Cargando…

Towards a multi protein and mRNA expression of biological predictive and distinguish model for post stroke depression

Previous studies suggest that neurotrophic factors participate in the development of stroke and depression. So we investigated the utility of these biomarkers as predictive and distinguish model for post stroke depression (PSD). 159 individuals including PSD, stroke without depression (Non-PSD), maj...

Descripción completa

Detalles Bibliográficos
Autores principales: Yue, Yingying, Jiang, Haitang, Liu, Rui, Yin, Yingying, Zhang, Yuqun, Liang, Jinfeng, Li, Shenghua, Wang, Jun, Lu, Jianxin, Geng, Deqin, Wu, Aiqin, Yuan, Yonggui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5342345/
https://www.ncbi.nlm.nih.gov/pubmed/27527872
http://dx.doi.org/10.18632/oncotarget.11105
_version_ 1782513157936250880
author Yue, Yingying
Jiang, Haitang
Liu, Rui
Yin, Yingying
Zhang, Yuqun
Liang, Jinfeng
Li, Shenghua
Wang, Jun
Lu, Jianxin
Geng, Deqin
Wu, Aiqin
Yuan, Yonggui
author_facet Yue, Yingying
Jiang, Haitang
Liu, Rui
Yin, Yingying
Zhang, Yuqun
Liang, Jinfeng
Li, Shenghua
Wang, Jun
Lu, Jianxin
Geng, Deqin
Wu, Aiqin
Yuan, Yonggui
author_sort Yue, Yingying
collection PubMed
description Previous studies suggest that neurotrophic factors participate in the development of stroke and depression. So we investigated the utility of these biomarkers as predictive and distinguish model for post stroke depression (PSD). 159 individuals including PSD, stroke without depression (Non-PSD), major depressive disorder (MDD) and normal control groups were recruited and examined the protein and mRNA expression levels of vascular endothelial growth factor (VEGF), vascular endothelial growth factor receptors (VEGFR2), placental growth factor (PIGF), insulin-like growth factor (IGF-1) and insulin-like growth factor receptors (IGF-1R). The chi-square test was used to evaluate categorical variable, while nonparametric test and one-way analysis of variance were applied to continuous variables of general characteristics, clinical and biological changes. In order to explore the predictive and distinguish role of these factors in PSD, discriminant analysis and receiver operating characteristic curve were calculated. The four groups had statistical differences in these neurotrophic factors (all P < 0.05) except VEGF concentration and IGF-1R mRNA (P = 0.776, P = 0.102 respectively). We identified these mRNA expression and protein analytes with general predictive performance for PSD and Non-PSD groups [area under the curve (AUC): 0.805, 95% CI, 0.704-0.907, P < 0.001]. Importantly, there is an excellent predictive performance (AUC: 0.984, 95% CI, 0.964-1.000, P < 0.001) to differentiate PSD patients from MDD patients. This was the first study to explore the changes of neurotrophic factors family in PSD patients, the results intriguingly demonstrated that the combination of protein and mRNA expression of biological factors could use as a predictive and discriminant model for PSD.
format Online
Article
Text
id pubmed-5342345
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher Impact Journals LLC
record_format MEDLINE/PubMed
spelling pubmed-53423452017-03-22 Towards a multi protein and mRNA expression of biological predictive and distinguish model for post stroke depression Yue, Yingying Jiang, Haitang Liu, Rui Yin, Yingying Zhang, Yuqun Liang, Jinfeng Li, Shenghua Wang, Jun Lu, Jianxin Geng, Deqin Wu, Aiqin Yuan, Yonggui Oncotarget Research Paper: Pathology Previous studies suggest that neurotrophic factors participate in the development of stroke and depression. So we investigated the utility of these biomarkers as predictive and distinguish model for post stroke depression (PSD). 