DISCOVERY AND VALIDATION OF GENES DRIVING DRUG-INTAKE AND RELATED BEHAVIORAL TRAITS IN MICE

Substance use disorders (SUDs) are heritable disorders characterized by compulsive drug use, but the biological mechanisms driving addiction remain largely unknown. Genetic correlations reveal that predisposing drug-naïve phenotypes, including anxiety, depression, novelty preference, and sensation seeking, are predictive of drug-use phenotypes, implicating shared genetic mechanisms. Because of this relationship, high-throughput behavioral screening of predictive phenotypes in knockout (KO) mice allows efficient discovery of genes likely to be involved in drug use. We used this strategy in two rounds of screening in which we identified 33 drug-use candidate genes and ultimately validated the perturbation of 22 of these genes as causal drivers of substance intake. In our initial round of screening, we employed the two-bottle-choice paradigms to assess alcohol, methamphetamine, and nicotine intake. We identified 19 KO strains that were extreme responders on at least one predictive phenotype. Thirteen of the 19 gene deletions (68%) significantly affected alcohol use three methamphetamine use, and two both. In the second round of screening, we employed a multivariate approach to identify outliers and performed validation using methamphetamine two-bottle choice and ethanol drinking-in-the-dark protocols. We identified 15 KO strains that were extreme responders across the predisposing drug-naïve phenotypes. Eight of the 15 gene deletions (53%) significantly affected intake or preference for three alcohol, eight methamphetamine or three both (3). We observed multiple relations between predisposing behaviors and drug intake, revealing many distinct biobehavioral processes underlying these relationships. The set of mouse models identified in this study can be used to characterize these addiction-related processes further.

[1]  E. Chesler,et al.  Behavioral phenotypes revealed during reversal learning are linked with novel genetic loci in diversity outbred mice , 2022, Addiction neuroscience.

[2]  Susan N. Wright,et al.  Microbial glutamate metabolism predicts intravenous cocaine self-administration in diversity outbred mice , 2022, Neuropharmacology.

[3]  A. Kassambara,et al.  Extract and Visualize the Results of Multivariate Data Analyses [R package factoextra version 1.0.7] , 2020 .

[4]  N. Volkow,et al.  The Neuroscience of Drug Reward and Addiction. , 2019, Physiological reviews.

[5]  Robert W. Williams,et al.  Taar1 gene variants have a causal role in methamphetamine intake and response and interact with Oprm1 , 2019, eLife.

[6]  E. Chesler,et al.  Tmod2 Is a Regulator of Cocaine Responses through Control of Striatal and Cortical Excitability and Drug-Induced Plasticity , 2019, The Journal of Neuroscience.

[7]  Robert D. White,et al.  Sex Differences in Binge‐Like and Aversion‐Resistant Alcohol Drinking in C57BL/6J Mice , 2018, Alcoholism, clinical and experimental research.

[8]  Helen E. Parkinson,et al.  The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019 , 2018, Nucleic Acids Res..

[9]  The Gene Ontology Consortium,et al.  The Gene Ontology Resource: 20 years and still GOing strong , 2018, Nucleic Acids Res..

[10]  Minoru Kanehisa,et al.  New approach for understanding genome variations in KEGG , 2018, Nucleic Acids Res..

[11]  Laura B. Ferguson,et al.  Dissecting Brain Networks Underlying Alcohol Binge Drinking Using a Systems Genomics Approach , 2018, Molecular Neurobiology.

[12]  K. Szumlinski,et al.  Prior binge-drinking history promotes the positive affective valence of methamphetamine in mice. , 2018, Drug and alcohol dependence.

[13]  Robert W. Williams,et al.  A Spontaneous Mutation in Taar1 Impacts Methamphetamine-Related Traits Exclusively in DBA/2 Mice from a Single Vendor , 2018, Front. Pharmacol..

[14]  Y. Hata,et al.  Early deprivation increases high-leaning behavior, a novel anxiety-like behavior, in the open field test in rats , 2017, Neuroscience Research.

