Comparison of Physiological and Biochemical Autonomic Indices in Children with and without Autism Spectrum Disorders

Background and objectives: Autism Spectrum Disorder (ASD) is a complex neuro-developmental disorder and it has been suggested that symptoms of ASD are associated with neural networks that regulate the Autonomic Nervous System (ANS). However, the nature of autonomic atypicalities in ASDs remain largely unknown. Measures like Heart Rate Variability (HRV) and urinary Vanillylmandelic Acid (VMA) estimation are sensitive and non-invasive physiological and biochemical indicators of autonomic nervous activity. This study aimed to compare the physiological and biochemical autonomic indices in children with and without ASD. Materials and Methods: In this case-control study, 40 children with autism and 40 Typically Developing (TD) children were recruited. Measures of physiological autonomic index were assessed by the analysis of short term HRV, and the urinary levels of VMA estimation was used as a biochemical autonomic index. Results: Cardiac sympathetic activity assessed by Low Frequency (nu) of HRV was significantly higher in the ASD group in comparison with the TD group (p = 0.006). On the contrary, both the High Frequency (abs) and (nu) of HRV were found to be significantly lower in autistic children (p = 0.034 and p = 0.000) than controls. Autistic children also exhibited a significantly higher level (p = 0.049) of VMA concentration compared to TD children. Conclusion: The study concludes that children with ASD exhibit lower cardio-vagal activity as measured by HRV and increased sympathetic activity as assessed by urinary VMA compared to that of TD children. The core autistic symptoms exhibited by children with ASD could be due to the differences in baseline arousal or stress which might be associated with autonomic dysfunction. Further studies are needed to examine the association of this autonomic dysregulation with ASD symptoms and comorbidities

3rd National Conference on Image Processing, Computing, Communication, Networking and Data Analytics

This volume contains contributed articles presented in the conference NCICCNDA 2018, organized by the Department of Computer Science and Engineering, GSSS Institute of Engineering and Technology for Women, Mysore, Karnataka (India) on 28th April 2018