Featured Publications
Exploiting 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
2024
Avocational exposure associations with ALS risk, survival, and phenotype: A Michigan-based case-control study
Goutman S, Boss J, Jang D, Piecuch C, Farid H, Batra M, Mukherjee B, Feldman E, Batterman S. Avocational exposure associations with ALS risk, survival, and phenotype: A Michigan-based case-control study. Journal Of The Neurological Sciences 2024, 457: 122899. PMID: 38278093, PMCID: PMC11060628, DOI: 10.1016/j.jns.2024.122899.Peer-Reviewed Original ResearchMeSH KeywordsAmyotrophic Lateral SclerosisCase-Control StudiesEnvironmental ExposureHumansMichiganMiddle AgedPhenotypeRisk FactorsConceptsALS riskLower educational attainmentAssociated with ALS riskCase-control studyExercise 5Onset ageSelf-completionExposure variablesYard workExposure associationsRecreational danceIdentified exposureExerciseEducational attainmentAL burdenEnvironmental exposuresParticipantsAL factorPersonal participationAvocational exposureRiskExposomeHobbiesALS onsetComparison correction
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 analysisA framework for assessing interactions for risk stratification models: the example of ovarian cancer
Phung M, Lee A, McLean K, Anton-Culver H, Bandera E, Carney M, Chang-Claude J, Cramer D, Doherty J, Fortner R, Goodman M, Harris H, Jensen A, Modugno F, Moysich K, Pharoah P, Qin B, Terry K, Titus L, Webb P, Wu A, Zeinomar N, Ziogas A, Berchuck A, Cho K, Hanley G, Meza R, Mukherjee B, Pike M, Pearce C, Trabert B. A framework for assessing interactions for risk stratification models: the example of ovarian cancer. Journal Of The National Cancer Institute 2023, 115: 1420-1426. PMID: 37436712, PMCID: PMC10637032, DOI: 10.1093/jnci/djad137.Peer-Reviewed Original ResearchConceptsFamily history of ovarian cancerOvarian Cancer Association ConsortiumHistory of ovarian cancerFirst-degree family historyMenopausal statusRisk stratification modelCase-control studyRisk prediction modelOvarian cancerDisease riskAccurate risk stratification modelsStratification modelRisk/protective factorsDepot medroxyprogesterone acetate useProtective factorsFactor analysisRiskComprehensive analysis of interactionsCancerAcetate useUnequivocal riskStatusBreastfeedingAnalysis of interactionsPairwise interactions
2022
A Case-Crossover Phenome-wide association study (PheWAS) for understanding Post-COVID-19 diagnosis patterns
Haupert S, Shi X, Chen C, Fritsche L, Mukherjee B. A Case-Crossover Phenome-wide association study (PheWAS) for understanding Post-COVID-19 diagnosis patterns. Journal Of Biomedical Informatics 2022, 136: 104237. PMID: 36283580, PMCID: PMC9595430, DOI: 10.1016/j.jbi.2022.104237.Peer-Reviewed Original ResearchConceptsPhenome-wide association studyPost-COVID-19 conditionCOVID-19 survivorsCohort of COVID-19 survivorsAssociation studiesMental health disordersConditional logistic regressionWithin-person confoundingSARS-CoV-2 infectionRobust study designsProportion of COVID-19 survivorsPost-COVID-19Healthcare needsMental healthSARS-CoV-2Circulatory diseasesPhenotype codesHealth disordersSARS-CoV-2 positivityStudy designSARS-CoV-2 positive patientsLogistic regressionPheWASPost-COVID-19 infectionCOVID-19Incorporating family disease history and controlling case–control imbalance for population-based genetic association studies
