1
|
Gupta P, Galimberti M, Liu Y, Beck S, Wingo A, Wingo T, Adhikari K, Kranzler HR, Stein MB, Gelernter J, Levey DF. A genome-wide investigation into the underlying genetic architecture of personality traits and overlap with psychopathology. Nat Hum Behav 2024:10.1038/s41562-024-01951-3. [PMID: 39134740 DOI: 10.1038/s41562-024-01951-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Accepted: 07/09/2024] [Indexed: 08/21/2024]
Abstract
Personality is influenced by both genetic and environmental factors and is associated with other psychiatric traits such as anxiety and depression. The 'big five' personality traits, which include neuroticism, extraversion, agreeableness, conscientiousness and openness, are a widely accepted and influential framework for understanding and describing human personality. Of the big five personality traits, neuroticism has most often been the focus of genetic studies and is linked to various mental illnesses, including depression, anxiety and schizophrenia. Our knowledge of the genetic architecture of the other four personality traits is more limited. Here, utilizing the Million Veteran Program cohort, we conducted a genome-wide association study in individuals of European and African ancestry. Adding other published data, we performed genome-wide association study meta-analysis for each of the five personality traits with sample sizes ranging from 237,390 to 682,688. We identified 208, 14, 3, 2 and 7 independent genome-wide significant loci associated with neuroticism, extraversion, agreeableness, conscientiousness and openness, respectively. These findings represent 62 novel loci for neuroticism, as well as the first genome-wide significant loci discovered for agreeableness. Gene-based association testing revealed 254 genes showing significant association with at least one of the five personality traits. Transcriptome-wide and proteome-wide analysis identified altered expression of genes and proteins such as CRHR1, SLC12A5, MAPT and STX4. Pathway enrichment and drug perturbation analyses identified complex biology underlying human personality traits. We also studied the inter-relationship of personality traits with 1,437 other traits in a phenome-wide genetic correlation analysis, identifying new associations. Mendelian randomization showed positive bidirectional effects between neuroticism and depression and anxiety, while a negative bidirectional effect was observed for agreeableness and these psychiatric traits. This study improves our comprehensive understanding of the genetic architecture underlying personality traits and their relationship to other complex human traits.
Collapse
Affiliation(s)
- Priya Gupta
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Marco Galimberti
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Yue Liu
- Department of Neurology and Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - Sarah Beck
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Aliza Wingo
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
- Atlanta Veterans Affairs Medical Center, Atlanta, GA, USA
| | - Thomas Wingo
- Department of Neurology and Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - Keyrun Adhikari
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Henry R Kranzler
- Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Murray B Stein
- Psychiatry Service, VA San Diego Healthcare System, San Diego, CA, USA
- Departments of Psychiatry, School of Medicine, and Herbert Wertheim School of Public Health, University of California San Diego, La Jolla, CA, USA
| | - Joel Gelernter
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Daniel F Levey
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA.
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA.
| |
Collapse
|
2
|
Trang KB, Chesi A, Toikumo S, Pippin JA, Pahl MC, O’Brien JM, Amundadottir LT, Brown KM, Yang W, Welles J, Santoleri D, Titchenell PM, Seale P, Zemel BS, Wagley Y, Hankenson KD, Kaestner KH, Anderson SA, Kayser MS, Wells AD, Kranzler HR, Kember RL, Grant SF. Shared and unique 3D genomic features of substance use disorders across multiple cell types. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.07.18.24310649. [PMID: 39072016 PMCID: PMC11275669 DOI: 10.1101/2024.07.18.24310649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/30/2024]
Abstract
Recent genome-wide association studies (GWAS) have revealed shared genetic components among alcohol, opioid, tobacco and cannabis use disorders. However, the extent of the underlying shared causal variants and effector genes, along with their cellular context, remain unclear. We leveraged our existing 3D genomic datasets comprising high-resolution promoter-focused Capture-C/Hi-C, ATAC-seq and RNA-seq across >50 diverse human cell types to focus on genomic regions that coincide with GWAS loci. Using stratified LD regression, we determined the proportion of genomewide SNP heritability attributable to the features assayed across our cell types by integrating recent GWAS summary statistics for the relevant traits: alcohol use disorder (AUD), tobacco use disorder (TUD), opioid use disorder (OUD) and cannabis use disorder (CanUD). Statistically significant enrichments (P<0.05) were observed in 14 specific cell types, with heritability reaching 9.2-fold for iPSC-derived cortical neurons and neural progenitors, confirming that they are crucial cell types for further functional exploration. Additionally, several pancreatic cell types, notably pancreatic beta cells, showed enrichment for TUD, with heritability enrichments up to 4.8-fold, suggesting genomic overlap with metabolic processes. Further investigation revealed significant positive genetic correlations between T2D with both TUD and CanUD (FDR<0.05) and a significant negative genetic correlation with AUD. Interestingly, after partitioning the heritability for each cell type's cis-regulatory elements, the correlation between T2D and TUD for pancreatic beta cells was greater (r=0.2) than the global genetic correlation value. Our study provides new genomic insights into substance use disorders and implicates cell types where functional follow-up studies could reveal causal variant-gene mechanisms underpinning these disorders.
Collapse
Affiliation(s)
- Khanh B. Trang
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Alessandra Chesi
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Sylvanus Toikumo
- Mental Illness Research, Education and Clinical Center, Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - James A. Pippin
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Matthew C. Pahl
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Joan M. O’Brien
- Scheie Eye Institute, Department of Ophthalmology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, PA, USA
- Penn Medicine Center for Ophthalmic Genetics in Complex Disease, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, PA, USA
| | - Laufey T. Amundadottir
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Kevin M. Brown
- Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Wenli Yang
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jaclyn Welles
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Physiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Dominic Santoleri
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Physiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Paul M. Titchenell
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Physiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Patrick Seale
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Babette S. Zemel
- Division of Gastroenterology, Hepatology, and Nutrition, Children’s Hospital of Philadelphia, PA, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Yadav Wagley
- Department of Orthopedic Surgery, University of Michigan Medical School Ann Arbor, MI, USA
| | - Kurt D. Hankenson
- Department of Orthopedic Surgery, University of Michigan Medical School Ann Arbor, MI, USA
| | - Klaus H. Kaestner
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Stewart A. Anderson
- Department of Child and Adolescent Psychiatry, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Matthew S. Kayser
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Chronobiology Sleep Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Andrew D. Wells
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Institute for Immunology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Henry R. Kranzler
- Mental Illness Research, Education and Clinical Center, Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Rachel L. Kember
- Mental Illness Research, Education and Clinical Center, Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Struan F.A. Grant
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Division of Endocrinology and Diabetes, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| |
Collapse
|
3
|
Carr S, Bryazka D, McLaughlin SA, Zheng P, Bahadursingh S, Aravkin AY, Hay SI, Lawlor HR, Mullany EC, Murray CJL, Nicholson SI, Rehm J, Roth GA, Sorensen RJD, Lewington S, Gakidou E. A burden of proof study on alcohol consumption and ischemic heart disease. Nat Commun 2024; 15:4082. [PMID: 38744810 PMCID: PMC11094064 DOI: 10.1038/s41467-024-47632-7] [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: 06/14/2023] [Accepted: 04/08/2024] [Indexed: 05/16/2024] Open
Abstract
Cohort and case-control data have suggested an association between low to moderate alcohol consumption and decreased risk of ischemic heart disease (IHD), yet results from Mendelian randomization (MR) studies designed to reduce bias have shown either no or a harmful association. Here we conducted an updated systematic review and re-evaluated existing cohort, case-control, and MR data using the burden of proof meta-analytical framework. Cohort and case-control data show low to moderate alcohol consumption is associated with decreased IHD risk - specifically, intake is inversely related to IHD and myocardial infarction morbidity in both sexes and IHD mortality in males - while pooled MR data show no association, confirming that self-reported versus genetically predicted alcohol use data yield conflicting findings about the alcohol-IHD relationship. Our results highlight the need to advance MR methodologies and emulate randomized trials using large observational databases to obtain more definitive answers to this critical public health question.
Collapse
Affiliation(s)
- Sinclair Carr
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
| | - Dana Bryazka
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Susan A McLaughlin
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Peng Zheng
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
- Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
| | - Sarasvati Bahadursingh
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, Oxfordshire, UK
| | - Aleksandr Y Aravkin
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
- Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
- Department of Applied Mathematics, University of Washington, Seattle, WA, USA
| | - Simon I Hay
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
- Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
| | - Hilary R Lawlor
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Erin C Mullany
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Christopher J L Murray
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
- Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
| | - Sneha I Nicholson
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Jürgen Rehm
- Institute for Mental Health Policy Research, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Faculty of Medicine, Institute of Medical Science (IMS), University of Toronto, Toronto, ON, Canada
- World Health Organization / Pan American Health Organization Collaborating Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Center for Interdisciplinary Addiction Research (ZIS), Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
- Institute of Clinical Psychology and Psychotherapy, Technische Universität Dresden, Dresden, Germany
| | - Gregory A Roth
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
- Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
- Division of Cardiology, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Reed J D Sorensen
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Sarah Lewington
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, Oxfordshire, UK
| | - Emmanuela Gakidou
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
- Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
| |
Collapse
|
4
|
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).
Collapse
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.
| |
Collapse
|
5
|
Indelicato E, Boesch S. GAA/FGF14 ataxia: an ode to the phenotype-first approach. EBioMedicine 2024; 103:105131. [PMID: 38631092 PMCID: PMC11035086 DOI: 10.1016/j.ebiom.2024.105131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2024] [Accepted: 04/08/2024] [Indexed: 04/19/2024] Open
Affiliation(s)
- Elisabetta Indelicato
- Center for Rare Movement Disorders Innsbruck, Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria.
| | - Sylvia Boesch
- Center for Rare Movement Disorders Innsbruck, Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| |
Collapse
|
6
|
Cabrera-Mendoza B, Wendt FR, Pathak GA, Yengo L, Polimanti R. The impact of assortative mating, participation bias and socioeconomic status on the polygenic risk of behavioural and psychiatric traits. Nat Hum Behav 2024; 8:976-987. [PMID: 38366106 PMCID: PMC11161911 DOI: 10.1038/s41562-024-01828-5] [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: 11/29/2022] [Accepted: 01/15/2024] [Indexed: 02/18/2024]
Abstract
To investigate assortative mating (AM), participation bias and socioeconomic status (SES) with respect to the genetics of behavioural and psychiatric traits, we estimated AM signatures using gametic phase disequilibrium and within-spouses and within-siblings polygenic risk score correlation analyses, also performing a SES conditional analysis. The cross-method meta-analysis identified AM genetic signatures for multiple alcohol-related phenotypes, bipolar disorder, major depressive disorder, schizophrenia and Tourette syndrome. Here, after SES conditioning, we observed changes in the AM genetic signatures for maximum habitual alcohol intake, frequency of drinking alcohol and Tourette syndrome. We also observed significant gametic phase disequilibrium differences between UK Biobank mental health questionnaire responders versus non-responders for major depressive disorder and alcohol use disorder. These results highlight the impact of AM, participation bias and SES on the polygenic risk of behavioural and psychiatric traits, particularly in alcohol-related traits.
Collapse
Affiliation(s)
- Brenda Cabrera-Mendoza
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- VA CT Healthcare System, West Haven, CT, USA
| | - Frank R Wendt
- 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, Toronto, Ontario, Canada
- Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Gita A Pathak
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- VA CT Healthcare System, West Haven, CT, USA
| | - Loic Yengo
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia.
| | - Renato Polimanti
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA.
- VA CT Healthcare System, West Haven, CT, USA.
- Wu Tsai Institute, Yale University, New Haven, CT, USA.
| |
Collapse
|
7
|
Andrade-Brito DE, Núñez-Ríos DL, Martínez-Magaña JJ, Nagamatsu ST, Rompala G, Zillich L, Witt SH, Clark SL, Lattig MC, Montalvo-Ortiz JL. Neuronal-specific methylome and hydroxymethylome analysis reveal significant loci associated with alcohol use disorder. Front Genet 2024; 15:1345410. [PMID: 38633406 PMCID: PMC11021708 DOI: 10.3389/fgene.2024.1345410] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Accepted: 03/14/2024] [Indexed: 04/19/2024] Open
Abstract
Background: Alcohol use disorder (AUD) is a complex condition associated with adverse health consequences that affect millions of individuals worldwide. Epigenetic modifications, including DNA methylation (5 mC), have been associated with AUD and other alcohol-related traits. Epigenome-wide association studies (EWAS) have identified differentially methylated genes associated with AUD in human peripheral and brain tissue. More recently, epigenetic studies of AUD have also evaluated DNA hydroxymethylation (5 hmC) in the human brain. However, most of the epigenetic work in postmortem brain tissue has examined bulk tissue. In this study, we investigated neuronal-specific 5 mC and 5 hmC alterations at CpG sites associated with AUD in the human orbitofrontal cortex (OFC). Methods: Neuronal nuclei from the OFC were evaluated in 34 human postmortem brain samples (10 AUD, 24 non-AUD). Reduced representation oxidative bisulfite sequencing was used to assess 5 mC and 5 hmC at the genome-wide level. Differential 5 mC and 5 hmC were evaluated using the methylKit R package and significance was set at false discovery rate < 0.05 and differential methylation > 2. Functional enrichment analyses were performed, and gene-level convergence was evaluated in an independent dataset that assessed 5 mC and 5 hmC of AUD in bulk cortical tissue. Results: We identified 417 5 mC and 363 5hmC significant differential CpG sites associated with AUD, with 59% in gene promoters. Some of the identified genes have been previously implicated in alcohol consumption, including SYK, DNMT3A for 5 mC, GAD1, DLX1, DLX2, for 5 hmC and GATA4 in both. Convergence with a previous AUD 5 mC and 5 hmC study was observed for 28 genes. We also identified 5 and 35 differential regions for 5 mC and 5 hmC, respectively. Lastly, GWAS enrichment analysis showed an association with AUD for differential 5 mC genes. Discussion: This study reveals neuronal-specific methylome and hydroxymethylome dysregulation associated with AUD, identifying both previously reported and potentially novel gene associations with AUD. Our findings provide new insights into the epigenomic dysregulation of AUD in the human brain.
Collapse
Affiliation(s)
- Diego E. Andrade-Brito
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
- National Center of Post-Traumatic Stress Disorder, VA CT Healthcare, West Haven, CT, United States
| | - Diana L. Núñez-Ríos
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
- National Center of Post-Traumatic Stress Disorder, VA CT Healthcare, West Haven, CT, United States
| | - José Jaime Martínez-Magaña
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
- National Center of Post-Traumatic Stress Disorder, VA CT Healthcare, West Haven, CT, United States
| | - Sheila T. Nagamatsu
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
- National Center of Post-Traumatic Stress Disorder, VA CT Healthcare, West Haven, CT, United States
| | - Gregory Rompala
- Icahn School of Medicine at Mount Sinai, New York City, NY, United States
| | - Lea Zillich
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Stephanie H. Witt
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Shaunna L. Clark
- Department of Psychiatry and Behavioral Sciences, Texas A&M University, College Station, TX, United States
| | - Maria C. Lattig
- Facultad de Ciencias, Universidad de los Andes, Bogotá, Colombia
| | - Janitza L. Montalvo-Ortiz
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
- National Center of Post-Traumatic Stress Disorder, VA CT Healthcare, West Haven, CT, United States
| |
Collapse
|
8
|
Waller C, Ho A, Batzler A, Geske J, Karpyak V, Biernacka J, Winham S. Genetic correlations of alcohol consumption and alcohol use disorder with sex hormone levels in females and males. RESEARCH SQUARE 2024:rs.3.rs-3944066. [PMID: 38464231 PMCID: PMC10925434 DOI: 10.21203/rs.3.rs-3944066/v1] [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
Background Alcohol consumption behaviors and alcohol use disorder risk and presentation differ by sex, and these complex traits are associated with blood concentrations of the steroid sex hormones, testosterone and estradiol, and their regulatory binding proteins, sex hormone binding globulin (SHBG) and albumin. Genetic variation is associated with alcohol consumption and alcohol use disorder, as well as levels of steroid sex hormones and their binding proteins. Methods To assess the contribution of genetic factors to previously described phenotypic associations between alcohol-use traits and sex-hormone levels, we estimated genetic correlations (rg) using summary statistics from prior published, large sample size genome-wide association studies (GWAS) of alcohol consumption, alcohol dependence, testosterone, estradiol, SHBG, and albumin. Results For alcohol consumption, we observed positive genetic correlation (i.e. genetic effects in the same direction) with total testosterone in males (rg = 0.084, p = 0.007) and trends toward positive genetic correlation with bioavailable testosterone (rg = 0.060, p = 0.084) and SHBG in males (rg = 0.056, p = 0.086) and with albumin in a sex-combined cohort (rg = 0.082, p = 0.015); however in females, we observed positive genetic correlation with SHBG (rg = 0.089, p = 0.004) and a trend toward negative genetic correlation (i.e. genetic effects in opposite directions) with bioavailable testosterone (rg = -0.064, p = 0.032). For alcohol dependence, we observed a trend toward negative genetic correlation with total testosterone in females (rg = -0.106, p = 0.024) and positive genetic correlation with BMI-adjusted SHBG in males (rg = 0.119, p = 0.017). Several of these genetic correlations differed between females and males and were not in the same direction as the corresponding phenotypic associations. Conclusions Findings suggest that shared genetic effects may contribute to positive associations of alcohol consumption with albumin in both sexes, as well as positive associations between alcohol consumption and bioavailable testosterone and between alcohol dependence and SHBG in males. However, relative contributions of heritable and environmental factors to associations between alcohol-use traits and sex-hormone levels may differ by sex, with genetic factors contributing more in males and environmental factors contributing more in females.
