2023
Do Polygenic Risk Scores Add to Clinical Data in Predicting Pancreatic Cancer? A Scoping Review.
Wang L, Grimshaw A, Mezzacappa C, Rahimi Larki N, Yang Y, Justice A. Do Polygenic Risk Scores Add to Clinical Data in Predicting Pancreatic Cancer? A Scoping Review. Cancer Epidemiology Biomarkers & Prevention 2023, 32: 1490-1497. PMID: 37610426, PMCID: PMC10873036, DOI: 10.1158/1055-9965.epi-23-0468.Peer-Reviewed Original ResearchMeSH KeywordsDatabases, FactualGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansMultifactorial InheritancePancreatic NeoplasmsRisk FactorsConceptsRoutine risk factorsPancreatic cancerRisk factorsPolygenic risk scoresClinical dataRisk scoreAddition of PRSClinical risk factorsRoutine clinical dataCancer risk predictionDatabase inceptionCancerClinical applicabilityRelevant exposuresGenetic riskRisk predictionCancer-specific polygenic risk scoresScoping ReviewRiskEuropean ancestryPopulation representativeScoresMost studiesAppropriate controlsFactorsGenetic Underpinnings of the Transition From Alcohol Consumption to Alcohol Use Disorder: Shared and Unique Genetic Architectures in a Cross-Ancestry Sample
Kember R, Vickers-Smith R, Zhou H, Xu H, Jennings M, Dao C, Davis L, Sanchez-Roige S, Justice A, Gelernter J, Vujkovic M, Kranzler H. Genetic Underpinnings of the Transition From Alcohol Consumption to Alcohol Use Disorder: Shared and Unique Genetic Architectures in a Cross-Ancestry Sample. American Journal Of Psychiatry 2023, 180: 584-593. PMID: 37282553, PMCID: PMC10731616, DOI: 10.1176/appi.ajp.21090892.Peer-Reviewed Original ResearchIdentifying 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 ResearchMeSH KeywordsAlcoholismGenetic LociGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansPhenomicsPhenotypePolymorphism, Single NucleotideConceptsGenome-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 samplesMulti-trait genome-wide association analyses leveraging alcohol use disorder findings identify novel loci for smoking behaviors in the Million Veteran Program
Cheng Y, Dao C, Zhou H, Li B, Kember R, Toikumo S, Zhao H, Gelernter J, Kranzler H, Justice A, Xu K. Multi-trait genome-wide association analyses leveraging alcohol use disorder findings identify novel loci for smoking behaviors in the Million Veteran Program. Translational Psychiatry 2023, 13: 148. PMID: 37147289, PMCID: PMC10162964, DOI: 10.1038/s41398-023-02409-2.Peer-Reviewed Original ResearchMeSH KeywordsAlcohol DrinkingAlcoholismGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansPhenotypePolymorphism, Single NucleotideSmokingVeteransConceptsSingle-trait genome-wide association studiesGenome-wide association studiesNovel lociPower of GWASJoint genome-wide association studyGenome-wide significant lociMillion Veteran ProgramGenome-wide associationSubstance use traitsGWAS summary statisticsNovel genetic variantsMulti-trait analysisFunctional annotationUse traitsSignificant lociHeritable traitMultiple lociAssociation studiesColocalization analysisLociPleiotropic effectsMTAgVeteran ProgramGenetic variantsTraits
2022
Cross-ancestry meta-analysis of opioid use disorder uncovers novel loci with predominant effects in brain regions associated with addiction
