In:
Psychiatry and Clinical Neurosciences, Wiley, Vol. 75, No. 4 ( 2021-04), p. 138-144
Abstract:
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.
Type of Medium:
Online Resource
ISSN:
1323-1316
,
1440-1819
Language:
English
Publisher:
Wiley
Publication Date:
2021
detail.hit.zdb_id:
2010264-1
