Evidence map›Paper›PMID 32934239›Full record

ArticleNature communications2020

A predictive index for health status using species-level gut microbiome profiling.

Vinod K Gupta, Minsuk Kim, Utpal Bakshi, Kevin Y Cunningham, John M Davis, Konstantinos N Lazaridis, Heidi Nelson, Nicholas Chia, Jaeyun Sung

Abstract read
In one paragraph

Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 177 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
177citing papers in PubMed, 7 pooled it
–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

177 citing papers in PubMed, 7 syntheses or guidelines pooled it.

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  11. Gut Microbial Topology and Metabolic Signatures Associated With Colorectal Neoplasia.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
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117 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Vinod K GuptaMicrobiome Program, Center for Individualized Medicine, Mayo Clinic, Rochester, MN, 55905, USA.
Minsuk KimMicrobiome Program, Center for Individualized Medicine, Mayo Clinic, Rochester, MN, 55905, USA.ORCID http://orcid.org/0000-0001-9958-0380
Utpal BakshiMicrobiome Program, Center for Individualized Medicine, Mayo Clinic, Rochester, MN, 55905, USA.ORCID http://orcid.org/0000-0001-8421-9031
Kevin Y CunninghamGraduate Research Education Program (GREP), Mayo Clinic, Rochester, MN, 55905, USA.
John M DavisDivision of Rheumatology, Department of Medicine, Mayo Clinic, Rochester, MN, 55905, USA.
Konstantinos N LazaridisDivision of Gastroenterology and Hepatology, Mayo Clinic College of Medicine and Science, Rochester, MN, 55905, USA.ORCID http://orcid.org/0000-0002-0437-681X
Heidi NelsonEmeritus Chair, Department of Surgery, Mayo Clinic, Rochester, MN, 55905, USA.
Nicholas ChiaMicrobiome Program, Center for Individualized Medicine, Mayo Clinic, Rochester, MN, 55905, USA.ORCID http://orcid.org/0000-0001-9652-691X
Jaeyun SungMicrobiome Program, Center for Individualized Medicine, Mayo Clinic, Rochester, MN, 55905, USA. Sung.Jaeyun@mayo.edu.ORCID http://orcid.org/0000-0002-3005-2798

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Providing insight into one's health status from a gut microbiome sample is an important clinical goal in current human microbiome research. Herein, we introduce the Gut Microbiome Health Index (GMHI), a biologically-interpretable mathematical formula for predicting the likelihood of disease independent of the clinical diagnosis. GMHI is formulated upon 50 microbial species associated with healthy gut ecosystems. These species are identified through a multi-study, integrative analysis on 4347 human stool metagenomes from 34 published studies across healthy and 12 different nonhealthy conditions, i.e., disease or abnormal bodyweight. When demonstrated on our population-scale meta-dataset, GMHI is the most robust and consistent predictor of disease presence (or absence) compared to α-diversity indices. Validation on 679 samples from 9 additional studies results in a balanced accuracy of 73.7% in distinguishing healthy from non-healthy groups. Our findings suggest that gut taxonomic signatures can predict health status, and highlight how data sharing efforts can provide broadly applicable discoveries.

Indexed as

Gastrointestinal MicrobiomeHealth StatusBacteriaFecesHumansMetagenomeMicrobiota

Identifiers

PMID32934239
PMCPMC7492273

What OpenQuestion holds

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Registered trials

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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.