Genome wide association for addiction: replicated results and comparisons of two analytic approaches.

paper Cited Public

Authors: Drgon, Tomas; Zhang, Ping-Wu; Johnson, Catherine; Walther, Donna; Hess, Judith; Nino, Michelle; Uhl, George R
Year: 2010
Journal: PloS one
PMID: 20098672
DOI: 10.1371/journal.pone.0008832
PMCID: PMC2809089

BACKGROUND: Vulnerabilities to dependence on addictive substances are substantially heritable complex disorders whose underlying genetic architecture is likely to be polygenic, with modest contributions from variants in many individual genes. "Nontemplate" genome wide association (GWA) approaches can identity groups of chromosomal regions and genes that, taken together, are much more likely to contain allelic variants that alter vulnerability to substance dependence than expected by chance. METHODOLOGY/PRINCIPAL FINDINGS: We report pooled "nontemplate" genome-wide association studies of two independent samples of substance dependent vs control research volunteers (n = 1620), one European-American and the other African-American using 1 million SNP (single nucleotide polymorphism) Affymetrix genotyping arrays. We assess convergence between results from these two samples using two related methods that seek clustering of nominally-positive results and assess significance levels with Monte Carlo and permutation approaches. Both "converge then cluster" and "cluster then converge" analyses document convergence between the results obtained from these two independent datasets in ways that are virtually never found by chance. The genes identified in this fashion are also identified by individually-genotyped dbGAP data that compare allele frequencies in cocaine dependent vs control individuals. CONCLUSIONS/SIGNIFICANCE: These overlapping results identify small chromosomal regions that are also identified by genome wide data from studies of other relevant samples to extents much greater than chance. These chromosomal regions contain more genes related to "cell adhesion" processes than expected by chance. They also contain a number of genes that encode potential targets for anti-addiction pharmacotherapeutics. "Nontemplate" GWA approaches that seek chromosomal regions in which nominally-positive associations are found in multiple independent samples are likely to complement classical, "template" GWA approaches in which "genome wide" levels of significance are sought for SNP data from single case vs control comparisons.

#	Section	Preview
20	Discussion — “Converge Then Cluster” and “Cluster Then Converge” Approaches	Results from approaches (1) and (2) share a number of potential strengths. These datasets provide…
21	Discussion — “Converge Then Cluster” and “Cluster Then Converge” Approaches	Monte Carlo methods allow us to test the probabilities of chance clustering of nominally positive…
22	Discussion — Differences between “Non-Template” and “Template” GWA Approaches	Validation studies provide evidence for excellent correlations between individually genotyped and…
23	Discussion — Differences between “Non-Template” and “Template” GWA Approaches	and control individuals studied in the present sample were collected at the same site, recruited in…
24	Discussion — Differences between “Non-Template” and “Template” GWA Approaches	that are carefully prepared from pools of DNA from 20 individuals. Quality control evaluations come…
25	Discussion — Differences between “Non-Template” and “Template” GWA Approaches	false-negative findings in our first analysis. 4a) Many of the results of individually-genotyped…
26	Discussion — Differences between “Non-Template” and “Template” GWA Approaches	at multiple nearby SNPs. In any single sample, many of the clusters of positive findings at nearby…
