1
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Zhou H, Gelernter J. Human genetics and epigenetics of alcohol use disorder. J Clin Invest 2024; 134:e172885. [PMID: 39145449 PMCID: PMC11324314 DOI: 10.1172/jci172885] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/16/2024] Open
Abstract
Alcohol use disorder (AUD) is a prominent contributor to global morbidity and mortality. Its complex etiology involves genetics, epigenetics, and environmental factors. We review progress in understanding the genetics and epigenetics of AUD, summarizing the key findings. Advancements in technology over the decades have elevated research from early candidate gene studies to present-day genome-wide scans, unveiling numerous genetic and epigenetic risk factors for AUD. The latest GWAS on more than one million participants identified more than 100 genetic variants, and the largest epigenome-wide association studies (EWAS) in blood and brain samples have revealed tissue-specific epigenetic changes. Downstream analyses revealed enriched pathways, genetic correlations with other traits, transcriptome-wide association in brain tissues, and drug-gene interactions for AUD. We also discuss limitations and future directions, including increasing the power of GWAS and EWAS studies as well as expanding the diversity of populations included in these analyses. Larger samples, novel technologies, and analytic approaches are essential; these include whole-genome sequencing, multiomics, single-cell sequencing, spatial transcriptomics, deep-learning prediction of variant function, and integrated methods for disease risk prediction.
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Affiliation(s)
- Hang Zhou
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut, USA
- Department of Biomedical Informatics and Data Science
- Center for Brain and Mind Health
| | - Joel Gelernter
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut, USA
- Department of Genetics, and
- Department of Neuroscience, Yale School of Medicine, New Haven, Connecticut, USA
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2
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Zhou H, Kember RL, Deak JD, Xu H, Toikumo S, Yuan K, Lind PA, Farajzadeh L, Wang L, Hatoum AS, Johnson J, Lee H, Mallard TT, Xu J, Johnston KJA, Johnson EC, Nielsen TT, Galimberti M, Dao C, Levey DF, Overstreet C, Byrne EM, Gillespie NA, Gordon S, Hickie IB, Whitfield JB, Xu K, Zhao H, Huckins LM, Davis LK, Sanchez-Roige S, Madden PAF, Heath AC, Medland SE, Martin NG, Ge T, Smoller JW, Hougaard DM, Børglum AD, Demontis D, Krystal JH, Gaziano JM, Edenberg HJ, Agrawal A, Justice AC, Stein MB, Kranzler HR, Gelernter J. Multi-ancestry study of the genetics of problematic alcohol use in over 1 million individuals. Nat Med 2023; 29:3184-3192. [PMID: 38062264 PMCID: PMC10719093 DOI: 10.1038/s41591-023-02653-5] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Accepted: 10/18/2023] [Indexed: 12/17/2023]
Abstract
Problematic alcohol use (PAU), a trait that combines alcohol use disorder and alcohol-related problems assessed with a questionnaire, is a leading cause of death and morbidity worldwide. Here we conducted a large cross-ancestry meta-analysis of PAU in 1,079,947 individuals (European, N = 903,147; African, N = 122,571; Latin American, N = 38,962; East Asian, N = 13,551; and South Asian, N = 1,716 ancestries). We observed a high degree of cross-ancestral similarity in the genetic architecture of PAU and identified 110 independent risk variants in within- and cross-ancestry analyses. Cross-ancestry fine mapping improved the identification of likely causal variants. Prioritizing genes through gene expression and chromatin interaction in brain tissues identified multiple genes associated with PAU. We identified existing medications for potential pharmacological studies by a computational drug repurposing analysis. Cross-ancestry polygenic risk scores showed better performance of association in independent samples than single-ancestry polygenic risk scores. Genetic correlations between PAU and other traits were observed in multiple ancestries, with other substance use traits having the highest correlations. This study advances our knowledge of the genetic etiology of PAU, and these findings may bring possible clinical applicability of genetics insights-together with neuroscience, biology and data science-closer.
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Affiliation(s)
- Hang Zhou
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA.
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA.
- Section of Biomedical Informatics and Data Science, Yale School of Medicine, New Haven, CT, USA.
| | - Rachel L Kember
- Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Joseph D Deak
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Heng Xu
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Sylvanus Toikumo
- Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Kai Yuan
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Penelope A Lind
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- School of Biomedical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
- Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia
| | - Leila Farajzadeh
- Department of Biomedicine - Human Genetics, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - Lu Wang
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Alexander S Hatoum
- Department of Psychological and Brain Sciences, Washington University in St. Louis, Saint Louis, MO, USA
| | - Jessica Johnson
- Pamela Sklar Division of Psychiatric Genomics, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Hyunjoon Lee
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Travis T Mallard
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Jiayi Xu
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | | | - Emma C Johnson
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Trine Tollerup Nielsen
- Department of Biomedicine - Human Genetics, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - Marco Galimberti
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Cecilia Dao
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Daniel F Levey
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Cassie Overstreet
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Enda M Byrne
- Child Health Research Centre, The University of Queensland, Brisbane, Queensland, Australia
| | - Nathan A Gillespie
- Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Scott Gordon
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Ian B Hickie
- Brain and Mind Centre, University of Sydney, Camperdown, New South Wales, Australia
| | - John B Whitfield
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Ke Xu
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Hongyu Zhao
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
| | - Laura M Huckins
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Lea K Davis
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Medicine, Division of Medical Genetics, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Sandra Sanchez-Roige
- Department of Medicine, Division of Medical Genetics, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Pamela A F Madden
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Andrew C Heath
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Sarah E Medland
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia
- School of Psychology, University of Queensland, Brisbane, Queensland, Australia
| | - Nicholas G Martin
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Tian Ge
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Center for Precision Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Jordan W Smoller
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Center for Precision Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - David M Hougaard
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Neonatal Screening, Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark
| | - Anders D Børglum
- Department of Biomedicine - Human Genetics, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - Ditte Demontis
- Department of Biomedicine - Human Genetics, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
- The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - John H Krystal
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA
- National Center for PTSD, US Department of Veterans Affairs, West Haven, CT, USA
- Department of Psychology, Yale University, New Haven, CT, USA
- Psychiatry and Behavioral Health Services, Yale-New Haven Hospital, New Haven, CT, USA
| | - J Michael Gaziano
- Massachusetts Veterans Epidemiology and Research Information Center (MAVERIC), Boston Veterans Affairs Healthcare System, Boston, MA, USA
- Department of Medicine, Divisions of Aging and Preventative Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Howard J Edenberg
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Amy C Justice
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
- Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT, USA
| | - Murray B Stein
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Psychiatry Service, VA San Diego Healthcare System, San Diego, CA, USA
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Henry R Kranzler
- Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Joel Gelernter
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA.
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA.
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA.
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA.
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3
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Nieto SJ, Kosten TA. Paternal alcohol exposure attenuates maintenance and reinstated operant responding for alcohol in the offspring of rats. ALCOHOL, CLINICAL & EXPERIMENTAL RESEARCH 2023; 47:1494-1504. [PMID: 37353981 DOI: 10.1111/acer.15136] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Revised: 05/10/2023] [Accepted: 06/15/2023] [Indexed: 06/25/2023]
Abstract
BACKGROUND The heritability of alcohol use disorder is close to 50%, yet common genetic variants account for less than 5% of risk. The missing heritability may reflect environmental exposure in the parents prior to conception. Indeed, paternal alcohol exposure has many behavioral and biological consequences for rodent offspring. We recently found that paternal alcohol exposure attenuated the acquisition of operant alcohol self-administration in offspring of rats of both sexes. Here we test whether this effect extends to other phases of operant self-administration thought to model motivation, craving, and relapse. METHODS Wistar male rats exposed to alcohol vapors or air for 6 weeks were mated with alcohol-naïve females 8 weeks later. The adult offspring were trained to lever press for alcohol and tested under several conditions: (1) maintenance responding under a progressive ratio schedule, (2) extinction responding due to removal of the alcohol delivery contingency, (3) reinstatement of extinguished responding in the presence of alcohol-associated cues, and (4) reinitiation of lever press responding for alcohol delivery under fixed and progressive ratio schedules. RESULTS Alcohol-sired offspring showed reduced responding under the progressive ratio schedule and blunted cue-induced reinstatement of extinguished responding. Alcohol-sired offspring also emitted fewer responses during extinction sessions and did not reinitiate responding to the same extent as control-sired rats after alcohol delivery was restored. CONCLUSIONS Across all conditions, paternal alcohol exposure led to a reduction in the reinforcing effects of alcohol in offspring. These results are consistent with studies conducted with paternal cocaine exposure except that here we find effects in rats of both sexes.
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Affiliation(s)
- Steven J Nieto
- Department of Psychology, University of Houston, Houston, Texas, USA
| | - Therese A Kosten
- Department of Psychology, University of Houston, Houston, Texas, USA
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Li R, Reiter JL, Chen AB, Chen SX, Foroud T, Edenberg HJ, Lai D, Liu Y. RNA alternative splicing impacts the risk for alcohol use disorder. Mol Psychiatry 2023; 28:2922-2933. [PMID: 37217680 PMCID: PMC10615768 DOI: 10.1038/s41380-023-02111-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 04/28/2023] [Accepted: 05/05/2023] [Indexed: 05/24/2023]
Abstract
Alcohol use disorder (AUD) is a complex genetic disorder characterized by problems arising from excessive alcohol consumption. Identifying functional genetic variations that contribute to risk for AUD is a major goal. Alternative splicing of RNA mediates the flow of genetic information from DNA to gene expression and expands proteome diversity. We asked whether alternative splicing could be a risk factor for AUD. Herein, we used a Mendelian randomization (MR)-based approach to identify skipped exons (the predominant splicing event in brain) that contribute to AUD risk. Genotypes and RNA-seq data from the CommonMind Consortium were used as the training dataset to develop predictive models linking individual genotypes to exon skipping in the prefrontal cortex. We applied these models to data from the Collaborative Studies on Genetics of Alcoholism to examine the association between the imputed cis-regulated splicing outcome and the AUD-related traits. We identified 27 exon skipping events that were predicted to affect AUD risk; six of these were replicated in the Australian Twin-family Study of Alcohol Use Disorder. Their host genes are DRC1, ELOVL7, LINC00665, NSUN4, SRRM2 and TBC1D5. The genes downstream of these splicing events are enriched in neuroimmune pathways. The MR-inferred impacts of the ELOVL7 skipped exon on AUD risk was further supported in four additional large-scale genome-wide association studies. Additionally, this exon contributed to changes of gray matter volumes in multiple brain regions, including the visual cortex known to be involved in AUD. In conclusion, this study provides strong evidence that RNA alternative splicing impacts the susceptibility to AUD and adds new information on AUD-relevant genes and pathways. Our framework is also applicable to other types of splicing events and to other complex genetic disorders.
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Affiliation(s)
- Rudong Li
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Jill L Reiter
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Andy B Chen
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Steven X Chen
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Tatiana Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Howard J Edenberg
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Dongbing Lai
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Yunlong Liu
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA.
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA.
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Gomez LM, Mitchell BL, McAloney K, Adsett J, Garden N, Wood M, Diaz-Torres S, Garcia-Marin LM, Breakspear M, Martin NG, Lupton MK. The Effect of Genetic Predisposition to Alzheimer's Disease and Related Traits on Recruitment Bias in a Study of Cognitive Aging. Twin Res Hum Genet 2023; 26:209-214. [PMID: 37476981 DOI: 10.1017/thg.2023.26] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/22/2023]
Abstract
The recruitment of participants for research studies may be subject to bias. The Prospective Imaging Study of Ageing (PISA) aims to characterize the phenotype and natural history of healthy adult Australians at high future risk of Alzheimer's disease (AD). Participants approached to take part in PISA were selected from existing cohort studies with available genomewide genetic data for both successfully and unsuccessfully recruited participants, allowing us to investigate the genetic contribution to voluntary recruitment, including the genetic predisposition to AD. We use a polygenic risk score (PRS) approach to test to what extent the genetic risk for AD, and related risk factors predict participation in PISA. We did not identify a significant association of genetic risk for AD with study participation, but we did identify significant associations with PRS for key causal risk factors for AD, IQ, household income and years of education. We also found that older and female participants were more likely to take part in the study. Our findings highlight the importance of considering bias in key risk factors for AD in the recruitment of individuals for cohort studies.
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Affiliation(s)
- Lina M Gomez
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | | | - Kerrie McAloney
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Jessica Adsett
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Natalie Garden
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Madeline Wood
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Santiago Diaz-Torres
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia
| | - Luis M Garcia-Marin
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia
| | - Michael Breakspear
- School of Psychological Sciences, The University of Newcastle, Newcastle, New South Wales, Australia
| | - Nicholas G Martin
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Michelle K Lupton
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Queensland, Australia
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6
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Bonea M, Coroama CI, Popp RA, Miclutia IV. The association between the CCDC88A gene polymorphism at rs1437396 and alcohol use disorder, with or without major depression disorder. Arh Hig Rada Toksikol 2023; 74:127-133. [PMID: 37357876 PMCID: PMC10291494 DOI: 10.2478/aiht-2023-74-3690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 11/01/2022] [Accepted: 05/01/2023] [Indexed: 06/27/2023] Open
Abstract
Girdin is a protein involved in neuronal migration and hippocampal development. It is encoded by the coiled-coil domain-containing 88A (CCDC88A) gene, located on the short arm of chromosome 2 (2p). The CCDC88A gene is modulated by the intergenic single-nucleotide polymorphism (SNP) of the rs1437396, situated 9.5 kb downstream from its transcription stop site. As recent genome-wide research has associated the T allele of the SNP with increased risk of alcohol use disorder (AUD), we wanted to validate this finding in an independent cohort and to test further for an association with comorbid major depressive disorder (MDD). The study included 226 AUD patients (AUD group), 53 patients with comorbid MDD, and 391 controls selected randomly. The participants were genotyped for the rs1437396 polymorphism using the real-time polymerase chain reaction. The association between the rs1437396 polymorphism and increased risk of AUD and AUD+MDD was tested with logistic regression. Our results show significantly higher frequency of the T risk allele in the AUD group (p=0.027) and even higher in the AUD+MDD group (p=0.016). In conclusion, this is the first study that has validated the association between the rs1437396 polymorphism of the CCDC88A gene and AUD with or without MDD. Studies on larger samples of patients are needed to further investigate the mechanism of this association.
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Affiliation(s)
- Maria Bonea
- Iuliu Hatieganu University of Medicine and Pharmacy, Department of Neurosciences – Psychiatry, Cluj-Napoca, Romania
| | | | - Radu Anghel Popp
- Iuliu Hatieganu University of Medicine and Pharmacy, Department of Medical Genetics, Cluj-Napoca, Romania
| | - Ioana Valentina Miclutia
- Iuliu Hatieganu University of Medicine and Pharmacy, Department of Neurosciences – Psychiatry, Cluj-Napoca, Romania
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7
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Domi E, Barchiesi R, Barbier E. Epigenetic Dysregulation in Alcohol-Associated Behaviors: Preclinical and Clinical Evidence. Curr Top Behav Neurosci 2023. [PMID: 36717533 DOI: 10.1007/7854_2022_410] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Alcohol use disorder (AUD) is characterized by loss of control over intake and drinking despite harmful consequences. At a molecular level, AUD is associated with long-term neuroadaptations in key brain regions that are involved in reward processing and decision-making. Over the last decades, a great effort has been made to understand the neurobiological basis underlying AUD. Epigenetic mechanisms have emerged as an important mechanism in the regulation of long-term alcohol-induced gene expression changes. Here, we review the literature supporting a role for epigenetic processes in AUD. We particularly focused on the three most studied epigenetic mechanisms: DNA methylation, Histone modification and non-coding RNAs. Clinical studies indicate an association between AUD and DNA methylation both at the gene and global levels. Using behavioral paradigms that mimic some of the characteristics of AUD, preclinical studies demonstrate that changes in epigenetic mechanisms can functionally impact alcohol-associated behaviors. While many studies support a therapeutic potential for targeting epigenetic enzymes, more research is needed to fully understand their role in AUD. Identification of brain circuits underlying alcohol-associated behaviors has made major advances in recent years. However, there are very few studies that investigate how epigenetic mechanisms can affect these circuits or impact the neuronal ensembles that promote alcohol-associated behaviors. Studies that focus on the role of circuit-specific and cell-specific epigenetic changes for clinically relevant alcohol behaviors may provide new insights on the functional role of epigenetic processes in AUD.
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Affiliation(s)
- Esi Domi
- Department of Biomedical and Clinical Sciences, Center for Social and Affective Neuroscience, Linköping University, Linköping, Sweden
- School of Pharmacy, Pharmacology Unit, Center for Neuroscience, University of Camerino, Camerino, Italy
| | - Riccardo Barchiesi
- Department of Neuroscience, Waggoner Center for Alcohol and Alcohol Addiction Research, University of Texas at Austin, Austin, TX, USA
| | - Estelle Barbier
- Department of Biomedical and Clinical Sciences, Center for Social and Affective Neuroscience, Linköping University, Linköping, Sweden.
