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Mignogna KM, Tatom Z, Macleod L, Sergi Z, Nguyen A, Michenkova M, Smith ML, Miles MF. Identification of novel genetic loci and candidate genes for progressive ethanol consumption in diversity outbred mice. Neuropsychopharmacology 2024:10.1038/s41386-024-01902-6. [PMID: 38951586 DOI: 10.1038/s41386-024-01902-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 04/26/2024] [Accepted: 06/05/2024] [Indexed: 07/03/2024]
Abstract
Mouse behavioral genetic mapping studies can identify genomic intervals modulating complex traits under well-controlled environmental conditions and have been used to study ethanol behaviors to aid in understanding genetic risk and the neurobiology of alcohol use disorder (AUD). However, historically such studies have produced large confidence intervals, thus complicating identification of potential causal candidate genes. Diversity Outbred (DO) mice offer the ability to perform high-resolution quantitative trait loci (QTL) mapping on a very genetically diverse background, thus facilitating identification of candidate genes. Here, we studied a population of 636 male DO mice with four weeks of intermittent ethanol access via a three-bottle choice procedure, producing a progressive ethanol consumption phenotype. QTL analysis identified 3 significant (Chrs 3, 4, and 12) and 13 suggestive loci for ethanol-drinking behaviors with narrow confidence intervals (1-4 Mbp for significant QTLs). Results suggested that genetic influences on initial versus progressive ethanol consumption were localized to different genomic intervals. A defined set of positional candidate genes were prioritized using haplotype analysis, identified coding polymorphisms, prefrontal cortex transcriptomics data, human GWAS data and prior rodent gene set data for ethanol or other misused substances. These candidates included Car8, the lone gene with a significant cis-eQTL within a Chr 4 QTL for week four ethanol consumption. These results represent the highest-resolution genetic mapping of ethanol consumption behaviors in mice to date, providing identification of novel loci and candidate genes for study in relation to the neurobiology of AUD.
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Affiliation(s)
- Kristin M Mignogna
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Zachary Tatom
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Lorna Macleod
- Department of Pharmacology and Toxicology, Virginia Commonwealth University, Richmond, VA, USA
| | - Zachary Sergi
- Department of Pharmacology and Toxicology, Virginia Commonwealth University, Richmond, VA, USA
| | - Angel Nguyen
- Department of Pharmacology and Toxicology, Virginia Commonwealth University, Richmond, VA, USA
| | - Marie Michenkova
- Department of Pharmacology and Toxicology, Virginia Commonwealth University, Richmond, VA, USA
| | - Maren L Smith
- Department of Pharmacology and Toxicology, Virginia Commonwealth University, Richmond, VA, USA
| | - Michael F Miles
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA.
- Department of Pharmacology and Toxicology, Virginia Commonwealth University, Richmond, VA, USA.
- Department of Neurology, Virginia Commonwealth University, Richmond, VA, USA.
- VCU Alcohol Research Center, Virginia Commonwealth University, Richmond, VA, USA.
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Thorpe HHA, Fontanillas P, Meredith JJ, Jennings MV, Cupertino RB, Pakala S, Elson SL, Khokhar JY, Davis LK, Johnson EC, Palmer AA, Sanchez-Roige S. Genome-wide association studies of lifetime and frequency cannabis use in 131,895 individuals. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.06.14.24308946. [PMID: 38947071 PMCID: PMC11213095 DOI: 10.1101/2024.06.14.24308946] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
Cannabis is one of the most widely used drugs globally. Decriminalization of cannabis is further increasing cannabis consumption. We performed genome-wide association studies ( GWASs ) of lifetime ( N= 131,895) and frequency ( N= 73,374) of cannabis use. Lifetime cannabis use GWAS identified two loci, one near CADM2 (rs11922956, p =2.40E-11) and another near GRM3 (rs12673181, p =6.90E-09). Frequency of use GWAS identified one locus near CADM2 (rs4856591, p =8.10E-09; r 2 =0.76 with rs11922956). Both traits were heritable and genetically correlated with previous GWASs of lifetime use and cannabis use disorder ( CUD ), as well as other substance use and cognitive traits. Polygenic scores ( PGSs ) for lifetime and frequency of cannabis use associated cannabis use phenotypes in AllofUs participants. Phenome-wide association study of lifetime cannabis use PGS in a hospital cohort replicated associations with substance use and mood disorders, and uncovered associations with celiac and infectious diseases. This work demonstrates the value of GWASs of CUD transition risk factors.