27	Discussion — Differences between “Non-Template” and “Template” GWA Approaches	to an even more prominent bias toward identification of larger genes in this way; 8a) “Template”…
28	Discussion — Genes Also Identified in Other Studies of Addiction	Despite the differences in approaches, primary substance of abuse and/or genetic background,…
29	Discussion — Genes Also Identified in Other Studies of Addiction	Our identification of some SNP markers whose allelic frequencies distinguish controls from addicts…
30	Discussion — Genes Also Identified in Other Studies of Addiction	The convergent data derived from studies of individuals with addictions to substances in several…
31	Discussion — Classes of Genes Identified Here	We focus on identification of genes. Although associations in chromosomal regions that do not…
32	Discussion — Classes of Genes Identified Here	3) These genes do not overlap, to extents greater than expected by chance, with genes listed in the…
33	Discussion — Classes of Genes Identified Here	Identification of cell adhesion molecule genes, which are represented in several of the above…
34	Discussion — Classes of Genes Identified Here	We also identify genes that are likely to be readily targeted and modulated by drugs, and thus…
35	Discussion — Genes Also Identified in Studies of Heritable, Co-Occurring Phenotypes	A number of the genes identified in this work are also identified in genome wide association and/or…
36	Discussion — Conclusions	The findings presented here promise to add to the ongoing consideration of methods for comparing GWA…
37	Materials and Methods — NIDA Research Volunteers	Research volunteers who came to the NIDA research facility in Baltimore, Maryland between 1990 and…
38	Materials and Methods — NIDA Research Volunteers	DNAs were assessed in pools since this: 1) provided us with the maximal ability to protect the…
39	Materials and Methods — NIDA Research Volunteers	DNA was prepared from blood [13], [55], [56]. Genotyping and primary assessments of genotyping were…

Name	Type
100k GWA studies of alcohol dependence in European-Americans local	cohort
38k GWA studies of nicotine dependent vs less nicotine dependent smokers local	cohort
3′ NRXN3 variant local	variant
500-600k GWA studies of methamphetamine dependent Japanese samples local	cohort
5′ NrCAM variant local	variant
600k GWA studies of polysubstance abusers local	cohort
abuser cohort local	cohort
Abusers local	phenotype
addiction	phenotype
Addiction-associated allelic variants local	variant
addiction-associated genes local	gene
addiction vulnerability variants local	variant
ADH1B	gene
adult locomotor behavior local	phenotype
African American	cohort
African-American control cohort local	cohort
African-American dependent cohort local	cohort
African-Americans	cohort
alcohol	phenotype
alcohol dependence	phenotype
ALDH2	gene
Allele frequency difference local	phenotype
Allelic variant local	variant
Alzheimer's disease	phenotype
amygdala	anatomy
Asian	cohort
Asian methamphetamine dependence samples local	cohort
auditory receptor cell differentiation local	phenotype
bipolar disorder	phenotype
blood	drug
brain	anatomy
brain development	phenotype
cases	cohort
caudate nucleus	anatomy
cell adhesion molecule genes local	gene
CEPH	cohort
cerebellum	anatomy
cocaine	phenotype
COGEND	cohort
cognitive ability	phenotype
Collaborative Study on the Genetics of Alcoholism (COGA)	cohort
Community-based comparison subjects local	cohort
complex disorders	phenotype
complex traits	phenotype
control	cohort
controls	cohort
control subjects	cohort
Co-occurring traits local	phenotype
corpus callosum	anatomy
cortex	anatomy
current data local	cohort
current sample	cohort
dbEST local	cohort
dbGaP	cohort
dbGAP data local	cohort
dbGAP dataset local	cohort
dbGAP datasets local	cohort
dbGAP samples	cohort
dbGAP samples of cocaine dependent vs control individuals local	cohort
