Alpha-Synuclein, cyclooxygenase-2 and prostaglandins-EP2 receptors as neuroinflammatory biomarkers of autism spectrum disorders: Use of combined ROC curves to increase their diagnostic values

Manan Alhakbany,Sarah Al-Mazidi,Laila Al-Ayadhi,Hanan Qasem,Abeer Aldbass,Afaf El-Ansary,Ramesa Shafi Bhat

doi:10.1186/s12944-021-01578-7

Abstract

BackgroundAutism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impairments in social interaction and restricted and repetitive behaviors. Neuroinflammation and abnormal lipid mediators have been identified in multiple investigations as an acknowledged etiological mechanism of ASD that can be targeted for therapeutic intervention.MethodsIn this study, multiple regression and combined receiver operating characteristic (ROC) curve analyses were used to determine the relationship between the neuroinflammatory marker α-synuclein and lipid mediator markers related to inflammation induction, such as cyclooxygenase-2 and prostaglandin-EP2 receptors, in the etiology of ASD. Additionally, the study aimed to determine the linear combination that maximizes the partial area under ROC curves for a set of markers. Forty children with ASD and 40 age- and sex-matched controls were enrolled in the study. Using ELISA, the levels of α-synuclein, cyclo-oxygenase-2, and prostaglandin-EP2 receptors were measured in the plasma of both groups. Statistical analyses using ROC curves and multiple and logistic regression models were performed.ResultsA remarkable increase in the area under the curve was observed using combined ROC curve analyses. Moreover, higher specificity and sensitivity of the combined markers were reported.ConclusionsThe present study indicates that measurement of the predictive value of selected biomarkers related to neuroinflammation and lipid metabolism in children with ASD using a ROC curve analysis should lead to a better understanding of the etiological mechanism of ASD and its link with metabolism. This information may facilitate early diagnosis and intervention.

Highlights

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impairments in social interaction and restricted and repetitive behaviors
Abruzzo et al [5] highlighted the benefit of using receiver operating characteristic (ROC) curves as an excellent statistical tool for identifying adequately sensitive biomarkers and specific for early ASD diagnosis
The ASD diagnosis was confirmed in all subjects using the Autism Diagnostic Interview-Revised (ADI-R); the Autism Diagnostic Observation Schedule (ADOS); and the Developmental, Dimensional, and Diagnostic Interview (3DI) protocols

Summary

Introduction

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impairments in social interaction and restricted and repetitive behaviors. Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders It is characterized by impaired communication skills, deficits in social interaction, and restricted and stereotypic behaviors [1, 2]. Abruzzo et al [5] highlighted the benefit of using receiver operating characteristic (ROC) curves as an excellent statistical tool for identifying adequately sensitive biomarkers and specific for early ASD diagnosis. Their utility in the prediction, risk evaluation, and assessment of therapeutic interventions still requires further studies, ROC curves emphasize the most statistically significant differences between patients and controls. ROC curve analyses combining two distinct markers usually increased their specificity [7], suggesting that combining a panel of variables instead of a single variable may be of great value as a diagnostic tool

Methods

Results

Conclusion