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Nivins S, Sauce B, Liebherr M, Judd N, Klingberg T. Long-term impact of digital media on brain development in children. Sci Rep 2024; 14:13030. [PMID: 38844772 PMCID: PMC11156852 DOI: 10.1038/s41598-024-63566-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2024] [Accepted: 05/30/2024] [Indexed: 06/09/2024] Open
Abstract
Digital media (DM) takes an increasingly large part of children's time, yet the long-term effect on brain development remains unclear. We investigated how individual effects of DM use (i.e., using social media, playing video games, or watching television/videos) on the development of the cortex (i.e., global cortical surface area), striatum, and cerebellum in children over 4 years, accounting for both socioeconomic status and genetic predisposition. We used a prospective, multicentre, longitudinal cohort of children from the Adolescent Brain and Cognitive Development Study, aged 9.9 years when entering the study, and who were followed for 4 years. Annually, children reported their DM usage through the Youth Screen Time Survey and underwent brain magnetic resonance imaging scans every 2 years. Quadratic-mixed effect modelling was used to investigate the relationship between individual DM usage and brain development. We found that individual DM usage did not alter the development of cortex or striatum volumes. However, high social media usage was associated with a statistically significant change in the developmental trajectory of cerebellum volumes, and the accumulated effect of high-vs-low social media users on cerebellum volumes over 4 years was only β = - 0.03, which was considered insignificant. Nevertheless, the developmental trend for heavy social media users was accelerated at later time points. This calls for further studies and longer follow-ups on the impact of social media on brain development.
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Affiliation(s)
- Samson Nivins
- Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden.
| | - Bruno Sauce
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Magnus Liebherr
- Department of General Psychology: Cognition, University Duisburg-Essen, Duisburg, Germany
| | - Nicholas Judd
- Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Torkel Klingberg
- Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden.
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Kranzler HR, Davis CN, Feinn R, Jinwala Z, Khan Y, Oikonomou A, Silva-Lopez D, Burton I, Dixon M, Milone J, Ramirez S, Shifman N, Levey D, Gelernter J, Hartwell EE, Kember RL. Gene × environment effects and mediation involving adverse childhood events, mood and anxiety disorders, and substance dependence. Nat Hum Behav 2024:10.1038/s41562-024-01885-w. [PMID: 38834750 DOI: 10.1038/s41562-024-01885-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Accepted: 04/10/2024] [Indexed: 06/06/2024]
Abstract
Adverse childhood events (ACEs) contribute to the development of mood and anxiety disorders and substance dependence. However, the extent to which these effects are direct or indirect and whether genetic risk moderates them is unclear. We examined associations among ACEs, mood/anxiety disorders and substance dependence in 12,668 individuals (44.9% female, 42.5% African American/Black, 42.1% European American/white). Using latent variables for each phenotype, we modelled direct and indirect associations of ACEs with substance dependence, mediated by mood/anxiety disorders (the forward or 'self-medication' model) and of ACEs with mood/anxiety disorders, mediated by substance dependence (the reverse or 'substance-induced' model). In a subsample, we tested polygenic scores for the substance dependence and mood/anxiety disorder factors as moderators in the mediation models. Although there were significant indirect paths in both directions, mediation by mood/anxiety disorders (the forward model) was greater than that by substance dependence (the reverse model). Greater genetic risk for substance use disorders was associated with a weaker direct association between ACEs and substance dependence in both ancestry groups (reflecting gene × environment interactions) and a weaker indirect association in European-ancestry individuals (reflecting moderated mediation). We found greater evidence that substance dependence reflects self-medication of mood/anxiety disorders than that mood/anxiety disorders are substance induced. Among individuals at higher genetic risk for substance dependence, ACEs were less associated with that outcome. Following exposure to ACEs, multiple pathways appear to underlie the associations between mood/anxiety disorders and substance dependence. Specification of these pathways could inform individually targeted prevention and treatment approaches.
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Affiliation(s)
- Henry R Kranzler
- Center for Studies of Addiction, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
- Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA, USA.
| | - Christal N Davis
- Center for Studies of Addiction, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA, USA
| | - Richard Feinn
- Department of Medical Sciences, Frank H. Netter School of Medicine at Quinnipiac University, North Haven, CT, USA
| | - Zeal Jinwala
- Center for Studies of Addiction, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA, USA
| | - Yousef Khan
- Center for Studies of Addiction, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Ariadni Oikonomou
- Center for Studies of Addiction, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Damaris Silva-Lopez
