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

Mengjuan Xing; Hui Gao; Lili Yao; Li Wang; Chengfang Zhang; Liping Zhu; Donghong Cui

doi:10.3389/fendo.2023.1190954

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

Front Endocrinol (Lausanne). 2023 Jul 27:14:1190954. doi: 10.3389/fendo.2023.1190954. eCollection 2023.

Authors

Mengjuan Xing¹, Hui Gao², Lili Yao², Li Wang², Chengfang Zhang³, Liping Zhu¹, Donghong Cui^{1

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Affiliations

¹ Department of General Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University, School of Medicine, Shanghai, China.
² The First Minzheng Mental Health Center, Shanghai, China.
³ Shanghai Pudong New Area Mental Health Center, Tongji University School of Medicine, Shanghai, China.
⁴ Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University, School of Medicine, Shanghai, China.
⁵ Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai, China.

Abstract

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.

Keywords: 16S rRNA; dyslipidemia; intestinal microbiota; metabolic syndrome; schizophrenia; type 2 diabetes.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Gastrointestinal Microbiome* / genetics
Humans
Metabolic Syndrome* / diagnosis
Microbiota*
Phylogeny
Schizophrenia* / complications
Schizophrenia* / diagnosis

Grants and funding

National Natural Science Foundation of China, 81671336; Shanghai Science and Technology Innovation Action Plan Medical Innovation Research Special Project, 21Y11921200.