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Mammographic density (MD) is regarded as an intermediate phenotype in breast cancer development. This association study investigated the influence of 14 breast cancer susceptibility loci identified through previous genome-wide association studies on MD among the participants in the "Determinants of Density in Mammographies in Spain" (DDM-Spain) study.Our study covered a total of 3348 Caucasian women aged 45-68years, recruited from seven Spanish breast cancer screening centres having DNA available. Mammographic density was blindly assessed by a single reader using a semiquantitative scale. Ordinal logistic models, adjusted for age, body mass index and menopausal status, were used to estimate the association between each genotype and MD.Evidence of association with MD was found for variant rs3803662 (TOX3) (Odds Ratio (OR)=1.13, 95% Confidence Interval (CI)=1.03-1.25), and marginal evidence of association for susceptibility loci rs3817198 (LSP1) (OR=1.09, 95% CI=1.00-1.20) and rs2981582 (FGFR2) (OR=0.92, 95% CI=0.84-1.01). Two other loci were associated with MD solely among pre-menopausal women, namely, rs4973768 (SLC4A7) (OR=0.83, 95% CI=0.70-1.00) and rs4415084 (MEPS30) (OR=1.22, 95% CI=1.00-1.49).Our findings lend some support to the hypothesis which links these susceptibility loci to MD.

International audience; Mammographic density (MD), or the proportion of the breast with respect to its overall area that is composed of dense tissue, is a strong risk factor for breast cancer. Studies support a positive association of mammographic density and alcohol drinking. This was a cross-sectional multicenter study based on 3584 women, aged 45-68 years, recruited from seven screening centers within the Spanish breast cancer screening program network. The association between MD, alcohol consumption and tobacco use was evaluated by using ordinal logistic models with random center-specific intercepts. We found a weak positive association between current alcohol intake and higher MD, with current alcohol consumption increasing the odds of high MD by 13% (OR = 1.13; 95% CI 0.99-1.28) and high daily grams of alcohol being positively associated with increased MD ( for trend = 0.045). There were no statistically significant differences in MD between smokers and non-smokers. Nevertheless, increased number of daily cigarettes and increased number of accumulated lifetime cigarettes were negatively associated with high MD ( for trend 0.017 and 0.021). The effect of alcohol on MD was modified by menopausal status and tobacco smoking: whereas, alcohol consumption and daily grams of alcohol were positively associated with higher MD in postmenopausal women and in women who were not currently smoking, alcohol consumption had no effect on MD in premenopausal women and current smokers. Our results support an association between recent alcohol consumption and high MD, characterized by a modest increase in risk at low levels of current consumption and a decrease in risk among heavier drinkers. Our study also shows how the effects of alcohol in the breast can be modified by other factors, such as smoking.

BACKGROUND: Measurement of obesity using self-reported anthropometric data usually involves underestimation of weight and/or overestimation of height. The dual aim of this study was, first, to ascertain and assess the validity of new cut-off points, for both overweight and obesity, using self-reported Body Mass Index furnished by women participants in breast cancer screening programmes, and second, to estimate and validate a predictive model that allows recalculate individual BMI based on self-reported data. METHODS: The study covered 2927 women enrolled at 7 breast cancer screening centres. At each centre, women were randomly selected in 2 samples, in a ratio of 2:1. The larger sample (n = 1951) was used to compare the values of measured and self-reported weight and height, to ascertain new overweight and obesity cut-off points with self-reported data, using ROC curves, and to estimate a predictive model of real BMI using a regression model. The second sample (n = 976) was used to validate the proposed cut-off points and the predictive model. RESULTS: Whereas reported prevalence of obesity was 19.8%, measured prevalence was 28.2%. The sensitivity and specificity of this classification would be maximised if the new cut-off points were 24.30 kg/m2 for overweight and 28.39 kg/m2 for obesity. The probability of classifying women correctly in their real weight categories on the basis of these points was 82.5% in the validation sample. Sensitivity and specificity for determining obesity using the new cut-off point in the validation sample were 90.0% and 92.3% respectively. The predictive model for real BMI included the self-reported BMI, age and educational level (university studies vs lower levels of education). This model succeeded in correctly classifying 90.5% of women according to BMI categories, but its performance was similar to that obtained with the new cut-off points. CONCLUSIONS: Quantification of self-reported obesity entails a considerable underestimation of this problem, thereby questioning its validity. The new cut-off points established in this study and the predictive equation both allow for more accurate estimation of these prevalences. This study was supported by the Research Grant FIS PI060386 from Spain's Health Research Fund (Fondo de Investigación Sanitaria); the EPY 1306/06 Collaboration Agreement between Astra-Zeneca and the Carlos III Institute of Health (Instituto de Salud Carlos III); and a grant from the Spanish Federation of Breast Cancer patients (FECMA 485 EPY 1170-10). Sí