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Breast Cancer Research
Published in: Breast Cancer Research 1/2022

01-12-2022 | Breast Cancer | Research article

Genome-wide and transcriptome-wide association studies of mammographic density phenotypes reveal novel loci

Authors: Hongjie Chen, Shaoqi Fan, Jennifer Stone, Deborah J. Thompson, Julie Douglas, Shuai Li, Christopher Scott, Manjeet K. Bolla, Qin Wang, Joe Dennis, Kyriaki Michailidou, Christopher Li, Ulrike Peters, John L. Hopper, Melissa C. Southey, Tu Nguyen-Dumont, Tuong L. Nguyen, Peter A. Fasching, Annika Behrens, Gemma Cadby, Rachel A. Murphy, Kristan Aronson, Anthony Howell, Susan Astley, Fergus Couch, Janet Olson, Roger L. Milne, Graham G. Giles, Christopher A. Haiman, Gertraud Maskarinec, Stacey Winham, Esther M. John, Allison Kurian, Heather Eliassen, Irene Andrulis, D. Gareth Evans, William G. Newman, Per Hall, Kamila Czene, Anthony Swerdlow, Michael Jones, Marina Pollan, Pablo Fernandez-Navarro, Daniel S. McConnell, Vessela N. Kristensen, Joseph H. Rothstein, Pei Wang, Laurel A. Habel, Weiva Sieh, Alison M. Dunning, Paul D. P. Pharoah, Douglas F. Easton, Gretchen L. Gierach, Rulla M. Tamimi, Celine M. Vachon, Sara Lindström, NBCS Investigators

Published in: Breast Cancer Research | Issue 1/2022

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Abstract

Background

Mammographic density (MD) phenotypes, including percent density (PMD), area of dense tissue (DA), and area of non-dense tissue (NDA), are associated with breast cancer risk. Twin studies suggest that MD phenotypes are highly heritable. However, only a small proportion of their variance is explained by identified genetic variants.

Methods

We conducted a genome-wide association study, as well as a transcriptome-wide association study (TWAS), of age- and BMI-adjusted DA, NDA, and PMD in up to 27,900 European-ancestry women from the MODE/BCAC consortia.

Results

We identified 28 genome-wide significant loci for MD phenotypes, including nine novel signals (5q11.2, 5q14.1, 5q31.1, 5q33.3, 5q35.1, 7p11.2, 8q24.13, 12p11.2, 16q12.2). Further, 45% of all known breast cancer SNPs were associated with at least one MD phenotype at p < 0.05. TWAS further identified two novel genes (SHOX2 and CRISPLD2) whose genetically predicted expression was significantly associated with MD phenotypes.

