大规模分析揭示了结核病进展和预后的拼接生物标志物
Hongli Lai1, Mengyuan Lyu2, Hongxia Ruan2
1Department of Laboratory Medicine/Clinical Laboratory Medicine Research Center, West China Hospital, Sichuan University, Chengdu, Sichuan Province, 610041, PR China; West China Medical School/West China Hospital, Sichuan University, Chengdu, Sichuan Province, 610041, PR China.
Computers in biology and medicine
|February 25, 2024
概括
异常的替代拼接 (AS) 显示了预测结核病 (TB) 结果的潜力. 特定的AS事件可以预测结核病预后,为疾病管理提供新的生物标志物.
科学领域:
- 基因组学就是基因组学.
- 分子生物学分子生物学
- 生物信息学是一种生物信息学.
背景情况:
- 异常的替代拼接 (AS) 越来越多地与结核病 (TB) 有关.
- 在预测结核病进展和预后方面,AS的作用需要进一步澄清.
研究的目的:
- 研究AS事件作为TB进展和预后的生物标志物的潜力.
- 使用机器学习开发结核病结果的预测模型.
主要方法:
- 对结核病进展和预后的公共RNA-seq数据集的分析.
- 使用百分比分成 (PSI) 和SUPPA2.2.使用AS事件的量化.
- 使用多种机器学习方法开发和评估预测模型.
主要成果:
- 三个AS事件 (GET1-SE,TPD52-AF,TIMM10-A5) 对结核病进展的预测价值有限.
- 五个AS事件 (PHF23-AF,KIB1B-SE,MACROD2-A3,CD55-RI,GALNT11-AF) 被确定为结核病预后的候选生物标志物.
- 整合了这五个事件的XGBoost模型在训练组中实现了0.875的AUC,在测试组中达到0.805.
结论:
- 特定的AS事件,特别是PHF23-AF,KIB1B-SE,MACROD2-A3,CD55-RI和GALNT11-AF,显示出预测结核病预后的希望.
- 这些AS事件代表了TB结果预测的潜在生物标志物.
- 需要进一步的研究来验证这些发现并探索它们的临床实用性.
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