Yue Yingying, Jiang Haitang, Liu Rui, Yin Yingying, Zhang Yuqun, Liang Jinfeng, Li Shenghua, Wang Jun, Lu Jianxin, Geng Deqin, Wu Aiqin, Yuan Yonggui
Department of Psychosomatics and Psychiatry, ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, PR China.
Institute of Psychosomatics, Medical School of Southeast University, Nanjing, PR China.
Oncotarget. 2016 Aug 23;7(34):54329-54338. doi: 10.18632/oncotarget.11105.
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.
先前的研究表明,神经营养因子参与中风和抑郁症的发展。因此,我们研究了这些生物标志物作为中风后抑郁症(PSD)预测和鉴别模型的效用。招募了159名个体,包括PSD组、无抑郁症的中风患者(非PSD组)、重度抑郁症(MDD)组和正常对照组,并检测了血管内皮生长因子(VEGF)、血管内皮生长因子受体(VEGFR2)、胎盘生长因子(PIGF)、胰岛素样生长因子(IGF-1)和胰岛素样生长因子受体(IGF-1R)的蛋白质和mRNA表达水平。卡方检验用于评估分类变量,而非参数检验和单因素方差分析应用于一般特征、临床和生物学变化的连续变量。为了探讨这些因素在PSD中的预测和鉴别作用,计算了判别分析和受试者工作特征曲线。除VEGF浓度和IGF-1R mRNA外(分别为P = 0.776,P = 0.102),这四种神经营养因子在四组之间存在统计学差异(所有P < 0.05)。我们确定这些mRNA表达和蛋白质分析物对PSD组和非PSD组具有一般预测性能[曲线下面积(AUC):0.805,95%CI,0.704 - 0.907,P < 0.001]。重要的是,在区分PSD患者和MDD患者方面具有出色的预测性能(AUC:0.984,95%CI,0.964 - 1.000,P < 0.001)。这是第一项探索PSD患者神经营养因子家族变化的研究,结果有趣地表明,生物因子的蛋白质和mRNA表达组合可作为PSD的预测和鉴别模型。