A Metabolomics Study of Serum in Hospitalized Patients With Chronic Schizophrenia - Okamoto, Naomichi; Ikenouchi, Atsuko; Watanabe, Keita; Igata, Ryohei; Fujii, Rintaro; Yoshimura, Reiji (Frontiers in Psychiatry, 2021)
Purpose: Metabolomics is imperative to the discovery of biomarkers and mechanisms associated with pathophysiological processes. We investigated metabolome changes in hospitalized patients with schizophrenia compared to that in healthy controls, and examined the correlations between the metabolome and psychiatric symptoms. Patients and methods: Thirty patients with schizophrenia and 10 healthy controls participated in this study between September 2019 and June 2020. The mean duration of disease in patients with schizophrenia was 26 years. Clinical and neuropsychiatric symptoms of patients with schizophrenia were assessed using the Positive and Negative Syndrome Scale (PANSS). Metabolomics was conducted using capillary electrophoresis Fourier transform mass spectrometry, using serum samples from healthy controls and patients with schizophrenia. Metabolomics assigned a candidate compound to the 446 (cation 279, anion 167) peaks. Hierarchical cluster analysis, principal component analysis, logistic regression, receiver operating characteristic analysis, and linear regression analysis was used to analyze the metabolome changes, identifying the disease and the relationship between metabolome and psychiatric symptoms. Results: Hierarchical cluster analysis visually showed that approximately 60% of metabolomes had lower peak values in patients with schizophrenia than in healthy controls. Glutamate metabolism and the urea cycle had the highest proportions in the metabolome pathway, which decreased in patients with schizophrenia. Principal component analysis showed a clear separation between patients with schizophrenia and healthy controls in the first principal component (the contribution ratio of the first principal component was 15.9%). Logistic regression analysis suggested that the first principal component is a predictor of disease (odds=1.36, 95%CI= 1.11-1.67, p= 0.0032). We extracted the high factor loadings for the first principal component. γ-Glu-Val was significantly negatively correlated with PANSS total scores (r= -0.45, p= 0.012) and PANSS general scores (r= -0.49, p= 0.0055). γ-Glu-Phe was significantly negatively correlated with PANSS total score (r= -0.40, p= 0.031) and PANSS general score (r= -0.41, p= 0.025). Tetrahydrouridine was significantly and positively correlated with PANSS negative scores (r= 0.53, p= 0.0061). Conclusion: Metabolome changes in patients with chronic schizophrenia showed extensive and generalized declines. Glutamate metabolism and the urea cycle had the highest proportions in the metabolome pathway, which decreased in the schizophrenia group.