ISSN: 1449-1907International Journal of Medical Sciences
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Int J Med Sci 2018; 15(9):900-906. doi:10.7150/ijms.24346 This issue Cite
Research Paper
Assessment of a combination of Serum Proteins as potential biomarkers to clinically predict Schizophrenia
1. Department of Laboratory Medicine, Hunan Provincial People's Hospital, The first affiliated hospital of Hunan Normal University, Changsha, 410005, Hunan, China
2. Department of Biochemistry and Molecular Biology, Hunan University of Chinese Medicine, Changsha 410208, Hunan, China
3. Department of Laboratory Medicine, The Second Xiangya Hospital, Central South University, Changsha 410011, Hunan, China
4. Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Mental Health Institute of Central South University & Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China; China National Clinical Research Center on Mental Disorders (Xiangya) & China National Technology Institute on Mental Disorders, China.
Abstract
Schizophrenia (SZ) is a devastating psychiatric disorder. Validation of potential serum biomarkers during first-episode psychosis (FEP) is especially helpful to understand the onset and prognosis of this disorder. To address this question, we examined multiple blood biomarkers and assessed the efficacy to diagnose SZ. The expression levels of Neuregulin1 (NRG1), ErbB4, brain-derived neurotrophic factor (BDNF), DNA methyltransferases 1 (DNMT1) and ten-eleven translocation 1 (TET1) proteins in peripheral blood of 53 FEP patients and 57 healthy controls were determined by enzyme-linked immunosorbent assay (ELISA). Multivariable logistic regression including biomarker concentration as covariates was used to predict SZ. Differentiating performance of these five serum protein levels was analyzed by Receiver Operating Characteristic (ROC) curve analysis. We found that patients with SZ present a higher concentration of DNMT1, and TET1 in peripheral blood, but a lower concentration of NRG1, ErbB4 and BDNF than controls. Multivariable logistic regression showed that ErbB4, BDNF and TET1 were independent predictors of SZ, and when combined, provided high diagnostic accuracy for SZ. Together, our findings highlight that altered expression of NRG1, ErbB4, BDNF, DNMT1 and TET1 are involved in schizophrenia development and they may serve as potential biomarkers for the diagnosis of the schizophrenia. Therefore, our study provides evidence that combination of ErbB4, BDNF and TET1 biomarkers could greatly improve the diagnostic performance.
Keywords: Schizophrenia, biomarker, NRG1, ErbB4, BDNF, DNMT1, TET1
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