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

NPJ Biofilms Microbiomes

Department of Microbiology, Department of Biochemistry and Molecular Biology, College of Basic Medical Sciences, Dalian Medical University, Dalian, 116044, China.

Published: October 2024

AI Article Synopsis

  • * Researchers found that many diseases were linked to lower microbial diversity, while some showed increased diversity, with notable changes in microbial communities across most cases.
  • * A machine learning classifier could accurately differentiate between diseased and healthy individuals using identified gut species, enhancing understanding and management of gut microbiome-related diseases in the Chinese population.

Article 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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11442664PMC
http://dx.doi.org/10.1038/s41522-024-00567-9DOI Listing

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