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A genome-wide linkage study of mammographic density, a risk factor for breast cancer
INTRODUCTION: Mammographic breast density is a highly heritable (h(2 )> 0.6) and strong risk factor for breast cancer. We conducted a genome-wide linkage study to identify loci influencing mammographic breast density (MD). METHODS: Epidemiological data were assembled on 1,415 families from the Au...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3326574/ https://www.ncbi.nlm.nih.gov/pubmed/22188651 http://dx.doi.org/10.1186/bcr3078 |
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author | Greenwood, Celia MT Paterson, Andrew D Linton, Linda Andrulis, Irene L Apicella, Carmel Dimitromanolakis, Apostolos Kriukov, Valentina Martin, Lisa J Salleh, Ayesha Samiltchuk, Elena Parekh, Rashmi V Southey, Melissa C John, Esther M Hopper, John L Boyd, Norman F Rommens, Johanna M |
author_facet | Greenwood, Celia MT Paterson, Andrew D Linton, Linda Andrulis, Irene L Apicella, Carmel Dimitromanolakis, Apostolos Kriukov, Valentina Martin, Lisa J Salleh, Ayesha Samiltchuk, Elena Parekh, Rashmi V Southey, Melissa C John, Esther M Hopper, John L Boyd, Norman F Rommens, Johanna M |
author_sort | Greenwood, Celia MT |
collection | PubMed |
description | INTRODUCTION: Mammographic breast density is a highly heritable (h(2 )> 0.6) and strong risk factor for breast cancer. We conducted a genome-wide linkage study to identify loci influencing mammographic breast density (MD). METHODS: 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. RESULTS: 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. CONCLUSIONS: 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. |
format | Online Article Text |
id | pubmed-3326574 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-33265742012-04-16 A genome-wide linkage study of mammographic density, a risk factor for breast cancer Greenwood, Celia MT Paterson, Andrew D Linton, Linda Andrulis, Irene L Apicella, Carmel Dimitromanolakis, Apostolos Kriukov, Valentina Martin, Lisa J Salleh, Ayesha Samiltchuk, Elena Parekh, Rashmi V Southey, Melissa C John, Esther M Hopper, John L Boyd, Norman F Rommens, Johanna M Breast Cancer Res Research Article INTRODUCTION: Mammographic breast density is a highly heritable (h(2 )> 0.6) and strong risk factor for breast cancer. We conducted a genome-wide linkage study to identify loci influencing mammographic breast density (MD). METHODS: 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. RESULTS: 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. CONCLUSIONS: 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. BioMed Central 2011 2011-12-21 /pmc/articles/PMC3326574/ /pubmed/22188651 http://dx.doi.org/10.1186/bcr3078 Text en Copyright ©2011 Greenwood et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Greenwood, Celia MT Paterson, Andrew D Linton, Linda Andrulis, Irene L Apicella, Carmel Dimitromanolakis, Apostolos Kriukov, Valentina Martin, Lisa J Salleh, Ayesha Samiltchuk, Elena Parekh, Rashmi V Southey, Melissa C John, Esther M Hopper, John L Boyd, Norman F Rommens, Johanna M A genome-wide linkage study of mammographic density, a risk factor for breast cancer |
title | A genome-wide linkage study of mammographic density, a risk factor for breast cancer |
title_full | A genome-wide linkage study of mammographic density, a risk factor for breast cancer |
title_fullStr | A genome-wide linkage study of mammographic density, a risk factor for breast cancer |
title_full_unstemmed | A genome-wide linkage study of mammographic density, a risk factor for breast cancer |
title_short | A genome-wide linkage study of mammographic density, a risk factor for breast cancer |
title_sort | genome-wide linkage study of mammographic density, a risk factor for breast cancer |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3326574/ https://www.ncbi.nlm.nih.gov/pubmed/22188651 http://dx.doi.org/10.1186/bcr3078 |
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