Dependent case cohort local	cohort
disease	phenotype
DNA	drug
DNA databases local	drug
DSMIII-R/IV dependence local	phenotype
endocytosis local	phenotype
endothelial cell proliferation local	phenotype
ethnically-matched samples local	cohort
European-American abusers	cohort
European-American control cohort local	cohort
European-American dependent cohort local	cohort
European ancestry	cohort
European population	cohort
Family study of cocaine dependence	cohort
female subjects	cohort
frontal cortex	anatomy
functional haplotype(s) local	variant
Gabbr2	gene
genes	gene
Genes identified by approaches (1) or (2) local	gene
Genomic variant local	variant
glutamate	drug
glutamate signaling pathway local	phenotype
GRIA4	gene
GRIK2	gene
GRM5	gene
GRM7	gene
GWA datasets	cohort
GWA study	cohort
HapMap	cohort
hippocampus	anatomy
human cDNA libraries local	cohort
hypothalamus	anatomy
illegal behaviors	phenotype
illicit drug use	phenotype
inner ear receptor cell differentiation local	phenotype
legal phenotypes local	phenotype
male subjects	cohort
marijuana	phenotype
marijuana dependence	phenotype
mechanoreceptor differentiation local	phenotype
medulla oblongata	anatomy
methamphetamine	drug
methamphetamine dependence	phenotype
Monte Carlo III simulation local	drug
Monte Carlo II simulation local	drug
National Survey of Drug Use in Households local	cohort
nicotine	drug
nicotine dependence	phenotype
nicotinic receptor gene local	gene
NIDA	cohort
NIDA research facility cohort local	cohort
nondependent	phenotype
No significant lifetime use of any addictive substance local	phenotype
NRCAM local	gene
NRXN3	gene
oligogenic loci local	variant
opiates	drug
opioid	drug
opioid dependence	phenotype
Oprd1	cohort
other drug dependence	phenotype
peripheral nerve local	anatomy
phenotype	phenotype
phv00066444.v1.p1 local	variant
physical abuse	phenotype
polygenic influences	cohort
Polysubstance abusers local	phenotype
polysubstance dependence	phenotype
pooled genotype data local	cohort
positive SNPs local	variant
reproducibly positive SNPs local	variant
reproducibly-positive SNPs local	variant
samples of different racial/ethnic backgrounds local	cohort
sex determination local	phenotype
smoking cessation	phenotype
smoking dependence	phenotype
smoking quantity	phenotype
SNP	cohort
Specific population local	cohort
Specific substance local	drug
stimulants	drug
substance	phenotype
substance abuse	phenotype
substance dependent subjects local	cohort
substance use	phenotype
substantia nigra	anatomy
subthalamic nucleus	anatomy
synaptic plasticity	phenotype
Table2_genes local	gene
thalamus	anatomy
tobacco use	phenotype
white matter	anatomy
whole brain	anatomy
Yoruba	cohort

Citation	PMID	DOI	Status
Amos, CI et al., Nat Genet, 2008, Genome-wide association scan of tag SNPs identifies a susceptibility locus for lung cancer at 15q25.1.	18385676	10.1038/ng.109	Cited
Bang-Ce, Y et al., Anal Biochem, 2004, Estimation of relative allele frequencies of single-nucleotide polymorphisms in different populations by microarray hybridization of pooled DNA.	15351282	10.1016/j.ab.2004.05.016	Cited
Barnes, MR et al.	—	—	—
Benson, DL et al., Trends Cell Biol, 2000, Making memories stick: cell-adhesion molecules in synaptic plasticity.	11050419	10.1016/s0962-8924(00)01838-9	Cited
Beuten, J et al., Am J Hum Genet, 2005, Single- and multilocus allelic variants within the GABA(B) receptor subunit 2 (GABAB2) gene are significantly associated with nicotine dependence.	15759211	10.1086/429839	Cited
Bierut, LJ et al., Hum Mol Genet, 2007, Novel genes identified in a high-density genome wide association study for nicotine dependence.	17158188	10.1093/hmg/ddl441	Cited
Butcher, LM et al., Hum Mol Genet, 2005, SNPs, microarrays and pooled DNA: identification of four loci associated with mild mental impairment in a sample of 6000 children.	15800012	10.1093/hmg/ddi142	Cited
