Predicting relapse in schizophrenia: Is BDNF a plausible biological marker?
Publication/Presentation Date
3-1-2018
Abstract
Understanding the biological processes that underlie why patients relapse is an issue of fundamental importance to the detection and prevention of relapse in schizophrenia. Brain Derived Neurotrophic Factor (BDNF), a facilitator of brain plasticity, is reduced in patients with schizophrenia. In the present study, we examined whether decreases in plasma BDNF levels could be used as a biological predictor of relapse in schizophrenia. A total of 221 patients were prospectively evaluated for relapse over 30months in the Preventing Relapse in Schizophrenia: Oral Antipsychotics Compared to Injectables: eValuating Efficacy (PROACTIVE) study. Serial blood samples were collected at a maximum of 23 time points during the 30-month trial and BDNF levels were measured in plasma samples by ELISA. Receiver Operating Characteristic (ROC) curve analysis indicated that BDNF was not a significant predictor of relapse, hospitalization or exacerbation. Regardless of treatment group (oral second generation antipsychotic vs. long-acting injectable risperidone microspheres), baseline BDNF value did not differ significantly between those who experienced any of the adverse outcomes and those who did not. While contrary to the study hypothesis, these robust results offer little support for the use of plasma BDNF alone as a biomarker to predict relapse in schizophrenia.
Volume
193
First Page
263
Last Page
268
ISSN
1573-2509
Published In/Presented At
Pillai, A., Schooler, N. R., Peter, D., Looney, S. W., Goff, D. C., Kopelowicz, A., Lauriello, J., Manschreck, T., Mendelowitz, A., Miller, D. D., Severe, J. B., Wilson, D. R., Ames, D., Bustillo, J., Kane, J. M., & Buckley, P. F. (2018). Predicting relapse in schizophrenia: Is BDNF a plausible biological marker?. Schizophrenia research, 193, 263–268. https://doi.org/10.1016/j.schres.2017.06.059
Disciplines
Business Administration, Management, and Operations | Health and Medical Administration | Management Sciences and Quantitative Methods
PubMedID
28734907
Department(s)
Administration and Leadership
Document Type
Article