UBC Faculty Research and Publications

Genome-wide and transcriptome-wide association studies of mammographic density phenotypes reveal novel loci 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. G.; 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, Sara

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.

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Attribution 4.0 International (CC BY 4.0)