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8
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Zhou H, Kember RL, Deak JD, Xu H, Toikumo S, Yuan K, Lind PA, Farajzadeh L, Wang L, Hatoum AS, Johnson J, Lee H, Mallard TT, Xu J, Johnston KJ, Johnson EC, Galimberti M, Dao C, Levey DF, Overstreet C, Byrne EM, Gillespie NA, Gordon S, Hickie IB, Whitfield JB, Xu K, Zhao H, Huckins LM, Davis LK, Sanchez-Roige S, Madden PAF, Heath AC, Medland SE, Martin NG, Ge T, Smoller JW, Hougaard DM, Børglum AD, Demontis D, Krystal JH, Gaziano JM, Edenberg HJ, Agrawal A, Justice AC, Stein MB, Kranzler HR, Gelernter J. Multi-ancestry study of the genetics of problematic alcohol use in >1 million individuals. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.01.24.23284960. [PMID: 36747741 PMCID: PMC9901058 DOI: 10.1101/2023.01.24.23284960] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
Problematic alcohol use (PAU) is a leading cause of death and disability worldwide. To improve our understanding of the genetics of PAU, we conducted a large cross-ancestry meta-analysis of PAU in 1,079,947 individuals. We observed a high degree of cross-ancestral similarity in the genetic architecture of PAU and identified 110 independent risk variants in within- and cross-ancestry analyses. Cross-ancestry fine-mapping improved the identification of likely causal variants. Prioritizing genes through gene expression and/or chromatin interaction in brain tissues identified multiple genes associated with PAU. We identified existing medications for potential pharmacological studies by drug repurposing analysis. Cross-ancestry polygenic risk scores (PRS) showed better performance in independent sample than single-ancestry PRS. Genetic correlations between PAU and other traits were observed in multiple ancestries, with other substance use traits having the highest correlations. The analysis of diverse ancestries contributed significantly to the findings, and fills an important gap in the literature.
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Affiliation(s)
- Hang Zhou
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
- These authors contributed equally
| | - Rachel L. Kember
- Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- These authors contributed equally
| | - Joseph D. Deak
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Heng Xu
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Sylvanus Toikumo
- Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Kai Yuan
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Penelope A. Lind
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, Queensland University of Technology, Brisbane, QLD, Australia
- Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
| | - Leila Farajzadeh
- Department of Biomedicine - Human Genetics, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - Lu Wang
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Alexander S. Hatoum
- Department of Psychological and Brain Sciences, Washington University in St. Louis, Saint Louis, MO, USA
| | - Jessica Johnson
- Pamela Sklar Division of Psychiatric Genomics, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Hyunjoon Lee
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Travis T. Mallard
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Jiayi Xu
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | | | - Emma C. Johnson
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Marco Galimberti
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Cecilia Dao
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
- Department of Chronic Disease Epidemiology, Yale University School of Public Health, New Haven, CT, USA
| | - Daniel F. Levey
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Cassie Overstreet
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Enda M. Byrne
- Child Health Research Centre, The University of Queensland, Brisbane, QLD, Australia
| | - Nathan A. Gillespie
- Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Scott Gordon
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Ian B. Hickie
- Brain and Mind Centre, University of Sydney, Camperdown, NSW, Australia
| | - John B. Whitfield
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Ke Xu
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Hongyu Zhao
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
| | - Laura M. Huckins
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Lea K. Davis
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Medicine, Division of Medical Genetics, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Sandra Sanchez-Roige
- Department of Medicine, Division of Medical Genetics, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Pamela A. F. Madden
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Andrew C. Heath
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Sarah E. Medland
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
- School of Psychology, University of Queensland, Brisbane, QLD, Australia
| | - Nicholas G. Martin
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Tian Ge
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Center for Precision Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Jordan W. Smoller
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - David M. Hougaard
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark
- Center for Neonatal Screening, Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark
| | - Anders D. Børglum
- Department of Biomedicine - Human Genetics, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - Ditte Demontis
- Department of Biomedicine - Human Genetics, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - John H. Krystal
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT, USA
- National Center for PTSD, US Department of Veterans Affairs, West Haven, CT, USA
| | - J. Michael Gaziano
- Massachusetts Veterans Epidemiology and Research Information Center (MAVERIC), Boston Veterans Affairs Healthcare System, Boston, MA, USA
- Department of Medicine, Divisions of Aging and Preventative Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Howard J. Edenberg
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | | | - Amy C. Justice
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
- Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT, USA
| | - Murray B. Stein
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- VA San Diego Healthcare System, Psychiatry Service, San Diego, CA, USA
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Henry R. Kranzler
- Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- These authors jointly supervised this work
| | - Joel Gelernter
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT, USA
- These authors jointly supervised this work
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9
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Nieto SJ, Harding MJ, Nielsen DA, Kosten TA. Paternal alcohol exposure has task- and sex-dependent behavioral effect in offspring. Alcohol Clin Exp Res 2022; 46:2191-2202. [PMID: 36281832 DOI: 10.1111/acer.14964] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2022] [Revised: 10/20/2022] [Accepted: 10/21/2022] [Indexed: 02/01/2023]
Abstract
BACKGROUND Endophenotypes for alcohol use disorder are well known and may reflect paternal exposure effects passed down to offspring via epigenetic mechanisms. Previously, we showed that paternal alcohol exposure prior to conception attenuates the acquisition of operant alcohol self-administration. We now test whether paternal alcohol exposure alters their offsprings' behavioral responses to alcohol (endophenotypes) and global DNA methylation levels in reward-related brain regions. METHODS Adult male rats were exposed to alcohol vapors or air for 6 weeks and mated with alcohol-naïve females 8 weeks later. Adult male and female offspring of the alcohol- and control-sired litters were tested on three behaviors 30 m after gavage with water or alcohol (1.5 g/kg): open field, elevated plus maze, and accelerating rotarod. Global DNA methylation levels in sperm, nucleus accumbens, and prefrontal cortex were examined in male sires and in another group of offspring. RESULTS Alcohol-sired males showed less anxiety-like behavior in the elevated plus maze that was not affected by alcohol administration. By contrast, alcohol had anxiolytic effects in the open field in male offspring only with no paternal alcohol effect. Neither paternal alcohol exposure nor alcohol administration altered locomotor activity in either sex. Sex-specific effects of paternal alcohol exposure were seen in the rotarod test. Alcohol-sired male offspring showed blunted sensitivity to the alcohol's motor-impairing effects, whereas alcohol-sired female offspring showed enhanced sensitivity. Global DNA methylation was altered in the sperm of alcohol-exposed males, but no changes were seen in their offspring. CONCLUSIONS Paternal alcohol exposure prior to conception has sex- and task-dependent effects on unconditioned behaviors in their offspring.
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Affiliation(s)
- Steven J Nieto
- Department of Psychology, University of Houston, Houston, Texas, USA
| | | | | | - Therese A Kosten
- Department of Psychology, University of Houston, Houston, Texas, USA
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10
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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: 2] [Impact Index Per Article: 1.0] [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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11
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Co-Inheritance of Variation in All-Cause Mortality and Biochemical Risk Factors. Twin Res Hum Genet 2022; 25:107-114. [PMID: 35818962 DOI: 10.1017/thg.2022.25] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Biomarkers may be useful endophenotypes for genetic studies if they share genetic sources of variation with the outcome, for example, with all-cause mortality. Australian adult study participants who had reported their parental survival information were included in the study: 14,169 participants had polygenic risk scores (PRS) from genotyping and up to 13,365 had biomarker results. We assessed associations between participants' biomarker results and parental survival, and between biomarker results and eight parental survival PRS at varying p-value cut-offs. Survival in parents was associated with participants' serum bilirubin, C-reactive protein, HDL cholesterol, triglycerides and uric acid, and with LDL cholesterol for participants' fathers but not for their mothers. PRS for all-cause mortality were associated with liver function tests (alkaline phosphatase, butyrylcholinesterase, gamma-glutamyl transferase), metabolic tests (LDL and HDL cholesterol, triglycerides, uric acid), and acute-phase reactants (C-reactive protein, globulins). Association between offspring biomarker results and parental survival demonstrates the existence of familial effects common to both, while associations between biomarker results and PRS for mortality favor at least a partial genetic cause of this covariation. Identification of genetic loci affecting mortality-associated biomarkers offers a route to the identification of additional loci affecting mortality.
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12
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Blum K, Brodie MS, Pandey SC, Cadet JL, Gupta A, Elman I, Thanos PK, Gondre-Lewis MC, Baron D, Kazmi S, Bowirrat A, Febo M, Badgaiyan RD, Braverman ER, Dennen CA, Gold MS. Researching Mitigation of Alcohol Binge Drinking in Polydrug Abuse: KCNK13 and RASGRF2 Gene(s) Risk Polymorphisms Coupled with Genetic Addiction Risk Severity (GARS) Guiding Precision Pro-Dopamine Regulation. J Pers Med 2022; 12:jpm12061009. [PMID: 35743793 PMCID: PMC9224860 DOI: 10.3390/jpm12061009] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 06/12/2022] [Accepted: 06/16/2022] [Indexed: 11/22/2022] Open
Abstract
Excessive alcohol intake, e.g., binge drinking, is a serious and mounting public health problem in the United States and throughout the world. Hence the need for novel insights into the underlying neurobiology that may help improve prevention and therapeutic strategies. Therefore, our group employed a darkness-induced alcohol intake protocol to define the reward deficiency domains of alcohol and other substance use disorders in terms of reward pathways' reduced dopamine signaling and its restoration via specifically-designed therapeutic compounds. It has been determined that KCNK13 and RASGRF2 genes, respectively, code for potassium two pore domain channel subfamily K member 13 and Ras-specific guanine nucleotide-releasing factor 2, and both genes have important dopamine-related functions pertaining to alcohol binge drinking. We present a hypothesis that identification of KCNK13 and RASGRF2 genes' risk polymorphism, coupled with genetic addiction risk score (GARS)-guided precision pro-dopamine regulation, will mitigate binge alcohol drinking. Accordingly, we review published reports on the benefits of this unique approach and provide data on favorable outcomes for both binge-drinking animals and drunk drivers, including reductions in alcohol intake and prevention of relapse to drinking behavior. Since driving under the influence of alcohol often leads to incarceration rather than rehabilitation, there is converging evidence to support the utilization of GARS with or without KCNK13 and RASGRF2 risk polymorphism in the legal arena, whereby the argument that "determinism" overrides the "free will" account may be a plausible defense strategy. Obviously, this type of research is tantamount to helping resolve a major problem related to polydrug abuse.
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Affiliation(s)
- Kenneth Blum
- The Kenneth Blum Behavioral & Neurogenetic Institute, Austin, TX 78701, USA; (E.R.B.); (C.A.D.)
- Division of Addiction Research & Education, Center for Psychiatry, Medicine & Primary Care (Office of Provost), Western University Health Sciences, Pomona, CA 91766, USA; (D.B.); (M.F.)
- Institute of Psychology, ELTE Eötvös Loránd University, Egyetem tér 1-3, 1053 Budapest, Hungary
- Department of Psychiatry, School of Medicine, University of Vermont, Burlington, VT 05405, USA
- Department of Psychiatry, Wright State University Boonshoft School of Medicine and Dayton VA Medical Centre, Dayton, OH 45324, USA
- Correspondence:
| | - Mark S. Brodie
- Center for Alcohol Research in Epigenetics, Departments of Physiology and Biophysics, and Psychiatry, University of Illinois at Chicago, Chicago, IL 60612, USA; (M.S.B.); (S.C.P.)
| | - Subhash C. Pandey
- Center for Alcohol Research in Epigenetics, Departments of Physiology and Biophysics, and Psychiatry, University of Illinois at Chicago, Chicago, IL 60612, USA; (M.S.B.); (S.C.P.)
| | - Jean Lud Cadet
- Molecular Neuropsychiatry Research Branch, National Institute on Drug Abuse, National Institutes of Health, Bethesda, MD 20892, USA;
| | - Ashim Gupta
- Future Biologics, Lawrenceville, GA 30043, USA;
| | - Igor Elman
- Center for Pain and the Brain (P.A.I.N Group), Department of Anesthesiology, Critical Care & Pain Medicine, Boston Children’s Hospital, Boston, MA 02115, USA;
| | - Panayotis K. Thanos
- Behavioral Neuropharmacology and Neuroimaging Laboratory on Addictions, Clinical Research Institute on Addictions, Department of Pharmacology and Toxicology, Jacobs School of Medicine and Biosciences, State University of New York at Buffalo, Buffalo, NY 14203, USA;
- Department of Psychology, State University of New York at Buffalo, Buffalo, NY 14203, USA
| | - Marjorie C. Gondre-Lewis
- Neuropsychopharmacology Laboratory, Department of Anatomy, Howard University College of Medicine, Washington, DC 20059, USA;
| | - David Baron
- Division of Addiction Research & Education, Center for Psychiatry, Medicine & Primary Care (Office of Provost), Western University Health Sciences, Pomona, CA 91766, USA; (D.B.); (M.F.)
| | - Shan Kazmi
- College of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, CA 91766, USA;
| | - Abdalla Bowirrat
- Department of Molecular Biology and Adelson School of Medicine, Ariel University, Ariel 40700, Israel;
| | - Marcelo Febo
- Division of Addiction Research & Education, Center for Psychiatry, Medicine & Primary Care (Office of Provost), Western University Health Sciences, Pomona, CA 91766, USA; (D.B.); (M.F.)
| | - Rajendra D. Badgaiyan
- Department of Psychiatry, South Texas Veteran Health Care System, Audie L. Murphy Memorial VA Hospital, Long School of Medicine, University of Texas Medical Center, San Antonio, TX 78229, USA;
| | - Eric R. Braverman
- The Kenneth Blum Behavioral & Neurogenetic Institute, Austin, TX 78701, USA; (E.R.B.); (C.A.D.)
| | - Catherine A. Dennen
- The Kenneth Blum Behavioral & Neurogenetic Institute, Austin, TX 78701, USA; (E.R.B.); (C.A.D.)
| | - Mark S. Gold
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA;
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13
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Parker CC, Philip VM, Gatti DM, Kasparek S, Kreuzman AM, Kuffler L, Mansky B, Masneuf S, Sharif K, Sluys E, Taterra D, Taylor WM, Thomas M, Polesskaya O, Palmer AA, Holmes A, Chesler EJ. Genome-wide association mapping of ethanol sensitivity in the Diversity Outbred mouse population. Alcohol Clin Exp Res 2022; 46:941-960. [PMID: 35383961 DOI: 10.1111/acer.14825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Revised: 03/04/2022] [Accepted: 03/30/2022] [Indexed: 12/01/2022]
Abstract
BACKGROUND A strong predictor for the development of alcohol use disorder (AUD) is altered sensitivity to the intoxicating effects of alcohol. Individual differences in the initial sensitivity to alcohol are controlled in part by genetic factors. Mice offer a powerful tool to elucidate the genetic basis of behavioral and physiological traits relevant to AUD, but conventional experimental crosses have only been able to identify large chromosomal regions rather than specific genes. Genetically diverse, highly recombinant mouse populations make it possible to observe a wider range of phenotypic variation, offer greater mapping precision, and thus increase the potential for efficient gene identification. METHODS We have taken advantage of the Diversity Outbred (DO) mouse population to identify and precisely map quantitative trait loci (QTL) associated with ethanol sensitivity. We phenotyped 798 male J:DO mice for three measures of ethanol sensitivity: ataxia, hypothermia, and loss of the righting response. We used high-density MegaMUGA and GigaMUGA to obtain genotypes ranging from 77,808 to 143,259 SNPs. We also performed RNA sequencing in striatum to map expression QTLs and identify gene expression-trait correlations. We then applied a systems genetic strategy to identify narrow QTLs and construct the network of correlations that exists between DNA sequence, gene expression values, and ethanol-related phenotypes to prioritize our list of positional candidate genes. RESULTS We observed large amounts of phenotypic variation with the DO population and identified suggestive and significant QTLs associated with ethanol sensitivity on chromosomes 1, 2, and 16. The implicated regions were narrow (4.5-6.9 Mb in size) and each QTL explained ~4-5% of the variance. CONCLUSIONS Our results can be used to identify alleles that contribute to AUD in humans, elucidate causative biological mechanisms, or assist in the development of novel therapeutic interventions.
