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
9. THE GENETIC ARCHITECTURE OF PAIN INTENSITY IN THE MILLION VETERAN PROGRAM
Toikumo S, Vickers-Smith R, Jinwala Z, Xu H, Saini D, Hartwell E, Pavicic M, Sullivan K, Jacobson D, Cheatle M, Zhou H, Waxman S, Justice A, Kember R, Kranzler H. 9. THE GENETIC ARCHITECTURE OF PAIN INTENSITY IN THE MILLION VETERAN PROGRAM. European Neuropsychopharmacology 2023, 75: s60-s61. DOI: 10.1016/j.euroneuro.2023.08.120.Peer-Reviewed Original ResearchIndependent lociGenetic architectureMillion Veteran ProgramGenome-wide association testingIndependent genetic lociLinkage disequilibrium score regressionDrug-gene interaction databaseDisequilibrium score regressionNovel genetic variantsPotential drug targetsComplex traitsGWAS resultsCausal genesDruggable genomeDrug repurposing analysisGenetic lociDruggable genesInteraction databasesDrug targetsGenetic correlationsMolecular contributorsAssociation testingLociPsychiatric traitsScore regressionIdentifying 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 association study in individuals of European and African ancestry and multi-trait analysis of opioid use disorder identifies 19 independent genome-wide significant risk loci
Deak JD, Zhou H, Galimberti M, Levey DF, Wendt FR, Sanchez-Roige S, Hatoum AS, Johnson EC, Nunez YZ, Demontis D, Børglum AD, Rajagopal VM, Jennings MV, Kember RL, Justice AC, Edenberg HJ, Agrawal A, Polimanti R, Kranzler HR, Gelernter J. Genome-wide association study in individuals of European and African ancestry and multi-trait analysis of opioid use disorder identifies 19 independent genome-wide significant risk loci. Molecular Psychiatry 2022, 27: 3970-3979. PMID: 35879402, PMCID: PMC9718667, DOI: 10.1038/s41380-022-01709-1.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesGenome-wide significant risk lociAssociation studiesVariant associationsLarge-scale genome-wide association studiesGenetic correlationsSignificant risk lociPsychiatric Genomics ConsortiumMulti-trait analysisPolygenic risk score analysisSingle-variant associationsGWS lociGenetic architectureIndividuals of EuropeanGWS associationsRisk lociGene regionGenomics ConsortiumMillion Veteran ProgramSusceptibility lociAfrican ancestryLociRisk score analysisGenetic informativenessSNPs one
2020
Genome-wide meta-analysis of problematic alcohol use in 435,563 individuals yields insights into biology and relationships with other traits
Zhou H, Sealock JM, Sanchez-Roige S, Clarke TK, Levey DF, Cheng Z, Li B, Polimanti R, Kember RL, Smith RV, Thygesen JH, Morgan MY, Atkinson SR, Thursz MR, Nyegaard M, Mattheisen M, Børglum AD, Johnson EC, Justice AC, Palmer AA, McQuillin A, Davis LK, Edenberg HJ, Agrawal A, Kranzler HR, Gelernter J. Genome-wide meta-analysis of problematic alcohol use in 435,563 individuals yields insights into biology and relationships with other traits. Nature Neuroscience 2020, 23: 809-818. PMID: 32451486, PMCID: PMC7485556, DOI: 10.1038/s41593-020-0643-5.Peer-Reviewed Original ResearchConceptsRegulatory genomic regionsGenome-wide association studiesNovel risk lociEuropean ancestry individualsPolygenic risk score analysisIndependent risk variantsGenetic architectureGenomic regionsRisk lociAssociation studiesGenetic relationshipsRisk genesGenetic correlationsPsychiatric traitsRisk variantsRisk score analysisTraitsGenetic heritabilityYields insightsBiobank samplesMendelian randomizationGenesLociBiologyHeritability
2019
Retrospective Association Analysis of Longitudinal Binary Traits Identifies Important Loci and Pathways in Cocaine Use
Wu W, Wang Z, Xu K, Zhang X, Amei A, Gelernter J, Zhao H, Justice AC, Wang Z. Retrospective Association Analysis of Longitudinal Binary Traits Identifies Important Loci and Pathways in Cocaine Use. Genetics 2019, 213: 1225-1236. PMID: 31591132, PMCID: PMC6893384, DOI: 10.1534/genetics.119.302598.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesAssociation analysisGenome-wide association analysisCase-control genome-wide association studyPhenotype model misspecificationImportant locusGenetic architectureComplex traitsGenetic association analysisGene mappingGenome scanPathway analysisAssociation studiesAxonal guidanceGenetic variantsBinary traitsAssociation TestElectronic health record-based studiesPathwayImportant pathwayLociTraitsPhenotype distributionLongitudinal phenotypesPhenotype