Publication Details

AFRICAN RESEARCH NEXUS

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medicine

Sialic acid and anti-ganglioside M1 antibodies are invaluable biomarkers correlated with the severity of autism spectrum disorder

Brain and Development, Volume 45, No. 4, Year 2023

Background: Autism spectrum disorders (ASD) are devastating neurodevelopmental disorders that showed global increased prevalence. They are characterized by impairment of social communication and stereotyped patterns. Objective: This study aimed at measuring the levels of total sialic acid (SA) and anti-ganglioside M1 (anti- GM1) IgG antibodies as essential biomarkers in a cohort of children with ASD to identify their diagnostic yield as well as their correlation with the severity of autistic behaviors. Methods: The demographic characteristics, anthropometric measurements, and clinical data were recorded. The levels of total plasma SA and serum anti-GM1 IgG antibodies levels were measured in 100 children with ASD and 100 healthy controls. The severity of ASD-related symptoms was assessed by using the Childhood Autism Rating Scale (CARS). Results: Children with ASD had significantly higher levels of both SA and anti-GM1 antibodies than healthy controls (p < 0.001). SA showed a statistically significant moderate diagnostic performance while anti-GM1 antibody showed a statistically significant high diagnostic in differentiating severe from mild to moderate autism. Moreover, both SA and anti-GM1 antibodies levels were significantly correlated to the severity of ASD symptoms (p < 0.001). Conclusion: The significantly increased levels of SA and anti-GM1 antibodies in children with ASD and their correlation with autism-related symptoms suggest their possible etiopathogenic role in autism as one of the pediatric autoimmune neuropsychiatric disorders. However, further large-scale studies are still needed to explore their possible bidirectional relationship as biomarkers for autism.
Statistics
Citations: 12
Authors: 12
Affiliations: 4
Identifiers
Research Areas
Disability
Maternal And Child Health
Study Design
Cross Sectional Study
Cohort Study