Butcher, LM et al., Mol Psychiatry, 2005, Association analysis of mild mental impairment using DNA pooling to screen 432 brain-expressed single-nucleotide polymorphisms.	15452586	10.1038/sj.mp.4001589	Cited
Carlson, CS et al., Nature, 2004, Mapping complex disease loci in whole-genome association studies.	15164069	10.1038/nature02623	Cited
Craig, DW et al., BMC Genomics, 2005, Identification of disease causing loci using an array-based genotyping approach on pooled DNA.	16197552	10.1186/1471-2164-6-138	Cited
Dupont, WD et al., Control Clin Trials, 1990, Power and sample size calculations. A review and computer program.	2161310	10.1016/0197-2456(90)90005-m	Cited
Dupont, WD et al., Control Clin Trials, 1998, Power and sample size calculations for studies involving linear regression.	9875838	10.1016/s0197-2456(98)00037-3	Cited
Gershon, ES et al., Mol Psychiatry, 2008, Genome-wide association in bipolar.	18084308	10.1038/sj.mp.4002117	Cited
Gorroochurn, P et al., Genet Med, 2007, Non-replication of association studies: “pseudo-failures” to replicate?	17575498	10.1097/gim.0b013e3180676d79	Cited
Hageman, GS et al., Proc Natl Acad Sci U S A, 2005, A common haplotype in the complement regulatory gene factor H (HF1/CFH) predisposes individuals to age-related macular degeneration.	15870199	10.1073/pnas.0501536102	Cited
Haines, JL et al., Science, 2005, Complement factor H variant increases the risk of age-related macular degeneration.	15761120	10.1126/science.1110359	Cited
Hinds, DA et al., Hum Genomics, 2004, Application of pooled genotyping to scan candidate regions for association with HDL cholesterol levels.	15606997	10.1186/1479-7364-1-6-421	Cited
Hishimoto, A et al., Hum Mol Genet, 2007, Neurexin 3 polymorphisms are associated with alcohol dependence and altered expression of specific isoforms.	17804423	10.1093/hmg/ddm247	Cited
Hung, RJ et al., Nature, 2008, A susceptibility locus for lung cancer maps to nicotinic acetylcholine receptor subunit genes on 15q25.	18385738	10.1038/nature06885	Cited
Ioannidis, JP, Hum Hered, 2007, Non-replication and inconsistency in the genome-wide association setting.	17551261	10.1159/000103512	Cited
Johnson, AD et al., BMC Med Genet, 2009, An open access database of genome-wide association results.	19161620	10.1186/1471-2350-10-6	Cited
Johnson, C et al., Am J Med Genet B Neuropsychiatr Genet, 2006, Pooled association genome scanning for alcohol dependence using 104,268 SNPs: validation and use to identify alcoholism vulnerability loci in unrelated individuals from the collaborative study on the genetics of alcoholism.	16894614	10.1002/ajmg.b.30346	Primary
Johnson, C et al., Am J Med Genet B Neuropsychiatr Genet, 2009, Convergent genome wide association results for bipolar disorder and substance dependence.	19127564	10.1002/ajmg.b.30900	Cited
Karkowski, LM et al., Am J Med Genet, 2000, Multivariate assessment of factors influencing illicit substance use in twins from female-female pairs.	11054775	—	Cited
Kavvoura, FK et al., Hum Genet, 2008, Methods for meta-analysis in genetic association studies: a review of their potential and pitfalls.	18026754	10.1007/s00439-007-0445-9	Cited
Kendler, KS et al., Arch Gen Psychiatry, 2000, Illicit psychoactive substance use, heavy use, abuse, and dependence in a US population-based sample of male twins.	10711912	10.1001/archpsyc.57.3.261	Cited
Khoury, MJ et al., Int J Epidemiol, 2007, On the synthesis and interpretation of consistent but weak gene-disease associations in the era of genome-wide association studies.	17182636	10.1093/ije/dyl253	Cited
Knight, J et al., Hum Hered, 2009, A comparison of association statistics between pooled and individual genotypes.	19172081	10.1159/000194975	Cited
