Reference details
Nguyen TL, Schmidt DF, Makalic E, Dite GS, Stone J, Apicella C, Bui M, Macinnis RJ, Odefrey F, Cawson J, Treloar SA, Southey MC, Giles GG, Hopper JL (2013) Explaining variance in the Cumulus mammographic measures that predict breast cancer risk: a twins and sisters study. Cancer Epidemiol Biomarkers Prev 22:2395-2403
ABTRACT
Background: Mammographic density (MD), the area of the mammographic image that appears white or bright, predicts breast cancer risk. We estimated the proportions of variance explained by questionnaire-measured breast cancer risk factors and by unmeasured residual familial factors. Methods: For 544 MZ and 339 DZ twin pairs, and 1,558 non-twin sisters from 1,564 families, MD was measured using the computer-assisted method Cumulus. We estimated associations using multi-level mixed-effects linear regression and studied familial aspects using a multivariate normal model. Results: The proportions of variance explained by age, body mass index (BMI), and other risk factors, respectively, were: 4%, 1% and 4% for dense area; 7%, 14% and 4% for percent dense area; and 7%, 40% and 1% for non-dense area. Associations with dense area and percent dense area were in opposite directions than for non-dense area. After adjusting for measured factors, the correlations of dense area with percent dense area and non-dense area were 0.84 and -0.46, respectively. The MZ, DZ and sister pair correlations were: 0.59, 0.28 and 0.29 for dense area; 0.57, 0.30 and 0.28 for percent dense area; and 0.56, 0.27 and 0.28 for non-dense area (standard error (SE) = 0.02, 0.04 and 0.03, respectively). Conclusions: Under the classic twin model, 50-60% (SE = 5%) of the variance of MD measures that predict breast cancer risk are due to undiscovered genetic factors, and the remainder to as yet unknown individual-specific, non-genetic factors. Impact: Much remains to be learnt about the genetic and environmental determinants of MD.
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