Mihaela Aslan, PhD
Research Scientist (General Medicine)DownloadHi-Res Photo
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Research Scientist (General Medicine)
Biography
Mihaela Aslan, Ph.D., is a graduate from the Department of Statistics at Yale University. As a mathematical statistician, she conducts methodological research on a range of topics, such as growth mixture models, competing risks methods in survival analysis, and observational methods to emulate randomized clinical trials. Multi-site observational study design represents another major methodological focus of Dr. Aslan's research. Some of her representative studies have focused on clinical topics such as prostate cancer, PTSD, suicidal ideation and behavior in patients with severe mental illness, Gulf War syndrome, and prediabetes. In her 17-year tenure with the Yale University School of Medicine and the VA Cooperative Studies Program (CSP), and in her current role as the Acting Director of Clinical Epidemiology Research Center (CERC), her goals are centered around advancing scientific knowledge, and helping train the next generation of analysts on applied clinical epidemiology methods, for improving translation and implementation of research results into clinical practice, and to benefit the health and healthcare of Veterans, and by extension, of all human beings.
Appointments
General Internal Medicine
Research ScientistPrimary
Other Departments & Organizations
- General Internal Medicine
- Internal Medicine
Research
Research at a Glance
Yale Co-Authors
Frequent collaborators of Mihaela Aslan's published research.
Publications Timeline
A big-picture view of Mihaela Aslan's research output by year.
Nallakkandi Rajeevan, PhD
Hongyu Zhao, PhD
Joel Gelernter, MD
Renato Polimanti, PhD, MSc
Daniel F. Levey, PhD
John Concato, MD, FACP, MS, MPH
52Publications
1,388Citations
Publications
2024
Association of deployment characteristics and exposures with persistent ill health among 1990-1991 Gulf War veterans in the VA Million Veteran Program
Steele L, Quaden R, Ahmed S, Harrington K, Duong L, Ko J, Gifford E, Polimanti R, Gaziano J, Aslan M, Helmer D, Hauser E. Association of deployment characteristics and exposures with persistent ill health among 1990-1991 Gulf War veterans in the VA Million Veteran Program. Environmental Health 2024, 23: 92. PMID: 39456027, PMCID: PMC11520114, DOI: 10.1186/s12940-024-01118-7.Peer-Reviewed Original ResearchAltmetricMeSH Keywords and ConceptsConceptsMillion Veteran ProgramVA Million Veteran ProgramGulf War veteransIll healthHealth outcomesGulf War IllnessVeteran ProgramMilitary characteristicsWar veteransChronic ill healthCenters for Disease Control and Prevention criteriaGulf War serviceEvaluation of genetic factorsGulf War exposureVeterans' healthPopulation of U.S.Pyridostigmine bromide pillsHealthcare providersWartime exposuresGulf War deploymentResultsThe final cohortVeteran cohortDeployment exposuresHealth problemsVeteransDevelopment of a prediction model for 30-day COVID-19 hospitalization and death in a national cohort of Veterans Health Administration patients–March 2022—April 2023
