Genetic epidemiological pipeline identifies candidate markers of clozapine-induced metabolic dysfunction: implications for precision prescribing

Abstract

OBJECTIVES: Clozapine, the gold-standard antipsychotic for treatment-resistant schizophrenia causes severe metabolic complications, including metabolic syndrome and increased type 2 diabetes (T2D) risk. A better understanding of the genetic factors influencing clozapine pharmacokinetics and the associated metabolic risk could inform precision medicine approaches to clozapine prescribing. METHODS: Using a series of genetic-epidemiological approaches, we aimed to identify candidate biomarkers associated with clozapine-induced metabolic dysfunction. Mendelian randomisation (MR) was employed to investigate evidence of causal relationships between clozapine metabolism and cardiometabolic traits. RESULTS: Higher plasma clozapine and clozapine-norclozapine ratio were associated with a higher risk of T2D and blood pressure. The phenome-scan-colocalization-MR pipeline identified traits influenced by clozapine-metabolism loci that might serve as markers of cardiometabolic risk. This pipeline identified 28 colocalizing markers associated with clozapine pharmacokinetic loci. Subsequent MR highlighted associations for 16 of these 28 biomarker candidates with cardiometabolic outcomes, which included haematological markers and excretory traits. CONCLUSIONS: These findings are hypothesis-generating and do not, in the absence of prospective clinical validation, establish causal relationships between clozapine and the identified cardiometabolic traits. They may inform the development of biomarker-guided monitoring approaches for risk stratification and early intervention, enabling a shift from reactive monitoring to predictive approaches in managing clozapine-induced metabolic dysfunction with appropriate clinical validation.