Unbiased lipidomic profiling reveals metabolomic changes during the onset and antipsychotics treatment of schizophrenia disease

Introduction

Schizophrenia (SCH) is one of the most common psychiatric disorders, which involves impairments in motivation and cognition. The pathological mechanisms underlying SCH are still unknown, and no effective therapies can prevent or treat perfectly the cognitive impairments and deficit symptoms caused by SCH.

Objectives

We aimed to find the lipid expression change in plasma that underlie SCH onset and antipsychotics treatment.

Methods

We performed a data independent acquisition-based untargeted lipidomic approach on a quadrupole-time of flight liquid chromatography coupled to mass spectrometry platform. The plasma lipidomic profiles of SCH patients (n?=?20) pre- and post-antipsychotics treatment were acquired as well as healthy controls (n?=?29). Grouped or paired t-test were used to analyze the data.

Results

Over 1000 features were detected by our lipidomic analysis, of which 445 lipids belonging to 17 lipid species were reliably identified by tandem mass spectrometry. After statistical analysis, 47 lipids belonging to 9 lipid species were found to be dysregulated between naive SCH patients and healthy controls, and 50 lipids belonging to 9 lipid species were found to be dysregulated after antipsychotics treatment. These findings include several new SCH-relevant lipid species such as sphingomyelin, acylcarnitine and ceramide. Four types of lipid expression regulative patterns can be concluded from the above mentioned findings, revealing information about mechanism, side-effect and potential target of antipsychotics.

Conclusions

The work presented here have revealed several new lipid species which are significantly dysregulated in SCH disease development or antipsychotics treatment. These lipids provide new evidence for the pathological studies of SCH and new antipsychotics development, or can be considered as potentially candidate biomarkers for further validation.

     

Comprehensive plasma metabolomic and lipidomic analyses reveal potential biomarkers for heart failure

Heart failure is a syndrome with symptoms or signs caused by cardiac dysfunction. In clinic, four stages (A, B, C, and D) were used to describe heart failure progression. This study was aimed to explore plasma metabolomic and lipidomic profiles in different HF stages to identify potential biomarkers. Metabolomics and lipidomics were performed using plasma of heart failure patients at stages A (n?=?49), B (n?=?61), and C+D (n?=?26). Analysis of Variance (ANOVA) was used for screening dysregulated molecules. Bioinformatics was used to retrieve perturbed metabolic pathways. Univariate and multivariate receiver operating characteristic curve (ROC) analyses were used for potential biomarker screening. Stage A showed significant difference to other stages, and 142 dysregulated lipids and 134 dysregulated metabolites were found belonging to several metabolic pathways. Several marker panels were proposed for the diagnosis of heart failure stage A versus stage B-D. Several molecules, including lysophosphatidylcholine 18:2, cholesteryl ester 18:1, alanine, choline, and Fructose, were found correlated with B-type natriuretic peptide or left ventricular ejection fractions. In summary, using untargeted metabolomic and lipidomic profiling, several dysregulated small molecules were successfully identified between HF stages A and B-D. These molecules would provide valuable information for further pathological researches and biomarker development.