Lachman, HM et al., Hum Mol Genet, 2007, Genomewide Suggestive Linkage of Opioid Dependence to Chromosome 14q.	17409192	10.1093/hmg/ddm081	Cited
Lambert, JC et al., Psychoneuroendocrinology, 2007, Genetic heterogeneity of Alzheimer's disease: complexity and advances.	17659844	10.1016/j.psyneuen.2007.05.015	Cited
Lander, ES et al., Science, 1994, Genetic dissection of complex traits.	8091226	10.1126/science.8091226	Cited
Li, CY et al., PLoS Comput Biol, 2008, Genes and (common) pathways underlying drug addiction.	18179280	10.1371/journal.pcbi.0040002	Cited
Liu, QR et al., Am J Med Genet B Neuropsychiatr Genet, 2006, Addiction molecular genetics: 639,401 SNP whole genome association identifies many “cell adhesion” genes.	17099884	10.1002/ajmg.b.30436	Cited
Liu, QR et al., Proc Natl Acad Sci U S A, 2005, Pooled association genome scanning: validation and use to identify addiction vulnerability loci in two samples.	16091475	10.1073/pnas.0500329102	Cited
Luczak, SE et al., J Stud Alcohol, 2002, Genetic risk for alcoholism relates to level of response to alcohol in Asian-American men and women.	11925062	—	Cited
Macgregor, S et al., Nucleic Acids Res, 2006, Analysis of pooled DNA samples on high density arrays without prior knowledge of differential hybridization rates.	16627870	10.1093/nar/gkl136	Cited
McElroy, JP et al., Curr Top Microbiol Immunol, 2008, Multiple sclerosis genetics.	18219814	10.1007/978-3-540-73677-6_3	Cited
Meaburn, E et al., Nucleic Acids Res, 2006, Genotyping pooled DNA using 100K SNP microarrays: a step towards genomewide association scans.	16478714	10.1093/nar/gnj027	Cited
Persico, AM et al., Biol Psychiatry, 1996, D2 dopamine receptor gene TaqI A1 and B1 restriction fragment length polymorphisms: enhanced frequencies in psychostimulant-preferring polysubstance abusers.	8894071	10.1016/0006-3223(95)00483-1	Cited
Qiu, S et al., Neurobiol Learn Mem, 2006, A fresh look at an ancient receptor family: emerging roles for low density lipoprotein receptors in synaptic plasticity and memory formation.	16198608	10.1016/j.nlm.2005.08.009	Cited
Saccone, SF et al., Hum Mol Genet, 2007, Cholinergic nicotinic receptor genes implicated in a nicotine dependence association study targeting 348 candidate genes with 3713 SNPs.	17135278	10.1093/hmg/ddl438	Cited
Schuckit, MA et al., J Clin Psychiatry, 1982, Alcohol-related flushing and the risk for alcoholism in sons of alcoholics.	7118836	—	Cited
Sham, P et al., Nat Rev Genet, 2002, DNA Pooling: a tool for large-scale association studies.	12415316	10.1038/nrg930	Cited
Sklar, P et al., Mol Psychiatry, 2008, Whole-genome association study of bipolar disorder.	18317468	10.1038/sj.mp.4002151	Cited
Smith, SS et al., Arch Gen Psychiatry, 1992, Genetic vulnerability to drug abuse. The D2 dopamine receptor Taq I B1 restriction fragment length polymorphism appears more frequently in polysubstance abusers.	1355337	10.1001/archpsyc.1992.01820090051009	Cited
Sullivan, PF, Biol Psychiatry, 2007, Spurious genetic associations.	17346679	10.1016/j.biopsych.2006.11.010	Cited
Thorgeirsson, TE et al., Nature, 2008, A variant associated with nicotine dependence, lung cancer and peripheral arterial disease.	18385739	10.1038/nature06846	Cited
True, WR et al., Am J Med Genet, 1999, Interrelationship of genetic and environmental influences on conduct disorder and alcohol and marijuana dependence symptoms.	10402507	10.1002/(sici)1096-8628(19990820)88:4<391::aid-ajmg17>3.0.co;2-l	Cited
Tsuang, MT et al., Arch Gen Psychiatry, 1998, Co-occurrence of abuse of different drugs in men: the role of drug-specific and shared vulnerabilities.	9819064	10.1001/archpsyc.55.11.967	Cited
Uhl, GR et al., Am J Hum Genet, 2001, Polysubstance abuse-vulnerability genes: genome scans for association, using 1,004 subjects and 1,494 single-nucleotide polymorphisms.	11704927	10.1086/324467	Cited