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Affiliation(s)
- Clarissa C Parker
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, Vermont, USA
| | - Vivek M Philip
- Center for Computational Sciences, The Jackson Laboratory, Bar Harbor, Maine, USA
| | - Daniel M Gatti
- Center for Computational Sciences, The Jackson Laboratory, Bar Harbor, Maine, USA
| | - Steven Kasparek
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, Vermont, USA
| | - Andrew M Kreuzman
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, Vermont, USA
| | - Lauren Kuffler
- Center for Mammalian Genetics, The Jackson Laboratory, Bar Harbor, Maine, USA
| | - Benjamin Mansky
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, Vermont, USA
| | - Sophie Masneuf
- Laboratory of Behavioral and Genomic Neuroscience, NIAAA, NIH, Rockville, MD, USA
| | - Kayvon Sharif
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, Vermont, USA
| | - Erica Sluys
- Laboratory of Behavioral and Genomic Neuroscience, NIAAA, NIH, Rockville, MD, USA
| | - Dominik Taterra
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, Vermont, USA
| | - Walter M Taylor
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, Vermont, USA
| | - Mary Thomas
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, Vermont, USA
| | - Oksana Polesskaya
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,Institute for Genomic Medicine, University of California San Diego, La Jolla, California, USA
| | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,Institute for Genomic Medicine, University of California San Diego, La Jolla, California, USA
| | - Andrew Holmes
- Laboratory of Behavioral and Genomic Neuroscience, NIAAA, NIH, Rockville, MD, USA
| | - Elissa J Chesler
- Center for Mammalian Genetics, The Jackson Laboratory, Bar Harbor, Maine, USA
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14
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Wu Y, Zhong Y, Liao X, Miao X, Yu J, Lai X, Zhang Y, Ma C, Pan H, Wang S. Transmembrane protein 108 inhibits the proliferation and myelination of oligodendrocyte lineage cells in the corpus callosum. Mol Brain 2022; 15:33. [PMID: 35410424 PMCID: PMC8996597 DOI: 10.1186/s13041-022-00918-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Accepted: 03/31/2022] [Indexed: 11/22/2022] Open
Abstract
Background Abnormal white matter is a common neurobiological change in bipolar disorder, and dysregulation of myelination in oligodendrocytes (OLs) is the cause. Transmembrane protein 108 (Tmem108), as a susceptible gene of bipolar disorder, is expressed higher in OL lineage cells than any other lineage cells in the central nervous system. Moreover, Tmem108 mutant mice exhibit mania-like behaviors, belonging to one of the signs of bipolar disorder. However, it is unknown whether Tmem108 regulates the myelination of the OLs. Results Tmem108 expression in the corpus callosum decreased with the development, and OL progenitor cell proliferation and OL myelination were enhanced in the mutant mice. Moreover, the mutant mice exhibited mania-like behavior after acute restraint stress and were susceptible to drug-induced epilepsy. Conclusions Tmem108 inhibited OL progenitor cell proliferation and mitigated OL maturation in the corpus callosum, which may also provide a new role of Tmem108 involving bipolar disorder pathogenesis. Supplementary Information The online version contains supplementary material available at 10.1186/s13041-022-00918-7.
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15
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Nieto SJ, Haile CN, Quave CB, Harding MJ, Nielsen DA, Meisch RA, Kosten TA. Paternal alcohol exposure reduces acquisition of operant alcohol self-administration and affects Bdnf DNA methylation in male and female offspring. Addict Biol 2022; 27:e13078. [PMID: 34363290 PMCID: PMC8720057 DOI: 10.1111/adb.13078] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 06/25/2021] [Accepted: 07/12/2021] [Indexed: 01/03/2023]
Abstract
Familial transmission of alcohol use disorder reflects genetic and environmental factors. Paternal alcohol exposure may affect rodent offspring via epigenetic modifications transmitted through the male germ line. While such exposure alters alcohol sensitivity in mouse offspring, no studies examined if it impacts the development of operant alcohol self-administration in rats. We exposed male (sires) Wistar rats to chronic intermittent ethanol in vapour chambers (16 h/day; 5 days/week) or to air for 6 weeks. Eight weeks later, rats were mated with alcohol-naive females. Adult alcohol- and control-sired F1 offspring were assessed in acquisition of alcohol self-administration in which increasing alcohol concentrations (2.5%, 5% and 10%, v/v) were delivered after one lever press (fixed ratio 1 or FR1). Prior to alcohol sessions, rats were trained to lever press for food delivery under an FR1 schedule of reinforcement. DNA methylation levels of the brain derived neurotrophic factor (Bdnf) gene were measured in sperm, nucleus accumbens (NAc) and medial prefrontal cortex (mPFC) in sires and in offspring. Alcohol-exposed sires had lower Bdnf DNA methylation levels in NAc and greater methylation levels in mPFC. Although this pattern was not recapitulated in offspring, alcohol-sired offspring of both sexes did show aberrant Bdnf DNA methylation patterns compared to control-sired offspring. Alcohol-sired offspring self-administered less alcohol (5% and 10%) with no group differences in food responding. Results indicate that paternal alcohol exposure prior to conception protects against alcohol's initial reinforcing effects but the pattern of dysregulated Bdnf methylation in reward-related circuitry did not mimic changes seen in sires.
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Affiliation(s)
- Steven J Nieto
- Department of Psychology and Texas Institute for Measurement, Evaluation and Statistics (TIMES), University of Houston, Houston, Texas, USA
| | - Colin N Haile
- Department of Psychology and Texas Institute for Measurement, Evaluation and Statistics (TIMES), University of Houston, Houston, Texas, USA
| | - Cana B Quave
- Department of Psychology and Texas Institute for Measurement, Evaluation and Statistics (TIMES), University of Houston, Houston, Texas, USA
| | - Mark J Harding
- The Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - David A Nielsen
- The Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - Richard A Meisch
- Department of Psychology and Texas Institute for Measurement, Evaluation and Statistics (TIMES), University of Houston, Houston, Texas, USA
| | - Therese A Kosten
- Department of Psychology and Texas Institute for Measurement, Evaluation and Statistics (TIMES), University of Houston, Houston, Texas, USA
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16
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Boness CL, Watts AL, Moeller KN, Sher KJ. The Etiologic, Theory-Based, Ontogenetic Hierarchical Framework of Alcohol Use Disorder: A Translational Systematic Review of Reviews. Psychol Bull 2021; 147:1075-1123. [PMID: 35295672 PMCID: PMC8923643 DOI: 10.1037/bul0000333] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
Modern nosologies (e.g., ICD-11, DSM-5) for alcohol use disorder (AUD) and dependence prioritize reliability and clinical presentation over etiology, resulting in a diagnosis that is not always strongly grounded in basic theory and research. Within these nosologies, DSM-5 AUD is treated as a discrete, largely categorical, but graded, phenomenon, which results in additional challenges (e.g., significant phenotypic heterogeneity). Efforts to increase the compatibility between AUD diagnosis and modern conceptualizations of alcohol dependence, which describe it as dimensional and partially overlapping with other psychopathology (e.g., other substance use disorders) will inspire a stronger scientific framework and strengthen AUD's validity. We conducted a systematic review of 144 reviews to integrate addiction constructs and theories into a comprehensive framework with the aim of identifying fundamental mechanisms implicated in AUD. The product of this effort was the Etiologic, Theory-Based, Ontogenetic Hierarchical Framework (ETOH Framework) of AUD mechanisms, which outlines superdomains of cognitive control, reward, as well as negative valence and emotionality, each of which subsume narrower, hierarchically-organized components. We also outline opponent processes and self-awareness as key moderators of AUD mechanisms. In contrast with other frameworks, we recommend an increased conceptual role for negative valence and compulsion in AUD. The ETOH framework serves as a critical step towards conceptualizations of AUD as dimensional and heterogeneous. It has the potential to improve AUD assessment and aid in the development of evidence-based diagnostic measures that focus on key mechanisms in AUD, consequently facilitating treatment matching.
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Affiliation(s)
| | - Ashley L Watts
- Department of Psychological Science, University of Missouri
| | | | - Kenneth J Sher
- Department of Psychological Science, University of Missouri
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Fantino M, Paquette M, Bernard S, Baass A. ANKS1A genotype predicts cardiovascular events in patients with familial hypercholesterolemia. J Clin Lipidol 2021; 15:602-607. [PMID: 34130940 DOI: 10.1016/j.jacl.2021.05.006] [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: 11/04/2020] [Revised: 05/24/2021] [Accepted: 05/25/2021] [Indexed: 10/21/2022]
Abstract
BACKGROUND The rs17609940 variant of the ANKS1A gene has been associated with coronary artery disease (CAD) risk in genome-wide association studies (GWAS), but no study has yet replicated this association in familial hypercholesterolemia (FH) population. OBJECTIVE The aim of this study is to validate the association between the rs17609940 genotype and incident major adverse cardiovascular events (MACE) in a cohort of genetically-confirmed FH patients. METHODS This association study includes 725 genetically-confirmed FH patients with a median observation period of 50 years (33 805 person-years). MACE were defined as either myocardial infarction (MI), stroke, coronary revascularization, hospital admission for unstable angina and cardiovascular disease (CVD) death. The rs17609940 genotype was imputed with an imputation quality of 0.831 following an exome chip genotyping method (Illumina). RESULTS The cohort comprised 469 subjects with GG genotype, 218 subjects with CG genotype and 38 subjects with CC genotype. All baseline characteristics were balanced between the three groups. The CC genotype of rs17609940 was associated with a significant lower risk of incident MACE compared to GG and GC carriers in a recessive model (HR 0.30, 95% CI 0.11-0.82, p=0.02). Even after correction for confounding cardiovascular risk factors, the association between the ANKS1A polymorphism and incident MACE remained strongly significant. CONCLUSIONS We demonstrated that the rs17609940 SNP of the ANKS1A gene is associated with the risk of incident MACE in FH subjects. The exact mechanism underlying this association remains to be clarified.
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Affiliation(s)
- Manon Fantino
- Genetic Dyslipidemias Clinic of the Montreal Clinical Research Institute, Québec, Canada
| | - Martine Paquette
- Genetic Dyslipidemias Clinic of the Montreal Clinical Research Institute, Québec, Canada
| | - Sophie Bernard
- Genetic Dyslipidemias Clinic of the Montreal Clinical Research Institute, Québec, Canada; Department of Medicine, Division of Endocrinology, Université de Montreal, Québec, Canada
| | - Alexis Baass
- Genetic Dyslipidemias Clinic of the Montreal Clinical Research Institute, Québec, Canada; Department of Medicine, Divisions of Experimental Medicine and Medical Biochemistry, McGill University, Québec, Canada.
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18
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Roughan WH, Campos AI, García-Marín LM, Cuéllar-Partida G, Lupton MK, Hickie IB, Medland SE, Wray NR, Byrne EM, Ngo TT, Martin NG, Rentería ME. Comorbid Chronic Pain and Depression: Shared Risk Factors and Differential Antidepressant Effectiveness. Front Psychiatry 2021; 12:643609. [PMID: 33912086 PMCID: PMC8072020 DOI: 10.3389/fpsyt.2021.643609] [Citation(s) in RCA: 46] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Accepted: 03/12/2021] [Indexed: 02/06/2023] Open
Abstract
The bidirectional relationship between depression and chronic pain is well-recognized, but their clinical management remains challenging. Here we characterize the shared risk factors and outcomes for their comorbidity in the Australian Genetics of Depression cohort study (N = 13,839). Participants completed online questionnaires about chronic pain, psychiatric symptoms, comorbidities, treatment response and general health. Logistic regression models were used to examine the relationship between chronic pain and clinical and demographic factors. Cumulative linked logistic regressions assessed the effect of chronic pain on treatment response for 10 different antidepressants. Chronic pain was associated with an increased risk of depression (OR = 1.86 [1.37-2.54]), recent suicide attempt (OR = 1.88 [1.14-3.09]), higher use of tobacco (OR = 1.05 [1.02-1.09]) and misuse of painkillers (e.g., opioids; OR = 1.31 [1.06-1.62]). Participants with comorbid chronic pain and depression reported fewer functional benefits from antidepressant use and lower benefits from sertraline (OR = 0.75 [0.68-0.83]), escitalopram (OR = 0.75 [0.67-0.85]) and venlafaxine (OR = 0.78 [0.68-0.88]) when compared to participants without chronic pain. Furthermore, participants taking sertraline (OR = 0.45 [0.30-0.67]), escitalopram (OR = 0.45 [0.27-0.74]) and citalopram (OR = 0.32 [0.15-0.67]) specifically for chronic pain (among other indications) reported lower benefits compared to other participants taking these same medications but not for chronic pain. These findings reveal novel insights into the complex relationship between chronic pain and depression. Treatment response analyses indicate differential effectiveness between particular antidepressants and poorer functional outcomes for these comorbid conditions. Further examination is warranted in targeted interventional clinical trials, which also include neuroimaging genetics and pharmacogenomics protocols. This work will advance the delineation of disease risk indicators and novel aetiological pathways for therapeutic intervention in comorbid pain and depression as well as other psychiatric comorbidities.
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Affiliation(s)
- William H. Roughan
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
| | - Adrián I. Campos
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
| | - Luis M. García-Marín
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
| | - Gabriel Cuéllar-Partida
- Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
- UQ Diamantina Institute, The University of Queensland and Translational Research Institute, Brisbane, QLD, Australia
| | - Michelle K. Lupton
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Ian B. Hickie
- Brain and Mind Centre, University of Sydney, Camperdown, NSW, Australia
| | - Sarah E. Medland
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Naomi R. Wray
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Enda M. Byrne
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
| | - Trung Thanh Ngo
- Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
- UQ Diamantina Institute, The University of Queensland and Translational Research Institute, Brisbane, QLD, Australia
| | - Nicholas G. Martin
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Miguel E. Rentería
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
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19
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Li W, Thygesen JH, O'Brien NL, Heydtmann M, Smith I, Degenhardt F, Nöthen MM, Morgan MY, Bass NJ, McQuillin A. The influence of regression models on genome-wide association studies of alcohol dependence: a comparison of binary and quantitative analyses. Psychiatr Genet 2021; 31:13-20. [PMID: 33290381 DOI: 10.1097/ypg.0000000000000268] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
INTRODUCTION Genome-wide association studies (GWAS) of alcohol dependence syndrome (ADS) offer a platform to detect genetic risk loci. However, the majority of the ADS GWAS undertaken, to date, have utilized a case-control design and have failed to identify consistently replicable loci with the exception of protective variants within the alcohol metabolizing genes, notably ADH1B. The ADS phenotype shows considerable variability which means that the use of quantitative variables as a proxy for the severity of ADS has the potential to facilitate identification of risk loci by increasing statistical power. The current study aims to examine the influences of using binary and adjusted quantitative measures of ADS on GWAS outcomes and on calculated polygenic risk scores (PRS). METHODS A GWAS was performed in 1251 healthy controls with no history of excess alcohol use and 739 patients with ADS classified using binary DMS-IV criteria. Two additional GWAS were undertaken using a quantitative score based on DSM-IV criteria, which were applied assuming both normal and non-normal distributions of the phenotypic variables. PRS analyses were performed utilizing the data from the binary and the quantitative trait analyses. RESULTS No associations were identified at genome-wide significance in any of the individual GWAS; results were comparable in all three. The top associated single nucleotide polymorphism was located on the alcohol dehydrogenase gene cluster on chromosome 4, consistent with previous ADS GWAS. The quantitative trait analysis adjusted for the distribution of the criterion score and the associated PRS had the smallest standard errors and thus the greatest precision. CONCLUSION Further exploitation of the use of qualitative trait analysis in GWAS in ADS is warranted.
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Affiliation(s)
- Wenqianglong Li
- Molecular Psychiatry Laboratory, Division of Psychiatry, University College London, London
| | - Johan Hilge Thygesen
- Molecular Psychiatry Laboratory, Division of Psychiatry, University College London, London
| | - Niamh Louise O'Brien
- Molecular Psychiatry Laboratory, Division of Psychiatry, University College London, London
| | - Mathis Heydtmann
- Royal Alexandria Hospital, NHS Greater Glasgow and Clyde, Paisley
| | - Iain Smith
- Glasgow Addiction Services, NHS Greater Glasgow and Clyde, Glasgow, UK
| | - Franziska Degenhardt
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn
- Department of Child and Adolescent Psychiatry, University of Duisburg-Essen, Essen, Germany
| | - Markus Maria Nöthen
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn
| | - Marsha Yvonne Morgan
- UCL Institute for Liver & Digestive Health, Division of Medicine, Royal Free Campus, University College London, London, UK
| | - Nicholas James Bass
- Molecular Psychiatry Laboratory, Division of Psychiatry, University College London, London
| | - Andrew McQuillin
- Molecular Psychiatry Laboratory, Division of Psychiatry, University College London, London
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20
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Abstract
Mortality risk is known to be associated with many physiological or biochemical risk factors, and polygenic risk scores (PRSs) may offer an additional or alternative approach to risk stratification. We have compared the predictive value of common biochemical tests, PRSs and information on parental survival in a cohort of twins and their families. Common biochemical test results were available for up to 13,365 apparently healthy men and women, aged 17-93 years (mean 49.0, standard deviation [SD] 13.7) at blood collection. PRSs for longevity were available for 14,169 study participants and reported parental survival for 25,784 participants. A search for information on date and cause of death was conducted through the Australian National Death Index, with median follow-up of 11.3 years. Cox regression was used to evaluate associations with mortality from all causes, cancers, cardiovascular diseases and other causes. Linear relationships with all-cause mortality were strongest for C-reactive protein, gamma-glutamyl transferase, glucose and alkaline phosphatase, with hazard ratios (HRs) of 1.16 (95% CI [1.07, 1.24]), 1.15 (95% CI 1.04-1.21), 1.13 (95% CI [1.08, 1.19]) and 1.11 (95% CI [1.05, 1.88]) per SD difference, respectively. Significant nonlinear effects were found for urea, uric acid and butyrylcholinesterase. Lipid risk factors were not statistically significant for mortality in our cohort. Family history and PRS showed weaker but significant associations with survival, with HR in the range 1.05 to 1.09 per SD difference. In conclusion, biochemical tests currently predict long-term mortality more strongly than genetic scores based on genotyping or on reported parental survival.
