2017
Update on the State of the Science for Analytical Methods for Gene-Environment Interactions
Gauderman W, Mukherjee B, Aschard H, Hsu L, Lewinger J, Patel C, Witte J, Amos C, Tai C, Conti D, Torgerson D, Lee S, Chatterjee N. Update on the State of the Science for Analytical Methods for Gene-Environment Interactions. American Journal Of Epidemiology 2017, 186: 762-770. PMID: 28978192, PMCID: PMC5859988, DOI: 10.1093/aje/kwx228.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesG x EGene-environment interactionsAssociation studiesAnalysis of gene-environment interactionsQuantitative trait studiesComplex traitsGenetic dataGene setsTrait studiesGene-environmentCase-controlEnvironmental dataConsortium settingFormation of consortiaGenesConsortiumAnalytical challengesTraitsSetsStudyInteractionStatistical approachDataExposure enriched outcome dependent designs for longitudinal studies of gene–environment interaction
Sun Z, Mukherjee B, Estes J, Vokonas P, Park S. Exposure enriched outcome dependent designs for longitudinal studies of gene–environment interaction. Statistics In Medicine 2017, 36: 2947-2960. PMID: 28497531, PMCID: PMC5523112, DOI: 10.1002/sim.7332.Peer-Reviewed Original ResearchConceptsLongitudinal cohort studyCohort studyCase-only designLongitudinal studyG x E interactionNormative Aging StudyComplete-case analysisGene-environmentSampling designCase-controlVeterans AdministrationComplex human diseasesE interactionExposure informationAging StudyOutcome trajectoriesStratified samplingRetrospective genotypingIndividual exposureCovariate dataExposure effectsJoint effectsOutcomesTime-varying outcomeEnvironmental factors
2014
The impact of exposure-biased sampling designs on detection of gene–environment interactions in case–control studies with potential exposure misclassification
Stenzel S, Ahn J, Boonstra P, Gruber S, Mukherjee B. The impact of exposure-biased sampling designs on detection of gene–environment interactions in case–control studies with potential exposure misclassification. European Journal Of Epidemiology 2014, 30: 413-423. PMID: 24894824, PMCID: PMC4256150, DOI: 10.1007/s10654-014-9908-1.Peer-Reviewed Original ResearchConceptsG-E interactionsExposure informationDetection of gene-environment interactionsPrevalence of exposureGene-environment interactionsSampling designCase-control studyRandom selection of subjectsPerformance of sampling designsCase-onlyExposure prevalenceJoint testExposure misclassificationCase-controlRare exposuresMarginal associationSelection of subjectsType I errorEmpirical simulation studyIdeal sampling schemesJoint effectsPrevalenceRandom selectionG-EMisclassification
2012
A Bayesian Semiparametric Approach for Incorporating Longitudinal Information on Exposure History for Inference in Case–Control Studies
Bhadra D, Daniels M, Kim S, Ghosh M, Mukherjee B. A Bayesian Semiparametric Approach for Incorporating Longitudinal Information on Exposure History for Inference in Case–Control Studies. Biometrics 2012, 68: 361-370. PMID: 22313248, PMCID: PMC3935236, DOI: 10.1111/j.1541-0420.2011.01686.x.Peer-Reviewed Original ResearchConceptsBayesian semiparametric approachSemiparametric approachCase-control studyReversible jump Markov chain Monte Carlo algorithmMarkov chain Monte Carlo algorithmMeasures of cumulative exposureLongitudinal biomarker informationMonte Carlo algorithmClinically meaningful estimatesSmooth functionsCase-control study of prostate cancerWeighted integralsCumulative exposureInfluence functionJoint likelihoodLikelihood formulationExposure historyStudy of prostate cancerDisease risk modelsHierarchical Bayesian frameworkDisease statusBayesian frameworkCase-controlRisk modelCohort study
2009
Case–Control Studies of Gene–Environment Interaction: Bayesian Design and Analysis
Mukherjee B, Ahn J, Gruber S, Ghosh M, Chatterjee N. Case–Control Studies of Gene–Environment Interaction: Bayesian Design and Analysis. Biometrics 2009, 66: 934-948. PMID: 19930190, PMCID: PMC3103064, DOI: 10.1111/j.1541-0420.2009.01357.x.Peer-Reviewed Original ResearchConceptsGene-environment interactionsCase-control study of colorectal cancerStudy of gene-environment interactionsStudy of colorectal cancerGene-environment independenceRed meat consumptionBayesian designCase-control studyBayesian approachSample size determination criteriaCase-controlEpidemiological studiesColorectal cancerFrequentist counterpartsNatural wayMeat consumptionAnalyze current dataHypothesis testingDetermination criteriaSmokingEpidemiological exposureAnalysis strategyStudy
2008
Tests for gene‐environment interaction from case‐control data: a novel study of type I error, power and designs
Mukherjee B, Ahn J, Gruber S, Rennert G, Moreno V, Chatterjee N. Tests for gene‐environment interaction from case‐control data: a novel study of type I error, power and designs. Genetic Epidemiology 2008, 32: 615-626. PMID: 18473390, DOI: 10.1002/gepi.20337.Peer-Reviewed Original ResearchConceptsGene-environment independence assumptionCase-control studyGene-environment interactionsGene-environment associationsCase-onlyCase-control study of colorectal cancerDetection of gene-environment interactionsType I errorGene-environment dependenceStudy of colorectal cancerGene-environment independenceEffect of genetic susceptibilityCase-only methodCase-only estimatorCase-control estimatorsCase-control dataGene-environment effectsCase-control designCase-control methodCase-control analysisGlutathione S-transferase M1Empirical-BayesEpidemiological researchCase-controlColorectal cancer