Skip to main content
Top
Published in: Breast Cancer Research 1/2015

Open Access 01-12-2015 | Research article

Identification of two novel mammographic density loci at 6Q25.1

Authors: Judith S Brand, Jingmei Li, Keith Humphreys, Robert Karlsson, Mikael Eriksson, Emma Ivansson, Per Hall, Kamila Czene

Published in: Breast Cancer Research | Issue 1/2015

Login to get access

Abstract

Introduction

Mammographic density (MD) is a strong heritable and intermediate phenotype for breast cancer, but much of its genetic variation remains unexplained. We performed a large-scale genetic association study including 8,419 women of European ancestry to identify MD loci.

Methods

Participants of three Swedish studies were genotyped on a custom Illumina iSelect genotyping array and percent and absolute mammographic density were ascertained using semiautomated and fully automated methods from film and digital mammograms. Linear regression analysis was used to test for SNP-MD associations, adjusting for age, body mass index, menopausal status and six principal components. Meta-analyses were performed by combining P values taking sample size, study-specific inflation factor and direction of effect into account.

Results

Genome-wide significant associations were observed for two previously identified loci: ZNF365 (rs10995194, P = 2.3 × 10−8 for percent MD and P = 8.7 × 10−9 for absolute MD) and AREG (rs10034692, P = 6.7 × 10−9 for absolute MD). In addition, we found evidence of association for two variants at 6q25.1, both of which are known breast cancer susceptibility loci: rs9485370 in the TAB2 gene (P = 4.8 × 10−9 for percent MD and P = 2.5 × 10−8 for absolute MD) and rs60705924 in the CCDC170/ESR1 region (P = 2.2 × 10−8 for absolute MD). Both regions have been implicated in estrogen receptor signaling with TAB2 being a potential regulator of tamoxifen response.

