The biological basis of autism spectrum disorders: evaluation of oxidative stress and erytrocyte membrane alterations

This case-control study involved a total of 29 autistic children (Au) aged 6 to 12 years, and 28 gender and age-matched typically developing children (TD). We evaluated a high number of peripheral oxidative stress parameters, erythrocyte and lymphocyte membrane functional features and membrane lipid composition of erythrocyte. Erythrocyte TBARS, Peroxiredoxin II, Protein Carbonyl Groups and urinary HEL and isoprostane levels were elevated in AU (confirming an imbalance of the redox status of Au); other oxidative stress markers or associated parameters (urinary 8-oxo-dG, plasma Total antioxidant capacity and plasma carbonyl groups, erythrocyte SOD and catalase activities) were unchanged, whilst peroxiredoxin I showed a trend of elevated levels in red blood cells of Au children. A very significant reduction of both erythrocyte and lymphocyte Na+, K+-ATPase activity (NKA), a reduction of erythrocyte membrane fluidity, a reduction of phospatydyl serine exposition on erythrocyte membranes, an alteration in erythrocyte fatty acid membrane profile (increase in MUFA and in ω6/ω3 ratio due to decrease in EPA and DHA) and a reduction of cholesterol content of erythrocyte membrane were found in Au compared to TD, without change in erythrocyte membrane sialic acid content and in lymphocyte membrane fluidity. Some Au clinical features appear to be correlated with these findings; in particular, hyperactivity score appears to be related with some parameters of the lipidomic profile and membrane fluidity, and ADOS and CARS score are inversely related to peroxiredoxin II levels. Oxidative stress and erythrocyte structural and functional alterations may play a role in the pathogenesis of Autism Spectrum Disorders and could be potentially utilized as peripheral biomarkers.

Non Invasive Tools for Early Detection of Autism Spectrum Disorders

Autism Spectrum Disorders (ASDs) describe a set of neurodevelopmental disorders. ASD represents a significant public health problem. Currently, ASDs are not diagnosed before the 2nd year of life but an early identification of ASDs would be crucial as interventions are much more effective than specific therapies starting in later childhood. To this aim, cheap an contact-less automatic approaches recently aroused great clinical interest. Among them, the cry and the movements of the newborn, both involving the central nervous system, are proposed as possible indicators of neurological disorders. This PhD work is a first step towards solving this challenging problem. An integrated system is presented enabling the recording of audio (crying) and video (movements) data of the newborn, their automatic analysis with innovative techniques for the extraction of clinically relevant parameters and their classification with data mining techniques. New robust algorithms were developed for the selection of the voiced parts of the cry signal, the estimation of acoustic parameters based on the wavelet transform and the analysis of the infant’s general movements (GMs) through a new body model for segmentation and 2D reconstruction. In addition to a thorough literature review this thesis presents the state of the art on these topics that shows that no studies exist concerning normative ranges for newborn infant cry in the first 6 months of life nor the correlation between cry and movements. Through the new automatic methods a population of control infants (“low-risk”, LR) was compared to a group of “high-risk” (HR) infants, i.e. siblings of children already diagnosed with ASD. A subset of LR infants clinically diagnosed as newborns with Typical Development (TD) and one affected by ASD were compared. The results show that the selected acoustic parameters allow good differentiation between the two groups. This result provides new perspectives both diagnostic and therapeutic.