NEW FRONTIERS IN AUTISM SPECTRUM DISORDER: DIAGNOSTIC INNOVATIONS, MULTIFACTORIAL ETIOLOGY AND FUNCTIONAL ADAPTATION

Abstract

Objective: To investigate the state of the art of Autism Spectrum Disorder (ASD), evaluating technological innovations in early diagnosis, the understanding of its multifactorial etiology, the clinical impact of associated comorbidities, and the transition of the therapeutic focus towards functional adaptation. Methodology: This is a systematic literature review focused on understanding how new technologies and a transdiagnostic approach redefine ASD management. The research was guided by the question: "How do predictive innovations and the integrated management of comorbidities impact early diagnosis and functional prognosis in Autism Spectrum Disorder?". The final sample consisted of 23 recently published scientific articles, critically analyzed for the construction of this collection. Results: The analysis demonstrated that ASD is a neurobiological continuum of complex etiology, where genetic vulnerability interacts strongly with environmental and epigenetic factors. Early diagnosis is being revolutionized by objective methods, such as Machine Learning algorithms and eye-tracking, which identify failures in social reward circuits before the consolidation of behavioral symptoms. Furthermore, it was found that comorbidities such as intellectual disability, anxiety disorders, and gastrointestinal disturbances are intrinsic to the disorder, requiring a Personalized Medicine approach. Conclusion: Clinical success in ASD transcends the reduction of atypical behaviors and is measured by the achievement of autonomy and activities of daily living. For technological and diagnostic innovations to reach their full potential, it is imperative to empower the family ecosystem, manage parental stress, and reduce sociocultural barriers, ensuring more assertive interventions and a better quality of life in adulthood.