Population-specific Prediction Models for Metabolic Syndrome and Treatment Response for Schizophrenia Spectrum Disorder Patients Using Clinical Data and Electronic Health Records

Schizophrenia spectrum disorder (SSD) patients exhibit higher prevalence of metabolic syndrome (MetS) compared to the general population, primarily attributed to antipsychotic use and lifestyle factors, with genetics remaining largely unassessed. Despite extensive research, clinical assessment of MetS in SSD patients remains inadequate, resulting in suboptimal risk estimation and treatment discontinuation. Our goal is to address this gap by developing population-specific prediction models for MetS and treatment response tailored for SSD patients. By leveraging thorough assessment of longitudinal clinical data, utilizing large-scale electronic health records, integrating genetics, and applying external validation, we aim to enhance risk assessment and management strategies of MetS and antipsychotic treatment response in SSD patients, ultimately improving health outcomes in this vulnerable population and providing further clarity of the molecular mechanisms underlying this comorbidity.