2023
Gene-Environment Analyses Reveal Novel Genetic Candidates with Prenatal Tobacco Exposure in Relation to Risk for Childhood Acute Lymphoblastic Leukemia.
Zhong C, Li S, Arroyo K, Morimoto L, de Smith A, Metayer C, Ma X, Kogan S, Gauderman W, Wiemels J. Gene-Environment Analyses Reveal Novel Genetic Candidates with Prenatal Tobacco Exposure in Relation to Risk for Childhood Acute Lymphoblastic Leukemia. Cancer Epidemiology Biomarkers & Prevention 2023, 32: 1707-1715. PMID: 37773025, DOI: 10.1158/1055-9965.epi-23-0258.Peer-Reviewed Original ResearchConceptsMaternal tobacco exposureAcute lymphoblastic leukemiaChildhood acute lymphoblastic leukemiaTobacco exposureLymphoblastic leukemiaLarge population-based studyPopulation-based studyEffects of tobaccoPrenatal tobacco exposureAryl hydrocarbon receptor repressor geneMode of deliverySelf-reported smokingIndividual-level risk factorsGenetic variantsPolygenetic risk scoresYear of birthAHRR hypomethylationSubsequent childhoodMaternal exposureGestational ageRisk factorsTobacco smokeRisk scoreBiological markersBlood spotsMendelian randomization study of birthweight, gestational age, and risk of childhood acute lymphoblastic leukemia
Rogne T, DeWan A, Metayer C, Wiemels J, Ma X. Mendelian randomization study of birthweight, gestational age, and risk of childhood acute lymphoblastic leukemia. American Journal Of Obstetrics & Gynecology MFM 2023, 5: 101058. PMID: 37330008, DOI: 10.1016/j.ajogmf.2023.101058.Peer-Reviewed Original Research
2022
Birth characteristics and risk of meningioma in a population-based study in California
Cote D, Wang R, Morimoto L, Metayer C, Stempel J, Zada G, Ma X, Wiemels J. Birth characteristics and risk of meningioma in a population-based study in California. Neuro-Oncology Advances 2022, 4: vdac173. PMID: 36479059, PMCID: PMC9721385, DOI: 10.1093/noajnl/vdac173.Peer-Reviewed Original ResearchPopulation-based studyHigher birth orderBirth characteristicsFemale sexRace/ethnicityBlack raceOdds ratioHigh riskUnconditional multivariable logistic regression modelsMultivariable logistic regression modelLarge population-based studyAge-stratified analysisConfidence intervalsCancer registry dataRisk of meningiomaAge of diagnosisCalifornia birth recordsPopulation-based linkageBirth orderLogistic regression modelsYear of birthGestational ageMaternal ageRisk factorsHigher birthweight
2020
Age-, sex- and disease subtype–related foetal growth differentials in childhood acute myeloid leukaemia risk: A Childhood Leukemia International Consortium analysis
Karalexi MA, Dessypris N, Ma X, Spector LG, Marcotte E, Clavel J, Pombo-de-Oliveira MS, Heck JE, Roman E, Mueller BA, Hansen J, Auvinen A, Lee PC, Schüz J, Magnani C, Mora AM, Dockerty JD, Scheurer ME, Wang R, Bonaventure A, Kane E, Doody DR, Group N, Baka M, Moschovi M, Polychronopoulou S, Kourti M, Hatzipantelis E, Pelagiadis I, Dana H, Kantzanou M, Tzanoudaki M, Anastasiou T, Grenzelia M, Gavriilaki E, Sakellari I, Anagnostopoulos A, Kitra V, Paisiou A, Bouka E, Group F, Nikkilä A, Lohi O, Erdmann F, Kang A, Metayer C, Milne E, Petridou E. Age-, sex- and disease subtype–related foetal growth differentials in childhood acute myeloid leukaemia risk: A Childhood Leukemia International Consortium analysis. European Journal Of Cancer 2020, 130: 1-11. PMID: 32163883, DOI: 10.1016/j.ejca.2020.01.018.Peer-Reviewed Original ResearchConceptsAcute myeloid leukemiaChildhood Leukemia International ConsortiumGestational ageFoetal growthInfant boyAcute myeloid leukemia riskMyeloid leukemia riskNewborn Growth ConsortiumRare childhood cancerBirth lengthGrowth markersChildhood cancerAML subtypesAML casesMyeloid leukemiaLeukemia riskNull associationDisease subtypesInternational FetalAgeMore studiesConsortium analysisLeukemiaSexBoys
2015
Birth weight, fetal growth, and risk of pediatric rhabdomyosarcoma: an updated record linkage study in California
Morimoto LM, McCauley K, Ma X, Wiemels JL, Chokkalingam AP, Metayer C. Birth weight, fetal growth, and risk of pediatric rhabdomyosarcoma: an updated record linkage study in California. Annals Of Epidemiology 2015, 26: 141-145. PMID: 26795698, DOI: 10.1016/j.annepidem.2015.11.007.Peer-Reviewed Original ResearchConceptsRisk of rhabdomyosarcomaHigh birth weightBirth weightGestational ageNon-Hispanic white childrenPost-term babiesCalifornia Cancer RegistryNormal gestational ageRecord linkage studyConditional logistic regressionCalifornia birth recordsNon-Hispanic whitesIndication of associationCancer RegistryBirth characteristicsFetal growthPediatric rhabdomyosarcomaRMS casesLower riskBirth recordsEthnic groupsLarger studyLogistic regressionWhite childrenAge
2014
Birth Weight Reference Percentiles for Chinese
Dai L, Deng C, Li Y, Zhu J, Mu Y, Deng Y, Mao M, Wang Y, Li Q, Ma S, Ma X, Zhang Y. Birth Weight Reference Percentiles for Chinese. PLOS ONE 2014, 9: e104779. PMID: 25127131, PMCID: PMC4134219, DOI: 10.1371/journal.pone.0104779.Peer-Reviewed Original ResearchConceptsBirth weight percentilesWeight percentilesNon-Chinese infantsWeeks of gestationBirth weight dataMost gestational agesGestational ageSingleton birthsFemale infantChinese infantsReference percentilesInfantsBirth defectsSignificant differencesLambda-muNational referencePercentileSurveillance systemNational population