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骨关节炎中孟德尔随机化分析的应用:现状与未来展望

Using Mendelian randomization analyses in osteoarthritis: state of art and future perspectives.

作者信息

Liu Houpu, Zhu Jiahao, Jiang Han, Cai Bingyue, Yang Chen, Sun Lingling, Wang Jing, Li Yingjun

机构信息

School of Public Health, Hangzhou Medical College, Hangzhou, China.

Department of Orthopaedics, the Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.

出版信息

Ann Med. 2025 Dec;57(1):2533428. doi: 10.1080/07853890.2025.2533428. Epub 2025 Jul 23.

Abstract

AIMS

The etiology of osteoarthritis (OA) remains unclear, involving a complex interaction of environmental and genetic factors. Observational studies have contributed substantially to identify modifiable risk factors that were associated with OA risk, but conclusions about the causality are hard to draw as these observed associations are susceptible to be interfered with reverse causality and residual confounding.

METHODS

Mendelian randomization (MR) is a valid approach to provide evidence on causal associations, by using genetic variants as 'proxies' for modifiable exposures to examine the effect of genetic susceptibility to the exposures on the outcomes. Such a method provides an opportunity to elucidate OA pathogenesis and therefore to provide evidence for novel interventions and treatment strategies.

FINDINGS

In this systematic review, we synthesized evidence from recent studies that applied MR in OA in terms of eight aspects, including lifestyle, nutrition, bone mineral density, reproductive factors, metabolic syndrome, cardiovascular disease, inflammation cytokines and other risk factors.

CONCLUSIONS

We reflected on the limitations of its current applications in OA, followed by a discussion of our findings and future directions in this field.

摘要

目的

骨关节炎(OA)的病因仍不明确,涉及环境和遗传因素的复杂相互作用。观察性研究在确定与OA风险相关的可改变风险因素方面做出了重大贡献,但由于这些观察到的关联易受反向因果关系和残余混杂因素的干扰,难以得出因果关系的结论。

方法

孟德尔随机化(MR)是一种有效的方法,通过使用基因变异作为可改变暴露的“代理”,来检验暴露的遗传易感性对结局的影响,从而为因果关联提供证据。这种方法为阐明OA发病机制提供了机会,进而为新的干预措施和治疗策略提供证据。

研究结果

在本系统评价中,我们从近期在OA中应用MR的研究中,就生活方式、营养、骨密度、生殖因素、代谢综合征、心血管疾病、炎症细胞因子和其他风险因素等八个方面综合了证据。

结论

我们反思了其目前在OA应用中的局限性,随后讨论了我们的研究结果以及该领域的未来方向。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd8d/12288192/7b9cb6015589/IANN_A_2533428_F0001_B.jpg

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