Conclusions

Our findings provided novel insight into the genetic background of MD phenotypes, and further demonstrated their shared genetic basis with breast cancer.
Appendix
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Literature
1.
Boyd NF, Martin LJ, Yaffe MJ, Minkin S. Mammographic density and breast cancer risk: current understanding and future prospects. Breast Cancer Res. 2011;13(6):223.PubMedPubMedCentralCrossRef
2.
McCormack VA, dos Santos SI. Breast density and parenchymal patterns as markers of breast cancer risk: a meta-analysis. Cancer Epidemiol Biomark Prev. 2006;15(6):1159–69.CrossRef
3.
Pettersson A, Graff RE, Ursin G, Santos Silva ID, McCormack V, Baglietto L, Vachon C, Bakker MF, Giles GG, Chia KS, et al. Mammographic density phenotypes and risk of breast cancer: a meta-analysis. J Natl Cancer Inst. 2014;106(5):dju078.PubMedPubMedCentralCrossRef
4.
Bond-Smith D, Stone J. Methodological challenges and updated findings from a meta-analysis of the association between mammographic density and breast cancer. Cancer Epidemiol Biomark Prev. 2019;28(1):22–31.CrossRef
5.
6.
Ursin G, Ma H, Wu AH, Bernstein L, Salane M, Parisky YR, Astrahan M, Siozon CC, Pike MC. Mammographic density and breast cancer in three ethnic groups. Cancer Epidemiol Biomark Prev. 2003;12(4):332–8.
7.
Maskarinec G, Pagano I, Lurie G, Wilkens LR, Kolonel LN. Mammographic density and breast cancer risk: the multiethnic cohort study. Am J Epidemiol. 2005;162(8):743–52.PubMedCrossRef
8.
Pettersson A, Hankinson SE, Willett WC, Lagiou P, Trichopoulos D, Tamimi RM. Nondense mammographic area and risk of breast cancer. Breast Cancer Res. 2011;13(5):R100.PubMedPubMedCentralCrossRef
9.
Boyd NF, Dite GS, Stone J, Gunasekara A, English DR, McCredie MR, Giles GG, Tritchler D, Chiarelli A, Yaffe MJ, et al. Heritability of mammographic density, a risk factor for breast cancer. N Engl J Med. 2002;347(12):886–94.PubMedCrossRef
10.
Stone J, Dite GS, Gunasekara A, English DR, McCredie MR, Giles GG, Cawson JN, Hegele RA, Chiarelli AM, Yaffe MJ, et al. The heritability of mammographically dense and nondense breast tissue. Cancer Epidemiol Biomark Prev. 2006;15(4):612–7.CrossRef
11.
Holowko N, Eriksson M, Kuja-Halkola R, Azam S, He W, Hall P, Czene K. Heritability of mammographic breast density, density change, microcalcifications, and masses. Cancer Res. 2020;80(7):1590–600.PubMedCrossRef
12.
Lindstrom S, Vachon CM, Li J, Varghese J, Thompson D, Warren R, Brown J, Leyland J, Audley T, Wareham NJ, et al. Common variants in ZNF365 are associated with both mammographic density and breast cancer risk. Nat Genet. 2011;43(3):185–7.PubMedPubMedCentralCrossRef
13.
Stevens KN, Lindstrom S, Scott CG, Thompson D, Sellers TA, Wang X, Wang A, Atkinson E, Rider DN, Eckel-Passow JE, et al. Identification of a novel percent mammographic density locus at 12q24. Hum Mol Genet. 2012;21(14):3299–305.PubMedPubMedCentralCrossRef
14.
Lindstrom S, Thompson DJ, Paterson AD, Li J, Gierach GL, Scott C, Stone J, Douglas JA, dos-Santos-Silva I, Fernandez-Navarro P, et al. Genome-wide association study identifies multiple loci associated with both mammographic density and breast cancer risk. Nat Commun. 2014;5:5303.PubMedCrossRef
15.
Brand JS, Li J, Humphreys K, Karlsson R, Eriksson M, Ivansson E, Hall P, Czene K. Identification of two novel mammographic density loci at 6Q25.1. Breast Cancer Res. 2015;17:756.CrossRef
16.
Fernandez-Navarro P, Gonzalez-Neira A, Pita G, Diaz-Uriarte R, Tais Moreno L, Ederra M, Pedraz-Pingarron C, Sanchez-Contador C, Vazquez-Carrete JA, Moreo P, et al. Genome wide association study identifies a novel putative mammographic density locus at 1q12-q21. Int J Cancer. 2015;136(10):2427–36.PubMedCrossRef
17.
Sieh W, Rothstein JH, Klein RJ, Alexeeff SE, Sakoda LC, Jorgenson E, McBride RB, Graff RE, McGuire V, Achacoso N, et al. Identification of 31 loci for mammographic density phenotypes and their associations with breast cancer risk. Nat Commun. 2020;11(1):5116.PubMedPubMedCentralCrossRef
