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McGrouther CC, Rangan AV, Di Florio A, Elman JA, Schork NJ, Kelsoe J. Heterogeneity analysis provides evidence for a genetically homogeneous subtype of bipolar-disorder. ARXIV 2024:arXiv:2405.00159v1. [PMID: 38745705 PMCID: PMC11092873] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
Bipolar Disorder (BD) is a complex disease. It is heterogeneous, both at the phenotypic and genetic level, although the extent and impact of this heterogeneity is not fully understood. One way to assess this heterogeneity is to look for patterns in the subphenotype data, identify a more phenotypically homogeneous set of subjects, and perform a genome-wide association-study (GWAS) and subsequent secondary analyses restricted to this homogeneous subset. Because of the variability in how phenotypic data was collected by the various BD studies over the years, homogenizing the phenotypic data is a challenging task, and so is replication. As members of the Psychiatric Genomics Consortium (PGC), we have access to the raw genotypes of 18,711 BD cases and 29,738 controls. This amount of data makes it possible for us to set aside the intricacies of phenotype and allow the genetic data itself to determine which subjects define a homogeneous genetic subgroup. In this paper, we leverage recent advances in heterogeneity analysis to look for distinct homogeneous genetic BD subgroups (or biclusters) that manifest the broad phenotype we think of as Bipolar Disorder. As our data was generated by 27 studies and genotyped on a variety of platforms (OMEX, Affymetrix, Illumina), we use a biclustering algorithm capable of covariate-correction. Covariate-correction is critical if we wish to distinguish disease-related signals from those which are a byproduct of ancestry, study or genotyping platform. We rely on the raw genotyped data and do not include any data generated through imputation. We first apply this covariate-corrected biclustering algorithm to a cohort of 2524 BD cases and 4106 controls from the Bipolar Disease Research Network (BDRN: OMEX). We find evidence of genetic heterogeneity delineating a statistically significant bicluster comprising a subset of BD cases which exhibits a disease-specific pattern of differential-expression across a subset of SNPs. This pattern replicates across the remaining data-sets collected by the PGC containing 5781/8289 (OMEX), 3581/7591 (Illumina), and 6825/9752(Affymetrix) cases/controls, respectively. This bicluster includes subjects diagnosed with bipolar type-I, as well as subjects diagnosed with bipolar type-II. However, the bicluster is enriched for bipolar type-I over type-II and may represent a collection of correlated genetic risk-factors. By investigating the bicluster-informed polygenic-risk-scoring (PRS), we find that the disease-specific pattern highlighted by the bicluster can be leveraged to eliminate noise from our GWAS analyses and improve not only risk prediction, particularly when using only a relatively small subset (e.g., ~ 1%) of the available SNPs, but also SNP replication. Though our primary focus is only the analysis of disease-related signal, we also identify replicable control-related heterogeneity. Covariate-corrected biclustering of raw genetic data appears to be a promising route for untangling heterogeneity and identifying replicable homogeneous genetic subtypes of complex disease. It may also prove useful in identifying protective effects within the control group. This approach circumvents some of the difficulties presented by subphenotype data collected by meta-analyses or 23 andMe, e.g., missingness, assessment variation, and reliance on self-report.
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Affiliation(s)
- Caroline C. McGrouther
- Courant Institute of Mathematical Sciences, New York University, New York, NY, United States of America
| | - Aaditya V. Rangan
- Courant Institute of Mathematical Sciences, New York University, New York, NY, United States of America
| | - Arianna Di Florio
- School of Medicine, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, United Kingdom
| | - Jeremy A. Elman
- Department of Psychiatry, University of California San Diego, San Diego, CA, United States of America
| | - Nicholas J. Schork
- The Translational Genomics Research Institute, Quantitative Medicine and Systems Biology, Phoenix, AZ, United States of America
| | - John Kelsoe
- Department of Psychiatry, University of California San Diego, La Jolla, CA, United States of America
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Barr PB, Bigdeli TB, Meyers JL, Peterson RE, Sanchez-Roige S, Mallard TT, Dick DM, Harden KP, Wilkinson A, Graham DP, Nielsen DA, Swann AC, Lipsky RK, Kosten TR, Aslan M, Harvey PD, Kimbrel NA, Beckham JC. Correlates of Risk for Disinhibited Behaviors in the Million Veteran Program Cohort. JAMA Psychiatry 2024; 81:188-197. [PMID: 37938835 PMCID: PMC10633411 DOI: 10.1001/jamapsychiatry.2023.4141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 09/01/2023] [Indexed: 11/10/2023]
Abstract
Importance Many psychiatric outcomes share a common etiologic pathway reflecting behavioral disinhibition, generally referred to as externalizing (EXT) disorders. Recent genome-wide association studies (GWASs) have demonstrated the overlap between EXT disorders and important aspects of veterans' health, such as suicide-related behaviors and substance use disorders (SUDs). Objective To explore correlates of risk for EXT disorders within the Veterans Health Administration (VA) Million Veteran Program (MVP). Design, Setting, and Participants A series of phenome-wide association studies (PheWASs) of polygenic risk scores (PGSs) for EXT disorders was conducted using electronic health records. First, ancestry-specific PheWASs of EXT PGSs were conducted in the African, European, and Hispanic or Latin American ancestries. Next, a conditional PheWAS, covarying for PGSs of comorbid psychiatric problems (depression, schizophrenia, and suicide attempt; European ancestries only), was performed. Lastly, to adjust for unmeasured confounders, a within-family analysis of significant associations from the main PheWAS was performed in full siblings (European ancestries only). This study included the electronic health record data from US veterans from VA health care centers enrolled in MVP. Analyses took place from February 2022 to August 2023 covering a period from October 1999 to January 2020. Exposures PGSs for EXT, depression, schizophrenia, and suicide attempt. Main Outcomes and Measures Phecodes for diagnoses derived from the International Statistical Classification of Diseases, Ninth and Tenth Revisions, Clinical Modification, codes from electronic health records. Results Within the MVP (560 824 patients; mean [SD] age, 67.9 [14.3] years; 512 593 male [91.4%]), the EXT PGS was associated with 619 outcomes, of which 188 were independent of risk for comorbid problems or PGSs (from odds ratio [OR], 1.02; 95% CI, 1.01-1.03 for overweight/obesity to OR, 1.44; 95% CI, 1.42-1.47 for viral hepatitis C). Of the significant outcomes, 73 (11.9%) were significant in the African results and 26 (4.5%) were significant in the Hispanic or Latin American results. Within-family analyses uncovered robust associations between EXT PGS and consequences of SUDs, including liver disease, chronic airway obstruction, and viral hepatitis C. Conclusions and Relevance Results of this cohort study suggest a shared polygenic basis of EXT disorders, independent of risk for other psychiatric problems. In addition, this study found associations between EXT PGS and diagnoses related to SUDs and their sequelae. Overall, this study highlighted the potential negative consequences of EXT disorders for health and functioning in the US veteran population.
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Affiliation(s)
- Peter B. Barr
- VA New York Harbor Healthcare System, Brooklyn
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, New York
- Institute for Genomics in Health, SUNY Downstate Health Sciences University, Brooklyn, New York
- Department of Epidemiology and Biostatistics, School of Public Health, SUNY Downstate Health Sciences University, Brooklyn, New York
| | - Tim B. Bigdeli
- VA New York Harbor Healthcare System, Brooklyn
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, New York
- Institute for Genomics in Health, SUNY Downstate Health Sciences University, Brooklyn, New York
- Department of Epidemiology and Biostatistics, School of Public Health, SUNY Downstate Health Sciences University, Brooklyn, New York
| | - Jacquelyn L. Meyers
- VA New York Harbor Healthcare System, Brooklyn
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, New York
- Institute for Genomics in Health, SUNY Downstate Health Sciences University, Brooklyn, New York
- Department of Epidemiology and Biostatistics, School of Public Health, SUNY Downstate Health Sciences University, Brooklyn, New York
| | - Roseann E. Peterson
- VA New York Harbor Healthcare System, Brooklyn
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, New York
- Institute for Genomics in Health, SUNY Downstate Health Sciences University, Brooklyn, New York
| | - Sandra Sanchez-Roige
- Department of Psychiatry, University of California San Diego, La Jolla
- Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Travis T. Mallard
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts
| | - Danielle M. Dick
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, New Jersey
- Rutgers Addiction Research Center, Rutgers University, Piscataway, New Jersey
| | - K. Paige Harden
- Department of Psychology, University of Texas at Austin, Austin
- Population Research Center, University of Texas at Austin, Austin
| | - Anna Wilkinson
- Michael E. DeBakey VA Medical Center, Houston, Texas
- The University of Texas Health Science Center at Houston, UTHealth Houston School of Public Health, Houston
- Michael and Susan Dell Center for Healthy Living, The University of Texas Health Science Center at Houston, Houston
| | - David P. Graham
- Michael E. DeBakey VA Medical Center, Houston, Texas
- Departments of Psychiatry, Neuroscience, Pharmacology, and Immunology and Rheumatology, Baylor College of Medicine, Houston, Texas
| | - David A. Nielsen
- Michael E. DeBakey VA Medical Center, Houston, Texas
- Departments of Psychiatry, Neuroscience, Pharmacology, and Immunology and Rheumatology, Baylor College of Medicine, Houston, Texas
| | - Alan C. Swann
- Michael E. DeBakey VA Medical Center, Houston, Texas
- Departments of Psychiatry, Neuroscience, Pharmacology, and Immunology and Rheumatology, Baylor College of Medicine, Houston, Texas
| | - Rachele K. Lipsky
- Michael E. DeBakey VA Medical Center, Houston, Texas
- Departments of Psychiatry, Neuroscience, Pharmacology, and Immunology and Rheumatology, Baylor College of Medicine, Houston, Texas
| | - Thomas R. Kosten
- Michael E. DeBakey VA Medical Center, Houston, Texas
- Departments of Psychiatry, Neuroscience, Pharmacology, and Immunology and Rheumatology, Baylor College of Medicine, Houston, Texas
| | - Mihaela Aslan
- Clinical Epidemiology Research Center, VA Connecticut Healthcare System, West Haven, Connecticut
- Yale University School of Medicine, New Haven, Connecticut
| | - Philip D. Harvey
- Research Service, Bruce W. Carter Miami Veterans Affairs Medical Center, Miami, Florida
- University of Miami Miller School of Medicine, Miami, Florida
| | - Nathan A. Kimbrel
- Durham VA Health Care System, Durham, North Carolina
- VA Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham, North Carolina
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, North Carolina
| | - Jean C. Beckham
- Durham VA Health Care System, Durham, North Carolina
- VA Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham, North Carolina
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, North Carolina
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Levey DF, Galimberti M, Deak JD, Wendt FR, Bhattacharya A, Koller D, Harrington KM, Quaden R, Johnson EC, Gupta P, Biradar M, Lam M, Cooke M, Rajagopal VM, Empke SLL, Zhou H, Nunez YZ, Kranzler HR, Edenberg HJ, Agrawal A, Smoller JW, Lencz T, Hougaard DM, Børglum AD, Demontis D, Gaziano JM, Gandal MJ, Polimanti R, Stein MB, Gelernter J. Multi-ancestry genome-wide association study of cannabis use disorder yields insight into disease biology and public health implications. Nat Genet 2023; 55:2094-2103. [PMID: 37985822 PMCID: PMC10703690 DOI: 10.1038/s41588-023-01563-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 10/09/2023] [Indexed: 11/22/2023]
Abstract
As recreational use of cannabis is being decriminalized in many places and medical use widely sanctioned, there are growing concerns about increases in cannabis use disorder (CanUD), which is associated with numerous medical comorbidities. Here we performed a genome-wide association study of CanUD in the Million Veteran Program (MVP), followed by meta-analysis in 1,054,365 individuals (ncases = 64,314) from four broad ancestries designated by the reference panel used for assignment (European n = 886,025, African n = 123,208, admixed American n = 38,289 and East Asian n = 6,843). Population-specific methods were applied to calculate single nucleotide polymorphism-based heritability within each ancestry. Statistically significant single nucleotide polymorphism-based heritability for CanUD was observed in all but the smallest population (East Asian). We discovered genome-wide significant loci unique to each ancestry: 22 in European, 2 each in African and East Asian, and 1 in admixed American ancestries. A genetically informed causal relationship analysis indicated a possible effect of genetic liability for CanUD on lung cancer risk, suggesting potential unanticipated future medical and psychiatric public health consequences that require further study to disentangle from other known risk factors such as cigarette smoking.
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Affiliation(s)
- Daniel F Levey
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA.
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA.
| | - Marco Galimberti
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Joseph D Deak
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Frank R Wendt
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
- Department of Anthropology, University of Toronto, Mississauga, Ontario, Canada
- Biostatistics Division, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Arjun Bhattacharya
- Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Dora Koller
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
- Department of Genetics, Microbiology and Statistics, Faculty of Biology, University of Barcelona, Catalonia, Spain
| | - Kelly M Harrington
- VA Boston Healthcare System, Massachusetts Veterans Epidemiology Research and Information Center, Boston, MA, USA
- Department of Psychiatry, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
| | - Rachel Quaden
- VA Boston Healthcare System, Massachusetts Veterans Epidemiology Research and Information Center, Boston, MA, USA
- Department of Psychiatry, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
| | - Emma C Johnson
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Priya Gupta
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Mahantesh Biradar
- NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK
| | - Max Lam
- Research Division, Institute of Mental Health, Singapore, Singapore
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Psychiatry and Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
| | - Megan Cooke
- Center for Addiction Medicine, Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Veera M Rajagopal
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
| | - Stefany L L Empke
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Hang Zhou
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Yaira Z Nunez
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Henry R Kranzler
- Mental Illness Research, Education and Clinical Center, Crescenz VAMC and Center for Studies of Addiction, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Howard J Edenberg
- Departments of Biochemistry and Molecular Biology and Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Jordan W Smoller
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Center for Precision Psychiatry, Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Todd Lencz
- Department of Psychiatry and Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
| | - David M Hougaard
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Neonatal Screening, Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark
| | - Anders D Børglum
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - Ditte Demontis
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
- The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - J Michael Gaziano
- Harvard Medical School, Boston, MA, USA
- Million Veteran Program Coordinating Center, VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Division of Aging, Brigham and Women's Hospital, Boston, MA, USA
| | - Michael J Gandal
- Departments of Psychiatry and Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- The Lifespan Brain Institute, Penn Medicine and the Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Renato Polimanti
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Murray B Stein
- Psychiatry Service, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry and Herbert Wertheim School of Public Health, University of California San Diego, La Jolla, CA, USA
| | - Joel Gelernter
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA.
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA.
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Ding Y, Chen H, Yan Y, Qiu Y, Zhao A, Li B, Xu W, Deng Y. Relationship Between FERMT2, CELF1, COPI, CHRNA2, and ABCA7 Genetic Polymorphisms and Alzheimer's Disease Risk in the Southern Chinese Population. J Alzheimers Dis Rep 2023; 7:1247-1257. [PMID: 38025799 PMCID: PMC10657721 DOI: 10.3233/adr-230072] [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: 07/15/2023] [Accepted: 10/05/2023] [Indexed: 12/01/2023] Open
Abstract
Background Alzheimer's disease (AD) is a multi-gene inherited disease, and apolipoprotein E (APOE) ɛ4 is a strong risk factor. Other genetic factors are important but limited. Objective This study aimed to investigate the relationship between 17 single-nucleotide polymorphisms (SNPs) and AD in the Southern Chinese populations. Methods We recruited 242 AD patients and 208 controls. The SNaPshot technique was used to detect the SNPs. Results Adjusted for sex and age, we found rs6572869 (FERMT2), rs11604680 (CELF1), and rs1317149 (CELF1) were associated with AD risk in the dominant (rs6572869: p = 0.022, OR = 1.55; rs11604680: p = 0.007, OR = 1.68; rs1317149: p = 0.033, OR = 1.50) and overdominant models (rs6572869: p = 0.001, OR = 1.96; rs11604680: p = 0.002, OR = 1.82; rs1317149: p = 0.003, OR = 1.80). rs9898218 (COPI) was associated with AD risk in the overdominant model (p = 0.004, OR = 1.81). Further, rs2741342 (CHRNA2) was associated with AD protection in the dominant (p = 0.002, OR = 0.5) and additive models (p = 0.002, OR = 0.64). Mutations in rs10742814 (CELF1), rs11039280 (CELF1), and rs3752242 (ABCA7) contributed to AD protection. Among them, rs10742814 (CELF1), rs3752242 (ABCA7), and rs11039280 (CELF1) were more significantly associated with AD carrying APOE ɛ4, whereas rs1317149 (CELF1) showed an opposite trend. Interestingly, rs4147912 (ABCA7) and rs2516049 (HLA-DRB1) were identified to be relevant with AD carrying APOE ɛ4. Using expression quantitative trait locus analysis, we found polymorphisms in CELF1 (rs10742814 and rs11039280), ABCA7 (rs4147912), HLA-DRB1 (rs2516049), and ADGRF4 (rs1109581) correlated with their corresponding gene expression in the brain. Conclusions We identified four risk and four protective SNPs associated with AD in the Southern Chinese population, with different correlations between APOE ɛ4 carriers and non-carriers. rs4147912 (ABCA7) and rs2516049 (HLA-DRB1) were associated with AD carrying APOE ɛ4.