Conclusions

We identified two novel MD loci at 6q25.1. These findings underscore the importance of 6q25.1 as a susceptibility region and provide more insight into the mechanisms through which MD influences breast cancer risk.
Appendix
Available only for authorised users
Literature
1.
go back to reference Boyd NF, Guo H, Martin LJ, Sun L, Stone J, Fishell E, et al. Mammographic density and the risk and detection of breast cancer. N Engl J Med. 2007;356:227–36.CrossRefPubMed Boyd NF, Guo H, Martin LJ, Sun L, Stone J, Fishell E, et al. Mammographic density and the risk and detection of breast cancer. N Engl J Med. 2007;356:227–36.CrossRefPubMed
2.
go back to reference Boyd NF, Dite GS, Stone J, Gunasekara A, English DR, McCredie MR, et al. Heritability of mammographic density, a risk factor for breast cancer. N Engl J Med. 2002;347:886–94.CrossRefPubMed Boyd NF, Dite GS, Stone J, Gunasekara A, English DR, McCredie MR, et al. Heritability of mammographic density, a risk factor for breast cancer. N Engl J Med. 2002;347:886–94.CrossRefPubMed
3.
go back to reference Stone J, Dite GS, Gunasekara A, English DR, McCredie MR, Giles GG, et al. The heritability of mammographically dense and nondense breast tissue. Cancer Epidemiol Biomarkers Prev. 2006;15:612–7.CrossRefPubMed Stone J, Dite GS, Gunasekara A, English DR, McCredie MR, Giles GG, et al. The heritability of mammographically dense and nondense breast tissue. Cancer Epidemiol Biomarkers Prev. 2006;15:612–7.CrossRefPubMed
4.
go back to reference Varghese JS, Thompson DJ, Michailidou K, Lindstrom S, Turnbull C, Brown J, et al. Mammographic breast density and breast cancer: evidence of a shared genetic basis. Cancer Res. 2012;72:1478–84.CrossRefPubMedPubMedCentral Varghese JS, Thompson DJ, Michailidou K, Lindstrom S, Turnbull C, Brown J, et al. Mammographic breast density and breast cancer: evidence of a shared genetic basis. Cancer Res. 2012;72:1478–84.CrossRefPubMedPubMedCentral
5.
go back to reference Brand JS, Humphreys K, Thompson DJ, Li J, Eriksson M, Hall P, et al. Volumetric mammographic density: heritability and association with breast cancer susceptibility Loci. J Natl Cancer Inst. 2014;106. doi:10.1093/jnci/dju334. Print 2014 Dec Brand JS, Humphreys K, Thompson DJ, Li J, Eriksson M, Hall P, et al. Volumetric mammographic density: heritability and association with breast cancer susceptibility Loci. J Natl Cancer Inst. 2014;106. doi:10.​1093/​jnci/​dju334. Print 2014 Dec
6.
go back to reference Boyd NF, Rommens JM, Vogt K, Lee V, Hopper JL, Yaffe MJ, et al. Mammographic breast density as an intermediate phenotype for breast cancer. Lancet Oncol. 2005;6:798–808.CrossRefPubMed Boyd NF, Rommens JM, Vogt K, Lee V, Hopper JL, Yaffe MJ, et al. Mammographic breast density as an intermediate phenotype for breast cancer. Lancet Oncol. 2005;6:798–808.CrossRefPubMed
7.
go back to reference Lindstrom S, Vachon CM, Li J, Varghese J, Thompson D, Warren R, et al. Common variants in ZNF365 are associated with both mammographic density and breast cancer risk. Nat Genet. 2011;43:185–7.CrossRefPubMedPubMedCentral Lindstrom S, Vachon CM, Li J, Varghese J, Thompson D, Warren R, et al. Common variants in ZNF365 are associated with both mammographic density and breast cancer risk. Nat Genet. 2011;43:185–7.CrossRefPubMedPubMedCentral
8.
go back to reference Lindstrom S, Thompson DJ, Paterson AD, Li J, Gierach GL, Scott C, et al. Genome-wide association study identifies multiple loci associated with both mammographic density and breast cancer risk. Nat Commun. 2014;5:5303.CrossRefPubMedPubMedCentral Lindstrom S, Thompson DJ, Paterson AD, Li J, Gierach GL, Scott C, et al. Genome-wide association study identifies multiple loci associated with both mammographic density and breast cancer risk. Nat Commun. 2014;5:5303.CrossRefPubMedPubMedCentral
9.
go back to reference Fernandez-Navarro P, Gonzalez-Neira A, Pita G, Diaz-Uriarte R, Tais Moreno L, Ederra M, et al. Genome-wide association study identifies a novel putative mammographic density locus at 1q12-q21. Int J Cancer. 2015;136:2427–36.CrossRefPubMed Fernandez-Navarro P, Gonzalez-Neira A, Pita G, Diaz-Uriarte R, Tais Moreno L, Ederra M, et al. Genome-wide association study identifies a novel putative mammographic density locus at 1q12-q21. Int J Cancer. 2015;136:2427–36.CrossRefPubMed
10.
go back to reference Byng JW, Boyd NF, Fishell E, Jong RA, Yaffe MJ. The quantitative analysis of mammographic densities. Phys Med Biol. 1994;39:1629–38.CrossRefPubMed Byng JW, Boyd NF, Fishell E, Jong RA, Yaffe MJ. The quantitative analysis of mammographic densities. Phys Med Biol. 1994;39:1629–38.CrossRefPubMed