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21
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Yu J, Liao X, Zhong Y, Wu Y, Lai X, Jiao H, Yan M, Zhang Y, Ma C, Wang S. The Candidate Schizophrenia Risk Gene Tmem108 Regulates Glucose Metabolism Homeostasis. Front Endocrinol (Lausanne) 2021; 12:770145. [PMID: 34690937 PMCID: PMC8531597 DOI: 10.3389/fendo.2021.770145] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Accepted: 09/23/2021] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Schizophrenia (SCZ) is a severe psychiatric disease affected by genetic factors and environmental contributors, and premorbid abnormality of glucose metabolism is one of the SCZ characteristics supposed to contribute to the disease's pathological process. Transmembrane protein 108 (Tmem108) is a susceptible gene associated with multiple psychiatric diseases, including SCZ. Moreover, Tmem108 mutant mice exhibit SCZ-like behaviors in the measurement of sensorimotor gating. However, it is unknown whether Tmem108 regulates glucose metabolism homeostasis while it involves SCZ pathophysiological process. RESULTS In this research, we found that Tmem108 mutant mice exhibited glucose intolerance, insulin resistance, and disturbed metabolic homeostasis. Food and oxygen consumption decreased, and urine production increased, accompanied by weak fatigue resistance in the mutant mice. Simultaneously, the glucose metabolic pathway was enhanced, and lipid metabolism decreased in the mutant mice, consistent with the elevated respiratory exchange ratio (RER). Furthermore, metformin attenuated plasma glucose levels and improved sensorimotor gating in Tmem108 mutant mice. CONCLUSIONS Hyperglycemia occurs more often in SCZ patients than in control, implying that these two diseases share common biological mechanisms, here we demonstrate that the Tmem108 mutant may represent such a comorbid mechanism.
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Affiliation(s)
- Jianbo Yu
- Laboratory of Synaptic Development and Plasticity, Institute of Life Science & School of Life Sciences, Nanchang University, Nanchang, China
| | - Xufeng Liao
- Laboratory of Synaptic Development and Plasticity, Institute of Life Science & School of Life Sciences, Nanchang University, Nanchang, China
| | - Yanzi Zhong
- Laboratory of Synaptic Development and Plasticity, Institute of Life Science & School of Life Sciences, Nanchang University, Nanchang, China
- Department of Biology, Senior Middle School of Yongfeng, Ji’an, China
| | - Yongqiang Wu
- Laboratory of Synaptic Development and Plasticity, Institute of Life Science & School of Life Sciences, Nanchang University, Nanchang, China
| | - Xinsheng Lai
- Laboratory of Synaptic Development and Plasticity, Institute of Life Science & School of Life Sciences, Nanchang University, Nanchang, China
- School of Basic Medical Sciences, Nanchang University, Nanchang, China
| | - Huifeng Jiao
- School of Basic Medical Sciences, Nanchang University, Nanchang, China
| | - Min Yan
- School of Basic Medical Sciences, Nanchang University, Nanchang, China
| | - Yu Zhang
- Laboratory of Synaptic Development and Plasticity, Institute of Life Science & School of Life Sciences, Nanchang University, Nanchang, China
| | - Chaolin Ma
- Laboratory of Synaptic Development and Plasticity, Institute of Life Science & School of Life Sciences, Nanchang University, Nanchang, China
- School of Basic Medical Sciences, Nanchang University, Nanchang, China
- *Correspondence: Chaolin Ma, ; Shunqi Wang,
| | - Shunqi Wang
- Laboratory of Synaptic Development and Plasticity, Institute of Life Science & School of Life Sciences, Nanchang University, Nanchang, China
- School of Basic Medical Sciences, Nanchang University, Nanchang, China
- *Correspondence: Chaolin Ma, ; Shunqi Wang,
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22
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Alcohol. Alcohol 2021. [DOI: 10.1016/b978-0-12-816793-9.00001-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
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23
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Ceci FM, Ferraguti G, Petrella C, Greco A, Ralli M, Iannitelli A, Carito V, Tirassa P, Chaldakov GN, Messina MP, Ceccanti M, Fiore M. Nerve Growth Factor in Alcohol Use Disorders. Curr Neuropharmacol 2020; 19:45-60. [PMID: 32348226 PMCID: PMC7903493 DOI: 10.2174/1570159x18666200429003239] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2020] [Revised: 03/19/2020] [Accepted: 04/24/2020] [Indexed: 12/11/2022] Open
Abstract
The nerve growth factor (NGF) belongs to the family of neurotrophic factors. Initially discovered as a signaling molecule involved in the survival, protection, differentiation, and proliferation of sympathetic and peripheral sensory neurons, it also participates in the regulation of the immune system and endocrine system. NGF biological activity is due to the binding of two classes of receptors: the tropomyosin-related kinase A (TrkA) and the low-affinity NGF pan-neurotrophin receptor p75. Alcohol Use Disorders (AUD) are one of the most frequent mental disorders in developed countries, characterized by heavy drinking, despite the negative effects of alcohol on brain development and cognitive functions that cause individual’s work, medical, legal, educational, and social life problems. In addition, alcohol consumption during pregnancy disrupts the development of the fetal brain causing a wide range of neurobehavioral outcomes collectively known as fetal alcohol spectrum disorders (FASD). The rationale of this review is to describe crucial findings on the role of NGF in humans and animals, when exposed to prenatal, chronic alcohol consumption, and on binge drinking.
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Affiliation(s)
- Flavio Maria Ceci
- Department of Experimental Medicine, Sapienza University Hospital of Rome, Italy
| | - Giampiero Ferraguti
- Department of Experimental Medicine, Sapienza University Hospital of Rome, Italy
| | - Carla Petrella
- Institute of Biochemistry and Cell Biology, Section of Neurobiology, National Research Council (IBBC-CNR), Rome, Italy
| | - Antonio Greco
- Department of Sense Organs, Sapienza University Hospital of Rome, Italy
| | - Massimo Ralli
- Department of Sense Organs, Sapienza University Hospital of Rome, Italy
| | - Angela Iannitelli
- Department of Biotechnology and Applied Clinical Sciences, University of L'Aquila, Italy
| | - Valentina Carito
- Institute of Biochemistry and Cell Biology, Section of Neurobiology, National Research Council (IBBC-CNR), Rome, Italy
| | - Paola Tirassa
- Institute of Biochemistry and Cell Biology, Section of Neurobiology, National Research Council (IBBC-CNR), Rome, Italy
| | - George N Chaldakov
- Department of Anatomy and Cell Biology, Medical University, Varna, Bulgaria
| | | | - Mauro Ceccanti
- Centro Riferimento Alcologico Regione Lazio, Sapienza University of Rome, Italy
| | - Marco Fiore
- Institute of Biochemistry and Cell Biology, Section of Neurobiology, National Research Council (IBBC-CNR), Rome, Italy
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24
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Lupton MK, Robinson GA, Adam RJ, Rose S, Byrne GJ, Salvado O, Pachana NA, Almeida OP, McAloney K, Gordon SD, Raniga P, Fazlollahi A, Xia Y, Ceslis A, Sonkusare S, Zhang Q, Kholghi M, Karunanithi M, Mosley PE, Lv J, Borne L, Adsett J, Garden N, Fripp J, Martin NG, Guo CC, Breakspear M. A prospective cohort study of prodromal Alzheimer's disease: Prospective Imaging Study of Ageing: Genes, Brain and Behaviour (PISA). NEUROIMAGE-CLINICAL 2020; 29:102527. [PMID: 33341723 PMCID: PMC7750170 DOI: 10.1016/j.nicl.2020.102527] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 11/11/2020] [Accepted: 12/04/2020] [Indexed: 12/20/2022]
Abstract
This prospective cohort study, "Prospective Imaging Study of Ageing: Genes, Brain and Behaviour" (PISA) seeks to characterise the phenotype and natural history of healthy adult Australians at high future risk of Alzheimer's disease (AD). In particular, we are recruiting midlife and older Australians with high and low genetic risk of dementia to discover biological markers of early neuropathology, identify modifiable risk factors, and establish the very earliest phenotypic and neuronal signs of disease onset. PISA utilises genetic prediction to recruit and enrich a prospective cohort and follow them longitudinally. Online surveys and cognitive testing are used to characterise an Australia-wide sample currently totalling over 3800 participants. Participants from a defined at-risk cohort and positive controls (clinical cohort of patients with mild cognitive impairment or early AD) are invited for onsite visits for detailed functional, structural and molecular neuroimaging, lifestyle monitoring, detailed neurocognitive testing, plus blood sample donation. This paper describes recruitment of the PISA cohort, study methodology and baseline demographics.
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Affiliation(s)
| | - Gail A Robinson
- School of Psychology, The University of Queensland, St. Lucia, Brisbane, Australia; Queensland Brain Institute, The University of Queensland, St. Lucia, Brisbane, Australia
| | - Robert J Adam
- QIMR Berghofer Medical Research Institute, Brisbane, Australia; Centre for Clinical Research (UQCCR), The University of Queensland, Brisbane, Australia; Royal Brisbane and Women's Hospital Mental Health Services, University of Queensland, Brisbane, Australia; Faculty of Medicine, University of Queensland, Brisbane, Australia
| | - Stephen Rose
- CSIRO Health and Biosecurity, Australian E-Health Research Centre, Brisbane, Australia
| | - Gerard J Byrne
- Royal Brisbane and Women's Hospital Mental Health Services, University of Queensland, Brisbane, Australia; Faculty of Medicine, University of Queensland, Brisbane, Australia
| | - Olivier Salvado
- CSIRO Health and Biosecurity, Australian E-Health Research Centre, Brisbane, Australia
| | - Nancy A Pachana
- School of Psychology, The University of Queensland, St. Lucia, Brisbane, Australia
| | - Osvaldo P Almeida
- Medical School, University of Western Australia, Perth, Australia; WA Centre for Health and Ageing of the University of Western Australia, Australia
| | - Kerrie McAloney
- QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Scott D Gordon
- QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Parnesh Raniga
- CSIRO Health and Biosecurity, Australian E-Health Research Centre, Brisbane, Australia
| | - Amir Fazlollahi
- CSIRO Health and Biosecurity, Australian E-Health Research Centre, Brisbane, Australia
| | - Ying Xia
- CSIRO Health and Biosecurity, Australian E-Health Research Centre, Brisbane, Australia
| | - Amelia Ceslis
- School of Psychology, The University of Queensland, St. Lucia, Brisbane, Australia
| | | | - Qing Zhang
- CSIRO Health and Biosecurity, Australian E-Health Research Centre, Brisbane, Australia
| | - Mahnoosh Kholghi
- CSIRO Health and Biosecurity, Australian E-Health Research Centre, Brisbane, Australia
| | - Mohan Karunanithi
- CSIRO Health and Biosecurity, Australian E-Health Research Centre, Brisbane, Australia
| | - Philip E Mosley
- QIMR Berghofer Medical Research Institute, Brisbane, Australia; Queensland Brain Institute, The University of Queensland, St. Lucia, Brisbane, Australia; Neurosciences Queensland, Brisbane, Queensland, Australia
| | - Jinglei Lv
- Sydney Imaging & School of Biomedical Engineering, The University of Sydney, Sydney, Australia
| | - Léonie Borne
- The University of Newcastle, Newcastle, Australia
| | - Jessica Adsett
- QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Natalie Garden
- QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Jurgen Fripp
- CSIRO Health and Biosecurity, Australian E-Health Research Centre, Brisbane, Australia
| | | | - Christine C Guo
- QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Michael Breakspear
- QIMR Berghofer Medical Research Institute, Brisbane, Australia; The University of Newcastle, Newcastle, Australia
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25
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Lathen DR, Merrill CB, Rothenfluh A. Flying Together: Drosophila as a Tool to Understand the Genetics of Human Alcoholism. Int J Mol Sci 2020; 21:E6649. [PMID: 32932795 PMCID: PMC7555299 DOI: 10.3390/ijms21186649] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Revised: 09/07/2020] [Accepted: 09/08/2020] [Indexed: 12/14/2022] Open
Abstract
Alcohol use disorder (AUD) exacts an immense toll on individuals, families, and society. Genetic factors determine up to 60% of an individual's risk of developing problematic alcohol habits. Effective AUD prevention and treatment requires knowledge of the genes that predispose people to alcoholism, play a role in alcohol responses, and/or contribute to the development of addiction. As a highly tractable and translatable genetic and behavioral model organism, Drosophila melanogaster has proven valuable to uncover important genes and mechanistic pathways that have obvious orthologs in humans and that help explain the complexities of addiction. Vinegar flies exhibit remarkably strong face and mechanistic validity as a model for AUDs, permitting many advancements in the quest to understand human genetic involvement in this disease. These advancements occur via approaches that essentially fall into one of two categories: (1) discovering candidate genes via human genome-wide association studies (GWAS), transcriptomics on post-mortem tissue from AUD patients, or relevant physiological connections, then using reverse genetics in flies to validate candidate genes' roles and investigate their molecular function in the context of alcohol. (2) Utilizing flies to discover candidate genes through unbiased screens, GWAS, quantitative trait locus analyses, transcriptomics, or single-gene studies, then validating their translational role in human genetic surveys. In this review, we highlight the utility of Drosophila as a model for alcoholism by surveying recent advances in our understanding of human AUDs that resulted from these various approaches. We summarize the genes that are conserved in alcohol-related function between humans and flies. We also provide insight into some advantages and limitations of these approaches. Overall, this review demonstrates how Drosophila have and can be used to answer important genetic questions about alcohol addiction.
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Affiliation(s)
- Daniel R. Lathen
- Department of Psychiatry and Neuroscience Ph.D. Program, University of Utah, Salt Lake City, UT 84108, USA;
| | - Collin B. Merrill
- Molecular Medicine Program, University of Utah, Salt Lake City, UT 84112, USA;
| | - Adrian Rothenfluh
- Department of Psychiatry and Neuroscience Ph.D. Program, University of Utah, Salt Lake City, UT 84108, USA;
- Molecular Medicine Program, University of Utah, Salt Lake City, UT 84112, USA;
- Department of Neurobiology and Anatomy, University of Utah, Salt Lake City, UT 84132, USA
- Department of Human Genetics, University of Utah, Salt Lake City, UT 84112, USA
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Gupta I, Dandavate R, Gupta P, Agrawal V, Kapoor M. Recent advances in genetic studies of alcohol use disorders. CURRENT GENETIC MEDICINE REPORTS 2020; 8:27-34. [PMID: 33344068 PMCID: PMC7748121 DOI: 10.1007/s40142-020-00185-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
PURPOSE OF REVIEW Alcohol use disorder (AUD) is a complex genetic disorder with very high heritability. This polygenic disorder not only results in increased morbidity and mortality, it is also a substantial social and economic burden on families and the nation. For past three decades, several genetic studies were conducted to identify genes and pathways associated with AUD. This review aims to summarize past efforts and recent advances in genetic association studies of AUD and related traits. RECENT FINDINGS Initial genetic association studies achieved a limted success and suffered from low power due to small sample sizes. AUD is a polygenic trait and data from several thousands individuals was required to identify the genetic factors of small effect sizes. The scenario changed recently with technological advances and significant reduction in cost of the genome wide association analyses (GWAS). This enabled researchers to generate genomic data on mega biobanks and cohorts with access to extensive clinical and non-clinical phenotypes. Public access to data from biobanks and collaborative efforts of researchers lead to identification of several novel loci associated with AUDs and related traits. Efforts are now underway to identify the causal variants under the GWAS loci to identify target genes and biological mechanisms underpining AUDs. Many GWAS variants occur in promoter or enhancer regions of the genes and are involved in regulation of gene expression of causal genes. This, large amounts of "omics" data from projects such as "ENCODE", RoadMap and GTEx is also helping researchers to integrate "multi-omics" data to interpret functional significance of GWAS variants. SUMMARY With current review, we aim to present the recent advances in genetic and molecular studies of AUDs. Recent successes in genetic studies of AUDs will definetely motivate researchers and lead to better therapeutic interventions for this complex disorder.
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Affiliation(s)
| | - Rohan Dandavate
- Indian Institute of Science Education and Research, Bhopal, India
| | - Pallavi Gupta
- Indian Institute of Science Education and Research, Bhopal, India
| | - Viplav Agrawal
- Indian Institute of Science Education and Research, Bhopal, India
| | - Manav Kapoor
- Icahn School of Medicine at Mount Sinai, New york, USA
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Vicente M, Jakobsson M, Ebbesen P, Schlebusch CM. Genetic Affinities among Southern Africa Hunter-Gatherers and the Impact of Admixing Farmer and Herder Populations. Mol Biol Evol 2020; 36:1849-1861. [PMID: 31288264 PMCID: PMC6735883 DOI: 10.1093/molbev/msz089] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
Southern African indigenous groups, traditionally hunter-gatherers (San) and herders (Khoekhoe), are commonly referred to as “Khoe-San” populations and have a long history in southern Africa. Their ancestors were largely isolated up until ∼2,000 years ago before the arrival of pastoralists and farmers in southern Africa. Assessing relationships among regional Khoe-San groups has been challenging due to admixture with immigrant populations that obscure past population affinities and gene flow among these autochthonous communities. We re-evaluate a combined genome-wide data set of previously published southern Africa Khoe-San populations in conjunction with novel data from Khoe-San individuals collected in Xade (Central Kalahari Game Reserve, Botswana) prior to their resettlement outside the reserve. After excluding regions in the genome that trace their ancestry to recent migrant groups, the genetic diversity of 20 Khoe-San groups fitted an isolation-by-distance model. Even though isolation-by-distance explained most genetic affinities between the different autochthonous groups, additional signals of contact between Khoe-San groups could be detected. For instance, we found stronger genetic affinities, than what would be explained by isolation-by-distance gene flow, between the two geographically separated Khoe-San groups, who speak branches of the Kx’a-language family (ǂHoan and Ju). We also scanned the genome-wide data for signals of adaptive gene flow from farmers/herders into Khoe-San groups and identified a number of genomic regions potentially introduced by the arrival of the new groups. This study provides a comprehensive picture of affinities among Khoe-San groups, prior to the arrival of recent migrants, and found that these affinities are primarily determined by the geographic landscape.