- Center for Studies of Addiction, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Isabel Burton
- Center for Studies of Addiction, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Morgan Dixon
- Center for Studies of Addiction, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Jackson Milone
- Center for Studies of Addiction, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Sarah Ramirez
- Center for Studies of Addiction, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Naomi Shifman
- Center for Studies of Addiction, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Daniel Levey
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- VA CT Healthcare Center, West Haven, CT, USA
| | - Joel Gelernter
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Departments of Genetics and Neurobiology, Yale University School of Medicine, New Haven, CT, USA
- VA CT Healthcare Center, West Haven, CT, USA
| | - Emily E Hartwell
- Center for Studies of Addiction, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA, USA
| | - Rachel L Kember
- Center for Studies of Addiction, Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA, USA
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Malone SG, Davis CN, Piserchia Z, Setzer MR, Toikumo S, Zhou H, Winterlind EL, Gelernter J, Justice A, Leggio L, Rentsch CT, Kranzler HR, Gray JC. Alcohol use disorder and body mass index show genetic pleiotropy and shared neural associations. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.03.24306773. [PMID: 38746260 PMCID: PMC11092735 DOI: 10.1101/2024.05.03.24306773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
Background The prevalence of co-occurring heavy alcohol consumption and obesity is increasing in the United States. Despite neurobiological overlap in the regulation of alcohol consumption and eating behavior, alcohol- and body mass index (BMI)-related phenotypes show no or minimal genetic correlation. We hypothesized that the lack of genetic correlation is due to mixed effect directions of variants shared by AUD and BMI. Methods We applied MiXeR, to investigate shared genetic architecture between AUD and BMI in individuals of European ancestry. We used conjunctional false discovery rate (conjFDR) analysis to detect loci associated with both phenotypes and their directional effect, Functional Mapping and Annotation (FUMA) to identify lead single nucleotide polymorphisms (SNPs), Genotype-Tissue Expression (GTEx) samples to examine gene expression enrichment across tissue types, and BrainXcan to evaluate the shared associations of AUD and BMI with brain image-derived phenotypes. Results MiXeR analysis indicated polygenic overlap of 80.9% between AUD and BMI, despite a genetic correlation (r g ) of -.03. ConjFDR analysis yielded 56 lead SNPs with the same effect direction and 76 with the opposite direction. Of the 132 shared lead SNPs, 53 were novel for both AUD and BMI. GTEx analyses identified significant overexpression in the frontal cortex (BA9), hypothalamus, cortex, anterior cingulate cortex (BA24), hippocampus, and amygdala. Amygdala and caudate nucleus gray matter volumes were significantly associated with both AUD and BMI in BrainXcan analyses. Conclusions More than half of variants significantly associated with AUD and BMI had opposite directions of effect for the traits, supporting our hypothesis that this is the basis for their lack of genetic correlation. Follow-up analyses identified brain regions implicated in executive functioning, reward, homeostasis, and food intake regulation. Together, these findings clarify the extensive polygenic overlap between AUD and BMI and elucidate several overlapping neurobiological mechanisms.
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MacDonald M, Fonseca PAS, Johnson K, Murray EM, Kember RL, Kranzler H, Mayfield D, da Silva D. Divergent gene expression patterns in alcohol and opioid use disorders lead to consistent alterations in functional networks within the Dorsolateral Prefrontal Cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.29.591734. [PMID: 38746311 PMCID: PMC11092658 DOI: 10.1101/2024.04.29.591734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
Substance Use Disorders (SUDs) manifest as persistent drug-seeking behavior despite adverse consequences, with Alcohol Use Disorder (AUD) and Opioid Use Disorder (OUD) representing prevalent forms associated with significant mortality rates and economic burdens. The co-occurrence of AUD and OUD is common, necessitating a deeper comprehension of their intricate interactions. While the causal link between these disorders remains elusive, shared genetic factors are hypothesized. Leveraging public datasets, we employed genomic and transcriptomic analyses to explore conserved and distinct molecular pathways within the dorsolateral prefrontal cortex associated with AUD and OUD. Our findings unveil modest transcriptomic overlap at the gene level between the two disorders but substantial convergence on shared biological pathways. Notably, these pathways predominantly involve inflammatory processes, synaptic plasticity, and key intracellular signaling regulators. Integration of transcriptomic data with the latest genome-wide association studies (GWAS) for problematic alcohol use (PAU) and OUD not only corroborated our transcriptomic findings but also confirmed the limited shared heritability between the disorders. Overall, our study indicates that while alcohol and opioids induce diverse transcriptional alterations at the gene level, they converge on select biological pathways, offering promising avenues for novel therapeutic targets aimed at addressing both disorders simultaneously.
