Evidence map›Paper›PMID 37553697›Full record

SynthesisMicrobiome2023

Identification of robust and generalizable biomarkers for microbiome-based stratification in lifestyle interventions.

Jiarui Chen, Sara Leal Siliceo, Yueqiong Ni, Henrik B Nielsen, Aimin Xu, Gianni Panagiotou

Open access · goldAbstract readVideo-Audio MediaMeta-Analysis
In one paragraph

Synthesis in Microbiome, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
4.5field-weighted citation impact, top 5% of its field
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

20 citing papers in PubMed, 29 citations in OpenAlex.

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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

6 authors at 4 institutions in 3 countries.

Jiarui Chen *Leibniz Institute for Natural Product Research and Infection Biology, Hans Knöll Institute -Microbiome Dynamics, Jena, Germany.
Sara Leal Siliceo *Leibniz Institute for Natural Product Research and Infection Biology, Hans Knöll Institute -Microbiome Dynamics, Jena, Germany.
Yueqiong NiLeibniz Institute for Natural Product Research and Infection Biology, Hans Knöll Institute -Microbiome Dynamics, Jena, Germany.
Henrik B NielsenClinical Microbiomics, Fruebjergvej 3, 2100, Copenhagen, Denmark.
Aimin XuState Key Laboratory of Pharmaceutical Biotechnology, The University of Hong Kong, Hong Kong S.A.R., China.
Gianni PanagiotouLeibniz Institute for Natural Product Research and Infection Biology, Hans Knöll Institute -Microbiome Dynamics, Jena, Germany. Gianni.Panagiotou@leibniz-hki.de.
Leibniz-Institut für Naturstoff-Forschung und Infektionsbiologie e. V. - Hans-Knöll-Institut (HKI) · DEChinese University of Hong Kong · HKClinical Microbiomics (Denmark) · DKUniversity of Hong Kong · HK

Funding

Marie Curie H2020-MSCA-ITN-2018
6 · The paper itself

Abstract

backgroundA growing body of evidence suggests that the gut microbiota is strongly linked to general human health. Microbiome-directed interventions, such as diet and exercise, are acknowledged as a viable and achievable strategy for preventing disorders and improving human health. However, due to the significant inter-individual diversity of the gut microbiota between subjects, lifestyle recommendations are expected to have distinct and highly variable impacts to the microbiome structure.

resultsHere, through a large-scale meta-analysis including 1448 shotgun metagenomics samples obtained longitudinally from 396 individuals during lifestyle studies, we revealed Bacteroides stercoris, Prevotella copri, and Bacteroides vulgatus as biomarkers of microbiota's resistance to structural changes, and aromatic and non-aromatic amino acid biosynthesis as important regulator of microbiome dynamics. We established criteria for distinguishing between significant compositional changes from normal microbiota fluctuation and classified individuals based on their level of response. We further developed a machine learning model for predicting "responders" and "non-responders" independently of the type of intervention with an area under the curve of up to 0.86 in external validation cohorts of different ethnicities.

conclusionsWe propose here that microbiome-based stratification is possible for identifying individuals with highly plastic or highly resistant microbial structures. Identifying subjects that will not respond to generalized lifestyle therapeutic interventions targeting the restructuring of gut microbiota is important to ensure that primary end-points of clinical studies are reached. Video Abstract.

Indexed as

Gastrointestinal MicrobiomeMicrobiotaBiomarkersDietHumansLife StyleBiomarkersGut microbiomeLifestyle interventionMachine learningMicrobiome dynamicsResistance

Identifiers

PMID37553697
PMCPMC10408196
OpenAlexW4385663270

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.