Featured Publications
A meta-inference framework to integrate multiple external models into a current study.
Gu T, Taylor J, Mukherjee B. A meta-inference framework to integrate multiple external models into a current study. Biostatistics 2021, 24: 406-424. PMID: 34269371, PMCID: PMC10102901, DOI: 10.1093/biostatistics/kxab017.Peer-Reviewed Original ResearchConceptsAccuracy of statistical inferenceEmpirical Bayes estimatorsSummary-level informationBias-variance trade-offRelevant external informationBayes estimatorsStatistical inferenceExternal informationExternal estimatesNaive analysisNaive combinationInternational dataWeight estimationExternal modelMeta-analysis frameworkIndividual-level dataEfficiency gainsEstimationInfluence of informationTrade-offsInformationFrameworkIncorporating functional annotation with bilevel continuous shrinkage for polygenic risk prediction
Zhuang Y, Kim N, Fritsche L, Mukherjee B, Lee S. Incorporating functional annotation with bilevel continuous shrinkage for polygenic risk prediction. BMC Bioinformatics 2024, 25: 65. PMID: 38336614, PMCID: PMC11323637, DOI: 10.1186/s12859-024-05664-2.Peer-Reviewed Original ResearchConceptsPredictive performance of polygenic risk scoresFunctional annotationGenetic architecturePerformance of polygenic risk scoresPRS-CSAnnotation informationPolygenic risk predictionGenetic risk predictionPolygenic risk scoresFunctional annotation informationKyoto Encyclopedia of GenesRisk predictionProportion of variantsEncyclopedia of GenesGenomes (KEGGSource of annotationTrait heritabilityAnnotation groupsPathway informationQuantitative traitsKyoto EncyclopediaFunctional categoriesBackgroundGenetic variantsHeritable contributionReal world data sourcesMethods for mediation analysis with high-dimensional DNA methylation data: Possible choices and comparisons
Clark-Boucher D, Zhou X, Du J, Liu Y, Needham B, Smith J, Mukherjee B. Methods for mediation analysis with high-dimensional DNA methylation data: Possible choices and comparisons. PLOS Genetics 2023, 19: e1011022. PMID: 37934796, PMCID: PMC10655967, DOI: 10.1371/journal.pgen.1011022.Peer-Reviewed Original ResearchMeSH KeywordsBayes TheoremDNA MethylationEnvironmental ExposureHumansLinear ModelsMediation AnalysisConceptsBayesian Sparse Linear Mixed ModelMediation analysisHigh-dimensional mediation analysisMulti-ethnic cohortEpigenetic researchHealth outcomesHigh-dimensional DNA methylation dataLinear mixed modelsDNA methylation dataContinuous outcomesEvaluate DNA methylationDNA methylationMethylation dataDNAm dataMixed modelsDiverse simulationsSeamless implementationModern statistical methodsMediation effectR packageUnited StatesOutcomesExploiting Gene-Environment Independence for Analysis of Case–Control Studies: An Empirical Bayes-Type Shrinkage Estimator to Trade-Off Between Bias and Efficiency
Mukherjee B, Chatterjee N. Exploiting Gene-Environment Independence for Analysis of Case–Control Studies: An Empirical Bayes-Type Shrinkage Estimator to Trade-Off Between Bias and Efficiency. Biometrics 2007, 64: 685-694. PMID: 18162111, DOI: 10.1111/j.1541-0420.2007.00953.x.Peer-Reviewed Original ResearchConceptsGene-environment independenceShrinkage estimatorsLog odds ratio parametersCase-control dataGene-environment independence assumptionOdds ratio parametersCase-control estimatorsData-adaptive fashionData exampleProspective logistic regression analysisBinary exposureGene-environment associationsIndependence assumptionLogistic regression analysisCase-onlyMaximum likelihood frameworkEstimationSample sizeBinary genesRegression analysisChatterjeeExamplesWeighted averageAssumptions
2023
