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通过整合生物信息学和机器学习,识别和实验验证与焦点细分样硬化相关的自基因,通过整合生物信息学和机器学习
Tianwen Yao1, Qingliang Wang2, Shisheng Han1
1Department of Nephrology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, 110 Ganhe Road, Hongkou District, Shanghai, 200437, China.
Scientific reports
|November 25, 2025
概括
焦点细分性淋巴细胞硬化 (FSGS) 涉及细胞损伤. 这项研究确定TP53和RELA是关键的自相关基因,具有FSGS患者的诊断和治疗潜力.
科学领域:
- 腎臟病學 (nephrology) 是一種醫學.
- 分子生物学分子生物学
- 免疫学 免疫学 免疫学
背景情况:
- 焦点细分性淋巴结核硬化 (FSGS) 是慢性病的主要原因,其特征是受细胞损伤.
- 自在维持受体细胞健康方面发挥着至关重要的作用,其失调与FSGS的发病有关.
研究的目的:
- 研究与自相关的基因 (ARG) 以及它们作为FSGS诊断和治疗标记物的潜力.
- 确定与FSGS发展和进展相关的核心ARG.
主要方法:
- 利用多个基因表达数据集 (GSE200828,GSE99340,GSE47183,GSE108109,GSE104948,GSE129973) 来识别与自相关的差异表达基因 (ARDEG).
- 进行了生物信息分析,包括蛋白质-蛋白质相互作用 (PPI) 网络,功能丰富,基因组丰富,免疫细胞透和比较毒基因组学 (cMAP).
- 在FSGS的体内大鼠模型中,使用西斑和qRT-PCR验证了关键基因 (TP53,RELA).
主要成果:
- 确定了9个ARDEG,其中TP53在PPI网络中显示了最高的连接性.
- 在自和免疫相关途径中,ARDEGs被显著丰富.
- 在FSGS中,FSGS患者表现出免疫细胞简介的改变,FSGS中TP53和RELA的上调,显示出高诊断价值.
结论:
- TP53和RELA是FSGS的有希望的自相关诊断标记物.
- 这些基因也代表管理FSGS的潜在治疗点.
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