Mononuclear Cells of Peripheral Blood in vitro. A Model of Antipsychotic Therapy Personalization

Abstract

The implementation of a unified strategy for prescribing antipsychotics has proved to be an ineffective approach to the treatment of mentally ill patients. The study of the efficiency of pharmacological drugs on models mimicking the individual pathophysiology of the patient is one means of personalized (predictive) therapy. We evaluated the mRNA level for the genes of the neurotransmitters’ receptors (ADR1B, HRH1, HTR2А, DRD1, DRD2, DRD4, and DRD5). These are targets of antipsychotic drugs; therefore, they can be used as the probable biomarkers of the success of the treatment of mental illnesses of schizophrenic spectrum. We used peripheral blood mononuclear cells (PBMC) in vitro as the therapeutic model. The study included 108 patients with a proved diagnosis of schizophrenia spectrum disorders, receiving a haloperidol or olanzapine as a monotherapy. The patients were divided into two groups based on their response to the pharmacotherapy (effective or ineffective). The response was estimated with psychometric analysis performed on 28 ± 2 days of the treatment. In the group with ineffective therapy, the level of expression of the studied genes in PBMC in vitro had increased with the presence of the antipsychotic drug, while, in the group of patients with positive dynamics of mental status normalization, the analyzed level of expression remained virtually unchanged. The highest significant differences for patients with different responses on the pharmacological treatment were observed for the ADR1B and HRH1 genes in the case of olanzapine therapy (Р = 0.004 and 0.038, respectively) and for the HTR2A gene in the case of haloperidol therapy (Р = 0.039). At the same time, basic levels of gene expression in non-cultivated PBMC were not associated with the patient’s response to therapy. Thus, the mRNA level for genes of neurotransmission in PBMC in vitro in the presence of antipsychotics can be proposed as a biomarker for predicting the pharmacotherapy outcome for mentally ill patients.