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Weng Y, Kruschwitz J, Rueda-Delgado LM, Ruddy K, Boyle R, Franzen L, Serin E, Nweze T, Hanson J, Smyth A, Farnan T, Banaschewski T, Bokde ALW, Desrivières S, Flor H, Grigis A, Garavan H, Gowland P, Heinz A, Brühl R, Martinot JL, Paillère Martinot ML, Artiges E, McGrath J, Nees F, Orfanos DP, Paus T, Poustka L, Holz N, Fröhner JH, Smolka MN, Vaidya N, Schumann G, Walter H, Whelan R. A robust brain network for sustained attention from adolescence to adulthood that predicts later substance use. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.03.587900. [PMID: 38617224 PMCID: PMC11014614 DOI: 10.1101/2024.04.03.587900] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
Substance use, including cigarettes and cannabis, is associated with poorer sustained attention in late adolescence and early adulthood. Previous studies were predominantly cross-sectional or under-powered and could not indicate if impairment in sustained attention was a consequence of substance-use or a marker of the inclination to engage in such behaviour. This study explored the relationship between sustained attention and substance use across a longitudinal span from ages 14 to 23 in over 1,000 participants. Behaviours and brain connectivity associated with diminished sustained attention at age 14 predicted subsequent increases in cannabis and cigarette smoking, establishing sustained attention as a robust biomarker for vulnerability to substance use. Individual differences in network strength relevant to sustained attention were preserved across developmental stages and sustained attention networks generalized to participants in an external dataset. In summary, brain networks of sustained attention are robust, consistent, and able to predict aspects of later substance use.
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Affiliation(s)
- Yihe Weng
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Ireland
| | - Johann Kruschwitz
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
- Collaborative Research Centre (SFB 940) "Volition and Cognitive Control", Technische Universität Dresden, 01069, Dresden, Germany
| | - Laura M Rueda-Delgado
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Ireland
| | - Kathy Ruddy
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Ireland
- School of Psychology, Queens University Belfast, Belfast, Northern Ireland, UK
| | - Rory Boyle
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Ireland
| | - Luisa Franzen
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Ireland
- Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Emin Serin
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
- Charité -Universitätsmedizin Berlin, Einstein Center for Neurosciences Berlin, 10117, Berlin, Germany
- Bernstein Center for Computational Neuroscience, 10115, Berlin, Germany
| | | | - Jamie Hanson
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA; Learning Research & Development Center, University of Pittsburgh, Pittsburgh, PA, USA
| | - Alannah Smyth
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Ireland
| | - Tom Farnan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Ireland
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Sylvane Desrivières
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, SGDP Centre, King's College London, United Kingdom
| | - Herta Flor
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
- Department of Psychology, School of Social Sciences, University of Mannheim, 68131 Mannheim, Germany
| | - Antoine Grigis
- NeuroSpin, CEA, Université Paris-Saclay, F-91191 Gif-sur-Yvette, France
| | - Hugh Garavan
- Departments of Psychiatry and Psychology, University of Vermont, 05405 Burlington, Vermont, USA
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, United Kingdom
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Rüdiger Brühl
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U 1299 "Trajectoires développementales & psychiatrie", University Paris-Saclay, CNRS; Ecole Normale Supérieure Paris-Saclay, Centre Borelli; Gif-sur-Yvette, France
| | - Marie-Laure Paillère Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U 1299 "Trajectoires développementales & psychiatrie", University Paris-Saclay, CNRS; Ecole Normale Supérieure Paris-Saclay, Centre Borelli; Gif-sur-Yvette; and AP-HP. Sorbonne University, Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, Paris, France
| | - Eric Artiges
- Institut National de la Santé et de la Recherche Médicale, INSERM U 1299 "Trajectoires développementales & psychiatrie", University Paris-Saclay, CNRS; Ecole Normale Supérieure Paris-Saclay, Centre Borelli; Gif-sur-Yvette; and Psychiatry Department, EPS Barthélémy Durand, Etampes, France
| | - Jane McGrath
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
- Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig Holstein, Kiel University, Kiel, Germany
| | | | - Tomáš Paus
- Departments of Psychiatry and Neuroscience, Faculty of Medicine and Centre Hosptalier Universitaire Sainte-Justine, University of Montreal, Montreal, Quebec, Canada
- Departments of Psychiatry and Psychology, University of Toronto, Toronto, Ontario, Canada
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, von-Siebold-Str. 5, 37075, Göttingen, Germany
| | - Nathalie Holz
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
| | - Juliane H Fröhner
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Michael N Smolka
- Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Neuroscience, Charité Universitätsmedizin Berlin, Germany
| | - Nilakshi Vaidya
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute for Science and Technology of Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai, China
| | - Gunter Schumann
- Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Neuroscience, Charité Universitätsmedizin Berlin, Germany
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute for Science and Technology of Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai, China
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Ireland
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2
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Xia D, Han X, Zeng Y, Wang J, Xu K, Zhang T, Jiang Y, Chen X, Song H, Suo C. Disease trajectory of high neuroticism and the relevance to psychiatric disorders: A retro-prospective cohort study. Acta Psychiatr Scand 2024; 149:133-146. [PMID: 38057974 DOI: 10.1111/acps.13645] [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: 09/18/2023] [Revised: 11/06/2023] [Accepted: 11/23/2023] [Indexed: 12/08/2023]
Abstract
BACKGROUND Neuroticism is a psychological personality trait that has a significant impact on public health and is also a potential predisposing factor for adverse disease outcomes; however, comprehensive studies of the subsequently developed conditions are lacking. The starting point of disease trajectory in terms of genetic variation remains unclear. METHOD Our study included 344,609 adult participants from the UK Biobank cohort who were virtually followed up from January 1, 1997. Neuroticism levels were assessed using 12 items from the Eysenck Personality Questionnaire. We performed a phenome-wide association analysis of neuroticism and subsequent diseases. Binomial tests and logistic regression models were used to test the temporal directionality and association between disease pairs to construct disease trajectories. We also investigated the association between polygenic risk scores (PRSs) for five psychiatric traits and high neuroticism. RESULTS The risk for 59 diseases was significantly associated with high neuroticism. Depression, anxiety, irritable bowel syndrome, migraine, spondylosis, and sleep disorders were the most likely to develop, with hazard ratios of 6.13, 3.66, 2.28, 1.74, 1.74, and 1.71, respectively. The disease trajectory network revealed two major disease clusters: cardiometabolic and chronic inflammatory diseases. Medium/high genetic risk groups stratified by the PRSs of four psychiatric traits were associated with an elevated risk of high neuroticism. We further identified eight complete phenotypic trajectory clusters of medium or high genetic risk for psychotic, anxiety-, depression-, and stress-related disorders. CONCLUSION Neuroticism plays an important role in the development of somatic and mental disorders. The full picture of disease trajectories from the genetic risk of psychiatric traits and neuroticism in early life to a series of diseases later provides evidence for future research to explore the etiological mechanisms and precision management.
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Affiliation(s)
- Ding Xia
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai, China
- Ministry of Education Key Laboratory of Public Health Safety, Fudan University, Shanghai, China
| | - Xin Han
- Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China
- Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Yu Zeng
- Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China
- Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Jingru Wang
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai, China
- Ministry of Education Key Laboratory of Public Health Safety, Fudan University, Shanghai, China
| | - Kelin Xu
- Ministry of Education Key Laboratory of Public Health Safety, Fudan University, Shanghai, China
- Department of Biostatistics, School of Public Health, Shanghai, China
- Taizhou Institute of Health Sciences, Fudan University, Taizhou, China
| | - Tiejun Zhang
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai, China
- Ministry of Education Key Laboratory of Public Health Safety, Fudan University, Shanghai, China
- Taizhou Institute of Health Sciences, Fudan University, Taizhou, China
| | - Yanfeng Jiang
- Taizhou Institute of Health Sciences, Fudan University, Taizhou, China
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences, Fudan University, Shanghai, China
| | - Xingdong Chen
- Taizhou Institute of Health Sciences, Fudan University, Taizhou, China
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences, Fudan University, Shanghai, China
| | - Huan Song
- Mental Health Center and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China
- Med-X Center for Informatics, Sichuan University, Chengdu, China
- Center of Public Health Sciences, Faculty of Medicine, University of Iceland, Reykjavík, Iceland
| | - Chen Suo
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai, China
- Ministry of Education Key Laboratory of Public Health Safety, Fudan University, Shanghai, China
- Taizhou Institute of Health Sciences, Fudan University, Taizhou, China
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3
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Pan S, Kang H, Liu X, Li S, Yang P, Wu M, Yuan N, Lin S, Zheng Q, Jia P. COLOCdb: a comprehensive resource for multi-model colocalization of complex traits. Nucleic Acids Res 2024; 52:D871-D881. [PMID: 37941154 PMCID: PMC10767919 DOI: 10.1093/nar/gkad939] [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: 08/15/2023] [Revised: 10/01/2023] [Accepted: 10/12/2023] [Indexed: 11/10/2023] Open
Abstract
Large-scale genome-wide association studies (GWAS) have provided profound insights into complex traits and diseases. Yet, deciphering the fine-scale molecular mechanisms of how genetic variants manifest to cause the phenotypes remains a daunting task. Here, we present COLOCdb (https://ngdc.cncb.ac.cn/colocdb), a comprehensive genetic colocalization database by integrating more than 3000 GWAS summary statistics and 13 types of xQTL to date. By employing two representative approaches for the colocalization analysis, COLOCdb deposits results from three key components: (i) GWAS-xQTL, pair-wise colocalization between GWAS loci and different types of xQTL, (ii) GWAS-GWAS, pair-wise colocalization between the trait-associated genetic loci from GWASs and (iii) xQTL-xQTL, pair-wise colocalization between the genetic loci associated with molecular phenotypes in xQTLs. These results together represent the most comprehensive colocalization analysis, which also greatly expands the list of shared variants with genetic pleiotropy. We expect that COLOCdb can serve as a unique and useful resource in advancing the discovery of new biological mechanisms and benefit future functional studies.
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Affiliation(s)
- Siyu Pan
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Hongen Kang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Xinxuan Liu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Shuhua Li
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Peng Yang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Mingqiu Wu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Na Yuan
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Shiqi Lin
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Qiwen Zheng
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Peilin Jia
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100101, China
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4
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An U, Pazokitoroudi A, Alvarez M, Huang L, Bacanu S, Schork AJ, Kendler K, Pajukanta P, Flint J, Zaitlen N, Cai N, Dahl A, Sankararaman S. Deep learning-based phenotype imputation on population-scale biobank data increases genetic discoveries. Nat Genet 2023; 55:2269-2276. [PMID: 37985819 PMCID: PMC10703681 DOI: 10.1038/s41588-023-01558-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 10/04/2023] [Indexed: 11/22/2023]
Abstract
Biobanks that collect deep phenotypic and genomic data across many individuals have emerged as a key resource in human genetics. However, phenotypes in biobanks are often missing across many individuals, limiting their utility. We propose AutoComplete, a deep learning-based imputation method to impute or 'fill-in' missing phenotypes in population-scale biobank datasets. When applied to collections of phenotypes measured across ~300,000 individuals from the UK Biobank, AutoComplete substantially improved imputation accuracy over existing methods. On three traits with notable amounts of missingness, we show that AutoComplete yields imputed phenotypes that are genetically similar to the originally observed phenotypes while increasing the effective sample size by about twofold on average. Further, genome-wide association analyses on the resulting imputed phenotypes led to a substantial increase in the number of associated loci. Our results demonstrate the utility of deep learning-based phenotype imputation to increase power for genetic discoveries in existing biobank datasets.
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Affiliation(s)
- Ulzee An
- Computer Science Department, UCLA, Los Angeles, CA, USA.
| | | | - Marcus Alvarez
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Lianyun Huang
- Helmholtz Pioneer Campus, Helmholtz Zentrum München, Neuherberg, Germany
- Computational Health Centre, Helmholtz Zentrum München, Neuherberg, Germany
- School of Medicine, Technical University of Munich, Munich, Germany
| | - Silviu Bacanu
- Virginia Institute for Psychiatric and Behavioral Genetics and Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Andrew J Schork
- Institute of Biological Psychiatry, Mental Health Center - Sct Hans, Copenhagen University Hospital, Copenhagen, Denmark
- Neurogenomics Division, The Translational Genomics Research Institute (TGEN), Phoenix, AZ, USA
- Section for Geogenetics, GLOBE Institute, Faculty of Health and Medical Sciences, Copenhagen University, Copenhagen, Denmark
| | - Kenneth Kendler
- Virginia Institute for Psychiatric and Behavioral Genetics and Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Päivi Pajukanta
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
- Institute for Precision Health, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Jonathan Flint
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Noah Zaitlen
- Neurology Department, UCLA, Los Angeles, CA, USA
| | - Na Cai
- Helmholtz Pioneer Campus, Helmholtz Zentrum München, Neuherberg, Germany
- Computational Health Centre, Helmholtz Zentrum München, Neuherberg, Germany
- School of Medicine, Technical University of Munich, Munich, Germany
| | - Andy Dahl
- Section of Genetic Medicine, University of Chicago, Chicago, IL, USA
| | - Sriram Sankararaman
- Computer Science Department, UCLA, Los Angeles, CA, USA.
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
- Department of Computational Medicine, UCLA, Los Angeles, CA, USA.
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5
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Koellinger PD, Okbay A, Kweon H, Schweinert A, Linnér RK, Goebel J, Richter D, Reiber L, Zweck BM, Belsky DW, Biroli P, Mata R, Tucker-Drob EM, Harden KP, Wagner G, Hertwig R. Cohort profile: Genetic data in the German Socio-Economic Panel Innovation Sample (SOEP-G). PLoS One 2023; 18:e0294896. [PMID: 38019829 PMCID: PMC10686514 DOI: 10.1371/journal.pone.0294896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Accepted: 11/12/2023] [Indexed: 12/01/2023] Open
Abstract
The German Socio-Economic Panel (SOEP) serves a global research community by providing representative annual longitudinal data of respondents living in private households in Germany. The dataset offers a valuable life course panorama, encompassing living conditions, socioeconomic status, familial connections, personality traits, values, preferences, health, and well-being. To amplify research opportunities further, we have extended the SOEP Innovation Sample (SOEP-IS) by collecting genetic data from 2,598 participants, yielding the first genotyped dataset for Germany based on a representative population sample (SOEP-G). The sample includes 107 full-sibling pairs, 501 parent-offspring pairs, and 152 triads, which overlap with the parent-offspring pairs. Leveraging the results from well-powered genome-wide association studies, we created a repository comprising 66 polygenic indices (PGIs) in the SOEP-G sample. We show that the PGIs for height, BMI, and educational attainment capture 22∼24%, 12∼13%, and 9% of the variance in the respective phenotypes. Using the PGIs for height and BMI, we demonstrate that the considerable increase in average height and the decrease in average BMI in more recent birth cohorts cannot be attributed to genetic shifts within the German population or to age effects alone. These findings suggest an important role of improved environmental conditions in driving these changes. Furthermore, we show that higher values in the PGIs for educational attainment and the highest math class are associated with better self-rated health, illustrating complex relationships between genetics, cognition, behavior, socio-economic status, and health. In summary, the SOEP-G data and the PGI repository we created provide a valuable resource for studying individual differences, inequalities, life-course development, health, and interactions between genetic predispositions and the environment.
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Affiliation(s)
- Philipp D. Koellinger
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Aysu Okbay
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Hyeokmoon Kweon
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Annemarie Schweinert
- Department of Economics, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Richard Karlsson Linnér
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Department of Economics, Leiden Law School, Leiden University, Leiden, The Netherlands
| | - Jan Goebel
- German Socio-Economic Panel Study, Deutsches Institut für Wirtschaftsforschung (DIW Berlin), Berlin, Germany
| | - David Richter
- Educational Science and Psychology, Freie Universität Berlin, Berlin, Germany
- SHARE Berlin, Berlin, Germany
| | - Lisa Reiber
- Center for Adaptive Rationality, Max-Planck Institute for Human Development, Berlin, Germany
| | | | - Daniel W. Belsky
- Department of Epidemiology and Butler Columbia Aging Center, Mailman School of Public Health, Columbia University, New York, New York, United States of America
- PROMENTA Center, University of Oslo, Oslo, Norway
| | - Pietro Biroli
- Department of Economics, University of Bologna, Bologna, Italy
| | - Rui Mata
- Center for Adaptive Rationality, Max-Planck Institute for Human Development, Berlin, Germany
- Faculty of Psychology, University of Basel, Basel, Switzerland
| | - Elliot M. Tucker-Drob
- Department of Psychology and Population Research Center, University of Texas at Austin, Austin, Texas, United States of America
| | - K. Paige Harden
- Department of Psychology and Population Research Center, University of Texas at Austin, Austin, Texas, United States of America
| | - Gert Wagner
- Educational Science and Psychology, Freie Universität Berlin, Berlin, Germany
- Center for Adaptive Rationality, Max-Planck Institute for Human Development, Berlin, Germany
- Federal Institute for Population Research, Wiesbaden, Germany
| | - Ralph Hertwig
- Center for Adaptive Rationality, Max-Planck Institute for Human Development, Berlin, Germany
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6
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Haas CB, Jordahl KM, Nance RM, Whitney BM, Wang L, Delaney JAC, Ruderman S, Jia T, Mathews WC, Saag MS, Lee SA, Napravnik S, Jacobson JM, Chander G, McCall EM, Moore RD, Mayer KH, Mukherjee S, Lee WJ, Crane PK, Crane H, Peter I, Lindström S. Assessing the associations between known genetic variants and substance use in people with HIV in the United States. PLoS One 2023; 18:e0292068. [PMID: 37796845 PMCID: PMC10553320 DOI: 10.1371/journal.pone.0292068] [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: 05/11/2023] [Accepted: 09/05/2023] [Indexed: 10/07/2023] Open
Abstract
BACKGROUND The prevalence of substance use in people with HIV (PWH) in the United States is higher than in the general population and is an important driver of HIV-related outcomes. We sought to assess if previously identified genetic associations that contribute to substance use are also observed in a population of PWH. METHODS We performed genome-wide association studies (GWAS) of alcohol, smoking, and cannabis use phenotypes in a multi-ancestry population of 7,542 PWH from the Center for AIDS Research Network of Integrated Clinical Systems (CNICS). We conducted multi-ancestry GWAS for individuals of African (n = 3,748), Admixed American (n = 1,334), and European (n = 2,460) ancestry. Phenotype data were self-reported and collected using patient reported outcomes (PROs) and three questions from AUDIT-C, an alcohol screening tool. We analyzed nine phenotypes: 1) frequency of alcohol consumption, 2) typical number of drinks on a day when drinking alcohol, 3) frequency of five or more alcoholic drinks in a 30-day period, 4) smoking initiation, 5) smoking cessation, 6) cigarettes per day, 7) cannabis use initiation, 8) cannabis use cessation, 9) frequency of cannabis use during the previous 30 days. For each phenotype we considered a) variants previously identified as associated with a substance use trait and b) novel associations. RESULTS We observed evidence for effects of previously reported single nucleotide polymorphisms (SNPs) related to alcohol (rs1229984, p = 0.001), tobacco (rs11783093, p = 2.22E-4), and cannabis use (rs2875907, p = 0.005). We also report two novel loci (19p13.2, p = 1.3E-8; and 20p11.21, p = 2.1E-8) associated with cannabis use cessation. CONCLUSIONS Our analyses contribute to understanding the genetic bases of substance use in a population with relatively higher rates of use compared to the general population.
