The purpose of this project is to combine multiple biological levels of information and their matching with the clinical phenotype and personal/family anamnesis of the single individual. In fact, by stratifying multiple levels of biomarkers, including behavioral (eye tracking), clinical and neuropsychological variables, parameters taken from transcriptomics (RNAseq), the goal is to identify a panel of intermediate biomarkers capable of (a) distinguishing autistic subjects from typically developing brothers/sisters, (b) to distinguish autistic subjects from typically developing subjects, (c) to stratify autistic patients into a limited number of homogeneous subgroups by physiopathology, in order to allow personalized pharmacology and improve their management clinic.
Early identification and diagnosis of autism spectrum disorder (ASD) is necessary to promote access to early treatment. Despite the high incidence, in Italy it is estimated that 1 in 77 children (age 7-9 years) (Narzisi et al., 2018), the diagnosis and the choice of rehabilitation treatment for patients with Autism Spectrum Disorder (ASD) are still based on clinical observation. In the absence of targeted pharmacological therapies, early surveillance and evaluation aimed at timely intervention represent the only successful strategy to reduce the severity of symptoms (Palomo R et al., 2006) and improve the quality of life of children affected by ASD and their families, thus also leading to a reduction in costs for the National Health Service (Ganz ML. 2007). However, compared to the great advances in neuroscience, the clinical management of autistic individuals is seriously lagging behind, and the disorder is often diagnosed after 3-4 years of age despite the presence of deficits starting from the very first months of life (Zwaigenbaum L et al. al., 2013). The aim of this project is to bridge the gap between research and clinic, thanks to the convergence of multiple biological and clinical data.