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Affiliation(s)
- Yanfei Ding
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Haijuan Chen
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yi Yan
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yinghui Qiu
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Aonan Zhao
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Binyin Li
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Wei Xu
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yulei Deng
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Department of Neurology, Ruijin Hospital, Luwan Branch, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Ciralli B, Malfatti T, Lima TZ, Silva SRB, Cederroth CR, Leao KE. Alterations of auditory sensory gating in mice with noise-induced tinnitus treated with nicotine and cannabis extract. J Psychopharmacol 2023; 37:1116-1131. [PMID: 37837354 DOI: 10.1177/02698811231200879] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/16/2023]
Abstract
Tinnitus is a phantom sound perception affecting both auditory and limbic structures. The mechanisms of tinnitus remain unclear and it is debatable whether tinnitus alters attention to sound and the ability to inhibit repetitive sounds, a phenomenon also known as auditory gating. Here we investigate if noise exposure interferes with auditory gating and whether natural extracts of cannabis or nicotine could improve auditory pre-attentional processing in noise-exposed mice. We used 22 male C57BL/6J mice divided into noise-exposed (exposed to a 9-11 kHz narrow band noise for 1 h) and sham (no sound during noise exposure) groups. Hearing thresholds were measured using auditory brainstem responses, and tinnitus-like behavior was assessed using Gap prepulse inhibition of acoustic startle. After noise exposure, mice were implanted with multi-electrodes in the dorsal hippocampus to assess auditory event-related potentials in response to paired clicks. The results showed that mice with tinnitus-like behavior displayed auditory gating of repetitive clicks, but with larger amplitudes and longer latencies of the N40 component of the aERP waveform. The combination of cannabis extract and nicotine improved the auditory gating ratio in noise-exposed mice without permanent hearing threshold shifts. Lastly, the longer latency of the N40 component appears due to an increased sensitivity to cannabis extract in noise-exposed mice compared to sham mice. The study suggests that the altered central plasticity in tinnitus is more sensitive to the combined actions on the cholinergic and the endocannabinoid systems. Overall, the findings contribute to a better understanding of pharmacological modulation of auditory sensory gating.
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Affiliation(s)
- Barbara Ciralli
- Brain Institute, Federal University of Rio Grande do Norte, Natal, RN, Brazil
| | - Thawann Malfatti
- Brain Institute, Federal University of Rio Grande do Norte, Natal, RN, Brazil
- Experimental Audiology, Department of Physiology and Pharmacology, Karolinska Institutet, Sweden
| | - Thiago Z Lima
- Brain Institute, Federal University of Rio Grande do Norte, Natal, RN, Brazil
- Department of Applied Mathematics and Statistics, Exact and Earth Sciences Center, Federal University of Rio Grande do Norte, Natal, RN, Brazil
| | | | - Christopher R Cederroth
- Experimental Audiology, Department of Physiology and Pharmacology, Karolinska Institutet, Sweden
- Translational Hearing Research, Tübingen Hearing Research Center, Department of Otolaryngology, Head and Neck Surgery, University of Tübingen, Tübingen, Germany
| | - Katarina E Leao
- Brain Institute, Federal University of Rio Grande do Norte, Natal, RN, Brazil
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Ribasés M, Mitjans M, Hartman CA, Soler Artigas M, Demontis D, Larsson H, Ramos-Quiroga JA, Kuntsi J, Faraone SV, Børglum AD, Reif A, Franke B, Cormand B. Genetic architecture of ADHD and overlap with other psychiatric disorders and cognition-related phenotypes. Neurosci Biobehav Rev 2023; 153:105313. [PMID: 37451654 PMCID: PMC10789879 DOI: 10.1016/j.neubiorev.2023.105313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Revised: 06/30/2023] [Accepted: 07/08/2023] [Indexed: 07/18/2023]
Abstract
Attention-deficit/hyperactivity disorder (ADHD) co-occurs with many other psychiatric disorders and traits. In this review, we summarize and interpret the existing literature on the genetic architecture of these comorbidities based on hypothesis-generating approaches. Quantitative genetic studies indicate that genetic factors play a substantial role in the observed co-occurrence of ADHD with many different disorders and traits. Molecular genetic correlations derived from genome-wide association studies and results of studies based on polygenic risk scores confirm the general pattern but provide effect estimates that are smaller than those from twin studies. The identification of the specific genetic variants and biological pathways underlying co-occurrence using genome-wide approaches is still in its infancy. The first analyses of causal inference using genetic data support causal relationships between ADHD and comorbid disorders, although bidirectional effects identified in some instances point to complex relationships. While several issues in the methodology and inferences from the results are still to be overcome, this review shows that the co-occurrence of ADHD with many psychiatric disorders and traits is genetically interpretable.
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Affiliation(s)
- M Ribasés
- Department of Mental Health, Hospital Universitari Vall d'Hebron, Barcelona, Spain; Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Barcelona, Spain; Department of Genetics, Microbiology, and Statistics, Faculty of Biology, Universitat de Barcelona, Barcelona, Spain
| | - M Mitjans
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Barcelona, Spain; Department of Genetics, Microbiology, and Statistics, Faculty of Biology, Universitat de Barcelona, Barcelona, Spain; Institut de Biomedicina de la Universitat de Barcelona (IBUB), Barcelona, Catalonia, Spain; Institut de Recerca Sant Joan de Déu (IRSJD), Esplugues de Llobregat, Catalonia, Spain
| | - C A Hartman
- Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion regulation (ICPE), University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - M Soler Artigas
- Department of Mental Health, Hospital Universitari Vall d'Hebron, Barcelona, Spain; Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Barcelona, Spain; Department of Genetics, Microbiology, and Statistics, Faculty of Biology, Universitat de Barcelona, Barcelona, Spain
| | - D Demontis
- Department of Biomedicine/Human Genetics, Aarhus University, Aarhus, Denmark; The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark; Center for Genomics and Personalized Medicine, Aarhus, Denmark; The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - H Larsson
- School of Medical Sciences, Örebro University, Örebro, Sweden; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - J A Ramos-Quiroga
- Department of Mental Health, Hospital Universitari Vall d'Hebron, Barcelona, Spain; Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Barcelona, Spain; Department of Psychiatry and Forensic Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - J Kuntsi
- Social, Genetic and Developmental Psychiatry Centre; Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - S V Faraone
- Departments of Psychiatry and of Neuroscience and Physiology, Norton College of Medicine, SUNY Upstate Medical University, Syracuse, NY, USA
| | - A D Børglum
- Department of Biomedicine/Human Genetics, Aarhus University, Aarhus, Denmark; The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark; Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - A Reif
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany
| | - B Franke
- Departments of Cognitive Neuroscience and Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands.
| | - B Cormand
- Department of Genetics, Microbiology, and Statistics, Faculty of Biology, Universitat de Barcelona, Barcelona, Spain; Institut de Biomedicina de la Universitat de Barcelona (IBUB), Barcelona, Catalonia, Spain; Institut de Recerca Sant Joan de Déu (IRSJD), Esplugues de Llobregat, Catalonia, Spain; Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBER-ER), Instituto de Salud Carlos III, Madrid, Spain.
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7
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Hilscher MM, Mikulovic S, Perry S, Lundberg S, Kullander K. The alpha2 nicotinic acetylcholine receptor, a subunit with unique and selective expression in inhibitory interneurons associated with principal cells. Pharmacol Res 2023; 196:106895. [PMID: 37652281 DOI: 10.1016/j.phrs.2023.106895] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 08/21/2023] [Accepted: 08/23/2023] [Indexed: 09/02/2023]
Abstract
Nicotinic acetylcholine receptors (nAChRs) play crucial roles in various human disorders, with the α7, α4, α6, and α3-containing nAChR subtypes extensively studied in relation to conditions such as Alzheimer's disease, Parkinson's disease, nicotine dependence, mood disorders, and stress disorders. In contrast, the α2-nAChR subunit has received less attention due to its more restricted expression and the scarcity of specific agonists and antagonists for studying its function. Nevertheless, recent research has shed light on the unique expression pattern of the Chrna2 gene, which encodes the α2-nAChR subunit, and its involvement in distinct populations of inhibitory interneurons. This review highlights the structure, pharmacology, localization, function, and disease associations of α2-containing nAChRs and points to the unique expression pattern of the Chrna2 gene and its role in different inhibitory interneuron populations. These populations, including the oriens lacunosum moleculare (OLM) cells in the hippocampus, Martinotti cells in the neocortex, and Renshaw cells in the spinal cord, share common features and contribute to recurrent inhibitory microcircuits. Thus, the α2-nAChR subunit's unique expression pattern in specific interneuron populations and its role in recurrent inhibitory microcircuits highlight its importance in various physiological processes. Further research is necessary to uncover the comprehensive functionality of α2-containing nAChRs, delineate their specific contributions to neuronal circuits, and investigate their potential as therapeutic targets for related disorders.
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Affiliation(s)
- Markus M Hilscher
- Department of Immunology, Genetics and Pathology, Uppsala University, IGP/BMC, Box 815, 751 08 Uppsala, Sweden; Department of Biochemistry and Biophysics, Science for Life Laboratory, Stockholm University, Solna, Sweden
| | - Sanja Mikulovic
- Department of Immunology, Genetics and Pathology, Uppsala University, IGP/BMC, Box 815, 751 08 Uppsala, Sweden; Leibniz Institute for Neurobiology, Cognition & Emotion Laboratory, Magdeburg, Germany; German Center for Mental Health(DZPG), Germany
| | - Sharn Perry
- Department of Immunology, Genetics and Pathology, Uppsala University, IGP/BMC, Box 815, 751 08 Uppsala, Sweden; Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Australia
| | - Stina Lundberg
- Department of Immunology, Genetics and Pathology, Uppsala University, IGP/BMC, Box 815, 751 08 Uppsala, Sweden
| | - Klas Kullander
- Department of Immunology, Genetics and Pathology, Uppsala University, IGP/BMC, Box 815, 751 08 Uppsala, Sweden.
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8
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Barr PB, Bigdeli TB, Meyers JL, Peterson RE, Sanchez-Roige S, Mallard TT, Dick DM, Paige Harden K, Wilkinson A, Graham DP, Nielsen DA, Swann A, Lipsky RK, Kosten T, Aslan M, Harvey PD, Kimbrel NA, Beckham JC. Correlates of Risk for Disinhibited Behaviors in the Million Veteran Program Cohort. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.03.22.23286865. [PMID: 37034805 PMCID: PMC10081391 DOI: 10.1101/2023.03.22.23286865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Background Many psychiatric outcomes are thought to share a common etiological pathway reflecting behavioral disinhibition, generally referred to as externalizing disorders (EXT). Recent genome-wide association studies (GWAS) have demonstrated the overlap between EXT and important aspects of veterans' health, such as suicide-related behaviors, substance use disorders, and other medical conditions. Methods We conducted a series of phenome-wide association studies (PheWAS) of polygenic scores (PGS) for EXT, and comorbid psychiatric problems (depression, schizophrenia, and suicide attempt) in an ancestrally diverse cohort of U.S. veterans (N = 560,824), using diagnostic codes from electronic health records. We conducted ancestry-specific PheWASs of EXT PGS in the European, African, and Hispanic/Latin American ancestries. To determine if associations were driven by risk for other comorbid problems, we performed a conditional PheWAS, covarying for comorbid psychiatric problems (European ancestries only). Lastly, to adjust for unmeasured confounders we performed a within-family analysis of significant associations from the main PheWAS in full-siblings (N = 12,127, European ancestries only). Results The EXT PGS was associated with 619 outcomes across all bodily systems, of which, 188 were independent of risk for comorbid problems of PGS. Effect sizes ranged from OR = 1.02 (95% CI = 1.01, 1.03) for overweight/obesity to OR = 1.44 (95% CI = 1.42, 1.47) for viral hepatitis C. Of the significant outcomes 73 (11.9%) and 26 (4.5%) were significant in the African and Hispanic/Latin American results, respectively. Within-family analyses uncovered robust associations between EXT and consequences of substance use disorders, including liver disease, chronic airway obstruction, and viral hepatitis C. Conclusion Our results demonstrate a shared polygenic basis of EXT across populations of diverse ancestries and independent of risk for other psychiatric problems. The strongest associations with EXT were for diagnoses related to substance use disorders and their sequelae. Overall, we highlight the potential negative consequences of EXT for health and functioning in the US veteran population.
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Affiliation(s)
- Peter B. Barr
- VA New York Harbor Healthcare System, Brooklyn, NY
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY
- Institute for Genomics in Health (IGH), SUNY Downstate Health Sciences University, Brooklyn, NY
- Department of Epidemiology and Biostatistics, School of Public Health, SUNY Downstate Health Sciences University, Brooklyn, NY
| | - Tim B. Bigdeli
- VA New York Harbor Healthcare System, Brooklyn, NY
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY
- Institute for Genomics in Health (IGH), SUNY Downstate Health Sciences University, Brooklyn, NY
- Department of Epidemiology and Biostatistics, School of Public Health, SUNY Downstate Health Sciences University, Brooklyn, NY
| | - Jacquelyn L. Meyers
- VA New York Harbor Healthcare System, Brooklyn, NY
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY
- Institute for Genomics in Health (IGH), SUNY Downstate Health Sciences University, Brooklyn, NY
- Department of Epidemiology and Biostatistics, School of Public Health, SUNY Downstate Health Sciences University, Brooklyn, NY
| | - Roseann E. Peterson
- VA New York Harbor Healthcare System, Brooklyn, NY
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY
- Institute for Genomics in Health (IGH), SUNY Downstate Health Sciences University, Brooklyn, NY
| | - Sandra Sanchez-Roige
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Travis T. Mallard
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Danielle M. Dick
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ
- Rutgers Addiction Research Center, Rutgers University, Piscataway, NJ
| | - K. Paige Harden
- Department of Psychology, University of Texas at Austin, Austin, TX
- Population Research Center, University of Texas at Austin, Austin, TX
| | - Anna Wilkinson
- Michael E. DeBakey VA Medical Center, Houston, TX
- UTHealth Houston School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX
- Michael and Susan Dell Center for Healthy Living, The University of Texas Health Science Center at Houston, Houston, TX
| | - David P. Graham
- Michael E. DeBakey VA Medical Center, Houston, TX
- Department of Psychiatry, Neuroscience, Pharmacology, and Immunology and Rheumatology, Baylor College of Medicine, Houston, TX
| | - David A. Nielsen
- Michael E. DeBakey VA Medical Center, Houston, TX
- Department of Psychiatry, Neuroscience, Pharmacology, and Immunology and Rheumatology, Baylor College of Medicine, Houston, TX
| | - Alan Swann
- Michael E. DeBakey VA Medical Center, Houston, TX
- Department of Psychiatry, Neuroscience, Pharmacology, and Immunology and Rheumatology, Baylor College of Medicine, Houston, TX
| | - Rachele K. Lipsky
- Michael E. DeBakey VA Medical Center, Houston, TX
- Department of Psychiatry, Neuroscience, Pharmacology, and Immunology and Rheumatology, Baylor College of Medicine, Houston, TX
| | - Thomas Kosten
- Michael E. DeBakey VA Medical Center, Houston, TX
- Department of Psychiatry, Neuroscience, Pharmacology, and Immunology and Rheumatology, Baylor College of Medicine, Houston, TX
| | - Mihaela Aslan
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Yale University School of Medicine, New Haven, CT
| | - Philip D. Harvey
- Research Service, Bruce W. Carter Miami Veterans Affairs (VA) Medical Center, Miami, FL
- University of Miami Miller School of Medicine, Miami, FL
| | - Nathan A. Kimbrel
- Durham VA Health Care System, Durham, NC
- VA Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham, NC
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC
| | - Jean C. Beckham
- Durham VA Health Care System, Durham, NC
- VA Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham, NC
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC
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9
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Babayeva M, Loewy ZG. Cannabis Pharmacogenomics: A Path to Personalized Medicine. Curr Issues Mol Biol 2023; 45:3479-3514. [PMID: 37185752 PMCID: PMC10137111 DOI: 10.3390/cimb45040228] [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: 03/10/2023] [Revised: 04/05/2023] [Accepted: 04/12/2023] [Indexed: 05/17/2023] Open
Abstract
Cannabis and related compounds have created significant research interest as a promising therapy in many disorders. However, the individual therapeutic effects of cannabinoids and the incidence of side effects are still difficult to determine. Pharmacogenomics may provide the answers to many questions and concerns regarding the cannabis/cannabinoid treatment and help us to understand the variability in individual responses and associated risks. Pharmacogenomics research has made meaningful progress in identifying genetic variations that play a critical role in interpatient variability in response to cannabis. This review classifies the current knowledge of pharmacogenomics associated with medical marijuana and related compounds and can assist in improving the outcomes of cannabinoid therapy and to minimize the adverse effects of cannabis use. Specific examples of pharmacogenomics informing pharmacotherapy as a path to personalized medicine are discussed.
