The Use of Multi-parametric Biomarker Profiles May Increase the Accuracy of ASD Prediction.

Effective biomarkers are urgently needed to facilitate early diagnosis of autism spectrum disorder (ASD), permitting early intervention, and consequently improving prognosis. In this study, we evaluate the usefulness of nine biomarkers and their association (combination) in predicting ASD onset and development. Data were analyzed using multiple independent mathematical and statistical approaches to verify the suitability of obtained results as predictive parameters. All biomarkers tested appeared useful in predicting ASD, particularly vitamin E, glutathione-S-transferase, and dopamine. Combining biomarkers into profiles improved the accuracy of ASD prediction but still failed to distinguish between participants with severe versus mild or moderate ASD. Library-based identification was effective in predicting the occurrence of disease. Due to the small sample size and wide participant age variation in this study, we conclude that the use of multi-parametric biomarker profiles directly related to autism phenotype may help predict the disease occurrence more accurately, but studies using larger, more age-homogeneous populations are needed to corroborate our findings.

A key role for an impaired detoxification mechanism in the etiology and severity of autism spectrum disorders.

BACKGROUND: Autism Spectrum Disorders (ASD) is a syndrome with a number of etiologies and different mechanisms that lead to abnormal development. The identification of autism biomarkers in patients with different degrees of clinical presentation (i.e., mild, moderate and severe) will give greater insight into the pathogenesis of this disease and will enable effective early diagnostic strategies and treatments for this disorder. METHODS: In this study, the concentration of two toxic heavy metals, lead (Pb) and mercury (Hg), were measured in red blood cells, while glutathione-s-transferase (GST) and vitamin E, as enzymatic and non-enzymatic antioxidants, respectively, were measured in the plasma of subgroups of autistic patients with different Social Responsiveness Scale (SRS) and Childhood Autism Rating Scale (CARS) scores. The results were compared to age- and gender-matched healthy controls. RESULTS: The obtained data showed that the patients with autism spectrum disorder had significantly higher Pb and Hg levels and lower GST activity and vitamin E concentrations compared with the controls. The levels of heavy metals (Hg and Pb), GST and vitamin E were correlated with the severity of the social and cognitive impairment measures (SRS and CARS). Receiver Operating Characteristics (ROC) analysis and predictiveness curves indicated that the four parameters show satisfactory sensitivity, very high specificity and excellent predictiveness. Multiple regression analyses confirmed that higher levels of Hg and Pb, together with lower levels of GST and vitamin E, can be used to predict social and cognitive impairment in patients with autism spectrum disorders. CONCLUSION: This study confirms earlier studies that implicate toxic metal accumulation as a consequence of impaired detoxification in autism and provides insight into the etiological mechanism of autism.

Association of social and cognitive impairment and biomarkers in autism spectrum disorders.

OBJECTIVES: The neurological basis for autism is still not fully understood, and the role of the interaction between neuro-inflammation and neurotransmission impairment needs to be clearer. This study aims to test the possible association between impaired levels of gamma aminobutyric acid (GABA), serotonin, dopamine, oxytocin, and interferon-γ-induced protein-16 (IFI16) and the severity of social and cognitive dysfunctions in individuals with autism spectrum disorders. MATERIALS AND METHODS: GABA, serotonin, dopamine, oxytocin, and IFI16 as biochemical parameters related to neurochemistry and inflammation were determined in the plasma of 52 Saudi autistic male patients, categorized as mild-moderate and severe as indicated by their Childhood Autism Rating Scale (CARS) or social responsiveness scale (SRS), and compared to 30 age- and gender-matched control samples. RESULTS: The data indicated that Saudi patients with autism have remarkably impaired plasma levels of the measured parameters compared to age and gender-matched controls. While serotonin in platelet-free plasma and dopamine did not correlated with the severity in social and cognitive dysfunction, GABA, oxytocin, and IFI16 were remarkably associated with the severity of both tested scores (SRS and CARS). CONCLUSIONS: The relationship between the selected parameters confirms the role of impaired neurochemistry and neuro-inflammation in the etiology of autism spectrum disorders and the possibility of using GABA, oxytocin, and IFI16 as markers of autism severity. Receiver operating characteristic analysis together with predictiveness diagrams proved that the measured parameters could be used as predictive biomarkers of clinical symptoms and provide significant guidance for future therapeutic strategy to re-establish physiological homeostasis.