Collapse
|
9
|
Sheerin CM, O’Hara-Payne RK, Lancaster EE, Suarez-Rivas H, Chatzinakos C, Prom-Wormley EC, Peterson RE. Examining interactions between polygenic scores and interpersonal trauma exposure on alcohol consumption and use disorder in an ancestrally diverse college cohort. Front Genet 2024; 14:1274381. [PMID: 38361984 PMCID: PMC10868390 DOI: 10.3389/fgene.2023.1274381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 11/22/2023] [Indexed: 02/17/2024] Open
Abstract
Introduction: Genetic factors impact alcohol consumption and use disorder (AUD), with large-scale genome-wide association studies (GWAS) identifying numerous associated variants. Aggregate genetic methods in combination with important environmental factors (e.g., interpersonal trauma [IPT]) can be applied to expand our understanding of the ways by which genetic and environmental variables work together to influence alcohol consumption and disordered use. The present study aimed to detail the relationships between genome-wide polygenic scores (PGS) for alcohol phenotypes (i.e., alcohol consumption and AUD status) and IPT exposure as well as the interaction between them across ancestry. Methods: Data were drawn from the Spit for Science (S4S) study, a US college student population, where participants reported on IPT exposure prior to college and alcohol consumption and problems during college (N = 9,006; ancestry: 21.3% African [AFR], 12.5% Admixed Americas [AMR], 9.6% East Asian [EAS], 48.1% European [EUR], 8.6% South Asian [SAS]). Two trans-ancestry PGS were constructed, one for alcohol consumption and another for AUD, using large-scale GWAS summary statistics from multiple ancestries weighted using PRS-CSx. Regression models were applied to test for the presence of associations between alcohol-PGS and IPT main and interaction effects. Results: In the meta-analysis across ancestry groups, IPT exposure and PGS were significantly associated with alcohol consumption (βIPT = 0.31, P IPT = 0.0002; βPGS = 0.09, P PGS = 0.004) and AUD (ORIPT = 1.12, P IPT = 3.5 × 10-8; ORPGS = 1.02, P PGS = 0.002). No statistically significant interactions were detected between IPT and sex nor between IPT and PGS. When inspecting ancestry specific results, the alcohol consumption-PGS and AUD-PGS were only statistically significant in the EUR ancestry group (βPGS = 0.09, P PGS = 0.04; ORPGS = 1.02, P PGS = 0.022, respectively). Discussion: IPT exposure prior to college was strongly associated with alcohol outcomes in this college-age sample, which could be used as a preventative measure to identify students at high risk for problematic alcohol use. Additionally, results add to developing evidence of polygenic score association in meta-analyzed samples, highlighting the importance of continued efforts to increase ancestral representation in genetic studies and inclusive analytic approaches to increase the generalizability of results from genetic association studies.
Collapse
Affiliation(s)
- Christina M. Sheerin
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, United States
- Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, United States
| | - Rowan K. O’Hara-Payne
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, United States
- Center for Biological Data Science, Virginia Commonwealth University, Richmond, VA, United States
| | - Eva E. Lancaster
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, United States
- Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, United States
| | - Hailie Suarez-Rivas
- Department of Psychology, Virginia Commonwealth University, Richmond, VA, United States
| | - Chris Chatzinakos
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, United States
- Institute for Genomics in Health, SUNY Downstate Health Sciences University, Brooklyn, NY, United States
| | - Elizabeth C. Prom-Wormley
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, United States
- Department of Epidemiology, Virginia Commonwealth University, Richmond, VA, United States
| | - Roseann E. Peterson
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, United States
- Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, United States
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, United States
- Institute for Genomics in Health, SUNY Downstate Health Sciences University, Brooklyn, NY, United States
| |
Collapse
|
10
|
Gupta P, Galimberti M, Liu Y, Beck S, Wingo A, Wingo T, Adhikari K, Stein MB, Gelernter J, Levey DF. A genome-wide investigation into the underlying genetic architecture of personality traits and overlap with psychopathology. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.01.17.24301428. [PMID: 38293137 PMCID: PMC10827244 DOI: 10.1101/2024.01.17.24301428] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
Personality is influenced by both genetic and environmental factors and is associated with other psychiatric traits such as anxiety and depression. The "Big Five" personality traits, which include neuroticism, extraversion, agreeableness, conscientiousness, and openness, are a widely accepted and influential framework for understanding and describing human personality. Of the big five personality traits, neuroticism has most often been the focus of genetic studies and is linked to various mental illnesses including depression, anxiety, and schizophrenia. Our knowledge of the genetic architecture of the other four personality traits is more limited. Utilizing the Million Veteran Program (MVP) cohort we conducted a genome-wide association study (GWAS) in individuals of European and African ancestry. Adding other published data, we performed GWAS meta-analysis for each of the five personality traits with sample sizes ranging from 237,390 to 682,688. We identified 158, 14, 3, 2, and 7 independent genome-wide significant (GWS) loci associated with neuroticism, extraversion, agreeableness, conscientiousness, and openness, respectively. These findings represent 55 novel loci for neuroticism, as well as the first GWS loci discovered for extraversion and agreeableness. Gene-based association testing revealed 254 genes showing significant association with at least one of the five personality traits. Transcriptome-wide and proteome-wide analysis identified altered expression of genes and proteins such as CRHR1, SLC12A5, MAPT, and STX4. Pathway enrichment and drug perturbation analyses identified complex biology underlying human personality traits. We also studied the inter-relationship of personality traits with 1,437 other traits in a phenome-wide genetic correlation analysis, identifying new associations. Mendelian randomization showed positive bidirectional effects between neuroticism and depression and anxiety while a negative bidirectional effect was observed for agreeableness and these psychiatric traits. This study improves our comprehensive understanding of the genetic architecture underlying personality traits and their relationship to other complex human traits.
Collapse
Affiliation(s)
- Priya Gupta
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Marco Galimberti
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Yue Liu
- Department of Neurology and Human Genetics, Emory University School of Medicine, Atlanta, USA
| | - Sarah Beck
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Aliza Wingo
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, USA
- Atlanta Veterans Affairs Medical Center, USA
| | - Thomas Wingo
- Department of Neurology and Human Genetics, Emory University School of Medicine, Atlanta, USA
| | - Keyrun Adhikari
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Murray B Stein
- Psychiatry Service, VA San Diego Healthcare System, San Diego, CA
- Departments of Psychiatry, School of Medicine, and Herbert Wertheim School of Public Health, University of California San Diego, La Jolla, CA
| | - Joel Gelernter
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Daniel F Levey
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| |
Collapse
|
11
|
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.
Collapse
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
| |
Collapse
|
12
|
Andrade-Brito DE, Núñez-Ríos DL, Martínez-Magaña JJ, Nagamatsu ST, Rompala G, Zillich L, Witt SH, Clark SL, Latig MC, Montalvo-Ortiz JL. Neuronal-specific methylome and hydroxymethylome analysis reveal replicated and novel loci associated with alcohol use disorder. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.11.28.23299094. [PMID: 38105948 PMCID: PMC10725575 DOI: 10.1101/2023.11.28.23299094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Alcohol use disorder (AUD) is a complex condition associated with adverse health consequences that affect millions of individuals worldwide. Epigenetic modifications, including DNA methylation (5mC), have been associated with AUD and other alcohol-related traits. Epigenome-wide association studies (EWAS) have identified differentially methylated genes associated with AUD in human peripheral and brain tissue. More recently, epigenetic studies of AUD have also evaluated DNA hydroxymethylation (5hmC) in the human brain. However, most of the epigenetic work in postmortem brain tissue has examined bulk tissue. In this study, we investigated neuronal-specific 5mC and 5hmC alterations at CpG sites associated with AUD in the human orbitofrontal cortex (OFC). Neuronal nuclei from the OFC were evaluated in 34 human postmortem brain samples (10 AUD, 24 non-AUD). Reduced representation oxidative bisulfite sequencing was used to assess 5mC and 5hmC at the genome-wide level. Differential 5mC and 5hmC were evaluated using the methylKit R package and significance was set at false discovery rate <0.05 and differential methylation >2. Functional enrichment analyses were performed and replication was evaluated replication in an independent dataset that assessed 5mC and 5hmC of AUD in bulk cortical tissue. We identified 417 5mC and 363 5hmC genome-wide significant differential CpG sites associated with AUD, with 59% in gene promoters. We also identified genes previously implicated in alcohol consumption, such as SYK, CHRM2, DNMT3A, and GATA4, for 5mC and GATA4, and GAD1, GATA4, DLX1 for 5hmC. Replication was observed for 28 CpG sites from a previous AUD 5mC and 5hmC study, including FOXP1. Lastly, GWAS enrichment analysis showed an association with AUD for differential 5mC genes. This study reveals neuronal-specific methylome and hydroxymethylome dysregulation associated with AUD. We replicated previous findings and identified novel associations with AUD for both 5mC and 5hmC marks within the OFC. Our findings provide new insights into the epigenomic dysregulation of AUD in the human brain.
Collapse
Affiliation(s)
- Diego E. Andrade-Brito
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- National Center of Post-Traumatic Stress Disorder, VA CT Healthcare, West Haven, CT, USA
| | - Diana L. Núñez-Ríos
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- National Center of Post-Traumatic Stress Disorder, VA CT Healthcare, West Haven, CT, USA
| | - José Jaime Martínez-Magaña
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- National Center of Post-Traumatic Stress Disorder, VA CT Healthcare, West Haven, CT, USA
| | - Sheila T. Nagamatsu
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- National Center of Post-Traumatic Stress Disorder, VA CT Healthcare, West Haven, CT, USA
| | - Gregory Rompala
- Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Lea Zillich
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Stephanie H. Witt
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Shaunna L. Clark
- Department of Psychiatry & Behavioral Sciences, Texas A&M University, College Station, Texas, USA
| | - Maria C. Latig
- Facultad de Ciencias, Universidad de los Andes, Bogotá, Colombia
| | | | - Janitza L. Montalvo-Ortiz
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- National Center of Post-Traumatic Stress Disorder, VA CT Healthcare, West Haven, CT, USA
| |
Collapse
|
13
|
Su J, Kuo SIC, Aliev F, Rabinowitz JA, Jamil B, Chan G, Edenberg HJ, Francis M, Hesselbrock V, Kamarajan C, Kinreich S, Kramer J, Lai D, McCutcheon V, Meyers J, Pandey A, Pandey G, Plawecki MH, Schuckit M, Tischfield J, Dick DM. Alcohol use polygenic risk score, social support, and alcohol use among European American and African American adults. Dev Psychopathol 2023:1-13. [PMID: 37781861 PMCID: PMC10985050 DOI: 10.1017/s0954579423001141] [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: 10/03/2023]
Abstract
Alcohol use is influenced by genetic and environmental factors. We examined the interactive effects between genome-wide polygenic risk scores for alcohol use (alc-PRS) and social support in relation to alcohol use among European American (EA) and African American (AA) adults across sex and developmental stages (emerging adulthood, young adulthood, and middle adulthood). Data were drawn from 4,011 EA and 1,274 AA adults from the Collaborative Study on the Genetics of Alcoholism who were between ages 18-65 and had ever used alcohol. Participants completed the Semi-Structured Assessment for the Genetics of Alcoholism and provided saliva or blood samples for genotyping. Results indicated that social support from friends, but not family, moderated the association between alc-PRS and alcohol use among EAs and AAs (only in middle adulthood for AAs); alc-PRS was associated with higher levels of alcohol use when friend support was low, but not when friend support was high. Associations were similar across sex but differed across developmental stages. Findings support the important role of social support from friends in buffering genetic risk for alcohol use among EA and AA adults and highlight the need to consider developmental changes in the role of social support in relation to alcohol use.
Collapse
Affiliation(s)
- Jinni Su
- Department of Psychology, Arizona State University, Tempe, AZ, USA
| | - Sally I-Chun Kuo
- Department of Psychiatry, Rutgers University, New Brunswick, NJ, USA
| | - Fazil Aliev
- Department of Psychiatry, Rutgers University, New Brunswick, NJ, USA
| | - Jill A Rabinowitz
- Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Belal Jamil
- Department of Psychology, Arizona State University, Tempe, AZ, USA
| | - Grace Chan
- Department of Psychiatry, University of Connecticut, Farmington, CT, USA
- Department of Psychiatry, University of Iowa, Iowa City, IA, USA
| | - Howard J Edenberg
- Department of Biochemistry and Molecular Biology, Indiana University, Indianapolis, IN, USA
| | - Meredith Francis
- Department of Psychiatry, Washington University, St. Louis, MO, USA
| | - Victor Hesselbrock
- Department of Psychiatry, University of Connecticut, Farmington, CT, USA
| | - Chella Kamarajan
- Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, USA
| | - Sivan Kinreich
- Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, USA
| | - John Kramer
- Department of Psychiatry, University of Iowa, Iowa City, IA, USA
| | - Donbing Lai
- Department of Biochemistry and Molecular Biology, Indiana University, Indianapolis, IN, USA
| | - Vivia McCutcheon
- Department of Psychiatry, Washington University, St. Louis, MO, USA
| | - Jacquelyn Meyers
- Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, USA
| | - Ashwini Pandey
- Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, USA
| | - Gayathri Pandey
- Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, USA
| | | | - Marc Schuckit
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Jay Tischfield
- Department of Genetics, Rutgers University, New Brunswick, NJ, USA
| | - Danielle M Dick
- Rutgers Addiction Research Center, Rutgers University, New Brunswick, NJ, USA
| |
Collapse
|
14
|
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.
Collapse
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.
| |
Collapse
|
15
|
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.
Collapse
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
| | | | | |
Collapse
|
16
|
Bountress KE, Cusack SE, Hawn SE, Grotzinger A, Bustamante D, Kirkpatrick RM, Edenberg HJ, Amstadter AB. Genetic associations between alcohol phenotypes and life satisfaction: a genomic structural equation modelling approach. Sci Rep 2023; 13:13443. [PMID: 37596344 PMCID: PMC10439217 DOI: 10.1038/s41598-023-40199-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 08/07/2023] [Indexed: 08/20/2023] Open
Abstract
Alcohol use (i.e., quantity, frequency) and alcohol use disorder (AUD) are common, associated with adverse outcomes, and genetically-influenced. Genome-wide association studies (GWAS) identified genetic loci associated with both. AUD is positively genetically associated with psychopathology, while alcohol use (e.g., drinks per week) is negatively associated or NS related to psychopathology. We wanted to test if these genetic associations extended to life satisfaction, as there is an interest in understanding the associations between psychopathology-related traits and constructs that are not just the absence of psychopathology, but positive outcomes (e.g., well-being variables). Thus, we used Genomic Structural Equation Modeling (gSEM) to analyze summary-level genomic data (i.e., effects of genetic variants on constructs of interest) from large-scale GWAS of European ancestry individuals. Results suggest that the best-fitting model is a Bifactor Model, in which unique alcohol use, unique AUD, and common alcohol factors are extracted. The genetic correlation (rg) between life satisfaction-AUD specific factor was near zero, the rg with the alcohol use specific factor was positive and significant, and the rg with the common alcohol factor was negative and significant. Findings indicate that life satisfaction shares genetic etiology with typical alcohol use and life dissatisfaction shares genetic etiology with heavy alcohol use.
Collapse
Affiliation(s)
- Kaitlin E Bountress
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, 800 E. Leigh St. Biotech One Suite 101, Richmond, VA, 23219, USA.
| | - Shannon E Cusack
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, 800 E. Leigh St. Biotech One Suite 101, Richmond, VA, 23219, USA
| | - Sage E Hawn
- Department of Psychology, Old Dominion University, Norfolk, USA
| | - Andrew Grotzinger
- Institute for Behavior Genetics, Behavioral, Psychiatric, and Statistical Genetics, University of Colorado Boulder, Boulder, USA
| | - Daniel Bustamante
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, 800 E. Leigh St. Biotech One Suite 101, Richmond, VA, 23219, USA
| | - Robert M Kirkpatrick
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, 800 E. Leigh St. Biotech One Suite 101, Richmond, VA, 23219, USA
| | | | - Ananda B Amstadter
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, 800 E. Leigh St. Biotech One Suite 101, Richmond, VA, 23219, USA
| |
Collapse
|
17
|
Kamarajan C, Pandey AK, Chorlian DB, Meyers JL, Kinreich S, Pandey G, Subbie-Saenz de Viteri S, Zhang J, Kuang W, Barr PB, Aliev F, Anokhin AP, Plawecki MH, Kuperman S, Almasy L, Merikangas A, Brislin SJ, Bauer L, Hesselbrock V, Chan G, Kramer J, Lai D, Hartz S, Bierut LJ, McCutcheon VV, Bucholz KK, Dick DM, Schuckit MA, Edenberg HJ, Porjesz B. Predicting Alcohol-Related Memory Problems in Older Adults: A Machine Learning Study with Multi-Domain Features. Behav Sci (Basel) 2023; 13:bs13050427. [PMID: 37232664 DOI: 10.3390/bs13050427] [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: 03/12/2023] [Revised: 05/08/2023] [Accepted: 05/11/2023] [Indexed: 05/27/2023] Open
Abstract
Memory problems are common among older adults with a history of alcohol use disorder (AUD). Employing a machine learning framework, the current study investigates the use of multi-domain features to classify individuals with and without alcohol-induced memory problems. A group of 94 individuals (ages 50-81 years) with alcohol-induced memory problems (the memory group) were compared with a matched control group who did not have memory problems. The random forests model identified specific features from each domain that contributed to the classification of the memory group vs. the control group (AUC = 88.29%). Specifically, individuals from the memory group manifested a predominant pattern of hyperconnectivity across the default mode network regions except for some connections involving the anterior cingulate cortex, which were predominantly hypoconnected. Other significant contributing features were: (i) polygenic risk scores for AUD, (ii) alcohol consumption and related health consequences during the past five years, such as health problems, past negative experiences, withdrawal symptoms, and the largest number of drinks in a day during the past twelve months, and (iii) elevated neuroticism and increased harm avoidance, and fewer positive "uplift" life events. At the neural systems level, hyperconnectivity across the default mode network regions, including the connections across the hippocampal hub regions, in individuals with memory problems may indicate dysregulation in neural information processing. Overall, the study outlines the importance of utilizing multidomain features, consisting of resting-state brain connectivity data collected ~18 years ago, together with personality, life experiences, polygenic risk, and alcohol consumption and related consequences, to predict the alcohol-related memory problems that arise in later life.