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Affiliation(s)
- Cameron B. Haas
- Department of Epidemiology, University of Washington, Seattle, WA, United States of America
| | - Kristina M. Jordahl
- Department of Epidemiology, University of Washington, Seattle, WA, United States of America
| | - Robin M. Nance
- Department of Medicine, University of Washington, Seattle, WA, United States of America
| | - Bridget M. Whitney
- Department of Medicine, University of Washington, Seattle, WA, United States of America
| | - Lu Wang
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, United States of America
| | | | - Stephanie Ruderman
- Department of Epidemiology, University of Washington, Seattle, WA, United States of America
| | - Tongqiu Jia
- Department of Epidemiology, University of Washington, Seattle, WA, United States of America
| | - Wm. Christopher Mathews
- Department of Medicine, University of California at San Diego, San Diego, CA, United States of America
| | - Michael S. Saag
- Department of Medicine at the School of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States of America
| | - Sulggi A. Lee
- Department of Medicine, University of California at San Francisco, San Francisco, CA, United States of America
| | - Sonia Napravnik
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, United States of America
| | - Jeffrey M. Jacobson
- Center for AIDS Research, Case Western Reserve University/University Hospitals Case Medical Center, Cleveland, OH, United States of America
| | - Geetanjali Chander
- Department of Medicine, University of Washington, Seattle, WA, United States of America
- Department of Medicine, Johns Hopkins University, Baltimore, MD, United States of America
| | - Elizabeth M. McCall
- Department of Medicine, Johns Hopkins University, Baltimore, MD, United States of America
| | - Richard D. Moore
- Department of Medicine, Johns Hopkins University, Baltimore, MD, United States of America
| | - Kenneth H. Mayer
- Harvard Medical School, Beth Israel Deaconess Medical Center, Fenway Health, Boston, MA, United States of America
| | - Shubhabrata Mukherjee
- Department of Medicine, University of Washington, Seattle, WA, United States of America
| | - Won Jun Lee
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Paul K. Crane
- Department of Medicine, University of Washington, Seattle, WA, United States of America
| | - Heidi Crane
- Department of Medicine, University of Washington, Seattle, WA, United States of America
| | - Inga Peter
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Sara Lindström
- Department of Epidemiology, University of Washington, Seattle, WA, United States of America
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, United States of America
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7
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Blum K, Gold MS, Cadet JL, Gondre-Lewis MC, McLaughlin T, Braverman ER, Elman I, Paul Carney B, Cortese R, Abijo T, Bagchi D, Giordano J, Dennen CA, Baron D, Thanos PK, Soni D, Makale MT, Makale M, Murphy KT, Jafari N, Sunder K, Zeine F, Ceccanti M, Bowirrat A, Badgaiyan RD. Invited Expert Opinion- Bioinformatic and Limitation Directives to Help Adopt Genetic Addiction Risk Screening and Identify Preaddictive Reward Dysregulation: Required Analytic Evidence to Induce Dopamine Homeostatsis. MEDICAL RESEARCH ARCHIVES 2023; 11:10.18103/mra.v11i8.4211. [PMID: 37885438 PMCID: PMC10601302 DOI: 10.18103/mra.v11i8.4211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
Addiction, albeit some disbelievers like Mark Lewis [1], is a chronic, relapsing brain disease, resulting in unwanted loss of control over both substance and non- substance behavioral addictions leading to serious adverse consequences [2]. Addiction scientists and clinicians face an incredible challenge in combatting the current opioid and alcohol use disorder (AUD) pandemic throughout the world. Provisional data from the Centers for Disease Control and Prevention (CDC) shows that from July 2021-2022, over 100,000 individuals living in the United States (US) died from a drug overdose, and 77,237 of those deaths were related to opioid use [3]. This number is expected to rise, and according to the US Surgeon General it is highly conceivable that by 2025 approximately 165,000 Americans will die from an opioid overdose. Alcohol abuse, according to data from the World Health Organization (WHO), results in 3 million deaths worldwide every year, which represents 5.3% of all deaths globally [4].
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Affiliation(s)
- Kenneth Blum
- The Kenneth Blum Behavioral & Neurogenetic Institute, Austin, TX., USA
- Division of Addiction Research & Education, Center for Sports, Exercise & Psychiatry, Western University Health Sciences, Pomona, CA., USA
- Institute of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary
- Department of Psychiatry, School of Medicine, University of Vermont, Burlington, VT.,USA
- Department of Psychiatry, Wright State University Boonshoft School of Medicine and Dayton VA Medical Centre, Dayton, OH, USA
- Division of Nutrigenomics Research, TranspliceGen Therapeutics, Inc., Austin, Tx., 78701, USA
- Department of Nutrigenomic Research, Victory Nutrition International, Inc., Bonita Springs, FL, USA
- Division of Personalized Medicine, Cross-Cultural Research and Educational Institute, San Clemente, CA., USA
- Sunder Foundation, Palm Springs, CA, USA
- Department of Molecular Biology and Adelson School of Medicine, Ariel University, Ariel, Israel
| | - Mark S Gold
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO., USA
| | - Jean Lud Cadet
- Molecular Neuropsychiatry Research Branch, National Institute on Drug Abuse, National Institutes of Health, Bethesda, MD., USA
| | - Marjorie C. Gondre-Lewis
- Neuropsychopharmacology Laboratory, Department of Anatomy, Howard University College of Medicine, Washington, DC., USA
| | - Thomas McLaughlin
- Division of Nutrigenomics Research, TranspliceGen Therapeutics, Inc., Austin, Tx., 78701, USA
| | - Eric R Braverman
- The Kenneth Blum Behavioral & Neurogenetic Institute, Austin, TX., USA
| | - Igor Elman
- Center for Pain and the Brain (P.A.I.N Group), Department of Anesthesiology, Critical Care & Pain Medicine, Boston Children’s Hospital, Boston, MA., USA
| | - B. Paul Carney
- Division Pediatric Neurology, University of Missouri, School of Medicine, Columbia, MO., USA
| | - Rene Cortese
- Department of Child Health – Child Health Research Institute, & Department of Obstetrics, Gynecology and Women’s Health School of Medicine, University of Missouri, MO., USA
| | - Tomilowo Abijo
- Neuropsychopharmacology Laboratory, Department of Anatomy, Howard University College of Medicine, Washington, DC., USA
| | - Debasis Bagchi
- Department of Pharmaceutical Sciences, Texas Southern University College of Pharmacy and Health Sciences, Houston, TX, USA
| | - John Giordano
- Division of Personalized Mental Illness Treatment & Research, Ketamine Infusion Clinics of South Florida, Pompano Beach, Fl., USA
| | - Catherine A. Dennen
- Department of Family Medicine, Jefferson Health Northeast, Philadelphia, PA, USA
| | - David Baron
- Institute of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary
| | - Panayotis K Thanos
- Behavioral Neuropharmacology and Neuroimaging Laboratory on Addictions, Clinical Research Institute on Addictions, Department of Pharmacology and Toxicology, Jacobs School of Medicine and Biosciences, State University of New York at Buffalo, Buffalo, NY 14203, USA
- Department of Psychology, State University of New York at Buffalo, Buffalo, NY 14203, USA
| | - Diwanshu Soni
- College of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, CA., USA
| | - Milan T. Makale
- Department of Radiation Medicine and Applied Sciences, UC San Diego, 3855 Health Sciences Drive, La Jolla, CA 92093-0819, USA
| | - Miles Makale
- Department of Psychology, UC San Diego, Health Sciences Drive, La Jolla, CA, 92093, USA
| | | | - Nicole Jafari
- Department of Human Development, California State University at long Beach, Long Beach, CA., USA
- Division of Personalized Medicine, Cross-Cultural Research and Educational Institute, San Clemente, CA., USA
| | - Keerthy Sunder
- Department of Psychiatry, Menifee Global Medical Center, Palm Desert, CA., USA
- Sunder Foundation, Palm Springs, CA, USA
| | - Foojan Zeine
- Awareness Integration Institute, San Clemente, CA., USA
- Department of Health Science, California State University at Long Beach, Long Beach, CA., USA
| | - Mauro Ceccanti
- Società Italiana per il Trattamento dell’Alcolismo e le sue Complicanze (SITAC), ASL Roma1, Sapienza University of Rome, Rome, Italy
| | - Abdalla Bowirrat
- Department of Molecular Biology and Adelson School of Medicine, Ariel University, Ariel, Israel
| | - Rajendra D. Badgaiyan
- Department of Psychiatry, South Texas Veteran Health Care System, Audie L. Murphy Memorial VA Hospital, Long School of Medicine, University of Texas Medical Center, San Antonio, TX., USA
- Department of Psychiatry, Mt Sinai University School of Medicine, New York, NY., USA
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Thorpe HHA, Fontanillas P, Pham BK, Meredith JJ, Jennings MV, Courchesne-Krak NS, Vilar-Ribó L, Bianchi SB, Mutz J, Elson SL, Khokhar JY, Abdellaoui A, Davis LK, Palmer AA, Sanchez-Roige S. Genome-Wide Association Studies of Coffee Intake in UK/US Participants of European Ancestry Uncover Gene-Cohort Influences. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.09.09.23295284. [PMID: 37745582 PMCID: PMC10516045 DOI: 10.1101/2023.09.09.23295284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
Coffee is one of the most widely consumed beverages. We performed a genome-wide association study (GWAS) of coffee intake in US-based 23andMe participants (N=130,153) and identified 7 significant loci, with many replicating in three multi-ancestral cohorts. We examined genetic correlations and performed a phenome-wide association study across thousands of biomarkers and health and lifestyle traits, then compared our results to the largest available GWAS of coffee intake from UK Biobank (UKB; N=334,659). The results of these two GWAS were highly discrepant. We observed positive genetic correlations between coffee intake and psychiatric illnesses, pain, and gastrointestinal traits in 23andMe that were absent or negative in UKB. Genetic correlations with cognition were negative in 23andMe but positive in UKB. The only consistent observations were positive genetic correlations with substance use and obesity. Our study shows that GWAS in different cohorts could capture cultural differences in the relationship between behavior and genetics.
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Affiliation(s)
- Hayley H A Thorpe
- Department of Anatomy and Cell Biology, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
- Department of Biomedical Sciences, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada
| | | | - Benjamin K Pham
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - John J Meredith
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Mariela V Jennings
- 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
| | - Sevim B Bianchi
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Julian Mutz
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - 23andMe Research Team
- Department of Biomedical Sciences, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada
| | - Sarah L Elson
- Department of Biomedical Sciences, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada
| | - Jibran Y Khokhar
- Department of Anatomy and Cell Biology, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
- Department of Biomedical Sciences, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada
| | - Abdel Abdellaoui
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Lea K Davis
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Sandra Sanchez-Roige
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
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9
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Nurmi EL, Laughlin CP, de Wit H, Palmer AA, MacKillop J, Cannon TD, Bilder RM, Congdon E, Sabb FW, Seaman LC, McElroy JJ, Libowitz MR, Weafer J, Gray J, Dean AC, Hellemann GS, London ED. Polygenic contributions to performance on the Balloon Analogue Risk Task. Mol Psychiatry 2023; 28:3524-3530. [PMID: 37582857 PMCID: PMC10618088 DOI: 10.1038/s41380-023-02123-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 05/03/2023] [Accepted: 06/07/2023] [Indexed: 08/17/2023]
Abstract
Risky decision-making is a common, heritable endophenotype seen across many psychiatric disorders. Its underlying genetic architecture is incompletely explored. We examined behavior in the Balloon Analogue Risk Task (BART), which tests risky decision-making, in two independent samples of European ancestry. One sample (n = 1138) comprised healthy participants and some psychiatric patients (53 schizophrenia, 42 bipolar disorder, 47 ADHD); the other (n = 911) excluded for recent treatment of various psychiatric disorders but not ADHD. Participants provided DNA and performed the BART, indexed by mean adjusted pumps. We constructed a polygenic risk score (PRS) for discovery in each dataset and tested it in the other as replication. Subsequently, a genome-wide MEGA-analysis, combining both samples, tested genetic correlation with risk-taking self-report in the UK Biobank sample and psychiatric phenotypes characterized by risk-taking (ADHD, Bipolar Disorder, Alcohol Use Disorder, prior cannabis use) in the Psychiatric Genomics Consortium. The PRS for BART performance in one dataset predicted task performance in the replication sample (r = 0.13, p = 0.000012, pFDR = 0.000052), as did the reciprocal analysis (r = 0.09, p = 0.0083, pFDR=0.04). Excluding participants with psychiatric diagnoses produced similar results. The MEGA-GWAS identified a single SNP (rs12023073; p = 3.24 × 10-8) near IGSF21, a protein involved in inhibitory brain synapses; replication samples are needed to validate this result. A PRS for self-reported cannabis use (p = 0.00047, pFDR = 0.0053), but not self-reported risk-taking or psychiatric disorder status, predicted behavior on the BART in our MEGA-GWAS sample. The findings reveal polygenic architecture of risky decision-making as measured by the BART and highlight its overlap with cannabis use.
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Affiliation(s)
- E L Nurmi
- Department of Psychiatry and Biobehavioral Sciences, University of California at Los Angeles, Los Angeles, CA, 90024, USA.
| | - C P Laughlin
- Department of Psychiatry and Biobehavioral Sciences, University of California at Los Angeles, Los Angeles, CA, 90024, USA
| | - H de Wit
- Department of Psychiatry, University of Chicago, Chicago, IL, 60637, USA
| | - A A Palmer
- Department of Psychiatry, University of California at San Diego, La Jolla, CA, 92093, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, 92093, USA
| | - J MacKillop
- Peter Boris Centre for Addictions Research, McMaster University and St. Joseph's Healthcare Hamilton, Hamilton, ON, L8S4L8, Canada
| | - T D Cannon
- Departments of Psychology and Psychiatry, Yale University, New Haven, CT, 06520, USA
| | - R M Bilder
- Department of Psychiatry and Biobehavioral Sciences, University of California at Los Angeles, Los Angeles, CA, 90024, USA
| | - E Congdon
- Department of Psychiatry and Biobehavioral Sciences, University of California at Los Angeles, Los Angeles, CA, 90024, USA
| | - F W Sabb
- Prevention Science Institute, University of Utah, Salt Lake City, UT, 84112, USA
| | - L C Seaman
- Department of Psychiatry and Biobehavioral Sciences, University of California at Los Angeles, Los Angeles, CA, 90024, USA
| | - J J McElroy
- Department of Psychiatry and Biobehavioral Sciences, University of California at Los Angeles, Los Angeles, CA, 90024, USA
| | - M R Libowitz
- Department of Neurobiology, University of Kentucky, Lexington, KY, 40506, USA
| | - J Weafer
- Department of Psychology, University of Kentucky, Lexington, KY, 40506, USA
| | - J Gray
- Department of Psychology, University of Georgia, Athens, GA, 30602, USA
| | - A C Dean
- Department of Psychiatry and Biobehavioral Sciences, University of California at Los Angeles, Los Angeles, CA, 90024, USA
| | - G S Hellemann
- Department of Public Health, University of Alabama at Birmingham, Birmingham, AL, 35294, USA
| | - E D London
- Department of Psychiatry and Biobehavioral Sciences, University of California at Los Angeles, Los Angeles, CA, 90024, USA
- Department of Molecular and Medical Pharmacology, University of California at Los Angeles, Los Angeles, CA, 90024, USA
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10
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Hillmer A, Chawar C, Lamri A, Hudson J, Kapczinski F, Minuzzi L, Marsh DC, Thabane L, Paterson AD, Samaan Z. Genetics of cannabis use in opioid use disorder: A genome-wide association and polygenic risk score study. PLoS One 2023; 18:e0289059. [PMID: 37494403 PMCID: PMC10370765 DOI: 10.1371/journal.pone.0289059] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 07/10/2023] [Indexed: 07/28/2023] Open
Abstract
BACKGROUND Individuals with an Opioid Use Disorder (OUD) have increased rates of cannabis use in comparison to the general population. Research on the short- and long-term impacts of cannabis use in OUD patients has been inconclusive. A genetic component may contribute to cannabis cravings. AIMS Identify genetic variants associated with cannabis use through Genome-wide Association Study (GWAS) methods and investigate a Polygenic Risk Score (PRS). In addition, we aim to identify any sex differences in effect size for genetic variants reaching or nearing genome-wide significance in the GWAS. METHODS The study outcomes of interest were: regular cannabis use (yes/no) (n = 2616), heaviness of cannabis use (n = 1293) and cannabis cravings (n = 836). Logistic and linear regressions were preformed, respectively, to test the association between genetic variants and each outcome, regular cannabis use and heaviness of cannabis use. GWAS summary statistics from a recent large meta-GWAS investigating cannabis use disorder were used to conduct PRS's. Findings are limited to a European ancestry sample. RESULTS No genome-wide significant associations were found. Rs1813412 (chromosome 17) for regular cannabis use and rs62378502 (chromosome 5) for heaviness of cannabis use were approaching genome-wide significance. Both these SNPs were nominally significant (p<0.05) within males and females, however sex did not modify the association. The PRS identified statistically significant association with cannabis cravings. The variance explained by all PRSs were less than 1.02x10-2. CONCLUSION This study provides promising results in understanding the genetic contribution to cannabis use in individuals living with OUD.
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Affiliation(s)
- Alannah Hillmer
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
| | - Caroul Chawar
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
| | - Amel Lamri
- Department of Medicine, McMaster University, Hamilton, ON, Canada
| | - Jacqueline Hudson
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
| | - Flavio Kapczinski
- McMaster University, Hamilton, ON, Canada
- Universidade Federal do Rio Grande do Sol, Porto Alegre, Brazil
| | - Luciano Minuzzi
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
| | | | - Lehana Thabane
- Department of Health Research Method, Evidence & Impact, Hamilton, ON, Canada
| | - Andrew D Paterson
- Program in Genetics and Genome Biology, The Hospital for Sick Children, Divisions of Biostatistics and Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Zainab Samaan
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
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11
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Ciucă Anghel DM, Nițescu GV, Tiron AT, Guțu CM, Baconi DL. Understanding the Mechanisms of Action and Effects of Drugs of Abuse. Molecules 2023; 28:4969. [PMID: 37446631 DOI: 10.3390/molecules28134969] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 06/18/2023] [Accepted: 06/22/2023] [Indexed: 07/15/2023] Open
Abstract
AIM Drug abuse and addiction are major public health concerns, with millions of people worldwide affected by the negative consequences of drug use. To better understand this complex issue, a review was conducted to examine the mechanisms of action and effects of drugs of abuse, including their acute and chronic effects, the symptoms of abstinence syndrome, as well as their cardiovascular impacts. METHODS The analyzed data were obtained after surveying an electronic database, namely PubMed, with no time limit, grey literature sources, and reference lists of relevant articles. RESULTS The review highlights the different categories of drugs of abuse, such as opioids, stimulants, depressants, hallucinogens, and cannabis, and discusses the specific ways that each drug affects the brain and body. Additionally, the review explores the short-term and long-term effects of drug abuse on the body and mind, including changes in brain structure and function, physical health problems, and mental health issues, such as depression and anxiety. In addition, the review explores the effects of drug abuse on cardiovascular health, focusing on electrocardiogram changes. Moreover, the analysis of relevant literature also highlighted possible genetic susceptibility in various addictions. Furthermore, the review delves into the withdrawal symptoms that occur when someone stops using drugs of abuse after a period of chronic use. CONCLUSION Overall, this review provides a comprehensive overview of the current state of knowledge on drug abuse and addiction. The findings of this review can inform the development of evidence-based prevention and intervention strategies to address this critical public health issue.
