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研究结性脊柱炎的潜在生物标志物:使用机器学习对线粒体和衰老途径的研究

Lu Yang^1,2, Chitat Chang¹, WengFai Tam³

¹Faculty of Chinese Medicine, Macau University of Science and Technology, Macau, People's Republic of China.

Journal of inflammation research

|November 10, 2025

概括

研究人员确定了COX17和MATK作为关键生物标志物,将线粒体功能障碍和细胞衰老与结性脊髓炎 (AS) 联系起来. 这些发现为早期发现疾病和为AS患者提供量身定制的治疗提供了潜力.

科学领域:

免疫学免疫学免疫学
遗传学是一个遗传学.
细胞生物学细胞生物学

背景情况:

化脊柱炎 (AS) 是一种慢性炎症性疾病.
线粒体功能障碍和细胞衰老与AS进展有关.

研究的目的:

确定结性脊柱炎的新生物标志物.
将线粒体功能障碍和细胞衰老与AS病原发生联系起来.

主要方法:

分析了来自AS患者和对照组的转录组数据.
利用生物信息学和机器学习来选生物标志物.
在独立数据集和小鼠模型中验证的结果.

主要成果:

在AS中鉴定出差异表达的线粒体和衰老相关基因.
发现COX17和MATK是重要的诊断候选物.
在AS小鼠模型中验证了COX17和MATK,显示出改变的表达和骨质生成活性.

结论:

COX17和MATK是结性脊柱炎的有希望的生物标志物.
这些生物标志物将线粒体功能障碍和细胞衰老与AS联系起来.
对AS进行更好的早期检测和个性化治疗的潜力.

关键词:

结性脊柱炎是一种疾病.细胞衰老细胞衰老机器学习是机器学习.线粒体功能障碍线粒体功能障碍转录组分析转录组分析

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