Kember RL, Vickers-Smith R, Xu H, Toikumo S, Niarchou M, Zhou H, Hartwell EE, Crist RC, Rentsch CT, Davis L, Justice A, Sanchez-Roige S, Kampman K, Gelernter J, Kranzler H. Cross-ancestry meta-analysis of opioid use disorder uncovers novel loci with predominant effects in brain regions associated with addiction. Nature Neuroscience 2022, 25: 1279-1287. PMID: 36171425, PMCID: PMC9682545, DOI: 10.1038/s41593-022-01160-z.Peer-Reviewed Original ResearchMeSH KeywordsBehavior, AddictiveBrainFurinGenome-Wide Association StudyHumansOpioid-Related DisordersConceptsOpioid use disorderGenome-wide association studiesWide significant lociGene expression enrichmentSignificant genetic correlationsCell type groupSignificant lociAssociation studiesExpression enrichmentMillion Veteran ProgramGenetic correlationsUse disordersLociBrain regionsExonic variantsIntronic variantsSubstance use disordersTraitsBiological basisOpioid epidemicPsychiatric disordersVeteran ProgramBrain diseasesTSNARE1FBXW4Genome-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 ResearchMeSH KeywordsAlcoholismBlack PeopleFurinGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansOpioid-Related DisordersPhenotypePolymorphism, Single NucleotideWhite PeopleConceptsGenome-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 oneValidation of a multi-ancestry polygenic risk score and age-specific risks of prostate cancer: A meta-analysis within diverse populations
Chen F, Darst BF, Madduri RK, Rodriguez AA, Sheng X, Rentsch CT, Andrews C, Tang W, Kibel AS, Plym A, Cho K, Jalloh M, Gueye SM, Niang L, Ogunbiyi OJ, Popoola O, Adebiyi AO, Aisuodionoe-Shadrach OI, Ajibola HO, Jamda MA, Oluwole OP, Nwegbu M, Adusei B, Mante S, Darkwa-Abrahams A, Mensah JE, Adjei AA, Diop H, Lachance J, Rebbeck TR, Ambs S, Gaziano JM, Justice AC, Conti DV, Haiman CA. Validation of a multi-ancestry polygenic risk score and age-specific risks of prostate cancer: A meta-analysis within diverse populations. ELife 2022, 11: e78304. PMID: 35801699, PMCID: PMC9322982, DOI: 10.7554/elife.78304.Peer-Reviewed Original ResearchMeSH KeywordsAge FactorsCase-Control StudiesGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansMaleMiddle AgedMultifactorial InheritanceProstatic NeoplasmsRisk FactorsUnited StatesConceptsProstate cancer riskPolygenic risk scoresProstate cancerCancer riskOdds ratioMillion Veteran ProgramRisk scoreRisk stratification toolAge-specific absolute risksAfrican ancestry menCancer odds ratiosVeterans Health AdministrationCase-control studyNonaggressive prostate cancerProstate Cancer FoundationAge-specific riskAssociation of PRSPRS categoriesRisk-stratified screeningVeteran ProgramNational Cancer InstituteEuropean ancestry menStratification toolAbsolute riskEffect modificationIdentifying intragenic functional modules of genomic variations associated with cancer phenotypes by learning representation of association networks
Kim M, Huffman JE, Justice A, Goethert I, Agasthya G, Danciu I. Identifying intragenic functional modules of genomic variations associated with cancer phenotypes by learning representation of association networks. BMC Medical Genomics 2022, 15: 151. PMID: 35794577, PMCID: PMC9258200, DOI: 10.1186/s12920-022-01298-6.Peer-Reviewed Original ResearchGenome-Wide Association StudyGenomicsHumansMalePhenotypeProstatic NeoplasmsReproducibility of ResultsSoluble CD14-associated DNA methylation sites predict mortality among men with HIV infection
