Featured Publications
To weight or not to weight? The effect of selection bias in 3 large electronic health record-linked biobanks and recommendations for practice
Salvatore M, Kundu R, Shi X, Friese C, Lee S, Fritsche L, Mondul A, Hanauer D, Pearce C, Mukherjee B. To weight or not to weight? The effect of selection bias in 3 large electronic health record-linked biobanks and recommendations for practice. Journal Of The American Medical Informatics Association 2024, 31: 1479-1492. PMID: 38742457, PMCID: PMC11187425, DOI: 10.1093/jamia/ocae098.Peer-Reviewed Original ResearchEHR-linked biobanksNational Health Interview Survey dataHealth Interview Survey dataPhenome-wide association studyMichigan Genomics InitiativeElectronic health record-linked biobankTarget populationInterview Survey dataColorectal cancerUS adult populationSelection biasUK BiobankAssociation estimatesBiobank dataRecruitment strategiesEffect of selection biasICD codesLog odds ratioUKBSelection weightsEffect sizeAssociation studiesAdult populationBiobankImpact prevalenceAssociation of Polygenic Risk Scores for Multiple Cancers in a Phenome-wide Study: Results from The Michigan Genomics Initiative
Fritsche L, Gruber S, Wu Z, Schmidt E, Zawistowski M, Moser S, Blanc V, Brummett C, Kheterpal S, Abecasis G, Mukherjee B. Association of Polygenic Risk Scores for Multiple Cancers in a Phenome-wide Study: Results from The Michigan Genomics Initiative. American Journal Of Human Genetics 2018, 102: 1048-1061. PMID: 29779563, PMCID: PMC5992124, DOI: 10.1016/j.ajhg.2018.04.001.Peer-Reviewed Original ResearchConceptsPolygenic risk scoresElectronic health recordsAssociations of polygenic risk scoresPhenome-wide significant associationsPolygenic risk score associationsLongitudinal biorepository effortNon-cancer diagnosesPatients' electronic health recordsPhenome-wide association studyAnalysis of temporal orderMichigan Genomics InitiativeRisk scoreAssociated with multiple phenotypesFemale breast cancerNHGRI-EBI CatalogRisk profileGenetic risk profilesMeasures of genomic variationCancer traitsCase-control studyPheWAS analysisHealth recordsHealth systemMichigan MedicineCancer diagnosis
2024
Improving prediction models of amyotrophic lateral sclerosis (ALS) using polygenic, pre-existing conditions, and survey-based risk scores in the UK Biobank
Jin W, Boss J, Bakulski K, Goutman S, Feldman E, Fritsche L, Mukherjee B. Improving prediction models of amyotrophic lateral sclerosis (ALS) using polygenic, pre-existing conditions, and survey-based risk scores in the UK Biobank. Journal Of Neurology 2024, 271: 6923-6934. PMID: 39249108, DOI: 10.1007/s00415-024-12644-2.Peer-Reviewed Original ResearchPolygenic risk scoresRisk scorePre-existing conditionsPhenome-wide association studyControls of European descentPhenotype risk scoreUK Biobank dataAmyotrophic lateral sclerosis riskRisk score distributionIncreased ALS riskInfluence of environmental exposuresExposure-related factorsCombined risk scoreUK BiobankAmyotrophic lateral sclerosisBaseline demographic covariatesBiobank dataPRS-CSALS riskAmyotrophic lateral sclerosis diagnosisDiagnosis 1Demographic covariatesAssociation studiesEuropean descentMethodsUtilizing data
2023
Uncovering associations between pre-existing conditions and COVID-19 Severity: A polygenic risk score approach across three large biobanks
Fritsche L, Nam K, Du J, Kundu R, Salvatore M, Shi X, Lee S, Burgess S, Mukherjee B. Uncovering associations between pre-existing conditions and COVID-19 Severity: A polygenic risk score approach across three large biobanks. PLOS Genetics 2023, 19: e1010907. PMID: 38113267, PMCID: PMC10763941, DOI: 10.1371/journal.pgen.1010907.Peer-Reviewed Original ResearchConceptsPolygenic risk scoresMichigan Genomics InitiativeUK BiobankPre-existing conditionsPhenome-wide association studyAssociation studiesCohort-specific analysesPolygenic risk score approachUK Biobank cohortMeta-analysisIncreased risk of hospitalizationGenome-wide association studiesBody mass indexRisk of hospitalizationIdentified novel associationsRisk score approachCOVID-19 outcome dataCOVID-19 hospitalizationCOVID-19Mass indexRisk scoreBiobankCardiovascular conditionsCOVID-19 severityIncreased risk
2022
A Case-Crossover Phenome-wide association study (PheWAS) for understanding Post-COVID-19 diagnosis patterns
Haupert S, Shi X, Chen C, Fritsche L, Mukherjee B. A Case-Crossover Phenome-wide association study (PheWAS) for understanding Post-COVID-19 diagnosis patterns. Journal Of Biomedical Informatics 2022, 136: 104237. PMID: 36283580, PMCID: PMC9595430, DOI: 10.1016/j.jbi.2022.104237.Peer-Reviewed Original ResearchConceptsPhenome-wide association studyPost-COVID-19 conditionCOVID-19 survivorsCohort of COVID-19 survivorsAssociation studiesMental health disordersConditional logistic regressionWithin-person confoundingSARS-CoV-2 infectionRobust study designsProportion of COVID-19 survivorsPost-COVID-19Healthcare needsMental healthSARS-CoV-2Circulatory diseasesPhenotype codesHealth disordersSARS-CoV-2 positivityStudy designSARS-CoV-2 positive patientsLogistic regressionPheWASPost-COVID-19 infectionCOVID-19ExPRSweb: An online repository with polygenic risk scores for common health-related exposures