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Affiliation(s)
- Martha MacDonald
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Pablo A. S. Fonseca
- Dpto. Producción Animal, Facultad de Veterinaria, Universidad de León. Campus de Vegazana s/n, 24007 Leon, Spain
| | - Kory Johnson
- Bioinformatics Section, Intramural Information Technology & Bioinformatics Program, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Erin M Murray
- Department of Neuroscience, University of Rochester School of Medicine, Rochester NY
| | - Rachel L Kember
- Center for Studies of Addiction, University of Pennsylvania, Perelman School of Medicine and Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA, USA
| | - Henry Kranzler
- Center for Studies of Addiction, University of Pennsylvania, Perelman School of Medicine and Mental Illness Research, Education and Clinical Center, Crescenz VAMC, Philadelphia, PA, USA
| | - Dayne Mayfield
- Department of Neuroscience Waggoner Center for Alcohol and Addiction Research, The University of Texas at Austin, Austin, TX
| | - Daniel da Silva
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY
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Holla B, Mahadevan J, Ganesh S, Sud R, Janardhanan M, Balachander S, Strom N, Mattheisen M, Sullivan PF, Huang H, Zandi P, Benegal V, Reddy YJ, Jain S, Purushottam M, Viswanath B. A cross ancestry genetic study of psychiatric disorders from India. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.25.24306377. [PMID: 38712191 PMCID: PMC11071591 DOI: 10.1101/2024.04.25.24306377] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Genome-wide association studies across diverse populations may help validate and confirm genetic contributions to risk of disease. We estimated the extent of population stratification as well as the predictive accuracy of polygenic scores (PGS) derived from European samples to a data set from India. We analysed 2685 samples from two data sets, a population neurodevelopmental study (cVEDA) and a hospital-based sample of bipolar affective disorder (BD) and obsessive-compulsive disorder (OCD). Genotyping was conducted using Illumina's Global Screening Array. Population structure was examined with principal component analysis (PCA), uniform manifold approximation and projection (UMAP), support vector machine (SVM) ancestry predictions, and admixture analysis. PGS were calculated from the largest available European discovery GWAS summary statistics for BD, OCD, and externalizing traits using two Bayesian methods that incorporate local linkage disequilibrium structures (PGS-CS-auto) and functional genomic annotations (SBayesRC). Our analyses reveal global and continental PCA overlap with other South Asian populations. Admixture analysis revealed a north-south genetic axis within India (FST 1.6%). The UMAP partially reconstructed the contours of the Indian subcontinent. The Bayesian PGS analyses indicates moderate-to-high predictive power for BD. This was despite the cross-ancestry bias of the discovery GWAS dataset, with the currently available data. However, accuracy for OCD and externalizing traits was much lower. The predictive accuracy was perhaps influenced by the sample size of the discovery GWAS and phenotypic heterogeneity across the syndromes and traits studied. Our study results highlight the accuracy and generalizability of newer PGS models across ancestries. Further research, across diverse populations, would help understand causal mechanisms that contribute to psychiatric syndromes and traits.
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Affiliation(s)
- Bharath Holla
- Department of Integrative Medicine, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Jayant Mahadevan
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Suhas Ganesh
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Reeteka Sud
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Meghana Janardhanan
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Srinivas Balachander
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Nora Strom
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
| | - Manuel Mattheisen
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
- Dalhousie University, Department of Community Health and Epidemiology & Faculty of Computer Science, Halifax, Nova Scotia, Canada
- University Hospital of Psychiatry and Psychotherapy, University of Bern
| | - Patrick F Sullivan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Genetics and Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - Hailiang Huang
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA02114, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA02142, USA
- Department of Medicine, Harvard Medical School, Boston, MA02114, USA
| | - Peter Zandi
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Vivek Benegal
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Yc Janardhan Reddy
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Sanjeev Jain
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Meera Purushottam
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Biju Viswanath
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
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Davis C, Khan Y, Toikumo S, Jinwala Z, Boomsma D, Levey D, Gelernter J, Kember R, Kranzler H. A Multivariate Genome-Wide Association Study Reveals Neural Correlates and Common Biological Mechanisms of Psychopathology Spectra. RESEARCH SQUARE 2024:rs.3.rs-4228593. [PMID: 38659902 PMCID: PMC11042423 DOI: 10.21203/rs.3.rs-4228593/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
There is considerable comorbidity across externalizing and internalizing behavior dimensions of psychopathology. We applied genomic structural equation modeling (gSEM) to genome-wide association study (GWAS) summary statistics to evaluate the factor structure of externalizing and internalizing psychopathology across 16 traits and disorders among European-ancestry individuals (n's = 16,400 to 1,074,629). We conducted GWAS on factors derived from well-fitting models. Downstream analyses served to identify biological mechanisms, explore drug repurposing targets, estimate genetic overlap between the externalizing and internalizing spectra, and evaluate causal effects of psychopathology liability on physical health. Both a correlated factors model, comprising two factors of externalizing and internalizing risk, and a higher-order single-factor model of genetic effects contributing to both spectra demonstrated acceptable t. GWAS identified 409 lead single nucleotide polymorphisms (SNPs) associated with externalizing and 85 lead SNPs associated with internalizing, while the second-order GWAS identified 256 lead SNPs contributing to broad psychopathology risk. In bivariate causal mixture models, nearly all externalizing and internalizing causal variants overlapped, despite a genetic correlation of only 0.37 (SE = 0.02) between them. Externalizing genes showed cell-type specific expression in GABAergic, cortical, and hippocampal neurons, and internalizing genes were associated with reduced subcallosal cortical volume, providing insight into the neurobiological underpinnings of psychopathology. Genetic liability for externalizing, internalizing, and broad psychopathology exerted causal effects on pain, general health, cardiovascular diseases, and chronic illnesses. These findings underscore the complex genetic architecture of psychopathology, identify potential biological pathways for the externalizing and internalizing spectra, and highlight the physical health burden of psychiatric comorbidity.