Zhuang Y, Wolford B, Nam K, Bi W, Zhou W, Willer C, Mukherjee B, Lee S. Incorporating family disease history and controlling case–control imbalance for population-based genetic association studies. Bioinformatics 2022, 38: 4337-4343. PMID: 35876838, PMCID: PMC9477535, DOI: 10.1093/bioinformatics/btac459.Peer-Reviewed Original ResearchMeSH KeywordsCase-Control StudiesComputer SimulationGenome-Wide Association StudyPhenotypePolymorphism, Single NucleotideConceptsEmpirical saddlepoint approximationFamily disease historyCase-control imbalanceSaddlepoint approximationGenome-wide association analysisPopulation-based genetic association studiesGenetic association testsVariant-phenotype associationsDisease historyGenetic association studiesLow detection powerType I error inflationCorrelation of phenotypesWhite British sampleSupplementary dataAssociation studiesPopulation-based biobanksIncreased phenotypic correlationsKorean GenomeSimulation studyPhenotype distributionPhenotypeAssociation TestBioinformaticsPhenotypic correlationsAssociations of self-reported occupational exposures and settings to ALS: a case–control study
Goutman S, Boss J, Godwin C, Mukherjee B, Feldman E, Batterman S. Associations of self-reported occupational exposures and settings to ALS: a case–control study. International Archives Of Occupational And Environmental Health 2022, 95: 1567-1586. PMID: 35593931, PMCID: PMC9424174, DOI: 10.1007/s00420-022-01874-4.Peer-Reviewed Original ResearchConceptsStandard Occupational ClassificationStandard Occupational Classification codesExposure to particulate matterProductive occupationsALS riskSelf-reported occupational exposureHigher risk of amyotrophic lateral sclerosisOccupational exposureHigher ALS riskRisk of amyotrophic lateral sclerosisRisk factor modificationOccupational exposure to particulate matterExposure surveyIncreased ALS riskCase-control studyMaintenance occupationsGrounds cleaningFactor modificationExposure scoreTargeted screeningAmyotrophic lateral sclerosis diagnosisRepair occupationsAdaptive elastic net modelOccupational classificationProgressive neurological disease
2021
Endometriosis and menopausal hormone therapy impact the hysterectomy-ovarian cancer association
Khoja L, Weber RP, Group T, Webb PM, Jordan SJ, Muthukumar A, Chang-Claude J, Fortner RT, Jensen A, Kjaer SK, Risch H, Doherty JA, Harris HR, Goodman MT, Modugno F, Moysich K, Berchuck A, Schildkraut JM, Cramer D, Terry KL, Anton-Culver H, Ziogas A, Phung MT, Hanley GE, Wu AH, Mukherjee B, McLean K, Cho K, Pike MC, Pearce CL, Lee AW. Endometriosis and menopausal hormone therapy impact the hysterectomy-ovarian cancer association. Gynecologic Oncology 2021, 164: 195-201. PMID: 34776242, PMCID: PMC9444325, DOI: 10.1016/j.ygyno.2021.10.088.Peer-Reviewed Original ResearchMeSH KeywordsCase-Control StudiesEndometriosisEstrogen Replacement TherapyFemaleHumansHysterectomyMenopauseOvarian NeoplasmsConceptsHistory of endometriosisOvarian cancer riskEPT useOvarian Cancer Association ConsortiumOvarian cancerInverse associationOdds ratioCancer riskCancer associationInvasive epithelial ovarian cancerHormone therapy useMenopausal hormone therapyEpithelial ovarian cancerCase-control studyConfidence intervalsSlight inverse associationWarrants further investigationHormone therapyTherapy usePooled analysisEndometriosisHysterectomyCancerTherapySelf-reported dataDepot-Medroxyprogesterone Acetate Use Is Associated with Decreased Risk of Ovarian Cancer: The Mounting Evidence of a Protective Role of ProgestinsDMPA Use Decreases Ovarian Cancer Risk