11.
go back to reference Highnam R, Brady M, Yaffe M, Karssemeijer N, Harvey J. Robust breast composition measurement - VolparaTM. Lect Notes Comput Sci. 2010;6136:342–9.CrossRef Highnam R, Brady M, Yaffe M, Karssemeijer N, Harvey J. Robust breast composition measurement - VolparaTM. Lect Notes Comput Sci. 2010;6136:342–9.CrossRef
12.
go back to reference Brand JS, Czene K, Shepherd JA, Leifland K, Heddson B, Sundbom A, et al. Automated measurement of volumetric mammographic density: a tool for widespread breast cancer risk assessment. Cancer Epidemiol Biomarkers Prev. 2014;23:1764–72.CrossRefPubMed Brand JS, Czene K, Shepherd JA, Leifland K, Heddson B, Sundbom A, et al. Automated measurement of volumetric mammographic density: a tool for widespread breast cancer risk assessment. Cancer Epidemiol Biomarkers Prev. 2014;23:1764–72.CrossRefPubMed
15.
go back to reference Sovio U, Li J, Aitken Z, Humphreys K, Czene K, Moss S, et al. Comparison of fully and semi-automated area-based methods for measuring mammographic density and predicting breast cancer risk. Br J Cancer. 2014;110:1908–16.CrossRefPubMedPubMedCentral Sovio U, Li J, Aitken Z, Humphreys K, Czene K, Moss S, et al. Comparison of fully and semi-automated area-based methods for measuring mammographic density and predicting breast cancer risk. Br J Cancer. 2014;110:1908–16.CrossRefPubMedPubMedCentral
16.
go back to reference Li J, Szekely L, Eriksson L, Heddson B, Sundbom A, Czene K, et al. High-throughput mammographic-density measurement: a tool for risk prediction of breast cancer. Breast Cancer Res. 2012;14:R114.CrossRefPubMedPubMedCentral Li J, Szekely L, Eriksson L, Heddson B, Sundbom A, Czene K, et al. High-throughput mammographic-density measurement: a tool for risk prediction of breast cancer. Breast Cancer Res. 2012;14:R114.CrossRefPubMedPubMedCentral
17.
go back to reference Couwenberg AM, Verkooijen HM, Li J, Pijnappel RM, Charaghvandi KR, Hartman M, et al. Assessment of a fully automated, high-throughput mammographic density measurement tool for use with processed digital mammograms. Cancer Causes Control. 2014;25:1037–43.CrossRefPubMed Couwenberg AM, Verkooijen HM, Li J, Pijnappel RM, Charaghvandi KR, Hartman M, et al. Assessment of a fully automated, high-throughput mammographic density measurement tool for use with processed digital mammograms. Cancer Causes Control. 2014;25:1037–43.CrossRefPubMed
18.
go back to reference Michailidou K, Hall P, Gonzalez-Neira A, Ghoussaini M, Dennis J, Milne RL, et al. Large-scale genotyping identifies 41 new loci associated with breast cancer risk. Nat Genet. 2013;45:353–61. 361e1-2.CrossRefPubMedPubMedCentral Michailidou K, Hall P, Gonzalez-Neira A, Ghoussaini M, Dennis J, Milne RL, et al. Large-scale genotyping identifies 41 new loci associated with breast cancer risk. Nat Genet. 2013;45:353–61. 361e1-2.CrossRefPubMedPubMedCentral
19.
go back to reference Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet. 2007;81:559–75.CrossRefPubMedPubMedCentral Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet. 2007;81:559–75.CrossRefPubMedPubMedCentral
20.
go back to reference 1000 Genomes Project Consortium, Abecasis GR, Auton A, Brooks LD, DePristo MA, Durbin RM, et al. An integrated map of genetic variation from 1,092 human genomes. Nature. 2012;491:56–65.CrossRef 1000 Genomes Project Consortium, Abecasis GR, Auton A, Brooks LD, DePristo MA, Durbin RM, et al. An integrated map of genetic variation from 1,092 human genomes. Nature. 2012;491:56–65.CrossRef
21.
go back to reference Howie B, Fuchsberger C, Stephens M, Marchini J, Abecasis GR. Fast and accurate genotype imputation in genome-wide association studies through pre-phasing. Nat Genet. 2012;44:955–9.CrossRefPubMedPubMedCentral Howie B, Fuchsberger C, Stephens M, Marchini J, Abecasis GR. Fast and accurate genotype imputation in genome-wide association studies through pre-phasing. Nat Genet. 2012;44:955–9.CrossRefPubMedPubMedCentral
23.
go back to reference Pruim RJ, Welch RP, Sanna S, Teslovich TM, Chines PS, Gliedt TP, et al. LocusZoom: regional visualization of genome-wide association scan results. Bioinformatics. 2010;26:2336–7.CrossRefPubMedPubMedCentral Pruim RJ, Welch RP, Sanna S, Teslovich TM, Chines PS, Gliedt TP, et al. LocusZoom: regional visualization of genome-wide association scan results. Bioinformatics. 2010;26:2336–7.CrossRefPubMedPubMedCentral
24.
