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

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 CadbyRachel 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, NBCS Investigators, 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

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)


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.

Original languageEnglish
Article number27
Pages (from-to)27
Number of pages1
JournalBreast cancer research : BCR
Issue number1
Publication statusPublished - Dec 2022


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