothesized to have a disproportionate influence on the brain based on its enrichment for genes that are expressed in the brain and associated with intellectual disability. Here, we verify this hypothesis through partitioned heritability analysis of X-chromosome influences (XIs) on human brain anatomy in 32,256 individuals from the UK Biobank. We first establish evidence for dosage compensation in XIs on brain anatomy-reflecting larger XIs in males compared to females, which correlate with regional sex-biases in neuroanatomical variance. XIs are significantly larger than would be predicted from X-chromosome size for the relative surface area of cortical systems supporting attention, decision-making and motor control. Follow-up association analyses implicate X-linked genes with pleiotropic effects on cognition. Our study reveals a privileged role for the X-chromosome in human neurodevelopment and urges greater inclusion of this chromosome in future genome-wide association studies.
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Affiliation(s)
- Travis T Mallard
- Department of Psychology, University of Texas at Austin, Austin, TX, USA
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health Intramural Research Program, Bethesda, MD, USA
| | - Siyuan Liu
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health Intramural Research Program, Bethesda, MD, USA
| | - Jakob Seidlitz
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health Intramural Research Program, Bethesda, MD, USA
| | - Zhiwei Ma
- Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Dustin Moraczewski
- Data Science and Sharing Team, National Institute of Mental Health, Bethesda, MD, USA
| | - Adam Thomas
- Data Science and Sharing Team, National Institute of Mental Health, Bethesda, MD, USA
| | - Armin Raznahan
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health Intramural Research Program, Bethesda, MD, USA.
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