Phung M, Lee A, Wu A, Berchuck A, Cho K, Cramer D, Doherty J, Goodman M, Hanley G, Harris H, McLean K, Modugno F, Moysich K, Mukherjee B, Schildkraut J, Terry K, Titus L, Consortium O, Jordan S, Webb P, Consortium O, Pike M, Pearce C. Depot-Medroxyprogesterone Acetate Use Is Associated with Decreased Risk of Ovarian Cancer: The Mounting Evidence of a Protective Role of ProgestinsDMPA Use Decreases Ovarian Cancer Risk. Cancer Epidemiology Biomarkers & Prevention 2021, 30: 927-935. PMID: 33619020, PMCID: PMC9281627, DOI: 10.1158/1055-9965.epi-20-1355.Peer-Reviewed Original ResearchConceptsOvarian cancer riskDepot medroxyprogesterone acetate useRisk of ovarian cancerDepot medroxyprogesterone acetateCancer riskOvarian cancerDecreased riskInverse associationRisk of invasive epithelial ovarian cancerRisk of ovarian cancer overallAssociated with decreased risk of ovarian cancerDecreased risk of ovarian cancerOvarian Cancer Association ConsortiumDecreased ovarian cancer riskSystematic reviewOvarian cancer overallInvasive epithelial ovarian cancerAssociated with decreased riskCombined oral contraceptive useInjectable progestin-only contraceptivesProgestin-only contraceptive useProgestin-releasing intrauterine deviceContraceptive useAssociated with ovarian cancerProgestin-only contraceptives
2020
Expanding Our Understanding of Ovarian Cancer Risk: The Role of Incomplete Pregnancies
Lee AW, Rosenzweig S, Wiensch A, Group T, Ramus SJ, Menon U, Gentry-Maharaj A, Ziogas A, Anton-Culver H, Whittemore AS, Sieh W, Rothstein JH, McGuire V, Wentzensen N, Bandera EV, Qin B, Terry KL, Cramer DW, Titus L, Schildkraut JM, Berchuck A, Goode EL, Kjaer SK, Jensen A, Jordan SJ, Ness RB, Modugno F, Moysich K, Thompson PJ, Goodman MT, Carney ME, Chang-Claude J, Rossing MA, Harris HR, Doherty JA, Risch HA, Khoja L, Alimujiang A, Phung MT, Brieger K, Mukherjee B, Pharoah PDP, Wu AH, Pike MC, Webb PM, Pearce CL. Expanding Our Understanding of Ovarian Cancer Risk: The Role of Incomplete Pregnancies. Journal Of The National Cancer Institute 2020, 113: 301-308. PMID: 32766851, PMCID: PMC7936053, DOI: 10.1093/jnci/djaa099.Peer-Reviewed Original ResearchConceptsOvarian cancer riskInvasive epithelial ovarian cancerClear cell ovarian cancerIncomplete pregnanciesEpithelial ovarian cancerOvarian cancerOvarian Cancer Association ConsortiumCancer riskOdds ratioInvasive epithelial ovarian cancer casesEpithelial ovarian cancer casesHistotype-specific analysesHistotype-specific associationsOral contraceptive useInvasive ovarian cancerHistory of breastfeedingConfidence intervalsOvarian cancer casesCase-control studyOCAC studiesMajor histotypesPooled analysisInverse associationCancer casesComplete pregnancyA Fast and Accurate Method for Genome-Wide Time-to-Event Data Analysis and Its Application to UK Biobank
Bi W, Fritsche L, Mukherjee B, Kim S, Lee S. A Fast and Accurate Method for Genome-Wide Time-to-Event Data Analysis and Its Application to UK Biobank. American Journal Of Human Genetics 2020, 107: 222-233. PMID: 32589924, PMCID: PMC7413891, DOI: 10.1016/j.ajhg.2020.06.003.Peer-Reviewed Original ResearchConceptsControlled type I error ratesTime-to-event data analysisType I error rateGenetic studies of human diseasesGenome-wide significance levelTime-to-event phenotypesSaddlepoint approximationGenome-wide analysisEuropean ancestry samplesMinor allele frequencyStudy of human diseaseElectronic health recordsCox PH regression modelRegression modelsStandard Wald testProportional hazardsBinary phenotypesData analysisAncestry samplesGenetic studiesHealth recordsUK BiobankAllele frequenciesInpatient dataCox proportional hazardsEstrogen Plus Progestin Hormone Therapy and Ovarian Cancer: A Complicated Relationship Explored.