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Affiliation(s)
- Mariana Babayeva
- Department of Biomedical and Pharmaceutical Sciences, Touro College of Pharmacy, New York, NY 10027, USA
| | - Zvi G Loewy
- Department of Biomedical and Pharmaceutical Sciences, Touro College of Pharmacy, New York, NY 10027, USA
- Department of Pathology, Microbiology and Immunology, New York Medical College, Valhalla, NY 10595, USA
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10
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Peng Q, Wilhelmsen KC, Ehlers CL. Pleiotropic loci for cannabis use disorder severity in multi-ancestry high-risk populations. Mol Cell Neurosci 2023; 125:103852. [PMID: 37061172 DOI: 10.1016/j.mcn.2023.103852] [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: 11/30/2022] [Revised: 04/04/2023] [Accepted: 04/07/2023] [Indexed: 04/17/2023] Open
Abstract
Cannabis use disorder (CUD) is common and has in part a genetic basis. The risk factors underlying its development likely involve multiple genes that are polygenetic and interact with each other and the environment to ultimately lead to the disorder. Co-morbidity and genetic correlations have been identified between CUD and other disorders and traits in select populations primarily of European descent. If two or more traits, such as CUD and another disorder, are affected by the same genetic locus, they are said to be pleiotropic. The present study aimed to identify specific pleiotropic loci for the severity level of CUD in three high-risk population cohorts: American Indians (AI), Mexican Americans (MA), and European Americans (EA). Using a previously developed computational method based on a machine learning technique, we leveraged the entire GWAS catalog and identified 114, 119, and 165 potentially pleiotropic variants for CUD severity in AI, MA, and EA respectively. Ten pleiotropic loci were shared between the cohorts although the exact variants from each cohort differed. While majority of the pleiotropic genes were distinct in each cohort, they converged on numerous enriched biological pathways. The gene ontology terms associated with the pleiotropic genes were predominately related to synaptic functions and neurodevelopment. Notable pathways included Wnt/β-catenin signaling, lipoprotein assembly, response to UV radiation, and components of the complement system. The pleiotropic genes were the most significantly differentially expressed in frontal cortex and coronary artery, up-regulated in adipose tissue, and down-regulated in testis, prostate, and ovary. They were significantly up-regulated in most brain tissues but were down-regulated in the cerebellum and hypothalamus. Our study is the first to attempt a large-scale pleiotropy detection scan for CUD severity. Our findings suggest that the different population cohorts may have distinct genetic factors for CUD, however they share pleiotropic genes from underlying pathways related to Alzheimer's disease, neuroplasticity, immune response, and reproductive endocrine systems.
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Affiliation(s)
- Qian Peng
- Department of Neuroscience, The Scripps Research Institute, La Jolla, CA 92037, USA.
| | - Kirk C Wilhelmsen
- Department of Neurology, West Virginia University, Morgantown, WV 26506, USA
| | - Cindy L Ehlers
- Department of Neuroscience, The Scripps Research Institute, La Jolla, CA 92037, USA
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11
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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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12
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Al-Soufi L, Costas J. Genetic susceptibility for schizophrenia after adjustment by genetic susceptibility for smoking: implications in identification of risk genes and genetic correlation with related traits. Psychol Med 2023; 53:1-11. [PMID: 36876478 DOI: 10.1017/s0033291723000326] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/07/2023]
Abstract
BACKGROUND Prevalence of smoking in schizophrenia (SCZ) is larger than in general population. Genetic studies provided some evidence of a causal effect of smoking on SCZ. We aim to characterize the genetic susceptibility to SCZ affected by genetic susceptibility to smoking. METHODS Multi-trait-based conditional and joint analysis was applied to the largest European SCZ genome-wide association studies (GWAS) to remove genetic effects on SCZ driven by smoking, estimated by generalized summary data-based Mendelian randomization. Enrichment analysis was performed to compare original v. conditional GWAS. Change in genetic correlation between SCZ and relevant traits after conditioning was assessed. Colocalization analysis was performed to identify specific loci confirming general findings. RESULTS Conditional analysis identified 19 new risk loci for SCZ and 42 lost loci whose association with SCZ may be partially driven by smoking. These results were strengthened by colocalization analysis. Enrichment analysis indicated a higher association of differentially expressed genes at prenatal brain stages after conditioning. Genetic correlation of SCZ with substance use and dependence, attention deficit-hyperactivity disorder, and several externalizing traits significantly changed after conditioning. Colocalization of association signal between SCZ and these traits was identified for some of the lost loci, such as CHRNA2, CUL3, and PCDH7. CONCLUSIONS Our approach led to identification of potential new SCZ loci, loci partially associated to SCZ through smoking, and a shared genetic susceptibility between SCZ and smoking behavior related to externalizing phenotypes. Application of this approach to other psychiatric disorders and substances may lead to a better understanding of the role of substances on mental health.
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Affiliation(s)
- Laila Al-Soufi
- Psychiatric Genetics group, Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Santiago de Compostela, Galicia, Spain
- Red de Investigación en Atención Primaria de Adicciones (RIAPAd), Spain
- Department of Zoology, Genetics and Physical Anthropology, Universidade de Santiago de Compostela (USC), Santiago de Compostela, Galicia, Spain
| | - Javier Costas
- Psychiatric Genetics group, Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Santiago de Compostela, Galicia, Spain
- Red de Investigación en Atención Primaria de Adicciones (RIAPAd), Spain
- Complexo Hospitalario Universitario de Santiago de Compostela (CHUS), Servizo Galego de Saúde (SERGAS), Santiago de Compostela, Galicia, Spain
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13
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Buzzi B, Koseli E, Moncayo L, Shoaib M, Damaj M. Role of Neuronal Nicotinic Acetylcholine Receptors in Cannabinoid Dependence. Pharmacol Res 2023; 191:106746. [PMID: 37001709 DOI: 10.1016/j.phrs.2023.106746] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 03/15/2023] [Accepted: 03/27/2023] [Indexed: 03/30/2023]
Abstract
Cannabis is among the most widely consumed psychoactive drugs around the world and cannabis use disorder (CUD) has no current approved pharmacological treatment. Nicotine and cannabis are commonly co-used which suggests there to be overlapping neurobiological actions supported primarily by the co-distribution of both receptor systems in the brain. There appears to be strong rationale to explore the role that nicotinic receptors play in cannabinoid dependence. Preclinical studies suggest that the ɑ7 nAChR subtype may play a role in modulating the reinforcing and discriminative stimulus effects of cannabinoids, while the ɑ4β2 * nAChR subtype may be involved in modulating the motor and sedative effects of cannabinoids. Preclinical and human genetic studies point towards a potential role of the ɑ5, ɑ3, and β4 nAChR subunits in CUD, while human GWAS studies strongly implicate the ɑ2 subunit as playing a role in CUD susceptibility. Clinical studies suggest that current smoking cessation agents, such as varenicline and bupropion, may also be beneficial in treating CUD, although more controlled studies are necessary. Additional behavioral, molecular, and mechanistic studies investigating the role of nAChR in the modulation of the pharmacological effects of cannabinoids are needed.
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14
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D'Souza DC, DiForti M, Ganesh S, George TP, Hall W, Hjorthøj C, Howes O, Keshavan M, Murray RM, Nguyen TB, Pearlson GD, Ranganathan M, Selloni A, Solowij N, Spinazzola E. Consensus paper of the WFSBP task force on cannabis, cannabinoids and psychosis. World J Biol Psychiatry 2022; 23:719-742. [PMID: 35315315 DOI: 10.1080/15622975.2022.2038797] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/09/2023]
Abstract
OBJECTIVES The liberalisation of cannabis laws, the increasing availability and potency of cannabis has renewed concern about the risk of psychosis with cannabis. METHODS The objective of the WFSBP task force was to review the literature about this relationship. RESULTS Converging lines of evidence suggest that exposure to cannabis increases the risk for psychoses ranging from transient psychotic states to chronic recurrent psychosis. The greater the dose, and the earlier the age of exposure, the greater the risk. For some psychosis outcomes, the evidence supports some of the criteria of causality. However, alternate explanations including reverse causality and confounders cannot be conclusively excluded. Furthermore, cannabis is neither necessary nor sufficient to cause psychosis. More likely it is one of the multiple causal components. In those with established psychosis, cannabis has a negative impact on the course and expression of the illness. Emerging evidence also suggests alterations in the endocannabinoid system in psychotic disorders. CONCLUSIONS Given that exposure to cannabis and cannabinoids is modifiable, delaying or eliminating exposure to cannabis or cannabinoids, could potentially impact the rates of psychosis related to cannabis, especially in those who are at high risk for developing the disorder.
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Affiliation(s)
- Deepak Cyril D'Souza
- Psychiatry Service, VA Connecticut Healthcare System, West Haven, CT, USA.,Abraham Ribicoff Research Facilities, Connecticut Mental Health Center, New Haven, CT, USA.,Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Marta DiForti
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King's College London, London, UK.,South London and Maudsley NHS Mental Health Foundation Trust, London, UK
| | - Suhas Ganesh
- Psychiatry Service, VA Connecticut Healthcare System, West Haven, CT, USA.,Abraham Ribicoff Research Facilities, Connecticut Mental Health Center, New Haven, CT, USA.,Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Tony P George
- Addictions Division and Centre for Complex Interventions, Centre for Addiction and Mental Health (CAMH), Toronto, Canada.,Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Wayne Hall
- The National Centre for Youth Substance Use Research, University of Queensland, Brisbane, Australia
| | - Carsten Hjorthøj
- Copenhagen Research Center for Mental Health - CORE, Mental Health Center Copenhagen, Copenhagen University, Copenhagen, Denmark.,Department of Public Health, Section of Epidemiology, University of Copenhagen, Copenhagen, Denmark
| | - Oliver Howes
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,Institute for Clinical Sciences, Imperial College London, London, UK
| | - Matcheri Keshavan
- Beth Israel Deaconess Medical Center, Massachusetts Mental Health Center, Harvard Medical School, Boston, MA, USA
| | - Robin M Murray
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Timothy B Nguyen
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King's College London, London, UK.,Institute for Clinical Sciences, Imperial College London, London, UK
| | - Godfrey D Pearlson
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA.,Olin Neuropsychiatry Ctr. Institute of Living, Hartford, CT, USA
| | - Mohini Ranganathan
- Psychiatry Service, VA Connecticut Healthcare System, West Haven, CT, USA.,Abraham Ribicoff Research Facilities, Connecticut Mental Health Center, New Haven, CT, USA.,Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Alex Selloni
- Abraham Ribicoff Research Facilities, Connecticut Mental Health Center, New Haven, CT, USA.,Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Nadia Solowij
- School of Psychology and Illawarra Health and Medical Research Institute, University of Wollongong, Wollongong, NSW, Australia.,Australian Centre for Cannabinoid Clinical and Research Excellence (ACRE), New Lambton Heights, NSW, Australia
| | - Edoardo Spinazzola
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
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15
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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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16
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Zuo Y, Iemolo A, Montilla-Perez P, Li HR, Yang X, Telese F. Chronic adolescent exposure to cannabis in mice leads to sex-biased changes in gene expression networks across brain regions. Neuropsychopharmacology 2022; 47:2071-2080. [PMID: 35995972 PMCID: PMC9556757 DOI: 10.1038/s41386-022-01413-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 07/06/2022] [Accepted: 07/25/2022] [Indexed: 11/17/2022]
Abstract
During adolescence, frequent and heavy cannabis use can lead to serious adverse health effects and cannabis use disorder (CUD). Rodent models of adolescent exposure to the main psychoactive component of cannabis, delta-9-tetrahydrocannabinol (THC), mimic the behavioral alterations observed in adolescent users. However, the underlying molecular mechanisms remain largely unknown. Here, we treated female and male C57BL6/N mice with high doses of THC during early adolescence and assessed their memory and social behaviors in late adolescence. We then profiled the transcriptome of five brain regions involved in cognitive and addiction-related processes. We applied gene coexpression network analysis and identified gene coexpression modules, termed cognitive modules, that simultaneously correlated with THC treatment and memory traits reduced by THC. The cognitive modules were related to endocannabinoid signaling in the female dorsal medial striatum, inflammation in the female ventral tegmental area, and synaptic transmission in the male nucleus accumbens. Moreover, cross-brain region module-module interaction networks uncovered intra- and inter-region molecular circuitries influenced by THC. Lastly, we identified key driver genes of gene networks associated with THC in mice and genetic susceptibility to CUD in humans. This analysis revealed a common regulatory mechanism linked to CUD vulnerability in the nucleus accumbens of females and males, which shared four key drivers (Hapln4, Kcnc1, Elavl2, Zcchc12). These genes regulate transcriptional subnetworks implicated in addiction processes, synaptic transmission, brain development, and lipid metabolism. Our study provides novel insights into disease mechanisms regulated by adolescent exposure to THC in a sex- and brain region-specific manner.
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Affiliation(s)
- Yanning Zuo
- grid.19006.3e0000 0000 9632 6718Department of Integrative Biology and Physiology, University of California, Los Angeles, CA USA ,grid.19006.3e0000 0000 9632 6718Neuroscience Interdepartmental Program, University of California Los Angeles, Los Angeles, CA USA ,grid.266100.30000 0001 2107 4242Department of Medicine, University of California, San Diego, CA USA
| | - Attilio Iemolo
- grid.266100.30000 0001 2107 4242Department of Medicine, University of California, San Diego, CA USA
| | - Patricia Montilla-Perez
- grid.266100.30000 0001 2107 4242Department of Medicine, University of California, San Diego, CA USA
| | - Hai-Ri Li
- grid.266100.30000 0001 2107 4242Department of Medicine, University of California, San Diego, CA USA
| | - Xia Yang
- grid.19006.3e0000 0000 9632 6718Department of Integrative Biology and Physiology, University of California, Los Angeles, CA USA ,grid.19006.3e0000 0000 9632 6718Institute for Quantitative and Computational Biosciences, University of California, Los Angeles, CA USA ,grid.19006.3e0000 0000 9632 6718Brain Research Institute, University of California, Los Angeles, CA USA
| | - Francesca Telese
- Department of Medicine, University of California, San Diego, CA, USA.
