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Objective <p>To screen significantly differential metabolites between schizophrenia (SZ) patients and healthy controls using univariate analysis combined with orthogonal partial least squares discriminant analysis (OPLS-DA), and to provide experimental evidence for disease-related research.</p> Methods <p>Plasma samples were collected from 30 SZ patients and 30 healthy controls for untargeted metabolomics analysis. T-test together with OPLS-DA was applied to screen differential metabolites, and pathway enrichment analysis was performed to identify the core metabolic pathways involved.</p> Results <p>A total of 1,129 metabolites were identified by untargeted metabolomics. Using the thresholds of t-test <i>P</i> &lt; 0.05 and VIP &gt; 1.0(with false discovery rate &lt; 0.05), 237 significantly differential metabolites were screened out. Three-level chemical taxonomy annotation showed that differential metabolites were mainly enriched in lipids and lipid-like molecules, organic acids and derivatives, and organoheterocyclic compounds (collectively accounting for nearly 70%), with amino acids, peptides and analogues being the core subclass. MetPA and MSEA pathway enrichment analyses revealed that differential metabolites were predominantly enriched in amino acid metabolism (biosynthesis of amino acids, alanine, aspartate and glutamate metabolism, glycine, serine and threonine metabolism), energy metabolism (glycolysis and TCA cycle), and neurotransmitter-related pathways (GABAergic synapse).</p> Conclusion <p>Differential metabolites in the plasma of SZ patients are mainly concentrated in amino acid metabolism, energy metabolism, and neurotransmitter-related pathways. These findings suggest that SZ is associated with altered plasma metabolites, particularly in amino acid, energy, lipid, and neurotransmitter-related metabolic pathways. Further studies with larger cohorts and independent validation are needed before these metabolites can be considered candidate biomarkers.</p> Trial registration <p>Not applicable.</p>

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Untargeted metabolomics reveals plasma metabolic dysregulation in schizophrenia

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月24日

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  • Bing Han,
  • Baie Feng,
  • Yanyan Ge,
  • Tongyuan Wang,
  • Li Liu,
  • Peng Sun,
  • Xianzi Chu,
  • Yanfen Zhang,
  • Xinhong Du,
  • Feng Wang,
  • Tianqi Shen

摘要

Objective

To screen significantly differential metabolites between schizophrenia (SZ) patients and healthy controls using univariate analysis combined with orthogonal partial least squares discriminant analysis (OPLS-DA), and to provide experimental evidence for disease-related research.

Methods

Plasma samples were collected from 30 SZ patients and 30 healthy controls for untargeted metabolomics analysis. T-test together with OPLS-DA was applied to screen differential metabolites, and pathway enrichment analysis was performed to identify the core metabolic pathways involved.

Results

A total of 1,129 metabolites were identified by untargeted metabolomics. Using the thresholds of t-test P < 0.05 and VIP > 1.0(with false discovery rate < 0.05), 237 significantly differential metabolites were screened out. Three-level chemical taxonomy annotation showed that differential metabolites were mainly enriched in lipids and lipid-like molecules, organic acids and derivatives, and organoheterocyclic compounds (collectively accounting for nearly 70%), with amino acids, peptides and analogues being the core subclass. MetPA and MSEA pathway enrichment analyses revealed that differential metabolites were predominantly enriched in amino acid metabolism (biosynthesis of amino acids, alanine, aspartate and glutamate metabolism, glycine, serine and threonine metabolism), energy metabolism (glycolysis and TCA cycle), and neurotransmitter-related pathways (GABAergic synapse).

Conclusion

Differential metabolites in the plasma of SZ patients are mainly concentrated in amino acid metabolism, energy metabolism, and neurotransmitter-related pathways. These findings suggest that SZ is associated with altered plasma metabolites, particularly in amino acid, energy, lipid, and neurotransmitter-related metabolic pathways. Further studies with larger cohorts and independent validation are needed before these metabolites can be considered candidate biomarkers.

Trial registration

Not applicable.