Phenomics and Genomics in Clozapine Pharmacotherapy: Current, Former and New Clozapine Users

A burgeoning body of research has pointed to increased efficacy of clozapine (CLZ) over other antipsychotics in schizophrenia (SCZ). On the other hand, safety concerns likely cause underutilization across a range of European and other nations. The lack of data available to predict efficacy and adverse drug reactions (ADRs) of CLZ further contributes to underprescription rates in these countries. Here, we hypothesize that (epi)genetic and non-genetic factors aid to help predict treatment outcome (efficacy + ADRs) to CLZ. We furthermore posit that such prediction will result in enhanced quality of life of both patients and family members. Our primary objective is to predict CLZ treatment outcome based on phenotypic and genetic data obtained through the current design. The first secondary objective is to investigate which methylation levels/patterns are correlated with CLZ treatment outcome. The second secondary objective is to aid in the further elucidation of the genetic architecture of SCZ and any possible differences between 'regular' SCZ patients and those on CLZ, who are generally more severely ill. We thus intend to cover two currently unmet needs using a precision medicine approach: the lack of knowledge about determinants of treatment response to CLZ and the lack of insight into neurobiological differences between 'regular' SCZ and relatively treatment resistant subjects (CLZ users). The prime analysis will be a common variant hypothesis-generating genotyping endeavor investigating treatment response to CLZ. Additional analyses include whole-genome methylation and gene expression analyses and analyses of non-genetic determinants of response. We will include 2,500 CLZ treated patients for our discovery cohort, which is in line with previous whole-genome pharmacogenomics studies and our power calculations. We will replicate any genome-wide loci using our prospectively collected cohort of new users (N=59). Potential yields include a publicly available prediction tool to help identify patients responsive to CLZ in early disease stages and prevent harmful effects. In addition, common variant analyses compounded by pathway analyses may help elucidate the mechanisms of action of CLZ. We ask for broad informed consent from participants ensuring rich, longitudinal phenotypic and genotypic data resources for both currently planned and future analyses, allowing e.g. next-generation sequencing focused on both CLZ and SCZ disease genetics (e.g. in large consortia). We plan to also generate polygenic risk scores (PRS) of CLZ efficacy and use those to identify other diseases or patients for which CLZ may be helpful, e.g. schizoaffective disorder patients who are sometimes first treated with mood stabilizers. Last, evidence hints that disparaging genetic loci influence efficacy to different antipsychotics. Adding genetic data from our cohort to existing datasets of response to other antipsychotics may help identify such loci. Finally, comparison studies with non-CLZ using patients suffering from SCZ may deepen the understanding of biological mechanisms underlying treatment resistance (or: a relatively severe course of illness).The results of this genetic part of the study will be combined with the results from our other research protocol 'Phenomics and genomic of clozapine pharmacotherapy - New Users'.The overarching goal of both projects is to create a prediction model for clozapine outcome (response (and side effects). This model includes genetic, epigenetic and clinical data.