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Affiliation(s)
| | - Yousef Khan
- University of Pennsylvania Perelman School of Medicine
| | | | - Zeal Jinwala
- University of Pennsylvania Perelman School of Medicine
| | - D Boomsma
- Vrije Universiteit Amsterdam, The Netherlands
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Wang L, Kranzler HR, Gelernter J, Zhou H. Multi-ancestry Whole-exome Sequencing Study of Alcohol Use Disorder in Two Cohorts. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.05.24305412. [PMID: 38645055 PMCID: PMC11030482 DOI: 10.1101/2024.04.05.24305412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Alcohol use disorder (AUD) is a leading cause of death and disability worldwide. There has been substantial progress in identifying genetic variants underlying AUD. However, there are few whole-exome sequencing (WES) studies of AUD. We analyzed WES of 4,530 samples from the Yale-Penn cohort and 469,835 samples from the UK Biobank (UKB). After quality control, 1,420 AUD cases and 619 controls of European ancestry (EUR) and 1,142 cases and 608 controls of African ancestry (AFR) from Yale-Penn were retained for subsequent analyses. WES data from 415,617 EUR samples (12,861 cases), 6,142 AFR samples (130 cases) and 4,607 South Asian (SAS) samples (130 cases) from UKB were also analyzed. Single-variant association analysis identified the well-known functional variant rs1229984 in ADH1B ( P =4.88×10 -31 ) and several other common variants in ADH1C . Gene-based tests identified ADH1B ( P =1.00×10 -31 ), ADH1C ( P =5.23×10 -7 ), CNST ( P =1.19×10 -6 ), and IFIT5 (3.74×10 -6 ). This study extends our understanding of the genetic basis of AUD.
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10
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Galimberti M, Levey DF, Deak JD, Zhou H, Stein MB, Gelernter J. Genetic influences and causal pathways shared between cannabis use disorder and other substance use traits. Mol Psychiatry 2024:10.1038/s41380-024-02548-y. [PMID: 38580809 DOI: 10.1038/s41380-024-02548-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Revised: 03/25/2024] [Accepted: 03/28/2024] [Indexed: 04/07/2024]
Abstract
Cannabis use disorder (CanUD) has increased with the legalization of the use of cannabis. Around 20% of individuals using cannabis develop CanUD, and the number of users has grown with increasing ease of access. CanUD and other substance use disorders (SUDs) are associated phenotypically and genetically. We leveraged new CanUD genomics data to undertake genetically-informed analyses with unprecedented power, to investigate the genetic architecture and causal relationships between CanUD and lifetime cannabis use with risk for developing SUDs and substance use traits. Analyses included calculating local and global genetic correlations, genomic structural equation modeling (genomicSEM), and Mendelian Randomization (MR). Results from the genetic correlation and genomicSEM analyses demonstrated that CanUD and cannabis use differ in their relationships with SUDs and substance use traits. We found significant causal effects of CanUD influencing all the analyzed traits: opioid use disorder (OUD) (Inverse variant weighted, IVW β = 0.925 ± 0.082), problematic alcohol use (PAU) (IVW β = 0.443 ± 0.030), drinks per week (DPW) (IVW β = 0.182 ± 0.025), Fagerström Test for Nicotine Dependence (FTND) (IVW β = 0.183 ± 0.052), cigarettes per day (IVW β = 0.150 ± 0.045), current versus former smokers (IVW β = 0.178 ± 0.052), and smoking initiation (IVW β = 0.405 ± 0.042). We also found evidence of bidirectionality showing that OUD, PAU, smoking initiation, smoking cessation, and DPW all increase risk of developing CanUD. For cannabis use, bidirectional relationships were inferred with PAU, smoking initiation, and DPW; cannabis use was also associated with a higher risk of developing OUD (IVW β = 0.785 ± 0.266). GenomicSEM confirmed that CanUD and cannabis use load onto different genetic factors. We conclude that CanUD and cannabis use can increase the risk of developing other SUDs. This has substantial public health implications; the move towards legalization of cannabis use may be expected to increase other kinds of problematic substance use. These harmful outcomes are in addition to the medical harms associated directly with CanUD.
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Affiliation(s)
- Marco Galimberti
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Daniel F Levey
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Joseph D Deak
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Hang Zhou
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Murray B Stein
- Department of Psychiatry and School of Public Health, University of California San Diego, La Jolla, CA, USA
- VA San Diego Healthcare System, San Diego, CA, USA
| | - Joel Gelernter
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA.
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA.
- Departments of Genetics and Neuroscience, Yale University School of Medicine, New Haven, CT, USA.
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Xavier RM. The Potential and Challenges of Genomics Informed Precision Care for Substance Use Disorders. J Psychosoc Nurs Ment Health Serv 2024; 62:11-14. [PMID: 38446624 DOI: 10.3928/02793695-20240206-01] [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: 03/08/2024]
Abstract
Substance use disorders (SUDs) are complex brain disorders with heritability rooted in the interplay of multiple genetic factors, alongside significant environmental influences. Gaining insights into the genetic mechanisms that heighten SUD risk can guide precision care, specifically in the development of targeted tools for prevention, early intervention, and the discovery of therapeutic targets. Nurses are ideally placed to advance genomics-informed precision care for individuals with SUDs. To fulfill this role, they must be adequately prepared to assess the value and utility of current genomics knowledge, its limitations, and ways to incorporate this understanding into clinical practice, education, research, and health care policy. [Journal of Psychosocial Nursing and Mental Health Services, 62(3), 11-14.].
