A genome-wide linkage study of mammographic density, a risk factor for breast cancer
1 Department of Oncology (Division of Cancer Epidemiology), and Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC; Lady Davis Research Institute, Centre for Clinical Epidemiology and Community Studies, Jewish General Hospital, 3755 Côte Ste-Catherine, Montreal, QC H3T 1E2 Canada
2 Program in Genetics & Genome Biology, The Hospital for Sick Children, 101 College Street, East Tower, Toronto, ON M5G 1L7 Canada
3 Dalla Lana School of Public Health, University of Toronto, Toronto, ON M5T 3M7 Canada
4 The Campbell Family Cancer Research Institute, Toronto, ON M5G 2M9 Canada
5 Ontario Genetics Network, Ontario Cancer Care, Toronto; Samuel Lunenfeld Research Institute and Department of Pathology & Laboratory Medicine, Mount Sinai Hospital, Toronto, ON M5G 1X5 Canada
6 Department of Molecular Genetics, University of Toronto, Toronto, ON M5G 1A8 Canada
7 Center for Molecular, Environmental, Genetic and Analytical Epidemiology, School of Public Health, The University of Melbourne, Melbourne, Melbourne, Victoria 3053, Australia
8 Department of Medical Biophysics, University of Toronto, Toronto, ON M5G 2M9 Canada
9 Department of Pathology, The University of Melbourne, Melbourne, Melbourne, Victoria 3053, Australia
10 Department of Health Research and Policy, Stanford University School of Medicine and Stanford Cancer Center, Stanford; Cancer Prevention Institute of California, Fremont, CA 94538, USA
Breast Cancer Research 2011, 13:R132 doi:10.1186/bcr3078Published: 21 December 2011
Mammographic breast density is a highly heritable (h2 > 0.6) and strong risk factor for breast cancer. We conducted a genome-wide linkage study to identify loci influencing mammographic breast density (MD).
Epidemiological data were assembled on 1,415 families from the Australia, Northern California and Ontario sites of the Breast Cancer Family Registry, and additional families recruited in Australia and Ontario. Families consisted of sister pairs with age-matched mammograms and data on factors known to influence MD. Single nucleotide polymorphism (SNP) genotyping was performed on 3,952 individuals using the Illumina Infinium 6K linkage panel.
Using a variance components method, genome-wide linkage analysis was performed using quantitative traits obtained by adjusting MD measurements for known covariates. Our primary trait was formed by fitting a linear model to the square root of the percentage of the breast area that was dense (PMD), adjusting for age at mammogram, number of live births, menopausal status, weight, height, weight squared, and menopausal hormone therapy. The maximum logarithm of odds (LOD) score from the genome-wide scan was on chromosome 7p14.1-p13 (LOD = 2.69; 63.5 cM) for covariate-adjusted PMD, with a 1-LOD interval spanning 8.6 cM. A similar signal was seen for the covariate adjusted area of the breast that was dense (DA) phenotype. Simulations showed that the complete sample had adequate power to detect LOD scores of 3 or 3.5 for a locus accounting for 20% of phenotypic variance. A modest peak initially seen on chromosome 7q32.3-q34 increased in strength when only the 513 families with at least two sisters below 50 years of age were included in the analysis (LOD 3.2; 140.7 cM, 1-LOD interval spanning 9.6 cM). In a subgroup analysis, we also found a LOD score of 3.3 for DA phenotype on chromosome 12.11.22-q13.11 (60.8 cM, 1-LOD interval spanning 9.3 cM), overlapping a region identified in a previous study.
The suggestive peaks and the larger linkage signal seen in the subset of pedigrees with younger participants highlight regions of interest for further study to identify genes that determine MD, with the goal of understanding mammographic density and its involvement in susceptibility to breast cancer.