Lee A, Wu A, Wiensch A, Mukherjee B, Terry K, Harris H, Carney M, Jensen A, Cramer D, Berchuck A, Doherty J, Modugno F, Goodman M, Alimujiang A, Rossing M, Cushing-Haugen K, Bandera E, Thompson P, Kjaer S, Hogdall E, Webb P, Huntsman D, Moysich K, Lurie G, Ness R, Stram D, Roman L, Pike M, Pearce C. Estrogen Plus Progestin Hormone Therapy and Ovarian Cancer: A Complicated Relationship Explored. Epidemiology 2020, 31: 402-408. PMID: 32028322, PMCID: PMC7584395, DOI: 10.1097/ede.0000000000001175.Peer-Reviewed Original ResearchMeSH KeywordsCase-Control StudiesEstrogen Replacement TherapyFemaleHumansOvarian NeoplasmsRisk AssessmentConceptsRisk of ovarian cancerEstrogen-progestin combined therapyEstrogen-alone therapyAssociated with increased riskOvarian cancerCombination therapyRisk of ovarian cancer overallAssociated with increased risk of ovarian cancerOvarian cancer risk factorsPopulation-based case-control studyOvarian Cancer Association ConsortiumMenopausal hormone therapy useIncreased risk of endometrial cancerOvarian cancer overallRisk of endometrial cancerCancer risk factorsHistotypes of ovarian cancerRisk factorsProgestin hormone therapyMucinous ovarian cancerOvarian cancer casesIn-person interviewsHormone therapy useOvarian cancer histotypesCase-control study
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 testA comprehensive gene–environment interaction analysis in Ovarian Cancer using genome‐wide significant common variants
Kim S, Wang M, Tyrer J, Jensen A, Wiensch A, Liu G, Lee A, Ness R, Salvatore M, Tworoger S, Whittemore A, Anton‐Culver H, Sieh W, Olson S, Berchuck A, Goode E, Goodman M, Doherty J, Chenevix‐Trench G, Rossing M, Webb P, Giles G, Terry K, Ziogas A, Fortner R, Menon U, Gayther S, Wu A, Song H, Brooks‐Wilson A, Bandera E, Cook L, Cramer D, Milne R, Winham S, Kjaer S, Modugno F, Thompson P, Chang‐Claude J, Harris H, Schildkraut J, Le N, Wentzensen N, Trabert B, Høgdall E, Huntsman D, Pike M, Pharoah P, Pearce C, Mukherjee B. A comprehensive gene–environment interaction analysis in Ovarian Cancer using genome‐wide significant common variants. International Journal Of Cancer 2019, 144: 2192-2205. PMID: 30499236, PMCID: PMC6399057, DOI: 10.1002/ijc.32029.Peer-Reviewed Original ResearchConceptsOral contraceptive pill useExcess risk due to additive interactionOvarian cancer risk factorsOral contraceptive pillsGene-environment interaction analysisCancer risk factorsGene-environment analysisOvarian cancer casesOCP useCase-control studyGenome-wide association analysisAdditive scaleCancer casesOvarian cancerOdds ratioCommon variantsDuration of OCP useRisk allelesRisk factorsGenetic variantsAdditive interactionAssociation analysisWomenFollow-upC allele
2018
Novel Common Genetic Susceptibility Loci for Colorectal Cancer
Schmit SL, Edlund CK, Schumacher FR, Gong J, Harrison TA, Huyghe JR, Qu C, Melas M, Van Den Berg DJ, Wang H, Tring S, Plummer SJ, Albanes D, Alonso MH, Amos CI, Anton K, Aragaki AK, Arndt V, Barry EL, Berndt SI, Bezieau S, Bien S, Bloomer A, Boehm J, Boutron-Ruault MC, Brenner H, Brezina S, Buchanan DD, Butterbach K, Caan BJ, Campbell PT, Carlson CS, Castelao JE, Chan AT, Chang-Claude J, Chanock SJ, Cheng I, Cheng YW, Chin LS, Church JM, Church T, Coetzee GA, Cotterchio M, Correa M, Curtis KR, Duggan D, Easton DF, English D, Feskens EJM, Fischer R, FitzGerald LM, Fortini BK, Fritsche LG, Fuchs CS, Gago-Dominguez M, Gala M, Gallinger SJ, Gauderman WJ, Giles GG, Giovannucci EL, Gogarten SM, Gonzalez-Villalpando C, Gonzalez-Villalpando EM, Grady WM, Greenson JK, Gsur A, Gunter M, Haiman CA, Hampe J, Harlid S, Harju JF, Hayes RB, Hofer