2024
A multi-ancestry genetic study of pain intensity in 598,339 veterans
Toikumo S, Vickers-Smith R, Jinwala Z, Xu H, Saini D, Hartwell E, Pavicic M, Sullivan K, Xu K, Jacobson D, Gelernter J, Rentsch C, Stahl E, Cheatle M, Zhou H, Waxman S, Justice A, Kember R, Kranzler H. A multi-ancestry genetic study of pain intensity in 598,339 veterans. Nature Medicine 2024, 30: 1075-1084. PMID: 38429522, DOI: 10.1038/s41591-024-02839-5.Peer-Reviewed Original ResearchPain intensityChronic painTreat chronic painCalcium channel blockersCross-ancestry meta-analysisGenome-wide association studiesExperience of painSamples of European ancestryPain phenotypesFunctional genomics dataGABAergic neuronsCalcium channelsAnalgesic effectB-blockersDrug groupMillion Veteran ProgramPainSubstance use disordersQuality of lifeDrug repurposing analysisOpioid crisisGenetic architectureCausal genesGenetic lociGenomic data
2023
Identifying genetic loci and phenomic associations of substance use traits: A multi‐trait analysis of GWAS (MTAG) study
Xu H, Toikumo S, Crist R, Glogowska K, Jinwala Z, Deak J, Justice A, Gelernter J, Johnson E, Kranzler H, Kember R. Identifying genetic loci and phenomic associations of substance use traits: A multi‐trait analysis of GWAS (MTAG) study. Addiction 2023, 118: 1942-1952. PMID: 37156939, PMCID: PMC10754226, DOI: 10.1111/add.16229.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesSignificant single nucleotide polymorphismsSubstance use traitsMulti-trait analysisAssociation studiesGenetic architectureUse traitsGenome-wide significant single nucleotide polymorphismsProtein-protein interaction analysisTrait genetic architectureNumber of lociPolygenic risk scoresEuropean ancestry individualsNovel lociSingle nucleotide polymorphismsGenetic lociGWAS studiesLociMultiple related phenotypesNucleotide polymorphismsRelated phenotypesTraitsNovel associationsMTAgBiobank samples
2022
Genome-Wide Investigation of Maximum Habitual Alcohol Intake in US Veterans in Relation to Alcohol Consumption Traits and Alcohol Use Disorder
Deak JD, Levey DF, Wendt FR, Zhou H, Galimberti M, Kranzler HR, Gaziano JM, Stein MB, Polimanti R, Gelernter J, Muralidhar S, Moser J, Deen J, Gaziano J, Beckham J, Chang K, Tsao P, Luoh S, Casas J, Churby L, Whitbourne S, Brewer J, Brophy M, Selva L, Shayan S, Cho K, Pyarajan S, DuVall S, Connor T, Argyres D, Aslan M, Stephens B, Concato J, Gelernter J, Gleason T, Huang G, Koenen K, Marx C, Radhakrishnan K, Schork N, Stein M, Zhao H, Kaufman J, Nunez Y, Pietrzak R, Beck D, Cissell S, Crutchfield P, Lance W, Cheung K, Li Y, Sun N, Chen Q, Rajeevan N, Sayward F, Gagnon D, Harrington K, Quaden R, O'Leary T, Ramoni R. Genome-Wide Investigation of Maximum Habitual Alcohol Intake in US Veterans in Relation to Alcohol Consumption Traits and Alcohol Use Disorder. JAMA Network Open 2022, 5: e2238880. PMID: 36301540, PMCID: PMC9614582, DOI: 10.1001/jamanetworkopen.2022.38880.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesGenome-wide significant lociGenomic structural equation modelingSignificant lociAlcohol traitsAssociation studiesAfrican ancestry participantsGenome-wide investigationAncestry-specific genome-wide association studiesGenetic correlationsPsychiatric traitsLinkage disequilibrium score regressionGenetic associationStrong genetic correlationSingle nucleotide variantsGenetic architectureGenetic association studiesGenetic lociTop associationsNegative rgEuropean ancestry participantsNucleotide variantsFunctional variantsScore regressionTraitsIntegrating human brain proteomic data with genome-wide association study findings identifies novel brain proteins in substance use traits
