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 ResearchConceptsVeterans 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 discoveriesPercent
2013
Measuring alcohol consumption using Timeline Followback in non-treatment-seeking medical clinic patients with and without HIV infection: 7-, 14-, or 30-day recall.
Fiellin DA, Mcginnis KA, Maisto SA, Justice AC, Bryant K. Measuring alcohol consumption using Timeline Followback in non-treatment-seeking medical clinic patients with and without HIV infection: 7-, 14-, or 30-day recall. Journal Of Studies On Alcohol And Drugs 2013, 74: 500-4. PMID: 23490581, PMCID: PMC3602364, DOI: 10.15288/jsad.2013.74.500.Peer-Reviewed Original ResearchConceptsTimeline FollowbackAlcohol consumptionHeavy episodic drinkingHIV infectionHIV statusEpisodic drinkingPercent agreementInfectious disease clinicMedical clinic patientsKappa statisticsUninfected menDisease clinicSpearman correlation coefficientClinic patientsClinic subjectsOptimal time windowHIVMedical careMedical clinicsPatientsGold standardClinicInfectionDrinkingDays