| Title: | Plasma proteomic profiles reveal proteins and three characteristic patterns associated with osteoporosis: A prospective cohort study |
| Journal: | Journal of Advanced Research |
| Published: | 25 Oct 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/39490735/ |
| DOI: | https://doi.org/10.1016/j.jare.2024.10.019 |
Publication 13310
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
Abstract
INTRODUCTION: Exploration of plasma proteins associated with osteoporosis can offer insights into its pathological development, identify novel biomarkers for screening high-risk populations, and facilitate the discovery of effective therapeutic targets.</p>
OBJECTIVES: The present study aimed to identify potential proteins associated with osteoporosis and to explore the underlying mechanisms from a proteomic perspective.</p>
METHODS: The study included 42,325 participants without osteoporosis in the UK Biobank (UKB), of whom 1,477 developed osteoporosis during the follow-up. We used Cox regression and Mendelian randomization analysis to examine the association between plasma proteins and osteoporosis. Machine learning was utilized to explore proteins with strong predictive power for osteoporosis risk.</p>
RESULTS: Of 2,919 plasma proteins, we identified 134 significantly associated with osteoporosis, with sclerostin (SOST), adiponectin (ADIPOQ), and creatine kinase B-type (CKB) exhibiting strong associations. Twelve of these proteins showed significant associations with bone mineral density (BMD) T-score at the femoral neck, lumbar spine, and total body. Mendelian randomization further supported causal relationships between 17 plasma proteins and osteoporosis. Moreover, follitropin subunit beta (FSHB), SOST, and ADIPOQ demonstrated high importance in predictive modeling. Utilizing a predictive model built with 10 proteins, we achieved relatively accurate prediction of osteoporosis onset up to 5 years in advance (AUC = 0.803). Finally, we identified three osteoporosis-related protein modules associated with immunity, lipid metabolism, and follicle-stimulating hormone (FSH) regulation from a network perspective, elucidating their mediating roles between various risk factors (smoking, sleep, physical activity, polygenic risk score (PRS), and menopause) and osteoporosis.</p>
CONCLUSION: We identified several proteins associated with osteoporosis and highlighted the role of plasma proteins in influencing its progression through three primary pathways: immunity, lipid metabolism, and FSH regulation. This provides further insights into the distinct molecular patterns and pathogenesis of bone loss and may contribute to strengthening early diagnosis and long-term monitoring of the condition.</p>
9 Authors
- Yi Zheng
- Jincheng Li
- Yucan Li
- Jiacheng Wang
- Chen Suo
- Yanfeng Jiang
- Li Jin
- Kelin Xu
- Xingdong Chen
1 Application
| Application ID | Title |
|---|---|
| 92718 | Deciphering chronic disease - association studies of genome, exposome and phenome |
Enabling scientific discoveries that improve human health