Toikumo S, Xu H, Gelernter J, Kember RL, Kranzler HR. Integrating human brain proteomic data with genome-wide association study findings identifies novel brain proteins in substance use traits. Neuropsychopharmacology 2022, 47: 2292-2299. PMID: 35941285, PMCID: PMC9630289, DOI: 10.1038/s41386-022-01406-1.Peer-Reviewed Original ResearchConceptsSubstance use traitsProteome-wide association studyUse traitsProtein abundanceAssociation studiesBrain protein abundanceWide association studyGenome-wide association study summary statisticsHuman brain proteomeFine-mapping analysisGenetic risk lociBrain transcriptomic dataEuropean ancestry individualsOpioid use disorderProteomic abundanceTranscriptomic levelTranscriptomic dataAlcohol use disorderProteomic dataBrain proteomeGenetic lociTranscript levelsRisk lociGene expressionSignificant genes
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
2020
A large-scale genome-wide association study meta-analysis of cannabis use disorder
Johnson EC, Demontis D, Thorgeirsson TE, Walters RK, Polimanti R, Hatoum AS, Sanchez-Roige S, Paul SE, Wendt FR, Clarke TK, Lai D, Reginsson GW, Zhou H, He J, Baranger DAA, Gudbjartsson DF, Wedow R, Adkins DE, Adkins AE, Alexander J, Bacanu SA, Bigdeli TB, Boden J, Brown SA, Bucholz KK, Bybjerg-Grauholm J, Corley RP, Degenhardt L, Dick DM, Domingue BW, Fox L, Goate AM, Gordon SD, Hack LM, Hancock DB, Hartz SM, Hickie IB, Hougaard DM, Krauter K, Lind PA, McClintick JN, McQueen MB, Meyers JL, Montgomery GW, Mors O, Mortensen PB, Nordentoft M, Pearson JF, Peterson RE, Reynolds MD, Rice JP, Runarsdottir V, Saccone NL, Sherva R, Silberg JL, Tarter RE, Tyrfingsson T, Wall TL, Webb BT, Werge T, Wetherill L, Wright MJ, Zellers S, Adams MJ, Bierut LJ, Boardman JD, Copeland WE, Farrer LA, Foroud TM, Gillespie NA, Grucza RA, Harris KM, Heath AC, Hesselbrock V, Hewitt JK, Hopfer CJ, Horwood J, Iacono WG, Johnson EO, Kendler KS, Kennedy MA, Kranzler HR, Madden PAF, Maes HH, Maher BS, Martin NG, McGue M, McIntosh AM, Medland SE, Nelson EC, Porjesz B, Riley BP, Stallings MC, Vanyukov MM, Vrieze S, Workgroup P, Walters R, Polimanti R, Johnson E, McClintick J, Hatoum A, He J, Wendt F, Zhou H, Adams M, Adkins A, Aliev F, Bacanu S, Batzler A, Bertelsen S, Biernacka J, Bigdeli T, Chen L, Clarke T, Chou Y, Degenhardt F, Docherty A, Edwards A, Fontanillas P, Foo J, Fox L, Frank J, Giegling I, Gordon S, Hack L, Hartmann A, Hartz S, Heilmann-Heimbach S, Herms S, Hodgkinson C, Hoffman P, Hottenga J, Kennedy M, Alanne-Kinnunen M, Konte B, Lahti J, Lahti-Pulkkinen M, Lai D, Ligthart L, Loukola A, Maher B, Mbarek H, McIntosh A, McQueen M, Meyers J, Milaneschi Y, Palviainen T, Pearson J, Peterson R, Ripatti S, Ryu E, Saccone N, Salvatore J, Sanchez-Roige S, Schwandt M, Sherva R, Streit F, Strohmaier J, Thomas N, Wang J, Webb B, Wedow R, Wetherill L, Wills A, Boardman J, Chen D, Choi D, Copeland W, Culverhouse R, Dahmen N, Degenhardt L, Domingue B, Elson S, Frye M, Gäbel W, Hayward C, Ising M, Keyes M, Kiefer F, Kramer J, Kuperman S, Lucae S, Lynskey M, Maier W, Mann K, Männistö S, Müller-Myhsok B, Murray A, Nurnberger J, Palotie A, Preuss U, Räikkönen K, Reynolds M, Ridinger M, Scherbaum N, Schuckit M, Soyka M, Treutlein J, Witt S, Wodarz N, Zill P, Adkins D, Boden J, Boomsma D, Bierut L, Brown S, Bucholz K, Cichon S, Costello E, de Wit H, Diazgranados N, Dick D, Eriksson J, Farrer L, Foroud T, Gillespie N, Goate A, Goldman D, Grucza R, Hancock D, Harris K, Heath A, Hesselbrock V, Hewitt J, Hopfer C, Horwood J, Iacono W, Johnson E, Kaprio J, Karpyak V, Kendler K, Kranzler H, Krauter K, Lichtenstein P, Lind P, McGue M, MacKillop J, Madden P, Maes H, Magnusson P, Martin N, Medland S, Montgomery G, Nelson E, Nöthen M, Palmer A, Pederson N, Penninx B, Porjesz B, Rice J, Rietschel M, Riley B, Rose R, Rujescu D, Shen P, Silberg J, Stallings M, Tarter R, Vanyukov M, Vrieze S, Wall T, Whitfield J, Zhao H, Neale B, Gelernter J, Edenberg H, Agrawal A, Davis L, Bogdan R, Gelernter J, Edenberg H, Stefansson K, Børglum A, Agrawal A. A large-scale genome-wide association study meta-analysis of cannabis use disorder. The Lancet Psychiatry 2020, 7: 1032-1045. PMID: 33096046, PMCID: PMC7674631, DOI: 10.1016/s2215-0366(20)30339-4.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesAssociation studiesGenome-wide significant lociLarge-scale genome-wide association studiesGenetic correlationsChromosome 7 locusTraits of interestLarge genome-wide association studiesLinkage disequilibrium score regressionChromosome 8 locusDifferent genetic underpinningsDifferent genetic correlationsWellcome Trust Case Control ConsortiumDisequilibrium score regressionNovel genetic variantsStrong genetic componentSignificant lociGenetic lociGenetic underpinningsGenetic componentLociScore regressionGenetic variantsGenetic overlapIntegrative sequencingA genome-wide association study of cocaine use disorder accounting for phenotypic heterogeneity and gene–environment interaction