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Affiliation(s)
| | - Gabriela Viorela Nițescu
- Ward ATI-Toxicology, Paediatric Clinic 2, "Grigore Alexandrescu" Emergency Clinical Hospital for Children, 011732 Bucharest, Romania
| | - Andreea-Taisia Tiron
- Department of Medical Semiology, Sf. Ioan Emergency Clinical Hospital, Carol Davila University of Medicine and Pharmacy, 20021 Bucharest, Romania
| | - Claudia Maria Guțu
- Department of Toxicology, Carol Davila University of Medicine and Pharmacy, 20021 Bucharest, Romania
| | - Daniela Luiza Baconi
- Department of Toxicology, Carol Davila University of Medicine and Pharmacy, 20021 Bucharest, Romania
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12
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Loureiro CM, Corsi-Zuelli F, Fachim HA, Shuhama R, de Oliveira AM, Menezes PR, Dalton CF, Louzada-Junior P, Belangero SI, Coeli-Lacchini F, Reynolds GP, Lacchini R, Del-Ben CM. Lifetime cannabis use and childhood trauma associated with CNR1 genetic variants increase the risk of psychosis: findings from the STREAM study. REVISTA BRASILEIRA DE PSIQUIATRIA (SAO PAULO, BRAZIL : 1999) 2023; 45:226-235. [PMID: 36918037 PMCID: PMC10288472 DOI: 10.47626/1516-4446-2022-2882] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Accepted: 02/03/2023] [Indexed: 03/06/2023]
Abstract
OBJECTIVES Gene-environment interactions increase the risk of psychosis. The objective of this study was to investigate gene-gene and gene-environment interactions in psychosis, including single nucleotide variants (SNVs) of dopamine-2 receptor (D2R), N-methyl-d-aspartate receptor (NMDAR), and cannabinoid receptor type 1 (CB1R), lifetime cannabis use, and childhood trauma. METHODS Twenty-three SNVs of genes encoding D2R (DRD2: rs1799978, rs7131056, rs6275), NMDAR (GRIN1: rs4880213, rs11146020; GRIN2A: rs1420040, rs11866328; GRIN2B: rs890, rs2098469, rs7298664), and CB1R (CNR1: rs806380, rs806379, rs1049353, rs6454674, rs1535255, rs2023239, rs12720071, rs6928499, rs806374, rs7766029, rs806378, rs10485170, rs9450898) were genotyped in 143 first-episode psychosis patients (FEPp) and 286 community-based controls by Illumina HumanCoreExome-24 BeadChip. Gene-gene and gene-environment associations were assessed using nonparametric Multifactor Dimensionality Reduction software. RESULTS Single-locus analyses among the 23 SNVs for psychosis and gene-gene interactions were not significant (p > 0.05 for all comparisons); however, both environmental risk factors showed an association with psychosis (p < 0.001). Moreover, gene-environment interactions were significant for an SNV in CNR1 and cannabis use. The best-performing model was the combination of CNR1 rs12720071 and lifetime cannabis use (p < 0.001), suggesting an increased risk of psychosis. CONCLUSION Our study supports the hypothesis of gene-environment interactions for psychosis involving T-allele carriers of CNR1 SNVs, childhood trauma, and cannabis use.
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Affiliation(s)
- Camila Marcelino Loureiro
- Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo (USP), Ribeirão Preto, SP, Brazil
- Centro de Pesquisas em Saúde Mental da População, São Paulo, SP, Brazil
| | - Fabiana Corsi-Zuelli
- Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo (USP), Ribeirão Preto, SP, Brazil
| | | | - Rosana Shuhama
- Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo (USP), Ribeirão Preto, SP, Brazil
- Centro de Pesquisas em Saúde Mental da População, São Paulo, SP, Brazil
| | | | - Paulo Rossi Menezes
- Centro de Pesquisas em Saúde Mental da População, São Paulo, SP, Brazil
- Faculdade de Medicina, USP, São Paulo, SP, Brazil
| | | | - Paulo Louzada-Junior
- Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo (USP), Ribeirão Preto, SP, Brazil
| | | | | | | | - Riccardo Lacchini
- Escola de Enfermagem de Ribeirão Preto, USP, Ribeirão Preto, SP, Brazil
| | - Cristina Marta Del-Ben
- Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo (USP), Ribeirão Preto, SP, Brazil
- Centro de Pesquisas em Saúde Mental da População, São Paulo, SP, Brazil
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13
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Lim CCW, Leung JKY, Gravely S, Gartner C, Sun T, Chiu V, Chung JYC, Stjepanović D, Connor J, Scheurer RW, Hall W, Chan GCK. A latent class analysis of patterns of tobacco and cannabis use in Australia and their health-related correlates. Drug Alcohol Rev 2023; 42:815-826. [PMID: 36780230 PMCID: PMC10947067 DOI: 10.1111/dar.13614] [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: 03/14/2022] [Revised: 12/10/2022] [Accepted: 01/08/2023] [Indexed: 02/14/2023]
Abstract
INTRODUCTION The shifting landscape in Australia's tobacco and cannabis policies and emerging new products and modes of administration may increase experimentation and the risks of addiction to these drugs. METHODS We analysed cross-sectional data from the 2019 National Drug Strategy and Household Survey (n = 22,015) of Australians aged 14 and above. Latent class analysis was used to identify distinct groups based on types of tobacco and cannabis products used. The socio-demographic, health-rated correlates and past-year substance use of each latent class was examined. RESULTS A four-class solution was identified: co-use of tobacco and cannabis (2.4%), cannabis-only (5.5%), tobacco-only (8.0%) and non-user (84.0%). Males (odds ratio [OR] range 1.5-2.9), younger age (OR range 2.4-8.4), moderate to high psychological distress (OR range 1.3-3.0), using illicit substances in the last year (OR range 1.41-22.87) and high risk of alcohol use disorder (OR range 2.0-21.7) were more likely to be in the tobacco/cannabis use classes than non-users. Within the co-use class, 78.4% mixed tobacco with cannabis and 89.4% had used alcohol with cannabis at least once. DISCUSSION AND CONCLUSIONS Approximately 16% of respondents used tobacco or cannabis, or both substances, and no major distinct subgroups were identified by the use of different product types. Mental health issues and the poly-substance use were more common in the class who were co-users of cannabis and tobacco. Existing policies need to minimise cannabis and tobacco-related harms to reduce the societal burden associated with both substances.
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Affiliation(s)
- Carmen C. W. Lim
- National Centre for Youth Substance Use Research, Faculty of Health and Behavioural SciencesThe University of QueenslandBrisbaneAustralia
- School of PsychologyThe University of QueenslandBrisbaneAustralia
- NHMRC Centre of Research Excellence on Achieving the Tobacco Endgame, School of Public Health, Faculty of MedicineThe University of QueenslandBrisbaneAustralia
| | - Janni K. Y. Leung
- National Centre for Youth Substance Use Research, Faculty of Health and Behavioural SciencesThe University of QueenslandBrisbaneAustralia
| | - Shannon Gravely
- Department of PsychologyUniversity of WaterlooWaterlooCanada
| | - Coral Gartner
- NHMRC Centre of Research Excellence on Achieving the Tobacco Endgame, School of Public Health, Faculty of MedicineThe University of QueenslandBrisbaneAustralia
| | - Tianze Sun
- National Centre for Youth Substance Use Research, Faculty of Health and Behavioural SciencesThe University of QueenslandBrisbaneAustralia
- School of PsychologyThe University of QueenslandBrisbaneAustralia
- NHMRC Centre of Research Excellence on Achieving the Tobacco Endgame, School of Public Health, Faculty of MedicineThe University of QueenslandBrisbaneAustralia
| | - Vivian Chiu
- National Centre for Youth Substance Use Research, Faculty of Health and Behavioural SciencesThe University of QueenslandBrisbaneAustralia
- School of PsychologyThe University of QueenslandBrisbaneAustralia
| | - Jack Y. C. Chung
- National Centre for Youth Substance Use Research, Faculty of Health and Behavioural SciencesThe University of QueenslandBrisbaneAustralia
- School of PsychologyThe University of QueenslandBrisbaneAustralia
| | - Daniel Stjepanović
- National Centre for Youth Substance Use Research, Faculty of Health and Behavioural SciencesThe University of QueenslandBrisbaneAustralia
| | - Jason Connor
- National Centre for Youth Substance Use Research, Faculty of Health and Behavioural SciencesThe University of QueenslandBrisbaneAustralia
- Discipline of Psychiatry, Faculty of MedicineThe University of QueenslandBrisbaneAustralia
| | - Roman W. Scheurer
- Queensland Centre for Mental Health ResearchThe Park Centre for Mental HealthBrisbaneAustralia
| | - Wayne Hall
- National Centre for Youth Substance Use Research, Faculty of Health and Behavioural SciencesThe University of QueenslandBrisbaneAustralia
- Queensland Alliance for Environmental Health SciencesThe University of QueenslandBrisbaneAustralia
| | - Gary C. K. Chan
- National Centre for Youth Substance Use Research, Faculty of Health and Behavioural SciencesThe University of QueenslandBrisbaneAustralia
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14
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Kitdumrongthum S, Trachootham D. An Individuality of Response to Cannabinoids: Challenges in Safety and Efficacy of Cannabis Products. Molecules 2023; 28:molecules28062791. [PMID: 36985763 PMCID: PMC10058560 DOI: 10.3390/molecules28062791] [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: 01/31/2023] [Revised: 03/10/2023] [Accepted: 03/13/2023] [Indexed: 03/30/2023] Open
Abstract
Since legalization, cannabis/marijuana has been gaining considerable attention as a functional ingredient in food. ∆-9 tetrahydrocannabinol (THC), cannabidiol (CBD), and other cannabinoids are key bioactive compounds with health benefits. The oral consumption of cannabis transports much less hazardous chemicals than smoking. Nevertheless, the response to cannabis is biphasically dose-dependent (hormesis; a low-dose stimulation and a high-dose inhibition) with wide individuality in responses. Thus, the exact same dose and preparation of cannabis may be beneficial for some but toxic to others. The purpose of this review is to highlight the concept of individual variations in response to cannabinoids, which leads to the challenge of establishing standard safe doses of cannabis products for the general population. The mechanisms of actions, acute and chronic toxicities, and factors affecting responses to cannabis products are updated. Based on the literature review, we found that the response to cannabis products depends on exposure factors (delivery route, duration, frequency, and interactions with food and drugs), individual factors (age, sex), and susceptibility factors (genetic polymorphisms of cannabinoid receptor gene, N-acylethanolamine-hydrolyzing enzymes, THC-metabolizing enzymes, and epigenetic regulations). Owing to the individuality of responses, the safest way to use cannabis-containing food products is to start low, go slow, and stay low.
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15
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Mao Q, Lin X, Yin Q, Liu P, Zhang Y, Qu S, Xu J, Cheng W, Luo X, Kang L, Taximaimaiti R, Zheng C, Zhang H, Wang X, Ren H, Cao Y, Lin J, Luo X. A significant, functional and replicable risk KTN1 variant block for schizophrenia. Sci Rep 2023; 13:3890. [PMID: 36890161 PMCID: PMC9995530 DOI: 10.1038/s41598-023-27448-z] [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: 10/12/2022] [Accepted: 01/02/2023] [Indexed: 03/10/2023] Open
Abstract
Cortical and subcortical structural alteration has been extensively reported in schizophrenia, including the unusual expansion of gray matter volumes (GMVs) of basal ganglia (BG), especially putamen. Previous genome-wide association studies pinpointed kinectin 1 gene (KTN1) as the most significant gene regulating the GMV of putamen. In this study, the role of KTN1 variants in risk and pathogenesis of schizophrenia was explored. A dense set of SNPs (n = 849) covering entire KTN1 was analyzed in three independent European- or African-American samples (n = 6704) and one mixed European and Asian Psychiatric Genomics Consortium sample (n = 56,418 cases vs. 78,818 controls), to identify replicable SNP-schizophrenia associations. The regulatory effects of schizophrenia-associated variants on the KTN1 mRNA expression in 16 cortical or subcortical regions in two European cohorts (n = 138 and 210, respectively), the total intracranial volume (ICV) in 46 European cohorts (n = 18,713), the GMVs of seven subcortical structures in 50 European cohorts (n = 38,258), and the surface areas (SA) and thickness (TH) of whole cortex and 34 cortical regions in 50 European cohorts (n = 33,992) and eight non-European cohorts (n = 2944) were carefully explored. We found that across entire KTN1, only 26 SNPs within the same block (r2 > 0.85) were associated with schizophrenia across ≥ 2 independent samples (7.5 × 10-5 ≤ p ≤ 0.048). The schizophrenia-risk alleles, which increased significantly risk for schizophrenia in Europeans (q < 0.05), were all minor alleles (f < 0.5), consistently increased (1) the KTN1 mRNA expression in 12 brain regions significantly (5.9 × 10-12 ≤ p ≤ 0.050; q < 0.05), (2) the ICV significantly (6.1 × 10-4 ≤ p ≤ 0.008; q < 0.05), (3) the SA of whole (9.6 × 10-3 ≤ p ≤ 0.047) and two regional cortices potentially (2.5 × 10-3 ≤ p ≤ 0.042; q > 0.05), and (4) the TH of eight regional cortices potentially (0.006 ≤ p ≤ 0.050; q > 0.05), and consistently decreased (1) the BG GMVs significantly (1.8 × 10-19 ≤ p ≤ 0.050; q < 0.05), especially putamen GMV (1.8 × 10-19 ≤ p ≤ 1.0 × 10-4; q < 0.05, (2) the SA of four regional cortices potentially (0.010 ≤ p ≤ 0.048), and (3) the TH of four regional cortices potentially (0.015 ≤ p ≤ 0.049) in Europeans. We concluded that we identified a significant, functional, and robust risk variant block covering entire KTN1 that might play a critical role in the risk and pathogenesis of schizophrenia.
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Affiliation(s)
- Qiao Mao
- Department of Psychosomatic Medicine, People's Hospital of Deyang City, Deyang, 618000, Sichuan, China
| | - Xiandong Lin
- Laboratory of Radiation Oncology and Radiobiology, Fujian Provincial Cancer Hospital, the Teaching Hospital of Fujian Medical University, Fuzhou, 350014, Fujian, China
| | - Qin Yin
- Department of Respiratory and Critical Care Medicine, Hubei Provincial Hospital of Integrated Chinese and Western Medicine, Wuhan, 430000, Hubei, China
| | - Ping Liu
- Department of Psychosomatic Medicine, People's Hospital of Deyang City, Deyang, 618000, Sichuan, China
| | - Yong Zhang
- Tianjin Mental Health Center, Tianjin, 300222, China
| | - Shihao Qu
- Zhuhai Center for Maternal and Child Health Care, Zhuhai, Guangdong, 519001, China
| | - Jianying Xu
- Zhuhai Center for Maternal and Child Health Care, Zhuhai, Guangdong, 519001, China
| | - Wenhong Cheng
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China
| | - Xinqun Luo
- Department of Neurosurgery, The First Hospital, Fujian Medical University, Fuzhou, 350004, Fujian, China
| | - Longli Kang
- Key Laboratory for Molecular Genetic Mechanisms and Intervention Research On High Altitude Diseases of Tibet Autonomous Region, Xizang Minzu University School of Medicine, Xiangyang, 712082, Shaanxi, China
| | - Reyisha Taximaimaiti
- Department of Neurology, Shanghai Tongren Hospital, Shanghai Jiao Tong University, Shanghai, 200080, China
| | - Chengchou Zheng
- Minqing Psychiatric Hospital, Minqing, 350800, Fujian, China
| | - Huihao Zhang
- The First Affiliated Hospital, Fujian Medical University, Fuzhou, 350001, China
| | - Xiaoping Wang
- Department of Neurology, The 1st People's Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 201620, USA
| | - Honggang Ren
- Department of Internal Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yuping Cao
- Department of Psychiatry, Second Xiangya Hospital, Central South University, China National Clinical Research Center On Mental Disorders, China National Technology Institute On Mental Disorders, Changsha, 410011, Hunan, China.
| | - Jie Lin
- Fujian Center for Disease Control and Prevention, Fuzhou, 350012, Fujian, China.
- Fujian Institute of Preventive Medicine, Fuzhou, 350012, Fujian, China.
| | - Xingguang Luo
- Beijing Huilongguan Hospital, Peking University Huilongguan School of Clinical Medicine, Beijing, 100096, China.
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16
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Knodt AR, Meier MH, Ambler A, Gehred MZ, Harrington H, Ireland D, Poulton R, Ramrakha S, Caspi A, Moffitt TE, Hariri AR. Diminished Structural Brain Integrity in Long-term Cannabis Users Reflects a History of Polysubstance Use. Biol Psychiatry 2022; 92:861-870. [PMID: 36008158 PMCID: PMC9637748 DOI: 10.1016/j.biopsych.2022.06.018] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 05/26/2022] [Accepted: 06/14/2022] [Indexed: 11/16/2022]
Abstract
BACKGROUND Cannabis legalization and use are outpacing our understanding of its long-term effects on brain and behavior, which is fundamental for effective policy and health practices. Existing studies are limited by small samples, cross-sectional measures, failure to separate long-term from recreational use, and inadequate control for other substance use. Here, we address these limitations by determining the structural brain integrity of long-term cannabis users in the Dunedin Study, a longitudinal investigation of a population-representative birth cohort followed to midlife. METHODS We leveraged prospective measures of cannabis, alcohol, tobacco, and other illicit drug use in addition to structural neuroimaging in 875 study members at age 45 to test for differences in both global and regional gray and white matter integrity between long-term cannabis users and lifelong nonusers. We additionally tested for dose-response associations between continuous measures of cannabis use and brain structure, including careful adjustments for use of other substances. RESULTS Long-term cannabis users had a thinner cortex, smaller subcortical gray matter volumes, and higher machine learning-predicted brain age than nonusers. However, these differences in structural brain integrity were explained by the propensity of long-term cannabis users to engage in polysubstance use, especially with alcohol and tobacco. CONCLUSIONS These findings suggest that diminished midlife structural brain integrity in long-term cannabis users reflects a broader pattern of polysubstance use, underlining the importance of understanding comorbid substance use in efforts to curb the negative effects of cannabis on brain and behavior as well as establish more effective policy and health practices.
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Affiliation(s)
- Annchen R Knodt
- Department of Psychology and Neuroscience, Duke University, Durham, North Carolina
| | - Madeline H Meier
- Department of Psychology, Arizona State University, Tempe, Arizona
| | - Antony Ambler
- Institute of Psychiatry, Psychology, & Neuroscience, King's College London, London, United Kingdom; Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Maria Z Gehred
- Department of Psychology and Neuroscience, Duke University, Durham, North Carolina
| | - HonaLee Harrington
- Department of Psychology and Neuroscience, Duke University, Durham, North Carolina
| | - David Ireland
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Richie Poulton
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Sandhya Ramrakha
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Avshalom Caspi
- Department of Psychology and Neuroscience, Duke University, Durham, North Carolina; Department of Psychiatry and Behavioral Sciences, Duke University, Durham, North Carolina; Institute of Psychiatry, Psychology, & Neuroscience, King's College London, London, United Kingdom
| | - Terrie E Moffitt
- Department of Psychology and Neuroscience, Duke University, Durham, North Carolina; Department of Psychiatry and Behavioral Sciences, Duke University, Durham, North Carolina; Institute of Psychiatry, Psychology, & Neuroscience, King's College London, London, United Kingdom
| | - Ahmad R Hariri
- Department of Psychology and Neuroscience, Duke University, Durham, North Carolina.
