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Transl Psychiatry. 2015 Jul 14;5:e601. doi: 10.1038/tp.2015.91.

Development of a blood-based molecular biomarker test for identification of schizophrenia before disease onset.

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Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK.
1] INSERM UMR 894, Centre of Psychiatry and Neurosciences, Lab Pathophysiology of Psychiatric Disorders, Institut de Psychiatrie (GDR 3557) Paris, France [2] University Paris Descartes, Sorbonne Paris Cité, Faculty of Medicine Paris Descartes, Service Hospitalo-Universitaire, Centre hospitalier Sainte-Anne, Paris, France.
Johns Hopkins University School of Medicine, Baltimore, MD, USA.
University of Muenster, Germany and Evangelisches Klinikum Niederrhein, Oberhausen, Germany.
Department of Psychiatry, University of Magdeburg, Magdeburg, Germany.
Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany.
Department of Neuroscience, Erasmus MC, Rotterdam, The Netherlands.
Walter Reed Army Institute of Research, Silver Spring, MD, USA.
CIBERSAM, University Hospital Marqués de Valdecilla, Department of Psychiatry, University of Cantabria - IDIVAL, Santander, Spain.
Myriad Genetic Laboratories, Inc., Salt Lake City, UT, USA.
1] Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK [2] Department of Neuroscience, Erasmus MC, Rotterdam, The Netherlands.


Recent research efforts have progressively shifted towards preventative psychiatry and prognostic identification of individuals before disease onset. We describe the development of a serum biomarker test for the identification of individuals at risk of developing schizophrenia based on multiplex immunoassay profiling analysis of 957 serum samples. First, we conducted a meta-analysis of five independent cohorts of 127 first-onset drug-naive schizophrenia patients and 204 controls. Using least absolute shrinkage and selection operator regression, we identified an optimal panel of 26 biomarkers that best discriminated patients and controls. Next, we successfully validated this biomarker panel using two independent validation cohorts of 93 patients and 88 controls, which yielded an area under the curve (AUC) of 0.97 (0.95-1.00) for schizophrenia detection. Finally, we tested its predictive performance for identifying patients before onset of psychosis using two cohorts of 445 pre-onset or at-risk individuals. The predictive performance achieved by the panel was excellent for identifying USA military personnel (AUC: 0.90 (0.86-0.95)) and help-seeking prodromal individuals (AUC: 0.82 (0.71-0.93)) who developed schizophrenia up to 2 years after baseline sampling. The performance increased further using the latter cohort following the incorporation of CAARMS (Comprehensive Assessment of At-Risk Mental State) positive subscale symptom scores into the model (AUC: 0.90 (0.82-0.98)). The current findings may represent the first successful step towards a test that could address the clinical need for early intervention in psychiatry. Further developments of a combined molecular/symptom-based test will aid clinicians in the identification of vulnerable patients early in the disease process, allowing more effective therapeutic intervention before overt disease onset.

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