Alteration of Lipids and Amino Acids in Plasma Distinguish Schizophrenia Patients from Controls: A Targeted Metabolomics Study
Abstract
BACKGROUND: Schizophrenia (SCZ) is a serious psychiatric disorder. Metabolite disturbance is an important pathogenic factor in schizophrenic patients. In this study, we aim to identify plasma lipid and amino acid biomarkers for SCZ using targeted metabolomics. METHODS: Plasma from 76 SCZ patients and 50 matched controls were analyzed using the LC/MS-based multiple reaction monitoring (MRM) metabolomics approach. A total of 182 targeted metabolites, including 22 amino acids and 160 lipids or lipid-related metabolites were observed. We used binary logistic regression analysis to determine whether the lipid and amino acid biomarkers could discriminate SCZ patients from controls. The area under the curve (AUC) from receiver operation characteristic (ROC) curve analysis was conducted to evaluate the diagnostic performance of the biomarkers panel. RESULTS: We identified 19 significantly differentially expressed metabolites between the SCZ patients and the controls (false discovery rate < 0.05), including one amino acid and 18 lipids or lipid-related metabolites. The binary logistic regression-selected panel showed good diagnostic performance in the drug-naïve group (AUC = 0.936) and all SCZ patients (AUC = 0.948), especially in the drug-treated group (AUC = 0.963). CONCLUSIONS: Plasma lipids and amino acids showed significant dysregulation in SCZ, which could effectively discriminate SCZ patients from controls. The LC/MS/MS-based approach provides reliable data for the objective diagnosis of SCZ.
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Nine studies evaluated broad panels of different lipid markers in patients with SCZ and detected statistical differences in fatty acyls, sterols, glycerolipids, sphingolipids, glycerophospholipids, and products of lipid metabolism.
“Nine studies evaluated the broad panels of different lipid markers in patients with SCZ [31,34,40,41,42,43,44,45,46] and detected statistical differences in the following lipid classes: fatty acyls, sterols, glycerolipids, sphingolipids, glycerophospholipids, and products of lipid metabolism.”
From Lipids in Psychiatric Disorders: Functional and Potential Diagnostic Role as Blood Biomarkers (2024) · cites this paper as [40]
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Lipids in Psychiatric Disorders: Functional and Potential Diagnostic Role as Blood Biomarkers
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- Authors
- Liu, Y., Song, X., Liu, X., Pu, J., Gui, S., Xu, S., Tian, L., Zhong, X., Zhao, L., Wang, H., Liu, L., Xu, G., & Xie, P.
- Affiliations
- Stomatological Hospital of Chongqing Medical University (CN)
- The Affiliated Yongchuan Hospital of Chongqing Medical University (CN)
- Dalian Institute of Chemical Physics (CN)
- Corresponding author
- Xu, Guowang
- Xie, Peng
- ORCID
- Venue
- Psychiatry and Clinical Neurosciences
- Publisher
- Wiley
- Published
- 2021-02-05
- Volume
- 75
- Issue
- 4
- Pages
- 138-144
- ISSN
- 1323-1316 (ISSN-L)
- 1440-1819
- OpenAlex
- W3120916036
- Cited by
- 48
- References
- 48
- Citations by year
- 2026: 8 · 2025: 8 · 2024: 12 · 2023: 5 · 2022: 9 · 2021: 6
- FWCI
- 2.51
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Psychiatry and Clinical Neurosciences (publishedVersion)
- PubMed (publishedVersion)
- Funders
- China Postdoctoral Science Foundation (2020M673160)
- National Key Research and Development Program of China (2017YFA 0505700)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
- Health Sciences › Medicine › Psychiatry and Mental health › Schizophrenia research and treatment
- Life Sciences › Neuroscience › Biological Psychiatry › Tryptophan and brain disorders
- Keywords
- schizophrenia, plasma lipids, plasma amino acids, metabolomic biomarkers, diagnostic biomarker panel, lipid dysregulation, plasma metabolite profiling, drug-naive patients
- MeSH terms
- Adult, Amino Acids, Chromatography, Liquid, Female, Humans, Lipids, Male, Middle Aged, Schizophrenia, Biomarkers, Tandem Mass Spectrometry, Metabolomics
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