Uhl, GR et al., Ann N Y Acad Sci, 2008, Molecular genetics of addiction and related heritable phenotypes: genome-wide association approaches identify “connectivity constellation” and drug target genes with pleiotropic effects.	18991966	10.1196/annals.1441.018	Cited
Uhl, GR et al., Arch Gen Psychiatry, 2008, Genome-wide association for methamphetamine dependence: convergent results from 2 samples.	18316681	10.1001/archpsyc.65.3.345	Cited
Uhl, GR et al., Arch Gen Psychiatry, 2008, Molecular genetics of successful smoking cessation: convergent genome-wide association study results.	18519826	10.1001/archpsyc.65.6.683	Cited
Uhl, GR et al., Biochem Pharmacol, 2008, “Higher order” addiction molecular genetics: convergent data from genome-wide association in humans and mice.	17764662	10.1016/j.bcp.2007.06.042	Cited
Uhl, GR et al., BMC Genet, 2007, Molecular genetics of nicotine dependence and abstinence: whole genome association using 520,000 SNPs.	17407593	10.1186/1471-2156-8-10	Cited
Uhl, GR et al., Psychopharmacology: The Fourth Generation of Progress, 1995, Genetic influences in drug abuse.	—	—	—
Welzl, H et al., News Physiol Sci, 2003, Cell adhesion molecules: key players in memory consolidation?	12869614	10.1152/nips.01422.2002	Cited
Zeggini, E et al., Nat Genet, 2008, Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes.	18372903	10.1038/ng.120	Cited

In this knowledge base

Title	Year	PMID
The genetic epidemiology of substance use disorder: A review.	2017	28938182
Examining the role of common genetic variants on alcohol, tobacco, cannabis and illicit drug dependence: genetics of vulnerability to drug dependence.	2015	25424661
Implications of genome wide association studies for addiction: are our a priori assumptions all wrong?	2013	23872493
Genomic regions identified by overlapping clusters of nominally-positive SNPs from genome-wide studies of alcohol and illegal substance dependence.	2011	21818250
Strong association of the alcohol dehydrogenase 1B gene (ADH1B) with alcohol dependence and alcohol-induced medical diseases.	2011	21497796

External

Title	Authors	Journal	Year	Link
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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.	Chang XW et al.	—	2022	→
Genetic basis of variation in cocaine and methamphetamine consumption in outbred populations of <i>Drosophila melanogaster</i>.	Baker BM et al.	—	2021	→
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Identification of novel risk loci with shared effects on alcoholism, heroin, and methamphetamine dependence.	Sun Y et al.	—	2021	→
LAR Receptor Tyrosine Phosphatase Family in Healthy and Diseased Brain.	Cornejo F et al.	—	2021	→
Attention-deficit/hyperactivity disorder and lifetime cannabis use: genetic overlap and causality.	Soler Artigas M et al.	—	2020	→
Prospects for finding the mechanisms of sex differences in addiction with human and model organism genetic analysis.	Datta U et al.	—	2020	→
The Streetlight Effect: Reappraising the Study of Addiction in Light of the Findings of Genome-wide Association Studies.	Hall FS et al.	—	2020	→
Molecular Imaging of Opioid and Dopamine Systems: Insights Into the Pharmacogenetics of Opioid Use Disorders.	Burns JA et al.	—	2019	→
Multivariate Analyses Reveal Biological Components Related to Neuronal Signaling and Immunity Mediating Electroencephalograms Abnormalities in Alcohol-Dependent Individuals from the Collaborative Study on the Genetics of Alcoholism Cohort.	Meda SA et al.	—	2019	→
β1-Integrins in the Developing Orbitofrontal Cortex Are Necessary for Expectancy Updating in Mice.	DePoy LM et al.	—	2019	→
Persistent accumulation of unrepaired DNA damage in rat cortical neurons: nuclear organization and ChIP-seq analysis of damaged DNA.	Mata-Garrido J et al.	—	2018	→