Prenatal per- and polyfluoroalkyl substances (PFAS) exposure in relation to preterm birth subtypes and size-for-gestational age in the LIFECODES cohort 2006–2008
Siwakoti R, Cathey A, Ferguson K, Hao W, Cantonwine D, Mukherjee B, McElrath T, Meeker J. Prenatal per- and polyfluoroalkyl substances (PFAS) exposure in relation to preterm birth subtypes and size-for-gestational age in the LIFECODES cohort 2006–2008. Environmental Research 2023, 237: 116967. PMID: 37634691, PMCID: PMC10913455, DOI: 10.1016/j.envres.2023.116967.Peer-Reviewed Original ResearchConceptsLarge-for-gestational agePreterm birth subtypesBayesian kernel machine regressionSize-for-gestational ageSmall-for-gestational agePreterm birthFetal sexPregnancy outcomesSex-specific estimatesIncreased risk of adverse pregnancy outcomesInterquartile range increaseRisk of adverse pregnancy outcomesBayesian kernel machine regression analysisEarly pregnancy samplesAdverse pregnancy outcomesCase-control studyPrenatal PFAS exposureAssociations of polyfluoroalkyl substancesBW z-scoreEffects of polyfluoroalkyl substancesKernel machine regressionEffect modificationEffects of prenatal exposureRange increaseStratified analysis
2022
Exposure to heavy metals and hormone levels in midlife women: The Study of Women's Health Across the Nation (SWAN)
Wang X, Ding N, Harlow S, Randolph J, Mukherjee B, Gold E, Park S. Exposure to heavy metals and hormone levels in midlife women: The Study of Women's Health Across the Nation (SWAN). Environmental Pollution 2022, 317: 120740. PMID: 36436662, PMCID: PMC9897061, DOI: 10.1016/j.envpol.2022.120740.Peer-Reviewed Original ResearchConceptsUrinary metal concentrationsExposure to heavy metalsHeavy metalsMetal concentrationsStudy of Women's HealthAssociation of heavy metalsEnvironmental heavy metal exposureHeavy metal exposureSex hormone-binding globulinFollicle-stimulating hormoneWomen's HealthBayesian kernel machine regressionAssociated with E<sub>2</sub>, TMidlife womenKernel machine regressionMetal exposureSerum hormone levelsMetal mixturesHealth-related factorsNation Multi-Pollutant StudyCalculate percent changesCadmiumHormone levelsProspective cohort studyLinear mixed effects modelsBiomarkers of Exposure to Phthalate Mixtures and Adverse Birth Outcomes in a Puerto Rico Birth Cohort
Cathey A, Watkins D, Rosario Z, Vélez C, Mukherjee B, Alshawabkeh A, Cordero J, Meeker J. Biomarkers of Exposure to Phthalate Mixtures and Adverse Birth Outcomes in a Puerto Rico Birth Cohort. Environmental Health Perspectives 2022, 130: 037009. PMID: 35333099, PMCID: PMC8953418, DOI: 10.1289/ehp8990.Peer-Reviewed Original ResearchConceptsSpontaneous preterm birthPreterm birthFetal sexGestational agePregnancy outcomesBirth outcomesBayesian kernel machine regressionPhthalate metabolitesRisk of early deliveryAssociated with increased odds of PTBOdds of preterm birthPhthalate mixtureReduced gestational ageIndividual phthalate metabolitesMeasures of birth weightAssociated with increased riskPhthalate metabolite mixturesAdverse birth outcomesAssociated with increased oddsPuerto Rico TestsiteEnvironmental risk scoreEarly deliveryBirth weightPregnancy cohortLongitudinal pregnancy cohortRace-specific associations of urinary phenols and parabens with adipokines in midlife women: The Study of Women's Health Across the Nation (SWAN)