Sun J, Kranzler HR, Gelernter J, Bi J. A genome-wide association study of cocaine use disorder accounting for phenotypic heterogeneity and gene–environment interaction. Journal Of Psychiatry And Neuroscience 2020, 45: 34-44. PMID: 31490055, PMCID: PMC6919916, DOI: 10.1503/jpn.180098.Peer-Reviewed Original ResearchConceptsGenetic lociGenome-wide association testsPhenotypic heterogeneityNew genetic lociGenetic variantsWide association studyGene-environment interplayNovel genetic variantsHigh heritability estimatesSignificant genomeReplication sampleSingle nucleotide polymorphismsGenetic variationAssociation studiesLociNucleotide polymorphismsAssociation TestHeritability estimatesGene-environment interactionsReplication resultsCluster analysisEnvironmental factorsTRAK2GenomeDiscovery phase
2015
Dissecting ancestry genomic background in substance dependence genome-wide association studies
Polimanti R, Yang C, Zhao H, Gelernter J. Dissecting ancestry genomic background in substance dependence genome-wide association studies. Pharmacogenomics 2015, 16: 1487-1498. PMID: 26267224, PMCID: PMC4632979, DOI: 10.2217/pgs.15.91.Peer-Reviewed Original ResearchMeSH KeywordsAlcoholismAlgorithmsAllelesBlack or African AmericanGene FrequencyGene-Environment InteractionGenetic Predisposition to DiseaseGenetic VariationGenome-Wide Association StudyHaplotypesHumansMolecular Sequence AnnotationOpioid-Related DisordersSubstance-Related DisordersTobacco Use DisorderWhite PeopleConceptsGenome-wide association studiesGenomic backgroundFunctional allelesAssociation studiesCommon functional allelesWide association studyLocal haplotype structureGenetic lociSD traitHaplotype structureRelevant genesGenesLociInteractive partnersPopulation diversityHigh frequency differencesAllelesFrequency differenceGenomeTraitsDiversityRoleVariants
2001
Linkage genome scan for loci predisposing to panic disorder or agoraphobia
Gelernter J, Bonvicini K, Page G, Woods S, Goddard A, Kruger S, Pauls D, Goodson S. Linkage genome scan for loci predisposing to panic disorder or agoraphobia. American Journal Of Medical Genetics 2001, 105: 548-557. PMID: 11496373, DOI: 10.1002/ajmg.1496.Peer-Reviewed Original ResearchMeSH KeywordsAgoraphobiaChromosome MappingChromosomes, Human, Pair 1Chromosomes, Human, Pair 11Chromosomes, Human, Pair 14Chromosomes, Human, Pair 3Chromosomes, Human, Pair 4Family HealthFemaleGenetic Predisposition to DiseaseGenome, HumanHumansLod ScoreMaleMicrosatellite RepeatsPanic DisorderPedigreeConceptsLinkage genome scanGenome scanChromosome 3LOD scoreSuggestive linkagePrevious genome scanComplex traitsGenomic regionsHeritable anxiety disordersGenetic lociMultipoint LOD scoreCandidate genesRisk lociChromosome 1Chromosome 11pSusceptibility lociLociStatistical supportLinkage resultsNPL analysisPotential lociNPL scoreAmerican pedigreesSingle familyPotential linkage
1995
Linkage mapping of serotonin transporter protein gene SLC6A4 on chromosome 17
Gelernter J, Pakstis AJ, Kidd KK. Linkage mapping of serotonin transporter protein gene SLC6A4 on chromosome 17. Human Genetics 1995, 95: 677-680. PMID: 7789954, DOI: 10.1007/bf00209486.Peer-Reviewed Original ResearchConceptsRestriction fragment length polymorphismTransporter proteinsTransporter protein geneSerotonin transporter protein geneNorepinephrine transporter proteinLinkage mapLinkage mappingProtein geneChromosome 16q21Genetic lociCandidate genesUntranslated regionFragment length polymorphismChromosome 17GenesLinkage resultsSitu hybridizationGene SLC6A4Length polymorphismLinkage studiesPCR productsProximal 17qProteinLogical candidate geneSLC6A4