2022
Dissecting the epigenomic differences between smoking and nicotine dependence in a veteran cohort
Nagamatsu S, Pietrzak R, Xu K, Krystal J, Gelernter J, Montalvo‐Ortiz J. Dissecting the epigenomic differences between smoking and nicotine dependence in a veteran cohort. Addiction Biology 2022, 28: e13259. PMID: 36577721, DOI: 10.1111/adb.13259.Peer-Reviewed Original ResearchConceptsSmoking statusNicotine dependenceVeteran cohortNon-current smokersSerious public health issueNovel treatment strategiesPublic health issueUS military veteransEpigenome-wide association studiesCurrent smokersTreatment strategiesFagerström TestNicotine addictionSmokingHealth issuesRole of epigeneticsMilitary veteransMethylationEPIC BeadChip arraySmokersContinuous variablesF2RL3 geneCohortBiomarkersBeadChip arrayPrevious findings
2021
Subthreshold post-traumatic stress disorder as a risk factor for post-traumatic stress disorder: results from a sample of USA veterans
Pietrzak RH, Javier FG, Krystal JH, Southwick SM. Subthreshold post-traumatic stress disorder as a risk factor for post-traumatic stress disorder: results from a sample of USA veterans. The British Journal Of Psychiatry 2021, 219: 456-459. PMID: 35048836, DOI: 10.1192/bjp.2021.17.Peer-Reviewed Original ResearchConceptsSubthreshold post-traumatic stress disorderPost-traumatic stress disorderStress disorderRisk factorsProspective national cohortPotential risk factorsLow dispositional optimismSpecific PTSD symptomsTrauma-exposed veteransNational cohortAssociated FactorsPreventive interventionsPTSD symptomsVeteransDisordersGreater ageCognitive difficultiesWave 1Dispositional optimismCohortSymptomsFactorsTrauma
2018
Predicting Barriers to Treatment for Depression in a U.S. National Sample: A Cross-Sectional, Proof-of-Concept Study
Chekroud AM, Foster D, Zheutlin AB, Gerhard DM, Roy B, Koutsouleris N, Chandra A, Esposti MD, Subramanyan G, Gueorguieva R, Paulus M, Krystal JH. Predicting Barriers to Treatment for Depression in a U.S. National Sample: A Cross-Sectional, Proof-of-Concept Study. Psychiatric Services 2018, 69: 927-934. PMID: 29962307, PMCID: PMC7232987, DOI: 10.1176/appi.ps.201800094.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overCross-Sectional StudiesDepressive DisorderFemaleHealth Services AccessibilityHumansLogistic ModelsMaleMiddle AgedPatient Acceptance of Health CarePrimary Health CareProof of Concept StudyPsychotherapySampling StudiesSelf-AssessmentSurveys and QuestionnairesTreatment RefusalUnited StatesYoung AdultConceptsDiagnosis of depressionHealth care providersSelf-report survey itemsImplementation of interventionsDerivation cohortUntreated depressionCare providersEffective treatmentU.S. national sampleDrug useDepressionDiagnosisTreatmentU.S. National SurveyPatientsCohortNational surveyNational sampleConcept studySurvey itemsBalanced accuracyIndividualsRetention rateIndependent responsesPrevalence
2016
Cross-trial prediction of treatment outcome in depression: a machine learning approach
Chekroud AM, Zotti RJ, Shehzad Z, Gueorguieva R, Johnson MK, Trivedi MH, Cannon TD, Krystal JH, Corlett PR. Cross-trial prediction of treatment outcome in depression: a machine learning approach. The Lancet Psychiatry 2016, 3: 243-250. PMID: 26803397, DOI: 10.1016/s2215-0366(15)00471-x.Peer-Reviewed Original ResearchConceptsTreatment outcomesTreatment groupsEscitalopram treatment groupSpecific antidepressantsPatient-reported dataSequenced Treatment AlternativesClinical trial dataIndependent clinical trialsClinical remissionSymptomatic remissionClinical trialsTreatment efficacyPatientsProspective identificationTreatment alternativesTrial dataDepressionRemissionAntidepressantsOutcomesGroupLevel 1CitalopramCohortClinicians
2015
A New Genomewide Association Meta‐Analysis of Alcohol Dependence
Zuo L, Tan Y, Zhang X, Wang X, Krystal J, Tabakoff B, Zhong C, Luo X. A New Genomewide Association Meta‐Analysis of Alcohol Dependence. Alcohol Clinical And Experimental Research 2015, 39: 1388-1395. PMID: 26173551, PMCID: PMC5587504, DOI: 10.1111/acer.12786.Peer-Reviewed Original ResearchConceptsAfrican American cohortAmerican cohortAlcohol dependenceSingle nucleotide polymorphismsAustralian cohortRisk genesEuropean American cohortRisk single nucleotide polymorphismsRat brainIndependent cohortMeta-AnalysisCohortMouse brainRisk variantsP-valueRNA expression analysisGenomewide association studiesBrainHuman tissuesNucleotide polymorphismsAssociation studiesGenomewide association analysisSignificant association between rare IPO11‐HTR1A variants and attention deficit hyperactivity disorder in Caucasians
Zuo L, Saba L, Lin X, Tan Y, Wang K, Krystal JH, Tabakoff B, Luo X. Significant association between rare IPO11‐HTR1A variants and attention deficit hyperactivity disorder in Caucasians. American Journal Of Medical Genetics Part B Neuropsychiatric Genetics 2015, 168: 544-556. PMID: 26079129, PMCID: PMC4851708, DOI: 10.1002/ajmg.b.32329.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAttention Deficit Disorder with HyperactivityBeta KaryopherinsBlack or African AmericanFemaleGene FrequencyGenetic Predisposition to DiseaseGenetic VariationHumansMaleMiddle AgedPolymorphism, Single NucleotideQuantitative Trait LociReceptor, Serotonin, 5-HT1ARisk FactorsWhite PeopleConceptsAttention deficit hyperactivity disorderDeficit hyperactivity disorderNeuropsychiatric disordersRare variantsHyperactivity disorderDifferent neuropsychiatric disordersRNA expression changesIndependent cohortSignificant associationSignificant regulatory effectDisordersCaucasiansEuropean descentRegulatory effectsHuman brainDiseaseAssociationCis-eQTL analysisIPO11African descentExpression changesSubjectsCohortFalse discovery rateVariants