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Diagnostic model development for schizophrenia based on peripheral blood mononuclear cell subtype-specific expression of metabolic markers.
Zaki, Jihan K; Lago, Santiago G; Rustogi, Nitin; Gangadin, Shiral S; Benacek, Jiri; van Rees, Geertje F; Haenisch, Frieder; Broek, Jantine A; Suarez-Pinilla, Paula; Ruland, Tillmann; Auyeung, Bonnie; Mikova, Olya; Kabacs, Nikolett; Arolt, Volker; Baron-Cohen, Simon; Crespo-Facorro, Benedicto; Drexhage, Hemmo A; de Witte, Lot D; Kahn, René S; Sommer, Iris E; Bahn, Sabine; Tomasik, Jakub.
Affiliation
  • Zaki JK; Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK.
  • Lago SG; Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK.
  • Rustogi N; Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK.
  • Gangadin SS; Department of Biomedical Sciences of Cells & Systems, University Medical Center Groningen (UMCG), University of Groningen, Groningen, The Netherlands.
  • Benacek J; Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK.
  • van Rees GF; Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK.
  • Haenisch F; Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK.
  • Broek JA; Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK.
  • Suarez-Pinilla P; Department of Psychiatry, Marqués de Valdecilla University Hospital, IDIVAL, School of Medicine, University of Cantabria, Santander, Spain.
  • Ruland T; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Santander, Spain.
  • Auyeung B; University Hospital Münster, Münster, Germany.
  • Mikova O; Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom.
  • Kabacs N; Foundation Biological Psychiatry, Sofia, Bulgaria.
  • Arolt V; Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, United Kingdom.
  • Baron-Cohen S; University Hospital Münster, Münster, Germany.
  • Crespo-Facorro B; Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom.
  • Drexhage HA; Department of Psychiatry, Marqués de Valdecilla University Hospital, IDIVAL, School of Medicine, University of Cantabria, Santander, Spain.
  • de Witte LD; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Santander, Spain.
  • Kahn RS; Department of Psychiatry, School of Medicine, University Hospital Virgen del Rocio, IBiS, Sevilla, Spain.
  • Sommer IE; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Sevilla, Spain.
  • Bahn S; Department of Immunology, Erasmus Medical Center, Rotterdam, The Netherlands.
  • Tomasik J; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Transl Psychiatry ; 12(1): 457, 2022 Oct 30.
Article in En | MEDLINE | ID: mdl-36310155
ABSTRACT
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 × 10-5, Q = 0.0004, respectively), as well as downregulation of glucose transporter 1 (GLUT1) expression in monocytes (F = 21.46, P = 2.9 × 10-5, 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.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Schizophrenia / Depressive Disorder, Major / Autism Spectrum Disorder Type of study: Diagnostic_studies / Prognostic_studies / Screening_studies Limits: Humans Language: En Journal: Transl Psychiatry Year: 2022 Type: Article Affiliation country: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Schizophrenia / Depressive Disorder, Major / Autism Spectrum Disorder Type of study: Diagnostic_studies / Prognostic_studies / Screening_studies Limits: Humans Language: En Journal: Transl Psychiatry Year: 2022 Type: Article Affiliation country: United kingdom