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17
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Identifying risk-thresholds for the association between frequency of cannabis use and development of cannabis use disorder: A systematic review and meta-analysis. Drug Alcohol Depend 2022; 238:109582. [PMID: 35932748 DOI: 10.1016/j.drugalcdep.2022.109582] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Revised: 07/15/2022] [Accepted: 07/18/2022] [Indexed: 12/23/2022]
Abstract
BACKGROUND Cannabis use disorder (CUD) affects one-in-five cannabis users, presenting a major contributor to cannabis-associated disease burden. Epidemiological data identify the frequency of cannabis use as a risk factor for CUD. This review aimed to determine quantifiable risk-thresholds of the frequency of cannabis use for developing CUD. METHODS Systematic search of Medline, EMBASE, PsycInfo, CINAHL, and Web of Science for cohort/case-control studies that assessed the association between frequency of cannabis use and CUD from 2000 to 2022. Effect estimates were converted to risk ratios (RR). A random-effects multi-level multivariate meta-analytic approach was utilized, and sensitivity analyses conducted. Quality of included studies was assessed with the Newcastle Ottawa Scale. RESULTS Six prospective cohort studies were included in this review, drawn from two main source studies. Random-effect modeling showed a significant log-linear dose-response association between the frequency of cannabis use and CUD risk (p < 0.0001). The risk of CUD increased from RR:2.03 (95% CI:1.85-2.22) for 'yearly' use, to RR:4.12 (95% CI:3.44-4.95) for 'monthly" use, RR:8.37 (95% CI:6.37-11.00) for 'weekly' use, and RR:16.99 (95% CI:11.80-24.46) for 'daily' use. Multi-level modeling showed an absolute risk increase (ARI) from 3.5% (95% CI:2.6-4.7) for 'yearly' use, to 8.0% (95% CI:5.3-12.1) for 'monthly' use, to 16.8% (95% CI:8.8-32.0) for 'weekly' use, and 36% (95% CI:27.047.9) for 'daily' use. CONCLUSION A limited risk of CUD as a potential outcome of cannabis use exists even at infrequent levels of use, but significantly increases as frequency of use increases. Corresponding information should be conveyed to cannabis users as part of targeted prevention messaging to promote safer cannabis use.
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18
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Chang XW, Sun Y, Muhai JN, Li YY, Chen Y, Lu L, Chang SH, Shi J. Common and distinguishing genetic factors for substance use behavior and disorder: an integrated analysis of genomic and transcriptomic studies from both human and animal studies. Addiction 2022; 117:2515-2529. [PMID: 35491750 DOI: 10.1111/add.15908] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/30/2021] [Accepted: 04/04/2022] [Indexed: 11/30/2022]
Abstract
BACKGROUND AND AIMS Genomic and transcriptomic findings greatly broaden the biological knowledge regarding substance use. However, systematic convergence and comparison evidence of genome-wide findings is lacking for substance use. Here, we combined all the genome-wide findings from both substance use behavior and disorder (SUBD) and identified common and distinguishing genetic factors for different SUBDs. METHODS Systemic literature search for genome-wide association (GWAS) and RNA-seq studies of alcohol/nicotine/drug use behavior (partially meets or not reported diagnostic criteria) and alcohol use behavior and disorder (AUBD), nicotine use behavior and disorder (NUBD) and drug use behavior and disorder (DUBD) was performed using PubMed and the GWAS catalog. Drug use was focused upon cannabis, opioid, cocaine and methamphetamine use. GWAS studies required case-control or case/cohort samples. RNA-seq studies were based on brain tissues. The genes which contained significant single nucleotide polymorphism (P ≤ 1 × 10-6 ) in GWAS and reported as significant in RNA-seq studies were extracted. Pathway enrichment was performed by using Metascape. Gene interaction networks were identified by using the Protein Interaction Network Analysis database. RESULTS Total SUBD-related 2910 genes were extracted from 75 GWAS studies (2 773 889 participants) and 17 RNA-seq studies. By overlapping the genes and pathways of AUBD, NUBD and DUBD, four shared genes (CACNB2, GRIN2B, PLXDC2 and PKNOX2), four shared pathways [two Gene Ontology (GO) terms of 'modulation of chemical synaptic transmission', 'regulation of trans-synaptic signaling', two Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of 'dopaminergic synapse', 'cocaine addiction'] were identified (significantly higher than random, P < 1 × 10-5 ). The top shared KEGG pathways (Benjamini-Hochberg-corrected P-value < 0.05) in the pairwise comparison of AUBD versus DUBD, NUBD versus DUBD, AUBD versus NUBD were 'Epstein-Barr virus infection', 'protein processing in endoplasmic reticulum' and 'neuroactive ligand-receptor interaction', respectively. We also identified substance-specific genetic factors: i.e. ADH1B and ALDH2 were unique for AUBD, while CHRNA3 and CHRNA4 were unique for NUBD. CONCLUSIONS This systematic review identifies the shared and unique genes and pathways for alcohol, nicotine and drug use behaviors and disorders at the genome-wide level and highlights critical biological processes for the common and distinguishing vulnerability of substance use behaviors and disorders.
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Affiliation(s)
- Xiang-Wen Chang
- Department of Pharmacology, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China.,National Institute on Drug Dependence, Peking University, Beijing, China
| | - Yan Sun
- Department of Pharmacology, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China.,National Institute on Drug Dependence, Peking University, Beijing, China
| | - Jia-Na Muhai
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Yang-Yang Li
- Department of Pharmacology, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China.,National Institute on Drug Dependence, Peking University, Beijing, China
| | - Yun Chen
- Department of Pharmacology, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China.,National Institute on Drug Dependence, Peking University, Beijing, China
| | - Lin Lu
- National Institute on Drug Dependence, Peking University, Beijing, China.,Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Su-Hua Chang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Jie Shi
- National Institute on Drug Dependence, Peking University, Beijing, China.,Beijing Key Laboratory of Drug Dependence Research, Peking University, Beijing, China.,The State Key Laboratory of Natural and Biomimetic Drugs, Peking University, Beijing, China.,The Key Laboratory for Neuroscience of the Ministry of Education and Health, Peking University, Beijing, China
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19
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Lesmana MHS, Le NQK, Chiu WC, Chung KH, Wang CY, Irham LM, Chung MH. Genomic-Analysis-Oriented Drug Repurposing in the Search for Novel Antidepressants. Biomedicines 2022; 10:biomedicines10081947. [PMID: 36009493 PMCID: PMC9405592 DOI: 10.3390/biomedicines10081947] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 08/07/2022] [Accepted: 08/08/2022] [Indexed: 12/02/2022] Open
Abstract
From inadequate prior antidepressants that targeted monoamine neurotransmitter systems emerged the discovery of alternative drugs for depression. For instance, drugs targeted interleukin 6 receptor (IL6R) in inflammatory system. Genomic analysis-based drug repurposing using single nucleotide polymorphism (SNP) inclined a promising method for several diseases. However, none of the diseases was depression. Thus, we aimed to identify drug repurposing candidates for depression treatment by adopting a genomic-analysis-based approach. The 5885 SNPs obtained from the machine learning approach were annotated using HaploReg v4.1. Five sets of functional annotations were applied to determine the depression risk genes. The STRING database was used to expand the target genes and identify drug candidates from the DrugBank database. We validated the findings using the ClinicalTrial.gov and PubMed databases. Seven genes were observed to be strongly associated with depression (functional annotation score = 4). Interestingly, IL6R was auspicious as a target gene according to the validation outcome. We identified 20 drugs that were undergoing preclinical studies or clinical trials for depression. In addition, we identified sarilumab and satralizumab as drugs that exhibit strong potential for use in the treatment of depression. Our findings indicate that a genomic-analysis-based approach can facilitate the discovery of drugs that can be repurposed for treating depression.
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Affiliation(s)
| | - Nguyen Quoc Khanh Le
- Professional Master Program in Artificial Intelligence in Medicine, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan
- Research Center for Artificial Intelligence in Medicine, Taipei Medical University, Taipei 11031, Taiwan
- Translational Imaging Research Center, Taipei Medical University Hospital, Taipei 11031, Taiwan
| | - Wei-Che Chiu
- Department of Psychiatry, Cathay General Hospital, Taipei 10630, Taiwan
- School of Medicine, Fu Jen Catholic University, New Taipei City 242062, Taiwan
| | - Kuo-Hsuan Chung
- Department of Psychiatry, School of Medicine, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan
- Department of Psychiatry and Psychiatric Research Center, Taipei Medical University Hospital, Taipei Medical University, Taipei 11031, Taiwan
| | - Chih-Yang Wang
- Ph.D. Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University and Academia Sinica, Taipei 11031, Taiwan
- Graduate Institute of Cancer Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, Taiwan
| | - Lalu Muhammad Irham
- Faculty of Pharmacy, University of Ahmad Dahlan, Yogyakarta 55164, Indonesia
- Correspondence: (L.M.I.); (M.-H.C.); Tel.: +62-851-322-55-414 (L.M.I.); +886-02-2736-1661 (M.-H.C.)
| | - Min-Huey Chung
- School of Nursing, College of Nursing, Taipei Medical University, Taipei 11031, Taiwan
- Department of Nursing, Shuang Ho Hospital, Taipei Medical University, New Taipei City 23561, Taiwan
- Correspondence: (L.M.I.); (M.-H.C.); Tel.: +62-851-322-55-414 (L.M.I.); +886-02-2736-1661 (M.-H.C.)
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20
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Ferraro L, Quattrone D, La Barbera D, La Cascia C, Morgan C, Kirkbride JB, Cardno AG, Sham P, Tripoli G, Sideli L, Seminerio F, Sartorio C, Szoke A, Tarricone I, Bernardo M, Rodriguez V, Stilo SA, Gayer-Anderson C, de Haan L, Velthorst E, Jongsma H, Bart RBP, Richards A, Arango C, Menezez PR, Lasalvia A, Tosato S, Tortelli A, Del Ben CM, Selten JP, Jones PB, van Os J, Di Forti M, Vassos E, Murray RM. First-Episode Psychosis Patients Who Deteriorated in the Premorbid Period Do Not Have Higher Polygenic Risk Scores Than Others: A Cluster Analysis of EU-GEI Data. Schizophr Bull 2022; 49:218-227. [PMID: 35947471 PMCID: PMC9810012 DOI: 10.1093/schbul/sbac100] [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] [Indexed: 01/07/2023]
Abstract
Cluster studies identified a subgroup of patients with psychosis whose premorbid adjustment deteriorates before the onset, which may reflect variation in genetic influence. However, other studies reported a complex relationship between distinctive patterns of cannabis use and cognitive and premorbid impairment that is worthy of consideration. We examined whether: (1) premorbid social functioning (PSF) and premorbid academic functioning (PAF) in childhood and adolescence and current intellectual quotient (IQ) define different clusters in 802 first-episode of psychosis (FEP) patients; resulting clusters vary in (2) polygenic risk scores (PRSs) for schizophrenia (SCZ_PRS), bipolar disorder (BD_PRS), major depression (MD_PRS), and IQ (IQ_PRS), and (3) patterns of cannabis use, compared to 1,263 population-based controls. Four transdiagnostic clusters emerged (BIC = 2268.5): (1) high-cognitive-functioning (n = 205), with the highest IQ (Mean = 106.1, 95% CI: 104.3, 107.9) and PAF, but low PSF. (2) Low-cognitive-functioning (n = 223), with the lowest IQ (Mean = 73.9, 95% CI: 72.2, 75.7) and PAF, but normal PSF. (3) Intermediate (n = 224) (Mean_IQ = 80.8, 95% CI: 79.1, 82.5) with low-improving PAF and PSF. 4) Deteriorating (n = 150) (Mean_IQ = 80.6, 95% CI: 78.5, 82.7), with normal-deteriorating PAF and PSF. The PRSs explained 7.9% of between-group membership. FEP had higher SCZ_PRS than controls [F(4,1319) = 20.4, P < .001]. Among the clusters, the deteriorating group had lower SCZ_PRS and was likelier to have used high-potency cannabis daily. Patients with FEP clustered according to their premorbid and cognitive abilities. Pronounced premorbid deterioration was not typical of most FEP, including those more strongly predisposed to schizophrenia, but appeared in a cluster with a history of high-potency cannabis use.
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Affiliation(s)
- Laura Ferraro
- To whom correspondence should be addressed; Via Gaetano La Loggia, 1, Palermo 90129, Italy; tel and fax: 091 6555170, e-mail
| | - Diego Quattrone
- Department of Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK,National Institute for Health Research, Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College, London, UK,South London and Maudsley Mental Health NHS Trust, London, UK
| | - Daniele La Barbera
- Department of Biomedicine, Neuroscience and Advanced Diagnostics (BiND), Psychiatry Section, University of Palermo, Palermo, Italy
| | - Caterina La Cascia
- Department of Biomedicine, Neuroscience and Advanced Diagnostics (BiND), Psychiatry Section, University of Palermo, Palermo, Italy
| | - Craig Morgan
- Department of Health Service and Population Research, Institute of Psychiatry, King’s College London, London, UK
| | - James B Kirkbride
- Division of Psychiatry, University College London, Psylife Group, London, UK
| | - Alastair G Cardno
- Division of Psychological and Social Medicine, University of Leeds, Leeds, UK
| | - Pak Sham
- Li KaShing Faculty of Medicine, The University of Hong Kong, Centre for Genomic Sciences, Hong Kong, China
| | - Giada Tripoli
- Department of Biomedicine, Neuroscience and Advanced Diagnostics (BiND), Psychiatry Section, University of Palermo, Palermo, Italy,Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Lucia Sideli
- Department of Biomedicine, Neuroscience and Advanced Diagnostics (BiND), Psychiatry Section, University of Palermo, Palermo, Italy,LUMSA University, Department of Human Science, Rome
| | - Fabio Seminerio
- Department of Biomedicine, Neuroscience and Advanced Diagnostics (BiND), Psychiatry Section, University of Palermo, Palermo, Italy
| | - Crocettarachele Sartorio
- Department of Biomedicine, Neuroscience and Advanced Diagnostics (BiND), Psychiatry Section, University of Palermo, Palermo, Italy
| | - Andrei Szoke
- University of Paris Est Creteil, INSERM, IMRB, AP-HP, Hôpitaux Universitaires, H. Mondor, DMU IMPACT, F-94010 Creteil, France
| | - Ilaria Tarricone
- Department of Medical and Surgical Science, Psychiatry Unit, Alma Mater Studiorum, University of Bologna, Bologna, Italy
| | - Miquel Bernardo
- Department of Medicine, IDIBAPS, CIBERSAM, Barcelona Clinic Schizophrenia Unit, Neuroscience Institute, Hospital Clinic of Barcelona, University of Barcelona, Barcelona, Spain
| | - Victoria Rodriguez
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Simona A Stilo
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK,Department of Mental Health and Addiction Services, ASP Crotone, Crotone, Italy
| | - Charlotte Gayer-Anderson
- Department of Health Service and Population Research, Institute of Psychiatry, King’s College London, London, UK
| | - Lieuwe de Haan
- Department of Psychiatry, Early Psychosis Section, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands
| | - Eva Velthorst
- Department of Psychiatry and Seaver Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, USA,Center for Transcultural Psychiatry Veldzicht, Balkbrug, Overijssel, The Netherlands
| | - Hannah Jongsma
- Division of Psychiatry, University College London, Psylife Group, London, UK,Center for Transcultural Psychiatry Veldzicht, Balkbrug, Overijssel, The Netherlands,University Centre for Psychiatry, University Medical Centre Groningen, Groningen, The Netherlands
| | - Rutten B P Bart
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Alexander Richards
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK
| | - Celso Arango
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense de Madrid, Madrid, Spain
| | - Paulo Rossi Menezez
- Department of Preventive Medicine, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
| | - Antonio Lasalvia
- Section of Psychiatry, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Sarah Tosato
- Section of Psychiatry, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Andrea Tortelli
- Institut Mondor de recherché biomedicale, Creteil, France,Etablissement Public de Sante Maison Blanche, Paris, France
| | - Cristina Marta Del Ben
- Neuroscience and Behaviour Department, Ribeirão Preto Medical School, University of São Paulo, Brazil
| | - Jean-Paul Selten
- University Centre for Psychiatry, University Medical Centre Groningen, Groningen, The Netherlands,Rivierduinen Institute for Mental Health Care, Leiden, The Netherlands
| | - Peter B Jones
- Department of Psychiatry, University of Cambridgeshire and Peterborough NHS Foundation Trust, CAMEO Early Intervention Service, Cambridge, UK
| | - Jim van Os
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK,Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands,UMC Utrecht Brain Centre Rudolf Magnus, Utrecht University, Utrecht, The Netherlands
| | | | - Marta Di Forti
- Department of Biomedicine, Neuroscience and Advanced Diagnostics (BiND), Psychiatry Section, University of Palermo, Palermo, Italy,Department of Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK,National Institute for Health Research, Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College, London, UK
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21
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de Marco A, Scozia G, Manfredi L, Conversi D. A Systematic Review of Genetic Polymorphisms Associated with Bipolar Disorder Comorbid to Substance Abuse. Genes (Basel) 2022; 13:genes13081303. [PMID: 35893041 PMCID: PMC9330731 DOI: 10.3390/genes13081303] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Revised: 07/20/2022] [Accepted: 07/21/2022] [Indexed: 01/09/2023] Open
Abstract
It is currently unknown which genetic polymorphisms are involved in substance use disorder (SUD) comorbid with bipolar disorder (BD). The research on polymorphisms in BD comorbid with SUD (BD + SUD) is summarized in this systematic review. We looked for case-control studies that genetically compared adults and adolescents with BD and SUD, healthy controls, and BD without SUD. PRISMA was used to create our protocol, which is PROSPERO-registered (identification: CRD4221270818). The following bibliographic databases were searched indefinitely until December 2021 to identify potentially relevant articles: PubMed, PsycINFO, Scopus, and Web of Science. This systematic review, after the qualitative analysis of the study selection, included 17 eligible articles. In the selected studies, 66 polymorphisms in 29 genes were investigated. The present work delivers a group of potentially valuable genetic polymorphisms associated with BD + SUD: rs11600996 (ARNTL), rs228642/rs228682/rs2640909 (PER3), PONQ192R (PON1), rs945032 (BDKRB2), rs1131339 (NR4A3), and rs6971 (TSPO). It is important to note that none of those findings have been confirmed by two or more studies; thus, we believe that all the polymorphisms identified in this review require additional evidence to be confirmed.
