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

TitleIdentification of robust and generalizable biomarkers for microbiome-based stratification in lifestyle interventions
Authors
KeywordsGut microbiome
Lifestyle intervention
Machine learning
Microbiome dynamics
Resistance
Issue Date8-Aug-2023
PublisherBioMed Central
Citation
Microbiome, 2023, v. 11, n. 1 How to Cite?
AbstractBackground A 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.Results Here, 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.Conclusions We 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.
Persistent Identifierhttp://hdl.handle.net/10722/338261
ISSN
2023 Impact Factor: 13.8
2023 SCImago Journal Rankings: 3.802
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorChen, JR-
dc.contributor.authorSiliceo, SL-
dc.contributor.authorNi, YQ-
dc.contributor.authorNielsen, HB-
dc.contributor.authorXu, AM-
dc.contributor.authorPanagiotou, G -
dc.date.accessioned2024-03-11T10:27:31Z-
dc.date.available2024-03-11T10:27:31Z-
dc.date.issued2023-08-08-
dc.identifier.citationMicrobiome, 2023, v. 11, n. 1-
dc.identifier.issn2049-2618-
dc.identifier.urihttp://hdl.handle.net/10722/338261-
dc.description.abstractBackground A 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.Results Here, 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.Conclusions We 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.-
dc.languageeng-
dc.publisherBioMed Central-
dc.relation.ispartofMicrobiome-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectGut microbiome-
dc.subjectLifestyle intervention-
dc.subjectMachine learning-
dc.subjectMicrobiome dynamics-
dc.subjectResistance-
dc.titleIdentification of robust and generalizable biomarkers for microbiome-based stratification in lifestyle interventions-
dc.typeArticle-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1186/s40168-023-01604-z-
dc.identifier.pmid37553697-
dc.identifier.scopuseid_2-s2.0-85167371654-
dc.identifier.volume11-
dc.identifier.issue1-
dc.identifier.eissn2049-2618-
dc.identifier.isiWOS:001044751100001-
dc.publisher.placeLONDON-
dc.identifier.issnl2049-2618-

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