[15]  Lin-Yun Liu,et al.  Effect of post-weaning isolation on anxiety- and depressive-like behaviors of C57BL/6J mice , 2017, Experimental Brain Research.

[16]  Caleb J. Browne,et al.  Depression and substance use comorbidity: What we have learned from animal studies , 2017, The American journal of drug and alcohol abuse.

[17]  Steve D. M. Brown,et al.  Disease Model Discovery from 3,328 Gene Knockouts by The International Mouse Phenotyping Consortium , 2017, Nature Genetics.

[18]  P. Fletcher,et al.  Pdxdc1 modulates prepulse inhibition of acoustic startle in the mouse , 2017, Translational Psychiatry.

[19]  N. Volkow,et al.  Neurobiology of addiction: a neurocircuitry analysis. , 2016, The lancet. Psychiatry.

[20]  Loet Leydesdorff,et al.  Cited references and Medical Subject Headings (MeSH) as two different knowledge representations: clustering and mappings at the paper level , 2016, Scientometrics.

[21]  Michael A. Langston,et al.  GeneWeaver: data driven alignment of cross-species genomics in biology and disease , 2015, Nucleic Acids Res..

[22]  Minoru Kanehisa,et al.  KEGG as a reference resource for gene and protein annotation , 2015, Nucleic Acids Res..

[23]  Terrence F. Meehan,et al.  PhenStat: A Tool Kit for Standardized Analysis of High Throughput Phenotypic Data , 2015, PloS one.

[24]  L. Ray,et al.  The relationship between methamphetamine and alcohol use in a community sample of methamphetamine users. , 2014, Drug and alcohol dependence.

[25]  J. Crabbe,et al.  “Drinking in the Dark” (DID): A Simple Mouse Model of Binge‐Like Alcohol Intake , 2014, Current protocols in neuroscience.

[26]  T. E. Thiele,et al.  "Drinking in the dark" (DID) procedures: a model of binge-like ethanol drinking in non-dependent mice. , 2014, Alcohol.

[27]  D. Goldman,et al.  The genetic basis of addictive disorders. , 2012, The Psychiatric clinics of North America.

[28]  R. A. Harris,et al.  Behavioral actions of alcohol: phenotypic relations from multivariate analysis of mutant mouse data , 2012, Genes, brain, and behavior.

[29]  D. Hasin,et al.  Comorbidity of psychiatric and substance use disorders in the United States: current issues and findings from the NESARC , 2012, Current opinion in psychiatry.

[30]  Elissa J. Chesler,et al.  Accelerating Discovery for Complex Neurological and Behavioral Disorders Through Systems Genetics and Integrative Genomics in the Laboratory Mouse , 2012, Neurotherapeutics.

[31]  A. Markou,et al.  Neuronal Mechanisms Underlying Development of Nicotine Dependence: Implications for Novel Smoking-Cessation Treatments , 2011, Addiction science & clinical practice.

[32]  M. Krebs,et al.  Impulsivity and Sensation Seeking in Alcohol Abusing Patients with Schizophrenia , 2010, Front. Psychiatry.

[33]  E. Chesler,et al.  High-throughput behavioral phenotyping in the expanded panel of BXD recombinant inbred strains , 2010, Genes, brain, and behavior.

[34]  J. Crabbe,et al.  A method for mapping intralocus interactions influencing excessive alcohol drinking , 2010, Mammalian Genome.

[35]  Ming D. Li,et al.  New insights into the genetics of addiction , 2009, Nature Reviews Genetics.

[36]  J. Crabbe,et al.  Multivariate analyses reveal common and drug-specific genetic influences on responses to four drugs of abuse. , 2008, Trends in pharmacological sciences.

[37]  David H. Goldberg,et al.  The Neuroscience Information Framework: A Data and Knowledge Environment for Neuroscience , 2008, Neuroinformatics.