Lee S, Karvonen-Gutierrez C, Mukherjee B, Herman W, Park S. Race-specific associations of urinary phenols and parabens with adipokines in midlife women: The Study of Women's Health Across the Nation (SWAN). Environmental Pollution 2022, 303: 119164. PMID: 35306088, PMCID: PMC9883839, DOI: 10.1016/j.envpol.2022.119164.Peer-Reviewed Original ResearchMeSH KeywordsAdipokinesAdiponectinBayes TheoremCross-Sectional StudiesFemaleHumansLeptinMiddle AgedParabensPhenolsWomen's HealthConceptsStudy of Women's HealthBayesian kernel machine regressionWomen's HealthLeptin levelsBlack womenAssociated with lower leptinAssociated with favorable profilesAsian womenSoluble leptin receptorRacial differencesRace-specific associationsUrinary phenolCross-sectional associationsNo significant associationObesity-related metabolic diseasesLog-transformed levelsSOB-RKernel machine regressionSerum adipokinesMetabolic disease burdenEffect modificationNation Multi-Pollutant StudyLow leptinLeptin receptorLinear regression models
2021
Bayesian hierarchical models for high‐dimensional mediation analysis with coordinated selection of correlated mediators
Song Y, Zhou X, Kang J, Aung M, Zhang M, Zhao W, Needham B, Kardia S, Liu Y, Meeker J, Smith J, Mukherjee B. Bayesian hierarchical models for high‐dimensional mediation analysis with coordinated selection of correlated mediators. Statistics In Medicine 2021, 40: 6038-6056. PMID: 34404112, PMCID: PMC9257993, DOI: 10.1002/sim.9168.Peer-Reviewed Original ResearchA comparison of five epidemiological models for transmission of SARS-CoV-2 in India
Purkayastha S, Bhattacharyya R, Bhaduri R, Kundu R, Gu X, Salvatore M, Ray D, Mishra S, Mukherjee B. A comparison of five epidemiological models for transmission of SARS-CoV-2 in India. BMC Infectious Diseases 2021, 21: 533. PMID: 34098885, PMCID: PMC8181542, DOI: 10.1186/s12879-021-06077-9.Peer-Reviewed Original ResearchAssociations of perfluoroalkyl and polyfluoroalkyl substances (PFAS) and PFAS mixtures with adipokines in midlife women
Ding N, Karvonen-Gutierrez C, Herman W, Calafat A, Mukherjee B, Park S. Associations of perfluoroalkyl and polyfluoroalkyl substances (PFAS) and PFAS mixtures with adipokines in midlife women. International Journal Of Hygiene And Environmental Health 2021, 235: 113777. PMID: 34090141, PMCID: PMC8207532, DOI: 10.1016/j.ijheh.2021.113777.Peer-Reviewed Original ResearchMeSH KeywordsAdipokinesAlkanesulfonic AcidsBayes TheoremEnvironmental PollutantsFemaleFluorocarbonsHumansWomen's HealthConceptsBayesian kernel machine regressionNormal weightStudy of Women's HealthCirculating levels of leptinHMW adiponectinBayesian kernel machine regression analysisSoluble leptin receptorFree leptin indexSOB-R concentrationsBaseline serum samplesLevels of leptinMultivariate linear regressionPhysical activityAssociated with obesityStatistically significant associationWomen's HealthPolyfluoroalkyl substancesWaist circumferenceKernel machine regressionWomen's backgroundInfluence obesityMidlife womenSmoking statusSOB-RMenopausal statusIndividual and joint effects of phthalate metabolites on biomarkers of oxidative stress among pregnant women in Puerto Rico
Cathey A, Eaton J, Ashrap P, Watkins D, Rosario Z, Vega C, Alshawabkeh A, Cordero J, Mukherjee B, Meeker J. Individual and joint effects of phthalate metabolites on biomarkers of oxidative stress among pregnant women in Puerto Rico. Environment International 2021, 154: 106565. PMID: 33882432, PMCID: PMC9923976, DOI: 10.1016/j.envint.2021.106565.Peer-Reviewed Original ResearchMeSH KeywordsBayes TheoremBiomarkersFemaleHumansOxidative StressPhthalic AcidsPregnancyPregnant WomenPuerto RicoConceptsBayesian kernel machine regressionPhthalate metabolitesEnvironmental risk scoreBiomarkers of oxidative stressPregnant womenPhthalate mixtureBayesian kernel machine regression analysisEffects of phthalate metabolitesOxidative stressIndividual phthalate metabolitesLipid oxidative stressUrinary biomarker measurementsKernel machine regressionAdverse birth outcomesPuerto Rico TestsiteOxidative stress biomarkersChemical fractionationContamination threatLongitudinal birth cohortPhthalate compoundsLinear mixed effects modelsBirth outcomesOxidative stress mechanismsStudy visitsPhthalate exposureCross-Sectional Estimation of Endogenous Biomarker Associations with Prenatal Phenols, Phthalates, Metals, and Polycyclic Aromatic Hydrocarbons in Single-Pollutant and Mixtures Analysis Approaches
