To allow better diagnosis and management of psychiatric illnesses, the use of easily accessible biomarkers are proposed. Therefore, recognition of some diseases by a set of related pathogenesis biomarkers is a promising approach. The study aims to assess the usefulness of examining oxidative stress (OS) in schizophrenia as a potential biomarker of illness using the commonly used data mining decision tree method. The study group was comprised of 147 participants: 98 patients with schizophrenia (SZ group), and the control group (n = 49; HC). The patients with schizophrenia were divided into two groups: first-episode schizophrenia (n = 49; FS) and chronic schizophrenia (n = 49; CS). The assessment included the following biomarkers in sera of patients: catalase (CAT), glutathione peroxidase (GPx), superoxide dismutase-1 (SOD-1), glutathione reductase (GR), reduced glutathione (GSH), total antioxidant capacity (TAC), ferric reducing ability of plasma (FRAP), advanced glycation end products (AGEs), advanced oxidation protein products (AOPP), dityrosine (DITYR), kynurenine (KYN), N-formylkynurenine (NFK), tryptophan (TRY), total oxidant status (TOS), nitric oxide (NO) and total protein. Maximum accuracy (89.36%) for distinguishing SZ from HC was attained with TOS and GPx (cut-off points: 392.70 and 15.33). For differentiating between FS and CS, the most promising were KYN, AOPP, TAC and NO (100%; cut-off points: 721.20, 0.55, 64.76 and 2.59). To distinguish FS from HC, maximum accuracy was found for GSH and TOS (100%; cut-off points: 859.96 and 0.31), and in order to distinguish CS from HC, the most promising were GSH and TOS (100%; cut-off points: 0.26 and 343.28). Using redox biomarkers would be the most promising approach for discriminating patients with schizophrenia from healthy individuals and, in the future, could be used as an add-on marker to diagnose and/or respond to treatment.
Keywords: biomarkers; data mining; oxidative stress; redox biomarkers; schizophrenia.