中国骨质疏松杂志

绝经后女性骨折风险与肌源性因子及骨代谢指标的相关性研究

Correlation between fracture risk and myokines and bone metabolic markers in postmenopausal women

DOI：10.3969/j.issn.1006-7108.2023.09.001

英文关键词:FRAX score postmenopausal osteoporosis bone metabolism index irisin

基金项目:国家自然科学基金（1873320）；江苏省中医药领军人才项目（SLJ0218）；无锡市“双百”中青年医疗卫生拔尖人才项目（HB2020063）

作者	单位
彭竑程1 李雨真2 华臻3 王建伟3 陈浩2 梁杰3*	1.锡山区人民医院东亭分院，江苏无锡 214101 2.南京中医药大学，江苏南京 210023 3.南京中医药大学无锡附院，江苏无锡 214071

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中文摘要:

目的探讨绝经后女性肌源性因子及骨代谢指标与骨质疏松性骨折风险的相关性。方法研究南京中医药大学无锡附院2021年6月至2022年6月门诊绝经后女性患者215例，根据纳排标准筛选出184例，其中绝经后骨质疏松88例，骨量减少65例，正常骨量31例。收集基线资料、肌骨代谢指标（碱性磷酸酶（ALP）、I型原胶原氨基端前肽（PINP）、鸢尾素（irisin）及肌肉抑制素（MSTN）等）及BMD，应用FRAX评估软件来评估骨折风险。控制年龄、骨量、FRAX风险等级比较肌骨代谢指标、体质指数（BMI）及体表面积（BS）的差异，并对绝经后女性骨折风险和各指标进行相关性分析；多重线性回归分析骨折风险概率与相关变量间的关系。结果不同年龄组间BMD、PMOF及PHF差异存在统计学意义（P<0.05）；不同骨量组间BMI、BS、ALP、PMOF及PHF差异存在统计学意义（P<0.05）；FRAX不同风险组年龄、BS、BMD、Ca、ALP、PINP、irisin及MSTN之间差异存在统计学意义（P<0.05）；相关性分析显示FRAX骨折概率与年龄、PINP、MSTN成正相关（P<0.05）,与BMI、BS、BMD及irisin成负相关（P<0.05），二元Logistic回归分析显示年龄、PINP与irisin是骨折风险的重要相关因素。结论基于适合亚洲人群的FRAX干预阈值研究，绝经后女性年龄、PINP与irisin是骨折风险评估的敏感因素，这对优化骨质疏松骨折风险模型有重要意义。

英文摘要:

Objective To investigate the correlation between myogenic factors and bone metabolic indexes and the risk of osteoporosis fractures in postmenopausal women. Methods A total of 215 postmenopausal female patients in the Wuxi Affiliated Hospital of Nanjing University of Traditional Chinese Medicine from June 2021 to June 2022 were studied. Among those, 184 patients were selected according to the criteria of admission and emission, including 88 cases with postmenopausal osteoporosis, 65 cases with bone mass reduction, and 31 cases with normal bone mass. Baseline data, musculoskeletal metabolic indicators including alkaline phosphatase (ALP), type I procollagen amino terminal propeptide (PINP), irisin, and muscle inhibin (MSTN), and BMD were collected. FRAX evaluation software was used to assess the fracture risk. The differences in muscle bone metabolic indicators, body mass index (BMI), and body surface area (BS) were compared based on control age, bone mass, and FRAX risk level. The correlation between postmenopausal women's fracture risk and various indicators was analyzed. Multiple linear regression analysis was used to analyze the relationship between fracture risk probability and related variables. Results There were significant differences in BMD, PMOF, and PHF among different age groups (P<0.05). There were significant differences in BMI, BS, ALP, PMOF, and PHF among different bone mass groups (P<0.05). There were significant differences between FRAX risk groups in age, BS, BMD, Ca, ALP, PINP, irisin, and MSTN (P<0.05). The correlation analysis showed that FRAX fracture probability was positively correlated with age, PINP, and MSTN (P<0.05), and negatively correlated with BMI, BS, BMD, and irisin (P<0.05). The binary logistic regression analysis showed that age, PINP, and irisin were important factors related to fracture risk. Conclusion Based on the FRAX intervention threshold study suitable for Asian populations, age, PINP, and irisin in postmenopausal women are sensitive factors for fracture risk assessment. This is important for optimizing fracture risk models for osteoporosis.

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