Aung M, Yu Y, Ferguson K, Cantonwine D, Zeng L, McElrath T, Pennathur S, Mukherjee B, Meeker J. Cross-Sectional Estimation of Endogenous Biomarker Associations with Prenatal Phenols, Phthalates, Metals, and Polycyclic Aromatic Hydrocarbons in Single-Pollutant and Mixtures Analysis Approaches. Environmental Health Perspectives 2021, 129: 037007. PMID: 33761273, PMCID: PMC7990518, DOI: 10.1289/ehp7396.Peer-Reviewed Original ResearchConceptsExposure analytesToxicity classesMixtures of toxicantsSingle-pollutant modelsPolycyclic aromatic hydrocarbonsHierarchical Bayesian kernel machine regressionBayesian kernel machine regressionKernel machine regressionPrenatal toxicant exposureAdaptive elastic net regressionClasses of toxicantsSingle-pollutantTrace metalsAromatic hydrocarbonsToxic mixturePair-wise associationsAdaptive elastic netToxicant exposurePhthalateMachine regressionEndogenous biomarkersBiomarkers indicativeMultiple linear regressionMetalToxicityRevisiting the genome-wide significance threshold for common variant GWAS
Chen Z, Boehnke M, Wen X, Mukherjee B. Revisiting the genome-wide significance threshold for common variant GWAS. G3: Genes, Genomes, Genetics 2021, 11: jkaa056. PMID: 33585870, PMCID: PMC8022962, DOI: 10.1093/g3journal/jkaa056.Peer-Reviewed Original ResearchConceptsGenome-wide significance thresholdP-value thresholdGWAS meta-analysesMeta-analysis consortiumExcessive false positive ratesSignificance thresholdGene set enrichmentBenjamini-Yekutieli procedureModest-sized studiesFDR-controlling proceduresGlobal lipidsMeta-analysesPathway analysisGWASReplication studyP-valueIncreased discoveryMultiple testing strategiesSample sizePositive discoveriesBenjamini-HochbergLipid levelsTesting strategiesDownstream workFDR
2020
Maternal blood metal and metalloid concentrations in association with birth outcomes in Northern Puerto Rico
Ashrap P, Watkins D, Mukherjee B, Boss J, Richards M, Rosario Z, Vélez-Vega C, Alshawabkeh A, Cordero J, Meeker J. Maternal blood metal and metalloid concentrations in association with birth outcomes in Northern Puerto Rico. Environment International 2020, 138: 105606. PMID: 32179314, PMCID: PMC7198231, DOI: 10.1016/j.envint.2020.105606.Peer-Reviewed Original ResearchMeSH KeywordsBayes TheoremFemaleGestational AgeHumansInfant, NewbornMaternal ExposureMetalloidsPregnancyPremature BirthPuerto RicoConceptsBayesian kernel machine regressionShorter gestational agePreterm birthGestational ageEnvironmental risk scoreBirth outcomesMetal concentrationsNon-essential metal(loid)sHigher risk of preterm birthRisk of preterm birthLow-level prenatal lead exposureInterquartile rangeOdds of preterm birthAssociated with higher risk of preterm birthRisk scoreEffects of metalsPredictors of birth outcomesAssociated with birth outcomesBayesian kernel machine regression modelsBirthweight z-scoreAssociated with adverse birth outcomesAssociated with higher riskAdverse birth outcomesKernel machine regressionPuerto Rico TestsiteMethods to Account for Uncertainty in Latent Class Assignments When Using Latent Classes as Predictors in Regression Models, with Application to Acculturation Strategy Measures.
