Clustering of patients with clinical risk of schizophrenia by platelet biochemical parameters topredict psychopharmacotherapy efficacy

A clinical-psychopathological and clinical-biochemical study was carried out in the Laboratory of Neurochemistry and the Department of Juvenile Psychiatry of the Mental Health Research Centre. Objective: to select platelet biochemical parameters for individual prediction of psychopharmacotherapy efficacy in patients with depression at high risk of schizophrenia. Material and Methods. The main group (n=54) included males aged 16-25 years, hospitalized with the first depressive episode (F32.1, F32.2, F32.38, F32.8 according to ICD-10) in the structure of which attenuated symptoms of schizophrenia were determined. The severity of psychopathological symptoms was assessed using the Hamilton Scale (HDRS-21) and the scale of prodromal symptoms (SOPS). The control group consisted of 25 healthy males aged 19-25 years. Biochemical signs - the activities of four platelet enzymes: cytochrome c-oxidase (COX), glutamate dehydrogenase (GDH), glutathione reductase (GR), and glutathione-S-transferase (GST) were determined in apparently healthy control group and in patients of the main group before and after treatment. Clustering the patients of the main group according to 4 normalized baseline (before the treatment) biochemical signs was performed using the kappa-means clustering algorithm with the number of clusters equal to 3. Results. Three clusters (K1, K2, K3) were obtained with 19, 18 and 17 patients, respectively. GDH and GR in the clusters differed significantly before and after the treatment, and GST - only before the treatment. The baseline signs in the clusters were significantly lower than the corresponding values in the control group (except for COX in all clusters, and GDH in K3). After the treatment course, various but significant changes in the signs’ values were observed in all clusters. The search for links of baseline biochemical signs with scores by psychometric scales after the treatment, as well as with changes in the scores as a result of the treatment, revealed significant correlations that differed in different clusters. Conclusion. Determination of the baseline biochemical signs and clustering of patients according to the selected signs can be validated to stratify patients of a heterogeneous group with a clinical risk of schizophrenia with the aim to predict treatment efficacy in the selected subgroups individually.