PDF(Pubmed)
Abstract：
BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impairments in social interaction and restricted and repetitive behaviors. Oxidative stress may be a critical link between mitochondrial dysfunction and ASD as reactive oxygen species (ROS) generated from pro-oxidant environmental toxicants and activated immune cells can result in mitochondrial failure. Recently, mitochondrial dysfunction, autoimmunity, and abnormal lipid mediators have been identified in multiple investigations as an acknowledged etiological mechanism of ASD that can be targeted for therapeutic intervention.
METHODS: The relationship between lipid mediator markers linked to inflammation induction, such as phospholipase A2/cyclooxygenase-2 (PLA2/Cox-2), and the mitochondrial dysfunction marker anti-mitochondrial antibodies (AMA-M2), and anti-histone autoantibodies in the etiology of ASD was investigated in this study using combined receiver operating characteristic (ROC) curve analyses. This study also sought to identify the linear combination for a given set of markers that optimizes the partial area under ROC curves. This study included 40 age- and sex-matched controls and 40 ASD youngsters. The plasma of both groups was tested for PLA2/COX-2, AMA-M2, and anti-histone autoantibodies\' levels using ELISA kits. ROC curves and logistic regression models were used in the statistical analysis.
RESULTS: Using the integrated ROC curve analysis, a notable rise in the area under the curve was noticed. Additionally, the combined markers had markedly improved specificity and sensitivity.
CONCLUSIONS: The current study suggested that measuring the predictive value of selected biomarkers related to mitochondrial dysfunction, autoimmunity, and lipid metabolism in children with ASD using a ROC curve analysis could lead to a better understanding of the etiological mechanism of ASD as well as its relationship with metabolism.
METHODS: The relationship between lipid mediator markers linked to inflammation induction, such as phospholipase A2/cyclooxygenase-2 (PLA2/Cox-2), and the mitochondrial dysfunction marker anti-mitochondrial antibodies (AMA-M2), and anti-histone autoantibodies in the etiology of ASD was investigated in this study using combined receiver operating characteristic (ROC) curve analyses. This study also sought to identify the linear combination for a given set of markers that optimizes the partial area under ROC curves. This study included 40 age- and sex-matched controls and 40 ASD youngsters. The plasma of both groups was tested for PLA2/COX-2, AMA-M2, and anti-histone autoantibodies\' levels using ELISA kits. ROC curves and logistic regression models were used in the statistical analysis.
RESULTS: Using the integrated ROC curve analysis, a notable rise in the area under the curve was noticed. Additionally, the combined markers had markedly improved specificity and sensitivity.
CONCLUSIONS: The current study suggested that measuring the predictive value of selected biomarkers related to mitochondrial dysfunction, autoimmunity, and lipid metabolism in children with ASD using a ROC curve analysis could lead to a better understanding of the etiological mechanism of ASD as well as its relationship with metabolism.
摘要：
背景：自闭症谱系障碍（ASD）是一种神经发育障碍，其特征是社交互动受损以及限制性和重复性行为。氧化应激可能是线粒体功能障碍与ASD之间的关键联系，因为由促氧化环境毒物和激活的免疫细胞产生的活性氧（ROS）可导致线粒体衰竭。最近,线粒体功能障碍，自身免疫,在多项研究中，异常脂质介质已被确定为ASD的公认病因机制，可作为治疗干预的目标。
方法：与炎症诱导相关的脂质介质标志物之间的关系，如磷脂酶A2/环氧合酶-2（PLA2/Cox-2），和线粒体功能障碍标记抗线粒体抗体（AMA-M2），在这项研究中，使用组合的受试者工作特征（ROC）曲线分析研究了ASD病因中的抗组蛋白自身抗体。该研究还试图鉴定一组给定标记的线性组合,其优化ROC曲线下的部分面积。这项研究包括40名年龄和性别匹配的对照和40名ASD青少年。使用ELISA试剂盒检测两组血浆的PLA2/COX-2、AMA-M2和抗组蛋白自身抗体水平。采用ROC曲线和logistic回归模型进行统计分析。
结果：使用综合ROC曲线分析，曲线下的面积显着上升。此外,联合标记物的特异性和敏感性明显提高.
结论：当前的研究表明，测量与线粒体功能障碍相关的选定生物标志物的预测价值，自身免疫,使用ROC曲线分析ASD儿童的脂质代谢可以更好地了解ASD的病因机制及其与代谢的关系。
方法：与炎症诱导相关的脂质介质标志物之间的关系，如磷脂酶A2/环氧合酶-2（PLA2/Cox-2），和线粒体功能障碍标记抗线粒体抗体（AMA-M2），在这项研究中，使用组合的受试者工作特征（ROC）曲线分析研究了ASD病因中的抗组蛋白自身抗体。该研究还试图鉴定一组给定标记的线性组合,其优化ROC曲线下的部分面积。这项研究包括40名年龄和性别匹配的对照和40名ASD青少年。使用ELISA试剂盒检测两组血浆的PLA2/COX-2、AMA-M2和抗组蛋白自身抗体水平。采用ROC曲线和logistic回归模型进行统计分析。
结果：使用综合ROC曲线分析，曲线下的面积显着上升。此外,联合标记物的特异性和敏感性明显提高.
结论：当前的研究表明，测量与线粒体功能障碍相关的选定生物标志物的预测价值，自身免疫,使用ROC曲线分析ASD儿童的脂质代谢可以更好地了解ASD的病因机制及其与代谢的关系。