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17
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Verweij KJH, Vink JM, Abdellaoui A, Gillespie NA, Derks EM, Treur JL. The genetic aetiology of cannabis use: from twin models to genome-wide association studies and beyond. Transl Psychiatry 2022; 12:489. [PMID: 36411281 PMCID: PMC9678872 DOI: 10.1038/s41398-022-02215-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 09/26/2022] [Accepted: 10/03/2022] [Indexed: 11/22/2022] Open
Abstract
Cannabis is among the most widely consumed psychoactive substances worldwide. Individual differences in cannabis use phenotypes can partly be explained by genetic differences. Technical and methodological advances have increased our understanding of the genetic aetiology of cannabis use. This narrative review discusses the genetic literature on cannabis use, covering twin, linkage, and candidate-gene studies, and the more recent genome-wide association studies (GWASs), as well as the interplay between genetic and environmental factors. Not only do we focus on the insights that these methods have provided on the genetic aetiology of cannabis use, but also on how they have helped to clarify the relationship between cannabis use and co-occurring traits, such as the use of other substances and mental health disorders. Twin studies have shown that cannabis use is moderately heritable, with higher heritability estimates for more severe phases of use. Linkage and candidate-gene studies have been largely unsuccessful, while GWASs so far only explain a small portion of the heritability. Dozens of genetic variants predictive of cannabis use have been identified, located in genes such as CADM2, FOXP2, and CHRNA2. Studies that applied multivariate methods (twin models, genetic correlation analysis, polygenic score analysis, genomic structural equation modelling, Mendelian randomisation) indicate that there is considerable genetic overlap between cannabis use and other traits (especially other substances and externalising disorders) and some evidence for causal relationships (most convincingly for schizophrenia). We end our review by discussing implications of these findings and suggestions for future work.
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Affiliation(s)
- Karin J. H. Verweij
- grid.7177.60000000084992262Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Meibergdreef 5, 1105 AZ Amsterdam, The Netherlands
| | - Jacqueline M. Vink
- grid.5590.90000000122931605Behavioural Science Institute, Radboud University Nijmegen, Thomas van Aquinostraat 4, 6525 GD Nijmegen, The Netherlands
| | - Abdel Abdellaoui
- grid.7177.60000000084992262Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Meibergdreef 5, 1105 AZ Amsterdam, The Netherlands
| | - Nathan A. Gillespie
- grid.224260.00000 0004 0458 8737Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, 800 East Leigh St, Suite 100, Richmond, VA 23219 USA
| | - Eske M. Derks
- grid.1049.c0000 0001 2294 1395Translational Neurogenomics, QIMR Berghofer Medical Research Institute, 300 Herston Road, Herston, QLD 4006 Australia
| | - Jorien L. Treur
- grid.7177.60000000084992262Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Meibergdreef 5, 1105 AZ Amsterdam, The Netherlands
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18
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Pan S, Kang H, Liu X, Lin S, Yuan N, Zhang Z, Bao Y, Jia P. Brain Catalog: a comprehensive resource for the genetic landscape of brain-related traits. Nucleic Acids Res 2022; 51:D835-D844. [PMID: 36243988 PMCID: PMC9825493 DOI: 10.1093/nar/gkac895] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 09/13/2022] [Accepted: 10/08/2022] [Indexed: 01/30/2023] Open
Abstract
A broad range of complex phenotypes are related to dysfunctions in brain (hereafter referred to as brain-related traits), including various mental and behavioral disorders and diseases of the nervous system. These traits in general share overlapping symptoms, pathogenesis, and genetic components. Here, we present Brain Catalog (https://ngdc.cncb.ac.cn/braincatalog), a comprehensive database aiming to delineate the genetic components of more than 500 GWAS summary statistics datasets for brain-related traits from multiple aspects. First, Brain Catalog provides results of candidate causal variants, causal genes, and functional tissues and cell types for each trait identified by multiple methods using comprehensive annotation datasets (58 QTL datasets spanning 6 types of QTLs). Second, Brain Catalog estimates the SNP-based heritability, the partitioning heritability based on functional annotations, and genetic correlations among traits. Finally, through bidirectional Mendelian randomization analyses, Brain Catalog presents inference of risk factors that are likely causal to each trait. In conclusion, Brain Catalog presents a one-stop shop for the genetic components of brain-related traits, potentially serving as a valuable resource for worldwide researchers to advance the understanding of how GWAS signals may contribute to the biological etiology of brain-related traits.
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Affiliation(s)
| | | | | | - Shiqi Lin
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China,College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100101, China
| | - Na Yuan
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Zhang Zhang
- Correspondence may also be addressed to Zhang Zhang.
| | - Yiming Bao
- Correspondence may also be addressed to Yiming Bao.
| | - Peilin Jia
- To whom correspondence should be addressed. Tel: +86 1084097798; ;
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19
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Chen W, Zeng Y, Suo C, Yang H, Chen Y, Hou C, Hu Y, Ying Z, Sun Y, Qu Y, Lu D, Fang F, Valdimarsdóttir UA, Song H. Genetic predispositions to psychiatric disorders and the risk of COVID-19. BMC Med 2022; 20:314. [PMID: 35999565 PMCID: PMC9397166 DOI: 10.1186/s12916-022-02520-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 08/08/2022] [Indexed: 12/03/2022] Open
Abstract
BACKGROUND Whether a genetic predisposition to psychiatric disorders is associated with coronavirus disease 2019 (COVID-19) is unknown. METHODS Our analytic sample consisted of 287,123 white British participants in UK Biobank who were alive on 31 January 2020. We performed a genome-wide association study (GWAS) analysis for each psychiatric disorder (substance misuse, depression, anxiety, psychotic disorder, and stress-related disorders) in a randomly selected half of the study population ("base dataset"). For the other half ("target dataset"), the polygenic risk score (PRS) was calculated as a proxy of individuals' genetic predisposition to a given psychiatric phenotype using discovered genetic variants from the base dataset. Ascertainment of COVID-19 was based on the Public Health England dataset, inpatient hospital data, or death registers in UK Biobank. COVID-19 cases from hospitalization records or death records were considered "severe cases." The association between the PRS for psychiatric disorders and COVID-19 risk was examined using logistic regression. We also repeated PRS analyses based on publicly available GWAS summary statistics. RESULTS A total of 143,562 participants (including 10,868 COVID-19 cases) were used for PRS analyses. A higher genetic predisposition to psychiatric disorders was associated with an increased risk of any COVID-19 and severe COVID-19. The adjusted odds ratio (OR) for any COVID-19 was 1.07 (95% confidence interval [CI] 1.02-1.13) and 1.06 (95% CI 1.01-1.11) among individuals with a high genetic risk (above the upper tertile of the PRS) for substance misuse and depression, respectively, compared with individuals with a low genetic risk (below the lower tertile). Slightly higher ORs were noted for severe COVID-19, and similar result patterns were obtained in analyses based on publicly available GWAS summary statistics. CONCLUSIONS Our findings suggest a potential role of genetic factors in the observed phenotypic association between psychiatric disorders and COVID-19. Our data underscore the need for increased medical surveillance for this vulnerable population during the COVID-19 pandemic.
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Affiliation(s)
- Wenwen Chen
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.,Med-X Center for Informatics, Sichuan University, Chengdu, China.,Division of Nephrology, Kidney Research Institute, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - Yu Zeng
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.,Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Chen Suo
- Department of Epidemiology & Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, China.
| | - Huazhen Yang
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.,Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Yilong Chen
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.,Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Can Hou
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.,Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Yao Hu
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.,Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Zhiye Ying
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.,Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Yajing Sun
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.,Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Yuanyuan Qu
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.,Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Donghao Lu
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.,Med-X Center for Informatics, Sichuan University, Chengdu, China.,Institute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden.,Department of Epidemiology, Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Fang Fang
- Institute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden
| | - Unnur A Valdimarsdóttir
- Institute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden.,Department of Epidemiology, Harvard T H Chan School of Public Health, Boston, MA, USA.,Center of Public Health Sciences, Faculty of Medicine, University of Iceland, Reykjavík, Iceland.,Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Huan Song
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China. .,Med-X Center for Informatics, Sichuan University, Chengdu, China. .,Center of Public Health Sciences, Faculty of Medicine, University of Iceland, Reykjavík, Iceland.
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20
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Cannabis Use in Autism: Reasons for Concern about Risk for Psychosis. Healthcare (Basel) 2022; 10:healthcare10081553. [PMID: 36011210 PMCID: PMC9407973 DOI: 10.3390/healthcare10081553] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 07/31/2022] [Accepted: 08/14/2022] [Indexed: 01/09/2023] Open
Abstract
Being particularly vulnerable to the pro-psychotic effects of cannabinoid exposure, autism spectrum individuals present with an increased risk of psychosis, which may be passed on to their own children. More specifically, cannabis exposure among autism spectrum individuals seems to exert disruptive epigenetic effects that can be intergenerationally inherited in brain areas which play a critical role in schizophrenia pathophysiology. Additionally, because of such cannabinoid-induced epigenetic effects, autism candidate genes present with bivalent chromatin markings which make them more vulnerable to subsequent disruption, possibly leading to psychosis onset later in life. Thus, findings support a developmental trajectory between autism and psychosis, as per endocannabinoid system modulation. However, such evidence has not received the attention it deserves.
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21
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Wormington B, Thorp JG, Scott JG, Derks EM. Influences on the Genetic Relationship Between Cannabis Use and Schizophrenia: The Role of the Externalizing Spectrum. Schizophr Bull 2022; 48:1318-1326. [PMID: 35925031 PMCID: PMC9673266 DOI: 10.1093/schbul/sbac095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
BACKGROUND AND HYPOTHESIS The nature of the robust association between cannabis use and schizophrenia remains undetermined. Plausible hypotheses explaining this relationship include the premise that cannabis use causes schizophrenia, increased liability for schizophrenia increases the risk of cannabis use initiation (eg, self-medication), or the bidirectional causal hypothesis where both factors play a role in the development of the other. Alternatively, factors that confound the relationship between schizophrenia and cannabis use may explain their association. Externalizing behaviors are related to both schizophrenia and cannabis use and may influence their relationship. STUDY DESIGN This study aimed to evaluate whether externalizing behaviors influence the genetic relationship between cannabis use and schizophrenia. We conducted a multivariate genome-wide association analysis of 6 externalizing behaviors in order to construct a genetic latent factor of the externalizing spectrum. Genomic structural equation modeling was used to evaluate the influence of externalizing behaviors on the genetic relationship between cannabis use and schizophrenia. RESULTS We found that externalizing behaviors partially explained the association between cannabis use and schizophrenia by up to 42%. CONCLUSIONS This partial explanation of the association by externalizing behaviors suggests that there may be other unidentified confounding factors, alongside a possible direct association between schizophrenia and cannabis use. Future studies should aim to identify further confounding factors to accurately explain the relationship between cannabis use and schizophrenia.
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Affiliation(s)
- Briar Wormington
- To whom correspondence should be addressed; Briar Wormington, QIMR Berghofer, 300 Herston Road, Herston, QLD 4006, e-mail:
| | - Jackson G Thorp
- QIMR Berghofer, Translational Neurogenomics Group, Herston, QLD, Australia,Faculty of Medicine, University of Queensland, Herston, QLD, Australia
| | - James G Scott
- Faculty of Medicine, University of Queensland, Herston, QLD, Australia,QIMR Berghofer, Child and Youth Mental Health, Herston, QLD, Australia,Metro North Mental Health Service, Brisbane, QLD, Australia
| | - Eske M Derks
- QIMR Berghofer, Translational Neurogenomics Group, Herston, QLD, Australia,Faculty of Medicine, University of Queensland, Herston, QLD, Australia
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22
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Marchi M, Elkrief L, Alkema A, van Gastel W, Schubart CD, van Eijk KR, Luykx JJ, Branje S, Mastrotheodoros S, Galeazzi GM, van Os J, Cecil CA, Conrod PJ, Boks MP. Childhood maltreatment mediates the effect of the genetic background on psychosis risk in young adults. Transl Psychiatry 2022; 12:219. [PMID: 35650188 PMCID: PMC9160238 DOI: 10.1038/s41398-022-01975-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Revised: 04/29/2022] [Accepted: 05/10/2022] [Indexed: 11/09/2022] Open
Abstract
Childhood maltreatment (CM) and genetic vulnerability are both risk factors for psychosis, but the relations between them are not fully understood. Guided by the recent identification of genetic risk to CM, this study investigates the hypothesis that genetic risk to schizophrenia also increases the risk of CM and thus impacts psychosis risk. The relationship between schizophrenia polygenetic risk, CM, and psychotic-like experiences (PLE) was investigated in participants from the Utrecht Cannabis Cohort (N = 1262) and replicated in the independent IMAGEN cohort (N = 1740). Schizophrenia polygenic risk score (SZ-PRS) were calculated from the most recent GWAS. The relationship between CM, PRS, and PLE was first investigated using multivariate linear regression. Next, mediation of CM in the pathway linking SZ-PRS and PLE was examined by structural equation modeling, while adjusting for a set of potential mediators including cannabis use, smoking, and neuroticism. In agreement with previous studies, PLE were strongly associated with SZ-PRS (B = 0.190, p = 0.009) and CM (B = 0.575, p < 0.001). Novel was that CM was also significantly associated with SZ-PRS (B = 0.171, p = 0.001), and substantially mediated the effects of SZ-PRS on PLE (proportion mediated = 29.9%, p = 0.001). In the replication cohort, the analyses yielded similar results, confirming equally strong mediation by CM (proportion mediated = 34.7%, p = 0.009). Our results suggest that CM acts as a mediator in the causal pathway linking SZ-PRS and psychosis risk. These findings open new perspectives on the relations between genetic and environmental risks and warrant further studies into potential interventions to reduce psychosis risk in vulnerable people.
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Affiliation(s)
- Mattia Marchi
- grid.7548.e0000000121697570Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Via Giuseppe Campi, 287 – 41125 Modena, Italy ,grid.5477.10000000120346234Department of Psychiatry, Brain Center University Medical Center Utrecht, University Utrecht, Utrecht, The Netherlands
| | - Laurent Elkrief
- grid.14848.310000 0001 2292 3357Department of Psychiatry, Université de Montréal, CHU Sainte-Justine Hospital, Montréal, QC Canada ,grid.411418.90000 0001 2173 6322Center Hospitalier Universitaire Sainte-Justine Research Center, Montreal, QC Canada
| | - Anne Alkema
- grid.5477.10000000120346234Department of Psychiatry, Brain Center University Medical Center Utrecht, University Utrecht, Utrecht, The Netherlands
| | - Willemijn van Gastel
- grid.5477.10000000120346234Department of Psychology, Utrecht University, Utrecht, The Netherlands
| | - Chris D. Schubart
- grid.413202.60000 0004 0626 2490Department of Psychiatry, Tergooi Hospital, Blaricum, The Netherlands
| | - Kristel R. van Eijk
- grid.5477.10000000120346234Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Jurjen J. Luykx
- grid.5477.10000000120346234Department of Psychiatry, Brain Center University Medical Center Utrecht, University Utrecht, Utrecht, The Netherlands
| | - Susan Branje
- grid.5477.10000000120346234Department of Youth and Family, Faculty of Social and Behavioral Sciences, Utrecht University, Utrecht, The Netherlands
| | - Stefanos Mastrotheodoros
- grid.5477.10000000120346234Department of Youth and Family, Faculty of Social and Behavioral Sciences, Utrecht University, Utrecht, The Netherlands ,grid.8127.c0000 0004 0576 3437Department of Psychology, University of Crete, Rethymno, Greece
| | - Gian M. Galeazzi
- grid.7548.e0000000121697570Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Via Giuseppe Campi, 287 – 41125 Modena, Italy ,Department of Mental Health and Addiction Services, Azienda USL-IRCCS di Reggio Emilia, Reggio Emilia, Italy
| | - Jim van Os
- grid.5477.10000000120346234Department of Psychiatry, Brain Center University Medical Center Utrecht, University Utrecht, Utrecht, The Netherlands
| | - Charlotte A. Cecil
- grid.5645.2000000040459992XDepartment of Child and Adolescent Psychiatry, Erasmus Medical Center, Sophia Children’s Hospital, University Medical Center Rotterdam, Rotterdam, The Netherlands ,grid.5645.2000000040459992XDepartment of Epidemiology, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Patricia J. Conrod
- grid.14848.310000 0001 2292 3357Department of Psychiatry, Université de Montréal, CHU Sainte-Justine Hospital, Montréal, QC Canada ,grid.411418.90000 0001 2173 6322Center Hospitalier Universitaire Sainte-Justine Research Center, Montreal, QC Canada
| | - Marco P. Boks
- grid.5477.10000000120346234Department of Psychiatry, Brain Center University Medical Center Utrecht, University Utrecht, Utrecht, The Netherlands
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23
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Colizzi M, Bortoletto R, Costa R, Bhattacharyya S, Balestrieri M. The Autism-Psychosis Continuum Conundrum: Exploring the Role of the Endocannabinoid System. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:5616. [PMID: 35565034 PMCID: PMC9105053 DOI: 10.3390/ijerph19095616] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 05/01/2022] [Accepted: 05/03/2022] [Indexed: 02/07/2023]
Abstract
Evidence indicates shared physiopathological mechanisms between autism and psychosis. In this regard, the endocannabinoid system has been suggested to modulate neural circuits during the early stage of neurodevelopment, with implications for both autism and psychosis. Nevertheless, such potential common markers of disease have been investigated in both autism and psychosis spectrum disorders, without considering the conundrum of differentiating the two groups of conditions in terms of diagnosis and treatment. Here, we systematically review all human and animal studies examining the endocannabinoid system and its biobehavioral correlates in the association between autism and psychosis. Studies indicate overlapping biobehavioral aberrancies between autism and schizophrenia, subject to correction by modulation of the endocannabinoid system. In addition, common cannabinoid-based pharmacological strategies have been identified, exerting epigenetic effects across genes controlling neural mechanisms shared between autism and schizophrenia. Interestingly, a developmental and transgenerational trajectory between autism and schizophrenia is supported by evidence that exogenous alteration of the endocannabinoid system promotes progression to inheritable psychosis phenotypes in the context of biobehavioral autism vulnerability. However, evidence for a diametral association between autism and psychosis is scant. Several clinical implications follow from evidence of a developmental continuum between autism and psychosis as a function of the endocannabinoid system dysregulation.
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Affiliation(s)
- Marco Colizzi
- Unit of Psychiatry, Department of Medicine (DAME), University of Udine, 33100 Udine, Italy;
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK;
| | - Riccardo Bortoletto
- Child and Adolescent Neuropsychiatry Unit, Maternal-Child Integrated Care Department, Integrated University Hospital of Verona, 37126 Verona, Italy;
| | - Rosalia Costa
- Community Mental Health Team, Friuli Centrale University Health Service (ASUFC), 33057 Palmanova, Italy;
| | - Sagnik Bhattacharyya
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK;
| | - Matteo Balestrieri
- Unit of Psychiatry, Department of Medicine (DAME), University of Udine, 33100 Udine, Italy;
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24
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Strong and weak cross-inheritance of substance use disorders in a nationally representative sample. Mol Psychiatry 2022; 27:1742-1753. [PMID: 34759357 PMCID: PMC9085976 DOI: 10.1038/s41380-021-01370-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/05/2021] [Revised: 10/18/2021] [Accepted: 10/19/2021] [Indexed: 12/21/2022]
Abstract
Substance use disorders (SUDs) are moderately to highly heritable and are in part cross-transmitted genetically, as observed in twin and family studies. We performed exome-focused genotyping to examine the cross-transmission of four SUDs: alcohol use disorder (AUD, n = 4487); nicotine use disorder (NUD, n = 4394); cannabis use disorder (CUD, n = 954); and nonmedical prescription opioid use disorder (NMPOUD, n = 346) within a large nationally representative sample (n = 36,309), the National Epidemiologic Survey on Alcohol and Related Conditions-III (NESARC-III). All diagnoses were based on in-person structured psychiatric interview (AUDADIS-5). SUD cases were compared alone and together to 3959 "super controls" who had neither a SUD nor a psychiatric disorder using an exome-focused array assaying 363,496 SNPs, yielding a representative view of within-disorder and cross-disorder genetic influences on SUDs. The 29 top susceptibility genes for one or more SUDs overlapped highly with genes previously implicated by GWAS of SUD. Polygenic scores (PGS) were computed within the European ancestry (EA) component of the sample (n = 12,505) using summary statistics from each of four clinically distinct SUDs compared to the 3959 "super controls" but then used for two distinctly different purposes: to predict SUD severity (mild, moderate, or severe) and to predict each of the other 3 SUDs. Our findings based on PGS highlight shared and unshared genetic contributions to the pathogenesis of SUDs, confirming the strong cross-inheritance of AUD and NUD as well as the distinctiveness of inheritance of opioid use disorder.
