2020
Does Reducing Drinking in Patients with Unhealthy Alcohol Use Improve Pain Interference, Use of Other Substances, and Psychiatric Symptoms?
Caniglia EC, Stevens ER, Khan M, Young KE, Ban K, Marshall BDL, Chichetto NE, Gaither JR, Crystal S, Edelman EJ, Fiellin DA, Gordon AJ, Bryant KJ, Tate J, Justice AC, Braithwaite RS. Does Reducing Drinking in Patients with Unhealthy Alcohol Use Improve Pain Interference, Use of Other Substances, and Psychiatric Symptoms? Alcohol Clinical And Experimental Research 2020, 44: 2257-2265. PMID: 33030753, PMCID: PMC8077101, DOI: 10.1111/acer.14455.Peer-Reviewed Original ResearchConceptsUnhealthy alcohol useAlcohol usePain interferenceTobacco smokingUS veteransOdds ratioPsychiatric symptomsDepressive symptomsCocaine useVeterans Aging Cohort StudyAlcohol Use Disorders Identification Test (AUDIT) questionnaireCannabis useSubstance useAging Cohort StudyAnxiety symptomsSeparate logistic regression modelsChronic pain interferenceMultisite observational studyLogistic regression modelsCohort studyInverse probability weightingNext followObservational studyPotential selection biasYears postbaselineAssociation 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 ResearchConceptsOpioid 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 Revision
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 ResearchConceptsWhite 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