Peripheral blood compounds in schizophrenia and major depressive disorder

Schizophrenia and major depressive disorder (MDD) have traditionally been considered distinct disorders, yet they share overlapping symptoms, including mood disturbances, apathy, and cognitive impairment. Increasing evidence points to shared biological mechanisms, particularly involving immune function, neuroplasticity, and energy metabolism. This thesis investigates alterations in peripheral blood markers across these domains, focusing on drug-naïve first-episode patients, the effects of psychotropic treatment, the efficacy of anti-inflammatory augmentation, and the potential utility of blood-based biomarkers for predicting outcomes and guiding treatment.
Three meta-analyses were conducted. The first showed that drug-naïve first-episode patients with schizophrenia or MDD exhibit alterations in neuroplasticity- and immune-related markers, with additional disturbances in glucose metabolism specific to schizophrenia. The second demonstrated that treatment tends to normalize neuroplasticity and immune alterations while worsening glucose regulation in schizophrenia. The third, a comprehensive analysis of 51 compounds in antipsychotic-naïve schizophrenia patients, confirmed widespread abnormalities at illness onset in neuroplasticity, immune function, and energy metabolism. Longitudinal analyses revealed improvements in neuroplasticity and immune markers following treatment, but further deterioration in energy metabolism.
Serum analyses from two large cohorts revealed shared metabolic alterations — elevated leptin and insulin levels — in both schizophrenia and MDD, particularly during active episodes. A population-based study linked higher body mass index and altered lipid profiles to psychotic-like experiences, suggesting that metabolic dysfunction may represent a broader vulnerability factor.
A meta-analysis of anti-inflammatory augmentation therapies showed beneficial effects, particularly in early illness and for negative symptoms. Finally, a machine learning study identified baseline markers of inflammation and endothelial function as predictors of negative symptom severity in schizophrenia six years later.
These findings support a biologically informed, cross-diagnostic approach to psychiatry and highlight the potential of blood-based biomarkers to guide personalized, mechanism-based care.