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Affiliation(s)
- Mário Vicente
- Human Evolution, Department of Organismal Biology, Uppsala University, Uppsala, Sweden
| | - Mattias Jakobsson
- Human Evolution, Department of Organismal Biology, Uppsala University, Uppsala, Sweden.,Palaeo-Research Institute, University of Johannesburg, Auckland Park, South Africa.,SciLifeLab, Uppsala, Sweden
| | - Peter Ebbesen
- Department of Health Science and Technology, University of Aalborg, Aalborg, Denmark
| | - Carina M Schlebusch
- Human Evolution, Department of Organismal Biology, Uppsala University, Uppsala, Sweden.,Palaeo-Research Institute, University of Johannesburg, Auckland Park, South Africa.,SciLifeLab, Uppsala, Sweden
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Nieto SJ, Grodin EN, Ray LA. On the path towards personalized medicine: Implications of pharmacogenetic studies of alcohol use disorder medications. EXPERT REVIEW OF PRECISION MEDICINE AND DRUG DEVELOPMENT 2020; 5:43-54. [PMID: 34291172 DOI: 10.1080/23808993.2020.1724510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
Introduction The heritability of alcohol use disorder (AUD) is estimated to be ~50%; however, the genetic basis of the disease is still poorly understood. The genetic variants identified thus far only explain a small percentage of AUD phenotypic variability. While genome-wide association studies (GWAS) are impacted by technical and methodological limitations, genetic variants that have been identified independently of GWAS findings can moderate the efficacy of AUD medications. Areas Covered This review discusses findings from clinical pharmacogenetic studies of AUD medications. While the pharmacogenetic studies reviewed involve several genetic variants in the major neurotransmitter systems, genetic loci in the opioid system have garnered the most attention. Expert Opinion The clinical utility of pharmacogenetics in AUD populations is uncertain at this time. There are several ongoing prospective clinical trials that will enhance knowledge regarding the applicability of pharmacogenetics in clinical populations. We recommend that future work in this area consider reverse translating from genotype to phenotype, mapping genes to stages of the addiction cycle, mapping genes to neural circuits, and harnessing large population-based cohorts.
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Affiliation(s)
- Steven J Nieto
- University of California Los Angeles, Department of Psychology, Los Angeles, CA, USA
| | - Erica N Grodin
- University of California Los Angeles, Department of Psychology, Los Angeles, CA, USA
| | - Lara A Ray
- University of California Los Angeles, Department of Psychology, Los Angeles, CA, USA.,University of California, Los Angeles, Department of Psychiatry and Biobehavioral Sciences, Los Angeles, CA, USA.,University of California Los Angeles, Brain Research Institute, Los Angeles, CA, USA
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29
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Chang LH, Whitfield JB, Liu M, Medland SE, Hickie IB, Martin NG, Verhulst B, Heath AC, Madden PA, Statham DJ, Gillespie NA. Associations between polygenic risk for tobacco and alcohol use and liability to tobacco and alcohol use, and psychiatric disorders in an independent sample of 13,999 Australian adults. Drug Alcohol Depend 2019; 205:107704. [PMID: 31731259 DOI: 10.1016/j.drugalcdep.2019.107704] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/27/2019] [Revised: 09/18/2019] [Accepted: 10/21/2019] [Indexed: 12/31/2022]
Abstract
BACKGROUND Substance use, substance use disorders (SUDs), and psychiatric disorders commonly co-occur. Genetic risk common to these complex traits is an important explanation; however, little is known about how polygenic risk for tobacco or alcohol use overlaps the genetic risk for the comorbid SUDs and psychiatric disorders. METHODS We constructed polygenic risk scores (PRSs) using GWAS meta-analysis summary statistics from a large discovery sample, GWAS & Sequencing Consortium of Alcohol and Nicotine use (GSCAN), for smoking initiation (SI; N = 631,564), age of initiating regular smoking (AI; N = 258,251), cigarettes per day (CPD; N = 258,999), smoking cessation (SC; N = 312,273), and drinks per week (DPW; N = 527,402). We then estimated the fixed effect of these PRSs on the liability to 15 phenotypes related to tobacco and alcohol use, substance use disorders, and psychiatric disorders in an independent target sample of Australian adults. RESULTS After adjusting for multiple testing, 10 of 75 combinations of discovery and target phenotypes remained significant. PRS-SI (R2 range: 1.98%-5.09 %) was positively associated with SI, DPW, and with DSM-IV and FTND nicotine dependence, and conduct disorder. PRS-AI (R2: 3.91 %) negatively associated with DPW. PRS-CPD (R2: 1.56 %-1.77 %) positively associated with DSM-IV nicotine dependence and conduct disorder. PRS-DPW (R2: 3.39 %-6.26 %) positively associated with only DPW. The variation of DPW was significantly influenced by sex*PRS-SI, sex*PRS-AI and sex*PRS-DPW. Such interaction effect was not detected in the other 14 phenotypes. CONCLUSIONS Polygenic risks associated with tobacco use are also associated with liability to alcohol consumption, nicotine dependence, and conduct disorder.
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Affiliation(s)
- Lun-Hsien Chang
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, 300 Herston Road, Herston QLD 4006, Australia; Faculty of Medicine, the University of Queensland, 20 Weightman St, Herston QLD 4006, Australia.
| | - John B Whitfield
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, 300 Herston Road, Herston QLD 4006, Australia.
| | - Mengzhen Liu
- Department of Psychology, University of Minnesota Twin Cities, 75 E River Rd, Minneapolis, MN 55455, USA.
| | - Sarah E Medland
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, 300 Herston Road, Herston QLD 4006, Australia.
| | - Ian B Hickie
- Brain and Mind Centre, University of Sydney, 94 Mallett St, Camperdown NSW 2050, USA.
| | - Nicholas G Martin
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, 300 Herston Road, Herston QLD 4006, Australia.
| | - Brad Verhulst
- Department of psychology, Michigan State University, 316 Physics Road #262, East Lansing, MI 48824, USA.
| | - Andrew C Heath
- Department of Psychiatry, Washington University School of Medicine, 660 S Euclid Ave, St. Louis, MO 63110, USA.
| | - Pamela A Madden
- Department of Psychiatry, Washington University School of Medicine, 660 S Euclid Ave, St. Louis, MO 63110, USA.
| | - Dixie J Statham
- School of Health and Life Sciences, Federation University, Federation University Australia, PO Box 663, Ballarat, VIC 3353, Australia.
| | - Nathan A Gillespie
- Virginia Institute for Psychiatric and Behavioural Genetics, Virginia Commonwealth University, Richmond, VA 23298, USA.
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Zhang Z, Luo D, Zhong X, Choi JH, Ma Y, Wang S, Mahrt E, Guo W, Stawiski EW, Modrusan Z, Seshagiri S, Kapur P, Hon GC, Brugarolas J, Wang T. SCINA: A Semi-Supervised Subtyping Algorithm of Single Cells and Bulk Samples. Genes (Basel) 2019; 10:E531. [PMID: 31336988 PMCID: PMC6678337 DOI: 10.3390/genes10070531] [Citation(s) in RCA: 131] [Impact Index Per Article: 26.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2019] [Revised: 07/05/2019] [Accepted: 07/08/2019] [Indexed: 12/30/2022] Open
Abstract
Advances in single-cell RNA sequencing (scRNA-Seq) have allowed for comprehensive analyses of single cell data. However, current analyses of scRNA-Seq data usually start from unsupervised clustering or visualization. These methods ignore prior knowledge of transcriptomes and the probable structures of the data. Moreover, cell identification heavily relies on subjective and possibly inaccurate human inspection afterwards. To address these analytical challenges, we developed SCINA (Semi-supervised Category Identification and Assignment), a semi-supervised model that exploits previously established gene signatures using an expectation-maximization (EM) algorithm. SCINA is applicable to scRNA-Seq and flow cytometry/CyTOF data, as well as other data of similar format. We applied SCINA to a wide range of datasets, and showed its accuracy, stability and efficiency, which exceeded most popular unsupervised approaches. SCINA discovered an intermediate stage of oligodendrocytes from mouse brain scRNA-Seq data. SCINA also detected immune cell population changes in cytometry data in a genetically-engineered mouse model. Furthermore, SCINA performed well with bulk gene expression data. Specifically, we identified a new kidney tumor clade with similarity to FH-deficient tumors (FHD), which we refer to as FHD-like tumors (FHDL). Overall, SCINA provides both methodological advances and biological insights from perspectives different from traditional analytical methods.
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Affiliation(s)
- Ze Zhang
- Quantitative Biomedical Research Center, Department of Population and Data Sciences, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Danni Luo
- Bioinformatics Core Facility, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Xue Zhong
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Jin Huk Choi
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Yuanqing Ma
- Kidney Cancer Program, Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, TX 75390, USA
| | - Stacy Wang
- Quantitative Biomedical Research Center, Department of Population and Data Sciences, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Elena Mahrt
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Wei Guo
- BioHPC, University of Texas Southwestern Medical Center, Dallas, Texas, TX 75390, USA
| | - Eric W Stawiski
- Molecular Biology Department, Genentech, Inc., South San Francisco, CA 94080, USA
- Bioinformatics and Computational Biology Department, Genentech, Inc., South San Francisco, CA 94080, USA
| | - Zora Modrusan
- Molecular Biology Department, Genentech, Inc., South San Francisco, CA 94080, USA
| | - Somasekar Seshagiri
- Molecular Biology Department, Genentech, Inc., South San Francisco, CA 94080, USA
| | - Payal Kapur
- Kidney Cancer Program, Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Gary C Hon
- Laboratory of Regulatory Genomics, Cecil H. and Ida Green Center for Reproductive Biology Sciences, Division of Basic Reproductive Biology Research, Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - James Brugarolas
- Kidney Cancer Program, Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, TX 75390, USA
| | - Tao Wang
- Quantitative Biomedical Research Center, Department of Population and Data Sciences, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
- Kidney Cancer Program, Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
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31
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Lai D, Wetherill L, Bertelsen S, Carey CE, Kamarajan C, Kapoor M, Meyers JL, Anokhin AP, Bennett DA, Bucholz KK, Chang KK, De Jager PL, Dick DM, Hesselbrock V, Kramer J, Kuperman S, Nurnberger JI, Raj T, Schuckit M, Scott DM, Taylor RE, Tischfield J, Hariri AR, Edenberg HJ, Agrawal A, Bogdan R, Porjesz B, Goate AM, Foroud T. Genome-wide association studies of alcohol dependence, DSM-IV criterion count and individual criteria. GENES, BRAIN, AND BEHAVIOR 2019; 18:e12579. [PMID: 31090166 PMCID: PMC6612573 DOI: 10.1111/gbb.12579] [Citation(s) in RCA: 49] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Revised: 04/19/2019] [Accepted: 05/11/2019] [Indexed: 01/04/2023]
Abstract
Genome-wide association studies (GWAS) of alcohol dependence (AD) have reliably identified variation within alcohol metabolizing genes (eg, ADH1B) but have inconsistently located other signals, which may be partially attributable to symptom heterogeneity underlying the disorder. We conducted GWAS of DSM-IV AD (primary analysis), DSM-IV AD criterion count (secondary analysis), and individual dependence criteria (tertiary analysis) among 7418 (1121 families) European American (EA) individuals from the Collaborative Study on the Genetics of Alcoholism (COGA). Trans-ancestral meta-analyses combined these results with data from 3175 (585 families) African-American (AA) individuals from COGA. In the EA GWAS, three loci were genome-wide significant: rs1229984 in ADH1B for AD criterion count (P = 4.16E-11) and Desire to cut drinking (P = 1.21E-11); rs188227250 (chromosome 8, Drinking more than intended, P = 6.72E-09); rs1912461 (chromosome 15, Time spent drinking, P = 1.77E-08). In the trans-ancestral meta-analysis, rs1229984 was associated with multiple phenotypes and two additional loci were genome-wide significant: rs61826952 (chromosome 1, DSM-IV AD, P = 8.42E-11); rs7597960 (chromosome 2, Time spent drinking, P = 1.22E-08). Associations with rs1229984 and rs18822750 were replicated in independent datasets. Polygenic risk scores derived from the EA GWAS of AD predicted AD in two EA datasets (P < .01; 0.61%-1.82% of variance). Identified novel variants (ie, rs1912461, rs61826952) were associated with differential central evoked theta power (loss - gain; P = .0037) and reward-related ventral striatum reactivity (P = .008), respectively. This study suggests that studying individual criteria may unveil new insights into the genetic etiology of AD liability.
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Affiliation(s)
- Dongbing Lai
- Department of Medical and Molecular Genetics, Indiana
University School of Medicine, Indianapolis, IN
| | - Leah Wetherill
- Department of Medical and Molecular Genetics, Indiana
University School of Medicine, Indianapolis, IN
| | - Sarah Bertelsen
- Department of Neuroscience, Icahn School of Medicine at Mt.
Sinai, New York, NY
| | - Caitlin E. Carey
- BRAIN Lab, Department of Psychological and Brain Sciences,
Washington University School of Medicine, St. Louis, MO
| | - Chella Kamarajan
- Henri Begleiter Neurodynamics Lab, Department of
Psychiatry, State University of New York, Downstate Medical Center, Brooklyn,
NY
| | - Manav Kapoor
- Department of Neuroscience, Icahn School of Medicine at Mt.
Sinai, New York, NY
| | - Jacquelyn L. Meyers
- Henri Begleiter Neurodynamics Lab, Department of
Psychiatry, State University of New York, Downstate Medical Center, Brooklyn,
NY
| | - Andrey P. Anokhin
- Department of Psychiatry, Washington University School of
Medicine, St. Louis, MO
| | - David A. Bennett
- Rush Alzheimer's Disease Center, Rush University
Medical Center, Chicago, IL
| | - Kathleen K. Bucholz
- Department of Psychiatry, Washington University School of
Medicine, St. Louis, MO
| | - Katharine K. Chang
- BRAIN Lab, Department of Psychological and Brain Sciences,
Washington University School of Medicine, St. Louis, MO
| | - Philip L. De Jager
- Departments of Neurology and Psychiatry, Brigham and
Women's Hospital, Boston, MA
| | - Danielle M. Dick
- Department of Psychology, Virginia Commonwealth University,
Richmond, VA
| | | | - John Kramer
- Department of Psychiatry, Roy Carver College of Medicine,
University of Iowa, Iowa City, IA
| | - Samuel Kuperman
- Department of Psychiatry, Roy Carver College of Medicine,
University of Iowa, Iowa City, IA
| | - John I. Nurnberger
- Department of Medical and Molecular Genetics, Indiana
University School of Medicine, Indianapolis, IN
- Department of Psychiatry, Indiana University School of
Medicine, Indianapolis, IN
| | - Towfique Raj
- Department of Neuroscience, Icahn School of Medicine at Mt.
Sinai, New York, NY
| | - Marc Schuckit
- Department of Psychiatry, University of California, San
Diego Medical School, San Diego, CA
| | - Denise M. Scott
- Departments of Pediatrics and Human Genetics, Howard
University, Washington, DC
| | | | | | - Ahmad R. Hariri
- Laboratory of NeuroGenetics, Department of Psychology and
Neuroscience, Duke University, Durham, NC, USA
| | - Howard J. Edenberg
- Department of Medical and Molecular Genetics, Indiana
University School of Medicine, Indianapolis, IN
- Department of Biochemistry and Molecular Biology, Indiana
University School of Medicine, Indianapolis, IN
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of
Medicine, St. Louis, MO
| | - Ryan Bogdan
- BRAIN Lab, Department of Psychological and Brain Sciences,
Washington University School of Medicine, St. Louis, MO
| | - Bernice Porjesz
- Henri Begleiter Neurodynamics Lab, Department of
Psychiatry, State University of New York, Downstate Medical Center, Brooklyn,
NY
| | - Alison M. Goate
- Department of Neuroscience, Icahn School of Medicine at Mt.
Sinai, New York, NY
| | - Tatiana Foroud
- Department of Medical and Molecular Genetics, Indiana
University School of Medicine, Indianapolis, IN
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Rompala GR, Homanics GE. Intergenerational Effects of Alcohol: A Review of Paternal Preconception Ethanol Exposure Studies and Epigenetic Mechanisms in the Male Germline. Alcohol Clin Exp Res 2019; 43:1032-1045. [PMID: 30908630 PMCID: PMC6551262 DOI: 10.1111/acer.14029] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2018] [Accepted: 03/13/2019] [Indexed: 12/11/2022]
Abstract
While alcohol use disorder (AUD) is a highly heritable psychiatric disease, efforts to elucidate that heritability by examining genetic variation (e.g., single nucleotide polymorphisms) have been insufficient to fully account for familial AUD risk. Perhaps not coincidently, there has been a burgeoning interest in novel nongenomic mechanisms of inheritance (i.e., epigenetics) that are shaped in the male or female germ cells by significant lifetime experiences such as exposure to chronic stress, malnutrition, or drugs of abuse. While many epidemiological and preclinical studies have long pointed to a role for the parental preconception environment in offspring behavior, over the last decade many studies have implicated a causal relationship between the environmentally sensitive sperm epigenome and intergenerational phenotypes. This critical review will detail the heritable effects of alcohol and the potential role for epigenetics.