Collapse
Affiliation(s)
- Chella Kamarajan
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry and Behavioral Science, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
| | - Ashwini K Pandey
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry and Behavioral Science, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
| | - David B Chorlian
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry and Behavioral Science, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
| | - Jacquelyn L Meyers
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry and Behavioral Science, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
| | - Sivan Kinreich
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry and Behavioral Science, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
| | - Gayathri Pandey
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry and Behavioral Science, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
| | - Stacey Subbie-Saenz de Viteri
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry and Behavioral Science, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
| | - Jian Zhang
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry and Behavioral Science, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
| | - Weipeng Kuang
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry and Behavioral Science, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
| | - Peter B Barr
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry and Behavioral Science, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
| | - Fazil Aliev
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ 08854, USA
| | - Andrey P Anokhin
- Department of Psychiatry, School of Medicine, Washington University, St. Louis, MO 63110, USA
| | | | - Samuel Kuperman
- Department of Psychiatry, University of Iowa, Iowa City, IA 52242, USA
| | - Laura Almasy
- The Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Alison Merikangas
- The Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Sarah J Brislin
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ 08854, USA
| | - Lance Bauer
- Department of Psychiatry, University of Connecticut, Farmington, CT 06030, USA
| | - Victor Hesselbrock
- Department of Psychiatry, University of Connecticut, Farmington, CT 06030, USA
| | - Grace Chan
- Department of Psychiatry, University of Iowa, Iowa City, IA 52242, USA
- Department of Psychiatry, University of Connecticut, Farmington, CT 06030, USA
| | - John Kramer
- Department of Psychiatry, University of Iowa, Iowa City, IA 52242, USA
| | - Dongbing Lai
- Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Sarah Hartz
- Department of Psychiatry, School of Medicine, Washington University, St. Louis, MO 63110, USA
| | - Laura J Bierut
- Department of Psychiatry, School of Medicine, Washington University, St. Louis, MO 63110, USA
| | - Vivia V McCutcheon
- Department of Psychiatry, School of Medicine, Washington University, St. Louis, MO 63110, USA
| | - Kathleen K Bucholz
- Department of Psychiatry, School of Medicine, Washington University, St. Louis, MO 63110, USA
| | - Danielle M Dick
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ 08854, USA
| | - Marc A Schuckit
- Department of Psychiatry, University of California, San Diego, CA 92103, USA
| | | | - Bernice Porjesz
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry and Behavioral Science, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
| |
Collapse
|
18
|
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: 6] [Impact Index Per Article: 6.0] [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.
Collapse
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
| |
Collapse
|
19
|
Mueller SH, Lai AG, Valkovskaya M, Michailidou K, Bolla MK, Wang Q, Dennis J, Lush M, Abu-Ful Z, Ahearn TU, Andrulis IL, Anton-Culver H, Antonenkova NN, Arndt V, Aronson KJ, Augustinsson A, Baert T, Freeman LEB, Beckmann MW, Behrens S, Benitez J, Bermisheva M, Blomqvist C, Bogdanova NV, Bojesen SE, Bonanni B, Brenner H, Brucker SY, Buys SS, Castelao JE, Chan TL, Chang-Claude J, Chanock SJ, Choi JY, Chung WK, Colonna SV, Cornelissen S, Couch FJ, Czene K, Daly MB, Devilee P, Dörk T, Dossus L, Dwek M, Eccles DM, Ekici AB, Eliassen AH, Engel C, Evans DG, Fasching PA, Fletcher O, Flyger H, Gago-Dominguez M, Gao YT, García-Closas M, García-Sáenz JA, Genkinger J, Gentry-Maharaj A, Grassmann F, Guénel P, Gündert M, Haeberle L, Hahnen E, Haiman CA, Håkansson N, Hall P, Harkness EF, Harrington PA, Hartikainen JM, Hartman M, Hein A, Ho WK, Hooning MJ, Hoppe R, Hopper JL, Houlston RS, Howell A, Hunter DJ, Huo D, Ito H, Iwasaki M, Jakubowska A, Janni W, John EM, Jones ME, Jung A, Kaaks R, Kang D, Khusnutdinova EK, Kim SW, Kitahara CM, Koutros S, Kraft P, Kristensen VN, Kubelka-Sabit K, Kurian AW, Kwong A, Lacey JV, Lambrechts D, Le Marchand L, Li J, Linet M, Lo WY, Long J, Lophatananon A, Mannermaa A, Manoochehri M, Margolin S, Matsuo K, Mavroudis D, Menon U, Muir K, Murphy RA, Nevanlinna H, Newman WG, Niederacher D, O'Brien KM, Obi N, Offit K, Olopade OI, Olshan AF, Olsson H, Park SK, Patel AV, Patel A, Perou CM, Peto J, Pharoah PDP, Plaseska-Karanfilska D, Presneau N, Rack B, Radice P, Ramachandran D, Rashid MU, Rennert G, Romero A, Ruddy KJ, Ruebner M, Saloustros E, Sandler DP, Sawyer EJ, Schmidt MK, Schmutzler RK, Schneider MO, Scott C, Shah M, Sharma P, Shen CY, Shu XO, Simard J, Surowy H, Tamimi RM, Tapper WJ, Taylor JA, Teo SH, Teras LR, Toland AE, Tollenaar RAEM, Torres D, Torres-Mejía G, Troester MA, Truong T, Vachon CM, Vijai J, Weinberg CR, Wendt C, Winqvist R, Wolk A, Wu AH, Yamaji T, Yang XR, Yu JC, Zheng W, Ziogas A, Ziv E, Dunning AM, Easton DF, Hemingway H, Hamann U, Kuchenbaecker KB. Aggregation tests identify new gene associations with breast cancer in populations with diverse ancestry. Genome Med 2023; 15:7. [PMID: 36703164 PMCID: PMC9878779 DOI: 10.1186/s13073-022-01152-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 12/16/2022] [Indexed: 01/27/2023] Open
Abstract
BACKGROUND Low-frequency variants play an important role in breast cancer (BC) susceptibility. Gene-based methods can increase power by combining multiple variants in the same gene and help identify target genes. METHODS We evaluated the potential of gene-based aggregation in the Breast Cancer Association Consortium cohorts including 83,471 cases and 59,199 controls. Low-frequency variants were aggregated for individual genes' coding and regulatory regions. Association results in European ancestry samples were compared to single-marker association results in the same cohort. Gene-based associations were also combined in meta-analysis across individuals with European, Asian, African, and Latin American and Hispanic ancestry. RESULTS In European ancestry samples, 14 genes were significantly associated (q < 0.05) with BC. Of those, two genes, FMNL3 (P = 6.11 × 10-6) and AC058822.1 (P = 1.47 × 10-4), represent new associations. High FMNL3 expression has previously been linked to poor prognosis in several other cancers. Meta-analysis of samples with diverse ancestry discovered further associations including established candidate genes ESR1 and CBLB. Furthermore, literature review and database query found further support for a biologically plausible link with cancer for genes CBLB, FMNL3, FGFR2, LSP1, MAP3K1, and SRGAP2C. CONCLUSIONS Using extended gene-based aggregation tests including coding and regulatory variation, we report identification of plausible target genes for previously identified single-marker associations with BC as well as the discovery of novel genes implicated in BC development. Including multi ancestral cohorts in this study enabled the identification of otherwise missed disease associations as ESR1 (P = 1.31 × 10-5), demonstrating the importance of diversifying study cohorts.
Collapse
Affiliation(s)
| | - Alvina G Lai
- Institute of Health Informatics, University College London, London, UK
| | | | - Kyriaki Michailidou
- Biostatistics Unit, The Cyprus Institute of Neurology and Genetics, 2371, Nicosia, Cyprus
- Cyprus School of Molecular Medicine, The Cyprus Institute of Neurology and Genetics, 2371, Nicosia, Cyprus
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Manjeet K Bolla
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Qin Wang
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Joe Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Michael Lush
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Zomoruda Abu-Ful
- Clalit National Cancer Control Center, Carmel Medical Center and Technion Faculty of Medicine, 35254, Haifa, Israel
| | - Thomas U Ahearn
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20850, USA
| | - Irene L Andrulis
- Fred A. Litwin Center for Cancer Genetics, Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Toronto, ON, M5G 1X5, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, M5S 1A8, Canada
| | - Hoda Anton-Culver
- Department of Medicine, Genetic Epidemiology Research Institute, University of California Irvine, Irvine, CA, 92617, USA
| | - Natalia N Antonenkova
- N.N. Alexandrov Research Institute of Oncology and Medical Radiology, 223040, Minsk, Belarus
| | - Volker Arndt
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Kristan J Aronson
- Department of Public Health Sciences, and Cancer Research Institute, Queen's University, Kingston, ON, K7L 3N6, Canada
| | - Annelie Augustinsson
- Department of Cancer Epidemiology, Clinical Sciences, Lund University, 222 42, Lund, Sweden
| | - Thais Baert
- Leuven Multidisciplinary Breast Center, Department of Oncology, Leuven Cancer Institute, University Hospitals Leuven, 3000, Louvain, Belgium
| | - Laura E Beane Freeman
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20850, USA
| | - Matthias W Beckmann
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg (FAU), 91054, Erlangen, Germany
| | - Sabine Behrens
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Javier Benitez
- Biomedical Network On Rare Diseases (CIBERER), 28029, Madrid, Spain
- Human Cancer Genetics Programme, Spanish National Cancer Research Centre (CNIO), 28029, Madrid, Spain
| | - Marina Bermisheva
- Institute of Biochemistry and Genetics, Ufa Federal Research Centre of the Russian Academy of Sciences, Ufa, 450054, Russia
| | - Carl Blomqvist
- Department of Oncology, Helsinki University Hospital, University of Helsinki, 00290, Helsinki, Finland
- Department of Oncology, Örebro University Hospital, 70185, Örebro, Sweden
| | - Natalia V Bogdanova
- N.N. Alexandrov Research Institute of Oncology and Medical Radiology, 223040, Minsk, Belarus
- Department of Radiation Oncology, Hannover Medical School, 30625, Hannover, Germany
- Gynaecology Research Unit, Hannover Medical School, 30625, Hannover, Germany
| | - Stig E Bojesen
- Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, 2730, Herlev, Denmark
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, 2730, Herlev, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, 2200, Copenhagen, Denmark
| | - Bernardo Bonanni
- Division of Cancer Prevention and Genetics, IEO, European Institute of Oncology IRCCS, 20141, Milan, Italy
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
- Division of Preventive Oncology, German Cancer Research Center (DKFZ), National Center for Tumor Diseases (NCT), 69120, Heidelberg, Germany
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Sara Y Brucker
- Department of Gynecology and Obstetrics, University of Tübingen, 72076, Tübingen, Germany
| | - Saundra S Buys
- Department of Medicine, Huntsman Cancer Institute, Salt Lake City, UT, 84112, USA
| | - Jose E Castelao
- Oncology and Genetics Unit, Instituto de Investigación Sanitaria Galicia Sur (IISGS), Xerencia de Xestion Integrada de Vigo-SERGAS, 36312, Vigo, Spain
| | - Tsun L Chan
- Hong Kong Hereditary Breast Cancer Family Registry, Hong Kong, China
- Department of Molecular Pathology, Hong Kong Sanatorium and Hospital, Hong Kong, China
| | - Jenny Chang-Claude
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
- Cancer Epidemiology Group, University Cancer Center Hamburg (UCCH), University Medical Center Hamburg-Eppendorf, 20246, Hamburg, Germany
| | - Stephen J Chanock
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20850, USA
| | - Ji-Yeob Choi
- Department of Biomedical Sciences, Seoul National University Graduate School, Seoul, 03080, Korea
- Cancer Research Institute, Seoul National University, Seoul, 03080, Korea
- Institute of Health Policy and Management, Seoul National University Medical Research Center, Seoul, 03080, Korea
| | - Wendy K Chung
- Departments of Pediatrics and Medicine, Columbia University, New York, NY, 10032, USA
| | - Sarah V Colonna
- Department of Medicine, Huntsman Cancer Institute, Salt Lake City, UT, 84112, USA
| | - Sten Cornelissen
- Division of Molecular Pathology, The Netherlands Cancer Institute - Antoni Van Leeuwenhoek Hospital, Amsterdam, 1066 CX, The Netherlands
| | - Fergus J Couch
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, 55905, USA
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 65, Stockholm, Sweden
| | - Mary B Daly
- Department of Clinical Genetics, Fox Chase Cancer Center, Philadelphia, PA, 19111, USA
| | - Peter Devilee
- Department of Pathology, Leiden University Medical Center, Leiden, 2333 ZA, The Netherlands
- Department of Human Genetics, Leiden University Medical Center, Leiden, 2333 ZA, The Netherlands
| | - Thilo Dörk
- Gynaecology Research Unit, Hannover Medical School, 30625, Hannover, Germany
| | - Laure Dossus
- Nutrition and Metabolism Section, International Agency for Research On Cancer (IARC-WHO), 69372, Lyon, France
| | - Miriam Dwek
- School of Life Sciences, University of Westminster, London, W1W 6UW, UK
| | - Diana M Eccles
- Faculty of Medicine, University of Southampton, Southampton, SO17 1BJ, UK
| | - Arif B Ekici
- Institute of Human Genetics, Comprehensive Cancer Center Erlangen-EMN, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg (FAU), 91054, Erlangen, Germany
| | - A Heather Eliassen
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Christoph Engel
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, 04107, Leipzig, Germany
- LIFE - Leipzig Research Centre for Civilization Diseases, University of Leipzig, 04103, Leipzig, Germany
| | - D Gareth Evans
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, M13 9WL, UK
- North West Genomics Laboratory Hub, Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, M13 9WL, UK
| | - Peter A Fasching
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg (FAU), 91054, Erlangen, Germany
- David Geffen School of Medicine, Department of Medicine Division of Hematology and Oncology, University of California at Los Angeles, Los Angeles, CA, 90095, USA
| | - Olivia Fletcher
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, SW7 3RP, UK
| | - Henrik Flyger
- Department of Breast Surgery, Herlev and Gentofte Hospital, Copenhagen University Hospital, 2730, Herlev, Denmark
| | - Manuela Gago-Dominguez
- Genomic Medicine Group, International Cancer Genetics and Epidemiology Group, Fundación Pœblica Galega de Medicina Xenómica, Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Complejo Hospitalario Universitario de Santiago, SERGAS, 15706, Santiago de Compostela, Spain
- Moores Cancer Center, University of California San Diego, La Jolla, CA, 92037, USA
| | - Yu-Tang Gao
- Department of Epidemiology, Shanghai Cancer Institute, Shanghai, 20032, China
| | - Montserrat García-Closas
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20850, USA
| | - José A García-Sáenz
- Medical Oncology Department, Centro Investigación Biomédica en Red de Cáncer (CIBERONC), Hospital Clínico San Carlos, Instituto de Investigación Sanitaria San Carlos (IdISSC), 28040, Madrid, Spain
| | - Jeanine Genkinger
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, 10032, USA
| | | | - Felix Grassmann
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 65, Stockholm, Sweden
- Health and Medical University, 14471, Potsdam, Germany
| | - Pascal Guénel
- Center for Research in Epidemiology and Population Health (CESP), Team Exposome and Heredity, INSERM, University Paris-Saclay, 94805, Villejuif, France
| | - Melanie Gündert
- Molecular Epidemiology Group, German Cancer Research Center (DKFZ), C08069120, Heidelberg, Germany
- Molecular Biology of Breast Cancer, University Womens Clinic Heidelberg, University of Heidelberg, 69120, Heidelberg, Germany
- Institute of Diabetes Research, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Lothar Haeberle
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg (FAU), 91054, Erlangen, Germany
| | - Eric Hahnen
- Center for Familial Breast and Ovarian Cancer, Faculty of Medicine, University Hospital Cologne, University of Cologne, 50937, Cologne, Germany
- Center for Integrated Oncology (CIO), Faculty of Medicine, University Hospital Cologne, University of Cologne, 50937, Cologne, Germany
| | - Christopher A Haiman
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA
| | - Niclas Håkansson
- Institute of Environmental Medicine, Karolinska Institutet, 171 77, Stockholm, Sweden
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 65, Stockholm, Sweden
- Department of Oncology, 118 83, Sšdersjukhuset, Stockholm, Sweden
| | - Elaine F Harkness
- Division of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, M13 9PT, UK
- Nightingale and Genesis Prevention Centre, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester, M23 9LT, UK
- NIHR Manchester Biomedical Research Unit, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, M13 9WL, UK
| | - Patricia A Harrington
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Jaana M Hartikainen
- Translational Cancer Research Area, University of Eastern Finland, 70210, Kuopio, Finland
- Institute of Clinical Medicine, Pathology and Forensic Medicine, University of Eastern Finland, 70210, Kuopio, Finland
| | - Mikael Hartman
- Saw Swee Hock School of Public Health, National University of Singapore, National University Health System, Singapore, 119077, Singapore
- Department of Surgery, National University Health System, Singapore, 119228, Singapore
| | - Alexander Hein
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg (FAU), 91054, Erlangen, Germany
| | - Weang-Kee Ho
- Department of Mathematical Sciences, Faculty of Science and Engineering, University of Nottingham Malaysia Campus, 43500, Semenyih, Selangor, Malaysia
- Breast Cancer Research Programme, Cancer Research Malaysia, Subang Jaya, 47500, Selangor, Malaysia
| | - Maartje J Hooning
- Department of Medical Oncology, Erasmus MC Cancer Institute, Rotterdam, 3015 GD, The Netherlands
| | - Reiner Hoppe
- Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, 70376, Stuttgart, Germany
- University of Tübingen, 72074, Tübingen, Germany
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, 3010, Australia
| | - Richard S Houlston
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, SM2 5NG, UK
| | - Anthony Howell
- Division of Cancer Sciences, University of Manchester, Manchester, M13 9PL, UK
| | - David J Hunter
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
- Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
| | - Dezheng Huo
- Center for Clinical Cancer Genetics, The University of Chicago, Chicago, IL, 60637, USA
| | - Hidemi Ito
- Division of Cancer Information and Control, Aichi Cancer Center Research Institute, Nagoya, 464-8681, Japan
