Potential Metabolite Markers of Schizophrenia
- UNCG Author/Contributor (non-UNCG co-authors, if there are any, appear on document)
- Wei Jia, Professor and Co-Director of the UNCG Center for Research Excellence in Bioactive Food Components (Creator)
- Yunping Qiu, Post Doctoral Fellow, Center for Research Excellence in Bioactive Food Components (Creator)
- Institution
- The University of North Carolina at Greensboro (UNCG )
- Web Site: http://library.uncg.edu/
Abstract: Schizophrenia is a severe mental disorder that affects 0.5–1% of the population worldwide. Current diagnostic methods are based on psychiatric interviews, which are subjective in nature. The lack of disease biomarkers to support objective laboratory tests has been a long-standing bottleneck in the clinical diagnosis and evaluation of schizophrenia. Here we report a global metabolic profiling study involving 112 schizophrenic patients and 110 healthy subjects, who were divided into a training set and a test set, designed to identify metabolite markers. A panel of serum markers consisting of glycerate, eicosenoic acid, ß-hydroxybutyrate, pyruvate and cystine was identified as an effective diagnostic tool, achieving an area under the receiver operating characteristic curve (AUC) of 0.945 in the training samples (62 patients and 62 controls) and 0.895 in the test samples (50 patients and 48 controls). Furthermore, a composite panel by the addition of urine ß-hydroxybutyrate to the serum panel achieved a more satisfactory accuracy, which reached an AUC of 1 in both the training set and the test set. Multiple fatty acids and ketone bodies were found significantly (P<0.01) elevated in both the serum and urine of patients, suggesting an upregulated fatty acid catabolism, presumably resulting from an insufficiency of glucose supply in the brains of schizophrenia patients.
Potential Metabolite Markers of Schizophrenia
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Created on 6/19/2012
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Additional Information
- Publication
- Molecular Psychiatry
- Language: English
- Date: 2011
- Keywords
- schizophrenia, biomarker, metaobonomics, GC-TOFMS, NMR