炎症性肠病中的微生物组和代谢组特征通过跨队列的多omics整合分析
Lijun Ning1, Yi-Lu Zhou1, Han Sun2
1State Key Laboratory of Systems Medicine for Cancer; Key Laboratory of Gastroenterology & Hepatology, Ministry of Health; Division of Gastroenterology and Hepatology; Shanghai Cancer Institute; Shanghai Institute of Digestive Disease; Renji Hospital, Shanghai Jiao Tong University School of Medicine. 145 Middle Shandong Road, Shanghai, 200001, China.
这项研究揭示了一致的肠道微生物模式,并确定了炎症性肠病 (IBD) 的新型细菌生物标志物. 多omics分析为IBD提供了强大的诊断工具,改善了对宿主微生物群相互作用的理解.
科学领域:
- 微生物组研究的研究.
- 代谢学 代谢学 代谢学
- 炎症性肠病 (IBD) 是一种炎症性肠病.
背景情况:
- 肠道微生物群和代谢物变化与IBD进展有关.
- 不一致的研究结果阻碍了IBD的理解和生物标志物开发.
研究的目的:
- 在不同人群中全面分析IBD的元基因组和代谢组数据.
- 为了确定一致的肠道微生物特征和IBD诊断的多omics生物标志物.
主要方法:
- 跨队列整合性分析 (CCIA) 对9个元基因组和4个代谢组IBD队列进行了跨队列整合分析.
- 超基因组功能分析和代谢学分析.
- 构建多omics生物相关性 (MOBC) 地图.
主要成果:
- 鉴定了与IBD相关的三个特定细菌 (Asaccharobacter celatus,Gemmiger formicilis,Erysipelatoclostridium ramosum) 的存在.
- 发现与IBD中的便calprotectin相关的双组件系统通路基因.
- 识别了36种不同丰富的代谢物和多omics生物标志物,具有高诊断准确度 (AUROC 0.92-0.98).
结论:
- 确定了IBD的一致的肠道微生物特征和新的生物标志物.
- 多omics分析为IBD提供了可靠的诊断方法.
- 研究结果提供了对宿主微生物群相互作用和IBD潜在治疗点的见解.
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