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Interactions between genetic and reproductive factors in breast cancer risk in a population-based sample of African-American families
Authors:Chaudru Valérie  Laing Amelia  Dunston Georgia M  Adams-Campbell Lucile L  Williams Rosemary  Lynch John J  Leffall LaSalle D  DeWitty Robert L  Gause Barry L  Bonney George E  Demenais Florence
Affiliation:INSERM EMI 00-06, INSERM-Université d'Evry, Evry, France.
Abstract:Incidence of breast cancer (BC) varies among ethnic groups, with higher rates in white than in African-American women. Until now, most epidemiological and genetic studies have been carried out in white women. To investigate whether interactions between genetic and reproductive risk factors may explain part of the ethnic disparity in BC incidence, a genetic epidemiology study was conducted, between 1989 and 1994, at the Howard University Cancer Center (Washington, DC), which led to the recruitment of 245 African-American families. Segregation analysis of BC was performed by use of the class D regressive logistic model that allows for censored data to account for a variable age of onset of disease, as implemented in the REGRESS program. Segregation analysis of BC was consistent with a putative dominant gene effect (P < 0.000001) and residual sister-dependence (P < 0.0001). This putative gene was found to interact significantly with age at menarche (P = 0.048), and an interaction with a history of spontaneous abortions was suggested (P = 0.08). A late age at menarche increased BC risk in gene carriers but had a protective effect in non-gene carriers. A history of spontaneous abortions had a protective effect in gene carriers and increased BC risk in non-gene carriers. Our findings agree partially with a similar analysis of French families showing a significant gene x parity interaction and a suggestive gene x age at menarche interaction. Investigating gene x risk factor interactions in different populations may have important implications for further biological investigations and for BC risk assessment.
Keywords:breast cancer  segregation analysis  regressive models  gene‐environment interactions  risk factors
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