解码IBD进展:个性化疾病分层的动态生物标志物地图
Yi Tao1,2, Lin-F Wang3, Pan Li4
1Phase I Clinical Trial Ward, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
Journal of translational medicine
|October 11, 2025
概括
这项研究揭示了肠道微生物群和宿主基因表达如何准确地非侵入性地分期炎症性肠病 (IBD). 整合多omics数据可以提高个性化IBD治疗策略的精度.
科学领域:
- 胃肠病学 胃肠病学
- 微生物组研究 微生物组研究
- 基因组学就是基因组学.
背景情况:
- 精确的炎症性肠病 (IBD) 阶段确定对于有效的治疗和患者的治疗结果至关重要.
- 肠道微生物群和宿主转录特征是IBD进展的关键决定因素.
- 预测IBD严重程度和指导个性化治疗需要非侵入性生物标志物.
研究的目的:
- 为非侵入性IBD分期开发一个多学科框架.
- 为了确定IBD分层的微生物和宿主转录生物标志物.
- 整合多omics数据,以便更好地预测IBD严重程度.
主要方法:
- 从97名参与者 (IBD患者和健康对照) 的便和血清样本的综合多组分析.
- 16S rRNA测序用于微生物分析和RNA-seq用于宿主转录组学.
- 基于网络 (NetMoss) 和机器学习 (REF-SVM,堆叠分类器) 的方法用于生物标志物发现和预测建模.
主要成果:
- 在IBD患者中确定了临床调节障碍和降低了微生物α多样性.
- 发现了特定阶段的微生物种群 (例如Bifidobacterium, Bacteroides) 和宿主基因表达标记物 (例如YIPF4, HBB, TUBB1).
- 多omics集成在IBD分期中实现了高精度 (AUCs~0.80),揭示了微生物与宿主相互作用.
结论:
- 为非侵入性IBD分期建立了一个多学科框架.
- 证明了结合微生物和转录基因数据的临床实用性,以实现精确的IBD分层.
- 这些研究结果支持多组生物标志物的潜力,以改变IBD管理和治疗干预措施.
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