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

Author

Listed:
  • Braden T. Tierney

    (Harvard Medical School
    Joslin Diabetes Center
    Joslin Diabetes Center
    Harvard Medical School)

  • Yingxuan Tan

    (Harvard Medical School)

  • Aleksandar D. Kostic

    (Joslin Diabetes Center
    Joslin Diabetes Center
    Harvard Medical School)

  • Chirag J. Patel

    (Harvard Medical School)

Abstract

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.

Suggested Citation

  • Braden T. Tierney & Yingxuan Tan & Aleksandar D. Kostic & Chirag J. Patel, 2021. "Gene-level metagenomic architectures across diseases yield high-resolution microbiome diagnostic indicators," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-23029-8
    DOI: 10.1038/s41467-021-23029-8
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    Cited by:

    1. JangKeun Kim & Braden T. Tierney & Eliah G. Overbey & Ezequiel Dantas & Matias Fuentealba & Jiwoon Park & S. Anand Narayanan & Fei Wu & Deena Najjar & Christopher R. Chin & Cem Meydan & Conor Loy & Be, 2024. "Single-cell multi-ome and immune profiles of the Inspiration4 crew reveal conserved, cell-type, and sex-specific responses to spaceflight," Nature Communications, Nature, vol. 15(1), pages 1-18, December.
    2. Braden T Tierney & Yingxuan Tan & Zhen Yang & Bing Shui & Michaela J Walker & Benjamin M Kent & Aleksandar D Kostic & Chirag J Patel, 2022. "Systematically assessing microbiome–disease associations identifies drivers of inconsistency in metagenomic research," PLOS Biology, Public Library of Science, vol. 20(3), pages 1-18, March.

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