2021
Multivariate analysis of 1.5 million people identifies genetic associations with traits related to self-regulation and addiction
Karlsson Linnér R, Mallard TT, Barr PB, Sanchez-Roige S, Madole JW, Driver MN, Poore HE, de Vlaming R, Grotzinger AD, Tielbeek JJ, Johnson EC, Liu M, Rosenthal SB, Ideker T, Zhou H, Kember RL, Pasman JA, Verweij KJH, Liu DJ, Vrieze S, Kranzler H, Gelernter J, Harris K, Tucker-Drob E, Waldman I, Palmer A, Harden K, Koellinger P, Dick D. Multivariate analysis of 1.5 million people identifies genetic associations with traits related to self-regulation and addiction. Nature Neuroscience 2021, 24: 1367-1376. PMID: 34446935, PMCID: PMC8484054, DOI: 10.1038/s41593-021-00908-3.Peer-Reviewed Original ResearchMeSH KeywordsAttention Deficit Disorder with HyperactivityBehavior, AddictiveBehavioral SymptomsComputational BiologyCrimeGenetic Association StudiesGenome-Wide Association StudyHIV InfectionsHumansMeta-Analysis as TopicMultifactorial InheritanceMultivariate AnalysisOpioid-Related DisordersReproducibility of ResultsSelf-ControlSuicideUnemployment
2018
Inferring phenotypes from substance use via collaborative matrix completion
Lu J, Sun J, Wang X, Kranzler H, Gelernter J, Bi J. Inferring phenotypes from substance use via collaborative matrix completion. BMC Systems Biology 2018, 12: 104. PMID: 30463556, PMCID: PMC6249733, DOI: 10.1186/s12918-018-0623-5.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsComputational BiologyFemaleGenotypeHumansMaleModels, StatisticalPhenotypeSubstance-Related DisordersConceptsRecent statistical methodsMatrix completion techniqueMatrix completionStatistical modelingStatistical methodsPhenotype imputationSpeed 20 timesBi-linear modelImputation methodsParallel algorithmSequential algorithmMultiple scalesSimilar genetic determinantsGood accuracyAlgorithmNew approachCompletion techniquesSample sizeAccuracyModelRisk Locus Identification Ties Alcohol Withdrawal Symptoms to SORCS2
Smith AH, Ovesen PL, Skeldal S, Yeo S, Jensen KP, Olsen D, Diazgranados N, Zhao H, Farrer LA, Goldman D, Glerup S, Kranzler HR, Nykjær A, Gelernter J. Risk Locus Identification Ties Alcohol Withdrawal Symptoms to SORCS2. Alcohol Clinical And Experimental Research 2018, 42: 2337-2348. PMID: 30252935, PMCID: PMC6317871, DOI: 10.1111/acer.13890.Peer-Reviewed Original ResearchConceptsAlcohol withdrawalEpigenomic data setsGenome-wide association studiesWide significant findingsLife-threatening seizuresAlcohol withdrawal symptomsTop association signalsTissue-specific activityNeural lineage cellsGenetic risk factorsHarmful alcohol useAssociation signalsRegulatory elementsBioinformatics analysisStress hormone levelsAlcohol cessationChromosome 4Neurotrophic factorWithdrawal symptomsRisk factorsEthanol exposureHormone levelsAssociation studiesNervous systemAdditional genotyping
2017
Widespread signatures of positive selection in common risk alleles associated to autism spectrum disorder
Polimanti R, Gelernter J. Widespread signatures of positive selection in common risk alleles associated to autism spectrum disorder. PLOS Genetics 2017, 13: e1006618. PMID: 28187187, PMCID: PMC5328401, DOI: 10.1371/journal.pgen.1006618.Peer-Reviewed Original ResearchMeSH KeywordsAllelesAttention Deficit Disorder with HyperactivityAutism Spectrum DisorderBipolar DisorderBrainComputational BiologyDepressive Disorder, MajorGene Expression ProfilingGene OntologyGene Regulatory NetworksGenetic Predisposition to DiseaseGenome-Wide Association StudyGenomicsHumansPituitary GlandPolymorphism, Single NucleotideRisk FactorsSchizophreniaTranscriptomeConceptsPositive selectionGene Ontology enrichmentGene expression enrichmentPrevious genetic studiesGWAS summary statisticsNervous system developmentCommon risk allelesPsychiatric Genomics ConsortiumSystems geneticsOntology enrichmentRisk allelesSynapse organizationWidespread signaturesEvolutionary processesGenetic studiesGenomics ConsortiumGWASHuman evolutionAllelesIncomplete selectionEffect directionMinor alleleComplete selectionEnrichmentSummary statisticsAlcohol and nicotine codependence-associated DNA methylation changes in promoter regions of addiction-related genes
Xu H, Wang F, Kranzler HR, Gelernter J, Zhang H. Alcohol and nicotine codependence-associated DNA methylation changes in promoter regions of addiction-related genes. Scientific Reports 2017, 7: 41816. PMID: 28165486, PMCID: PMC5292964, DOI: 10.1038/srep41816.Peer-Reviewed Original Research
