4.7 Article

Metagenomic Analysis of Common Intestinal Diseases Reveals Relationships among Microbial Signatures and Powers Multidisease Diagnostic Models

期刊

MSYSTEMS
卷 6, 期 3, 页码 -

出版社

AMER SOC MICROBIOLOGY
DOI: 10.1128/mSystems.00112-21

关键词

gut dysbiosis; human microbiome; intestinal disease; machine learning-based disease classification; noninvasive disease diagnosis

资金

  1. National Key Research and Development Program of China [2019YFA0905600, 2018YFC0910500]
  2. National Natural Science Foundation of China [61932008, 61772368, 61572363]
  3. Natural Science Foundation of Shanghai [17ZR1445600]
  4. Shanghai Municipal Science and Technology Major Project [2018SHZDZX01]
  5. ZJLab

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The study identified consistent microbial alterations in common intestinal diseases, distinguished disease-enriched marker species into disease-specific and disease-common clusters, and revealed their distinct phylogenetic relationships. Marker species showed similar metabolic preferences within clusters and different metabolic preferences between clusters. The diseased gut may represent a stressed environment, posing stronger selection pressure on gut microbes.
Common intestinal diseases such as Crohn's disease (CD), ulcerative colitis (UC), and colorectal cancer (CRC) share clinical symptoms and altered gut microbes, necessitating cross-disease comparisons and the use of multidisease models. Here, we performed meta-analyses on 13 fecal metagenome data sets of the three diseases. We identified 87 species and 65 pathway markers that were consistently changed in multiple data sets of the same diseases. According to their overall trends, we grouped the disease-enriched marker species into disease-specific and disease-common clusters and revealed their distinct phylogenetic relationships; species in the CD-specific cluster were phylogenetically related, while those in the CRC-specific cluster were more distant. Strikingly, UC-specific species were phylogenetically closer to CRC, likely because UC patients have higher risk of CRC. Consistent with their phylogenetic relationships, marker species had similar within-cluster and different between-cluster metabolic preferences. A portion of marker species and pathways correlated with an indicator of leaky gut, suggesting a link between gut dysbiosis and human-derived contents. Marker species showed more coordinated changes and tighter inner-connections in cases than the controls, suggesting that the diseased gut may represent a stressed environment and pose stronger selection on gut microbes. With the marker species and pathways, we constructed four high-performance (including multidisease) models with an area under the receiver operating characteristic curve (AUROC) of 0.87 and true-positive rates up to 90%, and explained their putative clinical applications. We identified consistent microbial alterations in common intestinal diseases, revealed metabolic capacities and the relationships among marker bacteria in distinct states, and supported the feasibility of metagenome-derived multidisease diagnosis. IMPORTANCE Gut microbes have been identified as potential markers in distinguishing patients from controls in colorectal cancer, ulcerative colitis, and Crohn's disease individually, whereas there lacks a systematic analysis to investigate the exclusive microbial shifts of these enteropathies with similar clinical symptoms. Our meta-analysis and cross-disease comparisons identified consistent microbial alterations in each enteropathy, revealed microbial ecosystems among marker bacteria in distinct states, and demonstrated the necessity and feasibility of metagenome-based multidisease classifications. To the best of our knowledge, this is the first study to construct multi-class models for these common intestinal diseases.

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