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Affiliation(s)
- Adriano de Marco
- Department of Psychology, Università degli Studi di Roma ‘La Sapienza’, 00185 Rome, Italy; (A.d.M.); (G.S.); (L.M.)
| | - Gabriele Scozia
- Department of Psychology, Università degli Studi di Roma ‘La Sapienza’, 00185 Rome, Italy; (A.d.M.); (G.S.); (L.M.)
- PhD Program in Behavioral Neuroscience, Università degli Studi di Roma ‘La Sapienza’, 00185 Rome, Italy
| | - Lucia Manfredi
- Department of Psychology, Università degli Studi di Roma ‘La Sapienza’, 00185 Rome, Italy; (A.d.M.); (G.S.); (L.M.)
| | - David Conversi
- Department of Psychology, Università degli Studi di Roma ‘La Sapienza’, 00185 Rome, Italy; (A.d.M.); (G.S.); (L.M.)
- Correspondence:
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22
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Pan C, Ye J, Wen Y, Chu X, Jia Y, Cheng B, Cheng S, Liu L, Yang X, Liang C, Wu C, Wang S, Wang X, Ning Y, Zhang F, Ma X. The associations between sleep behaviors, lifestyle factors, genetic risk and mental disorders: A cohort study of 402 290 UK Biobank participants. Psychiatry Res 2022; 311:114488. [PMID: 35247746 DOI: 10.1016/j.psychres.2022.114488] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Revised: 02/17/2022] [Accepted: 02/23/2022] [Indexed: 10/19/2022]
Abstract
BACKGROUND Sleep behaviors were believed to be associated with mental disorders (MD). However, the underlying mechanism of such association relationship, especially the role of multiple lifestyle factors in it remains unclear. METHODS A total of 402,290 participants from UK Biobank who don't have MD at baseline were included. They were divided into poor, intermediate and healthy sleep patterns according to the sleep score, which was calculated based on the data collecting from five sleep behaviors. Cox proportional hazard model was used to estimate the associations between sleep behaviors and MD. The associations were further estimated when taking lifestyle factors such as physical activity, coffee intake, tea intake and genetic susceptibility into account. RESULTS Healthy sleep pattern was associated with lower risk of overall MD status (HR,0.41, 95%CI,0.39-0.43), depressive disorders (HR,0.34, 95%CI,0.31-0.37) and anxiety disorders (HR,0.46, 95%CI,0.41-0.79), compared with poor sleep pattern. And in each subgroup of physical activity, tea intake, coffee intake, age and genetic risk scores (GRS), healthy sleep pattern could partly offset the risk of diseases. CONCLUSIONS Our study suggested healthy sleep behaviors could diminish the negative effect from genetic predisposition and lifestyle factors on the risk of MD, highlighting the benefit of healthy sleep pattern.
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Affiliation(s)
- Chuyu Pan
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Jing Ye
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Yan Wen
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Xiaomeng Chu
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Yumeng Jia
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Bolun Cheng
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Shiqiang Cheng
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Li Liu
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Xuena Yang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Chujun Liang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Cuiyan Wu
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Sen Wang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Xi Wang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Yujie Ning
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Feng Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China.
| | - Xiancang Ma
- Department of Psychiatry, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
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Associations between cannabis use, cannabis use disorder, and mood disorders: longitudinal, genetic, and neurocognitive evidence. Psychopharmacology (Berl) 2022; 239:1231-1249. [PMID: 34741634 PMCID: PMC9520129 DOI: 10.1007/s00213-021-06001-8] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Accepted: 10/11/2021] [Indexed: 12/16/2022]
Abstract
RATIONALE Cannabis use among people with mood disorders increased in recent years. While comorbidity between cannabis use, cannabis use disorder (CUD), and mood disorders is high, the underlying mechanisms remain unclear. OBJECTIVES We aimed to evaluate (1) the epidemiological evidence for an association between cannabis use, CUD, and mood disorders; (2) prospective longitudinal, genetic, and neurocognitive evidence of underlying mechanisms; and (3) prognosis and treatment options for individuals with CUD and mood disorders. METHODS Narrative review of existing literature is identified through PubMed searches, reviews, and meta-analyses. Evidence was reviewed separately for depression, bipolar disorder, and suicide. RESULTS Current evidence is limited and mixed but suggestive of a bidirectional relationship between cannabis use, CUD, and the onset of depression. The evidence more consistently points to cannabis use preceding onset of bipolar disorder. Shared neurocognitive mechanisms and underlying genetic and environmental risk factors appear to explain part of the association. However, cannabis use itself may also influence the development of mood disorders, while others may initiate cannabis use to self-medicate symptoms. Comorbid cannabis use and CUD are associated with worse prognosis for depression and bipolar disorder including increased suicidal behaviors. Evidence for targeted treatments is limited. CONCLUSIONS The current evidence base is limited by the lack of well-controlled prospective longitudinal studies and clinical studies including comorbid individuals. Future studies in humans examining the causal pathways and potential mechanisms of the association between cannabis use, CUD, and mood disorder comorbidity are crucial for optimizing harm reduction and treatment strategies.
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Jean FAM, Arsandaux J, Montagni I, Collet O, Fatséas M, Auriacombe M, Ramos-Quiroga JA, Côté SM, Tzourio C, Galéra C. Attention deficit hyperactivity disorder symptoms and cannabis use after one year among students of the i-Share cohort. Eur Psychiatry 2022; 65:1-18. [PMID: 35348052 PMCID: PMC9058443 DOI: 10.1192/j.eurpsy.2022.14] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 02/27/2022] [Accepted: 02/27/2022] [Indexed: 11/25/2022] Open
Abstract
Background Cannabis use in university students is associated with academic achievement failure and health issues. The objective of the study was to evaluate the association between attention deficit hyperactivity disorder (ADHD) symptoms and cannabis use after 1 year among students according to previous cannabis use. Methods Students in France were recruited from February 2013 to July 2020 in the i-Share cohort. 4,270 participants were included (2,135 who never used cannabis at inclusion and 2,135 who did). The Adult ADHD Self-Report Scale (ASRS) was used to assess ADHD symptoms at inclusion. Cannabis use frequency was evaluated 1 year after inclusion. Multinomial regressions were conducted to assess the association between inclusion ADHD symptoms and cannabis use after 1 year. Results Increase in ASRS scores was linked with a greater probability to use cannabis after 1 year and to have a higher cannabis use frequency (once a year—once a month adjusted odds ratio [OR]: 1.24 (1.15–1.34), more than once a month adjusted OR: 1.43 (1.27–1.61)). Among participants who never used cannabis at inclusion, this association disappeared (once a year—once a month adjusted OR: 1.15 (0.95–1.39), more than once a month adjusted OR: 1.16 (0.67–2)) but remained in participants who ever used cannabis at inclusion (once a year—once a month adjusted OR: 1.17 (1.06–1.29), more than once a month adjusted OR: 1.35 (1.18–1.55)). Conclusions High levels of ADHD symptoms in students could lead to continued cannabis use rather than new initiations.
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Affiliation(s)
- François Arnaud Matthieu Jean
- Department of Psychiatry, Dr Jean Eric Techer Hospital, Calais, France
- University of Bordeaux, Faculty of Medicine, Bordeaux, France
- Bordeaux Population Health Research Center, National Institute of Health and Medical Research (Institut National de la Santé et de la Recherche Médicale—INSERM), Bordeaux, France
| | - Julie Arsandaux
- University of Bordeaux, Faculty of Medicine, Bordeaux, France
- Bordeaux Population Health Research Center, National Institute of Health and Medical Research (Institut National de la Santé et de la Recherche Médicale—INSERM), Bordeaux, France
| | - Ilaria Montagni
- University of Bordeaux, Faculty of Medicine, Bordeaux, France
- Bordeaux Population Health Research Center, National Institute of Health and Medical Research (Institut National de la Santé et de la Recherche Médicale—INSERM), Bordeaux, France
| | - Ophélie Collet
- University of Bordeaux, Faculty of Medicine, Bordeaux, France
- Bordeaux Population Health Research Center, National Institute of Health and Medical Research (Institut National de la Santé et de la Recherche Médicale—INSERM), Bordeaux, France
| | - Mélina Fatséas
- University of Bordeaux, Faculty of Medicine, Bordeaux, France
- Charles Perrens Hospital, Bordeaux, France
- Centre Hospitalier Universitaire de Bordeaux (CHU de Bordeaux), Bordeaux, France
- National Center for Scientific Research (Centre national de la recherche scientifique—CNRS), Institut de Neurosciences Cognitives et Intégratives d’Aquitaine (INCIA), Bordeaux, France
| | - Marc Auriacombe
- University of Bordeaux, Faculty of Medicine, Bordeaux, France
- Charles Perrens Hospital, Bordeaux, France
- Centre Hospitalier Universitaire de Bordeaux (CHU de Bordeaux), Bordeaux, France
- National Center for Scientific Research (Centre national de la recherche scientifique—CNRS), Addiction Team/SANPSY, Bordeaux, France
| | - Josep Antoni Ramos-Quiroga
- Group of Psychiatry, Mental Health and Addiction, Vall d’Hebron Research Institute (VHIR), 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
| | - Sylvana M. Côté
- University of Bordeaux, Faculty of Medicine, Bordeaux, France
- Bordeaux Population Health Research Center, National Institute of Health and Medical Research (Institut National de la Santé et de la Recherche Médicale—INSERM), Bordeaux, France
- University of Montreal, Quebec, Canada
| | - Christophe Tzourio
- University of Bordeaux, Faculty of Medicine, Bordeaux, France
- Bordeaux Population Health Research Center, National Institute of Health and Medical Research (Institut National de la Santé et de la Recherche Médicale—INSERM), Bordeaux, France
- Centre Hospitalier Universitaire de Bordeaux (CHU de Bordeaux), Bordeaux, France
| | - Cédric Galéra
- University of Bordeaux, Faculty of Medicine, Bordeaux, France
- Bordeaux Population Health Research Center, National Institute of Health and Medical Research (Institut National de la Santé et de la Recherche Médicale—INSERM), Bordeaux, France
- Charles Perrens Hospital, Bordeaux, France
- Centre Hospitalier Universitaire de Bordeaux (CHU de Bordeaux), Bordeaux, France
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Faure P, Fayad SL, Solié C, Reynolds LM. Social Determinants of Inter-Individual Variability and Vulnerability: The Role of Dopamine. Front Behav Neurosci 2022; 16:836343. [PMID: 35386723 PMCID: PMC8979673 DOI: 10.3389/fnbeh.2022.836343] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 02/14/2022] [Indexed: 11/13/2022] Open
Abstract
Individuals differ in their traits and preferences, which shape their interactions, their prospects for survival and their susceptibility to diseases. These correlations are well documented, yet the neurophysiological mechanisms underlying the emergence of distinct personalities and their relation to vulnerability to diseases are poorly understood. Social ties, in particular, are thought to be major modulators of personality traits and psychiatric vulnerability, yet the majority of neuroscience studies are performed on rodents in socially impoverished conditions. Rodent micro-society paradigms are therefore key experimental paradigms to understand how social life generates diversity by shaping individual traits. Dopamine circuitry is implicated at the interface between social life experiences, the expression of essential traits, and the emergence of pathologies, thus proving a possible mechanism to link these three concepts at a neuromodulatory level. Evaluating inter-individual variability in automated social testing environments shows great promise for improving our understanding of the link between social life, personality, and precision psychiatry – as well as elucidating the underlying neurophysiological mechanisms.
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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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27
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Associations between cognition and polygenic liability to substance involvement in middle childhood: Results from the ABCD study. Drug Alcohol Depend 2022; 232:109277. [PMID: 35033950 PMCID: PMC9331817 DOI: 10.1016/j.drugalcdep.2022.109277] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 11/19/2021] [Accepted: 12/20/2021] [Indexed: 11/22/2022]
Abstract
BACKGROUND Cognition is robustly associated with substance involvement. This relationship is attributable to multiple factors, including genetics, though such contributions show inconsistent patterns in the literature. For instance, genome-wide association studies point to potential positive relationships between educational achievement and common substance use but negative relationships with heavy and/or problematic substance use. METHODS We estimated associations between polygenic risk for substance involvement (i.e., alcohol, tobacco, and cannabis use and problematic use) and cognition subfacets (i.e., general ability, executive function, learning/memory) derived from confirmatory factor analysis among 3205 substance naïve children (ages 9-10) of European ancestry who completed the baseline session of the Adolescent Brain Cognitive Development (ABCD) Study. FINDINGS Polygenic risk for lifetime cannabis use was positively associated with all three facets of cognitive ability (Bs ≥ 0.045, qs ≤ 0.044). No other substance polygenic risk scores showed significant associations with cognition after adjustment for multiple testing (|Bs|≤0.033, qs ≥ 0.118). CONCLUSIONS Polygenic liability to lifetime cannabis use, but not use disorder, was positively associated with cognitive performance among substance-naïve children, possibly reflecting shared genetic overlap with openness to experience or the influence of genetic variance associated with socioeconomic status. Our lack of findings for the other polygenic scores may reflect ascertainment differences between the genome-wide association study (GWAS) samples and the current sample and/or the young age of the present sample. As longitudinal data in ABCD are collected, this sample may be useful for disentangling putatively causal or predispositional influences of substance use and misuse on cognition.