[38]  C. D. Fowler,et al.  Subtypes of nicotinic acetylcholine receptors in nicotine reward, dependence, and withdrawal: evidence from genetically modified mice , 2008, Behavioural pharmacology.

[39]  J. Crabbe,et al.  Voluntary ethanol consumption in 22 inbred mouse strains. , 2008, Alcohol.

[40]  Elissa J Chesler,et al.  Progress in using mouse inbred strains, consomics, and mutants to identify genes related to stress, anxiety, and alcohol phenotypes. , 2006, Alcoholism, clinical and experimental research.

[41]  J. Crabbe,et al.  Genetic independence of mouse measures of some aspects of novelty seeking , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[42]  M. Bardo,et al.  Novelty seeking and drug use: contribution of an animal model. , 2005, Experimental and clinical psychopharmacology.

[43]  E. Butelman,et al.  Genetic influences on impulsivity, risk taking, stress responsivity and vulnerability to drug abuse and addiction , 2005, Nature Neuroscience.

[44]  Pablo Tamayo,et al.  Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[45]  David Goldman,et al.  The genetics of addictions: uncovering the genes , 2005, Nature Reviews Genetics.

[46]  Ting-kai Li,et al.  Quantifying the risks associated with exceeding recommended drinking limits. , 2005, Alcoholism, clinical and experimental research.

[47]  Kenneth S. Kendler,et al.  Personality and comorbidity of common psychiatric disorders , 2005, British Journal of Psychiatry.

[48]  J. Crabbe,et al.  Evaluation of a simple model of ethanol drinking to intoxication in C57BL/6J mice , 2005, Physiology & Behavior.

[49]  C. Reed,et al.  Sensitivity to psychostimulants in mice bred for high and low stimulation to methamphetamine , 2004, Genes, brain, and behavior.

[50]  S. Lauzurica,et al.  Carcass and meat quality of light lambs using principal component analysis. , 2004, Meat science.

[51]  M. Bogue,et al.  Acoustic startle and prepulse inhibition in 40 inbred strains of mice. , 2003, Behavioral neuroscience.

[52]  Hao Wu,et al.  R/qtl: QTL Mapping in Experimental Crosses , 2003, Bioinform..

[53]  M. Hascöet,et al.  The mouse light/dark box test. , 2003, European journal of pharmacology.

[54]  P. Mormède,et al.  Sex and strain differences in ethanol drinking: effects of gonadectomy. , 2001, Alcoholism, clinical and experimental research.

[55]  S. Tassone,et al.  The use of principal component analysis (PCA) to characterize beef. , 2000, Meat science.

[56]  G. Mcclearn,et al.  High genetic susceptibility to ethanol withdrawal predicts low ethanol consumption , 1998, Mammalian Genome.

[57]  S. Morgan,et al.  Outlier detection in multivariate analytical chemical data. , 1998, Analytical chemistry.

[58]  G. Gessa,et al.  Sardinian alcohol-preferring rats: A genetic animal model of anxiety , 1995, Physiology & Behavior.

[59]  J. Crabbe,et al.  Genetic animal models of alcohol and drug abuse. , 1994, Science.

[60]  S. File,et al.  Validity of head-dipping as a measure of exploration in a modified hole-board , 1975, Psychopharmacologia.

[61]  Heng Tao Shen,et al.  Principal Component Analysis , 2009, Encyclopedia of Biometrics.

[62]  P. Skolnick,et al.  Genetic differences in a tail suspension test for evaluating antidepressant activity , 2004, Psychopharmacology.

[63]  M. Ashburner,et al.  The Gene Ontology Consortium , 2000 .

[64]  Hiroyuki Ogata,et al.  KEGG: Kyoto Encyclopedia of Genes and Genomes , 1999, Nucleic Acids Res..

[65]  L. Lumeng,et al.  Comparison of alcohol-preferring (P) and nonpreferring (NP) rats on tests of anxiety and for the anxiolytic effects of ethanol. , 1993, Alcohol.