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

Medicine and Health

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

W. Sun, Y. Zhang, et al.

Delve into groundbreaking research by Wen Sun and colleagues as they uncover the intricate relationship between gut microbiome diversity and various diseases. This comprehensive study of 6314 fecal metagenomes reveals profound insights into disease-associated species and holds promise for personalized disease management.

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~3 min • Beginner • English
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 higher abundance of protective species in individuals from controls (AUC = 0.825), and high-risk paths inherent in distinguishing disease individuals from controls (AUC = 0.776) and high-risk patients from general cohorts. These results offer insights into the gut microbiome’s role in common diseases and the potential for personalized disease management strategies.
Publisher
npj Biofilms and Microbiomes
Published On
Oct 01, 2024
Authors
Wen Sun, Yue Zhang, Ruochun Guo, Shanshan Sha, Changming Chen, Hayan Ullah, Yan Zhang, Jie Ma, Wei You, Jinxin Meng, Qingbo Lv, Lin Cheng, Shao Fan, Rui Li, Xiaohong Mu, Shenghui Li, Qiulong Yan
Tags
gut microbiome
microbial diversity
disease signatures
opportunistic pathogens
protective species
personalized management
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