Bui D, Bajema K, Huang Y, Yan L, Li Y, Rajeevan N, Berry K, Rowneki M, Argraves S, Hynes D, Huang G, Aslan M, Ioannou G. Development of a prediction model for 30-day COVID-19 hospitalization and death in a national cohort of Veterans Health Administration patients–March 2022—April 2023. PLOS ONE 2024, 19: e0307235. PMID: 39365775, PMCID: PMC11451987, DOI: 10.1371/journal.pone.0307235.Peer-Reviewed Original ResearchMeSH Keywords and ConceptsConceptsVeterans Health AdministrationCOVID-19 hospitalizationArea under the receiver operating characteristic curveComprehensive electronic health recordNational cohortElectronic health recordsAll-cause mortalityNational cohort of patientsFull modelHealth recordsHealth AdministrationReceipt of COVID-19 vaccineMortality riskEpidemiology of COVID-19COVID-19High-risk patientsBrier scoreCohort of patientsAnti-SARS-CoV-2 treatmentCOVID-19 vaccineReceiver operating characteristic curveCalibration interceptHospitalAntiviral treatmentAvailability of effective vaccinesT32. GENETIC ARCHITECTURE OF BIPOLAR SPECTRUM DISORDERS IN NEARLY 102,000 LATINO ANCESTRY INDIVIDUALS
Bigdeli T, Voloudakis G, Chatzinakos C, Barr P, Gorman B, Peterson R, Pyarajan S, Huang G, Gaziano M, Pato M, Fanous A, Pato C, Aslan M, Roussos P, Harvey P. T32. GENETIC ARCHITECTURE OF BIPOLAR SPECTRUM DISORDERS IN NEARLY 102,000 LATINO ANCESTRY INDIVIDUALS. European Neuropsychopharmacology 2024, 87: 173-174. DOI: 10.1016/j.euroneuro.2024.08.342.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesPolygenic risk scoresEuropean ancestryMillion Veteran ProgramAdmixed AmericansGenomic Psychiatry CohortGenome-wide association study analysisGenome-wide significant signalsMulti-ancestry meta-analysisLocal ancestry inferenceStatistical fine-mappingBipolar disorderCooperative Studies ProgramGenomic structural equation modelingLatino individualsAncestry inferencePRS-CSxTrans-diagnostic approachBipolar spectrum disordersEast Asian populationsFine-mappingAssociation studiesGWAS statisticsPsychiatric genetic researchAncestry individualsW15. A MULTIVARIATE GENOMIC INVESTIGATION OF THE EXTERNALIZING SPECTRUM AND SUICIDE RISK
Barr P, Bigdeli T, Sanchez-Roige S, Mallard T, Ashley-Koch A, Dick D, Harden P, Hauser B, Qin X, Aslan M, Harvey P, Beckham J, Kimbrel N. W15. A MULTIVARIATE GENOMIC INVESTIGATION OF THE EXTERNALIZING SPECTRUM AND SUICIDE RISK. European Neuropsychopharmacology 2024, 87: 108. DOI: 10.1016/j.euroneuro.2024.08.224.Peer-Reviewed Original ResearchConceptsSuicide attemptsSuicidal ideationPolygenic scoresAssociated with suicide attemptsGenomic structural equation modelingLifetime suicide riskRisk factors associated with suicideExternalizing polygenic scoresLifetime suicide attemptsSubstance use disordersFactors associated with suicideSubstance-use behaviorsExternalizing spectrumExternalizing disordersBipolar disorderPsychiatric diagnosisSuicide riskStructural equation modelingResults Preliminary resultsSuicidal phenotypeGenome-wide association studiesPersonality indicesIdeationSuicideCohort of veteransAssociation of Race and Ethnicity with Prescriptions for Continuous Glucose Monitoring Systems Among a National Sample of Veterans with Diabetes on Insulin Therapy
Lipska K, Oladele C, Zawack K, Gulanski B, Mutalik P, Reaven P, Lynch J, Lee K, Shih M, Lee J, Aslan M. Association of Race and Ethnicity with Prescriptions for Continuous Glucose Monitoring Systems Among a National Sample of Veterans with Diabetes on Insulin Therapy. Diabetes Technology & Therapeutics 2024 PMID: 39177775, DOI: 10.1089/dia.2024.0152.Peer-Reviewed Original ResearchCitationsConceptsVeterans with diabetesAssociation of raceCross-sectional analysis of dataU.S. Veterans Health AdministrationNational sample of veteransNational sampleInsulin therapyVeterans Health AdministrationSystem-level factorsSample of veteransNon-Hispanic patientsSelf-reported raceContinuous glucose monitoringCross-sectional analysisContinuous glucose monitoring useRate of prescriptionMultivariate mixed-effects modelAfrican American patientsLatino patientsHealth AdministrationAlaska NativesType 2 diabetesPercentage of patientsSignificant disparitiesMixed-effects modelsIdentifying Veterans Who Benefit From Nirmatrelvir-Ritonavir: A Target Trial Emulation