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Affiliation(s)
- Gregory R Rompala
- Center for Neuroscience, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Gregg E Homanics
- Center for Neuroscience, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
- Department of Pharmacology & Chemical Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
- Department of Anesthesiology and Perioperative Medicine, University of Pittsburgh School Medicine, Pittsburgh, Pennsylvania
- Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
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33
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Cornelis MC. Genetic determinants of beverage consumption: Implications for nutrition and health. ADVANCES IN FOOD AND NUTRITION RESEARCH 2019; 89:1-52. [PMID: 31351524 PMCID: PMC7047661 DOI: 10.1016/bs.afnr.2019.03.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Beverages make important contributions to nutritional intake and their role in health has received much attention. This review focuses on the genetic determinants of common beverage consumption and how research in this field is contributing insight to what and how much we consume and why this genetic knowledge matters from a research and public health perspective. The earliest efforts in gene-beverage behavior mapping involved genetic linkage and candidate gene analysis but these approaches have been largely replaced by genome-wide association studies (GWAS). GWAS have identified biologically plausible loci underlying alcohol and coffee drinking behavior. No GWAS has identified variants specifically associated with consumption of tea, juice, soda, wine, beer, milk or any other common beverage. Thus far, GWAS highlight an important behavior-reward component (as opposed to taste) to beverage consumption which may serve as a potential barrier to dietary interventions. Loci identified have been used in Mendelian randomization and gene×beverage interaction analysis of disease but results have been mixed. This research is necessary as it informs the clinical relevance of SNP-beverage associations and thus genotype-based personalized nutrition, which is gaining interest in the commercial and public health sectors.
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Affiliation(s)
- Marilyn C Cornelis
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, United States.
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Hardwick SA, Bassett SD, Kaczorowski D, Blackburn J, Barton K, Bartonicek N, Carswell SL, Tilgner HU, Loy C, Halliday G, Mercer TR, Smith MA, Mattick JS. Targeted, High-Resolution RNA Sequencing of Non-coding Genomic Regions Associated With Neuropsychiatric Functions. Front Genet 2019; 10:309. [PMID: 31031799 PMCID: PMC6473190 DOI: 10.3389/fgene.2019.00309] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2019] [Accepted: 03/21/2019] [Indexed: 12/18/2022] Open
Abstract
The human brain is one of the last frontiers of biomedical research. Genome-wide association studies (GWAS) have succeeded in identifying thousands of haplotype blocks associated with a range of neuropsychiatric traits, including disorders such as schizophrenia, Alzheimer's and Parkinson's disease. However, the majority of single nucleotide polymorphisms (SNPs) that mark these haplotype blocks fall within non-coding regions of the genome, hindering their functional validation. While some of these GWAS loci may contain cis-acting regulatory DNA elements such as enhancers, we hypothesized that many are also transcribed into non-coding RNAs that are missing from publicly available transcriptome annotations. Here, we use targeted RNA capture ('RNA CaptureSeq') in combination with nanopore long-read cDNA sequencing to transcriptionally profile 1,023 haplotype blocks across the genome containing non-coding GWAS SNPs associated with neuropsychiatric traits, using post-mortem human brain tissue from three neurologically healthy donors. We find that the majority (62%) of targeted haplotype blocks, including 13% of intergenic blocks, are transcribed into novel, multi-exonic RNAs, most of which are not yet recorded in GENCODE annotations. We validated our findings with short-read RNA-seq, providing orthogonal confirmation of novel splice junctions and enabling a quantitative assessment of the long-read assemblies. Many novel transcripts are supported by independent evidence of transcription including cap analysis of gene expression (CAGE) data and epigenetic marks, and some show signs of potential functional roles. We present these transcriptomes as a preliminary atlas of non-coding transcription in human brain that can be used to connect neurological phenotypes with gene expression.
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Affiliation(s)
- Simon A. Hardwick
- Genomics and Epigenetics Division, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
- Faculty of Medicine, University of New South Wales Sydney, Kensington, NSW, Australia
- Brain and Mind Research Institute and Center for Neurogenetics, Weill Cornell Medicine, New York, NY, United States
| | - Samuel D. Bassett
- Genomics and Epigenetics Division, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
- Faculty of Medicine, University of New South Wales Sydney, Kensington, NSW, Australia
| | - Dominik Kaczorowski
- Genomics and Epigenetics Division, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
| | - James Blackburn
- Genomics and Epigenetics Division, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
- Faculty of Medicine, University of New South Wales Sydney, Kensington, NSW, Australia
| | - Kirston Barton
- Genomics and Epigenetics Division, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
| | - Nenad Bartonicek
- Genomics and Epigenetics Division, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
- Faculty of Medicine, University of New South Wales Sydney, Kensington, NSW, Australia
| | - Shaun L. Carswell
- Genomics and Epigenetics Division, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
| | - Hagen U. Tilgner
- Brain and Mind Research Institute and Center for Neurogenetics, Weill Cornell Medicine, New York, NY, United States
| | - Clement Loy
- Genomics and Epigenetics Division, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
- Brain and Mind Centre, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW, Australia
| | - Glenda Halliday
- Brain and Mind Centre, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW, Australia
| | - Tim R. Mercer
- Genomics and Epigenetics Division, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
- Faculty of Medicine, University of New South Wales Sydney, Kensington, NSW, Australia
- Altius Institute for Biomedical Sciences, Seattle, WA, United States
| | - Martin A. Smith
- Genomics and Epigenetics Division, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
- Faculty of Medicine, University of New South Wales Sydney, Kensington, NSW, Australia
| | - John S. Mattick
- Genomics and Epigenetics Division, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
- Faculty of Medicine, University of New South Wales Sydney, Kensington, NSW, Australia
- Green Templeton College, Oxford, United Kingdom
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Chang LH, Couvy-Duchesne B, Liu M, Medland SE, Verhulst B, Benotsch EG, Hickie IB, Martin NG, Gillespie NA. Association between polygenic risk for tobacco or alcohol consumption and liability to licit and illicit substance use in young Australian adults. Drug Alcohol Depend 2019; 197:271-279. [PMID: 30875648 PMCID: PMC11100300 DOI: 10.1016/j.drugalcdep.2019.01.015] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2018] [Revised: 12/25/2018] [Accepted: 01/19/2019] [Indexed: 11/21/2022]
Abstract
BACKGROUND Co-morbid substance use is very common. Despite a historical focus using genetic epidemiology to investigate comorbid substance use and misuse, few studies have examined substance-substance associations using polygenic risk score (PRS) methods. METHODS Using summary statistics from the largest substance use GWAS to date (258,797- 632,802 subjects), GWAS and Sequencing Consortium of Alcohol and Nicotine use (GSCAN), we constructed PRSs for smoking initiation (PRS-SI), age of initiation of regular smoking (PRS-AI), cigarettes per day (PRS-CPD), smoking cessation (PRS-SC), and drinks per week (PRS-DPW). We then estimated the fixed effect of individual PRSs on 22 lifetime substance use and substance use disorder phenotypes collected in an independent sample of 2463 young Australian adults using genetic restricted maximal likelihood (GREML) in Genome-wide Complex Trait Analysis (GCTA), separately in females, males and both sexes together. RESULTS After accounting for multiple testing, PRS-SI significantly explained variation in the risk of cocaine (0.67%), amphetamine (1.54%), hallucinogens (0.72%), ecstasy (1.66%) and cannabis initiation (0.97%), as well as DSM-5 alcohol use disorder (0.72%). PRS-DPW explained 0.75%, 0.59% and 0.90% of the variation of cocaine, amphetamine and ecstasy initiation respectively. None of the 22 phenotypes including emergent classes of substance use were significantly predicted by PRS-AI, PRS-CPD, and PRS-SC. CONCLUSIONS To our knowledge, this is the first study to report significant genetic overlap between the polygenic risks for smoking initiation and alcohol consumption and the risk of initiating major classes of illicit substances. PRSs constructed from large discovery GWASs allows the detection of novel genetic associations.
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Affiliation(s)
- Lun-Hsien Chang
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia; Faculty of Medicine, the University of Queensland, Brisbane, Australia.
| | - Baptiste Couvy-Duchesne
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia; Institute for Molecular Bioscience, the University of Queensland, Brisbane, Australia
| | - Mengzhen Liu
- Department of Psychology, University of Minnesota Twin Cities, Minneapolis, MN, USA
| | - Sarah E Medland
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Brad Verhulst
- Department of Psychology, Michigan State University, East Lansing, MI, USA
| | - Eric G Benotsch
- Psychology Department, Virginia Commonwealth University, VA, USA
| | - Ian B Hickie
- Brain and Mind Centre, University of Sydney, Sydney, New South Wales, Australia
| | - Nicholas G Martin
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Nathan A Gillespie
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia; Department of Psychology, Michigan State University, East Lansing, MI, USA
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36
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Whitfield JB, Zhu G, Madden PAF, Montgomery GW, Heath AC, Martin NG. Biomarker and Genomic Risk Factors for Liver Function Test Abnormality in Hazardous Drinkers. Alcohol Clin Exp Res 2019; 43:473-482. [PMID: 30589442 PMCID: PMC6445646 DOI: 10.1111/acer.13949] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2018] [Accepted: 12/21/2018] [Indexed: 12/15/2022]
Abstract
BACKGROUND Alcohol dependence and long-term excessive alcohol use may cause liver damage, but only some patients develop cirrhosis. Similarly, high alcohol intake without evident liver disease often but not always produces abnormal enzymatic liver function tests (LFTs), particularly gamma-glutamyl transferase (GGT). We postulate that the factors predisposing to cirrhosis in alcoholics and to liver enzyme abnormality in drinkers are similar, and that biochemical LFTs could therefore be useful as markers of risk of alcoholic liver disease in excessive drinkers. METHODS Data from participants in twin and twin-family studies on alcohol use and dependence were used to identify 1,003 people who had reported excessive alcohol intake (28 drinks or more per week). A total of 962 of these provided blood for biochemical tests at the same time. Body mass index (BMI) and biomarkers of metabolic syndrome, inflammation, and iron stores were used in logistic regression with abnormality in serum GGT, alanine aminotransferase (ALT), or aspartate aminotransferase (AST) as outcomes. We conducted genome-wide association analyses for GGT, ALT, and AST separately in the group reporting excessive alcohol intake (N = 951) and a low-intake group reporting 14 drinks or fewer per week (N = 8,716), and compared results. RESULTS Abnormal GGT and ALT among excessive drinkers were associated with higher BMI, triglycerides, insulin, uric acid, C-reactive protein, ferritin, and transferrin saturation; and with lower high-density-lipoprotein cholesterol. Abnormal AST was associated with triglycerides, ferritin, and transferrin saturation. ALT was significantly associated with variants at reported genetic loci for alcoholic liver disease (PNPLA3, rs738409, p = 0.0076; TM6SF2, rs10401969, p = 0.0076; HSD17B13, rs10433879, p = 0.0024). CONCLUSIONS Known risk factors for alcoholic cirrhosis including obesity and markers of metabolic syndrome, iron overload and inflammation are associated with liver enzyme abnormality in excessive drinkers.
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Affiliation(s)
- John B Whitfield
- QIMR Berghofer Medical Research Institute , Brisbane, Queensland
| | - Gu Zhu
- QIMR Berghofer Medical Research Institute , Brisbane, Queensland
| | - Pamela A F Madden
- Department of Psychiatry , Washington University School of Medicine, St. Louis, Missouri
| | - Grant W Montgomery
- Institute for Molecular Bioscience , The University of Queensland, St. Lucia, Queensland
| | - Andrew C Heath
- Department of Psychiatry , Washington University School of Medicine, St. Louis, Missouri
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Abstract
One of the most fruitful resources for systems genetic studies of nonhuman mammals is a panel of inbred strains that exhibits significant genetic diversity between strains but genetic stability (isogenicity) within strains. These characteristics allow for fine mapping of complex phenotypes (QTLs) and provide statistical power to identify loci which contribute nominally to the phenotype. This type of resource also allows the planning and performance of investigations using the same genetic backgrounds over several generations of the test animals. Often, rats are preferred over mice for physiologic and behavioral studies because of their larger size and more distinguishable anatomy (particularly for their central nervous system). The Hybrid Rat Diversity Panel (HRDP) is a panel of inbred rat strains, which combines two recombinant inbred panels (the HXB/BXH, 30 strains; the LEXF/FXLE, 34 strains and 35 more strains of inbred rats which were selected for genetic diversity, based on their fully sequenced genomes and/or thorough genotyping). The genetic diversity and statistical power of this panel for mapping studies rivals or surpasses currently available panels in mouse. The genetic stability of this panel makes it particularly suitable for collection of high-throughput omics data as relevant technology becomes available for engaging in truly integrative systems biology. The PhenoGen website ( http://phenogen.org ) is the repository for the initial transcriptome data, making the raw data, the processed data, and the analysis results, e.g., organ-specific protein coding and noncoding transcripts, isoform analysis, expression quantitative trait loci, and co-expression networks, available to the research public. The data sets and tools being developed will complement current efforts to analyze the human transcriptome and its genetic controls (the Genotype-Tissue Expression Project (GTEx)) and allow for dissection of genetic networks that predispose to particular phenotypes and gene-by-environment interactions that are difficult or even impossible to study in humans. The HRDP is an essential population for exploring truly integrative systems genetics.
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Farris SP, Riley BP, Williams RW, Mulligan MK, Miles MF, Lopez MF, Hitzemann R, Iancu OD, Colville A, Walter NAR, Darakjian P, Oberbeck DL, Daunais JB, Zheng CL, Searles RP, McWeeney SK, Grant KA, Mayfield RD. Cross-species molecular dissection across alcohol behavioral domains. Alcohol 2018; 72:19-31. [PMID: 30213503 PMCID: PMC6309876 DOI: 10.1016/j.alcohol.2017.11.036] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2017] [Revised: 11/17/2017] [Accepted: 11/28/2017] [Indexed: 12/14/2022]
Abstract
This review summarizes the proceedings of a symposium presented at the "Alcoholism and Stress: A Framework for Future Treatment Strategies" conference held in Volterra, Italy on May 9-12, 2017. Psychiatric diseases, including alcohol-use disorders (AUDs), are influenced through complex interactions of genes, neurobiological pathways, and environmental influences. A better understanding of the common neurobiological mechanisms underlying an AUD necessitates an integrative approach, involving a systematic assessment of diverse species and phenotype measures. As part of the World Congress on Stress and Alcoholism, this symposium provided a detailed account of current strategies to identify mechanisms underlying the development and progression of AUDs. Dr. Sean Farris discussed the integration and organization of transcriptome and postmortem human brain data to identify brain regional- and cell type-specific differences related to excessive alcohol consumption that are conserved across species. Dr. Brien Riley presented the results of a genome-wide association study of DSM-IV alcohol dependence; although replication of genetic associations with alcohol phenotypes in humans remains challenging, model organism studies show that COL6A3, KLF12, and RYR3 affect behavioral responses to ethanol, and provide substantial evidence for their role in human alcohol-related traits. Dr. Rob Williams expanded upon the systematic characterization of extensive genetic-genomic resources for quantifying and clarifying phenotypes across species that are relevant to precision medicine in human disease. The symposium concluded with Dr. Robert Hitzemann's description of transcriptome studies in a mouse model selectively bred for high alcohol ("binge-like") consumption and a non-human primate model of long-term alcohol consumption. Together, the different components of this session provided an overview of systems-based approaches that are pioneering the experimental prioritization and validation of novel genes and gene networks linked with a range of behavioral phenotypes associated with stress and AUDs.