Ma Y, Patil S, Zhou X, Mukherjee B, Fritsche L. ExPRSweb: An online repository with polygenic risk scores for common health-related exposures. American Journal Of Human Genetics 2022, 109: 1742-1760. PMID: 36152628, PMCID: PMC9606385, DOI: 10.1016/j.ajhg.2022.09.001.Peer-Reviewed Original ResearchConceptsPolygenic risk scoresChronic conditionsPhenome-wide association studyMichigan Genomics InitiativeRisk scoreAssociation studiesHealth-related exposuresGenome-wide association studiesUK BiobankGenetic risk factorsPRS methodsFollow-up studyRisk factorsComplex traitsGenome InitiativeGenetic modifiersBiobankInfluence of exposureEnvironmental variablesScoresLipid levelsExpRLifestyleSmokingOnline repositoryPolygenic Liability to Depression Is Associated With Multiple Medical Conditions in the Electronic Health Record: Phenome-wide Association Study of 46,782 Individuals
Fang Y, Fritsche L, Mukherjee B, Sen S, Richmond-Rakerd L. Polygenic Liability to Depression Is Associated With Multiple Medical Conditions in the Electronic Health Record: Phenome-wide Association Study of 46,782 Individuals. Biological Psychiatry 2022, 92: 923-931. PMID: 35965108, PMCID: PMC10712651, DOI: 10.1016/j.biopsych.2022.06.004.Peer-Reviewed Original ResearchConceptsPhenome-wide association studyPolygenic risk scoresMDD PRSHealth recordsRisk scoreAssociation studiesGenome-wide polygenic risk scoreAssociated with multiple medical conditionsMeasures of genetic riskMichigan Genomics InitiativePsychiatric traitsElectronic health recordsEuropean ancestry participantsMajor depressive disorderAssociated with tobacco use disorderTests of associationMultiple medical conditionsGenitourinary conditionsTobacco use disorderDisease-associated disabilityMolecular genetic toolsMolecular genetic discoveriesPsychiatric disease categoriesHealth outcomesSubstance-related disorders
2021
A Phenome-Wide Association Study (PheWAS) of COVID-19 Outcomes by Race Using the Electronic Health Records Data in Michigan Medicine
Salvatore M, Gu T, Mack J, Sankar S, Patil S, Valley T, Singh K, Nallamothu B, Kheterpal S, Lisabeth L, Fritsche L, Mukherjee B. A Phenome-Wide Association Study (PheWAS) of COVID-19 Outcomes by Race Using the Electronic Health Records Data in Michigan Medicine. Journal Of Clinical Medicine 2021, 10: 1351. PMID: 33805886, PMCID: PMC8037108, DOI: 10.3390/jcm10071351.Peer-Reviewed Original ResearchPhenome-wide association studyCOVID-19 outcomesIntensive care unitAssociation studiesNon-Hispanic blacksNon-Hispanic whitesAcademic medical centerAssociated with hospitalizationHealthcare deliveryAssociated with mortalityMedicine backgroundPre-existing conditionsMedical phenomeDisease preventionVulnerable populationsPulmonary heart diseaseTargeted screeningMental disordersCOVID-19Associated with intensive care unitMedical CenterRecord DataCare unitGenitourinary conditionsHeart disease
2020
An analytic framework for exploring sampling and observation process biases in genome and phenome‐wide association studies using electronic health records
Beesley L, Fritsche L, Mukherjee B. An analytic framework for exploring sampling and observation process biases in genome and phenome‐wide association studies using electronic health records. Statistics In Medicine 2020, 39: 1965-1979. PMID: 32198773, DOI: 10.1002/sim.8524.Peer-Reviewed Original ResearchConceptsElectronic health recordsHealth recordsAssociation studiesObservational health care databasesElectronic health record dataLongitudinal biorepository effortPhenome-wide association studyMichigan Genomics InitiativeHealth record dataHealth care databasesDisease-gene association studiesMichigan Health SystemCare databaseHealth systemPhenotype misclassificationStudy biasRecord dataNonprobability samplingAssociation analysisData sourcesGenome InitiativeMisclassificationAnalysis approachRecordsSensitivity analysis
2019
Exploring various polygenic risk scores for skin cancer in the phenomes of the Michigan genomics initiative and the UK Biobank with a visual catalog: PRSWeb
Fritsche L, Beesley L, VandeHaar P, Peng R, Salvatore M, Zawistowski M, Taliun S, Das S, LeFaive J, Kaleba E, Klumpner T, Moser S, Blanc V, Brummett C, Kheterpal S, Abecasis G, Gruber S, Mukherjee B. Exploring various polygenic risk scores for skin cancer in the phenomes of the Michigan genomics initiative and the UK Biobank with a visual catalog: PRSWeb. PLOS Genetics 2019, 15: e1008202. PMID: 31194742, PMCID: PMC6592565, DOI: 10.1371/journal.pgen.1008202.Peer-Reviewed Original ResearchConceptsMichigan Genomics InitiativeElectronic health recordsPolygenic risk scoresSkin cancer subtypesPheWAS resultsUK BiobankElectronic health record dataLongitudinal biorepository effortPhenome-wide association studyRisk scoreHealth record dataUK Biobank dataPrediction of disease riskPublicly-available sourcesHealth recordsGenetic architectureBiobank dataMichigan MedicineRecord dataSecondary phenotypesDisease riskVisual catalogAssociation studiesGenome InitiativePheWAS