There is large variation in schizophrenic patients to antipsychotic drugs response, leading to multiple trials to hit the desired response. Identification of biomarkers which predict response to antipsychotic drugs is of high importance since failed trials increase the treatment cost and also increase patients’ distress. However, the identification of reliable “genetic” biomarkers for this class of medications through clinical trials has been largely unsuccessful.
Schizophrenia risk genes have previously been reported to be among the predictors of clinical responses to antipsychotics, most genes reported to predict response to these drugs are related to synaptic transmission, calcium channels, pruning of synaptic spines, transcriptional factors or known antipsychotic drugs targets. An exome-sequencing study has demonstrated a polygenic burden of rare variants from these pathways which contributes to the risks for schizophrenia. These results suggest that some genes that contribute to risks of schizophrenia and its pathogenesis may also contribute to the mechanisms of action of antipsychotic drugs, however, there is no evidence that their contribution is greater than that of the non-risk genes.
In a recent research work published in the medical journal Schizophrenia Research, Dr. Jiang Li and Professor Herbert Y. Meltzer Director of the Translational Neuropharmacology Program at Northwestern University in Chicago in collaboration with Dr. Antony Loebel at Sunovion Pharmaceuticals Inc. conducted a meta-analysis on pharmacogenomics study with regard to response to Lurasidone by combining samples and including additional samples to identify genome wide significant (GWS) markers. Their study is considered the second largest study to identify predictors of antipsychotic response to a single antipsychotic drug.
The authors included data from a third lurasidone trial into a previous genome-wide association study (GWAS) based on two double-blind registration trials, which were not genome-wide significant (GWS), but which identified SNPs from four classes of genes as predictors of efficacy. After the inclusion of data from a third lurasidone trial, the authors observed that meta-analysis identified a GWS marker and other findings consistent with their first study. They found that the primary end-point was a change in Total Positive and Negative Syndrome Scale (PANSS) between baseline and last observation carried forward. The associations between PTPRD, NRG1, and MAGI1 previously reported to be related to response to lurasidone in the first two trials, showed a trend of significant association in the third trial
Their innovative research work yielded the first GWAS based GWS biomarker for Lurasidone response and additional support for the conclusion that genes related to synaptic biology and/or risk for schizophrenia are the strongest predictors of response to lurasidone in schizophrenia patients.
The study also showed that it is possible to identify functionally relevant biomarkers and/or potential drug targets for antipsychotic drugs, even with a relatively small sample. Their findings will advance further studies on biomarkers and/or potential drug targets for antipsychotic drugs.
Jiang Li, Antony Loebel, Herbert Y. Meltzer., Identifying the genetic risk factors for treatment response to lurasidone, by genome-wide association study (GWS): A meta-analysis of samples from three independent clinical trials. Schizophrenia Research 199 (2018) 203-213Go To Schizophrenia Research