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Affiliation(s)
- Sean P Farris
- University of Texas at Austin, Austin, TX, United States
| | - Brien P Riley
- Virginia Commonwealth University, Richmond, VA, United States
| | - Robert W Williams
- University of Tennessee Health Science Center, Memphis, TN, United States
| | - Megan K Mulligan
- University of Tennessee Health Science Center, Memphis, TN, United States
| | - Michael F Miles
- University of Tennessee Health Science Center, Memphis, TN, United States
| | - Marcelo F Lopez
- University of Tennessee Health Science Center, Memphis, TN, United States
| | - Robert Hitzemann
- Oregon Health and Science University, Portland, OR, United States
| | - Ovidiu D Iancu
- Oregon Health and Science University, Portland, OR, United States
| | | | | | | | | | - James B Daunais
- Wake Forest School of Medicine, Winston-Salem, NC, United States
| | | | - Robert P Searles
- Oregon Health and Science University, Portland, OR, United States
| | | | - Kathleen A Grant
- Oregon Health and Science University, Portland, OR, United States
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Almli LM, Lori A, Meyers JL, Shin J, Fani N, Maihofer AX, Nievergelt CM, Smith AK, Mercer KB, Kerley K, Leveille JM, Feng H, Abu‐Amara D, Flory JD, Yehuda R, Marmar CR, Baker DG, Bradley B, Koenen KC, Conneely KN, Ressler KJ. Problematic alcohol use associates with sodium channel and clathrin linker 1 (SCLT1) in trauma-exposed populations. Addict Biol 2018; 23:1145-1159. [PMID: 29082582 DOI: 10.1111/adb.12569] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2016] [Revised: 08/05/2017] [Accepted: 08/29/2017] [Indexed: 12/15/2022]
Abstract
Excessive alcohol use is extremely prevalent in the United States, particularly among trauma-exposed individuals. While several studies have examined genetic influences on alcohol use and related problems, this has not been studied in the context of trauma-exposed populations. We report results from a genome-wide association study of alcohol consumption and associated problems as measured by the alcohol use disorders identification test (AUDIT) in a trauma-exposed cohort. Results indicate a genome-wide significant association between total AUDIT score and rs1433375 [N = 1036, P = 2.61 × 10-8 (dominant model), P = 7.76 × 10-8 (additive model)], an intergenic single-nucleotide polymorphism located 323 kb upstream of the sodium channel and clathrin linker 1 (SCLT1) at 4q28. rs1433375 was also significant in a meta-analysis of two similar, but independent, cohorts (N = 1394, P = 0.0004), the Marine Resiliency Study and Systems Biology PTSD Biomarkers Consortium. Functional analysis indicated that rs1433375 was associated with SCLT1 gene expression and cortical-cerebellar functional connectivity measured via resting state functional magnetic resonance imaging. Together, findings suggest a role for sodium channel regulation and cerebellar functioning in alcohol use behavior. Identifying mechanisms underlying risk for problematic alcohol use in trauma-exposed populations is critical for future treatment and prevention efforts.
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Affiliation(s)
- Lynn M. Almli
- Department of Psychiatry and Behavioral Sciences Emory University Atlanta GA USA
| | - Adriana Lori
- Department of Psychiatry and Behavioral Sciences Emory University Atlanta GA USA
| | - Jacquelyn L. Meyers
- Department of Psychiatry State University of New York Downstate Medical Center Brooklyn NY USA
| | - Jaemin Shin
- Center for Advanced Brain Imaging Georgia State University/Georgia Institute of Technology Atlanta GA USA
| | - Negar Fani
- Department of Psychiatry and Behavioral Sciences Emory University Atlanta GA USA
| | - Adam X. Maihofer
- Department of Psychiatry University of California San Diego San Diego CA USA
- Veterans Affairs Center of Excellence for Stress and Mental Health San Diego USA
| | - Caroline M. Nievergelt
- Department of Psychiatry University of California San Diego San Diego CA USA
- Veterans Affairs Center of Excellence for Stress and Mental Health San Diego USA
| | - Alicia K. Smith
- Department of Psychiatry and Behavioral Sciences Emory University Atlanta GA USA
- Department of Gynecology and Obstetrics Emory University Atlanta GA USA
| | | | - Kimberly Kerley
- Department of Psychiatry and Behavioral Sciences Emory University Atlanta GA USA
| | - Jennifer M. Leveille
- Department of Psychiatry and Behavioral Sciences Emory University Atlanta GA USA
| | - Hao Feng
- Department of Human Genetics Emory University Atlanta GA USA
| | - Duna Abu‐Amara
- Steven and Alexandra Cohen Veterans Center for Posttraumatic Stress and Traumatic Brain Injury Department of Psychiatry, New York University New York NY USA
| | - Janine D. Flory
- Steven and Alexandra Cohen Veterans Center for Posttraumatic Stress and Traumatic Brain Injury Department of Psychiatry, New York University New York NY USA
- Department of Psychiatry MSSM/James J. Peters Veterans Administration Medical Center New York NY USA
| | - Rachel Yehuda
- Steven and Alexandra Cohen Veterans Center for Posttraumatic Stress and Traumatic Brain Injury Department of Psychiatry, New York University New York NY USA
- Department of Psychiatry MSSM/James J. Peters Veterans Administration Medical Center New York NY USA
| | - Charles R. Marmar
- Steven and Alexandra Cohen Veterans Center for Posttraumatic Stress and Traumatic Brain Injury Department of Psychiatry, New York University New York NY USA
| | - Dewleen G. Baker
- Department of Psychiatry University of California San Diego San Diego CA USA
- Veterans Affairs Center of Excellence for Stress and Mental Health San Diego USA
- Psychiatry Services VA San Diego Healthcare System San Diego CA USA
| | - Bekh Bradley
- Department of Psychiatry and Behavioral Sciences Emory University Atlanta GA USA
- Mental Health Service Line Department of Veterans Affairs Medical Center Atlanta GA USA
| | - Karestan C. Koenen
- Department of Epidemiology Harvard TH Chan School of Public Health Boston MA USA
| | | | - Kerry J. Ressler
- Department of Psychiatry and Behavioral Sciences Emory University Atlanta GA USA
- McLean Hospital Harvard Medical School Belmont MA USA
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40
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Colodro-Conde L, Couvey-Duchesne B, Zhu G, Coventry WL, Byrne EM, Gordon S, Wright MJ, Montgomery GW, Madden PAF, Ripke S, Eaves LJ, Heath AC, Wray NR, Medland SE, Martin NG. A direct test of the diathesis-stress model for depression. Mol Psychiatry 2018; 23:1590-1596. [PMID: 28696435 PMCID: PMC5764823 DOI: 10.1038/mp.2017.130] [Citation(s) in RCA: 153] [Impact Index Per Article: 25.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2016] [Revised: 04/07/2017] [Accepted: 04/28/2017] [Indexed: 12/19/2022]
Abstract
The diathesis-stress theory for depression states that the effects of stress on the depression risk are dependent on the diathesis or vulnerability, implying multiplicative interactive effects on the liability scale. We used polygenic risk scores for major depressive disorder (MDD) calculated from the results of the most recent analysis from the Psychiatric Genomics Consortium as a direct measure of the vulnerability for depression in a sample of 5221 individuals from 3083 families. In the same we also had measures of stressful life events and social support and a depression symptom score, as well as DSM-IV MDD diagnoses for most individuals. In order to estimate the variance in depression explained by the genetic vulnerability, the stressors and their interactions, we fitted linear mixed models controlling for relatedness for the whole sample as well as stratified by sex. We show a significant interaction of the polygenic risk scores with personal life events (0.12% of variance explained, P-value=0.0076) contributing positively to the risk of depression. Additionally, our results suggest possible differences in the aetiology of depression between women and men. In conclusion, our findings point to an extra risk for individuals with combined vulnerability and high number of reported personal life events beyond what would be expected from the additive contributions of these factors to the liability for depression, supporting the multiplicative diathesis-stress model for this disease.
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Affiliation(s)
- Lucía Colodro-Conde
- Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Australia,Human Anatomy and Psychobiology, University of Murcia, Murcia, Spain,Correspondence author: Lucía Colodro Conde, a Locked Bag 2000 Royal Brisbane Hospital. QLD 4029, Australia., t +61 7 3845 3018,
| | - Baptiste Couvey-Duchesne
- Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Australia,Queensland Brain Institute, The University of Queensland, Brisbane, Australia
| | - Gu Zhu
- Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - William L Coventry
- School of Behavioural and Social Sciences, University of New England, Armidale, Australia
| | - Enda M Byrne
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
| | - Scott Gordon
- Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Margaret J Wright
- Queensland Brain Institute, The University of Queensland, Brisbane, Australia,Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia
| | - Grant W Montgomery
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
| | - Pamela AF Madden
- Department of Psychiatry, Washington University School of Medicine, St Louis, US
| | | | - Stephan Ripke
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, US,Department of Psychiatry and Psychotherapy, Universitätsmedizin Berlin Campus Charité Mitte, Berlin, DE,Medical and Population Genetics, Broad Institute, Cambridge, US
| | - Lindon J Eaves
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, US
| | - Andrew C Heath
- Department of Psychiatry, Washington University School of Medicine, St Louis, US
| | - Naomi R Wray
- Queensland Brain Institute, The University of Queensland, Brisbane, Australia,Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
| | - Sarah E Medland
- Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Nicholas G Martin
- Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
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Koulentaki M, Kouroumalis E. GABA A receptor polymorphisms in alcohol use disorder in the GWAS era. Psychopharmacology (Berl) 2018; 235:1845-1865. [PMID: 29721579 DOI: 10.1007/s00213-018-4918-4] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/04/2017] [Accepted: 04/18/2018] [Indexed: 12/11/2022]
Abstract
Alcohol use disorder (AUD) is a chronic, relapsing, neuro-psychiatric illness of high prevalence and with a serious public health impact worldwide. It is complex and polygenic, with a heritability of about 50%, and influenced by environmental causal heterogeneity. Risk factors associated with its etiology have a genetic component. GABA (γ-aminobutyric acid) is a major inhibitory neurotransmitter in mammalian brain. GABAA receptors are believed to mediate some of the physiological and behavioral actions of alcohol. In this critical review, relevant genetic terms and type and methodology of the genetic studies are briefly explained. Postulated candidate genes that encode subunits of GABAA receptors, with all the reported SNPs, are presented. Genetic studies and meta-analyses examining polymorphisms of the GABAA receptor and their association with AUD predisposition are presented. The data are critically examined with reference to recent GWAS studies that failed to show relations between GABAA receptors and AUD. Restrictions and perspectives of the different findings are discussed.
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Affiliation(s)
- Mairi Koulentaki
- Alcohology Research Laboratory, Medical School, University of Crete, 71500, Heraklion, Crete, Greece.,Department of Gastroenterology, University Hospital Heraklion, 71500, Heraklion, Crete, Greece
| | - Elias Kouroumalis
- Department of Gastroenterology, University Hospital Heraklion, 71500, Heraklion, Crete, Greece.
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42
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Chen G, Xue WD, Zhu J. Full genetic analysis for genome-wide association study of Fangji: a powerful approach for effectively dissecting the molecular architecture of personalized traditional Chinese medicine. Acta Pharmacol Sin 2018; 39:906-911. [PMID: 29417942 DOI: 10.1038/aps.2017.137] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2017] [Accepted: 08/29/2017] [Indexed: 12/24/2022] Open
Abstract
Elucidation of the systems biology foundation underlying the effect of Fangji, which are multi-herbal traditional Chinese medicine (TCM) formulas, is one of the major aims in the field. The numerous bioactive ingredients of a Fangji deal with the multiple targets of a complex disease, which is influenced by a number of genes and their interactions with the environment. Genome-wide association study (GWAS) is an unbiased approach for dissecting the genetic variants underlying complex diseases and individual response to a given treatment. GWAS has great potential for the study of systems biology from the point of view of genomics, but the capacity using current analysis models is largely handicapped, as evidenced by missing heritability. Recent development of a full genetic model, in which gene-gene interactions (dominance and epistasis) and gene-environment interactions are all considered, has addressed these problems. This approach has been demonstrated to substantially increase model power, remarkably improving the detection of association of GWAS and the construction of the molecular architecture. This analysis does not require a very large sample size, which is often difficult to meet for a GWAS of treatment response. Furthermore, this analysis can integrate other omic information and allow for variations of Fangji, which is very promising for Fangjiomic study and detection of the sophisticated molecular architecture of the function of Fangji, as well as for the delineation of the systems biology of personalized medicine in TCM in an unbiased and comprehensive manner.
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43
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Agrawal A, Chou YL, Carey CE, Baranger DAA, Zhang B, Sherva R, Wetherill L, Kapoor M, Wang JC, Bertelsen S, Anokhin AP, Hesselbrock V, Kramer J, Lynskey MT, Meyers JL, Nurnberger JI, Rice JP, Tischfield J, Bierut LJ, Degenhardt L, Farrer LA, Gelernter J, Hariri AR, Heath AC, Kranzler HR, Madden PAF, Martin NG, Montgomery GW, Porjesz B, Wang T, Whitfield JB, Edenberg HJ, Foroud T, Goate AM, Bogdan R, Nelson EC. Genome-wide association study identifies a novel locus for cannabis dependence. Mol Psychiatry 2018; 23:1293-1302. [PMID: 29112194 PMCID: PMC5938138 DOI: 10.1038/mp.2017.200] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2016] [Revised: 06/26/2017] [Accepted: 07/13/2017] [Indexed: 01/01/2023]
Abstract
Despite moderate heritability, only one study has identified genome-wide significant loci for cannabis-related phenotypes. We conducted meta-analyses of genome-wide association study data on 2080 cannabis-dependent cases and 6435 cannabis-exposed controls of European descent. A cluster of correlated single-nucleotide polymorphisms (SNPs) in a novel region on chromosome 10 was genome-wide significant (lowest P=1.3E-8). Among the SNPs, rs1409568 showed enrichment for H3K4me1 and H3K427ac marks, suggesting its role as an enhancer in addiction-relevant brain regions, such as the dorsolateral prefrontal cortex and the angular and cingulate gyri. This SNP is also predicted to modify binding scores for several transcription factors. We found modest evidence for replication for rs1409568 in an independent cohort of African American (896 cases and 1591 controls; P=0.03) but not European American (EA; 781 cases and 1905 controls) participants. The combined meta-analysis (3757 cases and 9931 controls) indicated trend-level significance for rs1409568 (P=2.85E-7). No genome-wide significant loci emerged for cannabis dependence criterion count (n=8050). There was also evidence that the minor allele of rs1409568 was associated with a 2.1% increase in right hippocampal volume in an independent sample of 430 EA college students (fwe-P=0.008). The identification and characterization of genome-wide significant loci for cannabis dependence is among the first steps toward understanding the biological contributions to the etiology of this psychiatric disorder, which appears to be rising in some developed nations.
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Affiliation(s)
- Arpana Agrawal
- Washington University School of Medicine, Dept. of Psychiatry, 660 S. Euclid, CB 8134, Saint Louis, MO 63110, USA
| | - Yi-Ling Chou
- Washington University School of Medicine, Dept. of Psychiatry, 660 S. Euclid, CB 8134, Saint Louis, MO 63110, USA
| | - Caitlin E. Carey
- Washington University in St. Louis, Dept. of Psychological and Brain Sciences, St. Louis, MO, USA
| | - David A. A. Baranger
- Washington University in St. Louis, Dept. of Psychological and Brain Sciences, St. Louis, MO, USA
| | - Bo Zhang
- Washington University School of Medicine, Dept. of Developmental Biology, St. Louis, MO, USA
| | - Richard Sherva
- Boston University School of Medicine, Dept. of Medicine (Biomedical Genetics), Boston, MA, USA
| | - Leah Wetherill
- Indiana University School of Medicine, Dept. of Medical and Molecular Genetics, Indianapolis, IN, USA
| | - Manav Kapoor
- Icahn School of Medicine at Mount Sinai, Dept. of Neuroscience, New York, NY USA
| | - Jen-Chyong Wang
- Icahn School of Medicine at Mount Sinai, Dept. of Neuroscience, New York, NY USA
| | - Sarah Bertelsen
- Icahn School of Medicine at Mount Sinai, Dept. of Neuroscience, New York, NY USA
| | - Andrey P Anokhin
- Washington University School of Medicine, Dept. of Psychiatry, 660 S. Euclid, CB 8134, Saint Louis, MO 63110, USA
| | - Victor Hesselbrock
- University of Connecticut Health, Dept. of Psychiatry, Farmington, CT, USA
| | - John Kramer
- University of Iowa Carver College of Medicine, Dept. of Psychiatry, Iowa City, IA USA
| | - Michael T. Lynskey
- King’s College, Institute of Psychiatry, Psychology and Neuroscience, Addictions Department, London, UK
| | - Jacquelyn L. Meyers
- State University of New York, Downstate Medical Center, Dept. of Psychiatry, Brooklyn, NY USA
| | - John I Nurnberger
- Indiana University School of Medicine, Depts. of Psychiatry and Medical and Molecular Genetics, and Stark Neuroscience Center, Indianapolis, IN, USA
| | - John P. Rice
- Washington University School of Medicine, Dept. of Psychiatry, 660 S. Euclid, CB 8134, Saint Louis, MO 63110, USA
| | - Jay Tischfield
- Rutgers, The State University of New Jersey: New Brunswick, NJ, United States
| | - Laura J. Bierut
- Washington University School of Medicine, Dept. of Psychiatry, 660 S. Euclid, CB 8134, Saint Louis, MO 63110, USA
| | - Louisa Degenhardt
- National Drug and Alcohol Research Centre, University of New South Wales, Sydney, Australia
| | - Lindsay A Farrer
- Boston University School of Medicine, Dept. of Medicine (Biomedical Genetics), Boston, MA, USA
| | - Joel Gelernter
- Yale University School of Medicine: New Haven, CT, USA
- US Department of Veterans Affairs: West Haven, CT, USA
| | - Ahmad R. Hariri
- Duke University, Department of Psychology and Neuroscience, Durham, NC, USA
| | - Andrew C. Heath
- Washington University School of Medicine, Dept. of Psychiatry, 660 S. Euclid, CB 8134, Saint Louis, MO 63110, USA
| | - Henry R. Kranzler
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, VISN 4 MIRECC, Crescenz VAMC, Philadelphia, PA, USA
| | - Pamela A. F. Madden
- Washington University School of Medicine, Dept. of Psychiatry, 660 S. Euclid, CB 8134, Saint Louis, MO 63110, USA
| | | | - Grant W Montgomery
- University of Queensland, Institute for Molecular Bioscience, Queensland, Australia
| | - Bernice Porjesz
- State University of New York, Downstate Medical Center, Dept. of Psychiatry, Brooklyn, NY USA
| | - Ting Wang
- Washington University School of Medicine, Department of Genetics, St. Louis, MO, USA
| | | | - Howard J. Edenberg
- Indiana University School of Medicine, Dept. of Medical and Molecular Genetics, Indianapolis, IN, USA
- Indiana University, Dept. of Biochemistry and Molecular Biology, Indianapolis, IN, USA
| | - Tatiana Foroud
- Indiana University School of Medicine, Dept. of Medical and Molecular Genetics, Indianapolis, IN, USA
| | - Alison M. Goate
- Icahn School of Medicine at Mount Sinai, Dept. of Neuroscience, New York, NY USA
| | - Ryan Bogdan
- Washington University in St. Louis, Dept. of Psychological and Brain Sciences, St. Louis, MO, USA
| | - Elliot C. Nelson
- Washington University School of Medicine, Dept. of Psychiatry, 660 S. Euclid, CB 8134, Saint Louis, MO 63110, USA
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Novel approaches to alcohol rehabilitation: Modification of stress-responsive brain regions through environmental enrichment. Neuropharmacology 2018; 145:25-36. [PMID: 29477298 DOI: 10.1016/j.neuropharm.2018.02.021] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2017] [Revised: 02/05/2018] [Accepted: 02/21/2018] [Indexed: 01/08/2023]
Abstract
Relapse remains the most prominent hurdle to successful rehabilitation from alcoholism. The neural mechanisms underlying relapse are complex, but our understanding of the brain regions involved, the anatomical circuitry and the modulation of specific nuclei in the context of stress and cue-induced relapse have improved significantly in recent years. In particular, stress is now recognised as a significant trigger for relapse, adding to the well-established impact of chronic stress to escalate alcohol consumption. It is therefore unsurprising that the stress-responsive regions of the brain have also been implicated in alcohol relapse, such as the nucleus accumbens, amygdala and the hypothalamus. Environmental enrichment is a robust experimental paradigm which provides a non-pharmacological tool to alter stress response and, separately, alcohol-seeking behaviour and symptoms of withdrawal. In this review, we examine and consolidate the preclinical evidence that alcohol seeking behaviour and stress-induced relapse are modulated by environmental enrichment, and these are primarily mediated by modification of neural activity within the key nodes of the addiction circuitry. Finally, we discuss the limited clinical evidence that stress-reducing approaches such as mindfulness could potentially serve as adjunctive therapy in the treatment of alcoholism. This article is part of the Special Issue entitled "Neurobiology of Environmental Enrichment".
