2017
Current Challenges and New Opportunities for Gene-Environment Interaction Studies of Complex Diseases
McAllister K, Mechanic L, Amos C, Aschard H, Blair I, Chatterjee N, Conti D, Gauderman W, Hsu L, Hutter C, Jankowska M, Kerr J, Kraft P, Montgomery S, Mukherjee B, Papanicolaou G, Patel C, Ritchie M, Ritz B, Thomas D, Wei P, Witte J, participants O. Current Challenges and New Opportunities for Gene-Environment Interaction Studies of Complex Diseases. American Journal Of Epidemiology 2017, 186: 753-761. PMID: 28978193, PMCID: PMC5860428, DOI: 10.1093/aje/kwx227.Peer-Reviewed Original ResearchConceptsGene-environment interaction studiesStudies of complex diseasesGene-environmentAmerican Society of Human Genetics meetingMeasures of environmental exposureGene-environment interactionsComplex diseasesNational Institute of Environmental Health SciencesNational Cancer InstituteEnvironmental Health SciencesStudy designHealth SciencesCancer InstituteEnvironmental exposuresEnvironmental exposure assessmentNational InstituteLarge-scale studiesExposure assessmentNext-generation sequencing dataDisease outcomeNationalSequence dataThemesStudies of human populationsParticipants
2011
Testing Gene-Environment Interaction in Large-Scale Case-Control Association Studies: Possible Choices and Comparisons
Mukherjee B, Ahn J, Gruber S, Chatterjee N. Testing Gene-Environment Interaction in Large-Scale Case-Control Association Studies: Possible Choices and Comparisons. American Journal Of Epidemiology 2011, 175: 177-190. PMID: 22199027, PMCID: PMC3286201, DOI: 10.1093/aje/kwr367.Peer-Reviewed Original ResearchConceptsGene-environment independenceGene-environment interactionsCase-only methodTesting gene-environment interactionsCase-control testsExposure under studyCase-control association studyUnderlying populationCase-control methodCase-control analysisFraction of markersType I error propertiesGenome-wide scanClass of proceduresAssociation studiesData-adaptive wayComparative simulation studyLarge-scale studiesEmpirical-BayesIndependence assumptionFalse positivesPopulationReplication strategyHybrid methodIndependence