- Division of Cancer Epidemiology, Nagoya University Graduate School of Medicine, Nagoya, 466-8550, Japan
| | - Motoki Iwasaki
- Division of Epidemiology, Center for Public Health Sciences, National Cancer Center Institute for Cancer Control, Tokyo, 104-0045, Japan
| | - Anna Jakubowska
- Department of Genetics and Pathology, Pomeranian Medical University, 71-252, Szczecin, Poland
- Independent Laboratory of Molecular Biology and Genetic Diagnostics, Pomeranian Medical University, 71-252, Szczecin, Poland
| | - Wolfgang Janni
- Department of Gynaecology and Obstetrics, University Hospital Ulm, 89075, Ulm, Germany
| | - Esther M John
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Department of Medicine, Division of Oncology, Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, 94304, USA
| | - Michael E Jones
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, SM2 5NG, UK
| | - Audrey Jung
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Rudolf Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Daehee Kang
- Cancer Research Institute, Seoul National University, Seoul, 03080, Korea
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, 03080, Korea
| | - Elza K Khusnutdinova
- Institute of Biochemistry and Genetics, Ufa Federal Research Centre of the Russian Academy of Sciences, Ufa, 450054, Russia
- Department of Genetics and Fundamental Medicine, Bashkir State University, Ufa, 450000, Russia
| | - Sung-Won Kim
- Department of Surgery, Daerim Saint Mary's Hospital, Seoul, 07442, Korea
| | - Cari M Kitahara
- Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, 20892, USA
| | - Stella Koutros
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20850, USA
| | - Peter Kraft
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
- Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Vessela N Kristensen
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, 0450, Oslo, Norway
- Department of Medical Genetics, Oslo University Hospital and University of Oslo, 0379, Oslo, Norway
| | - Katerina Kubelka-Sabit
- Department of Histopathology and Cytology, Clinical Hospital Acibadem Sistina, Skopje, 1000, Republic of North Macedonia
| | - Allison W Kurian
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Department of Medicine, Division of Oncology, Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, 94304, USA
| | - Ava Kwong
- Hong Kong Hereditary Breast Cancer Family Registry, Hong Kong, China
- Department of Surgery, The University of Hong Kong, Hong Kong, China
- Department of Surgery and Cancer Genetics Center, Hong Kong Sanatorium and Hospital, Hong Kong, China
| | - James V Lacey
- Department of Computational and Quantitative Medicine, City of Hope, Duarte, CA, 91010, USA
- City of Hope Comprehensive Cancer Center, City of Hope, Duarte, CA, 91010, USA
| | - Diether Lambrechts
- VIB Center for Cancer Biology, 3001, Louvain, Belgium
- Laboratory for Translational Genetics, Department of Human Genetics, University of Leuven, 3000, Louvain, Belgium
| | - Loic Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, 96813, USA
| | - Jingmei Li
- Human Genetics Division, Genome Institute of Singapore, Singapore, 138672, Singapore
| | - Martha Linet
- Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, 20892, USA
| | - Wing-Yee Lo
- Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, 70376, Stuttgart, Germany
- University of Tübingen, 72074, Tübingen, Germany
| | - Jirong Long
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, 37232, USA
| | - Artitaya Lophatananon
- Division of Population Health, Health Services Research and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, M13 9PL, UK
| | - Arto Mannermaa
- Translational Cancer Research Area, University of Eastern Finland, 70210, Kuopio, Finland
- Institute of Clinical Medicine, Pathology and Forensic Medicine, University of Eastern Finland, 70210, Kuopio, Finland
- Biobank of Eastern Finland, Kuopio University Hospital, Kuopio, Finland
| | - Mehdi Manoochehri
- Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Sara Margolin
- Department of Oncology, 118 83, Sšdersjukhuset, Stockholm, Sweden
- Department of Clinical Science and Education, Sšdersjukhuset, Karolinska Institutet, 118 83, Stockholm, Sweden
| | - Keitaro Matsuo
- Division of Cancer Epidemiology, Nagoya University Graduate School of Medicine, Nagoya, 466-8550, Japan
- Division of Cancer Epidemiology and Prevention, Aichi Cancer Center Research Institute, Nagoya, 464-8681, Japan
| | - Dimitrios Mavroudis
- Department of Medical Oncology, University Hospital of Heraklion, 711 10, Heraklion, Greece
| | - Usha Menon
- Institute of Clinical Trials and Methodology, University College London, London, WC1V 6LJ, UK
| | - Kenneth Muir
- Division of Population Health, Health Services Research and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, M13 9PL, UK
| | - Rachel A Murphy
- School of Population and Public Health, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada
- Cancer Control Research, BC Cancer, Vancouver, BC, V5Z 1L3, Canada
| | - Heli Nevanlinna
- Department of Obstetrics and Gynecology, Helsinki University Hospital, University of Helsinki, 00290, Helsinki, Finland
| | - William G Newman
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, M13 9WL, UK
- North West Genomics Laboratory Hub, Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, M13 9WL, UK
| | - Dieter Niederacher
- Department of Gynecology and Obstetrics, University Hospital Düsseldorf, Heinrich-Heine University Düsseldorf, 40225, Düsseldorf, Germany
| | - Katie M O'Brien
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, 27709, USA
| | - Nadia Obi
- Institute for Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, 20246, Hamburg, Germany
| | - Kenneth Offit
- Clinical Genetics Research Lab, Department of Cancer Biology and Genetics, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA
- Clinical Genetics Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA
| | | | - Andrew F Olshan
- Department of Epidemiology, Gillings School of Global Public Health and UNC Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Håkan Olsson
- Department of Cancer Epidemiology, Clinical Sciences, Lund University, 222 42, Lund, Sweden
| | - Sue K Park
- Cancer Research Institute, Seoul National University, Seoul, 03080, Korea
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, 03080, Korea
- Integrated Major in Innovative Medical Science, Seoul National University College of Medicine, Seoul, 03080, South Korea
| | - Alpa V Patel
- Department of Population Science, American Cancer Society, Atlanta, GA, 30303, USA
| | - Achal Patel
- Department of Epidemiology, Gillings School of Global Public Health and UNC Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Charles M Perou
- Department of Genetics, Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Julian Peto
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, WC1E 7HT, UK
| | - Paul D P Pharoah
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Dijana Plaseska-Karanfilska
- Research Centre for Genetic Engineering and Biotechnology "Georgi D. Efremov", MASA, Skopje, 1000, Republic of North Macedonia
| | - Nadege Presneau
- School of Life Sciences, University of Westminster, London, W1W 6UW, UK
| | - Brigitte Rack
- Department of Gynaecology and Obstetrics, University Hospital Ulm, 89075, Ulm, Germany
| | - Paolo Radice
- Unit of Molecular Bases of Genetic Risk and Genetic Testing, Department of Research, Fondazione IRCCS Istituto Nazionale Dei Tumori (INT), 20133, Milan, Italy
| | - Dhanya Ramachandran
- Gynaecology Research Unit, Hannover Medical School, 30625, Hannover, Germany
| | - Muhammad U Rashid
- Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
- Department of Basic Sciences, Shaukat Khanum Memorial Cancer Hospital and Research Centre (SKMCH & RC), Lahore, 54000, Pakistan
| | - Gad Rennert
- Clalit National Cancer Control Center, Carmel Medical Center and Technion Faculty of Medicine, 35254, Haifa, Israel
| | - Atocha Romero
- Medical Oncology Department, Hospital Universitario Puerta de Hierro, 28222, Madrid, Spain
| | - Kathryn J Ruddy
- Department of Oncology, Mayo Clinic, Rochester, MN, 55905, USA
| | - Matthias Ruebner
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg (FAU), 91054, Erlangen, Germany
| | | | - Dale P Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, 27709, USA
| | - Elinor J Sawyer
- School of Cancer and Pharmaceutical Sciences, Comprehensive Cancer Centre, Guy's Campus, King's College London, London, SE1 9RT, UK
| | - Marjanka K Schmidt
- Division of Molecular Pathology, The Netherlands Cancer Institute - Antoni Van Leeuwenhoek Hospital, Amsterdam, 1066 CX, The Netherlands
- Division of Psychosocial Research and Epidemiology, The Netherlands Cancer Institute - Antoni Van Leeuwenhoek Hospital, Amsterdam, 1066 CX, The Netherlands
| | - Rita K Schmutzler
- Center for Familial Breast and Ovarian Cancer, Faculty of Medicine, University Hospital Cologne, University of Cologne, 50937, Cologne, Germany
- Center for Integrated Oncology (CIO), Faculty of Medicine, University Hospital Cologne, University of Cologne, 50937, Cologne, Germany
- Center for Molecular Medicine Cologne (CMMC), Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931, Cologne, Germany
| | - Michael O Schneider
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg (FAU), 91054, Erlangen, Germany
| | - Christopher Scott
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, 55905, USA
| | - Mitul Shah
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Priyanka Sharma
- Department of Internal Medicine, Division of Medical Oncology, University of Kansas Medical Center, Westwood, KS, 66205, USA
| | - Chen-Yang Shen
- Institute of Biomedical Sciences, Academia Sinica, Taipei, 115, Taiwan
- School of Public Health, China Medical University, Taichung, Taiwan
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, 37232, USA
| | - Jacques Simard
- Genomics Center, Centre Hospitalier Universitaire de Québec - Université Laval Research Center, Québec City, QC, G1V 4G2, Canada
| | - Harald Surowy
- Molecular Epidemiology Group, German Cancer Research Center (DKFZ), C08069120, Heidelberg, Germany
- Molecular Biology of Breast Cancer, University Womens Clinic Heidelberg, University of Heidelberg, 69120, Heidelberg, Germany
| | - Rulla M Tamimi
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
- Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, 10065, USA
| | - William J Tapper
- Faculty of Medicine, University of Southampton, Southampton, SO17 1BJ, UK
| | - Jack A Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, 27709, USA
- Epigenetic and Stem Cell Biology Laboratory, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, 27709, USA
| | - Soo Hwang Teo
- Breast Cancer Research Programme, Cancer Research Malaysia, Subang Jaya, 47500, Selangor, Malaysia
- Department of Surgery, Faculty of Medicine, University of Malaya, 50603, Kuala Lumpur, Malaysia
| | - Lauren R Teras
- Department of Population Science, American Cancer Society, Atlanta, GA, 30303, USA
| | - Amanda E Toland
- Department of Cancer Biology and Genetics, The Ohio State University, Columbus, OH, 43210, USA
| | - Rob A E M Tollenaar
- Department of Surgery, Leiden University Medical Center, Leiden, 2333 ZA, The Netherlands
| | - Diana Torres
- Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
- Institute of Human Genetics, Pontificia Universidad Javeriana, 110231, Bogota, Colombia
| | - Gabriela Torres-Mejía
- Center for Population Health Research, National Institute of Public Health, 62100, Cuernavaca, Morelos, Mexico
| | - Melissa A Troester
- Department of Epidemiology, Gillings School of Global Public Health and UNC Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Thérèse Truong
- Center for Research in Epidemiology and Population Health (CESP), Team Exposome and Heredity, INSERM, University Paris-Saclay, 94805, Villejuif, France
| | - Celine M Vachon
- Department of Quantitative Health Sciences, Division of Epidemiology, Mayo Clinic, Rochester, MN, 55905, USA
| | - Joseph Vijai
- Clinical Genetics Research Lab, Department of Cancer Biology and Genetics, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA
- Clinical Genetics Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA
| | - Clarice R Weinberg
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, 27709, USA
| | - Camilla Wendt
- Department of Clinical Science and Education, Sšdersjukhuset, Karolinska Institutet, 118 83, Stockholm, Sweden
| | - Robert Winqvist
- Laboratory of Cancer Genetics and Tumor Biology, Cancer and Translational Medicine Research Unit, Biocenter Oulu, University of Oulu, 90570, Oulu, Finland
- Laboratory of Cancer Genetics and Tumor Biology, Northern Finland Laboratory Centre Oulu, 90570, Oulu, Finland
| | - Alicja Wolk
- Institute of Environmental Medicine, Karolinska Institutet, 171 77, Stockholm, Sweden
- Department of Surgical Sciences, Uppsala University, 751 05, Uppsala, Sweden
| | - Anna H Wu
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA
| | - Taiki Yamaji
- Division of Epidemiology, Center for Public Health Sciences, National Cancer Center Institute for Cancer Control, Tokyo, 104-0045, Japan
| | - Xiaohong R Yang
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20850, USA
| | - Jyh-Cherng Yu
- Department of Surgery, Tri-Service General Hospital, National Defense Medical Center, Taipei, 114, Taiwan
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, 37232, USA
| | - Argyrios Ziogas
- Department of Medicine, Genetic Epidemiology Research Institute, University of California Irvine, Irvine, CA, 92617, USA
| | - Elad Ziv
- Department of Medicine, Diller Family Comprehensive Cancer Center, Institute for Human Genetics, UCSF Helen, University of California San Francisco, San Francisco, CA, 94115, USA
| | - Alison M Dunning
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Douglas F Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Harry Hemingway
- Institute of Health Informatics, University College London, London, UK
- Health Data Research UK, University College London, London, UK
- University College London Hospitals Biomedical Research Centre (UCLH BRC), London, UK
- The Alan Turing Institute, London, UK
| | - Ute Hamann
- Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
| | - Karoline B Kuchenbaecker
- Division of Psychiatry, University College London, London, UK.
- UCL Genetics Institute, University College London, London, UK.
| |
Collapse
|
20
|
Macedo GC, Kreifeldt M, Goulding SP, Okhuarobo A, Sidhu H, Contet C. Chronic MAP4343 reverses escalated alcohol drinking in a mouse model of alcohol use disorder. Neuropsychopharmacology 2023; 48:821-830. [PMID: 36670228 PMCID: PMC10066354 DOI: 10.1038/s41386-023-01529-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2021] [Revised: 12/28/2022] [Accepted: 12/31/2022] [Indexed: 01/22/2023]
Abstract
Alcohol use disorders can be driven by negative reinforcement. Alterations of the microtubule cytoskeleton have been associated with mood regulation in the context of depression. Notably, MAP4343, a pregnenolone derivative known to promote tubulin assembly, has antidepressant properties. In the present study, we tested the hypothesis that MAP4343 may reduce excessive alcohol drinking in a mouse model of alcohol dependence by normalizing affect during withdrawal. Adult male C57BL/6J mice were given limited access to voluntary alcohol drinking and ethanol intake escalation was induced by chronic intermittent ethanol (CIE) vapor inhalation. Chronic, but not acute, administration of MAP4343 reduced ethanol intake and this effect was more pronounced in CIE-exposed mice. There was a complex interaction between the effects of MAP4343 and alcohol on affective behaviors. In the elevated plus maze, chronic MAP4343 tended to increase open-arm exploration in alcohol-naive mice but reduced it in alcohol-withdrawn mice. In the tail suspension test, chronic MAP4343 reduced immobility selectively in Air-exposed alcohol-drinking mice. Finally, chronic MAP4343 countered the plasma corticosterone reduction induced by CIE. Parallel analysis of tubulin post-translational modifications revealed lower α-tubulin acetylation in the medial prefrontal cortex of CIE-withdrawn mice. Altogether, these data support the relevance of microtubules as a therapeutic target for the treatment of AUD.
Collapse
Affiliation(s)
- Giovana C Macedo
- Department of Molecular Medicine, The Scripps Research Institute, La Jolla, CA, USA
| | - Max Kreifeldt
- Department of Molecular Medicine, The Scripps Research Institute, La Jolla, CA, USA
| | - Scott P Goulding
- Department of Molecular Medicine, The Scripps Research Institute, La Jolla, CA, USA
| | - Agbonlahor Okhuarobo
- Department of Molecular Medicine, The Scripps Research Institute, La Jolla, CA, USA.,Faculty of Pharmacy, Department of Pharmacology & Toxicology, University of Benin, Benin City, Nigeria
| | - Harpreet Sidhu
- Department of Molecular Medicine, The Scripps Research Institute, La Jolla, CA, USA
| | - Candice Contet
- Department of Molecular Medicine, The Scripps Research Institute, La Jolla, CA, USA.
| |
Collapse
|
21
|
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: 14] [Impact Index Per Article: 14.0] [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.
Collapse
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.
| |
Collapse
|
22
|
Mantsch JR. Corticotropin releasing factor and drug seeking in substance use disorders: Preclinical evidence and translational limitations. ADDICTION NEUROSCIENCE 2022; 4:100038. [PMID: 36531188 PMCID: PMC9757758 DOI: 10.1016/j.addicn.2022.100038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
The neuropeptide, corticotropin releasing factor (CRF), has been an enigmatic target for the development of medications aimed at treating stress-related disorders. Despite a large body of evidence from preclinical studies in rodents demonstrating that CRF receptor antagonists prevent stressor-induced drug seeking, medications targeting the CRF-R1 have failed in clinical trials. Here, we provide an overview of the abundant findings from preclinical rodent studies suggesting that CRF signaling is involved in stressor-induced relapse. The scientific literature that has defined the receptors, mechanisms and neurocircuits through which CRF contributes to stressor-induced reinstatement of drug seeking following self-administration and conditioned place preference in rodents is reviewed. Evidence that CRF signaling is recruited with repeated drug use in a manner that heightens susceptibility to stressor-induced drug seeking in rodents is presented. Factors that may determine the influence of CRF signaling in substance use disorders, including developmental windows, biological sex, and genetics are examined. Finally, we discuss the translational failure of medications targeting CRF signaling as interventions for substance use disorders and other stress-related conditions. We conclude that new perspectives and research directions are needed to unravel the mysterious role of CRF in substance use disorders.
Collapse
Affiliation(s)
- John R Mantsch
- Department of Pharmacology & Toxicology, Medical College of Wisconsin, 8701 W Watertown Plank Rd, Milwaukee, WI 53226, United States
| |
Collapse
|
23
|
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.
Collapse
|
24
|
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: 18] [Impact Index Per Article: 9.0] [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.