Yan L, Bui D, Li Y, Rajeevan N, Rowneki M, Berry K, Argraves S, Huang Y, Hynes D, Cunningham F, Huang G, Aslan M, Ioannou G, Bajema K. Identifying Veterans Who Benefit From Nirmatrelvir-Ritonavir: A Target Trial Emulation. Clinical Infectious Diseases 2024, 79: 643-651. PMID: 38864601, DOI: 10.1093/cid/ciae202.Peer-Reviewed Original ResearchCitationsAltmetricConceptsRisk quartileVeterans Health AdministrationLowest risk quartileHighest risk quartileTarget trial emulationRisk prediction modelUntreated veteransRisk of deathOlder veteransYounger veteransHealth AdministrationTrial emulationMeasure incidenceNirmatrelvir-ritonavirVeteransHospitalUntreated participantsCOVID-19QuartileRiskSevere coronavirus disease 2019ParticipantsPersonsCoronavirus disease 2019Severe COVID-1932. Comparative Genetic Architectures of Schizophrenia in Admixed African American and European Populations
Bigdeli T, Chatzinakos C, Voloudakis G, Gorman B, Barr P, Genovese G, Burstein D, Braff D, Gaziano J, Muralidhar S, Huang G, Pyarajan S, 572 C, Program M, Aslan M, Harvey P, Roussos P. 32. Comparative Genetic Architectures of Schizophrenia in Admixed African American and European Populations. Biological Psychiatry 2024, 95: s88. DOI: 10.1016/j.biopsych.2024.02.210.Peer-Reviewed Original ResearchPredicting clinical outcomes of SARS-CoV-2 infection during the Omicron wave using machine learning
Cogill S, Nallamshetty S, Fullenkamp N, Heberer K, Lynch J, Lee K, Aslan M, Shih M, Lee J. Predicting clinical outcomes of SARS-CoV-2 infection during the Omicron wave using machine learning. PLOS ONE 2024, 19: e0290221. PMID: 38662748, PMCID: PMC11045098, DOI: 10.1371/journal.pone.0290221.Peer-Reviewed Original ResearchAltmetricMeSH Keywords and ConceptsConceptsHigh-risk groupSARS-CoV-2 infectionAnticoagulant useAdverse outcomesPredictor of adverse outcomesHigher risk of adverse outcomesLower body mass indexRisk of adverse outcomesVaccination of high-risk groupsOral anticoagulant useOutcome of SARS-CoV-2 infectionRetrospective longitudinal observational studySARS-CoV-2U.S. Veterans Health AdministrationClinical outcomes of SARS-CoV-2 infectionIdentification of patientsBody mass indexVeterans Health AdministrationPredictors of hospitalizationEscalation of careLongitudinal observational studyClinical outcomesOmicron SARS-CoV-2 variantSARS-CoV-2 variantsUnvaccinated patientsCorrelates of suicidal behaviors and genetic risk among United States veterans with schizophrenia or bipolar I disorder
Bigdeli T, Barr P, Rajeevan N, Graham D, Li Y, Meyers J, Gorman B, Peterson R, Sayward F, Radhakrishnan K, Natarajan S, Nielsen D, Wilkinson A, Malhotra A, Zhao H, Brophy M, Shi Y, O’Leary T, Gleason T, Przygodzki R, Pyarajan S, Muralidhar S, Gaziano J, Huang G, Concato J, Siever L, DeLisi L, Kimbrel N, Beckham J, Swann A, Kosten T, Fanous A, Aslan M, Harvey P. Correlates of suicidal behaviors and genetic risk among United States veterans with schizophrenia or bipolar I disorder. Molecular Psychiatry 2024, 29: 2399-2407. PMID: 38491344, DOI: 10.1038/s41380-024-02472-1.Peer-Reviewed Original ResearchCitationsAltmetricConceptsBipolar I disorderSuicidal behaviorElectronic health recordsPolygenic scoresVeterans Health AdministrationSelf-reported SBColumbia-Suicide Severity Rating ScaleBipolar I disorder patientsCorrelates of suicidal behaviorClasses of psychotropic medicationsSelf-injurious behaviorHealth recordsSeverity Rating ScaleDiagnosed mental illnessAssociated with clinical variablesElectronic health record codesEHR domainDepressive disorderC-SSRSLifetime diagnosisSubstance-relatedPsychotropic medicationsSuicidal ideationExternalizing behaviorsSuicide attemptsCorrelates of Risk for Disinhibited Behaviors in the Million Veteran Program Cohort
