2017
Genome-wide association study identifies a novel locus for cannabis dependence
Agrawal A, Chou YL, Carey CE, Baranger DAA, Zhang B, Sherva R, Wetherill L, Kapoor M, Wang JC, Bertelsen S, Anokhin AP, Hesselbrock V, Kramer J, Lynskey MT, Meyers JL, Nurnberger JI, Rice JP, Tischfield J, Bierut LJ, Degenhardt L, Farrer LA, Gelernter J, Hariri AR, Heath AC, Kranzler HR, Madden PAF, Martin NG, Montgomery GW, Porjesz B, Wang T, Whitfield JB, Edenberg HJ, Foroud T, Goate AM, Bogdan R, Nelson EC. Genome-wide association study identifies a novel locus for cannabis dependence. Molecular Psychiatry 2017, 23: 1293-1302. PMID: 29112194, PMCID: PMC5938138, DOI: 10.1038/mp.2017.200.Peer-Reviewed Original ResearchMeSH KeywordsAdultAllelesBlack or African AmericanCannabisCase-Control StudiesChromosomes, Human, Pair 10Cohort StudiesFemaleGene FrequencyGenetic Predisposition to DiseaseGenome-Wide Association StudyGenotypeHumansMaleMarijuana AbuseMiddle AgedPhenotypePolymorphism, Single NucleotideWhite PeopleYoung AdultConceptsWide significant lociSingle nucleotide polymorphismsSignificant lociGenome-wide significant lociGenome-wide association study dataGenome-wide association studiesAssociation study dataCorrelated single-nucleotide polymorphismsNovel lociTranscription factorsChromosome 10Association studiesModerate heritabilityNovel regionLociBiological contributionEA college studentsMinor alleleEuropean descentH3K4me1Criterion countsHeritabilityPhenotypeEnhancerIndependent cohort
2016
Meta-Analyses of Genome-Wide Association Data Hold New Promise for Addiction Genetics.
Agrawal A, Edenberg HJ, Gelernter J. Meta-Analyses of Genome-Wide Association Data Hold New Promise for Addiction Genetics. Journal Of Studies On Alcohol And Drugs 2016, 77: 676-80. PMID: 27588522, PMCID: PMC5015465, DOI: 10.15288/jsad.2016.77.676.Peer-Reviewed Original Research
2014
Genetic risk prediction and neurobiological understanding of alcoholism
Levey DF, Le-Niculescu H, Frank J, Ayalew M, Jain N, Kirlin B, Learman R, Winiger E, Rodd Z, Shekhar A, Schork N, Kiefe F, Wodarz N, Müller-Myhsok B, Dahmen N, Nöthen M, Sherva R, Farrer L, Smith A, Kranzler H, Rietschel M, Gelernter J, Niculescu A. Genetic risk prediction and neurobiological understanding of alcoholism. Translational Psychiatry 2014, 4: e391-e391. PMID: 24844177, PMCID: PMC4035721, DOI: 10.1038/tp.2014.29.Peer-Reviewed Original ResearchConceptsTop candidate genesCandidate genesGenetic risk predictionGenome-wide association study dataFunctional genomics approachConvergent functional genomics approachAssociation study dataGene expression dataInitial discovery stepGenomic approachesKey genesSignal transductionSignificant genetic overlapTop genesRelevant genesBiological pathwaysExpression dataTop findingsGenesStrict Bonferroni correctionGenetic overlapProtein knockout miceSmall panelFatty acidsKnockout mice