调查肠道微生物群对胆病的影响:通过测序和预测建模揭示洞察力
Hu Boyang1,2,3,4,5, Yao Yanjun1,2,3,4,5, Zhuang Jing1,2,3,4,5
1Department of General Surgery, Huzhou Central Hospital, Affiliated Huzhou Hospital, Zhejiang University School of Medicine, No.1558, Sanhuan North Road, Wuxing District, Huzhou, Zhejiang Province 313000, China.
Journal of applied microbiology
|April 13, 2024
概括
胆结石患者的肠道细菌组成不同. 像Escherichia flexneri和Klebsiella pneumonae这样的特定细菌在胆结石患者中更为丰富,有助于通过预测模型进行早期检测.
科学领域:
- 胃肠病学和肝病学 胃肠学和肝病学
- 微生物组研究 微生物组研究
- 医学诊断 医学诊断 医学诊断
背景情况:
- 胆结石 (胆结石) 是一种普遍存在的肝胆道疾病.
- 肠道微生物群的改变与胆结石的形成有关,可以作为预测生物标志物.
研究的目的:
- 为了研究胆病和肠道细菌社区之间的相关性.
- 为了识别与胆结石疾病相关的特定肠道细菌.
主要方法:
- 从100名胆病患者和250名健康对照者的便样本中对肠道细菌进行16S rRNA基因测序.
- 使用Mothur和LEfSe.Se进行细菌多样性和丰富性的分析.
- 使用机器学习算法开发胆病的预测模型.
主要成果:
- 在胆病患者和健康个体之间观察到肠道细菌丰富度的显著差异,但不是多样性.
- 在胆病患者中增加了Clostridia,Escherichia flexneri和Klebsiella pneumoniae的丰富性.
- 一个基于CatBoost的预测模型实现了高精度 (AUC:0.962) 的胆病检测.
结论:
- 典型的肠道细菌样本可以作为胆结石查的新型预测目标.
- 使用肠道细菌的机器学习模型可以促进胆病的早期检测和风险评估.
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