4.8 Article

Gene-level metagenomic architectures across diseases yield high-resolution microbiome diagnostic indicators

Journal

NATURE COMMUNICATIONS
Volume 12, Issue 1, Pages -

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41467-021-23029-8

Keywords

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Funding

  1. National Institute of Diabetes and Digestive and Kidney Diseases [T32 DK110919, P30DK036836-30]
  2. National Science Foundation [1636870]
  3. National Institute of Allergy and Infectious Disease [R01AI127250]
  4. American Diabetes Association (ADA) Pathway to Stop Diabetes Initiator Award [1-17-INI-13]
  5. Smith Family Foundation Award for Excellence in Biomedical Research
  6. Direct For Computer & Info Scie & Enginr
  7. Office of Advanced Cyberinfrastructure (OAC) [1636870] Funding Source: National Science Foundation

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The study explores strain-specific and cross-disease associations in the microbiome across seven human diseases, finding gene-level signatures shared by coronary artery disease, inflammatory bowel diseases, and liver cirrhosis, as well as a distinct metagenomic signature for type 2 diabetes. Discrepancies are observed in the reported connection between Solobacterium moorei and colorectal cancer across models, but strain-specific gene associations are identified.
We propose microbiome disease architectures: linking >1 million microbial features (species, pathways, and genes) to 7 host phenotypes from 13 cohorts using a pipeline designed to identify associations that are robust to analytical model choice. Here, we quantify conservation and heterogeneity in microbiome-disease associations, using gene-level analysis to identify strain-specific, cross-disease, positive and negative associations. We find coronary artery disease, inflammatory bowel diseases, and liver cirrhosis to share gene-level signatures ascribed to the Streptococcus genus. Type 2 diabetes, by comparison, has a distinct metagenomic signature not linked to any one specific species or genus. We additionally find that at the species-level, the prior-reported connection between Solobacterium moorei and colorectal cancer is not consistently identified across models-however, our gene-level analysis unveils a group of robust, strain-specific gene associations. Finally, we validate our findings regarding colorectal cancer and inflammatory bowel diseases in independent cohorts and identify that features inversely associated with disease tend to be less reproducible than features enriched in disease. Overall, our work is not only a step towards gene-based, cross-disease microbiome diagnostic indicators, but it also illuminates the nuances of the genetic architecture of the human microbiome, including tension between gene- and species-level associations. Here, combing the massive gene-universe of the gut microbiome to identify strain-specific, cross-disease, associations across seven human diseases, the authors introduce the concept of microbiome architecture, defined as the complete set of positive and negative associations between microbial genes and human host disease, highlighting microbiome architectures as potential diagnostic indicators.

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