Featured Publications
Set‐based tests for genetic association in longitudinal studies
He Z, Zhang M, Lee S, Smith J, Guo X, Palmas W, Kardia S, Diez Roux A, Mukherjee B. Set‐based tests for genetic association in longitudinal studies. Biometrics 2015, 71: 606-615. PMID: 25854837, PMCID: PMC4601568, DOI: 10.1111/biom.12310.Peer-Reviewed Original ResearchConceptsMulti-Ethnic Study of AtherosclerosisGenome-wide association studiesJoint effect of multiple variantsLinkage disequilibriumAssociation studiesEffects of multiple variantsMarkers of chronic diseaseGenetic variantsSet-based testGene-based testsLongitudinal outcomesMulti-Ethnic StudyGenetic association studiesStudy of AtherosclerosisChronic diseasesPhenotypic variationGenetic associationObservational studyLongitudinal analysisWithin-subject correlationMultiple variantsScore type testsJoint testJoint effectsMarker tests
2016
Tests for Gene-Environment Interactions and Joint Effects With Exposure Misclassification
Boonstra P, Mukherjee B, Gruber S, Ahn J, Schmit S, Chatterjee N. Tests for Gene-Environment Interactions and Joint Effects With Exposure Misclassification. American Journal Of Epidemiology 2016, 183: 237-247. PMID: 26755675, PMCID: PMC4724093, DOI: 10.1093/aje/kwv198.Peer-Reviewed Original ResearchConceptsG-E interactionsPresence of exposure misclassificationExposure misclassificationImpact of exposure misclassificationGene-environment (G-EGene-environment interactionsGenome-wide levelGenome-wide searchGenome-wide testingGenetic susceptibility lociJoint testDisease-gene relationshipsGene-environmentGenetic risk factorsType I error rateFamily-wise type I error rateSusceptibility lociG-EGenetic associationRisk factorsStatistical powerJoint effectsSimulation studyMisclassificationPublished simulation studies
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
2013
Environmental Confounding in Gene-Environment Interaction Studies
Vanderweele T, Ko Y, Mukherjee B. Environmental Confounding in Gene-Environment Interaction Studies. American Journal Of Epidemiology 2013, 178: 144-152. PMID: 23821317, PMCID: PMC3698991, DOI: 10.1093/aje/kws439.Peer-Reviewed Original ResearchConceptsGene-environment independenceGene-environment interaction studiesGene-environment interactionsEnvironmental confoundersGenetic factorsJoint testGene-environmentGenetic effectsEnvironmental factorsConfounding variablesConfoundingInteraction studiesSimulation studyJoint nullSample sizeBias estimatesFactorsIndependenceStudyTest