Collapse
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
| |
Collapse
|
25
|
Zhou H, Vasiliou V. Alcohol Use and Use Disorder and Cancer Risk: Perspective on Causal Inference. Complex Psychiatry 2022; 8:9-12. [PMID: 36601413 PMCID: PMC9669948 DOI: 10.1159/000526407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Accepted: 07/08/2022] [Indexed: 01/07/2023] Open
Affiliation(s)
- Hang Zhou
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut, USA
- *Hang Zhou,
| | - Vasilis Vasiliou
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, Connecticut, USA
| |
Collapse
|
26
|
Huang QQ, Sallah N, Dunca D, Trivedi B, Hunt KA, Hodgson S, Lambert SA, Arciero E, Wright J, Griffiths C, Trembath RC, Hemingway H, Inouye M, Finer S, van Heel DA, Lumbers RT, Martin HC, Kuchenbaecker K. Transferability of genetic loci and polygenic scores for cardiometabolic traits in British Pakistani and Bangladeshi individuals. Nat Commun 2022; 13:4664. [PMID: 35945198 PMCID: PMC9363492 DOI: 10.1038/s41467-022-32095-5] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 07/15/2022] [Indexed: 12/30/2022] Open
Abstract
Individuals with South Asian ancestry have a higher risk of heart disease than other groups but have been largely excluded from genetic research. Using data from 22,000 British Pakistani and Bangladeshi individuals with linked electronic health records from the Genes & Health cohort, we conducted genome-wide association studies of coronary artery disease and its key risk factors. Using power-adjusted transferability ratios, we found evidence for transferability for the majority of cardiometabolic loci powered to replicate. The performance of polygenic scores was high for lipids and blood pressure, but lower for BMI and coronary artery disease. Adding a polygenic score for coronary artery disease to clinical risk factors showed significant improvement in reclassification. In Mendelian randomisation using transferable loci as instruments, our findings were consistent with results in European-ancestry individuals. Taken together, trait-specific transferability of trait loci between populations is an important consideration with implications for risk prediction and causal inference.
Collapse
Affiliation(s)
- Qin Qin Huang
- Department of Human Genetics, Wellcome Sanger Institute, Cambridge, UK
| | - Neneh Sallah
- Institute of Health Informatics, University College London, London, UK
- UCL Genetics Institute, University College London, London, UK
| | - Diana Dunca
- Institute of Health Informatics, University College London, London, UK
- UCL Genetics Institute, University College London, London, UK
| | - Bhavi Trivedi
- Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Karen A Hunt
- Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Sam Hodgson
- Primary Care Research Centre, University of Southampton, Southampton, UK
| | - Samuel A Lambert
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
| | - Elena Arciero
- Department of Human Genetics, Wellcome Sanger Institute, Cambridge, UK
| | - John Wright
- Bradford Institute for Health Research, Bradford Teaching Hospitals National Health Service (NHS) Foundation Trust, Bradford, UK
| | - Chris Griffiths
- Institute of Population Health Sciences, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Richard C Trembath
- Department of Medical and Molecular Genetics, King's College London, London, UK
| | - Harry Hemingway
- Institute of Health Informatics, University College London, London, UK
- Health Data Research UK, University College London, London, UK
- University College London Hospitals Biomedical Research Centre (UCLH BRC), London, UK
| | - Michael Inouye
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- British Heart Foundation Cambridge Centre of Research Excellence, Department of Clinical Medicine, University of Cambridge, Cambridge, UK
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
| | - Sarah Finer
- Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - David A van Heel
- Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - R Thomas Lumbers
- Institute of Health Informatics, University College London, London, UK
- University College London Hospitals Biomedical Research Centre (UCLH BRC), London, UK
- British Heart Foundation Research Accelerator, University College London, London, UK
| | - Hilary C Martin
- Department of Human Genetics, Wellcome Sanger Institute, Cambridge, UK
| | - Karoline Kuchenbaecker
- UCL Genetics Institute, University College London, London, UK.
- Division of Psychiatry, University College London, London, UK.
| |
Collapse
|
27
|
de Marco A, Scozia G, Manfredi L, Conversi D. A Systematic Review of Genetic Polymorphisms Associated with Bipolar Disorder Comorbid to Substance Abuse. Genes (Basel) 2022; 13:genes13081303. [PMID: 35893041 PMCID: PMC9330731 DOI: 10.3390/genes13081303] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Revised: 07/20/2022] [Accepted: 07/21/2022] [Indexed: 01/09/2023] Open
Abstract
It is currently unknown which genetic polymorphisms are involved in substance use disorder (SUD) comorbid with bipolar disorder (BD). The research on polymorphisms in BD comorbid with SUD (BD + SUD) is summarized in this systematic review. We looked for case-control studies that genetically compared adults and adolescents with BD and SUD, healthy controls, and BD without SUD. PRISMA was used to create our protocol, which is PROSPERO-registered (identification: CRD4221270818). The following bibliographic databases were searched indefinitely until December 2021 to identify potentially relevant articles: PubMed, PsycINFO, Scopus, and Web of Science. This systematic review, after the qualitative analysis of the study selection, included 17 eligible articles. In the selected studies, 66 polymorphisms in 29 genes were investigated. The present work delivers a group of potentially valuable genetic polymorphisms associated with BD + SUD: rs11600996 (ARNTL), rs228642/rs228682/rs2640909 (PER3), PONQ192R (PON1), rs945032 (BDKRB2), rs1131339 (NR4A3), and rs6971 (TSPO). It is important to note that none of those findings have been confirmed by two or more studies; thus, we believe that all the polymorphisms identified in this review require additional evidence to be confirmed.
Collapse
Affiliation(s)
- Adriano de Marco
- Department of Psychology, Università degli Studi di Roma ‘La Sapienza’, 00185 Rome, Italy; (A.d.M.); (G.S.); (L.M.)
| | - Gabriele Scozia
- Department of Psychology, Università degli Studi di Roma ‘La Sapienza’, 00185 Rome, Italy; (A.d.M.); (G.S.); (L.M.)
- PhD Program in Behavioral Neuroscience, Università degli Studi di Roma ‘La Sapienza’, 00185 Rome, Italy
| | - Lucia Manfredi
- Department of Psychology, Università degli Studi di Roma ‘La Sapienza’, 00185 Rome, Italy; (A.d.M.); (G.S.); (L.M.)
| | - David Conversi
- Department of Psychology, Università degli Studi di Roma ‘La Sapienza’, 00185 Rome, Italy; (A.d.M.); (G.S.); (L.M.)
- Correspondence:
| |
Collapse
|
28
|
Parker CC, Philip VM, Gatti DM, Kasparek S, Kreuzman AM, Kuffler L, Mansky B, Masneuf S, Sharif K, Sluys E, Taterra D, Taylor WM, Thomas M, Polesskaya O, Palmer AA, Holmes A, Chesler EJ. Genome-wide association mapping of ethanol sensitivity in the Diversity Outbred mouse population. Alcohol Clin Exp Res 2022; 46:941-960. [PMID: 35383961 DOI: 10.1111/acer.14825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Revised: 03/04/2022] [Accepted: 03/30/2022] [Indexed: 12/01/2022]
Abstract
BACKGROUND A strong predictor for the development of alcohol use disorder (AUD) is altered sensitivity to the intoxicating effects of alcohol. Individual differences in the initial sensitivity to alcohol are controlled in part by genetic factors. Mice offer a powerful tool to elucidate the genetic basis of behavioral and physiological traits relevant to AUD, but conventional experimental crosses have only been able to identify large chromosomal regions rather than specific genes. Genetically diverse, highly recombinant mouse populations make it possible to observe a wider range of phenotypic variation, offer greater mapping precision, and thus increase the potential for efficient gene identification. METHODS We have taken advantage of the Diversity Outbred (DO) mouse population to identify and precisely map quantitative trait loci (QTL) associated with ethanol sensitivity. We phenotyped 798 male J:DO mice for three measures of ethanol sensitivity: ataxia, hypothermia, and loss of the righting response. We used high-density MegaMUGA and GigaMUGA to obtain genotypes ranging from 77,808 to 143,259 SNPs. We also performed RNA sequencing in striatum to map expression QTLs and identify gene expression-trait correlations. We then applied a systems genetic strategy to identify narrow QTLs and construct the network of correlations that exists between DNA sequence, gene expression values, and ethanol-related phenotypes to prioritize our list of positional candidate genes. RESULTS We observed large amounts of phenotypic variation with the DO population and identified suggestive and significant QTLs associated with ethanol sensitivity on chromosomes 1, 2, and 16. The implicated regions were narrow (4.5-6.9 Mb in size) and each QTL explained ~4-5% of the variance. CONCLUSIONS Our results can be used to identify alleles that contribute to AUD in humans, elucidate causative biological mechanisms, or assist in the development of novel therapeutic interventions.
Collapse
Affiliation(s)
- Clarissa C Parker
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, Vermont, USA
| | - Vivek M Philip
- Center for Computational Sciences, The Jackson Laboratory, Bar Harbor, Maine, USA
| | - Daniel M Gatti
- Center for Computational Sciences, The Jackson Laboratory, Bar Harbor, Maine, USA
| | - Steven Kasparek
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, Vermont, USA
| | - Andrew M Kreuzman
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, Vermont, USA
| | - Lauren Kuffler
- Center for Mammalian Genetics, The Jackson Laboratory, Bar Harbor, Maine, USA
| | - Benjamin Mansky
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, Vermont, USA
| | - Sophie Masneuf
- Laboratory of Behavioral and Genomic Neuroscience, NIAAA, NIH, Rockville, MD, USA
| | - Kayvon Sharif
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, Vermont, USA
| | - Erica Sluys
- Laboratory of Behavioral and Genomic Neuroscience, NIAAA, NIH, Rockville, MD, USA
| | - Dominik Taterra
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, Vermont, USA
| | - Walter M Taylor
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, Vermont, USA
| | - Mary Thomas
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, Vermont, USA
| | - Oksana Polesskaya
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,Institute for Genomic Medicine, University of California San Diego, La Jolla, California, USA
| | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,Institute for Genomic Medicine, University of California San Diego, La Jolla, California, USA
| | - Andrew Holmes
- Laboratory of Behavioral and Genomic Neuroscience, NIAAA, NIH, Rockville, MD, USA
| | - Elissa J Chesler
- Center for Mammalian Genetics, The Jackson Laboratory, Bar Harbor, Maine, USA
| |
Collapse
|
29
|
Ressler KJ, Berretta S, Bolshakov VY, Rosso IM, Meloni EG, Rauch SL, Carlezon WA. Post-traumatic stress disorder: clinical and translational neuroscience from cells to circuits. Nat Rev Neurol 2022; 18:273-288. [PMID: 35352034 PMCID: PMC9682920 DOI: 10.1038/s41582-022-00635-8] [Citation(s) in RCA: 116] [Impact Index Per Article: 58.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/18/2022] [Indexed: 01/16/2023]
Abstract
Post-traumatic stress disorder (PTSD) is a maladaptive and debilitating psychiatric disorder, characterized by re-experiencing, avoidance, negative emotions and thoughts, and hyperarousal in the months and years following exposure to severe trauma. PTSD has a prevalence of approximately 6-8% in the general population, although this can increase to 25% among groups who have experienced severe psychological trauma, such as combat veterans, refugees and victims of assault. The risk of developing PTSD in the aftermath of severe trauma is determined by multiple factors, including genetics - at least 30-40% of the risk of PTSD is heritable - and past history, for example, prior adult and childhood trauma. Many of the primary symptoms of PTSD, including hyperarousal and sleep dysregulation, are increasingly understood through translational neuroscience. In addition, a large amount of evidence suggests that PTSD can be viewed, at least in part, as a disorder that involves dysregulation of normal fear processes. The neural circuitry underlying fear and threat-related behaviour and learning in mammals, including the amygdala-hippocampus-medial prefrontal cortex circuit, is among the most well-understood in behavioural neuroscience. Furthermore, the study of threat-responding and its underlying circuitry has led to rapid progress in understanding learning and memory processes. By combining molecular-genetic approaches with a translational, mechanistic knowledge of fear circuitry, transformational advances in the conceptual framework, diagnosis and treatment of PTSD are possible. In this Review, we describe the clinical features and current treatments for PTSD, examine the neurobiology of symptom domains, highlight genomic advances and discuss translational approaches to understanding mechanisms and identifying new treatments and interventions for this devastating syndrome.
Collapse
Affiliation(s)
- Kerry J Ressler
- SPARED Center, Department of Psychiatry, McLean Hospital, Harvard Medical School, Boston, MA, USA.
| | - Sabina Berretta
- SPARED Center, Department of Psychiatry, McLean Hospital, Harvard Medical School, Boston, MA, USA
| | - Vadim Y Bolshakov
- SPARED Center, Department of Psychiatry, McLean Hospital, Harvard Medical School, Boston, MA, USA
| | - Isabelle M Rosso
- SPARED Center, Department of Psychiatry, McLean Hospital, Harvard Medical School, Boston, MA, USA
| | - Edward G Meloni
- SPARED Center, Department of Psychiatry, McLean Hospital, Harvard Medical School, Boston, MA, USA
| | - Scott L Rauch
- SPARED Center, Department of Psychiatry, McLean Hospital, Harvard Medical School, Boston, MA, USA
| | - William A Carlezon
- SPARED Center, Department of Psychiatry, McLean Hospital, Harvard Medical School, Boston, MA, USA
| |
Collapse
|
30
|
Bountress KE, Brick LA, Sheerin C, Grotzinger A, Bustamante D, Hawn SE, Gillespie N, Kirkpatrick RM, Kranzler H, Morey R, Edenberg HJ, Maihofer AX, Disner S, Ashley-Koch A, Peterson R, Lori A, Stein DJ, Kimbrel N, Nievergelt C, Andreassen OA, Luykx J, Javanbakht A, Youssef NA, Amstadter AB. Alcohol use and alcohol use disorder differ in their genetic relationships with PTSD: A genomic structural equation modelling approach. Drug Alcohol Depend 2022; 234:109430. [PMID: 35367939 PMCID: PMC9018560 DOI: 10.1016/j.drugalcdep.2022.109430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 03/09/2022] [Accepted: 03/21/2022] [Indexed: 11/20/2022]
Abstract
PURPOSE Posttraumatic Stress Disorder (PTSD) is associated with increased alcohol use and alcohol use disorder (AUD), which are all moderately heritable. Studies suggest the genetic association between PTSD and alcohol use differs from that of PTSD and AUD, but further analysis is needed. BASIC PROCEDURES We used genomic Structural Equation Modeling (genomicSEM) to analyze summary statistics from large-scale genome-wide association studies (GWAS) of European Ancestry participants to investigate the genetic relationships between PTSD (both diagnosis and re-experiencing symptom severity) and a range of alcohol use and AUD phenotypes. MAIN FINDINGS When we differentiated genetic factors for alcohol use and AUD we observed improved model fit relative to models with all alcohol-related indicators loading onto a single factor. The genetic correlations (rG) of PTSD were quite discrepant for the alcohol use and AUD factors. This was true when modeled as a three-correlated-factor model (PTSD-AUD rG:.36, p < .001; PTSD-alcohol use rG: -0.17, p < .001) and as a Bifactor model, in which the common and unique portions of alcohol phenotypes were pulled out into an AUD-specific factor (rG with PTSD:.40, p < .001), AU-specific factor (rG with PTSD: -0.57, p < .001), and a common alcohol factor (rG with PTSD:.16, NS). PRINCIPAL CONCLUSIONS These results indicate the genetic architecture of alcohol use and AUD are differentially associated with PTSD. When the portions of variance unique to alcohol use and AUD are extracted, their genetic associations with PTSD vary substantially, suggesting different genetic architectures of alcohol phenotypes in people with PTSD.
Collapse
Affiliation(s)
- Kaitlin E Bountress
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, USA.
| | - Leslie A Brick
- Department of Psychiatry and Human Behavior, Quantitative Sciences Program, Alpert Medical School at Brown University, USA
| | - Christina Sheerin
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, USA
| | - Andrew Grotzinger
- Behavioral, Psychiatric, and Statistical Genetics, Institute for Behavior Genetics, University of Colorado Boulder, USA
| | - Daniel Bustamante
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, USA; Integrative Life Sciences Doctoral Program, Virginia Commonwealth University, USA
| | - Sage E Hawn
- National Center for PTSD at VA Boston Healthcare System, Boston, MA, USA; Boston University School of Medicine, Department of Psychiatry, Boston, MA, USA
| | - Nathan Gillespie
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, USA
| | - Robert M Kirkpatrick
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, USA
| | - Henry Kranzler
- University of Pennsylvania Perelman School of Medicine, Department of Psychiatry, Philadelphia, PA, USA; Mental Illness Research, Education and Clinical Center, Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
| | - Rajendra Morey
- VA Mid-Atlantic Mental Illness Research Education and Clinical Center, Durham VAMC, Durham, NC, USA; Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA; Duke-UNC Brain Imaging and Analysis Center, Duke University, Durham, NC, USA
| | - Howard J Edenberg
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, USA; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, USA
| | - Adam X Maihofer
- Department of Psychiatry, University of California, San Diego, USA; Center of Excellence for Stress and Mental Health, Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
| | - Seth Disner
- Minneapolis VA Health Care System, Minneapolis, MN, USA; Department of Psychiatry and Behavioral Sciences, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Allison Ashley-Koch
- Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC, USA
| | - Roseann Peterson
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, USA
| | - Adriana Lori
- Department of Psychiatry and Behavioral Sciences, Emory University, USA
| | - Dan J Stein
- Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Nathan Kimbrel
- VA Mid-Atlantic Mental Illness Research Education and Clinical Center, Durham VAMC, Durham, NC, USA; Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
| | - Caroline Nievergelt
- Department of Psychiatry, University of California, San Diego, USA; Center of Excellence for Stress and Mental Health, Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
| | - Ole A Andreassen
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Jurjen Luykx
- School for Mental Health and Neuroscience, Maastricht University Medical Centre, Department of Psychiatry and Neuropsychology Maastricht, The Netherlands; UMC Utrecht Brain Center, University Medical Center Utrecht, Department of Psychiatry Utrecht, University, Utrecht, The Netherlands; Outpatient second opinion clinic, GGNet Mental Health, Warnsveld, The Netherlands
| | - Arash Javanbakht
- Stress, Trauma, and Anxiety Research Clinic (STARC), Department of Psychiatry and Behavioral Neurosciences, Wayne State University, Detroit, MI, USA
| | - Nagy A Youssef
- Department of Psychiatry and Behavioral Health, Ohio State University, Columbus, OH, USA
| | - Ananda B Amstadter
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, USA
| |
Collapse
|
31
|
Rabinowitz JA, Jin J, Kuo SIC, Campos AI, Rentería ME, Huhn AS, Thrul J, Reboussin BA, Benke K, Domingue B, Ialongo NS, Maher BS, Kertes D, Troiani V, Uhl G. Positive associations between cannabis and alcohol use polygenic risk scores and phenotypic opioid misuse among African-Americans. PLoS One 2022; 17:e0266384. [PMID: 35395044 PMCID: PMC8993003 DOI: 10.1371/journal.pone.0266384] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Accepted: 03/12/2022] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND This study examined whether polygenic risk scores (PRS) for lifetime cannabis and alcohol use were associated with misusing opioids, and whether sex differences existed in these relations in an urban, African-American sample. METHODS Data were drawn from three cohorts of participants (N = 1,103; 45% male) who were recruited in first grade as part of a series of elementary school-based, universal preventive intervention trials conducted in a Mid-Atlantic region of the U.S. In young adulthood, participants provided a DNA sample and reported on whether they had used heroin or misused prescription opioids in their lifetime. Three substance use PRS were computed based on prior GWAS: lifetime cannabis use from Pasman et al. (2018), heavy drinking indexed via maximum number of drinks from Gelernter et al. (2019), and alcohol consumption from Kranzler et al. (2019). RESULTS Higher PRS for lifetime cannabis use, greater heavy drinking, and greater alcohol consumption were associated with heightened risk for misusing opioids among the whole sample. Significant sex by PRS interactions were also observed such that higher PRS for heavy drinking and alcohol consumption were associated with a greater likelihood of opioid misuse among males, but not females. CONCLUSION Our findings further elucidate the genetic contributions to misusing opioids by showing that the genetics of cannabis and alcohol consumption are associated with lifetime opioid misuse among young adults, though replication of our findings is needed.
