Dataset Information

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

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.

SUBMITTER: Chang D

PROVIDER: S-EPMC11358288 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature

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

Chang Daniel D Gupta Vinod K VK Hur Benjamin B Cobo-López Sergio S Cunningham Kevin Y KY Han Nam Soo NS Lee Insuk I Kronzer Vanessa L VL Teigen Levi M LM Karnatovskaia Lioudmila V LV Longbrake Erin E EE Davis John M JM Nelson Heidi H Sung Jaeyun J

Nature communications 20240828 1

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 landsca ...[more]

PMID: 39198444

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Project description:Interest toward the human microbiome, particularly gut microbiome has flourished in recent decades owing to the rapidly advancing sequence-based screening and humanized gnotobiotic model in interrogating the dynamic operations of commensal microbiota. Although this field is still at a very preliminary stage, whereby the functional properties of the complex gut microbiome remain less understood, several promising findings have been documented and exhibit great potential toward revolutionizing disease etiology and medical treatments. In this review, the interactions between gut microbiota and the host have been focused on, to provide an overview of the role of gut microbiota and their unique metabolites in conferring host protection against invading pathogen, regulation of diverse host physiological functions including metabolism, development and homeostasis of immunity and the nervous system. We elaborate on how gut microbial imbalance (dysbiosis) may lead to dysfunction of host machineries, thereby contributing to pathogenesis and/or progression toward a broad spectrum of diseases. Some of the most notable diseases namely Clostridium difficile infection (infectious disease), inflammatory bowel disease (intestinal immune-mediated disease), celiac disease (multisystemic autoimmune disorder), obesity (metabolic disease), colorectal cancer, and autism spectrum disorder (neuropsychiatric disorder) have been discussed and delineated along with recent findings. Novel therapies derived from microbiome studies such as fecal microbiota transplantation, probiotic and prebiotics to target associated diseases have been reviewed to introduce the idea of how certain disease symptoms can be ameliorated through dysbiosis correction, thus revealing a new scientific approach toward disease treatment. Toward the end of this review, several research gaps and limitations have been described along with suggested future studies to overcome the current research lacunae. Despite the ongoing debate on whether gut microbiome plays a role in the above-mentioned diseases, we have in this review, gathered evidence showing a potentially far more complex link beyond the unidirectional cause-and-effect relationship between them.

Project description:BackgroundNurse researchers are well poised to study the connection of the microbiome to health and disease. Evaluating published microbiome results can assist with study design and hypothesis generation.ObjectivesThis article aims to present and define important analysis considerations in microbiome study planning and to identify genera shared across studies despite methodological differences. This methods article will highlight a workflow that the nurse scientist can use to combine and evaluate taxonomy tables for microbiome study or research proposal planning.MethodsWe compiled taxonomy tables from 13 published gut microbiome studies that had used Ion Torrent sequencing technology. We searched for studies that had amplified multiple hypervariable (V) regions of the 16S rRNA gene when sequencing the bacteria from healthy gut samples.ResultsWe obtained 15 taxonomy tables from the 13 studies, comprised of samples from four continents and eight V regions. Methodology among studies was highly variable, including differences in V regions amplified, geographic location, and population demographics. Nevertheless, of the 354 total genera identified from the 15 data sets, 25 were shared in all V regions and the four continents. When relative abundance differences across the V regions were compared, Dorea and Roseburia were statistically different. Taxonomy tables from Asian subjects had increased average abundances of Prevotella and lowered abundances of Bacteroides compared with the European, North American, and South American study subjects.DiscussionEvaluating taxonomy tables from previously published literature is essential for study planning. The genera found from different V regions and continents highlight geography and V region as important variables to consider in microbiome study design. The 25 shared genera across the various studies may represent genera commonly found in healthy gut microbiomes. Understanding the factors that may affect the results from a variety of microbiome studies will allow nurse scientists to plan research proposals in an informed manner. This work presents a valuable framework for future cross-study comparisons conducted across the globe.

Dataset Information

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

Publications

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

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