go back to reference Marchini J, Howie B, Myers S, McVean G, Donnelly P. A new multipoint method for genome-wide association studies by imputation of genotypes. Nat Genet. 2007;39:906–13.CrossRefPubMed Marchini J, Howie B, Myers S, McVean G, Donnelly P. A new multipoint method for genome-wide association studies by imputation of genotypes. Nat Genet. 2007;39:906–13.CrossRefPubMed
25.
go back to reference Marchini J, Howie B. Genotype imputation for genome-wide association studies. Nat Rev Genet. 2010;11:499–511.CrossRefPubMed Marchini J, Howie B. Genotype imputation for genome-wide association studies. Nat Rev Genet. 2010;11:499–511.CrossRefPubMed
26.
go back to reference Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D. Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet. 2006;38:904–9.CrossRefPubMed Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D. Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet. 2006;38:904–9.CrossRefPubMed
28.
go back to reference Ward LD, Kellis M. HaploReg: a resource for exploring chromatin states, conservation, and regulatory motif alterations within sets of genetically linked variants. Nucleic Acids Res. 2012;40:D930–4.CrossRefPubMed Ward LD, Kellis M. HaploReg: a resource for exploring chromatin states, conservation, and regulatory motif alterations within sets of genetically linked variants. Nucleic Acids Res. 2012;40:D930–4.CrossRefPubMed
29.
go back to reference ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature. 2012;489:57–74.CrossRef ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature. 2012;489:57–74.CrossRef
30.
go back to reference Ernst J, Kheradpour P, Mikkelsen TS, Shoresh N, Ward LD, Epstein CB, et al. Mapping and analysis of chromatin state dynamics in nine human cell types. Nature. 2011;473:43–9.CrossRefPubMedPubMedCentral Ernst J, Kheradpour P, Mikkelsen TS, Shoresh N, Ward LD, Epstein CB, et al. Mapping and analysis of chromatin state dynamics in nine human cell types. Nature. 2011;473:43–9.CrossRefPubMedPubMedCentral
31.
go back to reference Long J, Cai Q, Sung H, Shi J, Zhang B, Choi JY, et al. Genome-wide association study in east Asians identifies novel susceptibility loci for breast cancer. PLoS Genet. 2012;8:e1002532.CrossRefPubMedPubMedCentral Long J, Cai Q, Sung H, Shi J, Zhang B, Choi JY, et al. Genome-wide association study in east Asians identifies novel susceptibility loci for breast cancer. PLoS Genet. 2012;8:e1002532.CrossRefPubMedPubMedCentral
32.
go back to reference Zheng W, Zhang B, Cai Q, Sung H, Michailidou K, Shi J, et al. Common genetic determinants of breast-cancer risk in East Asian women: a collaborative study of 23 637 breast cancer cases and 25 579 controls. Hum Mol Genet. 2013;22:2539–50.CrossRefPubMedPubMedCentral Zheng W, Zhang B, Cai Q, Sung H, Michailidou K, Shi J, et al. Common genetic determinants of breast-cancer risk in East Asian women: a collaborative study of 23 637 breast cancer cases and 25 579 controls. Hum Mol Genet. 2013;22:2539–50.CrossRefPubMedPubMedCentral
33.
go back to reference Takaesu G, Kishida S, Hiyama A, Yamaguchi K, Shibuya H, Irie K, et al. TAB2, a novel adaptor protein, mediates activation of TAK1 MAPKKK by linking TAK1 to TRAF6 in the IL-1 signal transduction pathway. Mol Cell. 2000;5:649–58.CrossRefPubMed Takaesu G, Kishida S, Hiyama A, Yamaguchi K, Shibuya H, Irie K, et al. TAB2, a novel adaptor protein, mediates activation of TAK1 MAPKKK by linking TAK1 to TRAF6 in the IL-1 signal transduction pathway. Mol Cell. 2000;5:649–58.CrossRefPubMed
34.
go back to reference Benson JR. Role of transforming growth factor beta in breast carcinogenesis. Lancet Oncol. 2004;5:229–39.CrossRefPubMed Benson JR. Role of transforming growth factor beta in breast carcinogenesis. Lancet Oncol. 2004;5:229–39.CrossRefPubMed
36.
go back to reference Lee E, Van Den Berg D, Hsu C, Ursin G, Koh WP, Yuan JM, et al. Genetic variation in transforming growth factor beta 1 and mammographic density in Singapore Chinese women. Cancer Res. 2013;73:1876–82.CrossRefPubMedPubMedCentral Lee E, Van Den Berg D, Hsu C, Ursin G, Koh WP, Yuan JM, et al. Genetic variation in transforming growth factor beta 1 and mammographic density in Singapore Chinese women. Cancer Res. 2013;73:1876–82.CrossRefPubMedPubMedCentral
37.
go back to reference Zhu P, Baek SH, Bourk EM, Ohgi KA, Garcia-Bassets I, Sanjo H, et al. Macrophage/cancer cell interactions mediate hormone resistance by a nuclear receptor derepression pathway. Cell. 2006;124:615–29.CrossRefPubMed Zhu P, Baek SH, Bourk EM, Ohgi KA, Garcia-Bassets I, Sanjo H, et al. Macrophage/cancer cell interactions mediate hormone resistance by a nuclear receptor derepression pathway. Cell. 2006;124:615–29.CrossRefPubMed
