Disentangling the relationships of body mass index and circulating sex hormone concentrations in mammographic density using Mendelian randomization

Purpose Mammographic density phenotypes, adjusted for age and body mass index (BMI), are strong predictors of breast cancer risk. BMI is associated with mammographic density measures, but the role of circulating sex hormone concentrations is less clear. We investigated the relationship between BMI,...

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Published inBreast cancer research and treatment Vol. 206; no. 2; pp. 295 - 305
Main Authors Haas, Cameron B., Chen, Hongjie, Harrison, Tabitha, Fan, Shaoqi, Gago-Dominguez, Manuela, Castelao, Jose E., Bolla, Manjeet K., Wang, Qin, Dennis, Joe, Michailidou, Kyriaki, Dunning, Alison M., Easton, Douglas F., Antoniou, Antonis C., Hall, Per, Czene, Kamila, Andrulis, Irene L., Mulligan, Anna Marie, Milne, Roger L., Fasching, Peter A., Haeberle, Lothar, Garcia-Closas, Montserrat, Ahearn, Thomas, Gierach, Gretchen L., Haiman, Christopher, Maskarinec, Gertraud, Couch, Fergus J., Olson, Janet E., John, Esther M., Chenevix-Trench, Geogia, Berrington de Gonzalez, Amy, Jones, Michael, Stone, Jennifer, Murphy, Rachel, Aronson, Kristan J., Wernli, Karen J., Hsu, Li, Vachon, Celine, Tamimi, Rulla M., Lindström, Sara
Format Journal Article
LanguageEnglish
Published New York Springer US 2024
Springer Nature B.V
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Summary:Purpose Mammographic density phenotypes, adjusted for age and body mass index (BMI), are strong predictors of breast cancer risk. BMI is associated with mammographic density measures, but the role of circulating sex hormone concentrations is less clear. We investigated the relationship between BMI, circulating sex hormone concentrations, and mammographic density phenotypes using Mendelian randomization (MR). Methods We applied two-sample MR approaches to assess the association between genetically predicted circulating concentrations of sex hormones [estradiol, testosterone, sex hormone-binding globulin (SHBG)], BMI, and mammographic density phenotypes (dense and non-dense area). We created instrumental variables from large European ancestry-based genome-wide association studies and applied estimates to mammographic density phenotypes in up to 14,000 women of European ancestry. We performed analyses overall and by menopausal status. Results Genetically predicted BMI was positively associated with non-dense area (IVW: β  = 1.79; 95% CI = 1.58, 2.00; p  = 9.57 × 10 −63 ) and inversely associated with dense area (IVW: β  = − 0.37; 95% CI = − 0.51,− 0.23; p  = 4.7 × 10 −7 ). We observed weak evidence for an association of circulating sex hormone concentrations with mammographic density phenotypes, specifically inverse associations between genetically predicted testosterone concentration and dense area ( β  = − 0.22; 95% CI = − 0.38, − 0.053; p  = 0.009) and between genetically predicted estradiol concentration and non-dense area ( β  =  − 3.32; 95% CI = − 5.83, − 0.82; p  = 0.009), although results were not consistent across a range of MR approaches. Conclusion Our findings support a positive causal association between BMI and mammographic non-dense area and an inverse association between BMI and dense area. Evidence was weaker and inconsistent for a causal effect of circulating sex hormone concentrations on mammographic density phenotypes. Based on our findings, associations between circulating sex hormone concentrations and mammographic density phenotypes are weak at best.
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ISSN:0167-6806
1573-7217
1573-7217
DOI:10.1007/s10549-024-07306-w