Evidence map›Paper›PMID 37873265›Full record

ArticlebioRxiv : the preprint server for biology2023

Gut Microbiome Wellness Index 2 for Enhanced Health Status Prediction from Gut Microbiome Taxonomic Profiles.

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 and 4 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors.

Daniel ChangDepartment of Computer Science and Engineering, University of Minnesota, Minneapolis, MN 55455, USA.
Vinod K GuptaMicrobiome Program, Center for Individualized Medicine, Mayo Clinic, Rochester, MN 55905, USA.
Benjamin HurMicrobiome Program, Center for Individualized Medicine, Mayo Clinic, Rochester, MN 55905, USA.
Sergio Cobo-LópezViral Information Institute, San Diego State University, San Diego, CA 92182, USA.
Kevin Y CunninghamBioinformatics and Computational Biology Program, University of Minnesota, Minneapolis, MN 55455, USA.
Nam Soo HanBrain Korea 21 Center for Bio-Health Industry, Department of Food Science and Biotechnology, Chungbuk National University, Cheongju, South Korea.
Insuk LeeDepartment of Biotechnology, Yonsei University, Seoul 03722, South Korea.
Vanessa L KronzerDivision of Rheumatology, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA.
Levi M TeigenDepartment of Food Science and Nutrition, University of Minnesota, St. Paul, MN 55108, USA.
Lioudmila V KarnatovskaiaDepartment of Pulmonary & Critical Care, Mayo Clinic, Rochester, MN 55905, USA.
Erin E LongbrakeDepartment of Neurology, Yale University, New Haven, CT 06510, USA.
John M DavisDivision of Rheumatology, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA.
Heidi NelsonEmeritus, Department of Surgery, Mayo Clinic, Rochester, MN 55905, USA.
Jaeyun SungMicrobiome Program, Center for Individualized Medicine, Mayo Clinic, Rochester, MN 55905, USA.

Funding

Mayo Clinic Center for Clinical and Translational Science (CCaTS UL1 Supplement - Dr. Timothy Curry)UL1TR002377 · NCATS · MAYO CLINIC ROCHESTER · PI VESNA D GAROVIC · 2017 to 2026
$78.4M
University of Minnesota Clinical and Translational Science Institute (UMN CTSI)UL1TR002494 · NCATS · UNIVERSITY OF MINNESOTA · PI BLAZAR, BRUCE R, WEISDORF, DANIEL J · 2018 to 2022
$34.9M
NCATS NIH HHS UL1 TR002377NCATS NIH HHS UL1 TR002494
6 · The paper itself

Abstract

Recent advancements in human gut microbiome research have revealed its crucial role in shaping innovative predictive healthcare applications. We introduce Gut Microbiome Wellness Index 2 (GMWI2), an advanced iteration of our original GMWI prototype, designed as a robust, disease-agnostic health status indicator based on gut microbiome taxonomic profiles. Our analysis involved pooling existing 8069 stool shotgun metagenome data across a global demographic landscape to effectively capture biological signals linking gut taxonomies to health. 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"). The enhanced classification accuracy of GMWI2 outperforms both the original GMWI model and traditional species-level α-diversity indices, suggesting a more reliable tool for differentiating between healthy and non-healthy phenotypes using gut microbiome data. Furthermore, by reevaluating and reinterpreting previously published data, GMWI2 provides fresh insights into the established understanding of how diet, antibiotic exposure, and fecal microbiota transplantation influence gut health. Looking ahead, GMWI2 represents a timely pivotal tool for evaluating health based on an individual's unique gut microbial composition, paving the way for the early screening of adverse gut health shifts. GMWI2 is offered as an open-source command-line tool, ensuring it is both accessible to and adaptable for researchers interested in the translational applications of human gut microbiome science.

Identifiers

PMID37873265
PMCPMC10592848

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.