Titanji BK, Wang Z, Chen J, Hui Q, So-Armah K, Freiberg M, Justice AC, Ke X, Marconi VC, Sun YV. Soluble CD14-associated DNA methylation sites predict mortality among men with HIV infection. AIDS 2022, 36: 1563-1571. PMID: 35979830, PMCID: PMC9394925, DOI: 10.1097/qad.0000000000003279.Peer-Reviewed Original ResearchMeSH KeywordsCohort StudiesDNA MethylationEpigenesis, GeneticGenome-Wide Association StudyHIV InfectionsHumansInflammationLipopolysaccharide ReceptorsMaleConceptsVeterans Aging Cohort StudyAging Cohort StudyElevated plasma levelsCox regression modelUnderstanding of prognosisPeripheral blood samplesPotential therapeutic targetEpigenome-wide association studiesMultiple testingCause mortalitySCD14 levelsCohort studyHIV infectionPlasma levelsSoluble CD14Disease progressionImmune functionSurvival timeBlood samplesSCD14Therapeutic targetPWHAntiviral responseSignificant associationDNAm sites
2021
The impact of removing former drinkers from genome‐wide association studies of AUDIT‐C
Dao C, Zhou H, Small A, Gordon KS, Li B, Kember RL, Ye Y, Gelernter J, Xu K, Kranzler HR, Zhao H, Justice AC. The impact of removing former drinkers from genome‐wide association studies of AUDIT‐C. Addiction 2021, 116: 3044-3054. PMID: 33861876, PMCID: PMC9377185, DOI: 10.1111/add.15511.Peer-Reviewed Original Research
2020
Genome-wide association study of smoking trajectory and meta-analysis of smoking status in 842,000 individuals
Xu K, Li B, McGinnis KA, Vickers-Smith R, Dao C, Sun N, Kember RL, Zhou H, Becker WC, Gelernter J, Kranzler HR, Zhao H, Justice AC. Genome-wide association study of smoking trajectory and meta-analysis of smoking status in 842,000 individuals. Nature Communications 2020, 11: 5302. PMID: 33082346, PMCID: PMC7598939, DOI: 10.1038/s41467-020-18489-3.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesLarge genome-wide association studiesMillion Veteran ProgramAssociation studiesExpression quantitative trait lociQuantitative trait lociChromatin interactionsComplex traitsFunctional annotationTrait lociSequencing ConsortiumDozen genesSignificant lociSmoking phenotypesLociMultiple populationsNew insightsPhenotypeVeteran ProgramGenetic vulnerabilityGenesTraitsAnnotationEuropean AmericansConsortiumAssociation of OPRM1 Functional Coding Variant With Opioid Use Disorder
Zhou H, Rentsch CT, Cheng Z, Kember RL, Nunez YZ, Sherva RM, Tate JP, Dao C, Xu K, Polimanti R, Farrer LA, Justice AC, Kranzler HR, Gelernter J. Association of OPRM1 Functional Coding Variant With Opioid Use Disorder. JAMA Psychiatry 2020, 77: 1072-1080. PMID: 32492095, PMCID: PMC7270886, DOI: 10.1001/jamapsychiatry.2020.1206.Peer-Reviewed Original ResearchMeSH KeywordsAgedFemaleGenome-Wide Association StudyHumansMaleMiddle AgedOpioid-Related DisordersReceptors, Opioid, muUnited StatesUnited States Department of Veterans AffairsConceptsOpioid use disorderUse disordersMendelian randomization analysisAfrican American individualsMAIN OUTCOMEFunctional coding variantSignificant associationCausal associationRandomization analysisElectronic health record dataCurrent opioid crisisAmerican individualsHealth record dataCognitive performanceInternational Statistical ClassificationRelated Health ProblemsPotential causal associationAmerican controlsEuropean American controlsAfrican-American controlsCoding variantBuprenorphine treatmentOUD diagnosisTobacco smokingNinth RevisionGenome-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 ResearchMeSH KeywordsAlcohol DrinkingAlcoholismDatasets as TopicFemaleGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansMaleMultifactorial InheritanceConceptsRegulatory 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 phenotypesPhenotypeGenome-wide association study of alcohol consumption and use disorder in 274,424 individuals from multiple populations