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12
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Koller D, Mitjans M, Kouakou M, Friligkou E, Cabrera-Mendoza B, Deak JD, Llonga N, Pathak GA, Stiltner B, Løkhammer S, Levey DF, Zhou H, Hatoum AS, Kember RL, Kranzler HR, Stein MB, Corominas R, Demontis D, Artigas MS, Ramos-Quiroga JA, Gelernter J, Ribasés M, Cormand B, Polimanti R. Genetic contribution to the comorbidity between attention-deficit/hyperactivity disorder and substance use disorders. Psychiatry Res 2024; 333:115758. [PMID: 38335780 PMCID: PMC11157987 DOI: 10.1016/j.psychres.2024.115758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 01/17/2024] [Accepted: 01/23/2024] [Indexed: 02/12/2024]
Abstract
We characterized the genetic architecture of the attention-deficit hyperactivity disorder-substance use disorder (ADHD-SUD) relationship by investigating genetic correlation, causality, pleiotropy, and common polygenic risk. Summary statistics from genome-wide association studies (GWAS) were used to investigate ADHD (Neff = 51,568), cannabis use disorder (CanUD, Neff = 161,053), opioid use disorder (OUD, Neff = 57,120), problematic alcohol use (PAU, Neff = 502,272), and problematic tobacco use (PTU, Neff = 97,836). ADHD, CanUD, and OUD GWAS meta-analyses included cohorts with case definitions based on different diagnostic criteria. PAU GWAS combined information related to alcohol use disorder, alcohol dependence, and the items related to alcohol problematic consequences assessed by the alcohol use disorders identification test. PTU GWAS was generated a multi-trait analysis including information regarding Fagerström Test for Nicotine Dependence and cigarettes per day. Linkage disequilibrium score regression analyses indicated positive genetic correlation with CanUD, OUD, PAU, and PTU. Genomic structural equation modeling showed that these genetic correlations were related to two latent factors: one including ADHD, CanUD, and PTU and the other with OUD and PAU. The evidence of a causal effect of PAU and PTU on ADHD was stronger than the reverse in the two-sample Mendelian randomization analysis. Conversely, similar strength of evidence was found between ADHD and CanUD. CADM2 rs62250713 was a pleiotropic SNP between ADHD and all SUDs. We found seven, one, and twenty-eight pleiotropic variants between ADHD and CanUD, PAU, and PTU, respectively. Finally, OUD, CanUD, and PAU PRS were associated with increased odds of ADHD. Our findings demonstrated the contribution of multiple pleiotropic mechanisms to the comorbidity between ADHD and SUDs.
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Affiliation(s)
- Dora Koller
- Department of Psychiatry, Yale School of Medicine, New Haven, CA, USA; Veterans Affairs Connecticut Healthcare Center, West Haven, CA, USA; Department of Genetics, Microbiology, and Statistics, Faculty of Biology, University of Barcelona, Catalonia, Spain.
| | - Marina Mitjans
- Department of Genetics, Microbiology, and Statistics, Faculty of Biology, University of Barcelona, Catalonia, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Institute of Biomedicine of the University of Barcelona (IBUB), Barcelona, Catalonia Spain; Sant Joan de Déu Research Institute (IR-SJD), Esplugues de Llobregat, Catalonia, Spain
| | - Manuela Kouakou
- Department of Psychiatry, Yale School of Medicine, New Haven, CA, USA
| | - Eleni Friligkou
- Department of Psychiatry, Yale School of Medicine, New Haven, CA, USA; Veterans Affairs Connecticut Healthcare Center, West Haven, CA, USA
| | - Brenda Cabrera-Mendoza
- Department of Psychiatry, Yale School of Medicine, New Haven, CA, USA; Veterans Affairs Connecticut Healthcare Center, West Haven, CA, USA
| | - Joseph D Deak
- Department of Psychiatry, Yale School of Medicine, New Haven, CA, USA; Veterans Affairs Connecticut Healthcare Center, West Haven, CA, USA
| | - Natalia Llonga
- Psychiatric Genetics Unit, Group of Psychiatry Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Gita A Pathak
- Department of Psychiatry, Yale School of Medicine, New Haven, CA, USA; Veterans Affairs Connecticut Healthcare Center, West Haven, CA, USA
| | - Brendan Stiltner
- Department of Psychiatry, Yale School of Medicine, New Haven, CA, USA; Veterans Affairs Connecticut Healthcare Center, West Haven, CA, USA
| | - Solveig Løkhammer
- Department of Psychiatry, Yale School of Medicine, New Haven, CA, USA; NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway; Dr. Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - Daniel F Levey
- Department of Psychiatry, Yale School of Medicine, New Haven, CA, USA; Veterans Affairs Connecticut Healthcare Center, West Haven, CA, USA
| | - Hang Zhou
- Department of Psychiatry, Yale School of Medicine, New Haven, CA, USA; Veterans Affairs Connecticut Healthcare Center, West Haven, CA, USA
| | - Alexander S Hatoum
- Department of Psychological and Brain Sciences, Washington University in Saint Louis, St. Louis, MO, USA
| | - Rachel L Kember
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA; Mental Illness Research, Education and Clinical Center, Veterans Integrated Service Network 4, Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania, USA
| | - Henry R Kranzler
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA; Mental Illness Research, Education and Clinical Center, Veterans Integrated Service Network 4, Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania, USA
| | - Murray B Stein