159 individuals including PSD, stroke without depression (Non-PSD), major depressive disorder (MDD) and normal control groups were recruited and examined the protein and mRNA expression levels of vascular endothelial growth factor (VEGF), vascular endothelial growth factor receptors (VEGFR2), placental growth factor (PIGF), insulin-like growth factor (IGF-1) and insulin-like growth factor receptors (IGF-1R). The chi-square test was used to evaluate categorical variable, while nonparametric test and one-way analysis of variance were applied to continuous variables of general characteristics, clinical and biological changes. In order to explore the predictive and distinguish role of these factors in PSD, discriminant analysis and receiver operating characteristic curve were calculated. The four groups had statistical differences in these neurotrophic factors (all P < 0.05) except VEGF concentration and IGF-1R mRNA (P = 0.776, P = 0.102 respectively). We identified these mRNA expression and protein analytes with general predictive performance for PSD and Non-PSD groups [area under the curve (AUC): 0.805, 95% CI, 0.704-0.907, P < 0.001]. Importantly, there is an excellent predictive performance (AUC: 0.984, 95% CI, 0.964-1.000, P < 0.001) to differentiate PSD patients from MDD patients. This was the first study to explore the changes of neurotrophic factors family in PSD patients, the results intriguingly demonstrated that the combination of protein and mRNA expression of biological factors could use as a predictive and discriminant model for PSD. Impact Journals LLC 2016-08-05 /pmc/articles/PMC5342345/ /pubmed/27527872 http://dx.doi.org/10.18632/oncotarget.11105 Text en Copyright: © 2016 Yue et al. http://creativecommons.org/licenses/by/2.5/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper: Pathology
Yue, Yingying
Jiang, Haitang
Liu, Rui
Yin, Yingying
Zhang, Yuqun
Liang, Jinfeng
Li, Shenghua
Wang, Jun
Lu, Jianxin
Geng, Deqin
Wu, Aiqin
Yuan, Yonggui
Towards a multi protein and mRNA expression of biological predictive and distinguish model for post stroke depression
title Towards a multi protein and mRNA expression of biological predictive and distinguish model for post stroke depression
title_full Towards a multi protein and mRNA expression of biological predictive and distinguish model for post stroke depression
title_fullStr Towards a multi protein and mRNA expression of biological predictive and distinguish model for post stroke depression
title_full_unstemmed Towards a multi protein and mRNA expression of biological predictive and distinguish model for post stroke depression
title_short Towards a multi protein and mRNA expression of biological predictive and distinguish model for post stroke depression
title_sort towards a multi protein and mrna expression of biological predictive and distinguish model for post stroke depression
topic Research Paper: Pathology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5342345/
https://www.ncbi.nlm.nih.gov/pubmed/27527872
http://dx.doi.org/10.18632/oncotarget.11105
work_keys_str_mv AT yueyingying towardsamultiproteinandmrnaexpressionofbiologicalpredictiveanddistinguishmodelforpoststrokedepression
AT jianghaitang towardsamultiproteinandmrnaexpressionofbiologicalpredictiveanddistinguishmodelforpoststrokedepression
AT liurui towardsamultiproteinandmrnaexpressionofbiologicalpredictiveanddistinguishmodelforpoststrokedepression
AT yinyingying towardsamultiproteinandmrnaexpressionofbiologicalpredictiveanddistinguishmodelforpoststrokedepression
AT zhangyuqun towardsamultiproteinandmrnaexpressionofbiologicalpredictiveanddistinguishmodelforpoststrokedepression
AT liangjinfeng towardsamultiproteinandmrnaexpressionofbiologicalpredictiveanddistinguishmodelforpoststrokedepression
AT lishenghua towardsamultiproteinandmrnaexpressionofbiologicalpredictiveanddistinguishmodelforpoststrokedepression
AT wangjun towardsamultiproteinandmrnaexpressionofbiologicalpredictiveanddistinguishmodelforpoststrokedepression
AT lujianxin towardsamultiproteinandmrnaexpressionofbiologicalpredictiveanddistinguishmodelforpoststrokedepression
AT gengdeqin towardsamultiproteinandmrnaexpressionofbiologicalpredictiveanddistinguishmodelforpoststrokedepression
AT wuaiqin towardsamultiproteinandmrnaexpressionofbiologicalpredictiveanddistinguishmodelforpoststrokedepression
AT yuanyonggui towardsamultiproteinandmrnaexpressionofbiologicalpredictiveanddistinguishmodelforpoststrokedepression