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Potential role of CSF cytokine profiles in discriminating infectious from non-infectious CNS disorders

机译:CSF细胞因子谱在区分感染性与非感染性中枢神经系统疾病中的潜在作用

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摘要

Current laboratory testing of cerebrospinal fluid (CSF) does not consistently discriminate between different central nervous system (CNS) disease states. Rapidly distinguishing CNS infections from other brain and spinal cord disorders that share a similar clinical presentation is critical. New approaches focusing on aspects of disease biology, such as immune response profiles that can have stimulus-specific attributes, may be helpful. We undertook this preliminary proof-of-concept study using multiplex ELISA to measure CSF cytokine levels in various CNS disorders (infections, autoimmune/demyelinating diseases, lymphomas, and gliomas) to determine the potential utility of cytokine patterns in differentiating CNS infections from other CNS diseases. Both agglomerative hierarchical clustering and mixture discriminant analyses revealed grouping of CNS disease types based on cytokine expression. To further investigate the ability of CSF cytokine levels to distinguish various CNS disease states, non-parametric statistical analysis was performed. Mann-Whitney test analysis demonstrated that CNS infections are characterized by significantly higher CSF lP-10/CXCL10 levels than the pooled non-infectious CNS disorders (p = 0.0001). Within the infection group, elevated levels of MDC/CCL22 distinguished non-viral from viral infections (p = 0.0048). Each disease group of the non-infectious CNS disorders independently showed IP-10/CXCL10 levels that are significantly lower than the infection group [(autoimmune /demyelinating disorders (p = 0.0005), lymphomas (p = 0.0487), gliomas (p = 0.0294), and controls (p = 0.0001)]. Additionally, of the non-infectious diseases, gliomas can be distinguished from lymphomas by higher levels of GRO/CXCL1 (p = 0.0476), IL-7 (p = 0.0119), and IL-8 (p = 0.0460). Gliomas can also be distinguished from autoimmune/demyelinating disorders by higher levels of GRO/CXCL1 (p = 0.0044), IL-7 (p = 0.0035) and IL-8 (p = 0.0176). Elevated CSF levels of PDGF-AA distinguish lymphomas from autoimmune/demyelinating cases (p = 0.0130). Interrogation of the above comparisons using receiver operator characteristic analysis demonstrated area under the curve (AUC) values (ranging from 0.8636–1.0) that signify good to excellent utility as potential diagnostic discriminators. In conclusion, our work indicates that upon formal validation, measurement of CSF cytokine levels may have clinical utility in both identifying a CNS disorder as infectious in etiology and, furthermore, in distinguishing viral from non-viral CNS infections.
机译:当前对脑脊液(CSF)的实验室测试不能始终如一地区分不同的中枢神经系统(CNS)疾病状态。将CNS感染与具有相似临床表现的其他脑部和脊髓疾病迅速区分开来至关重要。专注于疾病生物学方面的新方法,例如可以具有刺激特异性的免疫应答谱,可能会有所帮助。我们进行了这项初步的概念验证研究,使用多重ELISA来测量各种中枢神经系统疾病(感染,自身免疫/脱髓鞘疾病,淋巴瘤和神经胶质瘤)中的脑脊液细胞因子水平,以确定细胞因子模式在区分中枢神经系统感染与其他中枢神经系统感染方面的潜在用途疾病。聚集层次聚类分析和混合判别分析均显示基于细胞因子表达的中枢神经系统疾病类型分组。为了进一步研究脑脊液细胞因子水平区分各种中枢神经系统疾病状态的能力,进行了非参数统计分析。曼恩·惠特尼(Mann-Whitney)测试分析表明,与合并的非感染性CNS疾病相比,CNS感染的特点是CSF IP-10 / CXCL10水平明显更高(p = 0.0001)。在感染组中,MDC / CCL22水平升高将非病毒感染与病毒感染区分开(p = 0.0048)。非感染性CNS疾病的每个疾病组独立显示的IP-10 / CXCL10水平显着低于感染组[(自身免疫/脱髓鞘疾病(p = 0.0005),淋巴瘤(p = 0.0487),神经胶质瘤(p = 0.0294) )和对照组(p = 0.0001)]。此外,在非传染性疾病中,神经胶质瘤可以通过较高的GRO / CXCL1(p = 0.0476),IL-7(p = 0.0119)和IL来与淋巴瘤区分开。 -8(p = 0.0460)。神经胶质瘤也可以通过较高水平的GRO / CXCL1(p = 0.0044),IL-7(p = 0.0035)和IL-8(p = 0.0176)与自身免疫/脱髓鞘疾病区分开。 PDGF-AA的脑脊液水平将淋巴瘤与自身免疫/脱髓鞘病例(p = 0.0130)区分开来,使用接收者操作员特征分析对上述比较进行的询问表明曲线下面积(AUC)值(范围为0.8636–1.0)表明其好坏。最后,我们的工作表明,为了验证有效性,对CSF细胞因子水平的测量可能在确定中枢神经系统疾病在病因学上具有传染性,以及区分病毒与非病毒中枢神经系统感染方面均具有临床实用性。

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