P, Hoffmeister M, Hopper JL, Huang SC, Huerta JM, Hudson TJ, Hunter DJ, Idos GE, Iwasaki M, Jackson RD, Jacobs EJ, Jee SH, Jenkins MA, Jia WH, Jiao S, Joshi AD, Kolonel LN, Kono S, Kooperberg C, Krogh V, Kuehn T, Küry S, LaCroix A, Laurie CA, Lejbkowicz F, Lemire M, Lenz HJ, Levine D, Li CI, Li L, Lieb W, Lin Y, Lindor NM, Liu YR, Loupakis F, Lu Y, Luh F, Ma J, Mancao C, Manion FJ, Markowitz SD, Martin V, Matsuda K, Matsuo K, McDonnell KJ, McNeil CE, Milne R, Molina AJ, Mukherjee B, Murphy N, Newcomb PA, Offit K, Omichessan H, Palli D, Cotoré JPP, Pérez-Mayoral J, Pharoah PD, Potter JD, Qu C, Raskin L, Rennert G, Rennert HS, Riggs BM, Schafmayer C, Schoen RE, Sellers TA, Seminara D, Severi G, Shi W, Shibata D, Shu XO, Siegel EM, Slattery ML, Southey M, Stadler ZK, Stern MC, Stintzing S, Taverna D, Thibodeau SN, Thomas DC, Trichopoulou A, Tsugane S, Ulrich CM, van Duijnhoven FJB, van Guelpan B, Vijai J, Virtamo J, Weinstein SJ, White E, Win AK, Wolk A, Woods M, Wu AH, Wu K, Xiang YB, Yen Y, Zanke BW, Zeng YX, Zhang B, Zubair N, Kweon SS, Figueiredo JC, Zheng W, Le Marchand L, Lindblom A, Moreno V, Peters U, Casey G, Hsu L, Conti DV, Gruber SB. Novel Common Genetic Susceptibility Loci for Colorectal Cancer. Journal Of The National Cancer Institute 2018, 111: 146-157. PMID: 29917119, PMCID: PMC6555904, DOI: 10.1093/jnci/djy099.Peer-Reviewed Original ResearchAssociations between maternal phenol and paraben urinary biomarkers and maternal hormones during pregnancy: A repeated measures study
Aker A, Johns L, McElrath T, Cantonwine D, Mukherjee B, Meeker J. Associations between maternal phenol and paraben urinary biomarkers and maternal hormones during pregnancy: A repeated measures study. Environment International 2018, 113: 341-349. PMID: 29366524, PMCID: PMC5866216, DOI: 10.1016/j.envint.2018.01.006.Peer-Reviewed Original ResearchConceptsThyroid hormonesAssociated with altered thyroid hormone levelsFetal health outcomesThyroid hormone levelsIQR increaseMultivariate regression analysisGestational ageMultivariate linear regression modelFetal neurodevelopmentPregnant womenFree thyroxinePotential biological mechanismsTime of exposureUrinary biomarkersCohort studyHormone levelsParaben biomarkersTotal triiodothyronineCase-control samplePregnancyBlood samplesTotal thyroxineHormone concentrationsHealth outcomesHormoneSubset-Based Analysis Using Gene-Environment Interactions for Discovery of Genetic Associations across Multiple Studies or Phenotypes
Yu Y, Xia L, Lee S, Zhou X, Stringham H, Boehnke M, Mukherjee B. Subset-Based Analysis Using Gene-Environment Interactions for Discovery of Genetic Associations across Multiple Studies or Phenotypes. Human Heredity 2018, 83: 283-314. PMID: 31132756, PMCID: PMC7034441, DOI: 10.1159/000496867.Peer-Reviewed Original ResearchMeSH KeywordsCase-Control StudiesCholesterolCohort StudiesComputer SimulationC-Reactive ProteinFinlandGene FrequencyGene-Environment InteractionGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansLipoproteins, LDLMeta-Analysis as TopicModels, GeneticPhenotypePolymorphism, Single NucleotideConceptsPresence of G-E interactionsGenetic associationHeterogeneity of genetic effectsDiscovery of genetic associationsGene-environment (G-EMarginal genetic effectsG-E interactionsGenome-wide association studiesGene-environment interactionsGenetic effectsData examplesSimulation studySingle nucleotide polymorphismsGene-environmentAssociation studiesAssociation analysisScreening toolMarginal associationNucleotide polymorphismsPresence of heterogeneityAssociationEnvironmental factorsIncreased powerMultiple studiesG-E
2017
