机器学习辅助的发现揭示了糖尿病病中肠道微生物群和宿主代谢干扰之间的新型相互作用
I-Wen Wu1,2, Yu-Chieh Liao3, Tsung-Hsien Tsai4
1Department of Nephrology, Chang Gung Memorial Hospital, Keelung, Taiwan.
Gut microbes
|March 6, 2025
概括
这项研究使用机器学习识别了糖尿病病 (DKD) 的肠道微生物群生物标志物. 这些与新陈代谢和功能相关的生物标志物揭示了DKD患者的肠-轴连接.
科学领域:
- 微生物组研究 微生物组研究
- 腎臟健康 腎臟健康
- 代谢障碍 代谢障碍 代谢障碍
背景情况:
- 糖尿病病 (DKD) 是一个重大的医疗保健挑战.
- 在DKD中,肠道微生物群和宿主健康之间的功能关系尚不清楚.
- 了解肠-轴对于DKD管理至关重要.
研究的目的:
- 阐明肠道微生物群在影响DKD患者功能方面的功能能力.
- 为了确定DKD的新型肠道微生物群生物标志物.
- 探索肠道微生物群,新陈代谢和病之间的机制联系.
主要方法:
- 招募了990名受试者:对照组 (n=455),2型糖尿病 (DM,n=204),DKD (n=182) 和慢性病 (CKD,n=149).
- 进行了便DNA的全长16S rRNA基因测序.
- 利用机器学习 (ML) 和差异丰度方法来识别微生物群生物标志物并分析功能能力.
主要成果:
- 开发了新的微生物群生物标志物 (相对丰富,存在/缺失,等级比) 具有高精度 (0.72-0.78) 和AUC (0.79-0.86) 区分疾病组.
- 确定了13种与人体指数,代谢指数和脏指数强烈相关的歧视性肠道微生物群生物标志物.
- 特定于DKD的生物标志物 *Gemmiger* spp. 显示碳水化合物代谢和分支链氨基酸 (BCAA) 生物合成的丰富,与DM和DKD患者循环BCAA和L-谷氨酸的增加相关.
结论:
- 在DKD患者中建立了涉及肠-轴的显著联系.
- 突出了特定的肠道细菌作为DKD的潜在诊断和机械生物标志物.
- 在高血糖条件下表明糖解,酸盐发酵和BCAA生物合成途径的改变.
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