Qingzhou Feng
Associate Research Scientist in Cell BiologyAbout
Research
Publications
2025
Karyopherins remodel the dynamic organization of the nuclear pore complex transport barrier
Kozai T, Fernandez-Martinez J, Kapinos L, Gallardo P, van Eeuwen T, Saladin M, Eliasian R, Mazur A, Zhang W, Tempkin J, Panatala R, Delgado-Izquierdo M, Escribano-Marin R, Feng Q, Lin C, Sali A, Chait B, Raveh B, Veenhoff L, Rout M, Lim R. Karyopherins remodel the dynamic organization of the nuclear pore complex transport barrier. Nature Cell Biology 2025, 27: 2089-2101. PMID: 41331088, PMCID: PMC12717009, DOI: 10.1038/s41556-025-01812-9.Peer-Reviewed Original ResearchA Computable Electronic Health Record ARDS Classifier and the Association Between the MUC5B Promoter Polymorphism and ARDS in Critically Ill Adults
Kerchberger V, McNeil J, Zheng N, Chang D, Rosenberger C, Rogers A, Bastarache J, Feng Q, Wei W, Ware L. A Computable Electronic Health Record ARDS Classifier and the Association Between the MUC5B Promoter Polymorphism and ARDS in Critically Ill Adults. CHEST Critical Care 2025, 3: 100150. DOI: 10.1016/j.chstcc.2025.100150.Peer-Reviewed Original ResearchElectronic health recordsCritically Ill AdultsElectronic health record dataMUC5B Promoter PolymorphismIll adultsAt-risk adultsNegative predictive valuePositive predictive valueDiagnostic billing codesHealth recordsHospital participationGenetic risk factorsDNA biobanksBilling codesBioVUStudy designPromoter polymorphismCohort of critically ill adultsAt-riskCohen's kappaModerate agreementRisk factorsGenotyped cohortPredictive valueBiobankRAB19, SERPINB9P1, and Pancreatitis in Patients Taking Azathioprine in Routine Clinical Practice: Genome and Transcriptome‐Wide Association Studies
Shah S, Reese T, Daniel L, Zanussi J, Dickson A, Nepal P, Tao R, Miller‐Fleming T, Straub P, Maizel J, Hung A, Wei W, Phillips E, Cox N, Stein C, Feng Q, Chung C. RAB19, SERPINB9P1, and Pancreatitis in Patients Taking Azathioprine in Routine Clinical Practice: Genome and Transcriptome‐Wide Association Studies. Clinical Pharmacology & Therapeutics 2025, 118: 946-953. PMID: 40698913, PMCID: PMC12439014, DOI: 10.1002/cpt.70003.Peer-Reviewed Original ResearchConceptsElectronic health recordsPancreatic injuryAcute pancreatitisClinical practiceTranscriptome-wide association studyRetrospective studyHealth recordsControl subjectsBioVU cohortPancreatic expressionUS cohortSecondary outcomesBioVURoutine clinical practicePrimary outcomeSerious adverse eventsAssociation studiesGenetic associationDefinitions of pancreatitisGWAS analysisHLA regionAdverse eventsAutoimmune diseasesAzathioprine usersAssociationPTPN2 and Leukopenia in Individuals With Normal TPMT and NUDT15 Metabolizer Status Taking Azathioprine
Daniel L, Nepal P, Zanussi J, Dickson A, Straub P, Miller‐Fleming T, Wei W, Hung A, Cox N, Kawai V, Mosley J, Stein C, Feng Q, Liu G, Tao R, Chung C. PTPN2 and Leukopenia in Individuals With Normal TPMT and NUDT15 Metabolizer Status Taking Azathioprine. Clinical And Translational Science 2025, 18: e70220. PMID: 40442974, PMCID: PMC12122386, DOI: 10.1111/cts.70220.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesGenome-wide significancePrincipal components of ancestryImmune cell developmentGenetic risk factorsDose-dependent side effectsAssociation studiesGenetic dataSide effects of azathioprineIntronic variantsElectronic health recordsVanderbilt's electronic health recordEffect of azathioprineCell developmentPTPN2Replication cohortTPMTHealth recordsNUDT15NIH-funded projectDrug discontinuationThiopurine useBioVUXanthine oxidase inhibitorLeukopeniaMotor clustering enhances kinesin-driven vesicle transport
Jiang R, Feng Q, Nong D, Kang Y, Sept D, Hancock W. Motor clustering enhances kinesin-driven vesicle transport. Biophysical Journal 2025, 124: 2033-2040. PMID: 40329534, PMCID: PMC12256910, DOI: 10.1016/j.bpj.2025.04.033.Peer-Reviewed Original ResearchConceptsKinesin-1 motorsKinesin-1In vitro biophysical studiesVesicle transportDynein motorsIn vivoIntracellular vesiclesMotor numberLong-distance transportBiophysical studiesDNA scaffoldIn vivo observationsVesiclesMotor clustersIn vitro studiesDyneinKinesinConsistent with predictionsDNAMotilityMotor organizationOrganizationBeyond Phecodes: leveraging PheMAP to identify patients lacking diagnosis codes in electronic health records