- Department of Psychiatry, University of California, San Diego, La Jolla, USA; Herbert Wertheim School of Public Health, University of California, San Diego, La Jolla, USA; VA San Diego Healthcare System, San Diego, CA, La Jolla, USA
| | - Roser Corominas
- Department of Genetics, Microbiology, and Statistics, Faculty of Biology, University of Barcelona, Catalonia, Spain; Institute of Biomedicine of the University of Barcelona (IBUB), Barcelona, Catalonia Spain; Sant Joan de Déu Research Institute (IR-SJD), Esplugues de Llobregat, Catalonia, Spain; Biomedical Network Research Centre on Rare Disorders (CIBERER), Instituto de Salud Carlos III, Madrid, Spain
| | - 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 02142, USA
| | - María Soler Artigas
- Department of Genetics, Microbiology, and Statistics, Faculty of Biology, University of Barcelona, Catalonia, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Psychiatric Genetics Unit, Group of Psychiatry Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain; Department of Mental Health, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Josep Antoni Ramos-Quiroga
- Department of Genetics, Microbiology, and Statistics, Faculty of Biology, University of Barcelona, Catalonia, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Psychiatric Genetics Unit, Group of Psychiatry Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain; Department of Psychiatry and Forensic Medicine, Universitat Autonoma de Barcelona, Barcelona, Spain
| | - Joel Gelernter
- Department of Psychiatry, Yale School of Medicine, New Haven, CA, USA; Veterans Affairs Connecticut Healthcare Center, West Haven, CA, USA; Department of Genetics, Yale School of Medicine, New Haven, CT, USA; Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA
| | - Marta Ribasés
- Department of Genetics, Microbiology, and Statistics, Faculty of Biology, University of Barcelona, Catalonia, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Psychiatric Genetics Unit, Group of Psychiatry Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain; Department of Mental Health, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Bru Cormand
- Department of Genetics, Microbiology, and Statistics, Faculty of Biology, University of Barcelona, Catalonia, Spain; Institute of Biomedicine of the University of Barcelona (IBUB), Barcelona, Catalonia Spain; Sant Joan de Déu Research Institute (IR-SJD), Esplugues de Llobregat, Catalonia, Spain; Biomedical Network Research Centre on Rare Disorders (CIBERER), Instituto de Salud Carlos III, Madrid, Spain
| | - Renato Polimanti
- Department of Psychiatry, Yale School of Medicine, New Haven, CA, USA; Veterans Affairs Connecticut Healthcare Center, West Haven, CA, USA; Wu Tsai Institute, Yale University, New Haven, CT, USA
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Koller D, Friligkou E, Stiltner B, Pathak GA, Løkhammer S, Levey DF, Zhou H, Hatoum AS, Deak JD, Kember RL, Treur JL, Kranzler HR, Johnson EC, Stein MB, Gelernter J, Polimanti R. Pleiotropy and genetically inferred causality linking multisite chronic pain to substance use disorders. Mol Psychiatry 2024:10.1038/s41380-024-02446-3. [PMID: 38355787 DOI: 10.1038/s41380-024-02446-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 01/18/2024] [Accepted: 01/22/2024] [Indexed: 02/16/2024]
Abstract
Individuals suffering from chronic pain develop substance use disorders (SUDs) more often than others. Understanding the shared genetic influences underlying the comorbidity between chronic pain and SUDs will lead to a greater understanding of their biology. Genome-wide association statistics were obtained from the UK Biobank for multisite chronic pain (MCP, Neffective = 387,649) and from the Million Veteran Program and the Psychiatric Genomics Consortium meta-analyses for alcohol use disorder (AUD, Neffective = 296,974), cannabis use disorder (CanUD, Neffective = 161,053), opioid use disorder (OUD, Neffective = 57,120), and problematic tobacco use (PTU, Neffective = 270,120). SNP-based heritability was estimated for each of the traits and genetic correlation (rg) analyses were performed to assess MCP-SUD pleiotropy. Bidirectional Mendelian Randomization analyses evaluated possible causal relationships. Finally, to identify and characterize individual loci, we performed a genome-wide pleiotropy analysis and a brain-wide analysis using imaging phenotypes available from the UK Biobank. MCP was positively genetically correlated with AUD (rg = 0.26, p = 7.55 × 10-18), CanUD (rg = 0.37, p = 8.21 × 10-37), OUD (rg = 0.20, p = 1.50 × 10-3), and PTU (rg = 0.29, p = 8.53 × 10-12). Although the MR analyses supported bi-directional relationships, MCP had larger effects on AUD (pain-exposure: beta = 0.18, p = 8.21 × 10-4; pain-outcome: beta = 0.07, p = 0.018), CanUD (pain-exposure: beta = 0.58, p = 2.70 × 10-6; pain-outcome: beta = 0.05, p = 0.014) and PTU (pain-exposure: beta = 0.43, p = 4.16 × 10-8; pain-outcome: beta = 0.09, p = 3.05 × 10-6) than the reverse. The genome-wide analysis identified two SNPs pleiotropic between MCP and all SUD investigated: IHO1 rs7652746 (ppleiotropy = 2.69 × 10-8), and CADM2 rs1248857 (ppleiotropy = 1.98 × 10-5). In the brain-wide analysis, rs7652746 was associated with multiple cerebellum and amygdala imaging phenotypes. When analyzing MCP pleiotropy with each SUD separately, we found 25, 22, and 4 pleiotropic variants for AUD, CanUD, and OUD, respectively. To our knowledge, this is the first large-scale study to provide evidence of potential causal relationships and shared genetic mechanisms underlying MCP-SUD comorbidity.