The Role of Cell Adhesion Molecule Genes Regulating Neuroplasticity in Addiction.	Muskiewicz DE et al.	—	2018	→
Blunted Dopamine Transmission in Addiction: Potential Mechanisms and Implications for Behavior.	Trifilieff P et al.	—	2017	→
Inferring pathobiology from structural MRI in schizophrenia and bipolar disorder: Modeling head motion and neuroanatomical specificity.	Yao N et al.	—	2017	→
The genetic epidemiology of substance use disorder: A review.	Prom-Wormley EC et al.	—	2017	→
Genetic deletion of fibroblast growth factor 14 recapitulates phenotypic alterations underlying cognitive impairment associated with schizophrenia.	Alshammari TK et al.	—	2016	→
Altered CSMD1 Expression Alters Cocaine-Conditioned Place Preference: Mutual Support for a Complex Locus from Human and Mouse Models.	Drgonova J et al.	—	2015	→
Examining the role of common genetic variants on alcohol, tobacco, cannabis and illicit drug dependence: genetics of vulnerability to drug dependence.	Palmer RH et al.	—	2015	→
Mouse Model for Protein Tyrosine Phosphatase D (<i>PTPRD</i>) Associations with Restless Leg Syndrome or Willis-Ekbom Disease and Addiction: Reduced Expression Alters Locomotion, Sleep Behaviors and Cocaine-Conditioned Place Preference.	Drgonova J et al.	—	2015	→
Synaptic Cytoskeletal Plasticity in the Prefrontal Cortex Following Psychostimulant Exposure.	DePoy LM et al.	—	2015	→
Transcriptomic and genetic studies identify NFAT5 as a candidate gene for cocaine dependence.	Fernàndez-Castillo N et al.	—	2015	→
Addiction science: Uncovering neurobiological complexity.	Volkow ND et al.	—	2014	→
Re-defininG AddiC(CH3)Tion: genomics and epigenomics on substance use disorders.	Rutter JL et al.	—	2014	→
Smoking quit success genotype score predicts quit success and distinct patterns of developmental involvement with common addictive substances.	Uhl GR et al.	—	2014	→
Association study of 37 genes related to serotonin and dopamine neurotransmission and neurotrophic factors in cocaine dependence.	Fernàndez-Castillo N et al.	—	2013	→
Cytoskeletal determinants of stimulus-response habits.	Gourley SL et al.	—	2013	→
Implications of genome wide association studies for addiction: are our a priori assumptions all wrong?	Hall FS et al.	—	2013	→
Arg kinase regulates prefrontal dendritic spine refinement and cocaine-induced plasticity.	Gourley SL et al.	—	2012	→
Association mapping of height and maturity across five environments using the sorghum mini core collection.	Upadhyaya HD et al.	—	2012	→
Genetics of dopamine receptors and drug addiction.	Gorwood P et al.	—	2012	→
Individual differences in the effects of environmental stimuli on cocaine choice in socially housed male cynomolgus monkeys.	Czoty PW et al.	—	2012	→
Addiction as a systems failure: focus on adolescence and smoking.	Baler RD et al.	—	2011	→
Genome-wide association studies of alcohol dependence and substance use disorders.	Treutlein J et al.	—	2011	→
Genome-wide Association study using pooled DNA to identify candidate markers mediating susceptibility to postoperative nausea and vomiting.	Janicki PK et al.	—	2011	→
Genomic regions identified by overlapping clusters of nominally-positive SNPs from genome-wide studies of alcohol and illegal substance dependence.	Johnson C et al.	—	2011	→
Menthol preference among smokers: association with TRPA1 variants.	Uhl GR et al.	—	2011	→
Meta-analysis and genome-wide interpretation of genetic susceptibility to drug addiction.	Li CY et al.	—	2011	→
"Replicated" genome wide association for dependence on illegal substances: genomic regions identified by overlapping clusters of nominally positive SNPs.	Drgon T et al.	—	2011	→
Strong association of the alcohol dehydrogenase 1B gene (ADH1B) with alcohol dependence and alcohol-induced medical diseases.	Li D et al.	—	2011	→