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Examining the Interaction of the Gut Microbiome with Host Metabolism and Cardiometabolic Health in Metabolic Syndrome

(1) Background: The microbiota-host cross-talk has been previously investigated, while its role in health is not yet clear. This study aimed to unravel the network of microbial-host interactions and correlate it with cardiometabolic risk factors. (2) Methods: A total of 47 adults with overweight/obe...

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Autores principales: Galié, Serena, Papandreou, Christopher, Arcelin, Pierre, Garcia, David, Palau-Galindo, Antoni, Gutiérrez-Tordera, Laia, Folch, Àlex, Bulló, Mònica
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8706982/
https://www.ncbi.nlm.nih.gov/pubmed/34959869
http://dx.doi.org/10.3390/nu13124318
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author Galié, Serena
Papandreou, Christopher
Arcelin, Pierre
Garcia, David
Palau-Galindo, Antoni
Gutiérrez-Tordera, Laia
Folch, Àlex
Bulló, Mònica
author_facet Galié, Serena
Papandreou, Christopher
Arcelin, Pierre
Garcia, David
Palau-Galindo, Antoni
Gutiérrez-Tordera, Laia
Folch, Àlex
Bulló, Mònica
author_sort Galié, Serena
collection PubMed
description (1) Background: The microbiota-host cross-talk has been previously investigated, while its role in health is not yet clear. This study aimed to unravel the network of microbial-host interactions and correlate it with cardiometabolic risk factors. (2) Methods: A total of 47 adults with overweight/obesity and metabolic syndrome from the METADIET study were included in this cross-sectional analysis. Microbiota composition (151 genera) was assessed by 16S rRNA sequencing, fecal (m = 203) and plasma (m = 373) metabolites were profiled. An unsupervised sparse generalized canonical correlation analysis was used to construct a network of microbiota-metabolite interactions. A multi-omics score was derived for each cluster of the network and associated with cardiometabolic risk factors. (3) Results: Five multi-omics clusters were identified. Thirty-one fecal metabolites formed these clusters and were correlated with plasma sphingomyelins, lysophospholipids and medium to long-chain acylcarnitines. Seven genera from Ruminococcaceae and a member from the Desulfovibrionaceae family were correlated with fecal and plasma metabolites. Positive correlations were found between the multi-omics scores from two clusters with cholesterol and triglycerides levels. (4) Conclusions: We identified a correlated network between specific microbial genera and fecal/plasma metabolites in an adult population with metabolic syndrome, suggesting an interplay between gut microbiota and host lipid metabolism on cardiometabolic health.
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spelling pubmed-87069822021-12-25 Examining the Interaction of the Gut Microbiome with Host Metabolism and Cardiometabolic Health in Metabolic Syndrome Galié, Serena Papandreou, Christopher Arcelin, Pierre Garcia, David Palau-Galindo, Antoni Gutiérrez-Tordera, Laia Folch, Àlex Bulló, Mònica Nutrients Article (1) Background: The microbiota-host cross-talk has been previously investigated, while its role in health is not yet clear. This study aimed to unravel the network of microbial-host interactions and correlate it with cardiometabolic risk factors. (2) Methods: A total of 47 adults with overweight/obesity and metabolic syndrome from the METADIET study were included in this cross-sectional analysis. Microbiota composition (151 genera) was assessed by 16S rRNA sequencing, fecal (m = 203) and plasma (m = 373) metabolites were profiled. An unsupervised sparse generalized canonical correlation analysis was used to construct a network of microbiota-metabolite interactions. A multi-omics score was derived for each cluster of the network and associated with cardiometabolic risk factors. (3) Results: Five multi-omics clusters were identified. Thirty-one fecal metabolites formed these clusters and were correlated with plasma sphingomyelins, lysophospholipids and medium to long-chain acylcarnitines. Seven genera from Ruminococcaceae and a member from the Desulfovibrionaceae family were correlated with fecal and plasma metabolites. Positive correlations were found between the multi-omics scores from two clusters with cholesterol and triglycerides levels. (4) Conclusions: We identified a correlated network between specific microbial genera and fecal/plasma metabolites in an adult population with metabolic syndrome, suggesting an interplay between gut microbiota and host lipid metabolism on cardiometabolic health. MDPI 2021-11-29 /pmc/articles/PMC8706982/ /pubmed/34959869 http://dx.doi.org/10.3390/nu13124318 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Galié, Serena
Papandreou, Christopher
Arcelin, Pierre
Garcia, David
Palau-Galindo, Antoni
Gutiérrez-Tordera, Laia
Folch, Àlex
Bulló, Mònica
Examining the Interaction of the Gut Microbiome with Host Metabolism and Cardiometabolic Health in Metabolic Syndrome
title Examining the Interaction of the Gut Microbiome with Host Metabolism and Cardiometabolic Health in Metabolic Syndrome
title_full Examining the Interaction of the Gut Microbiome with Host Metabolism and Cardiometabolic Health in Metabolic Syndrome
title_fullStr Examining the Interaction of the Gut Microbiome with Host Metabolism and Cardiometabolic Health in Metabolic Syndrome
title_full_unstemmed Examining the Interaction of the Gut Microbiome with Host Metabolism and Cardiometabolic Health in Metabolic Syndrome
title_short Examining the Interaction of the Gut Microbiome with Host Metabolism and Cardiometabolic Health in Metabolic Syndrome
title_sort examining the interaction of the gut microbiome with host metabolism and cardiometabolic health in metabolic syndrome
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8706982/
https://www.ncbi.nlm.nih.gov/pubmed/34959869
http://dx.doi.org/10.3390/nu13124318
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