2014
Differentially co-expressed genes in postmortem prefrontal cortex of individuals with alcohol use disorders: influence on alcohol metabolism-related pathways
Zhang H, Wang F, Xu H, Liu Y, Liu J, Zhao H, Gelernter J. Differentially co-expressed genes in postmortem prefrontal cortex of individuals with alcohol use disorders: influence on alcohol metabolism-related pathways. Human Genetics 2014, 133: 1383-1394. PMID: 25073604, PMCID: PMC4185230, DOI: 10.1007/s00439-014-1473-x.Peer-Reviewed Original ResearchConceptsCo-expressed genesGenome-wide association studiesHumanHT-12 v4 Expression BeadChipGene modulesPostmortem prefrontal cortexGene co-expression network analysisCo-expression network analysisDAVID Bioinformatics ResourcesGene expression alterationsMetabolism-related pathwaysV4 Expression BeadChipCellular functionsTranscriptome profilesFatty acid metabolismBioinformatics resourcesEnrichment analysisExpression probesBiological pathwaysAssociation studiesAldehyde detoxificationExpression alterationsGenesMitochondrial functionBrain reward regionsAcid metabolismIdentification of methylation quantitative trait loci (mQTLs) influencing promoter DNA methylation of alcohol dependence risk genes
Zhang H, Wang F, Kranzler HR, Yang C, Xu H, Wang Z, Zhao H, Gelernter J. Identification of methylation quantitative trait loci (mQTLs) influencing promoter DNA methylation of alcohol dependence risk genes. Human Genetics 2014, 133: 1093-1104. PMID: 24889829, PMCID: PMC4127343, DOI: 10.1007/s00439-014-1452-2.Peer-Reviewed Original ResearchConceptsMethylation quantitative trait lociQuantitative trait lociDNA methylationTrait lociSignificant methylation quantitative trait lociSequence variantsRisk genesGene expression regulationGenome-wide association studiesGenome-wide genotype dataPromoter DNA methylationAD risk genesGene promoter regionExpression QTLsExpression regulationGenetic variationPromoter CpGsPromoter region
2013
Integrating GWASs and Human Protein Interaction Networks Identifies a Gene Subnetwork Underlying Alcohol Dependence
Han S, Yang BZ, Kranzler HR, Liu X, Zhao H, Farrer LA, Boerwinkle E, Potash JB, Gelernter J. Integrating GWASs and Human Protein Interaction Networks Identifies a Gene Subnetwork Underlying Alcohol Dependence. American Journal Of Human Genetics 2013, 93: 1027-1034. PMID: 24268660, PMCID: PMC3853414, DOI: 10.1016/j.ajhg.2013.10.021.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesHuman protein interaction networkGene subnetworksProtein interaction networksIntegrating Genome-Wide Association StudyInteraction networksHuman complex disordersSubnetworks of genesGWAS data setsFunctional enrichment analysisAD risk genesEnrichment analysisProtein productsAssociation studiesSignificant genetic contributionGenesGenetics of AlcoholismStudy of AddictionGenetic contributionGeneticsComplex disorderAD etiologyCation transportImportant cluesEuropean descentAssociation of Gamma-Aminobutyric Acid A Receptor α2 Gene (GABRA2) with Alcohol Use Disorder
Li D, Sulovari A, Cheng C, Zhao H, Kranzler HR, Gelernter J. Association of Gamma-Aminobutyric Acid A Receptor α2 Gene (GABRA2) with Alcohol Use Disorder. Neuropsychopharmacology 2013, 39: 907-918. PMID: 24136292, PMCID: PMC3924525, DOI: 10.1038/npp.2013.291.Peer-Reviewed Original ResearchConceptsReceptor geneGABA receptor genesGABAA receptor genesCandidate gene association studiesSAGE data setsBonferroni-corrected thresholdGene association studiesSingle nucleotide polymorphismsAssociation studiesGenotype dataStudy of AddictionGamma-aminobutyric acidMammalian brainGenesComplex disorderGABRA2 single nucleotide polymorphismsSubstance dependenceMajor inhibitory neurotransmitterGeneticsInhibitory neurotransmitterVariantsGABA receptorsSignificant associationSubstance abuseMethamphetamine dependenceVariant Callers for Next-Generation Sequencing Data: A Comparison Study
Liu X, Han S, Wang Z, Gelernter J, Yang BZ. Variant Callers for Next-Generation Sequencing Data: A Comparison Study. PLOS ONE 2013, 8: e75619. PMID: 24086590, PMCID: PMC3785481, DOI: 10.1371/journal.pone.0075619.Peer-Reviewed Original Research
2011
M3: an improved SNP calling algorithm for Illumina BeadArray data
Li G, Gelernter J, Kranzler HR, Zhao H. M3: an improved SNP calling algorithm for Illumina BeadArray data. Bioinformatics 2011, 28: 358-365. PMID: 22155947, PMCID: PMC3268244, DOI: 10.1093/bioinformatics/btr673.Peer-Reviewed Original Research