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25
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Blum K, McLaughlin T, Bowirrat A, Modestino EJ, Baron D, Gomez LL, Ceccanti M, Braverman ER, Thanos PK, Cadet JL, Elman I, Badgaiyan RD, Jalali R, Green R, Simpatico TA, Gupta A, Gold MS. Reward Deficiency Syndrome (RDS) Surprisingly Is Evolutionary and Found Everywhere: Is It "Blowin' in the Wind"? J Pers Med 2022; 12:jpm12020321. [PMID: 35207809 PMCID: PMC8875142 DOI: 10.3390/jpm12020321] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Revised: 02/14/2022] [Accepted: 02/17/2022] [Indexed: 12/04/2022] Open
Abstract
Reward Deficiency Syndrome (RDS) encompasses many mental health disorders, including a wide range of addictions and compulsive and impulsive behaviors. Described as an octopus of behavioral dysfunction, RDS refers to abnormal behavior caused by a breakdown of the cascade of reward in neurotransmission due to genetic and epigenetic influences. The resultant reward neurotransmission deficiencies interfere with the pleasure derived from satisfying powerful human physiological drives. Epigenetic repair may be possible with precision gene-guided therapy using formulations of KB220, a nutraceutical that has demonstrated pro-dopamine regulatory function in animal and human neuroimaging and clinical trials. Recently, large GWAS studies have revealed a significant dopaminergic gene risk polymorphic allele overlap between depressed and schizophrenic cohorts. A large volume of literature has also identified ADHD, PTSD, and spectrum disorders as having the known neurogenetic and psychological underpinnings of RDS. The hypothesis is that the true phenotype is RDS, and behavioral disorders are endophenotypes. Is it logical to wonder if RDS exists everywhere? Although complex, “the answer is blowin’ in the wind,” and rather than intangible, RDS may be foundational in species evolution and survival, with an array of many neurotransmitters and polymorphic loci influencing behavioral functionality.
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Affiliation(s)
- Kenneth Blum
- Division of Addiction Research & Education, Center for Psychiatry, Medicine, & Primary Care (Office of the Provost), Graduate College, Western University of Health Sciences, Pomona, CA 91766, USA;
- Institute of Psychology, ELTE Eötvös Loránd University, 1075 Budapest, Hungary
- Division of Nutrigenomics, The Kenneth Blum Behavioral Neurogenetic Institute, (Ivitalize, Inc.), Austin, TX 78701, USA; (L.L.G.); (E.R.B.); (R.J.); (R.G.)
- Department of Psychiatry, University of Vermont, Burlington, VT 05405, USA;
- Department of Psychiatry, Wright University Boonshoff School of Medicine, Dayton, OH 45324, USA
- Correspondence: ; Tel.: +1-619-890-2167
| | | | - Abdalla Bowirrat
- Department of Molecular Biology, Adelson School of Medicine, Ariel University, Ariel 40700, Israel;
| | | | - David Baron
- Division of Addiction Research & Education, Center for Psychiatry, Medicine, & Primary Care (Office of the Provost), Graduate College, Western University of Health Sciences, Pomona, CA 91766, USA;
| | - Luis Llanos Gomez
- Division of Nutrigenomics, The Kenneth Blum Behavioral Neurogenetic Institute, (Ivitalize, Inc.), Austin, TX 78701, USA; (L.L.G.); (E.R.B.); (R.J.); (R.G.)
| | - Mauro Ceccanti
- Alcohol Addiction Program, Latium Region Referral Center, Sapienza University of Rome, 00185 Roma, Italy;
| | - Eric R. Braverman
- Division of Nutrigenomics, The Kenneth Blum Behavioral Neurogenetic Institute, (Ivitalize, Inc.), Austin, TX 78701, USA; (L.L.G.); (E.R.B.); (R.J.); (R.G.)
| | - Panayotis K. Thanos
- Behavioral Neuropharmacology and Neuroimaging Laboratory on Addictions, Clinical Research Institute on Addictions, Department of Pharmacology and Toxicology, Jacobs School of Medicine and Biosciences, State University of New York at Buffalo, Buffalo, NY 14203, USA;
- Department of Psychology, State University of New York at Buffalo, Buffalo, NY 14203, USA
| | - Jean Lud Cadet
- Molecular Neuropsychiatry Research Branch, DHHS/NIH/NIDA Intramural Research Program, National Institutes of Health, Baltimore, MD 21224, USA;
| | - Igor Elman
- Center for Pain and the Brain (PAIN Group), Department of Anesthesiology, Critical Care & Pain Medicine, Boston Children’s Hospital, Boston, MA 02115, USA;
- Cambridge Health Alliance, Harvard Medical School, Cambridge, MA 02139, USA
| | - Rajendra D. Badgaiyan
- Department of Psychiatry, South Texas Veteran Health Care System, Audie L. Murphy Memorial VA Hospital, Long School of Medicine, University of Texas Health Science Center, San Antonio, TX 78229, USA;
- Department of Psychiatry, MT. Sinai School of Medicine, New York, NY 10003, USA
| | - Rehan Jalali
- Division of Nutrigenomics, The Kenneth Blum Behavioral Neurogenetic Institute, (Ivitalize, Inc.), Austin, TX 78701, USA; (L.L.G.); (E.R.B.); (R.J.); (R.G.)
| | - Richard Green
- Division of Nutrigenomics, The Kenneth Blum Behavioral Neurogenetic Institute, (Ivitalize, Inc.), Austin, TX 78701, USA; (L.L.G.); (E.R.B.); (R.J.); (R.G.)
| | | | - Ashim Gupta
- Future Biologics, Lawrenceville, GA 30043, USA;
| | - Mark S. Gold
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA;
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26
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Jones HJ, Hammerton G, McCloud T, Hines LA, Wright C, Gage SH, Holmans P, Jones PB, Smith GD, Linden DEJ, O'Donovan MC, Owen MJ, Walters JT, Munafò MR, Heron J, Zammit S. Examining pathways between genetic liability for schizophrenia and patterns of tobacco and cannabis use in adolescence. Psychol Med 2022; 52:132-139. [PMID: 32515721 PMCID: PMC7614952 DOI: 10.1017/s0033291720001798] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
BACKGROUND It is not clear to what extent associations between schizophrenia, cannabis use and cigarette use are due to a shared genetic etiology. We, therefore, examined whether schizophrenia genetic risk associates with longitudinal patterns of cigarette and cannabis use in adolescence and mediating pathways for any association to inform potential reduction strategies. METHODS Associations between schizophrenia polygenic scores and longitudinal latent classes of cigarette and cannabis use from ages 14 to 19 years were investigated in up to 3925 individuals in the Avon Longitudinal Study of Parents and Children. Mediation models were estimated to assess the potential mediating effects of a range of cognitive, emotional, and behavioral phenotypes. RESULTS The schizophrenia polygenic score, based on single nucleotide polymorphisms meeting a training-set p threshold of 0.05, was associated with late-onset cannabis use (OR = 1.23; 95% CI = 1.08,1.41), but not with cigarette or early-onset cannabis use classes. This association was not mediated through lower IQ, victimization, emotional difficulties, antisocial behavior, impulsivity, or poorer social relationships during childhood. Sensitivity analyses adjusting for genetic liability to cannabis or cigarette use, using polygenic scores excluding the CHRNA5-A3-B4 gene cluster, or basing scores on a 0.5 training-set p threshold, provided results consistent with our main analyses. CONCLUSIONS Our study provides evidence that genetic risk for schizophrenia is associated with patterns of cannabis use during adolescence. Investigation of pathways other than the cognitive, emotional, and behavioral phenotypes examined here is required to identify modifiable targets to reduce the public health burden of cannabis use in the population.
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Affiliation(s)
- Hannah J. Jones
- Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, UK
- Medical Research Centre (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, UK
- NIHR Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust, University of Bristol, Bristol, UK
| | - Gemma Hammerton
- Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, UK
- Medical Research Centre (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, UK
| | - Tayla McCloud
- Division of Psychiatry, University College London, London, UK
| | - Lindsey A. Hines
- Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, UK
| | - Caroline Wright
- Population Health Sciences, Bristol Medical School, University of Bristol, UK
| | - Suzanne H. Gage
- Department of Psychological Sciences, University of Liverpool, Liverpool, UK
| | - Peter Holmans
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, UK
| | - Peter B Jones
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - George Davey Smith
- Medical Research Centre (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, UK
| | - David E. J. Linden
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, UK
| | - Michael C. O'Donovan
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, UK
| | - Michael J. Owen
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, UK
| | - James T. Walters
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, UK
| | - Marcus R. Munafò
- Medical Research Centre (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, UK
- UK Centre for Tobacco and Alcohol Studies, School of Psychological Science, University of Bristol, UK
| | - Jon Heron
- Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, UK
- Medical Research Centre (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, UK
| | - Stanley Zammit
- Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, UK
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, UK
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27
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Becker J, Burik CAP, Goldman G, Wang N, Jayashankar H, Bennett M, Belsky DW, Karlsson Linnér R, Ahlskog R, Kleinman A, Hinds DA, Caspi A, Corcoran DL, Moffitt TE, Poulton R, Sugden K, Williams BS, Harris KM, Steptoe A, Ajnakina O, Milani L, Esko T, Iacono WG, McGue M, Magnusson PKE, Mallard TT, Harden KP, Tucker-Drob EM, Herd P, Freese J, Young A, Beauchamp JP, Koellinger PD, Oskarsson S, Johannesson M, Visscher PM, Meyer MN, Laibson D, Cesarini D, Benjamin DJ, Turley P, Okbay A. Resource profile and user guide of the Polygenic Index Repository. Nat Hum Behav 2021; 5:1744-1758. [PMID: 34140656 PMCID: PMC8678380 DOI: 10.1038/s41562-021-01119-3] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Accepted: 04/16/2021] [Indexed: 02/05/2023]
Abstract
Polygenic indexes (PGIs) are DNA-based predictors. Their value for research in many scientific disciplines is growing rapidly. As a resource for researchers, we used a consistent methodology to construct PGIs for 47 phenotypes in 11 datasets. To maximize the PGIs' prediction accuracies, we constructed them using genome-wide association studies-some not previously published-from multiple data sources, including 23andMe and UK Biobank. We present a theoretical framework to help interpret analyses involving PGIs. A key insight is that a PGI can be understood as an unbiased but noisy measure of a latent variable we call the 'additive SNP factor'. Regressions in which the true regressor is this factor but the PGI is used as its proxy therefore suffer from errors-in-variables bias. We derive an estimator that corrects for the bias, illustrate the correction, and make a Python tool for implementing it publicly available.
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Affiliation(s)
- Joel Becker
- Department of Economics, New York University, New York, NY, USA
| | - Casper A P Burik
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Grant Goldman
- National Bureau of Economic Research, Cambridge, MA, USA
| | - Nancy Wang
- National Bureau of Economic Research, Cambridge, MA, USA
| | | | | | - Daniel W Belsky
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA
- Robert N. Butler Columbia Aging Center, Columbia University, New York, NY, USA
| | - Richard Karlsson Linnér
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Rafael Ahlskog
- Department of Government, Uppsala University, Uppsala, Sweden
| | | | | | - Avshalom Caspi
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
- Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
| | - David L Corcoran
- Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
| | - Terrie E Moffitt
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
- Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
| | - Richie Poulton
- Dunedin Multidisciplinary Health and Development Research Unit, University of Otago, Dunedin, New Zealand
| | - Karen Sugden
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
| | | | - Kathleen Mullan Harris
- Department of Sociology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Andrew Steptoe
- Department of Behavioural Science and Health, University College London, London, UK
| | - Olesya Ajnakina
- Department of Behavioural Science and Health, University College London, London, UK
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Lili Milani
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Tõnu Esko
- Institute of Genomics, University of Tartu, Tartu, Estonia
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - William G Iacono
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Matt McGue
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Patrik K E Magnusson
- Swedish Twin Registry, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Travis T Mallard
- Department of Psychology, The University of Texas at Austin, Austin, TX, USA
| | - K Paige Harden
- Department of Psychology, The University of Texas at Austin, Austin, TX, USA
- Population Research Center, The University of Texas at Austin, Austin, TX, USA
| | - Elliot M Tucker-Drob
- Department of Psychology, The University of Texas at Austin, Austin, TX, USA
- Population Research Center, The University of Texas at Austin, Austin, TX, USA
| | - Pamela Herd
- McCourt School of Public Policy, Georgetown University, Washington, DC, USA
| | - Jeremy Freese
- Department of Sociology, Stanford University, Stanford, CA, USA
| | - Alexander Young
- UCLA Anderson School of Management, Los Angeles, CA, USA
- Human Genetics Department, UCLA David Geffen School of Medicine, Los Angeles, CA, USA
| | - Jonathan P Beauchamp
- Interdisciplinary Center for Economic Science and Department of Economics, George Mason University, Fairfax, VA, USA
| | - Philipp D Koellinger
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Robert M. La Follette School of Public Affairs, University of Wisconsin-Madison, Madison, WI, USA
| | - Sven Oskarsson
- Department of Government, Uppsala University, Uppsala, Sweden
| | - Magnus Johannesson
- Department of Economics, Stockholm School of Economics, Stockholm, Sweden
| | - Peter M Visscher
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Michelle N Meyer
- Center for Translational Bioethics and Health Care Policy, Geisinger Health System, Danville, PA, USA
| | - David Laibson
- National Bureau of Economic Research, Cambridge, MA, USA
- Department of Economics, Harvard University, Cambridge, MA, USA
| | - David Cesarini
- Department of Economics, New York University, New York, NY, USA.
- National Bureau of Economic Research, Cambridge, MA, USA.
| | - Daniel J Benjamin
- National Bureau of Economic Research, Cambridge, MA, USA.
- UCLA Anderson School of Management, Los Angeles, CA, USA.
- Human Genetics Department, UCLA David Geffen School of Medicine, Los Angeles, CA, USA.
| | - Patrick Turley
- Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA.
- Department of Economics, University of Southern California, Los Angeles, CA, USA.
| | - Aysu Okbay
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
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28
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A Randomized Controlled Trial to Evaluate the Safety and Efficacy of a Novel Inhaled Biologic Therapeutic in Adults with Respiratory Distress Secondary to COVID-19 Infection. Infect Dis Ther 2021; 11:595-605. [PMID: 34775578 PMCID: PMC8590808 DOI: 10.1007/s40121-021-00562-z] [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: 10/06/2021] [Accepted: 10/29/2021] [Indexed: 12/15/2022] Open
Abstract
INTRODUCTION Inhaled therapeutics may act to directly target and attenuate lung inflammation due to COVID-19. An inhalation form of a novel biologic drug, AMP5A, is being developed as an immunomodulatory agent to treat dysregulated immune responses and is being studied in hospitalized patients to treat respiratory complications due to COVID-19. METHODS A randomized, controlled, phase I trial was conducted to evaluate hospitalized adults with respiratory distress secondary to COVID-19. Patients received the standard care (SOC) for COVID-19, including respiratory therapy, corticosteroids, and antiviral therapies such as remdesivir. Patients were randomized 1:1 to inhalation treatment with AMP5A as an adjunct to SOC or to SOC alone (control). AMP5A was administered via inhalation daily for 5 days via hand-held nebulizer, non-invasive ventilator, or mechanical ventilation. Safety and clinical efficacy endpoints were evaluated. RESULTS Forty subjects were enrolled and randomized (n = 19 AMP5A, n = 21 control). Remdesivir was used in fewer AMP5A subjects (26%) than control (52%), and dexamethasone was administered for most subjects (84% AMP5A, 71% control). The study met its primary endpoint with no AMP5A treatment-related adverse events (AEs), and the incidence and severity of AEs were comparable between groups: 18 AEs for control (8 mild, 1 moderate, 9 severe) and 19 AEs for AMP5A (7 mild, 7 moderate, 5 severe). Notably, subjects treated with AMP5A had fewer deaths (5% vs. 24%), shorter hospital stay (8 days vs. 12 days), fewer ICU admissions (21% vs. 33%), and a greater proportion with improved clinical outcomes than control. CONCLUSION The phase I clinical results indicate inhaled AMP5A is safe, is well tolerated, and could lead to fewer patients experiencing deterioration or death. Based on the treatment effect (i.e., reduced mortality), a phase II trial has been initiated. TRIAL REGISTRATION Clinicaltrials.gov identifier: NCT04606784.
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29
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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.
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30
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Arends RM, Pasman JA, Verweij KJ, Derks EM, Gordon SD, Hickie I, Thomas NS, Aliev F, Zietsch BP, Zee MD, Mitchell BL, Martin NG, Dick DM, Gillespie NA, Geus EJ, Boomsma DI, Schellekens AF, Vink JM. Associations between the CADM2 gene, substance use, risky sexual behavior, and self-control: A phenome-wide association study. Addict Biol 2021; 26:e13015. [PMID: 33604983 PMCID: PMC8596397 DOI: 10.1111/adb.13015] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Revised: 11/05/2020] [Accepted: 01/15/2021] [Indexed: 01/15/2023]
Abstract
Risky behaviors, such as substance use and unprotected sex, are associated with various physical and mental health problems. Recent genome-wide association studies indicated that variation in the cell adhesion molecule 2 (CADM2) gene plays a role in risky behaviors and self-control. In this phenome-wide scan for risky behavior, it was tested if underlying common vulnerability could be (partly) explained by pleiotropic effects of this gene and how large the effects were. Single nucleotide polymorphism (SNP)-level and gene-level association tests within four samples (25 and Up, Spit for Science, Netherlands Twin Register, and UK Biobank and meta-analyses over all samples (combined sample of 362,018 participants) were conducted to test associations between CADM2, substance- and sex-related risk behaviors, and various measures related to self-control. We found significant associations between the CADM2 gene, various risky behaviors, and different measures of self-control. The largest effect sizes were found for cannabis use, sensation seeking, and disinhibition. Effect sizes ranged from 0.01% to 0.26% for single top SNPs and from 0.07% to 3.02% for independent top SNPs together, with sufficient power observed only in the larger samples and meta-analyses. In the largest cohort, we found indications that risk-taking proneness mediated the association between CADM2 and latent factors for lifetime smoking and regular alcohol use. This study extends earlier findings that CADM2 plays a role in risky behaviors and self-control. It also provides insight into gene-level effect sizes and demonstrates the feasibility of testing mediation. These findings present a good starting point for investigating biological etiological pathways underlying risky behaviors.
