Blood plasma proteomic modulation induced by olanzapine and risperidone in schizophrenia patients.

Abstract Antipsychotics are the main line of treatment for schizophrenia. Even though there are significant rates of medication drop out due to side effects and limited response of approximately 50% of patients. This is likely due to incomplete knowledge in how these drugs act at the molecular level. To improve treatment efficacy during the critical early stages of schizophrenia, we aimed to identify molecular signatures at baseline (T0) for prediction of a positive response to the atypical antipsychotics olanzapine and risperidone after 6 weeks (T6) treatment. Blood plasma samples were processed and analyzed by label-free quantitative shotgun proteomics using two-dimensional nano-liquid chromatography, coupled online to a Synapt G2-Si mass spectrometer. Data were obtained in MSE mode (data-independent acquisition) in combination with ion-mobility (HDMSE). We were able to identify a potential panel of proteins that might predict a positive outcome to olanzapine and risperidone treatment. The proteins found to be differentially abundant between T0 and T6 in good responders compared to poor responders were analyzed in silico for enrichment pathways and found to be mostly involved with immune system functions. This data can contribute to better understand of the biochemical signaling mechanisms peripherally triggered by antipsychotic medication and eventually used to develop surrogate biomarker tests to help improve treatment outcomes and guide development of new treatment approaches. Significance The application of proteomics to the study of the atypical antipsychotic effects on the blood plasma proteome from schizophrenia patients could help in the search for new targets to improve the current therapies, as well as in the development of new therapeutic strategies. In this original article, we provided clues that atypical antipsychotics might be associated with good response by modulating proteins that play a role in inflammation and/or immune system pathways. In addition, the proteins with differential abundance found in the comparison between good and poor responders at the baseline might compose a signature for prediction of response effectiveness.