Genome-wide and transcriptome-wide association studies of mammographic density phenotypes reveal novel loci
-
Published:2022-04-12
Issue:1
Volume:24
Page:
-
ISSN:1465-542X
-
Container-title:Breast Cancer Research
-
language:en
-
Short-container-title:Breast Cancer Res
Author:
Chen Hongjie, Fan Shaoqi, Stone Jennifer, Thompson Deborah J., Douglas Julie, Li Shuai, Scott Christopher, Bolla Manjeet K., Wang Qin, Dennis Joe, Michailidou Kyriaki, Li Christopher, Peters Ulrike, Hopper John L., Southey Melissa C., Nguyen-Dumont Tu, Nguyen Tuong L., Fasching Peter A., Behrens Annika, Cadby Gemma, Murphy Rachel A., Aronson Kristan, Howell Anthony, Astley Susan, Couch Fergus, Olson Janet, Milne Roger L., Giles Graham G., Haiman Christopher A., Maskarinec Gertraud, Winham Stacey, John Esther M., Kurian Allison, Eliassen Heather, Andrulis Irene, Evans D. Gareth, Newman William G., Hall Per, Czene Kamila, Swerdlow Anthony, Jones Michael, Pollan Marina, Fernandez-Navarro Pablo, McConnell Daniel S., Kristensen Vessela N., Rothstein Joseph H., Wang Pei, Habel Laurel A., Sieh Weiva, Dunning Alison M., Pharoah Paul D. P., Easton Douglas F., Gierach Gretchen L., Tamimi Rulla M., Vachon Celine M., Lindström SaraORCID,
Abstract
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.
Funder
National Cancer Institute National Institutes of Health
Publisher
Springer Science and Business Media LLC
Reference47 articles.
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. 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. 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. 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. 5. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2018. CA Cancer J Clin. 2018;68(1):7–30.
Cited by
20 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|