18.
Heine JJ, Scott CG, Sellers TA, Brandt KR, Serie DJ, Wu FF, Morton MJ, Schueler BA, Couch FJ, Olson JE, et al. A novel automated mammographic density measure and breast cancer risk. J Natl Cancer Inst. 2012;104(13):1028–37.PubMedPubMedCentralCrossRef
19.
Michailidou K, Lindstrom S, Dennis J, Beesley J, Hui S, Kar S, Lemacon A, Soucy P, Glubb D, Rostamianfar A, et al. Association analysis identifies 65 new breast cancer risk loci. Nature. 2017;551(7678):92–4.PubMedPubMedCentralCrossRef
20.
Amos CI, Dennis J, Wang Z, Byun J, Schumacher FR, Gayther SA, Casey G, Hunter DJ, Sellers TA, Gruber SB, et al. The OncoArray consortium: a network for understanding the genetic architecture of common cancers. Cancer Epidemiol Biomark Prev. 2017;26(1):126–35.CrossRef
21.
Howie BN, Donnelly P, Marchini J. A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS Genet. 2009;5(6):e1000529.PubMedPubMedCentralCrossRef
22.
23.
Pruim RJ, Welch RP, Sanna S, Teslovich TM, Chines PS, Gliedt TP, Boehnke M, Abecasis GR, Willer CJ. LocusZoom: regional visualization of genome-wide association scan results. Bioinformatics. 2010;26(18):2336–7.PubMedPubMedCentralCrossRef
24.
Yang J, Ferreira T, Morris AP, Medland SE, Genetic Investigation of ATC, Replication DIG, Meta-analysis C, Madden PA, Heath AC, Martin NG, et al. Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits. Nat Genet. 2012;44(4):369–75, S361–63.
25.
Kapoor PM, Lindstrom S, Behrens S, Wang X, Michailidou K, Bolla MK, Wang Q, Dennis J, Dunning AM, Pharoah PDP, et al. Assessment of interactions between 205 breast cancer susceptibility loci and 13 established risk factors in relation to breast cancer risk, in the Breast Cancer Association Consortium. Int J Epidemiol. 2020;49(1):216–32.PubMedCrossRef
26.
Bulik-Sullivan BK, Loh PR, Finucane HK, Ripke S, Yang J, Schizophrenia Working Group of the Psychiatric Genomics C, Patterson N, Daly MJ, Price AL, Neale BM. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat Genet. 2015;47(3):291–5.
27.
Finucane HK, Bulik-Sullivan B, Gusev A, Trynka G, Reshef Y, Loh PR, Anttila V, Xu H, Zang C, Farh K, et al. Partitioning heritability by functional annotation using genome-wide association summary statistics. Nat Genet. 2015;47(11):1228–35.PubMedPubMedCentralCrossRef
28.
Bulik-Sullivan B, Finucane HK, Anttila V, Gusev A, Day FR, Loh PR, ReproGen C, Psychiatric Genomics C, Genetic Consortium for Anorexia Nervosa of the Wellcome Trust Case Control C, Duncan L, et al. An atlas of genetic correlations across human diseases and traits. Nat Genet 2015;47(11):1236–41.
29.
Shi H, Kichaev G, Pasaniuc B. Contrasting the genetic architecture of 30 complex traits from summary association data. Am J Hum Genet. 2016;99(1):139–53.PubMedPubMedCentralCrossRef
30.
Shi H, Mancuso N, Spendlove S, Pasaniuc B. Local genetic correlation gives insights into the shared genetic architecture of complex traits. Am J Hum Genet. 2017;101(5):737–51.PubMedPubMedCentralCrossRef
31.
Berisa T, Pickrell JK. Approximately independent linkage disequilibrium blocks in human populations. Bioinformatics. 2016;32(2):283–5.PubMed
32.
Consortium G. The genotype-tissue expression (GTEx) project. Nat Genet. 2013;45(6):580–5.CrossRef
33.
Gamazon ER, Wheeler HE, Shah KP, Mozaffari SV, Aquino-Michaels K, Carroll RJ, Eyler AE, Denny JC, Consortium GT, Nicolae DL, et al. A gene-based association method for mapping traits using reference transcriptome data. Nat Genet. 2015;47(9):1091–8.
34.
Gusev A, Ko A, Shi H, Bhatia G, Chung W, Penninx BW, Jansen R, de Geus EJ, Boomsma DI, Wright FA, et al. Integrative approaches for large-scale transcriptome-wide association studies. Nat Genet. 2016;48(3):245–52.PubMedPubMedCentralCrossRef
35.
Emami NC, Cavazos TB, Rashkin SR, Cario CL, Graff RE, Tai CG, Mefford JA, Kachuri L, Wan E, Wong S, et al. A large-scale association study detects novel rare variants, risk genes, functional elements, and polygenic architecture of prostate cancer susceptibility. Cancer Res. 2021;81(7):1695–703.PubMedCrossRef
