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一项涉及 36 项肠道微生物组研究的大规模分析揭示了常见疾病的普遍物种特征。

A population-scale analysis of 36 gut microbiome studies reveals universal species signatures for common diseases.

机构信息

Centre for Translational Medicine, Shenzhen Bao'an Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, 518000, China.

Key Laboratory of Health Cultivation of the Ministry of Education, Beijing University of Chinese Medicine, Beijing, 100029, China.

出版信息

NPJ Biofilms Microbiomes. 2024 Oct 1;10(1):96. doi: 10.1038/s41522-024-00567-9.

Abstract

The gut microbiome has been implicated in various human diseases, though findings across studies have shown considerable variability. In this study, we reanalyzed 6314 publicly available fecal metagenomes from 36 case-control studies on different diseases to investigate microbial diversity and disease-shared signatures. Using a unified analysis pipeline, we observed reduced microbial diversity in many diseases, while some exhibited increased diversity. Significant alterations in microbial communities were detected across most diseases. A meta-analysis identified 277 disease-associated gut species, including numerous opportunistic pathogens enriched in patients and a depletion of beneficial microbes. A random forest classifier based on these signatures achieved high accuracy in distinguishing diseased individuals from controls (AUC = 0.776) and high-risk patients from controls (AUC = 0.825), and it also performed well in external cohorts. These results offer insights into the gut microbiome's role in common diseases in the Chinese population and will guide personalized disease management strategies.

摘要

肠道微生物组与各种人类疾病有关,但各研究的结果表明其存在很大的可变性。在这项研究中,我们重新分析了 36 项不同疾病的病例对照研究中 6314 个公开可用的粪便宏基因组,以研究微生物多样性和与疾病相关的特征。使用统一的分析管道,我们观察到许多疾病中的微生物多样性降低,而有些疾病则表现出多样性增加。在大多数疾病中都检测到微生物群落的显著改变。荟萃分析确定了 277 种与肠道相关的疾病相关物种,其中包括许多在患者中富集的机会性病原体和有益微生物的减少。基于这些特征的随机森林分类器在区分患病个体和对照个体(AUC=0.776)以及高危患者和对照个体(AUC=0.825)方面具有很高的准确性,并且在外部队列中也表现良好。这些结果提供了对中国人群常见疾病中肠道微生物组作用的深入了解,并将指导个性化疾病管理策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0291/11442664/38f8f045e067/41522_2024_567_Fig1_HTML.jpg

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