| Title: | Genetic architecture of bone marrow fat fraction implies its involvement in osteoporosis risk |
| Journal: | Nature Communications |
| Published: | 12 Aug 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/40796918/ |
| DOI: | https://doi.org/10.1038/s41467-025-62826-3 |
Publication 19748
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Abstract
Bone marrow adipose tissue, as a distinct adipose subtype, has been implicated in the pathophysiology of skeletal, metabolic, and hematopoietic disorders. To identify its underlying genetic factors, we utilized a deep learning algorithm capable of quantifying bone marrow fat fraction (BMFF) in the vertebrae and proximal femur using magnetic resonance imaging data of over 38,000 UK Biobank participants. Genome-wide association analyses uncovered 373 significant BMFF-associated variants (P-value < 5 × 10−9), with enrichment in bone remodeling, metabolism, and hematopoiesis pathway. Furthermore, genetic correlation highlighted a significant association between BMFF and skeletal disease. In about 300,000 individuals, polygenic risk scores derived from three proximal femur BMFF were significantly associated with increased osteoporosis risk. Notably, Mendelian randomization analyses revealed a causal link between proximal femur BMFF and osteoporosis. Here, we show critical insights into the genetic determinants of BMFF and offer perspectives on the biological mechanisms driving osteoporosis development.</p>
17 Keywords
- Adipose Tissue
- Aged
- Bone Marrow
- Deep Learning
- Female
- Femur
- Genetic Predisposition to Disease
- Genome-Wide Association Study
- Humans
- Magnetic Resonance Imaging
- Male
- Mendelian Randomization Analysis
- Middle Aged
- Multifactorial Inheritance
- Osteoporosis
- Polymorphism, Single Nucleotide
- Risk Factors
18 Authors
- Zuyou Wu
- Yang Yang
- Caibo Ning
- Jiali Li
- Yimin Cai
- Yanmin Li
- Zilong Cao
- Shuangshuang Tian
- Jingyi Peng
- Qianying Ma
- Chunyi He
- Shuting Xia
- Jun Chen
- Xiaoping Miao
- Zhen Li
- Ying Zhu
- Qian Chu
- Jianbo Tian
1 Application
| Application ID | Title |
|---|---|
| 94939 | Combination of polygenic risk score and classical risk factors to predict Pan-cancer risks |
Enabling scientific discoveries that improve human health