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Abstract
PURPOSE OF REVIEW With the advent of the genome-wide association study (GWAS), our understanding of the genetics of addiction has made significant strides forward. Here, we summarize genetic loci containing variants identified at genome-wide statistical significance (P < 5 × 10-8) and independently replicated, review evidence of functional or regulatory effects for GWAS-identified variants, and outline multi-omics approaches to enhance discovery and characterize addiction loci. RECENT FINDINGS Replicable GWAS findings span 11 genetic loci for smoking, eight loci for alcohol, and two loci for illicit drugs combined and include missense functional variants and noncoding variants with regulatory effects in human brain tissues traditionally viewed as addiction-relevant (e.g., prefrontal cortex [PFC]) and, more recently, tissues often overlooked (e.g., cerebellum). GWAS analyses have discovered several novel, replicable variants contributing to addiction. Using larger sample sizes from harmonized datasets and new approaches to integrate GWAS with multiple 'omics data across human brain tissues holds great promise to significantly advance our understanding of the biology underlying addiction.
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Affiliation(s)
- Dana B Hancock
- Behavioral and Urban Health Program, Behavioral Health and Criminal Justice Division, RTI International, 3040 East Cornwallis Road, P. O. Box 12194, Research Triangle Park, NC, 27709, USA.
| | - Christina A Markunas
- Behavioral and Urban Health Program, Behavioral Health and Criminal Justice Division, RTI International, 3040 East Cornwallis Road, P. O. Box 12194, Research Triangle Park, NC, 27709, USA
| | - Laura J Bierut
- Department of Psychiatry, Washington University, St. Louis, MO, USA
| | - Eric O Johnson
- Fellow Program and Behavioral Health and Criminal Justice Division, RTI International, Research Triangle Park, NC, USA
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Whitfield JB, Heath AC, Madden PAF, Landers JG, Martin NG. Effects of high alcohol intake, alcohol-related symptoms and smoking on mortality. Addiction 2018; 113:158-166. [PMID: 28833688 PMCID: PMC5749262 DOI: 10.1111/add.14008] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2017] [Revised: 06/14/2017] [Accepted: 08/13/2017] [Indexed: 12/27/2022]
Abstract
BACKGROUND AND AIMS Both high alcohol intake and alcohol dependence increase mortality, and both are associated with smoking. We aimed to compare the associations of quantity of alcohol, number of alcohol-related symptoms and smoking history with all-cause mortality, and to assess symptom count and smoking history as confounders or mediators of the effects of high alcohol intake. DESIGN Survival was analysed by Cox regression with sex, body mass index, alcohol intake (overall and by beverage), maximum drinks on any day, alcohol symptom count and smoking status as potential predictors of age at death. SETTING Australia. PARTICIPANTS Participants were apparently healthy volunteers consisting of 33 593 Australian adult twins and their relatives who completed questionnaires or interviews between 1979 and 2005. MEASUREMENTS Data on alcohol use, smoking and occurrence of symptoms related to alcohol use disorders and death records from the Australian National Death Index. FINDINGS A total of 3764 participants were matched with deaths occurring within Australia up to July 2014. Individually, alcohol intake [hazard ratio (HR) = 1.0082, 95% confidence interval (CI) = 1.0063-1.0102, per drink per week], beer intake (HR = 1.0159, 95% CI = 1.0123-1.0195, per drink per week), life-time maximum number of drinks in 1 day (HR = 1.0176, 95% CI = 1.0130-1.0221, per drink), symptom count (HR = 1.0867, 95% CI = 1.0633-1.1106, per symptom) and smoking status (HR = 2.82, 95% CI = 2.52-3.16 for smokers of 10+ cigarettes/day versus never-smokers) were each significant predictors of all-cause mortality. After adjustment for the independently significant predictors alcohol symptom count and smoking status, alcohol intake was no longer significant (adjusted HR = 1.0012 per drink per week, 95% CI = 0.9979-1.0145). CONCLUSIONS Number of symptoms related to high alcohol intake and tobacco smoking appear to account for the positive association between alcohol consumption and premature mortality.
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Affiliation(s)
- John B Whitfield
- QIMR Berghofer Medical Research Institute, 300 Herston Road, Brisbane 4006, Queensland Australia
| | - Andrew C Heath
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Pamela A F Madden
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO 63110, USA
| | | | - Nicholas G Martin
- QIMR Berghofer Medical Research Institute, 300 Herston Road, Brisbane 4006, Queensland Australia
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47
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Chen G, Zhang F, Xue W, Wu R, Xu H, Wang K, Zhu J. An association study revealed substantial effects of dominance, epistasis and substance dependence co-morbidity on alcohol dependence symptom count. Addict Biol 2017; 22:1475-1485. [PMID: 27151647 DOI: 10.1111/adb.12402] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2015] [Revised: 02/27/2016] [Accepted: 03/15/2016] [Indexed: 12/12/2022]
Abstract
Alcohol dependence is a complex disease involving polygenes, environment and their interactions. Inadequate consideration of these interactions may have hampered the progress on genome-wide association studies of alcohol dependence. By using the dataset of the Study of Addiction: Genetics and Environment with 3838 subjects, we conducted a genome-wide association studies of alcohol dependence symptom count (ADSC) with a full genetic model considering additive, dominance, epistasis and their interactions with ethnicity, as well as conditions of co-morbid substance dependence. Twenty quantitative trait single nucleotide polymorphisms (QTSs) showed highly significant associations with ADSC, including four previously reported genes (ADH1C, PKNOX2, CPE and KCNB2) and the reported intergenic rs1363605, supporting the overall validity of the analysis. Two QTSs within or near ADH1C showed very strong association in a dominance inheritance mode and increased the phenotype value of ADSC when the effect of co-morbid opiate or marijuana dependence was controlled. Highly significant association was also identified in variants within four novel genes (RGS6, FMN1, NRM and BPTF), two non-coding RNA and two epistasis loci. QTS rs7616413, located near PTPRG encoding a protein tyrosine phosphatase receptor, interacted with rs10090742 within ANGPT1 encoding a protein tyrosine phosphatase in an additive × additive or dominance × additive manner. The detected QTSs contributed to about 20 percent of total heritability, in which dominance and epistasis effects accounted for over 50 percent. These results demonstrated that perturbations arising from gene-gene interaction and conditions of co-morbidity substantially influence the genetic architecture of complex trait.
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Affiliation(s)
- Gang Chen
- Center for Translational Systems Biology and Neuroscience, and Key Laboratory of Integrative Biomedicine for Brain Diseases; Nanjing University of Chinese Medicine; Nanjing China
| | - Futao Zhang
- Institute of Bioinformatics; Zhejiang University; Hangzhou China
| | - Wenda Xue
- Center for Translational Systems Biology and Neuroscience, and Key Laboratory of Integrative Biomedicine for Brain Diseases; Nanjing University of Chinese Medicine; Nanjing China
| | - Ruyan Wu
- Center for Translational Systems Biology and Neuroscience, and Key Laboratory of Integrative Biomedicine for Brain Diseases; Nanjing University of Chinese Medicine; Nanjing China
| | - Haiming Xu
- Institute of Bioinformatics; Zhejiang University; Hangzhou China
| | - Kesheng Wang
- Department of Biostatistics and Epidemiology, College of Public Health; East Tennessee State University; Johnson City TN USA
| | - Jun Zhu
- Institute of Bioinformatics; Zhejiang University; Hangzhou China
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48
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Prom-Wormley EC, Ebejer J, Dick DM, Bowers MS. The genetic epidemiology of substance use disorder: A review. Drug Alcohol Depend 2017; 180:241-259. [PMID: 28938182 PMCID: PMC5911369 DOI: 10.1016/j.drugalcdep.2017.06.040] [Citation(s) in RCA: 82] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/28/2016] [Revised: 06/20/2017] [Accepted: 06/23/2017] [Indexed: 12/15/2022]
Abstract
BACKGROUND Substance use disorder (SUD) remains a significant public health issue. A greater understanding of how genes and environment interact to regulate phenotypes comprising SUD will facilitate directed treatments and prevention. METHODS The literature studying the neurobiological correlates of SUD with a focus on the genetic and environmental influences underlying these mechanisms was reviewed. Results from twin/family, human genetic association, gene-environment interaction, epigenetic literature, phenome-wide association studies are summarized for alcohol, nicotine, cannabinoids, cocaine, and opioids. RESULTS There are substantial genetic influences on SUD that are expected to influence multiple neurotransmission pathways, and these influences are particularly important within the dopaminergic system. Genetic influences involved in other aspects of SUD etiology including drug processing and metabolism are also identified. Studies of gene-environment interaction emphasize the importance of environmental context in SUD. Epigenetic studies indicate drug-specific changes in gene expression as well as differences in gene expression related to the use of multiple substances. Further, gene expression is expected to differ by stage of SUD such as substance initiation versus chronic substance use. While a substantial literature has developed for alcohol and nicotine use disorders, there is comparatively less information for other commonly abused substances. CONCLUSIONS A better understanding of genetically-mediated mechanisms involved in the neurobiology of SUD provides increased opportunity to develop behavioral and biologically based treatment and prevention of SUD.
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Affiliation(s)
- Elizabeth C Prom-Wormley
- Dvision of Epidemiology, Department of Family Medicine and Population Health, Virginia Commonwealth University, PO Box 980212, Richmond, VA 23298-0212, USA.
| | - Jane Ebejer
- School of Cognitive Behavioural and Social Sciences, University of New England, Armidale, NSW 2350, Australia
| | - Danielle M Dick
- Department of Psychology, Virginia Commonwealth University, PO Box 842509, Richmond, VA 23284-2509, USA
| | - M Scott Bowers
- Faulk Center for Molecular Therapeutics, Biomedical Engeneering, Northwestern University, Evanston, IL 60201, USA
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49
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Yeung EW, Craggs JG, Gizer IR. Comorbidity of Alcohol Use Disorder and Chronic Pain: Genetic Influences on Brain Reward and Stress Systems. Alcohol Clin Exp Res 2017; 41:1831-1848. [PMID: 29048744 DOI: 10.1111/acer.13491] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2017] [Accepted: 08/25/2017] [Indexed: 01/10/2023]
Abstract
Alcohol use disorder (AUD) is highly comorbid with chronic pain (CP). Evidence has suggested that neuroadaptive processes characterized by reward deficit and stress surfeit are involved in the development of AUD and pain chronification. Neurological data suggest that shared genetic architecture associated with the reward and stress systems may contribute to the comorbidity of AUD and CP. This monograph first delineates the prevailing theories of the development of AUD and pain chronification focusing on the reward and stress systems. It then provides a brief summary of relevant neurological findings followed by an evaluation of evidence documented by molecular genetic studies. Candidate gene association studies have provided some initial support for the genetic overlap between AUD and CP; however, these results must be interpreted with caution until studies with sufficient statistical power are conducted and replications obtained. Genomewide association studies have suggested a number of genes (e.g., TBX19, HTR7, and ADRA1A) that are either directly or indirectly related to the reward and stress systems in the AUD and CP literature. Evidence reviewed in this monograph suggests that shared genetic liability underlying the comorbidity between AUD and CP, if present, is likely to be complex. As the advancement in molecular genetic methods continues, future studies may show broader central nervous system involvement in AUD-CP comorbidity.
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Affiliation(s)
- Ellen W Yeung
- Department of Psychological Sciences, University of Missouri, Columbia, Missouri.,Institute for Interdisciplinary Salivary Bioscience Research, University of California at Irvine, Irvine, California
| | - Jason G Craggs
- Department of Psychological Sciences, University of Missouri, Columbia, Missouri.,School of Health Professions, University of Missouri, Columbia, Missouri
| | - Ian R Gizer
- Department of Psychological Sciences, University of Missouri, Columbia, Missouri
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50
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Fochler S, Morozova TV, Davis MR, Gearhart AW, Huang W, Mackay TFC, Anholt RRH. Genetics of alcohol consumption in Drosophila melanogaster. GENES, BRAIN, AND BEHAVIOR 2017; 16:675-685. [PMID: 28627812 PMCID: PMC5667673 DOI: 10.1111/gbb.12399] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/26/2017] [Revised: 05/24/2017] [Accepted: 06/14/2017] [Indexed: 12/30/2022]
Abstract
Individual variation in alcohol consumption in human populations is determined by genetic, environmental, social and cultural factors. In contrast to humans, genetic contributions to complex behavioral phenotypes can be readily dissected in Drosophila, where both the genetic background and environment can be controlled and behaviors quantified through simple high-throughput assays. Here, we measured voluntary consumption of ethanol in ∼3000 individuals of each sex from an advanced intercross population derived from 37 lines of the Drosophila melanogaster Genetic Reference Panel. Extreme quantitative trait loci mapping identified 385 differentially segregating allelic variants located in or near 291 genes at P < 10-8 . The effects of single nucleotide polymorphisms associated with voluntary ethanol consumption are sex-specific, as found for other alcohol-related phenotypes. To assess causality, we used RNA interference knockdown or P{MiET1} mutants and their corresponding controls and functionally validated 86% of candidate genes in at least one sex. We constructed a genetic network comprised of 23 genes along with a separate trio and a pair of connected genes. Gene ontology analyses showed enrichment of developmental genes, including development of the nervous system. Furthermore, a network of human orthologs showed enrichment for signal transduction processes, protein metabolism and developmental processes, including nervous system development. Our results show that the genetic architecture that underlies variation in voluntary ethanol consumption is sexually dimorphic and partially overlaps with genetic factors that control variation in feeding behavior and alcohol sensitivity. This integrative genetic architecture is rooted in evolutionarily conserved features that can be extrapolated to human genetic interaction networks.
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Affiliation(s)
- S Fochler
- W. M. Keck Center for Behavioral Biology, Program in Genetics, and Department of Biological Sciences, North Carolina State University, Raleigh, NC, USA
- School of Biosciences and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK
| | - T V Morozova
- W. M. Keck Center for Behavioral Biology, Program in Genetics, and Department of Biological Sciences, North Carolina State University, Raleigh, NC, USA
| | - M R Davis
- W. M. Keck Center for Behavioral Biology, Program in Genetics, and Department of Biological Sciences, North Carolina State University, Raleigh, NC, USA
| | - A W Gearhart
- W. M. Keck Center for Behavioral Biology, Program in Genetics, and Department of Biological Sciences, North Carolina State University, Raleigh, NC, USA
| | - W Huang
- W. M. Keck Center for Behavioral Biology, Program in Genetics, and Department of Biological Sciences, North Carolina State University, Raleigh, NC, USA
| | - T F C Mackay
- W. M. Keck Center for Behavioral Biology, Program in Genetics, and Department of Biological Sciences, North Carolina State University, Raleigh, NC, USA
| | - R R H Anholt
- W. M. Keck Center for Behavioral Biology, Program in Genetics, and Department of Biological Sciences, North Carolina State University, Raleigh, NC, USA
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