划分疾病与疾病相互作用的标志物:一个系统的方法及其对多个糖尿病-虫队伍的应用
Nilesh Subramanian1,2, Philge Philip2,3, Anuradha Rajamanickam4
1Department of Computer Science and Engineering, Indian Institute of Technology (IIT) Madras, Chennai, India.
BMC bioinformatics
|November 1, 2025
概括
这项研究引入了一种新的方法来量化疾病的相互作用,发现IFN-和TNF-α等特定的免疫标记物在治疗前是糖尿病和虫共患症的关键.
科学领域:
- 免疫学 免疫学 免疫学
- 计算生物学 计算生物学
- 系统生物学 系统生物学
背景情况:
- 伴随性疾病复杂化了超出个体疾病的免疫反应.
- 这些复杂相互作用的数据驱动量化目前缺乏.
研究的目的:
- 开发和应用一种系统的方法来量化疾病与疾病相互作用 (DDI) 对分子标记物的影响.
- 为了确定在并发症条件下表现出明显反应的特定免疫标志物.
主要方法:
- 从单一和双重疾病队列收集和预处理的数据.
- 扩展差异表达分析以识别DDI标记物 (例如细胞因子).
- 使用细胞因子和免疫细胞知识库解释DDI标记.
主要成果:
- 在治疗前确定IFN-gamma,TNF-alpha和IL-2作为糖尿病-虫界面上的DDI标记物.
- 在虫感染治疗后观察到这些细胞因子的DDI状态的丧失.
- 对IFN-和TNF-α治疗后的DDI贡献的量化显著减少.
- 丰富的信号通路 (IL-10,IL-4/IL-13) 表明DDI标记物的机械作用.
结论:
- 量化了对细胞因子标记物的虫糖尿病DDI的程度,澄清了它们的致病作用.
- 开发的DDI方法可用于剖析任何两种疾病之间的相互作用,使用可用的多队列数据.
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