36.
Brand JS, Humphreys K, Li J, Karlsson R, Hall P, Czene K. Common genetic variation and novel loci associated with volumetric mammographic density. Breast Cancer Res. 2018;20(1):30.PubMedPubMedCentralCrossRef
37.
Lindberg K, Strom A, Lock JG, Gustafsson JA, Haldosen LA, Helguero LA. Expression of estrogen receptor beta increases integrin alpha1 and integrin beta1 levels and enhances adhesion of breast cancer cells. J Cell Physiol. 2010;222(1):156–67.PubMedCrossRef
38.
Haryono SJ, Datasena IG, Santosa WB, Mulyarahardja R, Sari K. A pilot genome-wide association study of breast cancer susceptibility loci in Indonesia. Asian Pac J Cancer Prev. 2015;16(6):2231–5.PubMedCrossRef
39.
Ali R, Wendt MK. The paradoxical functions of EGFR during breast cancer progression. Signal Transduct Target Ther. 2017, 2.
40.
Zeng C, Guo X, Long J, Kuchenbaecker KB, Droit A, Michailidou K, Ghoussaini M, Kar S, Freeman A, Hopper JL, et al. Identification of independent association signals and putative functional variants for breast cancer risk through fine-scale mapping of the 12p11 locus. Breast Cancer Res. 2016;18(1):64.PubMedPubMedCentralCrossRef
41.
Hens JR, Dann P, Zhang JP, Harris S, Robinson GW, Wysolmerski J. BMP4 and PTHrP interact to stimulate ductal outgrowth during embryonic mammary development and to inhibit hair follicle induction. Development. 2007;134(6):1221–30.PubMedCrossRef
42.
Akhtari M, Mansuri J, Newman KA, Guise TM, Seth P. Biology of breast cancer bone metastasis. Cancer Biol Ther. 2008;7(1):3–9.PubMedCrossRef
43.
Akbari ME, Gholamalizadeh M, Doaei S, Mirsafa F. FTO gene affects obesity and breast cancer through similar mechanisms: a new insight into the molecular therapeutic targets. Nutr Cancer. 2018;70(1):30–6.PubMedCrossRef
44.
Turnbull C, Ahmed S, Morrison J, Pernet D, Renwick A, Maranian M, Seal S, Ghoussaini M, Hines S, Healey CS, et al. Genome-wide association study identifies five new breast cancer susceptibility loci. Nat Genet. 2010;42(6):504–7.PubMedPubMedCentralCrossRef
45.
46.
Rice MS, Rosner BA, Tamimi RM. Percent mammographic density prediction: development of a model in the nurses’ health studies. Cancer Causes Control. 2017;28(7):677–84.PubMedPubMedCentralCrossRef
47.
Bissell MCS, Kerlikowske K, Sprague BL, Tice JA, Gard CC, Tossas KY, Rauscher GH, Trentham-Dietz A, Henderson LM, Onega T, et al. Breast cancer population attributable risk proportions associated with body mass index and breast density by race/ethnicity and menopausal status. Cancer Epidemiol Biomarkers Prev. 2020.
Metadata
Title
Genome-wide and transcriptome-wide association studies of mammographic density phenotypes reveal novel loci
Authors
Hongjie Chen
Shaoqi Fan
Jennifer Stone
Deborah J. Thompson
Julie Douglas
Shuai Li
Christopher Scott
Manjeet K. Bolla
Qin Wang
Joe Dennis
Kyriaki Michailidou
Christopher Li
Ulrike Peters
John L. Hopper
Melissa C. Southey
Tu Nguyen-Dumont
Tuong L. Nguyen
Peter A. Fasching
Annika Behrens
Gemma Cadby
Rachel A. Murphy
Kristan Aronson
Anthony Howell
Susan Astley
Fergus Couch
Janet Olson
Roger L. Milne
Graham G. Giles
Christopher A. Haiman
Gertraud Maskarinec
Stacey Winham
Esther M. John
Allison Kurian
Heather Eliassen
Irene Andrulis
D. Gareth Evans
William G. Newman
Per Hall
Kamila Czene
Anthony Swerdlow
Michael Jones
Marina Pollan
Pablo Fernandez-Navarro
Daniel S. McConnell
Vessela N. Kristensen
Joseph H. Rothstein
Pei Wang
Laurel A. Habel
Weiva Sieh
Alison M. Dunning
Paul D. P. Pharoah
Douglas F. Easton
Gretchen L. Gierach
Rulla M. Tamimi
Celine M. Vachon
Sara Lindström
NBCS Investigators
Publication date
01-12-2022
Publisher
BioMed Central
Published in
Breast Cancer Research / Issue 1/2022
Electronic ISSN: 1465-542X
DOI
https://doi.org/10.1186/s13058-022-01524-0

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