2021
Prevalence of predicted gene-drug interactions for antidepressants in the treatment of major depressive disorder in the Precision Medicine in Mental Health Care Study
Ramsey CM, Lynch KG, Thase ME, Gelernter J, Kranzler HR, Pyne JM, Shih MC, Stone A, Committee C, Oslin DW. Prevalence of predicted gene-drug interactions for antidepressants in the treatment of major depressive disorder in the Precision Medicine in Mental Health Care Study. Journal Of Affective Disorders 2021, 282: 1272-1277. PMID: 33601706, DOI: 10.1016/j.jad.2021.01.034.Peer-Reviewed Original ResearchConceptsMajor depressive disorderMental Health Care studyGene-drug interactionsDepressive disorderPGx testingAD treatmentCare studiesHealth care studiesPrecision medicineContext of pharmacotherapyPrevalence of antidepressantsUtility of PGxPrescribing practicesUS veteransPharmacogenetic testingAntidepressantsPatientsPrevious treatmentPrevalenceTreatmentDisordersPGxMedicineTest panelParticipants
2020
Study design and implementation of the PRecision Medicine In MEntal health Care (PRIME Care) Trial
Oslin DW, Chapman S, Duvall SL, Gelernter J, Ingram E, Kranzler HR, Lehmann LS, Lynch JA, Lynch KG, Pyne JM, Shih MC, Stone A, Thase ME, Wray LO. Study design and implementation of the PRecision Medicine In MEntal health Care (PRIME Care) Trial. Contemporary Clinical Trials 2020, 101: 106247. PMID: 33316457, DOI: 10.1016/j.cct.2020.106247.Peer-Reviewed Original ResearchMeSH KeywordsAntidepressive AgentsHumansMental HealthPharmacogeneticsPharmacogenomic TestingPrecision MedicineConceptsMajor depressive disorderPGx test resultsRandomized clinical trialsClinical trialsPGx testingHealth care cost implicationsUtility of PGxRoutine clinical carePragmatic randomized clinical trialsEpisode of careHealth care trialsPrecision medicineHealth care providersPrecision medicine approachPatient care costsImplementation science methodsCare trialsMedication selectionPsychotropic medicationsProvider educationDepressive disorderPatient outcomesPharmacogenetic testingCare providersClinical care
2018
GWAS of lifetime cannabis use reveals new risk loci, genetic overlap with psychiatric traits, and a causal effect of schizophrenia liability
Pasman JA, Verweij KJH, Gerring Z, Stringer S, Sanchez-Roige S, Treur JL, Abdellaoui A, Nivard MG, Baselmans BML, Ong JS, Ip HF, van der Zee MD, Bartels M, Day FR, Fontanillas P, Elson SL, the 23andMe Research Team, de Wit H, Davis LK, MacKillop J, The Substance Use Disorders Working Group of the Psychiatric Genomics Consortium, International Cannabis Consortium, Derringer JL, Branje SJT, Hartman CA, Heath AC, van Lier PAC, Madden PAF, Mägi R, Meeus W, Montgomery GW, Oldehinkel AJ, Pausova Z, Ramos-Quiroga JA, Paus T, Ribases M, Kaprio J, Boks MPM, Bell JT, Spector TD, Gelernter J, Boomsma DI, Martin NG, MacGregor S, Perry JRB, Palmer AA, Posthuma D, Munafò MR, Gillespie NA, Derks EM, Vink JM. GWAS of lifetime cannabis use reveals new risk loci, genetic overlap with psychiatric traits, and a causal effect of schizophrenia liability. Nature Neuroscience 2018, 21: 1161-1170. PMID: 30150663, PMCID: PMC6386176, DOI: 10.1038/s41593-018-0206-1.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAgedAged, 80 and overCell Adhesion MoleculesDatabases, GeneticFemaleGene Expression RegulationGenetic Predisposition to DiseaseGenome-Wide Association StudyGenotypeHumansMaleMarijuana AbuseMendelian Randomization AnalysisMental HealthMiddle AgedPolymorphism, Single NucleotideRisk-TakingSchizophreniaYoung AdultConceptsGenome-wide association studiesNew risk lociLarge genome-wide association studiesGene-based testsIndependent single nucleotide polymorphismsDifferent expression levelsSignificant genetic correlationsHealth-related traitsSingle nucleotide polymorphismsEtiology of cannabisHeritable traitRisk lociSignificant genesAssociation studiesGenetic correlationsPsychiatric traitsGenetic variantsNucleotide polymorphismsGenetic overlapExpression levelsTraitsGenesNew insightsSchizophrenia riskMendelian randomization analysis