| Title: | Bone mineral density and risk of breast cancer: A cohort study and Mendelian randomization analysis |
| Journal: | Cancer |
| Published: | 5 May 2022 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/35511874/ |
| DOI: | https://doi.org/10.1002/cncr.34252 |
Publication 7137
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Abstract
BACKGROUND: Estrogen is involved in both bone metabolism and breast cancer proliferation. However, evidence about the risk of breast cancer according to women's bone mineral density (BMD) is scarce, and little is known about their causal associations.METHODS: Women participating in the UK Biobank cohort were used to investigate the association between BMD and the risk of breast cancer using Cox regression models. Instrumental variants associated with estimated BMD (eBMD) were extracted from genome-wide association studies with European ancestry. Logistic regression was used to calculate the genetic association with breast cancer in the UK Biobank and 2-sample Mendelian randomization (MR) analyses to assess their causal associations with breast cancer. Finally, the pleiotropic conditional false discovery rate (cFDR) method was conducted to further detect common genetic variants between BMD and breast cancer.
RESULTS: Compared with the general population, postmenopausal women with BMD T scores <-2.5 had a lower risk of breast cancer (hazard ratio [HR], 0.77; 95% CI, 0.59-1.00), and this effect was stronger in women with fracture (HR, 0.31; 95% CI, 0.12-0.82). In MR analysis, no causal associations between eBMD and breast cancer were observed. The cFDR method identified 63 pleiotropic loci associated with both BMD and breast cancer, of which CCDC170, ESR1, and FTO might play crucial roles in their pleiotropy.
CONCLUSIONS: An association between BMD and the risk of postmenopausal breast cancer in the UK Biobank was observed, whereas no evidence supported their causal association. Instead, their association could be explained by pleiotropic genetic variants leading to the pathology of osteoporosis and breast cancer.
6 Authors
- Yanyu Zhang
- Xinhe Mao
- Xingxing Yu
- Xiaoxi Huang
- Wei He
- Haomin Yang
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