Elliott M, Zhao Z, Mukherjee B, Kanaya A, Needham B. Methods to Account for Uncertainty in Latent Class Assignments When Using Latent Classes as Predictors in Regression Models, with Application to Acculturation Strategy Measures. Epidemiology 2020, 31: 194-204. PMID: 31809338, PMCID: PMC7480960, DOI: 10.1097/ede.0000000000001139.Peer-Reviewed Original ResearchConceptsMeasurement error modelJoint modelRegression parametersLatent classesLikelihood-basedLatent class modelSimulation studyClass modelTwo-stage modelClassError modelPrimary interestAcculturation behaviorsMeasurement errorSouth Asian immigrantsLatent class analysisAsian immigrantsTrue classUncertaintyClass analysisEstimationStrategy measures
2019
Bayesian Shrinkage Estimation of High Dimensional Causal Mediation Effects in Omics Studies
Song Y, Zhou X, Zhang M, Zhao W, Liu Y, Kardia S, Roux A, Needham B, Smith J, Mukherjee B. Bayesian Shrinkage Estimation of High Dimensional Causal Mediation Effects in Omics Studies. Biometrics 2019, 76: 700-710. PMID: 31733066, PMCID: PMC7228845, DOI: 10.1111/biom.13189.Peer-Reviewed Original ResearchConceptsMediation analysisEffect of socioeconomic statusPotential mediatorsMulti-Ethnic StudyCausal mediation analysisCardiometabolic outcomesDNA methylation regionsSocioeconomic statusHigh-throughput technologiesMediation effectGenomic dataEpidemiological dataMethylation regionsHigh-dimensional mediatorsBayesian inference methodsContinuous shrinkage priorsHigh-dimensional settingsBayesian shrinkage estimatorsJoint analysisOutcomesShrinkage priorsPathwayNull caseInference methodsBiomedical studies
2018
Model-Based and Model-Free Techniques for Amyotrophic Lateral Sclerosis Diagnostic Prediction and Patient Clustering
Tang M, Gao C, Goutman S, Kalinin A, Mukherjee B, Guan Y, Dinov I. Model-Based and Model-Free Techniques for Amyotrophic Lateral Sclerosis Diagnostic Prediction and Patient Clustering. Neuroinformatics 2018, 17: 407-421. PMID: 30460455, PMCID: PMC6527505, DOI: 10.1007/s12021-018-9406-9.Peer-Reviewed Original ResearchConceptsAmyotrophic Lateral Sclerosis Functional Rating ScaleClusters of participantsModel-basedAmyotrophic lateral sclerosisRating ScaleComputable phenotypeFunctional Rating ScaleSets of featuresUnsupervised clusteringUnsupervised machine learning methodsClinical decision supportMachine learning methodsImputation of missing values in a large job exposure matrix using hierarchical information
Roberts B, Cheng W, Mukherjee B, Neitzel R. Imputation of missing values in a large job exposure matrix using hierarchical information. Journal Of Exposure Science & Environmental Epidemiology 2018, 28: 615-648. PMID: 29789667, PMCID: PMC9929916, DOI: 10.1038/s41370-018-0037-x.Peer-Reviewed Original ResearchImproving estimation and prediction in linear regression incorporating external information from an established reduced model
Cheng W, Taylor J, Vokonas P, Park S, Mukherjee B. Improving estimation and prediction in linear regression incorporating external information from an established reduced model. Statistics In Medicine 2018, 37: 1515-1530. PMID: 29365342, PMCID: PMC5889759, DOI: 10.1002/sim.7600.Peer-Reviewed Original ResearchMeSH KeywordsBayes TheoremData Interpretation, StatisticalHumansLinear ModelsModels, StatisticalRegression AnalysisConceptsOutcome variable YEfficiency of estimationApproximate Bayesian inferenceBayes solutionVariable YNonlinear constraintsInferential frameworkVariable BE(Y|XImprove inferenceBayesian inferenceEffective computational methodParameter spaceReduced modelImproved estimatesLinear regression modelsTransformation approachStandard errorDunsonInferenceEstimationRegression modelsProblemCovariatesSpace