Gut Microbiome Wellness Index 2 enhances health status prediction from gut microbiome taxonomic profiles

Autor: Daniel Chang, Vinod K. Gupta, Benjamin Hur, Sergio Cobo-López, Kevin Y. Cunningham, Nam Soo Han, Insuk Lee, Vanessa L. Kronzer, Levi M. Teigen, Lioudmila V. Karnatovskaia, Erin E. Longbrake, John M. Davis, Heidi Nelson, Jaeyun Sung
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Nature Communications, Vol 15, Iss 1, Pp 1-14 (2024)
Druh dokumentu: article
ISSN: 2041-1723
DOI: 10.1038/s41467-024-51651-9
Popis: Abstract Recent advancements in translational gut microbiome research have revealed its crucial role in shaping predictive healthcare applications. Herein, we introduce the Gut Microbiome Wellness Index 2 (GMWI2), an enhanced version of our original GMWI prototype, designed as a standardized disease-agnostic health status indicator based on gut microbiome taxonomic profiles. Our analysis involves pooling existing 8069 stool shotgun metagenomes from 54 published studies across a global demographic landscape (spanning 26 countries and six continents) to identify gut taxonomic signals linked to disease presence or absence. GMWI2 achieves a cross-validation balanced accuracy of 80% in distinguishing healthy (no disease) from non-healthy (diseased) individuals and surpasses 90% accuracy for samples with higher confidence (i.e., outside the “reject option”). This performance exceeds that of the original GMWI model and traditional species-level α-diversity indices, indicating a more robust gut microbiome signature for differentiating between healthy and non-healthy phenotypes across multiple diseases. When assessed through inter-study validation and external validation cohorts, GMWI2 maintains an average accuracy of nearly 75%. Furthermore, by reevaluating previously published datasets, GMWI2 offers new insights into the effects of diet, antibiotic exposure, and fecal microbiota transplantation on gut health. Available as an open-source command-line tool, GMWI2 represents a timely, pivotal resource for evaluating health using an individual’s unique gut microbial composition.
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