Barr P, Bigdeli T, Meyers J, Peterson R, Sanchez-Roige S, Mallard T, Dick D, Harden K, Wilkinson A, Graham D, Nielsen D, Swann A, Lipsky R, Kosten T, Aslan M, Harvey P, Kimbrel N, Beckham J, Aslan M, Antonelli M, de Asis M, Bauer M, Brophy M, Concato J, Cunningham F, Freedman R, Gaziano M, Gleason T, Harvey P, Huang G, Kelsoe J, Kosten T, Lehner T, Lohr J, Marder S, Miller P, O Leary T, Patterson T, Peduzzi P, Przygodski R, Siever L, Sklar P, Strakowski S, Zhao H, Fanous A, Farwell W, Malhorta A, Mane S, Palacios P, Bigdeli T, Corsey M, Zaluda L, Johnson J, Sueiro M, Cavaliere D, Jeanpaul V, Maffucci A, Mancini L, Deen J, Muldoon G, Whitbourne S, Canive J, Adamson L, Calais L, Fuldauer G, Kushner R, Toney G, Lackey M, Mank A, Mahdavi N, Villarreal G, Muly E, Amin F, Dent M, Wold J, Fischer B, Elliott A, Felix C, Gill G, Parker P, Logan C, McAlpine J, DeLisi L, Reece S, Hammer M, Agbor-Tabie D, Goodson W, Aslam M, Grainger M, Richtand N, Rybalsky A, Al Jurdi R, Boeckman E, Natividad T, Smith D, Stewart M, Torres S, Zhao Z, Mayeda A, Green A, Hofstetter J, Ngombu S, Scott M, Strasburger A, Sumner J, Paschall G, Mucciarelli J, Owen R, Theus S, Tompkins D, Potkin S, Reist C, Novin M, Khalaghizadeh S, Douyon R, Kumar N, Martinez B, Sponheim S, Bender T, Lucas H, Lyon A, Marggraf M, Sorensen L, Surerus C, Sison C, Amato J, Johnson D, Pagan-Howard N, Adler L, Alerpin S, Leon T, Mattocks K, Araeva N, Sullivan J, Suppes T, Bratcher K, Drag L, Fischer E, Fujitani L, Gill S, Grimm D, Hoblyn J, Nguyen T, Nikolaev E, Shere L, Relova R, Vicencio A, Yip M, Hurford I, Acheampong S, Carfagno G, Haas G, Appelt C, Brown E, Chakraborty B, Kelly E, Klima G, Steinhauer S, Hurley R, Belle R, Eknoyan D, Johnson K, Lamotte J, Granholm E, Bradshaw K, Holden J, Jones R, Le T, Molina I, Peyton M, Ruiz I, Sally L, Tapp A, Devroy S, Jain V, Kilzieh N, Maus L, Miller K, Pope H, Wood A, Meyer E, Givens P, Hicks P, Justice S, McNair K, Pena J, Tharp D, Davis L, Ban M, Cheatum L, Darr P, Grayson W, Munford J, Whitfield B, Wilson E, Melnikoff S, Schwartz B, Tureson M, D Souza D, Forselius K, Ranganathan M, Rispoli L, Sather M, Colling C, Haakenson C, Kruegar D, Muralidhar S, Ramoni R, Breeling J, Chang K, O Donnell C, Tsao P, Moser J, Brewer J, Warren S, Argyres D, Stevens B, Humphries D, Do N, Shayan S, Nguyen X, Pyarajan S, Cho K, Hauser E, Sun Y, Wilson P, McArdle R, Dellitalia L, Harley J, Whittle J. Correlates of Risk for Disinhibited Behaviors in the Million Veteran Program Cohort. JAMA Psychiatry 2024, 81: 188-197. PMID: 37938835, PMCID: PMC10633411, DOI: 10.1001/jamapsychiatry.2023.4141.Peer-Reviewed Original ResearchAltmetricConceptsSubstance use disordersPolygenic risk scoresMillion Veteran ProgramCorrelates of riskElectronic health recordsPsychiatric problemsComorbid psychiatric problemsViral hepatitis C.Chronic airway obstructionHealth recordsElectronic health record dataUS veteran populationMillion Veteran Program cohortCommon etiologic pathwayHealth care centersHealth record dataInternational Statistical ClassificationSuicide-related behaviorsAirway obstructionCohort studyHepatitis C.Recent genome-wide association studiesLiver diseaseUS veteransCare center
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