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Affiliation(s)
- Dora Koller
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA.
- Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA.
- Department of Genetics, Microbiology, and Statistics, Faculty of Biology, University of Barcelona, Catalonia, Spain.
| | - Eleni Friligkou
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Brendan Stiltner
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Gita A Pathak
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Solveig Løkhammer
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway
- Dr. Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - Daniel F Levey
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Hang Zhou
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Alexander S Hatoum
- Department of Psychological and Brain Sciences, Washington University in Saint Louis, St. Louis, MO, USA
| | - Joseph D Deak
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA
| | - Rachel L Kember
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Mental Illness Research, Education and Clinical Center, Veterans Integrated Service Network 4, Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
| | - Jorien L Treur
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Henry R Kranzler
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Mental Illness Research, Education and Clinical Center, Veterans Integrated Service Network 4, Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
| | - Emma C Johnson
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Murray B Stein
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- 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
| | - Joel Gelernter
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare Center, 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
- Wu Tsai Institute, Yale University, New Haven, CT, USA
| | - Renato Polimanti
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA.
- Veterans Affairs Connecticut Healthcare Center, West Haven, CT, USA.
- Wu Tsai Institute, Yale University, New Haven, CT, USA.
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Barr P, Neale Z, Chatzinakos C, Schulman J, Mullins N, Zhang J, Chorlian D, Kamarajan C, Kinreich S, Pandey A, Pandey G, de Viteri SS, Acion L, Bauer L, Bucholz K, Chan G, Dick D, Edenberg H, Foroud T, Goate A, Hesselbrock V, Johnson E, Kramer J, Lai D, Plawecki M, Salvatore J, Wetherill L, Agrawal A, Porjesz B, Meyers J. Clinical, genomic, and neurophysiological correlates of lifetime suicide attempts among individuals with alcohol dependence. RESEARCH SQUARE 2024:rs.3.rs-3894892. [PMID: 38405959 PMCID: PMC10889049 DOI: 10.21203/rs.3.rs-3894892/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
Research has identified clinical, genomic, and neurophysiological markers associated with suicide attempts (SA) among individuals with psychiatric illness. However, there is limited research among those with an alcohol use disorder (AUD), despite their disproportionately higher rates of SA. We examined lifetime SA in 4,068 individuals with DSM-IV alcohol dependence from the Collaborative Study on the Genetics of Alcoholism (23% lifetime suicide attempt; 53% female; 17% Admixed African American ancestries; mean age: 38). We 1) conducted a genome-wide association study (GWAS) of SA and performed downstream analyses to determine whether we could identify specific biological pathways of risk, and 2) explored risk in aggregate across other clinical conditions, polygenic scores (PGS) for comorbid psychiatric problems, and neurocognitive functioning between those with AD who have and have not reported a lifetime suicide attempt. The GWAS and downstream analyses did not produce any significant associations. Participants with an AUD who had attempted suicide had greater rates of trauma exposure, major depressive disorder, post-traumatic stress disorder, and other substance use disorders compared to those who had not attempted suicide. Polygenic scores for suicide attempt, depression, and PTSD were associated with reporting a suicide attempt (ORs = 1.22-1.44). Participants who reported a SA also had decreased right hemispheric frontal-parietal theta and decreased interhemispheric temporal-parietal alpha electroencephalogram resting-state coherences relative to those who did not, but differences were small. Overall, individuals with alcohol dependence who report SA appear to experience a variety of severe comorbidities and elevated polygenic risk for SA. Our results demonstrate the need to further investigate suicide attempts in the presence of substance use disorders.
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Affiliation(s)
- Peter Barr
- SUNY Downstate Health Sciences University
| | - Zoe Neale
- SUNY Downstate Health Sciences University
| | | | | | | | | | | | | | | | - Ashwini Pandey
- State University of New York Downstate Health Sciences University
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Jacquelyn Meyers
- State University of New York (SUNY) Downstate Health Sciences University
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