2019
A Fast and Accurate Method for Genome-wide Scale Phenome-wide G × E Analysis and Its Application to UK Biobank
Bi W, Zhao Z, Dey R, Fritsche L, Mukherjee B, Lee S. A Fast and Accurate Method for Genome-wide Scale Phenome-wide G × E Analysis and Its Application to UK Biobank. American Journal Of Human Genetics 2019, 105: 1182-1192. PMID: 31735295, PMCID: PMC6904814, DOI: 10.1016/j.ajhg.2019.10.008.Peer-Reviewed Original ResearchConceptsCase-control ratioGenome-wide significance levelMeasures of environmental exposureGenome-wide analysisEuropean ancestry samplesGenetic association studiesSaddlepoint approximationCase-control imbalanceAnalysis of phenotypesGene-environment interactionsPopulation-based biobanksControlled type I error ratesAssociation studiesG x E effectsUK BiobankType I error rateGenetic variantsE analysisSPAGEComplex diseasesEnvironmental exposuresTest statisticsE studySimulation studyWald test
2014
Latent variable models for gene–environment interactions in longitudinal studies with multiple correlated exposures
Tao Y, Sánchez B, Mukherjee B. Latent variable models for gene–environment interactions in longitudinal studies with multiple correlated exposures. Statistics In Medicine 2014, 34: 1227-1241. PMID: 25545894, PMCID: PMC4355187, DOI: 10.1002/sim.6401.Peer-Reviewed Original ResearchMeSH KeywordsBiostatisticsChild, PreschoolComputer SimulationEnvironmental ExposureFemaleGene-Environment InteractionHemochromatosis ProteinHistocompatibility Antigens Class IHumansInfantInfant, NewbornLead PoisoningLongitudinal StudiesMembrane ProteinsMexicoModels, GeneticModels, StatisticalPolymorphism, Single NucleotidePregnancyPrenatal Exposure Delayed EffectsConceptsGene-environment interactionsOutcome measuresCohort studyHealth effects of environmental exposuresEnvironmental exposuresInvestigate health effectsGene-environment associationsEffects of environmental exposuresEarly life exposuresLV frameworkG x E effectsMultivariate exposuresGenotyped single nucleotide polymorphismsEffect modificationShrinkage estimatorsLife exposureExposure measurementsSingle nucleotide polymorphismsData-adaptive wayMultiple testingOutcome dataLongitudinal studyLongitudinal natureGenetic factorsNucleotide polymorphisms
2011
A Latent Variable Approach to Study Gene–Environment Interactions in the Presence of Multiple Correlated Exposures
Sánchez B, Kang S, Mukherjee B. A Latent Variable Approach to Study Gene–Environment Interactions in the Presence of Multiple Correlated Exposures. Biometrics 2011, 68: 466-476. PMID: 21955029, PMCID: PMC4405908, DOI: 10.1111/j.1541-0420.2011.01677.x.Peer-Reviewed Original ResearchMeSH KeywordsAnalysis of VarianceBiasBiometryBirth WeightCase-Control StudiesComputer SimulationEnvironmental ExposureEpidemiologic FactorsFemaleGene-Environment InteractionHumansInfant, NewbornIronLead PoisoningModels, StatisticalPregnancyPrenatal Exposure Delayed EffectsPrincipal Component AnalysisConceptsGene-environment interactionsGene-environmentEnvironmental epidemiologyCohort studyGene-environment dependenceBurden of multiple testingStudy gene-environment interactionsEnvironmental exposuresExposure dataEarly life exposuresLV frameworkG x E effectsHealth StudyCorrelated exposuresG x EDisease riskLife exposureMultiple testingFunction of environmental exposureE studyGenotype categoriesStudy of lead exposureBirth weightIron metabolism genesAdaptive trade-off