Featured Publications
Understanding the comorbidity between posttraumatic stress severity and coronary artery disease using genome-wide information and electronic health records
Polimanti R, Wendt FR, Pathak GA, Tylee DS, Tcheandjieu C, Hilliard AT, Levey DF, Adhikari K, Gaziano JM, O’Donnell C, Assimes TL, Stein MB, Gelernter J. Understanding the comorbidity between posttraumatic stress severity and coronary artery disease using genome-wide information and electronic health records. Molecular Psychiatry 2022, 27: 3961-3969. PMID: 35986173, PMCID: PMC10986859, DOI: 10.1038/s41380-022-01735-z.Peer-Reviewed Original ResearchConceptsCoronary artery diseasePosttraumatic stress disorderElectronic health recordsMillion Veteran ProgramArtery diseaseTotal scoreCAD diagnosisPlatelet amyloid precursor proteinHealth recordsPosttraumatic stress severityAmyloid precursor proteinEarly CAD diagnosisUK BiobankBidirectional relationshipTwo-sample Mendelian randomization (MR) analysisMendelian randomization analysisCAD riskHigh morbidityPTSD symptom severityCARDIoGRAMplusC4D consortiumPleiotropic mechanismsSymptom severityLongitudinal changesDiscordant effectsStress disorder
2024
Multi-ancestry meta-analysis of tobacco use disorder identifies 461 potential risk genes and reveals associations with multiple health outcomes
Toikumo S, Jennings M, Pham B, Lee H, Mallard T, Bianchi S, Meredith J, Vilar-Ribó L, Xu H, Hatoum A, Johnson E, Pazdernik V, Jinwala Z, Pakala S, Leger B, Niarchou M, Ehinmowo M, Jenkins G, Batzler A, Pendegraft R, Palmer A, Zhou H, Biernacka J, Coombes B, Gelernter J, Xu K, Hancock D, Cox N, Smoller J, Davis L, Justice A, Kranzler H, Kember R, Sanchez-Roige S. Multi-ancestry meta-analysis of tobacco use disorder identifies 461 potential risk genes and reveals associations with multiple health outcomes. Nature Human Behaviour 2024, 8: 1177-1193. PMID: 38632388, PMCID: PMC11199106, DOI: 10.1038/s41562-024-01851-6.Peer-Reviewed Original ResearchMeSH KeywordsElectronic Health RecordsFemaleGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansMaleTobacco Use DisorderUnited StatesConceptsTobacco use disorderPotential risk genesMulti-ancestry meta-analysisMultiple health outcomesElectronic health recordsSource of phenotypic informationGenome-wide association studiesUse disorderAscertainment cohortHealth outcomesHealth recordsPrevalent substance use disordersRisk genesIndependent risk lociUK BiobankSubstance use disordersSmoking behaviorMedical outcomesFunctional genomics toolsPsychiatric traitsAssociation studiesRisk lociRisk variantsHeart diseaseGenomic tools
2019
Validation of an Electronic Medical Record–Based Algorithm for Identifying Posttraumatic Stress Disorder in U.S. Veterans
Harrington KM, Quaden R, Stein MB, Honerlaw JP, Cissell S, Pietrzak RH, Zhao H, Radhakrishnan K, Aslan M, Gaziano JM, Concato J, Gagnon DR, Gelernter J, Cho K, Program O. Validation of an Electronic Medical Record–Based Algorithm for Identifying Posttraumatic Stress Disorder in U.S. Veterans. Journal Of Traumatic Stress 2019, 32: 226-237. PMID: 31009556, PMCID: PMC6699164, DOI: 10.1002/jts.22399.Peer-Reviewed Original Research
2018
Using DNA methylation to validate an electronic medical record phenotype for smoking
McGinnis KA, Justice AC, Tate JP, Kranzler HR, Tindle HA, Becker WC, Concato J, Gelernter J, Li B, Zhang X, Zhao H, Crothers K, Xu K, Group F. Using DNA methylation to validate an electronic medical record phenotype for smoking. Addiction Biology 2018, 24: 1056-1065. PMID: 30284751, PMCID: PMC6541538, DOI: 10.1111/adb.12670.Peer-Reviewed Original ResearchMeSH KeywordsDNA MethylationElectronic Health RecordsFemaleHumansMaleMiddle AgedPhenotypeReproducibility of ResultsSelf ReportSmokingVeteransConceptsVeterans Aging Cohort StudyAging Cohort StudyStrong associationDNA methylation sitesSmoking metricsCohort studyCurrent smokingSmoking statusSpearman correlation coefficientBiomarker cohortBlood samplesSmoking behaviorCriterion standardLogistic regressionSmokingSmoking phenotypesCurve analysisGroup assignmentText notesAssociationDescriptive statisticsPhenotypeCorrelation coefficientGenetic discoveriesPercentAUDIT‐C and ICD codes as phenotypes for harmful alcohol use: association with ADH1B polymorphisms in two US populations
Justice AC, Smith RV, Tate JP, McGinnis K, Xu K, Becker WC, Lee K, Lynch K, Sun N, Concato J, Fiellin DA, Zhao H, Gelernter J, Kranzler HR, Program O. AUDIT‐C and ICD codes as phenotypes for harmful alcohol use: association with ADH1B polymorphisms in two US populations. Addiction 2018, 113: 2214-2224. PMID: 29972609, PMCID: PMC6226338, DOI: 10.1111/add.14374.Peer-Reviewed Original Research