| Title: | MRI-Derived Body Composition and Breast Cancer Risk in Postmenopausal Women: UK Biobank Study |
| Journal: | Cancers |
| Published: | 18 Dec 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/41463284/ |
| DOI: | https://doi.org/10.3390/cancers17244036 |
| URL: | https://www.mdpi.com/2072-6694/17/24/4036/pdf |
Publication 17105
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Abstract
Background: Obesity is a risk factor for breast cancer mortality in postmenopausal women. However, it remains unclear which specific components of adipose tissue and skeletal muscle are associated with risk. This study assessed the associations between MRI-assessed adiposity, skeletal mass, and breast cancer risk in a population-based cohort. Methods: We analyzed data from 15,669 postmenopausal women in the UK Biobank who underwent MRI for body composition assessment. Age- and multivariable-adjusted hazard ratios (HRs) with 95% confidence intervals (CIs) were estimated using Cox proportional-hazards regression to evaluate the associations between body composition and breast cancer risk, adjusting for relevant confounders. Sensitivity analyses were conducted by excluding breast cancer cases diagnosed within 2 years of the MRI scan. To explore nonlinear relationships, we applied restricted cubic splines with three knots to model associations between visceral adipose tissue (VAT), muscle-fat infiltration (MFI), and breast cancer risk. Results: The mean age of participants was 58.6 years (SD = 5.2; range = 40-69). Higher VAT was significantly associated with increased breast cancer risk (3rd vs. 1st tertile aHR = 1.24, 95% CI: 1.10-1.45). Elevated MFI was also linked with greater risk (3rd vs. 1st tertile aHR = 1.53, 95% CI: 1.25-1.87). These associations persisted after excluding early cancer cases. We observed a J-shaped relationship between VAT, MFI, and breast cancer risk. Conclusions: Higher levels of VAT and MFI are associated with elevated breast cancer risk in postmenopausal women, suggesting that imaging-derived body composition measures may enhance risk prediction and inform prevention strategies.</p>
8 Authors
- Livingstone Aduse-Poku
- Lusine Yaghjyan
- Stephen E. Kimmel
- Susmita Datta
- Shama D. Karanth
- Jae Jeong Yang
- Caretia Washington
- Dejana Braithwaite
1 Application
| Application ID | Title |
|---|---|
| 123666 | Magnetic resonance image-assessed body composition, weight change, and their associations with breast cancer risk and mortality. |
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