Collapse
Affiliation(s)
- Jill A. Rabinowitz
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America
| | - Jin Jin
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America
| | - Sally I-Chun Kuo
- Department of Psychology, Virginia Commonwealth University, Richmond, VA, United States of America
| | - Adrian I. Campos
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Miguel E. Rentería
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Andrew S. Huhn
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America
| | - Johannes Thrul
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America
- Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD, United States of America
- Centre for Alcohol Policy Research, La Trobe University, Melbourne, Australia
| | - Beth A. Reboussin
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC, United States of America
| | - Kelly Benke
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America
| | - Benjamin Domingue
- Graduate School of Education, Stanford University, Stanford, CA, United States of America
| | - Nicholas S. Ialongo
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America
| | - Brion S. Maher
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America
| | - Darlene Kertes
- Department of Psychology, University of Florida, Gainesville, FL, United States of America
| | | | - George Uhl
- New Mexico VA HealthCare System, Albuquerque, New Mexico, United States of America
| |
Collapse
|
32
|
Salim C, Kan AK, Batsaikhan E, Patterson EC, Jee C. Neuropeptidergic regulation of compulsive ethanol seeking in C. elegans. Sci Rep 2022; 12:1804. [PMID: 35110557 PMCID: PMC8810865 DOI: 10.1038/s41598-022-05256-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Accepted: 01/07/2022] [Indexed: 11/09/2022] Open
Abstract
Despite the catastrophic consequences of alcohol abuse, alcohol use disorders (AUD) and comorbidities continue to strain the healthcare system, largely due to the effects of alcohol-seeking behavior. An improved understanding of the molecular basis of alcohol seeking will lead to enriched treatments for these disorders. Compulsive alcohol seeking is characterized by an imbalance between the superior drive to consume alcohol and the disruption or erosion in control of alcohol use. To model the development of compulsive engagement in alcohol seeking, we simultaneously exploited two distinct and conflicting Caenorhabditis elegans behavioral programs, ethanol preference and avoidance of aversive stimulus. We demonstrate that the C. elegans model recapitulated the pivotal features of compulsive alcohol seeking in mammals, specifically repeated attempts, endurance, and finally aversion-resistant alcohol seeking. We found that neuropeptide signaling via SEB-3, a CRF receptor-like GPCR, facilitates the development of ethanol preference and compels animals to seek ethanol compulsively. Furthermore, our functional genomic approach and behavioral elucidation suggest that the SEB-3 regulates another neuropeptidergic signaling, the neurokinin receptor orthologue TKR-1, to facilitate compulsive ethanol-seeking behavior.
Collapse
Affiliation(s)
- Chinnu Salim
- Department of Pharmacology, Addiction Science and Toxicology, College of Medicine, University of Tennessee Health Science Center (UTHSC), 71 S. Manassas St., Suite 217, Memphis, TN, 38103, USA
| | - Ann Ke Kan
- Department of Pharmacology, Addiction Science and Toxicology, College of Medicine, University of Tennessee Health Science Center (UTHSC), 71 S. Manassas St., Suite 217, Memphis, TN, 38103, USA
| | - Enkhzul Batsaikhan
- Department of Pharmacology, Addiction Science and Toxicology, College of Medicine, University of Tennessee Health Science Center (UTHSC), 71 S. Manassas St., Suite 217, Memphis, TN, 38103, USA
| | - E Clare Patterson
- Department of Pharmacology, Addiction Science and Toxicology, College of Medicine, University of Tennessee Health Science Center (UTHSC), 71 S. Manassas St., Suite 217, Memphis, TN, 38103, USA
| | - Changhoon Jee
- Department of Pharmacology, Addiction Science and Toxicology, College of Medicine, University of Tennessee Health Science Center (UTHSC), 71 S. Manassas St., Suite 217, Memphis, TN, 38103, USA.
| |
Collapse
|
33
|
Kandaswamy R, Allegrini A, Nancarrow AF, Cave SN, Plomin R, von Stumm S. Predicting Alcohol Use From Genome-Wide Polygenic Scores, Environmental Factors, and Their Interactions in Young Adulthood. Psychosom Med 2022; 84:244-250. [PMID: 34469941 DOI: 10.1097/psy.0000000000001005] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
OBJECTIVE Alcohol use during emerging adulthood is associated with adverse life outcomes, but its risk factors are not well known. Here, we predicted alcohol use in 3153 young adults aged 22 years from a) genome-wide polygenic scores (GPS) based on genome-wide association studies for the target phenotypes number of drinks per week and Alcohol Use Disorders Identification Test scores, b) 30 environmental factors, and c) their interactions (i.e., G × E effects). METHODS Data were collected from 1994 to 2018 as a part of the UK Twins Early Development Study. RESULTS GPS accounted for up to 1.9% of the variance in alcohol use (i.e., Alcohol Use Disorders Identification Test score), whereas the 30 measures of environmental factors together accounted for 21.1%. The 30 GPS by environment interactions did not explain any additional variance, and none of the interaction terms exceeded the significance threshold after correcting for multiple testing. CONCLUSIONS GPS and some environmental factors significantly predicted alcohol use in young adulthood, but we observed no GPS by environment interactions in our study.
Collapse
Affiliation(s)
- Radhika Kandaswamy
- From the Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience (Kandaswamy, Allegrini, Plomin), King's College London, London; Department of Education (Nancarrow, von Stumm), University of York, Heslington, York, United Kingdom; and School of Psychology (Cave), University of Nottingham, Nottingham, United Kingdom
| | | | | | | | | | | |
Collapse
|
34
|
Katz DH, Tahir UA, Bick AG, Pampana A, Ngo D, Benson MD, Yu Z, Robbins JM, Chen ZZ, Cruz DE, Deng S, Farrell L, Sinha S, Schmaier AA, Shen D, Gao Y, Hall ME, Correa A, Tracy RP, Durda P, Taylor KD, Liu Y, Johnson WC, Guo X, Yao J, Ida Chen YD, Manichaikul AW, Jain D, Bouchard C, Sarzynski MA, Rich SS, Rotter JI, Wang TJ, Wilson JG, Natarajan P, Gerszten RE. Whole Genome Sequence Analysis of the Plasma Proteome in Black Adults Provides Novel Insights Into Cardiovascular Disease. Circulation 2022; 145:357-370. [PMID: 34814699 PMCID: PMC9158509 DOI: 10.1161/circulationaha.121.055117] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Accepted: 10/27/2021] [Indexed: 02/03/2023]
Abstract
BACKGROUND Plasma proteins are critical mediators of cardiovascular processes and are the targets of many drugs. Previous efforts to characterize the genetic architecture of the plasma proteome have been limited by a focus on individuals of European descent and leveraged genotyping arrays and imputation. Here we describe whole genome sequence analysis of the plasma proteome in individuals with greater African ancestry, increasing our power to identify novel genetic determinants. METHODS Proteomic profiling of 1301 proteins was performed in 1852 Black adults from the Jackson Heart Study using aptamer-based proteomics (SomaScan). Whole genome sequencing association analysis was ascertained for all variants with minor allele count ≥5. Results were validated using an alternative, antibody-based, proteomic platform (Olink) as well as replicated in the Multi-Ethnic Study of Atherosclerosis and the HERITAGE Family Study (Health, Risk Factors, Exercise Training and Genetics). RESULTS We identify 569 genetic associations between 479 proteins and 438 unique genetic regions at a Bonferroni-adjusted significance level of 3.8×10-11. These associations include 114 novel locus-protein relationships and an additional 217 novel sentinel variant-protein relationships. Novel cardiovascular findings include new protein associations at the APOE gene locus including ZAP70 (sentinel single nucleotide polymorphism [SNP] rs7412-T, β=0.61±0.05, P=3.27×10-30) and MMP-3 (β=-0.60±0.05, P=1.67×10-32), as well as a completely novel pleiotropic locus at the HPX gene, associated with 9 proteins. Further, the associations suggest new mechanisms of genetically mediated cardiovascular disease linked to African ancestry; we identify a novel association between variants linked to APOL1-associated chronic kidney and heart disease and the protein CKAP2 (rs73885319-G, β=0.34±0.04, P=1.34×10-17) as well as an association between ATTR amyloidosis and RBP4 levels in community-dwelling individuals without heart failure. CONCLUSIONS Taken together, these results provide evidence for the functional importance of variants in non-European populations, and suggest new biological mechanisms for ancestry-specific determinants of lipids, coagulation, and myocardial function.
Collapse
Affiliation(s)
- Daniel H. Katz
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Usman A. Tahir
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | | | | | - Debby Ngo
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Mark D. Benson
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Zhi Yu
- Broad Institute of Harvard and MIT, Cambridge, MA
| | - Jeremy M. Robbins
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Zsu-Zsu Chen
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Daniel E. Cruz
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Shuliang Deng
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Laurie Farrell
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Sumita Sinha
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Alec A. Schmaier
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Dongxiao Shen
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Yan Gao
- Univ of Mississippi Medical Center, Jackson, MS
| | | | - Adolfo Correa
- University of Mississippi Medical Center, Jackson, MS
| | - Russell P. Tracy
- Department of Pathology Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT
| | - Peter Durda
- Department of Pathology Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT
| | - 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
| | - Yongmei Liu
- Department of Medicine, Division of Cardiology, Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC
| | - W. Craig Johnson
- Department of Biostatistics, University of Washington, Seattle, WA
| | - 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
| | - Jie Yao
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Ani W. Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia
- Division of Biostatistics and Epidemiology, Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia
| | - Deepti Jain
- University of Washington, Seattle, Washington
| | | | - Claude Bouchard
- Human Genomic Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA
| | - Mark A. Sarzynski
- Department of Exercise Science, University of South Carolina, Columbia, SC
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia
| | - 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
| | - Thomas J. Wang
- Department of Medicine, UT Southwestern Medical Center, Dallas, TX
| | - James G. Wilson
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Pradeep Natarajan
- Broad Institute of Harvard and MIT, Cambridge, MA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA
- Department of Medicine Harvard Medical School, Boston, MA
| | - Robert E. Gerszten
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA
- Broad Institute of Harvard and MIT, Cambridge, MA
| |
Collapse
|
35
|
Mallard TT, Savage JE, Johnson EC, Huang Y, Edwards AC, Hottenga JJ, Grotzinger AD, Gustavson DE, Jennings MV, Anokhin A, Dick DM, Edenberg HJ, Kramer JR, Lai D, Meyers JL, Pandey AK, Paige Harden K, Nivard MG, de Geus EJC, Boomsma DI, Agrawal A, Davis LK, Clarke TK, Palmer AA, Sanchez-Roige S. Item-Level Genome-Wide Association Study of the Alcohol Use Disorders Identification Test in Three Population-Based Cohorts. Am J Psychiatry 2022; 179:58-70. [PMID: 33985350 PMCID: PMC9272895 DOI: 10.1176/appi.ajp.2020.20091390] [Citation(s) in RCA: 52] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
OBJECTIVE Genome-wide association studies (GWASs) of the Alcohol Use Disorders Identification Test (AUDIT), a 10-item screen for alcohol use disorder (AUD), have elucidated novel loci for alcohol consumption and misuse. However, these studies also revealed that GWASs can be influenced by numerous biases (e.g., measurement error, selection bias), which may have led to inconsistent genetic correlations between alcohol involvement and AUD, as well as paradoxically negative genetic correlations between alcohol involvement and psychiatric disorders and/or medical conditions. The authors used genomic structural equation modeling to elucidate the genetics of alcohol consumption and problematic consequences of alcohol use as measured by AUDIT. METHODS To explore these unexpected differences in genetic correlations, the authors conducted the first item-level and the largest GWAS of AUDIT items (N=160,824) and applied a multivariate framework to mitigate previous biases. RESULTS The authors identified novel patterns of similarity (and dissimilarity) among the AUDIT items and found evidence of a correlated two-factor structure at the genetic level ("consumption" and "problems," rg=0.80). Moreover, by applying empirically derived weights to each of the AUDIT items, the authors constructed an aggregate measure of alcohol consumption that was strongly associated with alcohol dependence (rg=0.67), moderately associated with several other psychiatric disorders, and no longer positively associated with health and positive socioeconomic outcomes. Lastly, by conducting polygenic analyses in three independent cohorts that differed in their ascertainment and prevalence of AUD, the authors identified novel genetic associations between alcohol consumption, alcohol misuse, and health. CONCLUSIONS This work further emphasizes the value of AUDIT for both clinical and genetic studies of AUD and the importance of using multivariate methods to study genetic associations that are more closely related to AUD.
Collapse
Affiliation(s)
- Travis T Mallard
- Department of Psychology, University of Texas at Austin, Austin, TX, 78712
| | - Jeanne E Savage
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Netherlands, 1081HV
| | - Emma C Johnson
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO 63110
| | - Yuye Huang
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093
| | - Alexis C Edwards
- Virginia Institute for Psychiatric and Behavioral Genetics, Richmond, VA 23298
| | - Jouke J Hottenga
- Dept of Biological Psychology & EMGO+ Institute for Health and Care Research, Vrije Universiteit Amsterdam, Amsterdam, NL
| | | | - Daniel E Gustavson
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN 37232
| | - Mariela V Jennings
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093
| | - Andrey Anokhin
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO 63110
| | - Danielle M Dick
- Department of Psychology, Virginia Commonwealth University, Richmond, VA 23220
| | - Howard J Edenberg
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN 46202
| | - John R Kramer
- Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa City, IA 52242
| | - Dongbing Lai
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 4622
| | - Jacquelyn L Meyers
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY 11203
| | - Ashwini K Pandey
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY 11203
| | | | - Michel G Nivard
- Dept of Biological Psychology & EMGO+ Institute for Health and Care Research, Vrije Universiteit Amsterdam, Amsterdam, NL
| | - Eco JC de Geus
- Dept of Biological Psychology & EMGO+ Institute for Health and Care Research, Vrije Universiteit Amsterdam, Amsterdam, NL
| | - Dorret I Boomsma
- Dept of Biological Psychology & EMGO+ Institute for Health and Care Research, Vrije Universiteit Amsterdam, Amsterdam, NL
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO 63110
| | - Lea K Davis
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN 37232
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Toni-Kim Clarke
- Division of Psychiatry, University of Edinburgh, Scotland, UK, EH8 9YL
| | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA 92093
| | - Sandra Sanchez-Roige
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN 37232
| |
Collapse
|
36
|
Plawecki MH, Boes J, Wetherill L, Kosobud AEK, Stangl BL, Ramchandani VA, Zimmermann US, Nurnberger JI, Schuckit M, Edenberg HJ, Pandey G, Kamarajan C, Porjesz B, Foroud T, O'Connor S. Binge and high-intensity drinking-Associations with intravenous alcohol self-administration and underlying risk factors. Addict Biol 2022; 27:e13228. [PMID: 36301209 PMCID: PMC9786574 DOI: 10.1111/adb.13228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 06/06/2022] [Accepted: 08/14/2022] [Indexed: 01/24/2023]
Abstract
Some styles of alcohol consumption are riskier than others. How the level and rate of alcohol exposure contribute to the increased risk of alcohol use disorder is unclear, but likely depends on the alcohol concentration time course. We hypothesized that the brain is sensitive to the alcohol concentration rate of change and that people at greater risk would self-administer faster. We developed a novel intravenous alcohol self-administration paradigm to allow participants direct and reproducible control over how quickly their breath alcohol concentration changes. We used drinking intensity and the density of biological family history of alcohol dependence as proxies for risk. Thirty-five alcohol drinking participants aged 21-28 years provided analytical data from a single, intravenous alcohol self-administration session using our computer-assisted alcohol infusion system rate control paradigm. A shorter time to reach 80 mg/dl was associated with increasing multiples of the binge drinking definition (p = 0.004), which was in turn related to higher density of family history of alcoholism (FHD, p = 0.04). Rate-dependent changes in subjective response (intoxication and stimulation) were also associated with FHD (each p = 0.001). Subsequently, given the limited sample size and FHD range, associations between multiples of the binge drinking definition and FHD were replicated and extended in analyses of the Collaborative Study on the Genetics of Alcoholism database. The rate control paradigm models binge and high-intensity drinking in the laboratory and provides a novel way to examine the relationship between the pharmacokinetics and pharmacodynamics of alcohol and potentially the risk for the development of alcohol use disorders.