Yan C, Grabowska M, Thakkar R, Dickson A, Embí P, Feng Q, Denny J, Kerchberger V, Malin B, Wei W. Beyond Phecodes: leveraging PheMAP to identify patients lacking diagnosis codes in electronic health records. Journal Of The American Medical Informatics Association 2025, 32: 1007-1014. PMID: 40156924, PMCID: PMC12089765, DOI: 10.1093/jamia/ocaf055.Peer-Reviewed Original ResearchConceptsElectronic health recordsSensorineural hearing lossHearing lossDiagnosis codesHealth recordsPhenotype risk scorePatient recordsClinical terminologyProstate cancerType 2 diabetes mellitusRisk scoreDementiaExpert reviewT2DMPHEMAPPhenotype patientsProstatePatientsCancerPositive casesPhecodesResearch reliabilityDiagnosisRecordsPhenotypeBiomechanical analysis of clear aligners for mandibular anterior teeth intrusion and its clinical application in the design of new aligner attachment
Xiao S, Cheng C, Li H, Li L, Shen C, Feng Q, Zhao Y, Duan Y, Xia L, Chu F, Fang B. Biomechanical analysis of clear aligners for mandibular anterior teeth intrusion and its clinical application in the design of new aligner attachment. Progress In Orthodontics 2025, 26: 11. PMID: 40059251, PMCID: PMC11891119, DOI: 10.1186/s40510-025-00557-3.Peer-Reviewed Original ResearchConceptsIncisor mandibular plane angleMandibular anterior teethAnterior teethAligner attachmentsExcessive alveolar bone resorptionTreatment outcomesMandibular plane angleLower anterior teethAlveolar bone resorptionClinical treatment outcomesTooth intrusionLingual inclinationOrthodontic techniquesCBCT dataBone resorptionBone wallLabial movementPlane angleClinical practiceResultsSignificant differencesClinical applicationLingual movementTeethClinical issuesConclusionThis studyImproving topic modeling performance on social media through semantic relationships within biomedical terminology
Xin Y, Grabowska M, Gangireddy S, Krantz M, Kerchberger V, Dickson A, Feng Q, Yin Z, Wei W. Improving topic modeling performance on social media through semantic relationships within biomedical terminology. PLOS ONE 2025, 20: e0318702. PMID: 39982945, PMCID: PMC11845042, DOI: 10.1371/journal.pone.0318702.Peer-Reviewed Original ResearchConceptsSocial media textsTopic modelsSocial mediaHealth-related topicsAnalyze social mediaSemantic relationshipsBiomedical terminologiesMedical conceptsSemantic typesRecord validationModeling pipelineMedia textsUnsupervised machineExpert evaluationHealthcare ResearchModel performanceOnline discussionsTextTopicsPipelineUsersMachineModeling approachModelTechnique's potentialRisk factors affecting polygenic score performance across diverse cohorts
Hui D, Dudek S, Kiryluk K, Walunas T, Kullo I, Wei W, Tiwari H, Peterson J, Chung W, Davis B, Khan A, Kottyan L, Limdi N, Feng Q, Puckelwartz M, Weng C, Smith J, Karlson E, Center R, BioBank P, Jarvik G, Ritchie M. Risk factors affecting polygenic score performance across diverse cohorts. ELife 2025, 12: rp88149. PMID: 39851248, PMCID: PMC11771958, DOI: 10.7554/elife.88149.Peer-Reviewed Original ResearchConceptsBody mass indexPolygenic scoresAssociated with body mass indexPolygenic score performancePhysical activityStandard deviation changeAlcohol consumptionMass indexDiverse cohortInteraction effectsRisk factorsBlood lipidsDeviation changeQuintileScore performanceCohortCovariatesBinary covariateAncestryModel R2Continuous covariatesDifferencesRisk factors affecting polygenic score performance across diverse cohorts
Hui D, Dudek S, Kiryluk K, Walunas T, Kullo I, Wei W, Tiwari H, Peterson J, Chung W, Davis B, Khan A, Kottyan L, Limdi N, Feng Q, Puckelwartz M, Weng C, Smith J, Karlson E, Jarvik G, Ritchie M. Risk factors affecting polygenic score performance across diverse cohorts. ELife 2025, 12 DOI: 10.7554/elife.88149.3.Peer-Reviewed Original ResearchBody mass indexPolygenic scoresAssociated with body mass indexPolygenic score performancePhysical activityStandard deviation changeBMI effectsBMI individualsAlcohol consumptionDiverse cohortMass indexInteraction effectsRisk factorsBlood lipidsDeviation changeQuintileScore performanceCohortCovariatesBinary covariateAncestryContinuous covariatesModel R 2DifferencesScores