Correlation of Neuroimaging Biomarkers and Pharmacogenetic Profiles in Optimizing Personalized Therapy in Children and Adolescents with Psychotic Disorders.

<b>Background/Objectives:</b> Psychotic disorders with childhood or adolescent onset pose major therapeutic challenges due to their complex etiology and variable treatment response. While pharmacogenetics and neuroimaging biomarkers have independently shown potential for guiding therapy, their combined utility remains underexplored. This study aimed to investigate whether integrating CYP2D6 pharmacogenetic profiles with structural neuroimaging findings can enhance personalized treatment and predict clinical outcomes in pediatric psychotic disorders. <b>Methods:</b> This prospective observational study included 63 children and adolescents (10-18 years) with DSM-5 diagnosed psychotic disorders. All patients underwent baseline MRI and standardized clinical assessments (PANSS, CGI, GAF). CYP2D6 genotyping was performed in 31 patients (49.2%), categorizing them as extensive (EMs) or intermediate metabolizers (IMs). Patients were treated with atypical antipsychotics and followed for 18 months. Outcomes included symptom severity, global functioning, and side-effect profiles. <b>Results:</b> EM patients demonstrated superior clinical improvement, as evidenced by a reduction in PANSS scores (from 118 to 40) and a corresponding increase in GAF scores (from 39 to 76), compared to the IM and non-tested groups. IM patients exhibited a higher prevalence of MRI abnormalities and slower response. Significant correlations emerged between CYP2D6 genotype, MRI findings, and treatment outcomes (<i>p</i> < 0.001). Combined biomarker profiles enhanced the prediction of therapeutic response and tolerability. <b>Conclusions:</b> Integrating CYP2D6 pharmacogenetic data with neuroimaging biomarkers provides valuable guidance for personalizing antipsychotic treatment in pediatric psychosis. This approach improves clinical outcomes and reduces adverse effects. Future research should further explore the integration of multimodal biomarkers in larger, longitudinal cohorts to optimize individualized psychiatric care for this vulnerable population.