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Affiliation(s)
- Rachel M. Arends
- Department of Psychiatry Radboud University Medical Center The Netherlands
- Donders Center for Medical Neuroscience Donders Institute for Brain, Cognition and Behavior The Netherlands
- Tactus Addiction Care The Netherlands
| | - Joëlle A. Pasman
- Behavioural Science Institute Radboud University The Netherlands
| | - Karin J.H. Verweij
- Faculty of Medicine Amsterdam Medical Centre and University of Amsterdam The Netherlands
| | - Eske M. Derks
- Genetic Epidemiology, Statistical Genetics and Translational Neurogenomics Laboratories QIMR Berghofer Medical Research Institute Australia
| | - Scott D. Gordon
- Genetic Epidemiology, Statistical Genetics and Translational Neurogenomics Laboratories QIMR Berghofer Medical Research Institute Australia
| | - Ian Hickie
- Brain and Mind Centre University of Sydney Australia
| | | | - Fazil Aliev
- Faculty of Business Karbük University Turkey
- Department of African American Studies Virginia Commonwealth University Richmond VA USA
| | - Brendan P. Zietsch
- School of Medicine and School of Psychology University of Queensland Australia
| | - Matthijs D. Zee
- Department of Biological Psychology Vrije Universiteit Amsterdam The Netherlands
- Netherlands Twin Register The Netherlands
| | - Brittany L. Mitchell
- Department of Genetics and Computational Biology QIMR Berghofer Medical Research Institute Australia
- School of Biomedical Sciences and Institute of Health and Biomedical Innovation Queensland University of Technology Australia
| | - Nicholas G. Martin
- Genetic Epidemiology, Statistical Genetics and Translational Neurogenomics Laboratories QIMR Berghofer Medical Research Institute Australia
- School of Medicine and School of Psychology University of Queensland Australia
| | - Danielle M. Dick
- Department of Psychology Virginia Commonwealth University Richmond VA USA
| | - Nathan A. Gillespie
- Genetic Epidemiology, Statistical Genetics and Translational Neurogenomics Laboratories QIMR Berghofer Medical Research Institute Australia
- School of Medicine and School of Psychology University of Queensland Australia
- Virginia Institute for Psychiatric and Behavior Genetics, Department of Psychiatry Virginia Commonwealth University Richmond VA USA
| | - Eco J.C. Geus
- Faculty of Medicine Amsterdam Medical Centre and University of Amsterdam The Netherlands
- Netherlands Twin Register The Netherlands
| | - Dorret I. Boomsma
- Faculty of Medicine Amsterdam Medical Centre and University of Amsterdam The Netherlands
- Department of Biological Psychology Vrije Universiteit Amsterdam The Netherlands
- Netherlands Twin Register The Netherlands
| | - Arnt F.A. Schellekens
- Department of Psychiatry Radboud University Medical Center The Netherlands
- Donders Center for Medical Neuroscience Donders Institute for Brain, Cognition and Behavior The Netherlands
- Nijmegen Institute for Scientist‐Practitioners in Addiction The Netherlands
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Brick LA, Benca-Bachman CE, Bertin L, Martin KP, Risner V, Palmer RHC. The intermediary role of adolescent temperamental and behavioral traits on the prospective associations between polygenic risk and cannabis use among young adults of European Ancestry. Addiction 2021; 116:2779-2789. [PMID: 33686717 PMCID: PMC8426427 DOI: 10.1111/add.15476] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Revised: 10/14/2020] [Accepted: 02/24/2021] [Indexed: 11/30/2022]
Abstract
BACKGROUND AND AIMS Cannabis use (CU) is an etiologically complex behavior with several social, temperamental, neurocognitive, and behavioral precursors. Biometrical and molecular studies suggest an interplay of environmental and pleiotropic influences. However, it remains unclear whether identified genetic effects related to behavioral and temperamental characteristics have developmentally direct or indirect mechanisms on CU behavior. The Transmissible Liability Index (TLI) is a measure of continuous liability based on developmental precursors of substance use disorders. This study aimed to examine if the TLI plays a role in understanding genetic risk for CU behaviors. DESIGN Genome-wide association studies (n > 10 000; European Ancestry [EA]) of CU, risk tolerance, neuroticism, anxiety, and depression were used to construct polygenic scores (PGSs). Analyses assessed whether PGSs indirectly impacted risk for repeated use via TLI. SETTING United States of America. PARTICIPANTS From Add Health study, 4077 individuals of EA age 11 to 21 during baseline interview collection. MEASUREMENTS Outcomes were initiation and repeated cannabis use (>5× in lifetime). The TLI was parameterized using a latent factor from 21 questions assessing for precursors of disordered use. FINDINGS The marker-based heritability of TLI, initiation, and repeated use were significant, but modest (14%, P = 0.033; 15%, P = 0.025; and 17%, P = 0.008, respectively). TLI and repeated use were genetically correlated (rg = 0.76, P = 0.033). The PGS for CU was associated with increased risk for repeated use and PGS for risk tolerance and depression were associated with TLI. Mediation analyses indicated significant, but very weak, indirect effects of PGS for risk tolerance and depression on repeated CU via the TLI. CONCLUSIONS Adolescent behavioral and temperamental characteristics (i.e. the Transmissible Liability Index) appear to be early indicators of repeated cannabis use in adulthood. Although polygenic scores for cannabis use directly increased risk for repeated cannabis use, weak evidence was found for the role of polygenic scores of other internalizing/externalizing traits acting through adolescent derived Transmissible Liability Index on cannabis use behavior.
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Affiliation(s)
- Leslie A Brick
- Behavioral Genetics of Addiction Laboratory, Department of Psychology at Emory University, Atlanta, Georgia, USA,Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Chelsie E Benca-Bachman
- Behavioral Genetics of Addiction Laboratory, Department of Psychology at Emory University, Atlanta, Georgia, USA
| | - Lauren Bertin
- Behavioral Genetics of Addiction Laboratory, Department of Psychology at Emory University, Atlanta, Georgia, USA
| | - Kathleen P Martin
- Behavioral Genetics of Addiction Laboratory, Department of Psychology at Emory University, Atlanta, Georgia, USA
| | - Victoria Risner
- Behavioral Genetics of Addiction Laboratory, Department of Psychology at Emory University, Atlanta, Georgia, USA
| | - Rohan HC Palmer
- Behavioral Genetics of Addiction Laboratory, Department of Psychology at Emory University, Atlanta, Georgia, USA
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32
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Masroor A, Khorochkov A, Prieto J, Singh KB, Nnadozie MC, Abdal M, Shrestha N, Abe RAM, Mohammed L. Unraveling the Association Between Schizophrenia and Substance Use Disorder-Predictors, Mechanisms and Treatment Modifications: A Systematic Review. Cureus 2021; 13:e16722. [PMID: 34513357 PMCID: PMC8405179 DOI: 10.7759/cureus.16722] [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: 06/19/2021] [Accepted: 07/28/2021] [Indexed: 11/05/2022] Open
Abstract
Individuals with schizophrenia are particularly vulnerable to substance abuse problems. Comorbidity with substance use disorders (SUDs) frequently results in early death and increased dysfunction observed in schizophrenia. This dual diagnosis can be explained through multiple general mechanisms. Tobacco, alcohol, cannabis, and cocaine are substances widely used by individuals with schizophrenia. This study highlights the predictors, mechanisms responsible for the relationship between substance use disorder and schizophrenia and how it can help with the treatment of both disorders. The publications were rigorously reviewed after being found in multiple databases. The study's inclusion criteria were research published within the last five years, publications written in English, full-text availability, and human studies. A total of ten papers were selected for examination from a total of 9,106 articles found using the search method across several databases. This study follows the rules listed within the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist 2009. The information gathered from these published studies was used to investigate the elements that contribute to the link between schizophrenia and substance abuse. Here, we evaluate a close relationship between schizophrenia and substance use disorders. The articles studied exhibit a bidirectional association between the two disorders in most individuals. From our analysis, the comorbidity between the two disorders is partially due to shared polygenic liability. Individuals with schizophrenia have dysfunctional Mesocorticolimbic brain reward circuits indicating a history of substance use. An underlying genetic vulnerability to schizophrenia may be triggered by extensive cannabis usage at a young age. A combination of psychological and pharmacological interventions for both disorders can significantly improve the outcome.
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Affiliation(s)
- Anum Masroor
- Psychiatry, California Institute of Behavioral Neurosciences & Psychology, Fairfield, USA.,Psychiatry, Psychiatric Care Associates, Englewood, USA.,Medicine, Khyber Medical College, Peshawar, PAK
| | - Arseni Khorochkov
- Internal Medicine, California Institute of Behavioral Neurosciences & Psychology, Fairfield, USA
| | - Jose Prieto
- Internal Medicine, California Institute of Behavioral Neurosciences & Psychology, Fairfield, USA
| | - Karan B Singh
- Internal Medicine, California Institute of Behavioral Neurosciences & Psychology, Fairfield, USA
| | - Maduka C Nnadozie
- Research, California Institute of Behavioral Neurosciences & Psychology, Fairfield, USA
| | - Muhammad Abdal
- Emergency Medicine, California Institute of Behavioral Neurosciences & Psychology, Fairfield, USA
| | - Niki Shrestha
- Research, California Institute of Behavioral Neurosciences & Psychology, Fairfield, USA
| | - Rose Anne M Abe
- Research, California Institute of Behavioral Neurosciences & Psychology, Fairfield, USA
| | - Lubna Mohammed
- Internal Medicine, California Institute of Behavioral Neurosciences & Psychology, Fairfield, USA
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33
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Zhao J, Chen H, Zhuo C, Xia S. Cannabis Use and the Risk of Cardiovascular Diseases: A Mendelian Randomization Study. Front Cardiovasc Med 2021; 8:676850. [PMID: 34409073 PMCID: PMC8366226 DOI: 10.3389/fcvm.2021.676850] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Accepted: 07/02/2021] [Indexed: 12/02/2022] Open
Abstract
Several observational studies have shown that cannabis use has negative effects on the cardiovascular system, but the causality of this relationship has not been confirmed. The aim of the current study was to estimate the effects of genetically determined cannabis use on risk of cardiovascular diseases. Ten single-nucleotide polymorphisms related to cannabis use were employed as instruments to estimate the association between genetically determined cannabis use and risk of cardiovascular diseases using a two-sample Mendelian randomization (MR) method. Summary statistics data on exposure and outcomes were obtained from different genome-wide association meta-analysis studies. The results of this MR analysis showed no causal effects of cannabis use on the risk of several common cardiovascular diseases, including coronary artery disease, myocardial infarction, stroke and ischemic stroke subtypes, atrial fibrillation (AF), and heart failure. Various sensitivity analyses yielded similar results, and no heterogeneity and directional pleiotropy were observed. After adjusting for tobacco use and body mass index, multivariable MR analysis suggested a causal effect of cannabis use on small vessel stroke (SVS) [odds ratio (OR) 1.17; 95% CI 1.02–1.35; p = 0.03] and AF (OR 1.06; 95% CI 1.01–1.10; p = 0.01), respectively. This two-sample MR study did not demonstrate a causal effect of genetic predisposition to cannabis use on several common cardiovascular outcomes. After adjusting for tobacco use and body mass index, the multivariable MR analysis suggested a detrimental effect of cannabis use on the risk of SVS and AF, respectively.
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Affiliation(s)
- Jianqiang Zhao
- Department of Cardiology, The Fourth Affiliated Hospital of Zhejiang University School of Medicine, Yiwu, China
| | - Heng Chen
- Department of Cardiology, The First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Chengui Zhuo
- Department of Cardiology, Taizhou Central Hospital, Taizhou University Hospital, Taizhou, China
| | - Shudong Xia
- Department of Cardiology, The Fourth Affiliated Hospital of Zhejiang University School of Medicine, Yiwu, China
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Hillmer A, Chawar C, Sanger S, D’Elia A, Butt M, Kapoor R, Kapczinski F, Thabane L, Samaan Z. Genetic basis of cannabis use: a systematic review. BMC Med Genomics 2021; 14:203. [PMID: 34384432 PMCID: PMC8359088 DOI: 10.1186/s12920-021-01035-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 07/15/2021] [Indexed: 01/19/2023] Open
Abstract
BACKGROUND With the increase in cannabis use rates, cannabis use disorder is being reported as one of the most common drug use disorders globally. Cannabis use has several known physical, psychological, and social adverse events, such as altered judgement, poor educational outcomes, and respiratory symptoms. The propensity for taking cannabis and the development of a cannabis use disorder may be genetically influenced for some individuals. Heritability estimates suggest a genetic basis for cannabis use, and several genome-wide association studies (GWASs) have identified possible regions of association, albeit with inconsistent findings. This systematic review aims to summarize the findings from GWASs investigating cannabis use and cannabis use disorder. METHODS This systematic review incorporates articles that have performed a GWAS investigating cannabis use or cannabis use disorder. MEDLINE, Web of Science, EMBASE, CINAHL, GWAS Catalog, GWAS Central, and NIH Database of Genotype and Phenotype were searched using a comprehensive search strategy. All studies were screened in duplicate, and the quality of evidence was assessed using the quality of genetic association studies (Q-Genie) tool. All studies underwent qualitative synthesis; however, quantitative analysis was not feasible. RESULTS Our search identified 5984 articles. Six studies met our eligibility criteria and were included in this review. All six studies reported results that met our significance threshold of p ≤ 1.0 × 10-7. In total 96 genetic variants were identified. While meta-analysis was not possible, this review identified the following genes, ANKFN1, INTS7, PI4K2B, CSMD1, CST7, ACSS1, and SCN9A, to be associated with cannabis use. These regions were previously reported in different mental health conditions, however not in relation to cannabis use. CONCLUSION This systematic review summarized GWAS findings within the field of cannabis research. While a meta-analysis was not possible, the summary of findings serves to inform future candidate gene studies and replication efforts. Systematic Review Registration PROSPERO CRD42020176016.
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Affiliation(s)
- Alannah Hillmer
- Neuroscience Graduate Program, Department of Psychiatry and Behavioural Neurosciences, McMaster University, 100 West 5th St., Hamilton, ON L8N 3K7 Canada
| | - Caroul Chawar
- Neuroscience Graduate Program, Department of Psychiatry and Behavioural Neurosciences, McMaster University, 100 West 5th St., Hamilton, ON L8N 3K7 Canada
| | - Stephanie Sanger
- Health Science Library, McMaster University, 1280 Main St. W., Hamilton, ON L8S 4L8 Canada
| | - Alessia D’Elia
- Neuroscience Graduate Program, Department of Psychiatry and Behavioural Neurosciences, McMaster University, 100 West 5th St., Hamilton, ON L8N 3K7 Canada
| | - Mehreen Butt
- Integrated Science Program, McMaster University, 1280 Main St. W., Hamilton, ON L8S 4L8 Canada
| | - Raveena Kapoor
- Michael G. DeGroote School of Medicine, McMaster University, 1280 Main St. W., Hamilton, ON L8S 4L8 Canada
| | - Flavio Kapczinski
- Neuroscience Graduate Program, Department of Psychiatry and Behavioural Neurosciences, McMaster University, 100 West 5th St., Hamilton, ON L8N 3K7 Canada
| | - Lehana Thabane
- Department of Health Research Method, Evidence and Impact, 1280 Main St. W., Hamilton, ON L8S 4L8 Canada
| | - Zainab Samaan
- Neuroscience Graduate Program, Department of Psychiatry and Behavioural Neurosciences, McMaster University, 100 West 5th St., Hamilton, ON L8N 3K7 Canada
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Parks C, Rogers CM, Prins P, Williams RW, Chen H, Jones BC, Moore BM, Mulligan MK. Genetic Modulation of Initial Sensitivity to Δ9-Tetrahydrocannabinol (THC) Among the BXD Family of Mice. Front Genet 2021; 12:659012. [PMID: 34367237 PMCID: PMC8343140 DOI: 10.3389/fgene.2021.659012] [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: 01/26/2021] [Accepted: 04/08/2021] [Indexed: 11/16/2022] Open
Abstract
Cannabinoid receptor 1 activation by the major psychoactive component in cannabis, Δ9-tetrahydrocannabinol (THC), produces motor impairments, hypothermia, and analgesia upon acute exposure. In previous work, we demonstrated significant sex and strain differences in acute responses to THC following administration of a single dose (10 mg/kg, i.p.) in C57BL/6J (B6) and DBA/2J (D2) inbred mice. To determine the extent to which these differences are heritable, we quantified acute responses to a single dose of THC (10 mg/kg, i.p.) in males and females from 20 members of the BXD family of inbred strains derived by crossing and inbreeding B6 and D2 mice. Acute THC responses (initial sensitivity) were quantified as changes from baseline for: 1. spontaneous activity in the open field (mobility), 2. body temperature (hypothermia), and 3. tail withdrawal latency to a thermal stimulus (antinociception). Initial sensitivity to the immobilizing, hypothermic, and antinociceptive effects of THC varied substantially across the BXD family. Heritability was highest for mobility and hypothermia traits, indicating that segregating genetic variants modulate initial sensitivity to THC. We identified genomic loci and candidate genes, including Ndufs2, Scp2, Rps6kb1 or P70S6K, Pde4d, and Pten, that may control variation in THC initial sensitivity. We also detected strong correlations between initial responses to THC and legacy phenotypes related to intake or response to other drugs of abuse (cocaine, ethanol, and morphine). Our study demonstrates the feasibility of mapping genes and variants modulating THC responses in the BXDs to systematically define biological processes and liabilities associated with drug use and abuse.
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Affiliation(s)
- Cory Parks
- Department of Genetics, Genomics and Informatics, The University of Tennessee Health Science Center, Memphis, TN, United States
- Department of Agriculture, Biology and Health Sciences, Cameron University, Lawton, OK, United States
| | - Chris M. Rogers
- Department of Genetics, Genomics and Informatics, The University of Tennessee Health Science Center, Memphis, TN, United States
| | - Pjotr Prins
- Department of Genetics, Genomics and Informatics, The University of Tennessee Health Science Center, Memphis, TN, United States
| | - Robert W. Williams
- Department of Genetics, Genomics and Informatics, The University of Tennessee Health Science Center, Memphis, TN, United States
| | - Hao Chen
- Department of Pharmacology, Addiction Science and Toxicology, The University of Tennessee Health Science Center, Memphis, TN, United States
| | - Byron C. Jones
- Department of Genetics, Genomics and Informatics, The University of Tennessee Health Science Center, Memphis, TN, United States
| | - Bob M. Moore
- Department of Pharmaceutical Sciences, The University of Tennessee Health Science Center, Memphis, TN, United States
| | - Megan K. Mulligan
- Department of Genetics, Genomics and Informatics, The University of Tennessee Health Science Center, Memphis, TN, United States
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36
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Treur JL, Munafò MR, Logtenberg E, Wiers RW, Verweij KJH. Using Mendelian randomization analysis to better understand the relationship between mental health and substance use: a systematic review. Psychol Med 2021; 51:1593-1624. [PMID: 34030749 PMCID: PMC8327626 DOI: 10.1017/s003329172100180x] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Revised: 04/17/2021] [Accepted: 04/21/2021] [Indexed: 12/18/2022]
Abstract
BACKGROUND Poor mental health has consistently been associated with substance use (smoking, alcohol drinking, cannabis use, and consumption of caffeinated drinks). To properly inform public health policy it is crucial to understand the mechanisms underlying these associations, and most importantly, whether or not they are causal. METHODS In this pre-registered systematic review, we assessed the evidence for causal relationships between mental health and substance use from Mendelian randomization (MR) studies, following PRISMA. We rated the quality of included studies using a scoring system that incorporates important indices of quality, such as the quality of phenotype measurement, instrument strength, and use of sensitivity methods. RESULTS Sixty-three studies were included for qualitative synthesis. The final quality rating was '-' for 16 studies, '- +' for 37 studies, and '+'for 10 studies. There was robust evidence that higher educational attainment decreases smoking and that there is a bi-directional, increasing relationship between smoking and (symptoms of) mental disorders. Another robust finding was that higher educational attainment increases alcohol use frequency, but decreases binge-drinking and alcohol use problems, and that mental disorders causally lead to more alcohol drinking without evidence for the reverse. CONCLUSIONS The current MR literature increases our understanding of the relationship between mental health and substance use. Bi-directional causal relationships are indicated, especially for smoking, providing further incentive to strengthen public health efforts to decrease substance use. Future MR studies should make use of large(r) samples in combination with detailed phenotypes, a wide range of sensitivity methods, and triangulate with other research methods.
