Diagnostic model development for schizophrenia based on peripheral blood mononuclear cell subtype-specific expression of metabolic markers.
Jihan K ZakiSantiago G LagoNitin RustogiShiral S GangadinJiří BenáčekGeertje F van ReesFrieder HaenischJantine A BroekPaula Suarez-PinillaTillmann RulandBonnie AuyeungOlya MikovaNikolett KabacsVolker AroltSimon Baron-CohenBenedicto Crespo-FacorroHemmo A DrexhageLotje D de WitteRene S KahnIris E SommerSabine BahnJakub TomasikPublished in: Translational psychiatry (2022)
A significant proportion of the personal and economic burden of schizophrenia can be attributed to the late diagnosis or misdiagnosis of the disorder. A novel, objective diagnostic approaches could facilitate the early detection and treatment of schizophrenia and improve patient outcomes. In the present study, we aimed to identify robust schizophrenia-specific blood biomarkers, with the goal of developing an accurate diagnostic model. The levels of selected serum and peripheral blood mononuclear cell (PBMC) markers relevant to metabolic and immune function were measured in healthy controls (n = 26) and recent-onset schizophrenia patients (n = 36) using multiplexed immunoassays and flow cytometry. Analysis of covariance revealed significant upregulation of insulin receptor (IR) and fatty acid translocase (CD36) levels in T helper cells (F = 10.75, P = 0.002, Q = 0.024 and F = 21.58, P = 2.8 × 10<sup>-5</sup>, Q = 0.0004, respectively), as well as downregulation of glucose transporter 1 (GLUT1) expression in monocytes (F = 21.46, P = 2.9 × 10<sup>-5</sup>, Q = 0.0004). The most robust predictors, monocyte GLUT1 and T helper cell CD36, were used to develop a diagnostic model, which showed a leave-one-out cross-validated area under the receiver operating characteristic curve (AUC) of 0.78 (95% CI: 0.66-0.92). The diagnostic model was validated in two independent datasets. The model was able to distinguish first-onset, drug-naïve schizophrenia patients (n = 34) from healthy controls (n = 39) with an AUC of 0.75 (95% CI: 0.64-0.86), and also differentiated schizophrenia patients (n = 22) from patients with other neuropsychiatric conditions, including bipolar disorder, major depressive disorder and autism spectrum disorder (n = 68), with an AUC of 0.83 (95% CI: 0.75-0.92). These findings indicate that PBMC-derived biomarkers have the potential to support an accurate and objective differential diagnosis of schizophrenia.
Keyphrases
- bipolar disorder
- major depressive disorder
- peripheral blood
- end stage renal disease
- single cell
- ejection fraction
- newly diagnosed
- autism spectrum disorder
- chronic kidney disease
- poor prognosis
- prognostic factors
- type diabetes
- cell therapy
- dendritic cells
- stem cells
- immune response
- emergency department
- mass spectrometry
- metabolic syndrome
- flow cytometry
- adipose tissue
- peritoneal dialysis
- endothelial cells
- oxidative stress
- mesenchymal stem cells
- rna seq
- blood pressure
- blood glucose
- induced apoptosis
- patient reported
- attention deficit hyperactivity disorder
- pi k akt
- glycemic control
- adverse drug