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Alteration of lipids and amino acids in plasma distinguish schizophrenia patients from controls: A targeted metabolomics study
Author(s) -
Liu Yiyun,
Song Xuemian,
Liu Xinyu,
Pu Juncai,
Gui Siwen,
Xu Shaohua,
Tian Lu,
Zhong Xiaogang,
Zhao Libo,
Wang Haiyang,
Liu Lanxiang,
Xu Guowang,
Xie Peng
Publication year - 2021
Publication title -
psychiatry and clinical neurosciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.609
H-Index - 74
eISSN - 1440-1819
pISSN - 1323-1316
DOI - 10.1111/pcn.13194
Subject(s) - metabolomics , receiver operating characteristic , metabolite , logistic regression , amino acid , schizophrenia (object oriented programming) , area under the curve , chemistry , medicine , chromatography , biochemistry , psychiatry
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.