Collapse
Affiliation(s)
- Martin H. Plawecki
- Department of PsychiatryIndiana University School of MedicineIndianapolisIndianaUSA
| | - Julian Boes
- Department of Medical and Molecular GeneticsIndiana University School of MedicineIndianapolisIndianaUSA
| | - Leah Wetherill
- Department of Medical and Molecular GeneticsIndiana University School of MedicineIndianapolisIndianaUSA
| | - Ann E. K. Kosobud
- Department of NeurologyIndiana University School of MedicineIndianapolisIndianaUSA
| | - Bethany L. Stangl
- Human Psychopharmacology Laboratory, Division of Intramural Clinical and Biological ResearchNIAAABethesdaMarylandUSA
| | - Vijay A. Ramchandani
- Human Psychopharmacology Laboratory, Division of Intramural Clinical and Biological ResearchNIAAABethesdaMarylandUSA
| | - Ulrich S. Zimmermann
- Department of Psychiatry and PsychotherapyUniversity Hospital Carl Gustav Carus of the Technische Universität DresdenDresdenGermany,Department of Addiction Medicine and Psychotherapykbo Isar‐Amper‐Klinikum Haar/MunichMunichGermany
| | - John I. Nurnberger
- Department of PsychiatryIndiana University School of MedicineIndianapolisIndianaUSA
| | - Marc Schuckit
- Department of PsychiatryUniversity of California San DiegoSan DiegoCaliforniaUSA
| | - Howard J. Edenberg
- Department of Medical and Molecular GeneticsIndiana University School of MedicineIndianapolisIndianaUSA,Department of Biochemistry and Molecular BiologyIndiana University School of MedicineIndianapolisIndianaUSA
| | - Gayathri Pandey
- Henri Begleiter Neurodynamics LaboratoryState University of New York Downstate Health Sciences UniversityBrooklynNew YorkUSA
| | - Chella Kamarajan
- Henri Begleiter Neurodynamics LaboratoryState University of New York Downstate Health Sciences UniversityBrooklynNew YorkUSA
| | - Bernice Porjesz
- Henri Begleiter Neurodynamics LaboratoryState University of New York Downstate Health Sciences UniversityBrooklynNew YorkUSA
| | - Tatiana Foroud
- Department of Medical and Molecular GeneticsIndiana University School of MedicineIndianapolisIndianaUSA
| | - Sean O'Connor
- Department of PsychiatryIndiana University School of MedicineIndianapolisIndianaUSA
| |
Collapse
|
37
|
Bowen MT, George O, Muskiewicz DE, Hall FS. FACTORS CONTRIBUTING TO THE ESCALATION OF ALCOHOL CONSUMPTION. Neurosci Biobehav Rev 2022; 132:730-756. [PMID: 34839930 PMCID: PMC8892842 DOI: 10.1016/j.neubiorev.2021.11.017] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Revised: 11/05/2021] [Accepted: 11/12/2021] [Indexed: 01/03/2023]
Abstract
Understanding factors that contribute to the escalation of alcohol consumption is key to understanding how an individual transitions from non/social drinking to AUD and to providing better treatment. In this review, we discuss how the way ethanol is consumed as well as individual and environmental factors contribute to the escalation of ethanol consumption from intermittent low levels to consistently high levels. Moreover, we discuss how these factors are modelled in animals. It is clear a vast array of complex, interacting factors influence changes in alcohol consumption. Some of these factors act early in the acquisition of ethanol consumption and initial escalation, while others contribute to escalation of ethanol consumption at a later stage and are involved in the development of alcohol dependence. There is considerable need for more studies examining escalation associated with the formation of dependence and other hallmark features of AUD, especially studies examining mechanisms, as it is of considerable relevance to understanding and treating AUD.
Collapse
Affiliation(s)
- Michael T. Bowen
- The University of Sydney, Brain and Mind Centre, Sydney, NSW, 2050, Australia,The University of Sydney, Faculty of Science, School of Psychology, Sydney, NSW, 2006, Australia,Corresponding Author: Michael T. Bowen, Brain and Mind Centre, The University of Sydney, 94 Mallett Street, Camperdown, Sydney, NSW, 2050, Australia,
| | - Olivier George
- Department of Psychology, University of California, San Diego, School of Medicine, La Jolla, CA, 92093, USA
| | - Dawn E. Muskiewicz
- Department of Pharmacology & Experimental Therapeutics, College of Pharmacology and Pharmacological Science, University of Toledo, OH, USA
| | - F. Scott Hall
- Department of Pharmacology & Experimental Therapeutics, College of Pharmacology and Pharmacological Science, University of Toledo, OH, USA
| |
Collapse
|
38
|
High Polygenic Risk Scores Are Associated With Early Age of Onset of Alcohol Use Disorder in Adolescents and Young Adults at Risk. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2021; 2:379-388. [DOI: 10.1016/j.bpsgos.2021.10.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 09/30/2021] [Accepted: 10/01/2021] [Indexed: 11/22/2022] Open
|
39
|
Abstract
Substance use disorders (SUDs) are conditions in which the use of legal or illegal substances, such as nicotine, alcohol or opioids, results in clinical and functional impairment. SUDs and, more generally, substance use are genetically complex traits that are enormously costly on an individual and societal basis. The past few years have seen remarkable progress in our understanding of the genetics, and therefore the biology, of substance use and abuse. Various studies - including of well-defined phenotypes in deeply phenotyped samples, as well as broadly defined phenotypes in meta-analysis and biobank samples - have revealed multiple risk loci for these common traits. A key emerging insight from this work establishes a biological and genetic distinction between quantity and/or frequency measures of substance use (which may involve low levels of use without dependence), versus symptoms related to physical dependence.
Collapse
|
40
|
Dao C, Zhou H, Small A, Gordon KS, Li B, Kember RL, Ye Y, Gelernter J, Xu K, Kranzler HR, Zhao H, Justice AC. The impact of removing former drinkers from genome-wide association studies of AUDIT-C. Addiction 2021; 116:3044-3054. [PMID: 33861876 PMCID: PMC9377185 DOI: 10.1111/add.15511] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Revised: 11/27/2020] [Accepted: 03/24/2021] [Indexed: 11/30/2022]
Abstract
BACKGROUND AND AIMS The Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) questionnaire screens for harmful drinking using a 12-month timeframe. A score of 0 is assigned to individuals who report abstaining from alcohol in the past year. However, many middle-age individuals reporting current abstinence are former drinkers (FDs). Because FDs may be more genetically prone to harmful alcohol use than lifelong abstainers (LAs) and are often combined with LAs, we evaluated the impact of differentiating them on the identification of genetic association. DESIGN AND SETTING The United Kingdom Biobank (UKBB) includes AUDIT-C and alcohol drinker status. PARTICIPANTS 131 510 Europeans, including 5135 FDs. MEASUREMENTS We compared three genome-wide association (GWAS) analyses to explore the effects of removing FDs: the full AUDIT-C data, AUDIT-C data without FDs, and data from a random sample numerically matched to the data without FDs. Because prior studies show a consistent association of the ADH1B polymorphism rs1229984 with both alcohol consumption and alcohol use disorder, we compared allele frequencies for rs1229984 stratified by AUDIT-C value and FD versus LA status. Additionally, we calculated polygenic risk scores (PRS) of related diseases. FINDINGS The rs1229984 allele frequencies among FDs were numerically comparable to those with high AUDIT-C scores and very different from those of LAs. Removing FDs from GWAS yielded a stronger association with rs1229984 (P value after removal: 1.9 × 10-70 vs 1.7 × 10-65 and 2.5 × 10-62 ), more statistically significant single nucleotide polymorphisms (SNPs) (after removal: 11 vs 9 and 8), and genomic loci (after removal: 11 vs 9 and 7). Additional independent SNPs were identified after removal of FDs: rs2817866 (PTGER3), rs7105867 (ANO3), and rs17601612 (DRD2). For PRS of alcohol use disorder and major depressive disorder, there are statistically significant differences between FDs and LAs. CONCLUSIONS Differentiating between former drinkers and lifelong abstainers can improve Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) genome-wide association results.
Collapse
Affiliation(s)
- Cecilia Dao
- Yale University School of Public Health, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Hang Zhou
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
- Yale University School of Medicine, New Haven, CT, USA
| | - Aeron Small
- Yale University School of Medicine, New Haven, CT, USA
| | - Kirsha S. Gordon
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
- Yale University School of Medicine, New Haven, CT, USA
| | - Boyang Li
- Yale University School of Public Health, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Rachel L. Kember
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
| | - Yixuan Ye
- Yale University School of Public Health, New Haven, CT, USA
| | - Joel Gelernter
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
- Yale University School of Medicine, New Haven, CT, USA
| | - Ke Xu
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
- Yale University School of Medicine, New Haven, CT, USA
| | - Henry R. Kranzler
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
| | - Hongyu Zhao
- Yale University School of Public Health, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
- Yale University School of Medicine, New Haven, CT, USA
| | - Amy C. Justice
- Yale University School of Public Health, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
- Yale University School of Medicine, New Haven, CT, USA
| |
Collapse
|
41
|
Ding J, Tu Z, Chen H, Liu Z. Identifying modifiable risk factors of lung cancer: Indications from Mendelian randomization. PLoS One 2021; 16:e0258498. [PMID: 34662362 PMCID: PMC8523078 DOI: 10.1371/journal.pone.0258498] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Accepted: 09/28/2021] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Lung cancer is the major cause of mortality in tumor patients. While its incidence rate has recently declined, it is still far from satisfactory and its potential modifiable risk factors should be explored. METHODS We performed a two-sample Mendelian randomization (MR) study to investigate the causal relationship between potentially modifiable risk factors (namely smoking behavior, alcohol intake, anthropometric traits, blood pressure, lipidemic traits, glycemic traits, and fasting insulin) and lung cancer. Besides, a bi-directional MR analysis was carried out to disentangle the complex relationship between different risk factors. Inverse-variance weighted (IVW) was utilized to combine the estimation for each SNP. Cochrane's Q value was used to evaluate heterogeneity and two methods, including MR-Egger intercept and MR-PRESSO, were adopted to detect horizontal pleiotropy. RESULTS Three kinds of smoking behavior were all causally associated with lung cancer. Overall, smokers were more likely to suffer from lung cancer compared with non-smokers (OR = 2.58 [1.95, 3.40], p-value = 2.07 x 10-11), and quitting smoking could reduce the risk (OR = 4.29[2.60, 7.07], p-value = 1.23 x 10-8). Furthermore, we found a dose-response relationship between the number of cigarettes and lung cancer (OR = 6.10 [5.35, 6.96], p-value = 4.43x10-161). Lower HDL cholesterol could marginally increase the risk of lung cancer, but become insignificant after Bonferroni correction (OR = 0.82 [0.68, 1.00], p-value = 0.045). In addition, we noted no direct causal relationship between other risk factors and lung cancer. Neither heterogeneity nor pleiotropy was observed in this study. However, when treating the smoking behavior as the outcome, we found the increased BMI could elevate the number of cigarettes per day (beta = 0.139[0.104, 0.175], p-value = 1.99x10-14) and a similar effect was observed for the waist circumference and hip circumference. Additionally, the elevation of SBP could also marginally increase the number of cigarettes per day (beta = 0.001 [0.0002, 0.002], p-value = 0.018). CONCLUSION Smoking behavior might be the most direct and effective modifiable way to reduce the risk of lung cancer. Meanwhile, smoking behavior can be affected by other risk factors, especially obesity.
Collapse
Affiliation(s)
- Jie Ding
- Cancer Center, The Affiliated Changzhou No.2 People’s Hospital of Nanjing Medical University, Changzhou, Jiangsu Province, China
| | - Zhenxing Tu
- Department of Hand Surgery, The Second Hospital of Tangshan, Tangshan, Hebei Province, China
| | - Hongquan Chen
- Department of Bone Surgery, Affiliated Hospital of North China University of Science and Technology, Tangshan, Hebei Province, China
| | - Zhiguang Liu
- Department of Pulmonary and Critical Care Medicine, Affiliated Changzhou Second People’s Hospital affiliated to Nanjing Medical University, Changzhou, Jiangsu Province, China
| |
Collapse
|
42
|
Exploring the Role of Alcohol Metabolizing Genotypes in a 12-Week Clinical Trial of Naltrexone for Alcohol Use Disorder. Biomolecules 2021; 11:biom11101495. [PMID: 34680127 PMCID: PMC8533258 DOI: 10.3390/biom11101495] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Revised: 09/26/2021] [Accepted: 10/03/2021] [Indexed: 11/16/2022] Open
Abstract
Background: The efficacy of naltrexone in the treatment of alcohol use disorder (AUD) has been associated with a set of variables not directly related with the expression of opioid receptors. All the variables have been found to be highly associated with AUD itself or more severe clinical levels of AUD. Objectives: Given the high association between alcohol metabolizing enzymes (AME) and the outcome of AUD, the present study aims to investigate the role of AME genotype variants in the treatment of AUD with naltrexone. Methods: We carried out a 12-week longitudinal clinical trial based on the treatment of AUD patients with naltrexone (N = 101), stratified by different alcohol metabolization genotypes. Genotyping was performed after the inclusion of the patients in the study, based on the individual presence of single nucleotide polymorphisms (SNPs) in the ADH (alcohol dehydrogenase)1B (ADH1B*2 and ADH1B*3), ADH1C (ADHC*1) and ALDH (aldehyde dehydrogenase) 2 (ALDH2*2) genes. The outcome of alcohol use has been monitored employing the timeline follow-back during the treatment. Results: The ADH1C*1 (Ile350Val, rs698) and ALDH2*2 (Glu504Lys, rs671) polymorphisms were associated with a better response to naltrexone treatment, whereas the ADH1B*3 (Arg370Cys, rs2066702) allelic variant showed a negative outcome. Conclusions: The present study explores a genomic setting for the treatment of AUD with naltrexone. According to our findings, the association between ADH1C*1 and ALDH2*2 variants and better outcomes suggests a successful treatment, whereas the ADH1B*3 mutated allele might lead to an unsuccessful treatment. Further studies should be performed to investigate the relationship between alcohol metabolizing genotypes, the family history of alcohol use disorders and the effect of naltrexone on the outcomes. Genotyping may be a valuable tool for precision-medicine and individualized approach, especially in the context of alcohol use disorders. The small number of subjects was the main limitation of the present study.
Collapse
|
43
|
Abstract
Substance use disorders (SUDs) are prevalent and result in an array of negative consequences. They are influenced by genetic factors (h2 = ~50%). Recent years have brought substantial progress in our understanding of the genetic etiology of SUDs and related traits. The present review covers the current state of the field for SUD genetics, including the epidemiology and genetic epidemiology of SUDs, findings from the first-generation of SUD genome-wide association studies (GWAS), cautions about translating GWAS findings to clinical settings, and suggested prioritizations for the next wave of SUD genetics efforts. Recent advances in SUD genetics have been facilitated by the assembly of large GWAS samples, and the development of state-of-the-art methods modeling the aggregate effect of genome-wide variation. These advances have confirmed that SUDs are highly polygenic with many variants across the genome conferring risk, the vast majority of which are of small effect. Downstream analyses have enabled finer resolution of the genetic architecture of SUDs and revealed insights into their genetic relationship with other psychiatric disorders. Recent efforts have also prioritized a closer examination of GWAS findings that have suggested non-uniform genetic influences across measures of substance use (e.g. consumption) and problematic use (e.g. SUD). Additional highlights from recent SUD GWAS include the robust confirmation of loci in alcohol metabolizing genes (e.g. ADH1B and ALDH2) affecting alcohol-related traits, and loci within the CHRNA5-CHRNA3-CHRNB4 gene cluster influencing nicotine-related traits. Similar successes are expected for cannabis, opioid, and cocaine use disorders as sample sizes approach those assembled for alcohol and nicotine.
Collapse
Affiliation(s)
- Joseph D. Deak
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Emma C. Johnson
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| |
Collapse
|
44
|
Ho MF, Zhang C, Zhang L, Wei L, Zhou Y, Moon I, Geske JR, Choi DS, Biernacka J, Frye M, Wen Z, Karpyak VM, Li H, Weinshilboum R. TSPAN5 influences serotonin and kynurenine: pharmacogenomic mechanisms related to alcohol use disorder and acamprosate treatment response. Mol Psychiatry 2021; 26:3122-3133. [PMID: 32753686 PMCID: PMC7858703 DOI: 10.1038/s41380-020-0855-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/01/2020] [Revised: 07/16/2020] [Accepted: 07/23/2020] [Indexed: 01/13/2023]
Abstract
We previously reported that SNPs near TSPAN5 were associated with plasma serotonin (5-HT) concentrations which were themselves associated with selective serotonin reuptake inhibitor treatment outcomes in patients with major depressive disorder (MDD). TSPAN5 SNPs were also associated with alcohol consumption and alcohol use disorder (AUD) risk. The present study was designed to explore the biological function of TSPAN5 with a focus on 5-HT and kynurenine concentrations in the tryptophan pathway. Ethanol treatment resulted in decreased 5-HT concentrations in human induced pluripotent stem cell (iPSC)-derived neuron culture media, and the downregulation of gene expression of TSPAN5, DDC, MAOA, MAOB, TPH1, and TPH2 in those cells. Strikingly, similar observations were made when the cells were treated with acamprosate-an FDA approved drug for AUD therapy. These results were replicated in iPSC-derived astrocytes. Furthermore, TSPAN5 interacted physically with proteins related to clathrin and other vesicle-related proteins, raising the possibility that TSPAN5 might play a role in vesicular function in addition to regulating expression of genes associated with 5-HT biosynthesis and metabolism. Downregulation of TSPAN5 expression by ethanol or acamprosate treatment was also associated with decreased concentrations of kynurenine, a major metabolite of tryptophan that plays a role in neuroinflammation. Knockdown of TSPAN5 also influenced the expression of genes associated with interferon signaling pathways. Finally, we determined that TSPAN5 SNPs were associated with acamprosate treatment outcomes in AUD patients. In conclusion, TSPAN5 can modulate the concentrations of 5-HT and kynurenine. Our data also highlight a potentially novel pharmacogenomic mechanism related to response to acamprosate.
