ArticleFrontiers in psychiatry2024
Unveiling the gut microbiota blueprint of schizophrenia: a multilevel omics approach.
Article in Frontiers in psychiatry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Gut Microbiota in Schizophrenia: Taxonomic Shifts, Beta- Diversity Alterations, and Biomarker Potential: A Systematic Review.International journal of molecular sciences · 2026Pooled it
- The Impact ofNutrients · 2025Trial
- Untargeted metabolomics reveals plasma metabolic dysregulation in schizophrenia.BMC psychiatry · 2026Article
- Can the Posterior Segment Findings of the Eye and Serum Microbiota Metabolites Be a Biomarker in Schizophrenia?Medicina (Kaunas, Lithuania) · 2026Article
- Mechanisms and clinical implications of gut-brain interactions.The Journal of clinical investigation · 2026Review
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Authors and funding
5 authors.
Funding
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Abstract
Background: Schizophrenia is a persistent incurable mental disorder and is characterized by the manifestation of negative emotions and behaviors with anxiety and depression, fear and insecurity, self-harm and social withdrawal. The intricate molecular mechanisms underlying this phenomenon remain largely elusive. Accumulating evidence points towards the gut microbiota exerting an influence on brain function via the gut-brain axis, potentially contributing to the development of schizophrenia. Therefore, the objective of this study is to delineate the gut microbial composition and metabolic profile of fecal samples from individuals with schizophrenia. Methods: Liquid chromatography-mass spectrometry (LC-MS) and 16S ribosomal RNA (16S rRNA) gene sequencing were employed to analyze fecal metabolites and gut microbiota profiles in a cohort of 29 patients diagnosed with schizophrenia and 30 normal controls. The microbial composition of fecal samples was determined through the 16S rRNA gene sequencing, and microbial α-diversity and β-diversity indices were calculated. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were performed to analyze the distribution of samples. The metabolites and gut microbiota exhibiting differential expression were identified through the application of biological variance criteria. Co-occurrence analysis of bacteria and metabolites was conducted using the spearman's rank correlation coefficient and visualized in a circular layout with the Cytoscape software. Results: The findings of the study indicated a lack of substantial evidence supporting significant disparities in α-diversity and β-diversity between individuals with schizophrenia and normal controls. In terms of metabolomics, a discernible pattern in sample distribution between the two groups was observed. Our analysis has revealed 30 bacterial species and 45 fecal metabolites that exhibited notable differences in abundance between individuals diagnosed with schizophrenia and normal controls. These alterations in multilevel omics have led to the development of a co-expression network associated with schizophrenia. The perturbed microbial genes and fecal metabolites consistently demonstrated associations with amino acid and lipid metabolism, which play essential roles in regulating the central nervous system. Conclusion: Our results offered profound insights into the impact of imbalanced gut microbiota and metabolism on brain function in individuals with schizophrenia.
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