38.
go back to reference Cutrupi S, Reineri S, Panetto A, Grosso E, Caizzi L, Ricci L, et al. Targeting of the adaptor protein Tab2 as a novel approach to revert tamoxifen resistance in breast cancer cells. Oncogene. 2012;31:4353–61.CrossRefPubMed Cutrupi S, Reineri S, Panetto A, Grosso E, Caizzi L, Ricci L, et al. Targeting of the adaptor protein Tab2 as a novel approach to revert tamoxifen resistance in breast cancer cells. Oncogene. 2012;31:4353–61.CrossRefPubMed
39.
go back to reference Wang Y, He Y, Qin Z, Jiang Y, Jin G, Ma H, et al. Evaluation of functional genetic variants at 6q25.1 and risk of breast cancer in a Chinese population. Breast Cancer Res. 2014;16:422.CrossRefPubMedPubMedCentral Wang Y, He Y, Qin Z, Jiang Y, Jin G, Ma H, et al. Evaluation of functional genetic variants at 6q25.1 and risk of breast cancer in a Chinese population. Breast Cancer Res. 2014;16:422.CrossRefPubMedPubMedCentral
40.
go back to reference Zheng W, Long J, Gao YT, Li C, Zheng Y, Xiang YB, et al. Genome-wide association study identifies a new breast cancer susceptibility locus at 6q25.1. Nat Genet. 2009;41:324–8.CrossRefPubMedPubMedCentral Zheng W, Long J, Gao YT, Li C, Zheng Y, Xiang YB, et al. Genome-wide association study identifies a new breast cancer susceptibility locus at 6q25.1. Nat Genet. 2009;41:324–8.CrossRefPubMedPubMedCentral
41.
go back to reference Yang Z, Shen J, Cao Z, Wang B. Association between a novel polymorphism (rs2046210) of the 6q25.1 locus and breast cancer risk. Breast Cancer Res Treat. 2013;139:267–75.CrossRefPubMed Yang Z, Shen J, Cao Z, Wang B. Association between a novel polymorphism (rs2046210) of the 6q25.1 locus and breast cancer risk. Breast Cancer Res Treat. 2013;139:267–75.CrossRefPubMed
42.
go back to reference Veeraraghavan J, Tan Y, Cao XX, Kim JA, Wang X, Chamness GC, et al. Recurrent ESR1-CCDC170 rearrangements in an aggressive subset of oestrogen receptor-positive breast cancers. Nat Commun. 2014;5:4577.CrossRefPubMedPubMedCentral Veeraraghavan J, Tan Y, Cao XX, Kim JA, Wang X, Chamness GC, et al. Recurrent ESR1-CCDC170 rearrangements in an aggressive subset of oestrogen receptor-positive breast cancers. Nat Commun. 2014;5:4577.CrossRefPubMedPubMedCentral
43.
go back to reference Assi V, Warwick J, Cuzick J, Duffy SW. Clinical and epidemiological issues in mammographic density. Nat Rev Clin Oncol. 2011;9:33–40.CrossRefPubMed Assi V, Warwick J, Cuzick J, Duffy SW. Clinical and epidemiological issues in mammographic density. Nat Rev Clin Oncol. 2011;9:33–40.CrossRefPubMed
44.
go back to reference Cheddad A, Czene K, Eriksson M, Li J, Easton D, Hall P, et al. Area and volumetric density estimation in processed full-field digital mammograms for risk assessment of breast cancer. PLoS One. 2014;9:e110690.CrossRefPubMedPubMedCentral Cheddad A, Czene K, Eriksson M, Li J, Easton D, Hall P, et al. Area and volumetric density estimation in processed full-field digital mammograms for risk assessment of breast cancer. PLoS One. 2014;9:e110690.CrossRefPubMedPubMedCentral
45.
go back to reference Stone J, Thompson DJ, Dos Santos Silva I, Scott C, Tamimi RM, Lindstrom S, et al. Novel associations between common breast cancer susceptibility variants and risk-predicting mammographic density measures. Cancer Res. 2015. doi:10.1158/0008-5472. Stone J, Thompson DJ, Dos Santos Silva I, Scott C, Tamimi RM, Lindstrom S, et al. Novel associations between common breast cancer susceptibility variants and risk-predicting mammographic density measures. Cancer Res. 2015. doi:10.​1158/​0008-5472.
Metadata
Title
Identification of two novel mammographic density loci at 6Q25.1
Authors
Judith S Brand
Jingmei Li
Keith Humphreys
Robert Karlsson
Mikael Eriksson
Emma Ivansson
Per Hall
Kamila Czene
Publication date
01-12-2015
Publisher
BioMed Central
Published in
Breast Cancer Research / Issue 1/2015
Electronic ISSN: 1465-542X
DOI
https://doi.org/10.1186/s13058-015-0591-2

Other articles of this Issue 1/2015

Breast Cancer Research 1/2015 Go to the issue
Webinar | 19-02-2024 | 17:30 (CET)

Keynote webinar | Spotlight on antibody–drug conjugates in cancer

Antibody–drug conjugates (ADCs) are novel agents that have shown promise across multiple tumor types. Explore the current landscape of ADCs in breast and lung cancer with our experts, and gain insights into the mechanism of action, key clinical trials data, existing challenges, and future directions.

Dr. Véronique Diéras
Prof. Fabrice Barlesi
Developed by: Springer Medicine