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Affiliation(s)
- Jorien L. Treur
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
- Addiction Development and Psychopathology (ADAPT) Lab, Department of Psychology, University of Amsterdam, Amsterdam, the Netherlands
| | - Marcus R. Munafò
- School of Psychological Science, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, the University of Bristol, Bristol, UK
| | - Emma Logtenberg
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Reinout W. Wiers
- Addiction Development and Psychopathology (ADAPT) Lab, Department of Psychology, University of Amsterdam, Amsterdam, the Netherlands
- Center for Urban Mental Health, University of Amsterdam, Amsterdam, the Netherlands
| | - Karin J. H. Verweij
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
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Jugl S, Okpeku A, Costales B, Morris EJ, Alipour-Haris G, Hincapie-Castillo JM, Stetten NE, Sajdeya R, Keshwani S, Joseph V, Zhang Y, Shen Y, Adkins L, Winterstein AG, Goodin A. A Mapping Literature Review of Medical Cannabis Clinical Outcomes and Quality of Evidence in Approved Conditions in the USA from 2016 to 2019. Med Cannabis Cannabinoids 2021; 4:21-42. [PMID: 34676348 PMCID: PMC8525213 DOI: 10.1159/000515069] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Accepted: 02/03/2021] [Indexed: 12/15/2022] Open
Abstract
In 2017, a National Academies of Sciences, Engineering, and Medicine (NASEM) report comprehensively evaluated the body of evidence regarding cannabis health effects through the year 2016. The objectives of this study are to identify and map the most recently (2016-2019) published literature across approved conditions for medical cannabis and to evaluate the quality of identified recent systematic reviews, published following the NASEM report. Following the literature search from 5 databases and consultation with experts, 11 conditions were identified for evidence compilation and evaluation: amyotrophic lateral sclerosis, autism, cancer, chronic noncancer pain, Crohn's disease, epilepsy, glaucoma, human immunodeficiency virus/AIDS, multiple sclerosis (MS), Parkinson's disease, and posttraumatic stress disorder. A total of 198 studies were included after screening for condition-specific relevance and after imposing the following exclusion criteria: preclinical focus, non-English language, abstracts only, editorials/commentary, case studies/series, and non-U.S. study setting. Data extracted from studies included: study design type, outcome definition, intervention definition, sample size, study setting, and reported effect size. Few completed randomized controlled trials (RCTs) were identified. Studies classified as systematic reviews were graded using the Assessing the Methodological Quality of Systematic Reviews-2 tool to evaluate the quality of evidence. Few high-quality systematic reviews were available for most conditions, with the exceptions of MS (9 of 9 graded moderate/high quality; evidence for 2/9 indicating cannabis improved outcomes; evidence for 7/9 indicating cannabis inconclusive), epilepsy (3 of 4 graded moderate/high quality; 3 indicating cannabis improved outcomes; 1 indicating cannabis inconclusive), and chronic noncancer pain (12 of 13 graded moderate/high quality; evidence for 7/13 indicating cannabis improved outcomes; evidence from 6/7 indicating cannabis inconclusive). Among RCTs, we identified few studies of substantial rigor and quality to contribute to the evidence base. However, there are some conditions for which significant evidence suggests that select dosage forms and routes of administration likely have favorable risk-benefit ratios (i.e., epilepsy and chronic noncancer pain). The body of evidence for medical cannabis requires more rigorous evaluation before consideration as a treatment option for many conditions, and evidence necessary to inform policy and treatment guidelines is currently insufficient for many conditions.
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Affiliation(s)
- Sebastian Jugl
- Pharmaceutical Outcomes and Policy, University of Florida, Gainesville, Florida, USA
- Center for Drug Evaluation and Safety (CoDES), University of Florida, Gainesville, Florida, USA
| | - Aimalohi Okpeku
- Pharmaceutical Outcomes and Policy, University of Florida, Gainesville, Florida, USA
- Center for Drug Evaluation and Safety (CoDES), University of Florida, Gainesville, Florida, USA
| | - Brianna Costales
- Pharmaceutical Outcomes and Policy, University of Florida, Gainesville, Florida, USA
- Center for Drug Evaluation and Safety (CoDES), University of Florida, Gainesville, Florida, USA
| | - Earl J. Morris
- Pharmaceutical Outcomes and Policy, University of Florida, Gainesville, Florida, USA
- Center for Drug Evaluation and Safety (CoDES), University of Florida, Gainesville, Florida, USA
| | - Golnoosh Alipour-Haris
- Pharmaceutical Outcomes and Policy, University of Florida, Gainesville, Florida, USA
- Center for Drug Evaluation and Safety (CoDES), University of Florida, Gainesville, Florida, USA
| | - Juan M. Hincapie-Castillo
- Pharmaceutical Outcomes and Policy, University of Florida, Gainesville, Florida, USA
- Center for Drug Evaluation and Safety (CoDES), University of Florida, Gainesville, Florida, USA
| | | | - Ruba Sajdeya
- Epidemiology, University of Florida, Gainesville, Florida, USA
| | - Shailina Keshwani
- Pharmaceutical Outcomes and Policy, University of Florida, Gainesville, Florida, USA
- Center for Drug Evaluation and Safety (CoDES), University of Florida, Gainesville, Florida, USA
| | - Verlin Joseph
- Epidemiology, University of Florida, Gainesville, Florida, USA
| | - Yahan Zhang
- Pharmaceutical Outcomes and Policy, University of Florida, Gainesville, Florida, USA
- Center for Drug Evaluation and Safety (CoDES), University of Florida, Gainesville, Florida, USA
| | - Yun Shen
- Pharmaceutical Outcomes and Policy, University of Florida, Gainesville, Florida, USA
- Center for Drug Evaluation and Safety (CoDES), University of Florida, Gainesville, Florida, USA
| | - Lauren Adkins
- Health Sciences Center Libraries, University of Florida, Gainesville, Florida, USA
| | - Almut G. Winterstein
- Pharmaceutical Outcomes and Policy, University of Florida, Gainesville, Florida, USA
- Center for Drug Evaluation and Safety (CoDES), University of Florida, Gainesville, Florida, USA
| | - Amie Goodin
- Pharmaceutical Outcomes and Policy, University of Florida, Gainesville, Florida, USA
- Center for Drug Evaluation and Safety (CoDES), University of Florida, Gainesville, Florida, USA
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Genome-wide association study of early-onset bipolar I disorder in the Han Taiwanese population. Transl Psychiatry 2021; 11:301. [PMID: 34016946 PMCID: PMC8137921 DOI: 10.1038/s41398-021-01407-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Revised: 04/05/2021] [Accepted: 04/21/2021] [Indexed: 02/04/2023] Open
Abstract
The search for susceptibility genes underlying the heterogeneous bipolar disorder has been inconclusive, often with irreproducible results. There is a hope that narrowing the phenotypes will increase the power of genetic analysis. Early-onset bipolar disorder is thought to be a genetically homogeneous subtype with greater symptom severity. We conducted a genome-wide association study (GWAS) for this subtype in bipolar I (BPI) disorder. Study participants included 1779 patients of Han Chinese descent with BPI disorder recruited by the Taiwan Bipolar Consortium. We conducted phenotype assessment using the Chinese version of the Schedules for Clinical Assessment in Neuropsychiatry and prepared a life chart with graphic depiction of lifetime clinical course for each of the BPI patient recruited. The assessment of onset age was based on this life chart with early onset defined as ≤20 years of age. We performed GWAS in a discovery group of 516 early-onset and 790 non-early-onset BPI patients, followed by a replication study in an independent group of 153 early-onset and 320 non-early-onset BPI patients and a meta-analysis with these two groups. The SNP rs11127876, located in the intron of CADM2, showed association with early-onset BPI in the discovery cohort (P = 7.04 × 10-8) and in the test of replication (P = 0.0354). After meta-analysis, this SNP was demonstrated to be a new genetic locus in CADM2 gene associated with early-onset BPI disorder (P = 5.19 × 10-8).
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Oyaci Y, Aytac HM, Pasin O, Cetinay Aydin P, Pehlivan S. Detection of altered methylation of MB-COMT promotor and DRD2 gene in cannabinoid or synthetic cannabinoid use disorder regarding gene variants and clinical parameters. J Addict Dis 2021; 39:526-536. [PMID: 33781176 DOI: 10.1080/10550887.2021.1906618] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
This study aims to investigate the association between cannabinoid use disorder (CUD) or synthetic cannabinoid use disorder (SCUD) and methylation status of MB-COMT (membrane-bound catechol-O-methyltransferase) promotor or DRD2 gene considering gene variants and clinical parameters. Based on the DSM-5 criteria, 218 CUD/SCUD patients' diagnoses were confirmed with a positive urine test, and a control group consisting of 102 participants without substance use disorders was included. Methylation-specific PCR was used to identify the methylation of the MB-COMT promotor and DRD2 gene. DRD2-141C Ins/Del and COMT Val158Met gene variants were evaluated by using PCR-RFLP. When the DRD2 and MB-COMT promoter methylation of CUD/SCUD patients were compared with the control group, there was a significant difference between the MB-COMT promoter methylation status of the two groups. When comparing DRD2 gene methylation due to clinical parameters and DRD2 genotype distribution in patients, the methylation status was significantly different between the groups due to the family history. Again, comparing the MB-COMT promotor methylation due to the COMT Val158Met genotype distribution and clinical parameters in patients, the MB-COMT promoter methylation status was significantly different between the groups due to the presence of alcohol usage. In summary, whereas the MB-COMT promoter methylation may be associated with the CUD/SCUD, the methylation of the DRD2 gene was not related to CUD/SCUD.
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Affiliation(s)
- Yasemin Oyaci
- Department of Medical Biology, Istanbul Faculty of Medicine, Istanbul University, Istanbul, Turkey
| | - Hasan Mervan Aytac
- Department of Psychiatry, Basaksehir Cam and Sakura City Hospital, Istanbul, Turkey
| | - Ozge Pasin
- Department of Biostatistics, Faculty of Medicine, Istanbul University, Istanbul, Turkey
| | - Pinar Cetinay Aydin
- Department of Psychiatry, University of Health Sciences, Psychiatry Clinic, Bakirkoy Research and Training Hospital for Psychiatry, Neurology and Neurosurgery, Istanbul, Turkey
| | - Sacide Pehlivan
- Department of Medical Biology, Istanbul Faculty of Medicine, Istanbul University, Istanbul, Turkey
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Winiger EA, Ellingson JM, Morrison CL, Corley RP, Pasman JA, Wall TL, Hopfer CJ, Hewitt JK. Sleep deficits and cannabis use behaviors: an analysis of shared genetics using linkage disequilibrium score regression and polygenic risk prediction. Sleep 2021; 44:zsaa188. [PMID: 32935850 PMCID: PMC7953210 DOI: 10.1093/sleep/zsaa188] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2020] [Revised: 08/27/2020] [Indexed: 12/17/2022] Open
Abstract
STUDY OBJECTIVES Estimate the genetic relationship of cannabis use with sleep deficits and an eveningness chronotype. METHODS We used linkage disequilibrium score regression (LDSC) to analyze genetic correlations between sleep deficits and cannabis use behaviors. Secondly, we generated sleep deficit polygenic risk score (PRS) and estimated their ability to predict cannabis use behaviors using linear and logistic regression. Summary statistics came from existing genome-wide association studies of European ancestry that were focused on sleep duration, insomnia, chronotype, lifetime cannabis use, and cannabis use disorder (CUD). A target sample for PRS prediction consisted of high-risk participants and participants from twin/family community-based studies (European ancestry; n = 760, male = 64%; mean age = 26.78 years). Target data consisted of self-reported sleep (sleep duration, feeling tired, and taking naps) and cannabis use behaviors (lifetime ever use, number of lifetime uses, past 180-day use, age of first use, and lifetime CUD symptoms). RESULTS Significant genetic correlation between lifetime cannabis use and an eveningness chronotype (rG = 0.24, p < 0.001), as well as between CUD and both short sleep duration (<7 h; rG = 0.23, p = 0.017) and insomnia (rG = 0.20, p = 0.020). Insomnia PRS predicted earlier age of first cannabis use (OR = 0.92, p = 0.036) and increased lifetime CUD symptom count (OR = 1.09, p = 0.012). CONCLUSION Cannabis use is genetically associated with both sleep deficits and an eveningness chronotype, suggesting that there are genes that predispose individuals to both cannabis use and sleep deficits.
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Affiliation(s)
- Evan A Winiger
- Institute for Behavioral Genetics, University of Colorado Boulder, CO
- Department of Psychology and Neuroscience, University of Colorado Boulder, CO
| | - Jarrod M Ellingson
- Institute for Behavioral Genetics, University of Colorado Boulder, CO
- Department of Psychiatry, University of Colorado School of Medicine, Aurora, CO
| | - Claire L Morrison
- Institute for Behavioral Genetics, University of Colorado Boulder, CO
- Department of Psychology and Neuroscience, University of Colorado Boulder, CO
| | - Robin P Corley
- Institute for Behavioral Genetics, University of Colorado Boulder, CO
| | - Joëlle A Pasman
- Behavioural Science Institute, Radboud University Nijmegen, Amsterdam, The Netherlands
| | - Tamara L Wall
- Department of Psychiatry, University of California, San Diego, CA
| | - Christian J Hopfer
- Department of Psychiatry, University of Colorado School of Medicine, Aurora, CO
| | - John K Hewitt
- Institute for Behavioral Genetics, University of Colorado Boulder, CO
- Department of Psychology and Neuroscience, University of Colorado Boulder, CO
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Thorpe HHA, Talhat MA, Khokhar JY. High genes: Genetic underpinnings of cannabis use phenotypes. Prog Neuropsychopharmacol Biol Psychiatry 2021; 106:110164. [PMID: 33152387 DOI: 10.1016/j.pnpbp.2020.110164] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2020] [Revised: 09/25/2020] [Accepted: 10/29/2020] [Indexed: 12/19/2022]
Abstract
Cannabis is one of the most widely used substances across the globe and its use has a substantial heritable component. However, the heritability of cannabis use varies according to substance use phenotype, suggesting that a unique profile of gene variants may contribute to the different stages of use, such as age of use onset, lifetime use, cannabis use disorder, and withdrawal and craving during abstinence. Herein, we review a subset of genes identified by candidate gene, family-based linkage, and genome-wide association studies related to these cannabis use phenotypes. We also describe their relationships with other substances, and their functions at the neurobiological, cognitive, and behavioral levels to hypothesize the role of these genes in cannabis use risk. Delineating genetic risk factors in the various stages of cannabis use will provide insight into the biological mechanisms related to cannabis use and highlight points of intervention prior to and following the development of dependence, as well as identify targets to aid drug development for treating problematic cannabis use.
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Affiliation(s)
- Hayley H A Thorpe
- Department of Biomedical Sciences, University of Guelph, Guelph, ON, Canada
| | | | - Jibran Y Khokhar
- Department of Biomedical Sciences, University of Guelph, Guelph, ON, Canada.
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Luo X, Guo X, Luo X, Tan Y, Zhang P, Yang K, Xie T, Shi J, Zhang Y, Xu J, Zuo L, Li CR. Significant, replicable, and functional associations between KTN1 variants and alcohol and drug codependence. Addict Biol 2021; 26:e12888. [PMID: 32115811 DOI: 10.1111/adb.12888] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Revised: 02/04/2020] [Accepted: 02/13/2020] [Indexed: 01/01/2023]
Abstract
The gray matter volume (GMV) of the putamen has been reported to be regulated by kinectin 1 gene (KTN1). As a hub of the dopaminergic circuit, the putamen is widely implicated in the etiological processes of substance use disorders (SUD). Here, we aimed to identify robust and reliable associations between KTN1 SNPs and SUD across multiple samples. We examined the associations between SUD and KTN1 SNPs in four independent population-based or family-based samples (n = 10,209). The potential regulatory effects of the risk alleles on the putamen GMVs, the effects of alcohol, nicotine, marijuana and cocaine on KTN1 mRNA expression, and the relationship between KTN1 mRNA expression and SUD were explored. We found that a total of 23 SNPs were associated with SUD across at least two independent samples (1.4 × 10-4 ≤ p ≤ 0.049), including one SNP (rs12895072) across three samples (8.8 × 10-3 ≤ p ≤ 0.049). Four other SNPs were significantly or suggestively associated with SUD only in European-Australians (4.8 × 10-4 ≤ p ≤ 0.058). All of the SUD-risk alleles of these 27 SNPs increased (β > 0) the putamen GMVs and represented major alleles (f > 0.5) in Europeans. Twenty-two SNPs were potentially biologically functional. Alcohol, nicotine and cocaine significantly affected the KTN1 mRNA expression, and the KTN1 mRNA was differentially expressed between nicotine or cocaine dependent and control subjects. We concluded that there was a replicable and robust relationship among the KTN1 variants, KTN1 mRNA expression, putamen GMVs, molecular effects of substances, and SUD, suggesting that some risk KTN1 alleles might increase kinectin 1 expression in the putamen, altering putamen structures and functions, and leading to SUD.
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Affiliation(s)
- Xingguang Luo
- Biological Psychiatry Research Center Beijing Huilongguan Hospital Beijing China
| | - Xiaoyun Guo
- Department of Psychiatry Shanghai Mental Health Center Shanghai China
- Department of Psychiatry Yale University School of Medicine New Haven CT USA
| | - Xingqun Luo
- Department of Clinical Medicine, College of Integrated Traditional Chinese and Western Medicine Fujian University of Traditional Chinese Medicine Fuzhou Fujian China
| | - Yunlong Tan
- Biological Psychiatry Research Center Beijing Huilongguan Hospital Beijing China
| | - Ping Zhang
- Biological Psychiatry Research Center Beijing Huilongguan Hospital Beijing China
| | - Kebing Yang
- Biological Psychiatry Research Center Beijing Huilongguan Hospital Beijing China
| | - Ting Xie
- Biological Psychiatry Research Center Beijing Huilongguan Hospital Beijing China
| | - Jing Shi
- Biological Psychiatry Research Center Beijing Huilongguan Hospital Beijing China
| | - Yong Zhang
- Department of Psychiatry Tianjin Mental Health Center Tianjin China
| | - Jianying Xu
- Department of Obstetrics and Gynecology Zhuhai Municipal Maternal and Children's Health Hospital Zhuhai Guangdong China
| | - Lingjun Zuo
- Department of Psychiatry Yale University School of Medicine New Haven CT USA
| | - Chiang‐Shan R. Li
- Department of Psychiatry Yale University School of Medicine New Haven CT USA
- Department of Neuroscience Yale University School of Medicine New Haven CT USA
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Abstract
Cannabis use disorder (CUD) is an underappreciated risk of using cannabis that affects ~10% of the 193 million cannabis users worldwide. The individual and public health burdens are less than those of other forms of drug use, but CUD accounts for a substantial proportion of persons seeking treatment for drug use disorders owing to the high global prevalence of cannabis use. Cognitive behavioural therapy, motivational enhancement therapy and contingency management can substantially reduce cannabis use and cannabis-related problems, but enduring abstinence is not a common outcome. No pharmacotherapies have been approved for cannabis use or CUD, although a number of drug classes (such as cannabinoid agonists) have shown promise and require more rigorous evaluation. Treatment of cannabis use and CUD is often complicated by comorbid mental health and other substance use disorders. The legalization of non-medical cannabis use in some high-income countries may increase the prevalence of CUD by making more potent cannabis products more readily available at a lower price. States that legalize medical and non-medical cannabis use should inform users about the risks of CUD and provide information on how to obtain assistance if they develop cannabis-related mental and/or physical health problems.
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Thomas NS, Salvatore JE, Gillespie NA, Aliev F, Ksinan AJ, Dick DM. Cannabis use in college: Genetic predispositions, peers, and activity participation. Drug Alcohol Depend 2021; 219:108489. [PMID: 33373877 PMCID: PMC8369492 DOI: 10.1016/j.drugalcdep.2020.108489] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Revised: 11/10/2020] [Accepted: 11/22/2020] [Indexed: 12/01/2022]
Abstract
BACKGROUND Among adult college students in the US, cannabis use is common and associated with considerable negative consequences to health, cognition, and academic functioning, underscoring the importance of identifying risk and protective factors. Cannabis use is influenced by genetic factors, but genetic risk is not determinative. Accordingly, it is critical to identify environments that reduce risk among those who are at elevated genetic risk. This study examined the impact of polygenic scores for cannabis initiation, various forms of social activity participation, and peer deviance on recent cannabis use. Our aim was to test whether these environments moderate genetic risk for cannabis use. METHODS Data came from a longitudinal sample of undergraduate college students of European American (EA; NEA = 750) and African American (AA; NAA = 405) ancestry. Generalized estimating equations with a logit link function were used to examine main effects and two-way interactions. RESULTS Engagement with church activities was associated with lower probability of cannabis use. Peer deviance was associated with higher probability of cannabis use. Engagement with community activities moderated the influence of the polygenic risk score in the EA sample, such that PRS was associated with recent cannabis use among those who never engaged in community activities. This effect did not replicate in AAs, which may have been due to the portability of PRS based on EA discovery samples. CONCLUSIONS Results suggest that community activities may limit the influence of genetic risk, as associations between PRS and cannabis use were only observed among individuals who never engaged in community activities.