Collapse
Affiliation(s)
- Ming-Fen Ho
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Cheng Zhang
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Lingxin Zhang
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Lixuan Wei
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Ying Zhou
- Department of Cell Biology, Emory University, 615 Michael Street, Atlanta, GA, 30322, USA
| | - Irene Moon
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Jennifer R Geske
- Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Doo-Sup Choi
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Joanna Biernacka
- Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Mark Frye
- Department of Psychiatry and Psychology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Zhexing Wen
- Department of Cell Biology, Emory University, 615 Michael Street, Atlanta, GA, 30322, USA
| | - Victor M Karpyak
- Department of Psychiatry and Psychology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Hu Li
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Richard Weinshilboum
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
| |
Collapse
|
45
|
Ressler KJ. Translating Across Circuits and Genetics Toward Progress in Fear- and Anxiety-Related Disorders. FOCUS (AMERICAN PSYCHIATRIC PUBLISHING) 2021; 19:247-255. [PMID: 34690590 PMCID: PMC8475910 DOI: 10.1176/appi.focus.19205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 01/15/2020] [Indexed: 06/13/2023]
Abstract
(Reprinted with permission from Am J Psychiatry 2020; 177:214-222).
Collapse
|
46
|
Iob E, Schoeler T, Cecil CM, Walton E, McQuillin A, Pingault J. Identifying risk factors involved in the common versus specific liabilities to substance use: A genetically informed approach. Addict Biol 2021; 26:e12944. [PMID: 32705754 PMCID: PMC8427469 DOI: 10.1111/adb.12944] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Revised: 06/09/2020] [Accepted: 07/08/2020] [Indexed: 12/15/2022]
Abstract
Individuals most often use several rather than one substance among alcohol, cigarettes or cannabis. This widespread co-occurring use of multiple substances is thought to stem from a common liability that is partly genetic in origin. Genetic risk may indirectly contribute to a common liability to substance use through genetically influenced mental health vulnerabilities and individual traits. To test this possibility, we used polygenic scores indexing mental health and individual traits and examined their association with the common versus specific liabilities to substance use. We used data from the Avon Longitudinal Study of Parents and Children (N = 4218) and applied trait-state-occasion models to delineate the common and substance-specific factors based on four classes of substances (alcohol, cigarettes, cannabis and other illicit substances) assessed over time (ages 17, 20 and 22). We generated 18 polygenic scores indexing genetically influenced mental health vulnerabilities and individual traits. In multivariable regression, we then tested the independent contribution of selected polygenic scores to the common and substance-specific factors. Our results implicated several genetically influenced traits and vulnerabilities in the common liability to substance use, most notably risk taking (bstandardised = 0.14; 95% confidence interval [CI] [0.10, 0.17]), followed by extraversion (bstandardised = -0.10; 95% CI [-0.13, -0.06]), and schizophrenia risk (bstandardised = 0.06; 95% CI [0.02, 0.09]). Educational attainment (EA) and body mass index (BMI) had opposite effects on substance-specific liabilities such as cigarette use (bstandardised-EA = -0.15; 95% CI [-0.19, -0.12]; bstandardised-BMI = 0.05; 95% CI [0.02, 0.09]) and alcohol use (bstandardised-EA = 0.07; 95% CI [0.03, 0.11]; bstandardised-BMI = -0.06; 95% CI [-0.10, -0.02]). These findings point towards largely distinct sets of genetic influences on the common versus specific liabilities.
Collapse
Affiliation(s)
- Eleonora Iob
- Department of Behavioral Science and HealthUniversity College LondonLondonUK
| | - Tabea Schoeler
- Department of Clinical, Educational and Health Psychology, Division of Psychology and Language SciencesUniversity College LondonLondonUK
| | - Charlotte M. Cecil
- Department of Child and Adolescent PsychiatryErasmus University Medical CenterRotterdamThe Netherlands
- Department of EpidemiologyErasmus University Medical CenterRotterdamThe Netherlands
| | - Esther Walton
- MRC Integrative Epidemiology Unit, Bristol Medical School, Population Health SciencesUniversity of BristolBristolUK
- Department of PsychologyUniversity of BathBathUK
| | | | - Jean‐Baptiste Pingault
- Department of Clinical, Educational and Health Psychology, Division of Psychology and Language SciencesUniversity College LondonLondonUK
- Social, Genetic and Developmental Psychiatry CentreKing's College LondonLondonUK
| |
Collapse
|
47
|
Burmeister M, Sen S. Genetic interactions with stressful environments in depression and addiction. BJPSYCH ADVANCES 2021; 27:153-157. [DOI: 10.1192/bja.2021.21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
SUMMARYStress is the most important proximal precipitant of depression, yet most large genome-wide association studies (GWAS) do not include stress as a variable. Here, we review how gene × environment (G × E) interaction might impede the discovery of genetic factors, discuss two examples of G × E interaction in depression and addiction, studies incorporating high-stress environments, as well as upcoming waves of genome-wide environment interaction studies (GWEIS). We discuss recent studies which have shown that genetic distributions can be affected by social factors such as migrations and socioeconomic background. These distinctions are not just academic but have practical consequences. Owing to interaction with the environment, genetic predispositions to depression should not be viewed as unmodifiable destiny. Patients may genetically differ not just in their response to drugs, as in the now well-recognised field of pharmacogenetics, but also in how they react to stressful environments and how they are affected by behavioural therapies.
Collapse
|
48
|
Hade AC, Philips MA, Reimann E, Jagomäe T, Eskla KL, Traks T, Prans E, Kõks S, Vasar E, Väli M. Chronic Alcohol Use Induces Molecular Genetic Changes in the Dorsomedial Thalamus of People with Alcohol-Related Disorders. Brain Sci 2021; 11:435. [PMID: 33805312 PMCID: PMC8066746 DOI: 10.3390/brainsci11040435] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Revised: 03/25/2021] [Accepted: 03/26/2021] [Indexed: 01/12/2023] Open
Abstract
The Mediodorsal (MD) thalamus that represents a fundamental subcortical relay has been underrepresented in the studies focusing on the molecular changes in the brains of subjects with alcohol use disorder (AUD). In the current study, MD thalamic regions from AUD subjects and controls were analyzed with Affymetrix Clariom S human microarray. Long-term alcohol use induced a significant (FDR ≤ 0.05) upregulation of 2802 transcripts and downregulation of 1893 genes in the MD thalamus of AUD subjects. A significant upregulation of GRIN1 (glutamate receptor NMDA type 1) and FTO (alpha-ketoglutarate dependent dioxygenase) was confirmed in western blot analysis. Immunohistochemical staining revealed similar heterogenous distribution of GRIN1 in the thalamic nuclei of both AUD and control subjects. The most prevalent functional categories of upregulated genes were related to glutamatergic and GABAergic neurotransmission, cellular metabolism, and neurodevelopment. The prevalent gene cluster among down-regulated genes was immune system mediators. Forty-two differentially expressed genes, including FTO, ADH1B, DRD2, CADM2, TCF4, GCKR, DPP6, MAPT and CHRH1, have been shown to have strong associations (FDR p < 10-8) with AUD or/and alcohol use phenotypes in recent GWA studies. Despite a small number of subjects, we were able to detect robust molecular changes in the mediodorsal thalamus caused by alcohol emphasizing the importance of deeper brain structures such as diencephalon, in the development of AUD-related dysregulation of neurocircuitry.
Collapse
Affiliation(s)
- Andreas-Christian Hade
- Department of Pathological Anatomy and Forensic Medicine, University of Tartu, 19 Ravila Street, 50411 Tartu, Estonia; (A.-C.H.); (M.V.)
- Forensic Medical Examination Department, Estonian Forensic Science Institute, 30 Tervise Street, 13419 Tallinn, Estonia
| | - Mari-Anne Philips
- Department of Physiology, Institute of Biomedicine and Translational Medicine, University of Tartu, 50411 Tartu, Estonia; (T.J.); (K.-L.E.); (E.V.)
- Centre of Excellence in Genomics and Translational Medicine, University of Tartu, 50411 Tartu, Estonia
| | - Ene Reimann
- Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010 Tartu, Estonia;
| | - Toomas Jagomäe
- Department of Physiology, Institute of Biomedicine and Translational Medicine, University of Tartu, 50411 Tartu, Estonia; (T.J.); (K.-L.E.); (E.V.)
- Centre of Excellence in Genomics and Translational Medicine, University of Tartu, 50411 Tartu, Estonia
| | - Kattri-Liis Eskla
- Department of Physiology, Institute of Biomedicine and Translational Medicine, University of Tartu, 50411 Tartu, Estonia; (T.J.); (K.-L.E.); (E.V.)
- Centre of Excellence in Genomics and Translational Medicine, University of Tartu, 50411 Tartu, Estonia
| | - Tanel Traks
- Department of Dermatology and Venerology, Institute of Clinical Medicine, University of Tartu, 51010 Tartu, Estonia;
| | - Ele Prans
- Department of Anaesthesiology and Intensive Care, Tartu University Hospital, 50406 Tartu, Estonia;
| | - Sulev Kõks
- Perron Institute for Neurological and Translational Science, Perth, WA 6009, Australia;
- Centre for Molecular Medicine and Innovative Therapeutics, Murdoch University, Perth, WA 6150, Australia
| | - Eero Vasar
- Department of Physiology, Institute of Biomedicine and Translational Medicine, University of Tartu, 50411 Tartu, Estonia; (T.J.); (K.-L.E.); (E.V.)
- Centre of Excellence in Genomics and Translational Medicine, University of Tartu, 50411 Tartu, Estonia
| | - Marika Väli
- Department of Pathological Anatomy and Forensic Medicine, University of Tartu, 19 Ravila Street, 50411 Tartu, Estonia; (A.-C.H.); (M.V.)
- Forensic Medical Examination Department, Estonian Forensic Science Institute, 30 Tervise Street, 13419 Tallinn, Estonia
| |
Collapse
|
49
|
Polimanti R, Levey DF, Pathak GA, Wendt FR, Nunez YZ, Ursano RJ, Kessler RC, Kranzler HR, Stein MB, Gelernter J. Multi-environment gene interactions linked to the interplay between polysubstance dependence and suicidality. Transl Psychiatry 2021; 11:34. [PMID: 33431810 PMCID: PMC7801457 DOI: 10.1038/s41398-020-01153-1] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Revised: 11/27/2020] [Accepted: 12/03/2020] [Indexed: 12/19/2022] Open
Abstract
Substance dependence diagnoses (SDs) are important risk factors for suicidality. We investigated the associations of multiple SDs with different suicidality outcomes, testing how genetic background moderates these associations. The Yale-Penn cohort (N = 15,557) was recruited to investigate the genetics of SDs. The Army STARRS (Study to Assess Risk and Resilience in Servicemembers) cohort (N = 11,236) was recruited to evaluate mental health risk and resilience among Army personnel. We applied multivariate logistic regression to investigate the associations of SDs with suicidality and, in the Yale-Penn cohort, we used the structured linear mixed model (StructLMM) to study multivariate gene-environment interactions. In Yale-Penn, lifetime polysubstance dependence was strongly associated with lifetime suicidality: having five SDs showed an association with suicidality, from odds ratio (OR) = 6.77 (95% confidence interval, CI = 5.74-7.99) for suicidal ideation (SI) to OR = 3.61 (95% CI = 2.7-4.86) for suicide attempt (SA). In Army STARRS, having multiple substance use disorders for alcohol and/or drugs was associated with increased suicidality ranging from OR = 2.88 (95% CI = 2.6-3.19) for SI to OR = 3.92 (95% CI = 3.19-4.81) for SA. In Yale-Penn, we identified multivariate gene-environment interactions (Bayes factors, BF > 0) of SI with respect to a gene cluster on chromosome 16 (LCAT, p = 1.82 × 10-7; TSNAXIP1, p = 2.13 × 10-7; CENPT, p = 2.32 × 10-7; PARD6A, p = 5.57 × 10-7) for opioid dependence (BF = 12.2), cocaine dependence (BF = 12.1), nicotine dependence (BF = 9.2), and polysubstance dependence (BF = 2.1). Comorbidity of multiple SDs is a significant associated with suicidality and heritability of suicidality is partially moderated by multivariate gene interactions.
Collapse
Affiliation(s)
- Renato Polimanti
- Department of Psychiatry, Yale School of Medicine, Yale University, West Haven, CT, USA. .,Veteran Affairs CT Healthcare System, West Haven, CT, USA.
| | - Daniel F. Levey
- grid.47100.320000000419368710Department of Psychiatry, Yale School of Medicine, Yale University, West Haven, CT USA ,Veteran Affairs CT Healthcare System, West Haven, CT USA
| | - Gita A. Pathak
- grid.47100.320000000419368710Department of Psychiatry, Yale School of Medicine, Yale University, West Haven, CT USA ,Veteran Affairs CT Healthcare System, West Haven, CT USA
| | - Frank R. Wendt
- grid.47100.320000000419368710Department of Psychiatry, Yale School of Medicine, Yale University, West Haven, CT USA ,Veteran Affairs CT Healthcare System, West Haven, CT USA
| | - Yaira Z. Nunez
- grid.47100.320000000419368710Department of Psychiatry, Yale School of Medicine, Yale University, West Haven, CT USA ,Veteran Affairs CT Healthcare System, West Haven, CT USA
| | - Robert J. Ursano
- grid.265436.00000 0001 0421 5525Center for the Study of Traumatic Stress, Department of Psychiatry, Uniformed Services University of the Health Sciences, Bethesda, MD USA
| | - Ronald C. Kessler
- grid.38142.3c000000041936754XDepartment of Health Care Policy, Harvard Medical School, Boston, MA USA
| | - Henry R. Kranzler
- grid.25879.310000 0004 1936 8972University of Pennsylvania Perelman School of Medicine, Philadelphia, PA USA ,grid.410355.60000 0004 0420 350XCrescenz Veterans Affairs Medical Center, Philadelphia, PA USA
| | - Murray B. Stein
- grid.266100.30000 0001 2107 4242Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA USA ,grid.410371.00000 0004 0419 2708Psychiatry Service, Veterans Affairs San Diego Healthcare System, San Diego, CA USA
| | - Joel Gelernter
- grid.47100.320000000419368710Department of Psychiatry, Yale School of Medicine, Yale University, West Haven, CT USA ,Veteran Affairs CT Healthcare System, West Haven, CT USA ,grid.47100.320000000419368710Departments of Genetics and Neuroscience, Yale University School of Medicine, New Haven, CT 06510 USA
| |
Collapse
|
50
|
Nguyen TTL, Liu D, Ho MF, Athreya AP, Weinshilboum R. Selective Serotonin Reuptake Inhibitor Pharmaco-Omics: Mechanisms and Prediction. Front Pharmacol 2021; 11:614048. [PMID: 33510640 PMCID: PMC7836019 DOI: 10.3389/fphar.2020.614048] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Accepted: 12/07/2020] [Indexed: 01/14/2023] Open
Abstract
Selective serotonin reuptake inhibitors (SSRIs) are a standard of care for the pharmacotherapy of patients suffering from Major Depressive Disorder (MDD). However, only one-half to two-thirds of MDD patients respond to SSRI therapy. Recently, a "multiple omics" research strategy was applied to identify genetic differences between patients who did and did not respond to SSRI therapy. As a first step, plasma metabolites were assayed using samples from the 803 patients in the PGRN-AMPS SSRI MDD trial. The metabolomics data were then used to "inform" genomics by performing a genome-wide association study (GWAS) for plasma concentrations of the metabolite most highly associated with clinical response, serotonin (5-HT). Two genome-wide or near genome-wide significant single nucleotide polymorphism (SNP) signals were identified, one that mapped near the TSPAN5 gene and another across the ERICH3 gene, both genes that are highly expressed in the brain. Knocking down TSPAN5 and ERICH3 resulted in decreased 5-HT concentrations in neuroblastoma cell culture media and decreased expression of enzymes involved in 5-HT biosynthesis and metabolism. Functional genomic studies demonstrated that ERICH3 was involved in clathrin-mediated vesicle formation and TSPAN5 was an ethanol-responsive gene that may be a marker for response to acamprosate pharmacotherapy of alcohol use disorder (AUD), a neuropsychiatric disorder highly co-morbid with MDD. In parallel studies, kynurenine was the plasma metabolite most highly associated with MDD symptom severity and application of a metabolomics-informed pharmacogenomics approach identified DEFB1 and AHR as genes associated with variation in plasma kynurenine levels. Both genes also contributed to kynurenine-related inflammatory pathways. Finally, a multiply replicated predictive algorithm for SSRI clinical response with a balanced predictive accuracy of 76% (compared with 56% for clinical data alone) was developed by including the SNPs in TSPAN5, ERICH3, DEFB1 and AHR. In summary, application of a multiple omics research strategy that used metabolomics to inform genomics, followed by functional genomic studies, identified novel genes that influenced monoamine biology and made it possible to develop a predictive algorithm for SSRI clinical outcomes in MDD. A similar pharmaco-omic research strategy might be broadly applicable for the study of other neuropsychiatric diseases and their drug therapy.
Collapse
Affiliation(s)
- Thanh Thanh L Nguyen
- Division of Clinical Pharmacology, Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, United States.,Graduate School of Biomedical Sciences, Mayo Clinic, Rochester, MN, United States
| | - Duan Liu
- Division of Clinical Pharmacology, Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, United States
| | - Ming-Fen Ho
- Division of Clinical Pharmacology, Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, United States
| | - Arjun P Athreya
- Division of Clinical Pharmacology, Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, United States
| | - Richard Weinshilboum
- Division of Clinical Pharmacology, Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, United States
| |
Collapse
|