Potential plasma biomarker panels identification for the diagnosis of first-episode schizophrenia and monitoring antipsychotic monotherapy with the use of metabolomics analyses

Abstract

Schizophrenia (SCZ) is a severe mental disorder. Using liquid chromatography mass spectrometry, we performed comprehensive metabolomics analyses of plasma samples from healthy controls (HC) and first episode SCZ patients before and after an acute period of medication. Ten lipid metabolites and 27 soluble small molecules were identified as potential biomarkers associated with the diagnosis and treatment of SCZ. These metabolites were significantly reduced in SCZ, and lipids and sulfate were significantly increased after treatment. Of the metabolites identified, four showed significant correlations with the Positive and Negative Syndrome Scale total scores. A biomarker panel composed of alpha-dimorphecolic, Phosphatidylcholine (PC) (16:0/18:1(11Z)), 1-methylnicotinamide, Phosphatidylethanolamine (PE) (20:2(11Z,14Z)/18:2(9Z,12Z)), sulfate, and L-tryptophan was selected to distinguish SCZ from HC; this provided the maximum classification performance with an AUC of 0.972. A biomarker panel including C16 sphinganine, gamma-linolenic acid, linoleic acid, PC(16:0/18:1(11Z)), PE(20:2(11Z,14Z)/18:2(9Z,12Z)), and sulfate, was selected for discrimination between SCZ before and after medication, and produced the optimal classification performance with an AUC of 0.905. Disturbances in lipid metabolism, sulfation modification, tryptophan metabolism, anti-inflammatory and antioxidant systems, and unsaturated fatty acids metabolism, were identified in SCZ. Our findings could facilitate the development of objective diagnostic or drug treatment monitoring tools for schizophrenia.