Tao Rui, Qiao Mei-Qi, Wang Bin, Fan Jian-Pin, Gao Feng, Wang Shao-Jun, Guo Sheng-Yang, Xia Sheng-Li
Department of Orthopedics, Shanghai University of Medicine & Health Sciences Affiliated Zhoupu Hospital, 1500 Zhoupu Zhouyuan Road, Pudong New Area, Shanghai, 201318, China.
Graduate School, Shanghai University of Traditional Chinese Medicine, 1200 Cailun Road, Pudong New Area, Shanghai, 201203, China.
Curr Osteoporos Rep. 2025 Apr 8;23(1):19. doi: 10.1007/s11914-025-00914-5.
Osteoporosis (OP) is characterized by degraded bone microstructure, loss of bone mass and increased risk of fragility fractures. Currently, T-score determined by dual-energy X-ray absorptiometry (DEXA) measurements has been regarded as the gold standard for the diagnosis of osteoporosis. However, multiple factors have indicated that the T-score is insufficient to identify individuals with osteoporosis at a potentially high risk of fracture, or accurately detect those who require treatment, or continuously monitor the risk of re-fracture and clinical outcomes after treatment. This review covers publications in a range of ten years and comprehensively summarizes the studies in laboratory-based biomarkers for osteoporotic fractures (OF), aiming to provide physicians and surgeons with an update of clinical research in identification, verification and application of these tools, and to provide useful information for the design of future clinical studies.
It was found that bone formation markers (such as PINP, BGP, ECM1 and SOST), bone resorption markers (such as β-CTX, TRAcP5b, osteocalcin, RANKL, RANKL/OPG ratio, and t-PINP/β-CTX), hormonal biomarkers (such as IGF- 1, PTH, leptin, adiponectin and AMH), indicators of inflammation and oxidative stress (SII, IL- 6, LTL, FlOP_360, FlOP_400, and GGT), microRNAs (such as miR- 21, miR- 320a- 3p, miR- 491 - 5p, miR- 485 - 3p, miR- 19b- 1- 5p, miR- 203a, miR- 31 - 5p, miR- 502 - 3p, miR- 4739, miR- 497, miR- 19b, and miR- 107), other biomarkers (SAF-AGEs and glycine), adipocytokines (irisin and Omentin- 1), senescence biomarkers (RDW), and lncRNAs (MIAT) may be useful biomarkers for clinical practice. Further validation of these biomarkers and a better understanding of the underlying molecular mechanisms may help in the development and application of these biomarkers for risk prediction of OF, differential diagnosis among OP, OF and healthy individuals, as well as post-operative monitoring of re-fracture risk and treatment outcomes.
骨质疏松症(OP)的特征是骨微结构退化、骨量丢失以及脆性骨折风险增加。目前,通过双能X线吸收测定法(DEXA)测量确定的T值已被视为骨质疏松症诊断的金标准。然而,多种因素表明,T值不足以识别骨折风险可能较高的骨质疏松症患者,或准确检测出需要治疗的患者,也无法持续监测再次骨折风险和治疗后的临床结局。本综述涵盖了十年间的相关出版物,并全面总结了基于实验室的骨质疏松性骨折(OF)生物标志物的研究,旨在为内科医生和外科医生提供这些工具在识别、验证和应用方面的临床研究最新进展,并为未来临床研究的设计提供有用信息。
研究发现,骨形成标志物(如PINP、BGP、ECM1和SOST)、骨吸收标志物(如β-CTX、TRAcP5b、骨钙素、RANKL、RANKL/OPG比值和t-PINP/β-CTX)、激素生物标志物(如IGF-1、PTH、瘦素、脂联素和AMH)、炎症和氧化应激指标(SII、IL-6、LTL、FlOP_360、FlOP_400和GGT)、微小RNA(如miR-21、miR-320a-3p、miR-491-5p、miR-485-3p、miR-19b-1-5p、miR-203a、miR-31-5p、miR-502-3p、miR-4739、miR-497、miR-19b和miR-107)、其他生物标志物(SAF-AGEs和甘氨酸)、脂肪细胞因子(鸢尾素和网膜素-1)、衰老生物标志物(红细胞分布宽度)和长链非编码RNA(MIAT)可能是临床实践中有用的生物标志物。对这些生物标志物的进一步验证以及对潜在分子机制的更好理解,可能有助于开发和应用这些生物标志物来预测OF风险、在OP、OF和健康个体之间进行鉴别诊断,以及术后监测再次骨折风险和治疗效果。