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Mills L, Lintzeris N, O'Malley M, Arnold JC, McGregor IS. Prevalence and correlates of cannabis use disorder among Australians using cannabis products to treat a medical condition. Drug Alcohol Rev 2022; 41:1095-1108. [PMID: 35172040 DOI: 10.1111/dar.13444] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 12/14/2021] [Accepted: 01/21/2022] [Indexed: 12/23/2022]
Abstract
INTRODUCTION Prior research has examined the prevalence and correlates of cannabis use disorder (CUD) in people who use cannabis; however, these are poorly described for people using cannabis for medical reasons. METHODS Data came from a 2018 to 2019 online, anonymous, cross-sectional survey of Australians reporting using either illicit or licit cannabis for medical reasons within the past year. Included were questions on demographics, current and lifetime patterns of cannabis use, clinical conditions for which medical cannabis was used, and individual criteria for CUD and cannabis withdrawal syndrome. Bayesian Horseshoe logistic regression models were used to identify covariates associated with meeting CUD DSM-5 conditions for any-CUD (≥2/11 criteria) and moderate-severe-CUD (≥4/11). RESULTS A total of 905 participants were included in the analysis. The majority (98%) used illicit cannabis products. Criteria for any-CUD criteria were met by 290 (32.0%), and 117 (12.9%) met criteria for moderate-severe-CUD. Tolerance (21%) and withdrawal (35%) were the most commonly met criteria. Correlates with the strongest association with CUD were inhaled route of administration [odds ratio (OR) = 2.96, 95% credible interval 1.11, 7.06], frequency of cannabis use (OR = 1.24, 1.11-1.35), proportion of cannabis for medical reasons (OR = 0.83, 0.74, 0.94), frequency of tobacco use (OR = 1.10, 1.03, 1.17), age (OR = 0.75, 0.64, 0.90) and pain as main clinical indication (OR = 0.58, 0.36, 1.00). DISCUSSION AND CONCLUSIONS Prevalence of CUD in medical cannabis users appears comparable to 'recreational' users, with many similar correlates. CUD was associated with using cannabis to treat mental health rather than pain conditions and inhaled over other routes of administration.
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Affiliation(s)
- Llewellyn Mills
- Drug and Alcohol Services, South East Sydney Local Health District, Sydney, Australia.,Discipline of Addiction Medicine, Faculty of Medicine and Public Health, The University of Sydney, Sydney, Australia.,Drug and Alcohol Clinical Research and Improvement Network, Sydney, Australia.,National Drug and Alcohol Research Centre, UNSW Sydney, Sydney, Australia
| | - Nicholas Lintzeris
- Drug and Alcohol Services, South East Sydney Local Health District, Sydney, Australia.,Discipline of Addiction Medicine, Faculty of Medicine and Public Health, The University of Sydney, Sydney, Australia.,Drug and Alcohol Clinical Research and Improvement Network, Sydney, Australia
| | - Michael O'Malley
- Drug and Alcohol Services, South East Sydney Local Health District, Sydney, Australia.,Discipline of Addiction Medicine, Faculty of Medicine and Public Health, The University of Sydney, Sydney, Australia
| | - Jonathon C Arnold
- Lambert Initiative for Cannabinoid Therapeutics, The University of Sydney, Sydney, Australia.,Discipline of Pharmacology, Sydney Pharmacy School, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.,Brain and Mind Centre, The University of Sydney, Sydney, Australia
| | - Iain S McGregor
- Lambert Initiative for Cannabinoid Therapeutics, The University of Sydney, Sydney, Australia.,Brain and Mind Centre, The University of Sydney, Sydney, Australia.,School of Psychology, Faculty of Science, The University of Sydney, Sydney, Australia
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29
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Merikangas AK, Shelly M, Knighton A, Kotler N, Tanenbaum N, Almasy L. What genes are differentially expressed in individuals with schizophrenia? A systematic review. Mol Psychiatry 2022; 27:1373-1383. [PMID: 35091668 PMCID: PMC9095490 DOI: 10.1038/s41380-021-01420-7] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 11/17/2021] [Accepted: 12/01/2021] [Indexed: 11/15/2022]
Abstract
Schizophrenia is a severe, complex mental disorder characterized by a combination of positive symptoms, negative symptoms, and impaired cognitive function. Schizophrenia is highly heritable (~80%) with multifactorial etiology and complex polygenic genetic architecture. Despite the large number of genetic variants associated with schizophrenia, few causal variants have been established. Gaining insight into the mechanistic influences of these genetic variants may facilitate our ability to apply these findings to prevention and treatment. Though there have been more than 300 studies of gene expression in schizophrenia over the past 15 years, none of the studies have yielded consistent evidence for specific genes that contribute to schizophrenia risk. The aim of this work is to conduct a systematic review and synthesis of case-control studies of genome-wide gene expression in schizophrenia. Comprehensive literature searches were completed in PubMed, EmBase, and Web of Science, and after a systematic review of the studies, data were extracted from those that met the following inclusion criteria: human case-control studies comparing the genome-wide transcriptome of individuals diagnosed with schizophrenia to healthy controls published between January 1, 2000 and June 30, 2020 in the English language. Genes differentially expressed in cases were extracted from these studies, and overlapping genes were compared to previous research findings from the genome-wide association, structural variation, and tissue-expression studies. The transcriptome-wide analysis identified different genes than those previously reported in genome-wide association, exome sequencing, and structural variation studies of schizophrenia. Only one gene, GBP2, was replicated in five studies. Previous work has shown that this gene may play a role in immune function in the etiology of schizophrenia, which in turn could have implications for risk profiling, prevention, and treatment. This review highlights the methodological inconsistencies that impede valid meta-analyses and synthesis across studies. Standardization of the use of covariates, gene nomenclature, and methods for reporting results could enhance our understanding of the potential mechanisms through which genes exert their influence on the etiology of schizophrenia. Although these results are promising, collaborative efforts with harmonization of methodology will facilitate the identification of the role of genes underlying schizophrenia.
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Affiliation(s)
- Alison K. Merikangas
- grid.239552.a0000 0001 0680 8770Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, PA USA ,grid.25879.310000 0004 1936 8972Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA ,grid.25879.310000 0004 1936 8972Lifespan Brain Institute, Children’s Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
| | - Matthew Shelly
- grid.239552.a0000 0001 0680 8770Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, PA USA ,grid.268256.d0000 0000 8510 1943Department of Biology, College of Science and Engineering, Wilkes University, Wilkes-Barre, PA USA
| | - Alexys Knighton
- grid.25879.310000 0004 1936 8972Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
| | - Nicholas Kotler
- grid.25879.310000 0004 1936 8972Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
| | - Nicole Tanenbaum
- grid.25879.310000 0004 1936 8972Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
| | - Laura Almasy
- grid.239552.a0000 0001 0680 8770Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, PA USA ,grid.25879.310000 0004 1936 8972Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA ,grid.25879.310000 0004 1936 8972Lifespan Brain Institute, Children’s Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
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Wills L, Ables JL, Braunscheidel KM, Caligiuri SPB, Elayouby KS, Fillinger C, Ishikawa M, Moen JK, Kenny PJ. Neurobiological Mechanisms of Nicotine Reward and Aversion. Pharmacol Rev 2022; 74:271-310. [PMID: 35017179 PMCID: PMC11060337 DOI: 10.1124/pharmrev.121.000299] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Accepted: 08/24/2021] [Indexed: 12/27/2022] Open
Abstract
Neuronal nicotinic acetylcholine receptors (nAChRs) regulate the rewarding actions of nicotine contained in tobacco that establish and maintain the smoking habit. nAChRs also regulate the aversive properties of nicotine, sensitivity to which decreases tobacco use and protects against tobacco use disorder. These opposing behavioral actions of nicotine reflect nAChR expression in brain reward and aversion circuits. nAChRs containing α4 and β2 subunits are responsible for the high-affinity nicotine binding sites in the brain and are densely expressed by reward-relevant neurons, most notably dopaminergic, GABAergic, and glutamatergic neurons in the ventral tegmental area. High-affinity nAChRs can incorporate additional subunits, including β3, α6, or α5 subunits, with the resulting nAChR subtypes playing discrete and dissociable roles in the stimulatory actions of nicotine on brain dopamine transmission. nAChRs in brain dopamine circuits also participate in aversive reactions to nicotine and the negative affective state experienced during nicotine withdrawal. nAChRs containing α3 and β4 subunits are responsible for the low-affinity nicotine binding sites in the brain and are enriched in brain sites involved in aversion, including the medial habenula, interpeduncular nucleus, and nucleus of the solitary tract, brain sites in which α5 nAChR subunits are also expressed. These aversion-related brain sites regulate nicotine avoidance behaviors, and genetic variation that modifies the function of nAChRs in these sites increases vulnerability to tobacco dependence and smoking-related diseases. Here, we review the molecular, cellular, and circuit-level mechanisms through which nicotine elicits reward and aversion and the adaptations in these processes that drive the development of nicotine dependence. SIGNIFICANCE STATEMENT: Tobacco use disorder in the form of habitual cigarette smoking or regular use of other tobacco-related products is a major cause of death and disease worldwide. This article reviews the actions of nicotine in the brain that contribute to tobacco use disorder.
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Affiliation(s)
- Lauren Wills
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, New York
| | - Jessica L Ables
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, New York
| | - Kevin M Braunscheidel
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, New York
| | - Stephanie P B Caligiuri
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, New York
| | - Karim S Elayouby
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, New York
| | - Clementine Fillinger
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, New York
| | - Masago Ishikawa
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, New York
| | - Janna K Moen
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, New York
| | - Paul J Kenny
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, New York
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Fischer B, Robinson T, Bullen C, Curran V, Jutras-Aswad D, Medina-Mora ME, Pacula RL, Rehm J, Room R, van den Brink W, Hall W. Lower-Risk Cannabis Use Guidelines (LRCUG) for reducing health harms from non-medical cannabis use: A comprehensive evidence and recommendations update. THE INTERNATIONAL JOURNAL OF DRUG POLICY 2022; 99:103381. [PMID: 34465496 DOI: 10.1016/j.drugpo.2021.103381] [Citation(s) in RCA: 55] [Impact Index Per Article: 27.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 07/05/2021] [Accepted: 07/07/2021] [Indexed: 02/08/2023]
Abstract
BACKGROUND Cannabis use is common, especially among young people, and is associated with risks for various health harms. Some jurisdictions have recently moved to legalization/regulation pursuing public health goals. Evidence-based 'Lower Risk Cannabis Use Guidelines' (LRCUG) and recommendations were previously developed to reduce modifiable risk factors of cannabis-related adverse health outcomes; related evidence has evolved substantially since. We aimed to review new scientific evidence and to develop comprehensively up-to-date LRCUG, including their recommendations, on this evidence basis. METHODS Targeted searches for literature (since 2016) on main risk factors for cannabis-related adverse health outcomes modifiable by the user-individual were conducted. Topical areas were informed by previous LRCUG content and expanded upon current evidence. Searches preferentially focused on systematic reviews, supplemented by key individual studies. The review results were evidence-graded, topically organized and narratively summarized; recommendations were developed through an iterative scientific expert consensus development process. RESULTS A substantial body of modifiable risk factors for cannabis use-related health harms were identified with varying evidence quality. Twelve substantive recommendation clusters and three precautionary statements were developed. In general, current evidence suggests that individuals can substantially reduce their risk for adverse health outcomes if they delay the onset of cannabis use until after adolescence, avoid the use of high-potency (THC) cannabis products and high-frequency/-intensity of use, and refrain from smoking-routes for administration. While young people are particularly vulnerable to cannabis-related harms, other sub-groups (e.g., pregnant women, drivers, older adults, those with co-morbidities) are advised to exercise particular caution with use-related risks. Legal/regulated cannabis products should be used where possible. CONCLUSIONS Cannabis use can result in adverse health outcomes, mostly among sub-groups with higher-risk use. Reducing the risk factors identified can help to reduce health harms from use. The LRCUG offer one targeted intervention component within a comprehensive public health approach for cannabis use. They require effective audience-tailoring and dissemination, regular updating as new evidence become available, and should be evaluated for their impact.
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Affiliation(s)
- Benedikt Fischer
- Schools of Population Health and Pharmacy, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand; Centre for Applied Research in Mental Health and Addiction, Faculty of Health Sciences, Simon Fraser University, Vancouver, Canada; Department of Psychiatry, Federal University of Sao Paulo, Sao Paulo, Brazil.
| | - Tessa Robinson
- Centre for Applied Research in Mental Health and Addiction, Faculty of Health Sciences, Simon Fraser University, Vancouver, Canada; Department of Health Research Methods, Evidence & Impact, Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada
| | - Chris Bullen
- Schools of Population Health and Pharmacy, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand; National Institute for Health Innovation (NIHI), The University of Auckland, Auckland, New Zealand
| | - Valerie Curran
- Clinical Psychopharmacology Unit, Research Department of Clinical, Educational and Health Psychology, University College London, London, United Kingdom; NIHR University College London Hospitals Biomedical Research Centre, London, United Kingdom
| | - Didier Jutras-Aswad
- Department of Psychiatry and Addictology, Université de Montréal, Montreal, Canada; Research Centre of the Centre Hospitalier de l'Université de Montréal (CRCHUM), Montreal, Canada
| | - Maria Elena Medina-Mora
- Center for Global Mental Health Research, National Institute of Psychiatry Ramón de la Fuente Muñiz, Mexico City, Mexico; Department of Psychiatry and Mental Health, Faculty of Medicine, National Autonomous University of Mexico, Mexico City, Mexico
| | - Rosalie Liccardo Pacula
- Schaeffer Center for Health Policy and Economics, Sol Price School of Public Policy, University of Southern California, Los Angeles, United States
| | - Jürgen Rehm
- Institute for Mental Health Policy Research, Centre for Addiction & Mental Health, Toronto, Canada; Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | - Robin Room
- Centre for Alcohol Policy Research, La Trobe University, Melbourne, Australia; Centre for Social Research on Alcohol and Drugs, Department of Public Health Sciences, Stockholm University, Stockholm, Sweden
| | - Wim van den Brink
- Department of Psychiatry, University of Amsterdam, Amsterdam, the Netherlands; Amsterdam University Medical Centre, University of Amsterdam, Amsterdam, the Netherlands
| | - Wayne Hall
- National Centre for Youth Substance Use Research, Faculty of Health and Behavioural Sciences, University of Queensland, St Lucia, QLD 4072, Australia; National Addiction Centre, Institute of Psychiatry, Kings College London, United Kingdom
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Maxwell JM, Coleman JRI, Breen G, Vassos E. Association Between Genetic Risk for Psychiatric Disorders and the Probability of Living in Urban Settings. JAMA Psychiatry 2021; 78:1355-1364. [PMID: 34705035 PMCID: PMC8552117 DOI: 10.1001/jamapsychiatry.2021.2983] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
IMPORTANCE Urban residence has been highlighted as an environmental risk factor for schizophrenia and, to a lesser extent, several other psychiatric disorders. However, few studies have explored genetic effects on the choice of residence. OBJECTIVE To investigate whether individuals with genetic predisposition to a range of psychiatric disorders have an increased likelihood to live in urban areas. DESIGN, SETTING, AND PARTICIPANTS A cross-sectional retrospective cohort study including genotypes, address history, and geographic distribution of population density in the UK based on census data from 1931-2011 was conducted. Polygenic risk score (PRS) analyses, genome-wide association studies, genetic correlation, and 2-sample mendelian randomization analyses were applied to 385 793 UK Biobank participants with self-reported or general practitioner registration-based address history. The study was conducted from February 2018 to May 2021, and data analysis was performed from April 2018 to May 2021. MAIN OUTCOMES AND MEASURES Population density of residence at different ages and movement during the life span between urban and rural environments. RESULTS In this cohort study of 385 793 unrelated UK Biobank participants (207 963 [54%] were women; age, 37-73 years; mean [SD], 56.7 [8] years), PRS analyses showed significant associations with higher population density across adult life (age 25 to >65 years) reaching highest significance at the 45- to 55-year age group for schizophrenia (88 people/km2; 95% CI, 65-98 people/km2), bipolar disorder (44 people/km2; 95% CI, 34-54 people/km2), anorexia nervosa (36 people/km2; 95% CI, 22-50 people/km2), and autism spectrum disorder (35 people/km2; 95% CI, 25-45 people/km2). The schizophrenia PRS was also significantly associated with higher birthplace population density (37 people/km2; 95% CI, 19-55 people/km2; P = 8 × 10-5). Attention-deficit/hyperactivity disorder PRS was significantly associated with reduced population density in adult life (-31 people/km2; 95% CI, -42 to -20 people/km2 at age 35-45 years). Individuals with higher PRS for schizophrenia, bipolar disorder, anorexia nervosa, and autism spectrum disorder and lower PRS for attention-deficit/hyperactivity disorder preferentially moved from rural environments to cities (difference in PRS with Tukey pairwise comparisons for schizophrenia: 0.05; 95% CI, 0.03 to 0.60; bipolar disorder: 0.10; 95% CI, 0.08 to 0.13; anorexia nervosa: 0.05; 95% CI, 0.03 to 0.07; autism spectrum disorder: 0.04; 95% CI 0.03 to 0.06; and attention-deficit/hyperactivity disorder: -0.09, 95% CI, -0.12 to -0.06). Genetic correlation results were largely consistent with PRS analyses, whereas mendelian randomization provided support for associations between schizophrenia and bipolar disorder and living in high population-density areas. CONCLUSIONS AND RELEVANCE These findings suggest that a high genetic risk for a variety of psychiatric disorders may affect an individual's choice of residence. This result supports the hypothesis of genetic selection of an individual's environment, which intersects the traditional gene-environment dichotomy.
