Background: The choice of efficient antipsychotic therapy for schizophrenia relies on a time-consuming trial-and-error approach, whereas the social and economic burdens of the disease call for faster alternatives. Material & methods: In a search for predictive biomarkers of antipsychotic response, blood methylomes of 28 patients were analyzed before and 4 weeks into risperidone therapy. Results: Several CpGs exhibiting response-specific temporal dynamics were identified in otherwise temporally stable methylomes and noticeable global response-related differences were observed between good and bad responders. These were associated with genes involved in immunity, neurotransmission and neuronal development. Polymorphisms in many of these genes were previously linked with schizophrenia etiology and antipsychotic response. Conclusion: Antipsychotic response seems to be shaped by both stable and medication-induced methylation differences.
Keywords: antipsychotic; biomarker; epigenome; immunity; methylome; pharmaco-epigenetics; psychiatric disease.
The most common way to treat schizophrenia is antipsychotic medication. However, not all antipsychotics work for all patients. The only way to find a suitable antipsychotic is to prescribe one and wait, sometimes for months, to see if it works. Finding an alternative to this trial-and-error method would help reduce patient suffering and costs for healthcare systems. The idea is to look in the DNA of our blood cells for specific marks that can change in response to our lifestyle or health condition. These marks could help us predict how patients will react to the drug. In other words, they can serve as biomarkers of antipsychotic response. The current work examined the blood of schizophrenia patients before and 4 weeks after starting medication. The patients who did not respond well to the drug had different marks on the genes involved in immune defense and nervous system functioning. Some of these genes also play roles in the development of schizophrenia, whereas others can directly affect what happens to the drug in the patient's body. Although marks that predict how patients will react were not identified with certainty, valuable targets for future research were identified.