Subclinical Changes in Maternal Thyroid Function Parameters in Pregnancy and Fetal Growth
Johns L, Ferguson K, Cantonwine D, Mukherjee B, Meeker J, McElrath T. Subclinical Changes in Maternal Thyroid Function Parameters in Pregnancy and Fetal Growth. The Journal Of Clinical Endocrinology & Metabolism 2017, 103: 1349-1358. PMID: 29293986, PMCID: PMC6018657, DOI: 10.1210/jc.2017-01698.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAsymptomatic DiseasesBirth WeightCase-Control StudiesFemaleFetal DevelopmentHumansInfant, NewbornPregnancyPregnancy ComplicationsPremature BirthProspective StudiesSocioeconomic FactorsThyroid DiseasesThyroid Function TestsThyroid GlandThyroid HormonesThyroxineUltrasonography, PrenatalYoung AdultConceptsBirth weight z-scoreOvert thyroid diseaseThyroid function parametersWeight z-scoreFetal growthThyroid diseaseInverse associationPregnant womenMeasurements of estimated fetal weightSubclinical changesIndices of fetal growthCase-control study of preterm birthStudy of preterm birthZ-scoreAbnormal fetal growthMaternal thyroid functionWeeks of gestationInfluence fetal growthZ-score decreaseThyroid-stimulating hormoneProspective birth cohortCase-control studyFunction parametersFetal weightPreterm birthUrinary BPA and Phthalate Metabolite Concentrations and Plasma Vitamin D Levels in Pregnant Women: A Repeated Measures Analysis
Johns L, Ferguson K, Cantonwine D, McElrath T, Mukherjee B, Meeker J. Urinary BPA and Phthalate Metabolite Concentrations and Plasma Vitamin D Levels in Pregnant Women: A Repeated Measures Analysis. Environmental Health Perspectives 2017, 125: 087026. PMID: 28934718, PMCID: PMC5783673, DOI: 10.1289/ehp1178.Peer-Reviewed Original ResearchConceptsCohort of pregnant womenMono-3-carboxypropyl phthalateVitamin D levelsPregnant womenD levelsNested case-control study of preterm birthMeasures of urinary phthalate metabolitesProspective cohort of pregnant womenOdds of vitamin D deficiencyCase-control study of preterm birthDi(2-ethylhexyl) phthalate metabolitesInverse associationStudy of preterm birthInterquartile rangePlasma vitamin D levelsCirculating total 25(OH)DNested case-control studyMetabolites of di(2-ethylhexyl) phthalateVitamin D deficiencyDi(2-ethylhexyl) phthalatePhthalate metabolite concentrationsUrinary phthalate metabolitesUrinary bisphenol AProspective birth cohortPreterm birthMeta‐analysis of gene‐environment interaction exploiting gene‐environment independence across multiple case‐control studies
Estes J, Rice J, Li S, Stringham H, Boehnke M, Mukherjee B. Meta‐analysis of gene‐environment interaction exploiting gene‐environment independence across multiple case‐control studies. Statistics In Medicine 2017, 36: 3895-3909. PMID: 28744888, PMCID: PMC5624850, DOI: 10.1002/sim.7398.Peer-Reviewed Original ResearchMeSH KeywordsAge FactorsAlpha-Ketoglutarate-Dependent Dioxygenase FTOBayes TheoremBiasBiometryBody Mass IndexCase-Control StudiesComputer SimulationDiabetes Mellitus, Type 2Gene-Environment InteractionHumansLogistic ModelsMeta-Analysis as TopicModels, GeneticModels, StatisticalPolymorphism, Single NucleotideRetrospective StudiesConceptsGene-environment independenceGene-environmentEmpirical Bayes estimatorsGene-environment interactionsCase-control studyMeta-analysis settingBayes estimatorsRetrospective likelihood frameworkShrinkage estimatorsMeta-analysisTesting gene-environment interactionsCombination of estimatesFactors body mass indexSimulation studyBody mass indexUnconstrained modelLikelihood frameworkInverse varianceMeta-analysis frameworkFTO geneMass indexGenetic markersEstimationStandard alternativeChatterjee