Featured Publications
Risk of Non-Melanoma Cancers in First-Degree Relatives of CDKN2A Mutation Carriers
Mukherjee B, DeLancey J, Raskin L, Everett J, Jeter J, Begg C, Orlow I, Berwick M, Armstrong B, Kricker A, Marrett L, Millikan R, Culver H, Rosso S, Zanetti R, Kanetsky P, From L, Gruber S, Investigators F. Risk of Non-Melanoma Cancers in First-Degree Relatives of CDKN2A Mutation Carriers. Journal Of The National Cancer Institute 2012, 104: 953-956. PMID: 22534780, PMCID: PMC3379723, DOI: 10.1093/jnci/djs221.Peer-Reviewed Original ResearchConceptsFirst-degree relatives of carriersCDKN2A mutation carriersFirst-degree relativesMutation carriersNon-melanoma cancersFirst-degree relatives of melanoma patientsFirst-degree relatives of mutation carriersKin-cohort methodConfidence intervalsRisk of cancerMelanoma patientsLifetime riskProband's genotypeNon-melanomaFamily membersIncreased riskGastrointestinal cancerCDKN2A mutationsWilms tumorRiskMelanoma StudyPancreatic cancerNoncarriersGenotype distributionMelanoma
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 riskUsing Multi-Modal Electronic Health Record Data for the Development and Validation of Risk Prediction Models for Long COVID Using the Super Learner Algorithm
Jin W, Hao W, Shi X, Fritsche L, Salvatore M, Admon A, Friese C, Mukherjee B. Using Multi-Modal Electronic Health Record Data for the Development and Validation of Risk Prediction Models for Long COVID Using the Super Learner Algorithm. Journal Of Clinical Medicine 2023, 12: 7313. PMID: 38068365, PMCID: PMC10707399, DOI: 10.3390/jcm12237313.Peer-Reviewed Original ResearchComposite risk scoreRisk scoreElectronic health recordsAnalyses identified several factorsValidation of risk prediction modelsModerate discriminatory abilityRisk prediction modelPost-acute sequelae of COVID-19Health recordsCombined risk scorePost-acuteIdentification of individualsPrevention effortsSuper Learner algorithmMedical recordsHealthcare challengesPublic healthMedical phenotypesCOVID-19Increased riskPredictive factorsCOVID-19 infectionRecord DataPost-acute sequelaeHigh riskCharacterizing and Predicting Post-Acute Sequelae of SARS CoV-2 Infection (PASC) in a Large Academic Medical Center in the US
Fritsche L, Jin W, Admon A, Mukherjee B. Characterizing and Predicting Post-Acute Sequelae of SARS CoV-2 Infection (PASC) in a Large Academic Medical Center in the US. Journal Of Clinical Medicine 2023, 12: 1328. PMID: 36835863, PMCID: PMC9967320, DOI: 10.3390/jcm12041328.Peer-Reviewed Original ResearchPost-Acute Sequelae of SARS CoV-2 infectionElectronic health record dataPhenotype risk scoreHealth record dataCase-control study designPhenome-wide scanAcademic medical centerRisk prediction modelPost-COVID-19Risk stratification approachStudy designRecord dataRisk scoreHistory of COVID-19Medical CenterCOVID-19Increased riskPre-COVID-19Post-acute sequelaePre-COVID-19 periodRiskPost-COVID-19 periodCohortStratification approachSARS CoV-2 infectionCOVID-19 outcomes by cancer status, site, treatment, and vaccination
Salvatore M, Hu M, Beesley L, Mondul A, Pearce C, Friese C, Fritsche L, Mukherjee B. COVID-19 outcomes by cancer status, site, treatment, and vaccination. Cancer Epidemiology Biomarkers & Prevention 2023, 32: 748-759. PMID: 36626383, DOI: 10.1158/1055-9965.epi-22-0607.Peer-Reviewed Original ResearchConceptsCOVID-19 outcomesCancer statusCancer diagnosisAssociated with higher ratesElectronic health record dataHealth record dataColorectal cancerIncreased riskAcademic medical centerKidney cancerCancer-free patientsIntensive care unit admissionCancer sitesAssociated with lower ratesChemotherapy receiptHigher ratesCOVID-19 precautionsRecord dataCOVID-19Logistic regressionMedical CenterUnit admissionRetrospective cohortVaccination statusLung cancer
2021
Maternal lipidomic signatures in relation to spontaneous preterm birth and large-for-gestational age neonates
Aung M, Ashrap P, Watkins D, Mukherjee B, Rosario Z, Vélez-Vega C, Alshawabkeh A, Cordero J, Meeker J. Maternal lipidomic signatures in relation to spontaneous preterm birth and large-for-gestational age neonates. Scientific Reports 2021, 11: 8115. PMID: 33854141, PMCID: PMC8046995, DOI: 10.1038/s41598-021-87472-9.Peer-Reviewed Original ResearchConceptsSpontaneous preterm birthBiomarkers of pregnancy outcomesGestational age neonatesPreterm birthAge neonatesPregnancy outcomesDegree of hydrocarbon chain saturationIncreased riskNeonatal anthropometric parametersAssociated with increased riskPlasmenyl phosphatidylethanolamineMaternal lipidomeWeeks gestationGestational ageLipidomic signatureAnthropometric parametersLiquid chromatography tandem mass spectrometryLipidomic profilesLipid metabolitesHydrocarbon chain saturationPlasma samplesBirthLogistic regressionHigh-performance liquid chromatography tandem mass spectrometryNeonates