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Affiliation(s)
- Nathaniel S Thomas
- Department of Psychology, Virginia Commonwealth University, Box 842018, Richmond, VA, 23284-2018, United States; College Behavioral and Emotional Health Institute, Virginia Commonwealth University, Box 843092, Richmond, VA, 23284-3092, United States.
| | - Jessica E Salvatore
- Department of Psychology, Virginia Commonwealth University, Box 842018, Richmond, VA, 23284-2018, United States; Virginia Institute for Psychiatric and Behavioral Genetics, Box 980126, Richmond, VA, 23298-0126, United States
| | - Nathan A Gillespie
- Department of Psychiatry, Virginia Commonwealth University, Box 980308, Richmond, VA, 23219-1359, United States; Virginia Institute for Psychiatric and Behavioral Genetics, Box 980126, Richmond, VA, 23298-0126, United States; Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Locked Bag 2000, Royal Brisbane Hospital, QLD, 4029, Brisbane, Australia
| | - Fazil Aliev
- Department of Psychology, Virginia Commonwealth University, Box 842018, Richmond, VA, 23284-2018, United States; Karabuk University, Faculty of Business, Turkey
| | - Albert J Ksinan
- Department of Health Behavior and Policy, Virginia Commonwealth University, 830 E Main St., Richmond, VA, 23219, United States
| | - Danielle M Dick
- Department of Psychology, Virginia Commonwealth University, Box 842018, Richmond, VA, 23284-2018, United States; College Behavioral and Emotional Health Institute, Virginia Commonwealth University, Box 843092, Richmond, VA, 23284-3092, United States; Department of Human & Molecular Genetics, Virginia Commonwealth University, Box 980033, Richmond, VA, 23298-0033, United States.
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Thapa KS, Chen AB, Lai D, Xuei X, Wetherill L, Tischfield JA, Liu Y, Edenberg HJ. Identification of Functional Genetic Variants Associated With Alcohol Dependence and Related Phenotypes Using a High-Throughput Assay. Alcohol Clin Exp Res 2020; 44:2494-2518. [PMID: 33119910 PMCID: PMC7725989 DOI: 10.1111/acer.14492] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Accepted: 10/20/2020] [Indexed: 01/22/2023]
Abstract
BACKGROUND Genome-wide association studies (GWAS) of alcohol dependence (AD) and related phenotypes have identified multiple loci, but the functional variants underlying the loci have in most cases not been identified. Noncoding variants can influence phenotype by affecting gene expression; for example, variants in the 3' untranslated regions (3'UTR) can affect gene expression posttranscriptionally. METHODS We adapted a high-throughput assay known as PASSPORT-seq (parallel assessment of polymorphisms in miRNA target sites by sequencing) to identify among variants associated with AD and related phenotypes those that cause differential expression in neuronal cell lines. Based upon meta-analyses of alcohol-related traits in African American and European Americans in the Collaborative Study on the Genetics of Alcoholism, we tested 296 single nucleotide polymorphisms (SNPs with meta-analysis p values ≤ 0.001) that were located in 3'UTRs. RESULTS We identified 60 SNPs that affected gene expression (false discovery rate [FDR] < 0.05) in SH-SY5Y cells and 92 that affected expression in SK-N-BE(2) cells. Among these, 30 SNPs altered RNA levels in the same direction in both cell lines. Many of these SNPs reside in the binding sites of miRNAs and RNA-binding proteins and are expression quantitative trait loci of genes including KIF6,FRMD4A,CADM2,ADD2,PLK2, and GAS7. CONCLUSION The SNPs identified in the PASSPORT-seq assay are functional variants that might affect the risk for AD and related phenotypes. Our study provides insights into gene regulation in AD and demonstrates the value of PASSPORT-seq as a tool to screen genetic variants in GWAS loci for one potential mechanism of action.
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Affiliation(s)
- Kriti S. Thapa
- Department of Biochemistry & Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana
| | - Andy B Chen
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
| | - Dongbing Lai
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
| | - Xiaoling Xuei
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
| | - Leah Wetherill
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
| | - Jay A. Tischfield
- Department of Genetics, Rutgers University, Piscataway, NJ, 99999, USA
| | - Yunlong Liu
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
| | - Howard J. Edenberg
- Department of Biochemistry & Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
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Soler Artigas M, Sánchez-Mora C, Rovira P, Richarte V, Garcia-Martínez I, Pagerols M, Demontis D, Stringer S, Vink JM, Børglum AD, Neale BM, Franke B, Faraone SV, Casas M, Ramos-Quiroga JA, Ribasés M. Attention-deficit/hyperactivity disorder and lifetime cannabis use: genetic overlap and causality. Mol Psychiatry 2020; 25:2493-2503. [PMID: 30610198 PMCID: PMC8025199 DOI: 10.1038/s41380-018-0339-3] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2018] [Revised: 11/02/2018] [Accepted: 12/10/2018] [Indexed: 11/09/2022]
Abstract
Attention-deficit/hyperactivity disorder (ADHD) is a severely impairing neurodevelopmental disorder with a prevalence of 5% in children and adolescents and of 2.5% in adults. Comorbid conditions in ADHD play a key role in symptom progression, disorder course and outcome. ADHD is associated with a significantly increased risk for substance use, abuse and dependence. ADHD and cannabis use are partly determined by genetic factors; the heritability of ADHD is estimated at 70-80% and of cannabis use initiation at 40-48%. In this study, we used summary statistics from the largest available meta-analyses of genome-wide association studies (GWAS) of ADHD (n = 53,293) and lifetime cannabis use (n = 32,330) to gain insights into the genetic overlap and causal relationship of these two traits. We estimated their genetic correlation to be r2 = 0.29 (P = 1.63 × 10-5) and identified four new genome-wide significant loci in a cross-trait analysis: two in a single variant association analysis (rs145108385, P = 3.30 × 10-8 and rs4259397, P = 4.52 × 10-8) and two in a gene-based association analysis (WDPCP, P = 9.67 × 10-7 and ZNF251, P = 1.62 × 10-6). Using a two-sample Mendelian randomization approach we found support that ADHD is causal for lifetime cannabis use, with an odds ratio of 7.9 for cannabis use in individuals with ADHD in comparison to individuals without ADHD (95% CI (3.72, 15.51), P = 5.88 × 10-5). These results substantiate the temporal relationship between ADHD and future cannabis use and reinforce the need to consider substance misuse in the context of ADHD in clinical interventions.
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Affiliation(s)
- 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 Psychiatry, Hospital Universitari Vall d'Hebron, Barcelona, Spain.
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Barcelona, Spain.
| | - Cristina Sánchez-Mora
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
- Department of Psychiatry, Hospital Universitari Vall d'Hebron, Barcelona, Spain
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Barcelona, Spain
| | - Paula Rovira
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
- Department of Psychiatry, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Vanesa Richarte
- Department of Psychiatry, Hospital Universitari Vall d'Hebron, Barcelona, Spain
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Barcelona, Spain
- Department of Psychiatry and Legal Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Iris Garcia-Martínez
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
- Department of Psychiatry, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Mireia Pagerols
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
- Department of Psychiatry, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Ditte Demontis
- Department of Biomedicine-Human Genetics, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark
| | - Sven Stringer
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, The Netherlands
| | - Jacqueline M Vink
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
| | - Anders D Børglum
- Department of Biomedicine-Human Genetics, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark
| | - Benjamin M Neale
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research and the Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Barbara Franke
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Stephen V Faraone
- Departments of Psychiatry and of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Miguel Casas
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
- Department of Psychiatry, Hospital Universitari Vall d'Hebron, Barcelona, Spain
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Barcelona, Spain
- Department of Psychiatry and Legal Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Josep Antoni Ramos-Quiroga
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
- Department of Psychiatry, Hospital Universitari Vall d'Hebron, Barcelona, Spain
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Barcelona, Spain
- Department of Psychiatry and Legal Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Marta Ribasés
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain.
- Department of Psychiatry, Hospital Universitari Vall d'Hebron, Barcelona, Spain.
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Barcelona, Spain.
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Abstract
There is a well-established relationship between cannabis use and psychosis, although the exact nature of this relationship is not fully understood. Recent studies have observed significant genetic overlap between a diagnosis of schizophrenia and lifetime cannabis use. Expanding on this work, the current study aimed to examine whether genetic overlap also occurs for subclinical psychosis (schizotypy) and cannabis use, as well as examining the phenotypic association between the traits. Phenotypic correlations were calculated for a variety of schizotypy and cannabis phenotypes in the UK Biobank (UKB), and single nucleotide polymorphism (SNP)-based heritability estimates and genetic correlations were calculated for these UKB phenotypes as well as for several other variables taken from recent genomewide association studies. Positive phenotypic correlations were observed between 11 out of 12 pairs of the cannabis use and schizotypy phenotypes (correlation range .05-.18), indicating a robust association between increased symptoms of schizotypy and cannabis use. SNP-based heritability estimates for two schizotypy phenotypes remained significant after multiple testing correction: social anhedonia (h2SNP = .08, SE = .02, N = 4025) and ever seen an unreal vision (h2SNP = .35, SE = .10, N = 150,717). Finally, one significant genetic correlation was observed between schizotypy and cannabis use, a negative correlation between social anhedonia and number of times used cannabis (rg = -.30, p = .012). The current study suggests the relationship between cannabis use and psychosis is also seen in subclinical symptoms of psychosis, but further research with larger samples is needed to determine the biological mechanisms underlying this association.
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Parks C, Jones BC, Moore BM, Mulligan MK. Sex and Strain Variation in Initial Sensitivity and Rapid Tolerance to Δ9-Tetrahydrocannabinol. Cannabis Cannabinoid Res 2020; 5:231-245. [PMID: 32923660 PMCID: PMC7480727 DOI: 10.1089/can.2019.0047] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Background and Objectives: For cannabis and other drugs of abuse, initial response and/or tolerance to drug effects can predict later dependence and problematic use. Our objective is to identify sex and genetic (strain) differences in initial response and rapid tolerance to Δ9–tetrahydrocannabinol (THC), the main psychoactive ingredient in cannabis, between highly genetically divergent inbred mouse strains—C57BL/6J (B6) and DBA/2J (D2). Experimental Approach: Sex and strain responses relative to baseline were quantified following daily exposure (i.p.) to 10 mg/kg THC or vehicle (VEH) over the course of 5 days. Dependent measures included hypothermia (decreased body temperature) and ataxia (decreased spontaneous activity in the open field), and antinociception (increase in tail withdrawal latency to a thermal stimulus). Initial sensitivity to THC was defined as the difference in response between baseline and day 1. Rapid tolerance to THC was defined as the difference in response between days 1 and 2. Results: B6 exhibited greater THC-induced motor activity suppression and initial sensitivity to ataxia relative to the D2 strain. Females demonstrated greater levels of THC-induced hypothermia and initial sensitivity relative to males. Higher levels of THC-induced antinociception and initial sensitivity were observed for D2 relative to B6. Rapid tolerance to THC was observed for hypothermia and antinociception. Much less tolerance was observed for THC-induced ataxia. D2 exhibited rapid tolerance to THC-induced hypothermia and antinociception at time points associated with peak THC initial response. Likewise, at the peak initial THC response time point, females demonstrated greater levels of rapid tolerance to hypothermic effects relative to males. Conclusions: Both sex and genetic factors drive variation in initial response and rapid tolerance to the ataxic, antinociceptive, and hypothermic effects of THC. As these traits directly result from THC activation of the cannabinoid receptor 1, gene variants between B6 and D2 in cannabinoid signaling pathways are likely to mediate strain differences in response to THC.
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Affiliation(s)
- Cory Parks
- Department of Genetics, Genomics and Informatics, College of Medicine, The University of Tennessee Health Science Center, Memphis, Tennessee
| | - Byron C Jones
- Department of Genetics, Genomics and Informatics, College of Medicine, The University of Tennessee Health Science Center, Memphis, Tennessee
| | - Bob M Moore
- Department of Pharmaceutical Sciences, College of Medicine, The University of Tennessee Health Science Center, Memphis, Tennessee
| | - Megan K Mulligan
- Department of Genetics, Genomics and Informatics, College of Medicine, The University of Tennessee Health Science Center, Memphis, Tennessee
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Hillmer A, Chawar C, Sanger S, D'Elia A, Butt M, Kapoor R, Kapczinski F, Pare G, Thabane L, Samaan Z. Genetic determinants of cannabis use: a systematic review protocol. Syst Rev 2020; 9:190. [PMID: 32819433 PMCID: PMC7441561 DOI: 10.1186/s13643-020-01442-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Accepted: 07/31/2020] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND With the legalization of cannabis in Canada, there is an increase trend in use. Cannabis has been known to have several health implications, one of which is the development of cannabis use disorder (CUD). CUD is more common in males than females, as well as in certain ethnic groups such as Native Americans. Additionally, both environmental and genetic risk factors have been found for cannabis use. The objective of this systematic review will be to summarize the genetic variants associated with cannabis use which have reached borderline genome-wide significance. METHODS This systematic review will incorporate articles that have performed a genome-wide association study (GWAS) investigating cannabis use. MEDLINE, Web of Science, EMBASE, GWAS Catalog, GWAS Central, and NIH Database of Genotype and Phenotype will be searched using a comprehensive search strategy. The quality of genetic association studies (Q-Genie) tool will be utilized to assess the quality of the included studies. All screening and data extraction will occur independently by two authors. If feasible, a random-effects meta-analysis will be conducted on pooled odds ratios of single nucleotide polymorphisms reaching borderline genome-wide significance. DISCUSSION This systematic review will synthesize available GWAS on cannabis use. Results from this review will inform and direct further investigation of genetic variants associated with cannabis use. SYSTEMATIC REVIEW REGISTRATION PROSPERO CRD42020176016.
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Affiliation(s)
- Alannah Hillmer
- Neuroscience Graduate Program, Department of Psychiatry and Behavioural Neurosciences, McMaster University, 100 West 5th St., Hamilton, ON, L8N 3 K7, Canada
| | - Caroul Chawar
- Neuroscience Graduate Program, Department of Psychiatry and Behavioural Neurosciences, McMaster University, 100 West 5th St., Hamilton, ON, L8N 3 K7, Canada
| | - Stephanie Sanger
- Health Science Library, McMaster University, 1280 Main St. W, Hamilton, ON, L8S 4 L8, Canada
| | - Alessia D'Elia
- Neuroscience Graduate Program, Department of Psychiatry and Behavioural Neurosciences, McMaster University, 100 West 5th St., Hamilton, ON, L8N 3 K7, Canada
| | - Mehreen Butt
- Integrated Science Program, McMaster University, 1280 Main St. W, Hamilton, ON, L8S 4 L8, Canada
| | - Raveena Kapoor
- Health Sciences Program, McMaster University, 1280 Main St. W, Hamilton, ON, L8S 4 L8, Canada
| | - Flavio Kapczinski
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, 100 West 5th St., Hamilton, ON, L8N 3 K7, Canada
| | - Guillaume Pare
- Population Health Research Institute, McMaster University, 1280 Main St. W, Hamilton, ON, L8S 4 L8, Canada
| | - Lehana Thabane
- Department of Health Research Method, Evidence & Impact, 1280 Main St. W, Hamilton, ON, L8S 4 L8, Canada
| | - Zainab Samaan
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, 100 West 5th St., Hamilton, ON, L8N 3 K7, Canada.
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50
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Boks MP, He Y, Schubart CD, Gastel WV, Elkrief L, Huguet G, Eijk KV, Vinkers CH, Kahn RS, Paus T, Conrod P, Hol EM, de Witte LD. Cannabinoids and psychotic symptoms: A potential role for a genetic variant in the P2X purinoceptor 7 (P2RX7) gene. Brain Behav Immun 2020; 88:573-581. [PMID: 32330591 DOI: 10.1016/j.bbi.2020.04.051] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Revised: 04/07/2020] [Accepted: 04/20/2020] [Indexed: 12/17/2022] Open
Abstract
To investigate the biological mechanisms underlying the higher risk for psychosis in those that use cannabis, we conducted a genome-wide environment-interaction study (GWEIS). In a sample of individuals without a psychiatric disorder (N = 1262), we analyzed the interactions between regular cannabis use and genotype with psychotic-like experiences (PLE) as outcome. PLE were measured using the Community Assessment of Psychic Experiences (CAPE). The sample was enriched for those at the extremes of both cannabis use and PLE to increase power. A single nucleotide polymorphism in the P2RX7 gene (rs7958311) was associated with risk for a high level of psychotic experiences in regular cannabis users (p = 1.10 x10-7) and in those with high levels of lifetime cannabis use (p = 4.5 × 10-6). This interaction was replicated in individuals with high levels of lifetime cannabis use in the IMAGEN cohort (N = 1217, p = 0.020). Functional relevance of P2RX7 in cannabis users was suggested by in vitro experiments on activated monocytes. Exposure of these cells to tetrahydrocannabinol (THC) or cannabidiol (CBD) reduced the immunological response of the P2X7 receptor, which was dependent on the identified genetic variant. P2RX7 variants have been implicated in psychiatric disorders before and the P2X7 receptor is involved in pathways relevant to psychosis, such as neurotransmission, synaptic plasticity and immune regulation. We conclude that P2RX7 plays a role in vulnerability to develop psychotic symptoms when using cannabis and point to a new pathway that can potentially be targeted by newly developed P2X7 antagonists.
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Affiliation(s)
- Marco P Boks
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Centre Utrecht, Utrecht University, The Netherlands
| | - Yujie He
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Centre Utrecht, Utrecht University, The Netherlands
| | - Chris D Schubart
- Department of Psychiatry, Tergooi Hospital, Blaricum, The Netherlands
| | | | - Laurent Elkrief
- Department of Medicine, Université de Montréal, Montreal, Quebec, Canada
| | - Guillaume Huguet
- Department of Pediatrics, Université de Montréal, Montreal, Quebec, Canada; Center Hospitalier Universitaire Sainte-Justine Research Center, Montreal, Quebec, Canada
| | - Kristel van Eijk
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, Utrecht University, The Netherlands
| | - Christiaan H Vinkers
- Department of Psychiatry, Amsterdam UMC (location VUmc), Amsterdam, The Netherlands; Department of Anatomy and Neurosciences, Amsterdam UMC (location VUmc), Amsterdam, The Netherlands
| | - René S Kahn
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Centre Utrecht, Utrecht University, The Netherlands; Department of psychiatry, Icahn School of Medicine at Mount Sinai, New York City, USA
| | - Tomás Paus
- Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital and Departments of Psychology and Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Patricia Conrod
- Center Hospitalier Universitaire Sainte-Justine Research Center, Montreal, Quebec, Canada; Department of Psychiatry, University of Montreal, Montréal, QC, Canada
| | - Elly M Hol
- Department of Translational Neuroscience, UMC Utrecht Brain Center, Utrecht University, The Netherlands; Neuroimmunology Research Group, Netherlands Institute for Neuroscience, An Institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, Netherlands
| | - Lot D de Witte
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Centre Utrecht, Utrecht University, The Netherlands; Department of psychiatry, Icahn School of Medicine at Mount Sinai, New York City, USA.
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