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Affiliation(s)
- Jessye M. Maxwell
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom,National Institute for Health Research Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, London, United Kingdom
| | - Jonathan R. I. Coleman
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom,National Institute for Health Research Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, London, United Kingdom
| | - Gerome Breen
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom,National Institute for Health Research Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, London, United Kingdom
| | - Evangelos Vassos
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom,National Institute for Health Research Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, London, United Kingdom
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Genomic and Personalized Medicine Approaches for Substance Use Disorders (SUDs) Looking at Genome-Wide Association Studies. Biomedicines 2021; 9:biomedicines9121799. [PMID: 34944615 PMCID: PMC8698472 DOI: 10.3390/biomedicines9121799] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Revised: 11/23/2021] [Accepted: 11/25/2021] [Indexed: 12/19/2022] Open
Abstract
Drug addiction, or substance use disorder (SUD), is a chronic, relapsing disorder in which compulsive drug-seeking and drug-taking behaviour persist despite serious negative consequences. Drug abuse represents a problem that deserves great attention from a social point of view, and focuses on the importance of genetic studies to help in understanding the genetic basis of addiction and its medical treatment. Despite the complexity of drug addiction disorders, and the high number of environmental variables playing a role in the onset, recurrence, and duration of the symptoms, several studies have highlighted the non-negligible role of genetics, as demonstrated by heritability and genome-wide association studies. A correlation between the relative risk of addiction to specific substances and heritability has been recently observed, suggesting that neurobiological mechanisms may be, at least in part, inherited. All these observations point towards a scenario where the core neurobiological factors of addiction, involving the reward system, impulsivity, compulsivity, stress, and anxiety response, are transmitted, and therefore, genes and mutations underlying their variation might be detected. In the last few years, the development of new and more efficient sequencing technologies has paved the way for large-scale studies in searching for genetic and epigenetic factors affecting drug addiction disorders and their treatments. These studies have been crucial to pinpoint single nucleotide polymorphisms (SNPs) in genes that affect the reaction to medical treatments. This is critically important to identify pharmacogenomic approaches for substance use disorder, such as OPRM1 SNPs and methadone required doses for maintenance treatment (MMT). Nevertheless, despite the promising results obtained by genome-wide association and pharmacogenomic studies, specific studies related to population genetics diversity are lacking, undermining the overall applicability of the preliminary findings, and thus potentially affecting the portability and the accuracy of the genetic studies. In this review, focusing on cannabis, cocaine and heroin use, we report the state-of-the-art genomics and pharmacogenomics of SUDs, and the possible future perspectives related to medical treatment response in people that ask for assistance in solving drug-related problems.
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Baumeister S, Nolde M, Alayash Z, Leitzmann M, Baurecht H, Meisinger C. Cannabis use does not impact on type 2 diabetes: A two-sample Mendelian randomization study. Addict Biol 2021; 26:e13020. [PMID: 33580533 DOI: 10.1111/adb.13020] [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: 10/07/2020] [Revised: 01/18/2021] [Accepted: 01/20/2021] [Indexed: 12/17/2022]
Abstract
Cannabis has effects on the insulin/glucose metabolism. As the use of cannabis and the prevalence of type 2 diabetes increase worldwide, it is important to examine the effect of cannabis on the risk of diabetes. We conducted a Mendelian randomization (MR) study by using 19 single-nucleotide polymorphisms (SNPs) as instrumental variables for lifetime cannabis use and 14 SNPs to instrument cannabis use disorder and linking these to type 2 diabetes risk using genome-wide association study data (lifetime cannabis use [N = 184,765]; cannabis use disorder [2387 cases/48,985 controls], type 2 diabetes [74,124 cases/824,006 controls]). The MR analysis suggested no effect of lifetime cannabis use (inverse-variance weighted odds ratio [95% confidence interval] = 1.00 [0.93-1.09], P value = 0.935) and cannabis use disorder (OR = 1.03 [0.99-1.08]) on type 2 diabetes. Sensitivity analysis to assess potential pleiotropy led to no substantive change in the estimates. This study adds to the evidence base that cannabis use does not play a causal role in type 2 diabetes.
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Affiliation(s)
- Sebastian‐Edgar Baumeister
- Chair of Epidemiology LMU München, UNIKA‐T Augsburg Augsburg Germany
- Independent Research Group Clinical Epidemiology Helmholtz Zentrum München, German Research Center for Environmental Health Munich Germany
- Institute of Health Services Research in Dentistry University of Münster Münster Germany
| | - Michael Nolde
- Chair of Epidemiology LMU München, UNIKA‐T Augsburg Augsburg Germany
- Independent Research Group Clinical Epidemiology Helmholtz Zentrum München, German Research Center for Environmental Health Munich Germany
| | - Zoheir Alayash
- Chair of Epidemiology LMU München, UNIKA‐T Augsburg Augsburg Germany
| | - Michael Leitzmann
- Department of Epidemiology and Preventive Medicine University of Regensburg Regensburg Germany
| | - Hansjörg Baurecht
- Department of Epidemiology and Preventive Medicine University of Regensburg Regensburg Germany
| | - Christa Meisinger
- Chair of Epidemiology LMU München, UNIKA‐T Augsburg Augsburg Germany
- Independent Research Group Clinical Epidemiology Helmholtz Zentrum München, German Research Center for Environmental Health Munich Germany
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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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O'Connell KS, Coombes BJ. Genetic contributions to bipolar disorder: current status and future directions. Psychol Med 2021; 51:2156-2167. [PMID: 33879273 PMCID: PMC8477227 DOI: 10.1017/s0033291721001252] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Revised: 03/12/2021] [Accepted: 03/19/2021] [Indexed: 12/12/2022]
Abstract
Bipolar disorder (BD) is a highly heritable mental disorder and is estimated to affect about 50 million people worldwide. Our understanding of the genetic etiology of BD has greatly increased in recent years with advances in technology and methodology as well as the adoption of international consortiums and large population-based biobanks. It is clear that BD is also highly heterogeneous and polygenic and shows substantial genetic overlap with other psychiatric disorders. Genetic studies of BD suggest that the number of associated loci is expected to substantially increase in larger future studies and with it, improved genetic prediction of the disorder. Still, a number of challenges remain to fully characterize the genetic architecture of BD. First among these is the need to incorporate ancestrally-diverse samples to move research away from a Eurocentric bias that has the potential to exacerbate health disparities already seen in BD. Furthermore, incorporation of population biobanks, registry data, and electronic health records will be required to increase the sample size necessary for continued genetic discovery, while increased deep phenotyping is necessary to elucidate subtypes within BD. Lastly, the role of rare variation in BD remains to be determined. Meeting these challenges will enable improved identification of causal variants for the disorder and also allow for equitable future clinical applications of both genetic risk prediction and therapeutic interventions.
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Affiliation(s)
- Kevin S. O'Connell
- Division of Mental Health and Addiction, NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo University Hospital, 0407Oslo, Norway
| | - Brandon J. Coombes
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
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Abstract
Substance use disorders (SUDs) are prevalent and result in an array of negative consequences. They are influenced by genetic factors (h2 = ~50%). Recent years have brought substantial progress in our understanding of the genetic etiology of SUDs and related traits. The present review covers the current state of the field for SUD genetics, including the epidemiology and genetic epidemiology of SUDs, findings from the first-generation of SUD genome-wide association studies (GWAS), cautions about translating GWAS findings to clinical settings, and suggested prioritizations for the next wave of SUD genetics efforts. Recent advances in SUD genetics have been facilitated by the assembly of large GWAS samples, and the development of state-of-the-art methods modeling the aggregate effect of genome-wide variation. These advances have confirmed that SUDs are highly polygenic with many variants across the genome conferring risk, the vast majority of which are of small effect. Downstream analyses have enabled finer resolution of the genetic architecture of SUDs and revealed insights into their genetic relationship with other psychiatric disorders. Recent efforts have also prioritized a closer examination of GWAS findings that have suggested non-uniform genetic influences across measures of substance use (e.g. consumption) and problematic use (e.g. SUD). Additional highlights from recent SUD GWAS include the robust confirmation of loci in alcohol metabolizing genes (e.g. ADH1B and ALDH2) affecting alcohol-related traits, and loci within the CHRNA5-CHRNA3-CHRNB4 gene cluster influencing nicotine-related traits. Similar successes are expected for cannabis, opioid, and cocaine use disorders as sample sizes approach those assembled for alcohol and nicotine.
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Affiliation(s)
- Joseph D. Deak
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Emma C. Johnson
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
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Russell JT, Zhou Y, Weinstock GM, Bubier JA. The Gut Microbiome and Substance Use Disorder. Front Neurosci 2021; 15:725500. [PMID: 34531718 PMCID: PMC8439419 DOI: 10.3389/fnins.2021.725500] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Accepted: 08/12/2021] [Indexed: 01/15/2023] Open
Abstract
Substance use disorders (SUDs) remain a significant public health challenge, affecting tens of millions of individuals worldwide each year. Often comorbid with other psychiatric disorders, SUD can be poly-drug and involve several different substances including cocaine, opiates, nicotine, and alcohol. SUD has a strong genetic component. Much of SUD research has focused on the neurologic and genetic facets of consumption behavior. There is now interest in the role of the gut microbiome in the pathogenesis of SUD. In this review, we summarize current animal and clinical evidence that the gut microbiome is involved in SUD, then address the underlying mechanisms by which the gut microbiome interacts with SUD through metabolomic, immune, neurological, and epigenetic mechanisms. Lastly, we discuss methods using various inbred and outbred mice models to gain an integrative understanding of the microbiome and host genetic controls in SUD.
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Affiliation(s)
- Jordan T Russell
- School of Medicine, University of Connecticut Health Center, Farmington, CT, United States
| | - Yanjiao Zhou
- School of Medicine, University of Connecticut Health Center, Farmington, CT, United States
| | - George M Weinstock
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, United States
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Agnew-Blais JC, Belsky DW, Caspi A, Danese A, Moffitt TE, Polanczyk GV, Sugden K, Wertz J, Williams BS, Lewis CM, Arseneault L. Polygenic Risk and the Course of Attention-Deficit/Hyperactivity Disorder From Childhood to Young Adulthood: Findings From a Nationally Representative Cohort. J Am Acad Child Adolesc Psychiatry 2021; 60:1147-1156. [PMID: 33440202 PMCID: PMC8417462 DOI: 10.1016/j.jaac.2020.12.033] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Revised: 10/01/2020] [Accepted: 12/31/2020] [Indexed: 11/25/2022]
Abstract
OBJECTIVE To understand whether genetic risk for attention-deficit/hyperactivity disorder (ADHD) is associated with the course of the disorder across childhood and into young adulthood. METHOD Participants were from the Environmental Risk (E-Risk) Longitudinal Twin Study, a population-based birth cohort of 2,232 twins. ADHD was assessed at ages 5, 7, 10, and 12 with mother- and teacher-reports and at age 18 with self-report. Polygenic risk scores (PRSs) were created using a genome-wide association study of ADHD case status. Associations with PRS were examined at multiple points in childhood and longitudinally from early childhood to adolescence. We investigated ADHD PRS and course to young adulthood, as reflected by ADHD remission, persistence, and late onset. RESULTS Participants with higher ADHD PRSs had increased risk for meeting ADHD diagnostic criteria (odds ratios ranging from 1.17 at age 10 to 1.54 at age 12) and for elevated symptoms at ages 5, 7, 10, and 12. Higher PRS was longitudinally associated with more hyperactivity/impulsivity (incidence rate ratio = 1.18) and inattention (incidence rate ratio = 1.14) from age 5 to age 12. In young adulthood, participants with persistent ADHD exhibited the highest PRS (mean PRS = 0.37), followed by participants with remission (mean PRS = 0.21); both groups had higher PRS than controls (mean PRS = -0.03), but did not significantly differ from one another. Participants with late-onset ADHD did not show elevated PRS for ADHD, depression, alcohol dependence, or marijuana use disorder. CONCLUSION Genetic risk scores derived from case-control genome-wide association studies may have relevance not only for incidence of mental health disorders, but also for understanding the longitudinal course of mental health disorders.
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Affiliation(s)
| | | | - Avshalom Caspi
- King’s College London, United Kingdom,Duke University, Durham, North Carolina
| | - Andrea Danese
- King’s College London, United Kingdom,South London and Maudsley NHS Foundation Trust, London, United Kingdom
| | - Terrie E. Moffitt
- King’s College London, United Kingdom,Duke University, Durham, North Carolina
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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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Krueger RF, Hobbs KA, Conway CC, Dick DM, Dretsch MN, Eaton NR, Forbes MK, Forbush KT, Keyes KM, Latzman RD, Michelini G, Patrick CJ, Sellbom M, Slade T, South S, Sunderland M, Tackett J, Waldman I, Waszczuk MA, Wright AG, Zald DH, Watson D, Kotov R. Validity and utility of Hierarchical Taxonomy of Psychopathology (HiTOP): II. Externalizing superspectrum. World Psychiatry 2021; 20:171-193. [PMID: 34002506 PMCID: PMC8129870 DOI: 10.1002/wps.20844] [Citation(s) in RCA: 85] [Impact Index Per Article: 28.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
The Hierarchical Taxonomy of Psychopathology (HiTOP) is an empirical effort to address limitations of traditional mental disorder diagnoses. These include arbitrary boundaries between disorder and normality, disorder co-occurrence in the modal case, heterogeneity of presentation within dis-orders, and instability of diagnosis within patients. This paper reviews the evidence on the validity and utility of the disinhibited externalizing and antagonistic externalizing spectra of HiTOP, which together constitute a broad externalizing superspectrum. These spectra are composed of elements subsumed within a variety of mental disorders described in recent DSM nosologies, including most notably substance use disorders and "Cluster B" personality disorders. The externalizing superspectrum ranges from normative levels of impulse control and self-assertion, to maladaptive disinhibition and antagonism, to extensive polysubstance involvement and personality psychopathology. A rich literature supports the validity of the externalizing superspectrum, and the disinhibited and antagonistic spectra. This evidence encompasses common genetic influences, environmental risk factors, childhood antecedents, cognitive abnormalities, neural alterations, and treatment response. The structure of these validators mirrors the structure of the phenotypic externalizing superspectrum, with some correlates more specific to disinhibited or antagonistic spectra, and others relevant to the entire externalizing superspectrum, underlining the hierarchical structure of the domain. Compared with traditional diagnostic categories, the externalizing superspectrum conceptualization shows improved utility, reliability, explanatory capacity, and clinical applicability. The externalizing superspectrum is one aspect of the general approach to psychopathology offered by HiTOP and can make diagnostic classification more useful in both research and the clinic.
