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Profiles and diagnostic value of intestinal microbiota in schizophrenia patients with metabolic syndrome

AIMS/HYPOTHESIS: It is widely thought that the intestinal microbiota plays a significant role in the pathogenesis of metabolic disorders. However, the gut microbiota composition and characteristics of schizophrenia patients with metabolic syndrome (MetS) have been largely understudied. Herein, we in...

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Autores principales: Xing, Mengjuan, Gao, Hui, Yao, Lili, Wang, Li, Zhang, Chengfang, Zhu, Liping, Cui, Donghong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10415044/
https://www.ncbi.nlm.nih.gov/pubmed/37576972
http://dx.doi.org/10.3389/fendo.2023.1190954
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author Xing, Mengjuan
Gao, Hui
Yao, Lili
Wang, Li
Zhang, Chengfang
Zhu, Liping
Cui, Donghong
author_facet Xing, Mengjuan
Gao, Hui
Yao, Lili
Wang, Li
Zhang, Chengfang
Zhu, Liping
Cui, Donghong
author_sort Xing, Mengjuan
collection PubMed
description AIMS/HYPOTHESIS: It is widely thought that the intestinal microbiota plays a significant role in the pathogenesis of metabolic disorders. However, the gut microbiota composition and characteristics of schizophrenia patients with metabolic syndrome (MetS) have been largely understudied. Herein, we investigated the association between the metabolic status of mainland Chinese schizophrenia patients with MetS and the intestinal microbiome. METHODS: Fecal microbiota communities from 115 male schizophrenia patients (57 with MetS and 58 without MetS) were assessed by 16S ribosomal RNA gene sequencing. We assessed the variations of gut microbiome between both groups and explored potential associations between intestinal microbiota and parameters of MetS. In addition, the Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) based on the KEGG database was used to predict the function of intestinal microbiota. We also conducted Decision Tree Analysis to develop a diagnostic model for the MetS in patients with schizophrenia based on the composition of intestinal microbiota. RESULTS: The fecal microbial diversity significantly differed between groups with or without MetS (α-diversity (Shannon index and Simpson index): p=0.0155, p=0.0089; β-diversity: p=0.001). Moreover, the microbial composition was significantly different between the two groups, involving five phyla and 38 genera (p<0.05). In addition, a significant correlation was observed between the metabolic-related parameters and abundance of altered microbiota including HDL-c (r2 = 0.203, p=0.0005), GLU (r2 = 0.286, p=0.0005) and WC (r2 = 0.061, p=0.037). Furthermore, KEGG pathway analysis showed that 16 signaling pathways were significantly enriched between the two groups (p<0.05). Importantly, our diagnostic model based on five microorganisms established by decision tree analysis could effectively distinguish between patients with and without MetS (AUC = 0.94). CONCLUSIONS/INTERPRETATION: Our study established the compositional and functional characteristics of intestinal microbiota in schizophrenia patients with MetS. These new findings provide novel insights into a better understanding of this disease and provide the theoretical basis for implementing new interventional therapies in clinical practice.
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spelling pubmed-104150442023-08-11 Profiles and diagnostic value of intestinal microbiota in schizophrenia patients with metabolic syndrome Xing, Mengjuan Gao, Hui Yao, Lili Wang, Li Zhang, Chengfang Zhu, Liping Cui, Donghong Front Endocrinol (Lausanne) Endocrinology AIMS/HYPOTHESIS: It is widely thought that the intestinal microbiota plays a significant role in the pathogenesis of metabolic disorders. However, the gut microbiota composition and characteristics of schizophrenia patients with metabolic syndrome (MetS) have been largely understudied. Herein, we investigated the association between the metabolic status of mainland Chinese schizophrenia patients with MetS and the intestinal microbiome. METHODS: Fecal microbiota communities from 115 male schizophrenia patients (57 with MetS and 58 without MetS) were assessed by 16S ribosomal RNA gene sequencing. We assessed the variations of gut microbiome between both groups and explored potential associations between intestinal microbiota and parameters of MetS. In addition, the Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) based on the KEGG database was used to predict the function of intestinal microbiota. We also conducted Decision Tree Analysis to develop a diagnostic model for the MetS in patients with schizophrenia based on the composition of intestinal microbiota. RESULTS: The fecal microbial diversity significantly differed between groups with or without MetS (α-diversity (Shannon index and Simpson index): p=0.0155, p=0.0089; β-diversity: p=0.001). Moreover, the microbial composition was significantly different between the two groups, involving five phyla and 38 genera (p<0.05). In addition, a significant correlation was observed between the metabolic-related parameters and abundance of altered microbiota including HDL-c (r2 = 0.203, p=0.0005), GLU (r2 = 0.286, p=0.0005) and WC (r2 = 0.061, p=0.037). Furthermore, KEGG pathway analysis showed that 16 signaling pathways were significantly enriched between the two groups (p<0.05). Importantly, our diagnostic model based on five microorganisms established by decision tree analysis could effectively distinguish between patients with and without MetS (AUC = 0.94). CONCLUSIONS/INTERPRETATION: Our study established the compositional and functional characteristics of intestinal microbiota in schizophrenia patients with MetS. These new findings provide novel insights into a better understanding of this disease and provide the theoretical basis for implementing new interventional therapies in clinical practice. Frontiers Media S.A. 2023-07-27 /pmc/articles/PMC10415044/ /pubmed/37576972 http://dx.doi.org/10.3389/fendo.2023.1190954 Text en Copyright © 2023 Xing, Gao, Yao, Wang, Zhang, Zhu and Cui https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Endocrinology
Xing, Mengjuan
Gao, Hui
Yao, Lili
Wang, Li
Zhang, Chengfang
Zhu, Liping
Cui, Donghong
Profiles and diagnostic value of intestinal microbiota in schizophrenia patients with metabolic syndrome
title Profiles and diagnostic value of intestinal microbiota in schizophrenia patients with metabolic syndrome
title_full Profiles and diagnostic value of intestinal microbiota in schizophrenia patients with metabolic syndrome
title_fullStr Profiles and diagnostic value of intestinal microbiota in schizophrenia patients with metabolic syndrome
title_full_unstemmed Profiles and diagnostic value of intestinal microbiota in schizophrenia patients with metabolic syndrome
title_short Profiles and diagnostic value of intestinal microbiota in schizophrenia patients with metabolic syndrome
title_sort profiles and diagnostic value of intestinal microbiota in schizophrenia patients with metabolic syndrome
topic Endocrinology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10415044/
https://www.ncbi.nlm.nih.gov/pubmed/37576972
http://dx.doi.org/10.3389/fendo.2023.1190954
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