Kranzler HR, Zhou H, Kember RL, Vickers Smith R, Justice AC, Damrauer S, Tsao PS, Klarin D, Baras A, Reid J, Overton J, Rader DJ, Cheng Z, Tate JP, Becker WC, Concato J, Xu K, Polimanti R, Zhao H, Gelernter J. Genome-wide association study of alcohol consumption and use disorder in 274,424 individuals from multiple populations. Nature Communications 2019, 10: 1499. PMID: 30940813, PMCID: PMC6445072, DOI: 10.1038/s41467-019-09480-8.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesAssociation studiesMillion Veteran Program sampleGenetic correlationsWide significant lociSignificant genetic correlationsPolygenic risk scoresCell type groupSignificant lociHeritable traitEnrichment analysisTraitsMultiple populationsLociPhenotypeProgram samples
2018
Machine learning selected smoking-associated DNA methylation signatures that predict HIV prognosis and mortality
Zhang X, Hu Y, Aouizerat BE, Peng G, Marconi VC, Corley MJ, Hulgan T, Bryant KJ, Zhao H, Krystal JH, Justice AC, Xu K. Machine learning selected smoking-associated DNA methylation signatures that predict HIV prognosis and mortality. Clinical Epigenetics 2018, 10: 155. PMID: 30545403, PMCID: PMC6293604, DOI: 10.1186/s13148-018-0591-z.Peer-Reviewed Original ResearchMeSH KeywordsAdultCpG IslandsDNA MethylationEpigenesis, GeneticFemaleFrailtyGenome-Wide Association StudyHIV InfectionsHumansMachine LearningMaleMiddle AgedMortalityPrognosisSignal TransductionSmokingConceptsWhite blood cellsSmoking-associated DNA methylationHIV prognosisInfection-related clinical outcomesBlood cellsSmoking-associated CpGsHIV-positive individualsImmune-related outcomesEpigenome-wide significant CpGsClinical outcomesTobacco smokingVeteran populationSurvival rateDNA methylation indexMortalityFrailtyHIVMethylation indexPrognosisMethylation signaturesDNA methylationOutcomesCell cycleCpGSignificant CpGs
2017
DNA methylation signatures of illicit drug injection and hepatitis C are associated with HIV frailty
Zhang X, Hu Y, Justice AC, Li B, Wang Z, Zhao H, Krystal JH, Xu K. DNA methylation signatures of illicit drug injection and hepatitis C are associated with HIV frailty. Nature Communications 2017, 8: 2243. PMID: 29269866, PMCID: PMC5740109, DOI: 10.1038/s41467-017-02326-1.Peer-Reviewed Original ResearchConceptsIllicit drug injectionHepatitis C infectionWhite blood cellsIllicit drug useCo-occurring conditionsMethylation signaturesDiscovery sampleC infectionHepatitis CEpigenome-wide association analysisLower frailtyDrug injectionHigh frailtyImmune functionHealth outcomesDrug useFrailtyDNA methylation signaturesBlood cellsHIVReplication sampleEpigenetic programmingSignificant CpGsEpigenetic effectsIndividualsIdentification of HIV infection-related DNA methylation sites and advanced epigenetic aging in HIV-positive, treatment-naive U.S. veterans
Nelson KN, Hui Q, Rimland D, Xu K, Freiberg MS, Justice AC, Marconi VC, Sun YV. Identification of HIV infection-related DNA methylation sites and advanced epigenetic aging in HIV-positive, treatment-naive U.S. veterans. AIDS 2017, 31: 571-575. PMID: 27922854, PMCID: PMC5263111, DOI: 10.1097/qad.0000000000001360.Peer-Reviewed Original ResearchMeSH KeywordsAgingDNA MethylationEpigenesis, GeneticFollow-Up StudiesGenome-Wide Association StudyHIV InfectionsHumansMaleMiddle AgedUnited StatesVeteransConceptsHIV-positive individualsHIV-negative individualsHIV infectionART initiationBlood samplesTreatment-naive HIV-positive individualsVeterans Aging Cohort StudyHIV-negative groupHIV-positive patientsAging Cohort StudyDNAm ageCohort of veteransPeripheral blood samplesNaive HIVAntiretroviral therapyAntiretroviral treatmentCohort studyStudy cohortAge-related diseasesMyocardial infarctionLarge cohortHealthy personsHigh riskHIVU.S. veterans