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Affiliation(s)
| | - Kelsey A. Hobbs
- Department of PsychologyUniversity of MinnesotaMinneapolisMNUSA
| | | | - Danielle M. Dick
- Department of PsychologyVirginia Commonwealth UniversityRichmondVAUSA
| | - Michael N. Dretsch
- US Army Medical Research Directorate ‐ WestWalter Reed Army Institute of Research, Joint Base Lewis‐McChordWAUSA
| | | | - Miriam K. Forbes
- Centre for Emotional Health, Department of PsychologyMacquarie UniversitySydneyNSWAustralia
| | | | | | | | - Giorgia Michelini
- Semel Institute for Neuroscience and Human BehaviorUniversity of California Los AngelesLos AngelesCAUSA
| | | | - Martin Sellbom
- Department of PsychologyUniversity of OtagoDunedinNew Zealand
| | - Tim Slade
- Matilda Centre for Research in Mental Health and Substance UseUniversity of SydneySydneyNSWAustralia
| | - Susan C. South
- Department of Psychological SciencesPurdue UniversityWest LafayetteINUSA
| | - Matthew Sunderland
- Matilda Centre for Research in Mental Health and Substance UseUniversity of SydneySydneyNSWAustralia
| | | | - Irwin Waldman
- Department of PsychologyEmory UniversityAtlantaGAUSA
| | | | | | - David H. Zald
- Department of PsychologyVanderbilt UniversityNashvilleTNUSA
| | - David Watson
- Department of PsychologyUniversity of Notre DameNotre DameINUSA
| | - Roman Kotov
- Department of PsychiatryStony Brook UniversityStony BrookNYUSA
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Iob E, Schoeler T, Cecil CM, Walton E, McQuillin A, Pingault J. Identifying risk factors involved in the common versus specific liabilities to substance use: A genetically informed approach. Addict Biol 2021; 26:e12944. [PMID: 32705754 PMCID: PMC8427469 DOI: 10.1111/adb.12944] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Revised: 06/09/2020] [Accepted: 07/08/2020] [Indexed: 12/15/2022]
Abstract
Individuals most often use several rather than one substance among alcohol, cigarettes or cannabis. This widespread co-occurring use of multiple substances is thought to stem from a common liability that is partly genetic in origin. Genetic risk may indirectly contribute to a common liability to substance use through genetically influenced mental health vulnerabilities and individual traits. To test this possibility, we used polygenic scores indexing mental health and individual traits and examined their association with the common versus specific liabilities to substance use. We used data from the Avon Longitudinal Study of Parents and Children (N = 4218) and applied trait-state-occasion models to delineate the common and substance-specific factors based on four classes of substances (alcohol, cigarettes, cannabis and other illicit substances) assessed over time (ages 17, 20 and 22). We generated 18 polygenic scores indexing genetically influenced mental health vulnerabilities and individual traits. In multivariable regression, we then tested the independent contribution of selected polygenic scores to the common and substance-specific factors. Our results implicated several genetically influenced traits and vulnerabilities in the common liability to substance use, most notably risk taking (bstandardised = 0.14; 95% confidence interval [CI] [0.10, 0.17]), followed by extraversion (bstandardised = -0.10; 95% CI [-0.13, -0.06]), and schizophrenia risk (bstandardised = 0.06; 95% CI [0.02, 0.09]). Educational attainment (EA) and body mass index (BMI) had opposite effects on substance-specific liabilities such as cigarette use (bstandardised-EA = -0.15; 95% CI [-0.19, -0.12]; bstandardised-BMI = 0.05; 95% CI [0.02, 0.09]) and alcohol use (bstandardised-EA = 0.07; 95% CI [0.03, 0.11]; bstandardised-BMI = -0.06; 95% CI [-0.10, -0.02]). These findings point towards largely distinct sets of genetic influences on the common versus specific liabilities.
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Affiliation(s)
- Eleonora Iob
- Department of Behavioral Science and HealthUniversity College LondonLondonUK
| | - Tabea Schoeler
- Department of Clinical, Educational and Health Psychology, Division of Psychology and Language SciencesUniversity College LondonLondonUK
| | - Charlotte M. Cecil
- Department of Child and Adolescent PsychiatryErasmus University Medical CenterRotterdamThe Netherlands
- Department of EpidemiologyErasmus University Medical CenterRotterdamThe Netherlands
| | - Esther Walton
- MRC Integrative Epidemiology Unit, Bristol Medical School, Population Health SciencesUniversity of BristolBristolUK
- Department of PsychologyUniversity of BathBathUK
| | | | - Jean‐Baptiste Pingault
- Department of Clinical, Educational and Health Psychology, Division of Psychology and Language SciencesUniversity College LondonLondonUK
- Social, Genetic and Developmental Psychiatry CentreKing's College LondonLondonUK
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44
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Russell AE, Hemani G, Jones HJ, Ford T, Gunnell D, Heron J, Joinson C, Moran P, Relton C, Suderman M, Watkins S, Mars B. An exploration of the genetic epidemiology of non-suicidal self-harm and suicide attempt. BMC Psychiatry 2021; 21:207. [PMID: 33892675 PMCID: PMC8066869 DOI: 10.1186/s12888-021-03216-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Accepted: 04/14/2021] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Empirical evidence supporting the distinction between suicide attempt (SA) and non-suicidal self-harm (NSSH) is lacking. Although NSSH is a risk factor for SA, we do not currently know whether these behaviours lie on a continuum of severity, or whether they are discrete outcomes with different aetiologies. We conducted this exploratory genetic epidemiology study to investigate this issue further. METHODS We explored the extent of genetic overlap between NSSH and SA in a large, richly-phenotyped cohort (the Avon Longitudinal Study of Parents and Children; N = 4959), utilising individual-level genetic and phenotypic data to conduct analyses of genome-wide complex traits and polygenic risk scores (PRS). RESULTS The single nucleotide polymorphism heritability of NSSH was estimated to be 13% (SE 0.07) and that of SA to be 0% (SE 0.07). Of the traits investigated, NSSH was most strongly correlated with higher IQ (rG = 0.31, SE = 0.22), there was little evidence of high genetic correlation between NSSH and SA (rG = - 0.1, SE = 0.54), likely due to the low heritability estimate for SA. The PRS for depression differentiated between those with NSSH and SA in multinomial regression. The optimal PRS prediction model for SA (Nagelkerke R2 0.022, p < 0.001) included ADHD, depression, income, anorexia and neuroticism and explained more variance than the optimal prediction model for NSSH (Nagelkerke R2 0.010, p < 0.001) which included ADHD, alcohol consumption, autism spectrum conditions, depression, IQ, neuroticism and suicide attempt. CONCLUSIONS Our findings suggest that SA does not have a large genetic component, and that although NSSH and SA are not discrete outcomes there appears to be little genetic overlap between the two. The relatively small sample size and resulting low heritability estimate for SA was a limitation of the study. Combined with low heritability estimates, this implies that family or population structures in SA GWASs may contribute to signals detected.
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Affiliation(s)
- Abigail Emma Russell
- Children and Young People's Mental Health Research Collaboration (ChYMe), University of Exeter College of Medicine and Health, Exeter, UK.
| | - Gibran Hemani
- MRC Integrative Epidemiology Unit, University of Bristol Medical School, Bristol, UK
- Population Health Sciences, University of Bristol Medical School, Bristol, UK
| | - Hannah J Jones
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol Medical School, Bristol, UK
| | - Tamsin Ford
- University of Cambridge Department of Psychiatry, Cambridge, UK
| | - David Gunnell
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol Medical School, Bristol, UK
- NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, UK
| | - Jon Heron
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol Medical School, Bristol, UK
| | - Carol Joinson
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol Medical School, Bristol, UK
| | - Paul Moran
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol Medical School, Bristol, UK
- NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, UK
| | - Caroline Relton
- MRC Integrative Epidemiology Unit, University of Bristol Medical School, Bristol, UK
- Population Health Sciences, University of Bristol Medical School, Bristol, UK
| | - Matthew Suderman
- MRC Integrative Epidemiology Unit, University of Bristol Medical School, Bristol, UK
- Population Health Sciences, University of Bristol Medical School, Bristol, UK
| | - Sarah Watkins
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol Medical School, Bristol, UK
| | - Becky Mars
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol Medical School, Bristol, UK
- NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, UK
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45
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Gerring ZF, Vargas AM, Gamazon ER, Derks EM. An integrative systems-based analysis of substance use: eQTL-informed gene-based tests, gene networks, and biological mechanisms. Am J Med Genet B Neuropsychiatr Genet 2021; 186:162-172. [PMID: 33369091 PMCID: PMC8137546 DOI: 10.1002/ajmg.b.32829] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Revised: 11/17/2020] [Accepted: 11/27/2020] [Indexed: 01/03/2023]
Abstract
Genome-wide association studies have identified multiple genetic risk factors underlying susceptibility to substance use, however, the functional genes and biological mechanisms remain poorly understood. The discovery and characterization of risk genes can be facilitated by the integration of genome-wide association data and gene expression data across biologically relevant tissues and/or cell types to identify genes whose expression is altered by DNA sequence variation (expression quantitative trait loci; eQTLs). The integration of gene expression data can be extended to the study of genetic co-expression, under the biologically valid assumption that genes form co-expression networks to influence the manifestation of a disease or trait. Here, we integrate genome-wide association data with gene expression data from 13 brain tissues to identify candidate risk genes for 8 substance use phenotypes. We then test for the enrichment of candidate risk genes within tissue-specific gene co-expression networks to identify modules (or groups) of functionally related genes whose dysregulation is associated with variation in substance use. We identified eight gene modules in brain that were enriched with gene-based association signals for substance use phenotypes. For example, a single module of 40 co-expressed genes was enriched with gene-based associations for drinks per week and biological pathways involved in GABA synthesis, release, reuptake and degradation. Our study demonstrates the utility of eQTL and gene co-expression analysis to uncover novel biological mechanisms for substance use traits.
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Affiliation(s)
- Zachary F Gerring
- Translational Neurogenomics Laboratory; QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Angela Mina Vargas
- Translational Neurogenomics Laboratory; QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Eric R Gamazon
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA,Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA,Clare Hall, University of Cambridge, Cambridge, United Kingdom
| | - Eske M Derks
- Translational Neurogenomics Laboratory; QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
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46
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Maldonado R, Calvé P, García-Blanco A, Domingo-Rodriguez L, Senabre E, Martín-García E. Genomics and epigenomics of addiction. Am J Med Genet B Neuropsychiatr Genet 2021; 186:128-139. [PMID: 33819378 DOI: 10.1002/ajmg.b.32843] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Revised: 03/04/2021] [Accepted: 03/24/2021] [Indexed: 12/15/2022]
Abstract
Recent progress in the genomics and epigenomics of addiction has contributed to improving our understanding of this complex mental disorder's etiology, filling the gap between genes, environment, and behavior. We review the behavioral genetic studies reporting gene and environment interactions that explain the polygenetic contribution to the resilience and vulnerability to develop addiction. We discuss the evidence of polymorphic candidate genes that confer susceptibility to develop addiction as well as the studies of specific epigenetic marks that contribute to vulnerability and resilience to addictive-like behavior. A particular emphasis has been devoted to the miRNA changes that are considered potential biomarkers. The increasing knowledge about the technology required to alter miRNA expression may provide promising novel therapeutic tools. Finally, we give future directions for the field's progress in disentangling the connection between genes, environment, and behavior.
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Affiliation(s)
- Rafael Maldonado
- Laboratory of Neuropharmacology-Neurophar, Department of Experimental and Health Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain.,Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
| | - Pablo Calvé
- Laboratory of Neuropharmacology-Neurophar, Department of Experimental and Health Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Alejandra García-Blanco
- Laboratory of Neuropharmacology-Neurophar, Department of Experimental and Health Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Laura Domingo-Rodriguez
- Laboratory of Neuropharmacology-Neurophar, Department of Experimental and Health Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Eric Senabre
- Laboratory of Neuropharmacology-Neurophar, Department of Experimental and Health Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Elena Martín-García
- Laboratory of Neuropharmacology-Neurophar, Department of Experimental and Health Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain
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47
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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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48
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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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49
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Colocalization of association signals at nicotinic acetylcholine receptor genes between schizophrenia and smoking traits. Drug Alcohol Depend 2021; 220:108517. [PMID: 33454625 DOI: 10.1016/j.drugalcdep.2021.108517] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Revised: 12/16/2020] [Accepted: 12/17/2020] [Indexed: 11/20/2022]
Abstract
BACKGROUND Epidemiological data suggest that smoking may be a risk factor for schizophrenia (SCZ), but more evidence is needed. Two regions coding nicotinic acetylcholine receptor (nAchR) subunits, atCHRNA2 and the CHRNA5/A3/B4 cluster, were associated with SCZ in genome-wide association studies (GWAS). Additionally, a signal at CHRNA4 is near significance. CHRNA2 was also associated with cannabis use disorder (CUD). These regions were also associated with smoking behaviors. If tobacco is a risk factor, the GWAS signals at smoking behaviors and SCZ have to be due to the same causal variants, i.e. they have to colocalize, although colocalization does not necessarily imply causality. Here, we present colocalization analysis at these loci between SCZ and smoking behaviors. METHODS The Bayesian approach implemented in coloc was used to check for posterior probability of colocalization versus independent signals at the three loci with some evidence of association with SCZ and smoking behaviors, using GWAS summary statistics. Colocalization was also assessed for positive control traits and CUD. Three different sensibility analyses were used to confirm the results. A visualization tool, LocusCompare, was used to facilitate interpretation of the coloc results. RESULTS Evidence for colocalization of GWAS signals between SCZ and smoking behaviors was found for CHRNA2. Evidence for independent causal variants was found for the other two loci. CUD GWAS signal at CHRNA2 colocalizes with SCZ and smoking behaviors. CONCLUSIONS Overall, the results indicate that the association between some nAchR subunit genes and SCZ cannot be solely explained by their effect on smoking behaviors.
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50
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Abdellaoui A, Smit DJA, van den Brink W, Denys D, Verweij KJH. Genomic relationships across psychiatric disorders including substance use disorders. Drug Alcohol Depend 2021; 220:108535. [PMID: 33524898 DOI: 10.1016/j.drugalcdep.2021.108535] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Revised: 12/08/2020] [Accepted: 12/23/2020] [Indexed: 11/16/2022]
Abstract
BACKGROUND A recent study investigated the genetic associations and latent genetic structure among eight psychiatric disorders using findings from genome-wide association studies (GWASs). No data from substance use disorders were included, while these represent an important category of mental disorders and could influence the latent genetic structure. We extended the original paper by recreating the genetic relationship matrix, graph, and latent genetic factor structure, including additional data from substance use disorders. METHODS We used GWAS summary statistics of 11 psychiatric disorders, including alcohol dependence, nicotine dependence, and cannabis use disorder. We estimated genetic correlations between all traits in Linkage Disequilibrium-Score Regression. A graph was created to illustrate the network of genetic correlations. We then used the genetic relationships to model a latent genetic factor structure. RESULTS Alcohol and nicotine dependence showed significant genetic correlations with several other psychiatric disorders, including ADHD, schizophrenia, and major depression. Cannabis use disorder was only significantly associated with ADHD. The addition of substance use disorders resulted in some changes in the latent structure of the factor model when compared to the original model including eight disorders. All substance use disorders contributed mostly to Factor 3, a heterogeneous factor with also loadings from ADHD, major depression, Autism Spectrum Disorders, and Tourette Syndrome. CONCLUSIONS Alcohol and nicotine dependence show widespread genetic correlations with other psychiatric disorders. Including substance use disorders in the factor analysis results in some changes in the underlying genetic factor structure. Given the instability of such models, identified structures should be interpreted with caution.
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Affiliation(s)
- Abdel Abdellaoui
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, 1105 AZ, Amsterdam, the Netherlands
| | - Dirk J A Smit
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, 1105 AZ, Amsterdam, the Netherlands
| | - Wim van den Brink
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, 1105 AZ, Amsterdam, the Netherlands
| | - Damiaan Denys
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, 1105 AZ, Amsterdam, the Netherlands
| | - Karin J H Verweij
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, 1105 AZ, Amsterdam, the Netherlands.
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