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Combining Anti-Mitochondrial Antibodies, Anti-Histone, and PLA2/COX Biomarkers to Increase Their Diagnostic Accuracy
Afaf El-Ansary1, Hanan A Alfawaz2, Abir Ben Bacha3
1Autism Center, Lotus Holistic Alternative Medical Center, Abu Dhabi P.O. Box 110281, United Arab Emirates.
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.
