Cortese, Samuele, Bellato, Alessio, Gabellone, Alessandra, Marzulli, Lucia, Matera, Emilia, Parlatini, Valeria, Petruzelli, Maria Giuseppina, Persico, Antonio M., Delorme, Richard, Fusar-Poli, Paolo, Gosling, Corentin J., Solmi, Marco and Margari, Lucia (2025) Latest clinical frontiers related to autism diagnostic strategies. Cell Reports Medicine, 6 (2), [101916]. (doi:10.1016/j.xcrm.2024.101916).
Abstract
The diagnosis of autism is currently based on the developmental history, direct observation of behavior, reported symptoms, and scoring of rating scales/tools - which is influenced by the clinician’s knowledge and experience- with no established diagnostic biomarkers. A growing body of research has been conducted over the past decades to improve diagnostic accuracy. Here, we provide an overview of the current diagnostic assessment process as well as of recent and ongoing developments in terms of genetic evaluation, telemedicine, digital technologies, use of machine learning/artificial intelligence, and research on candidate diagnostic biomarkers. Genetic testing can effectively contribute to the diagnostic process, but caution is required when interpreting negative results and more work is needed to strengthen the transferability of genetic information into clinical practice. Digital diagnostic and machine learning-based approaches are emerging as promising approaches, but larger and more robust studies are needed. Finally, to date, there are no available diagnostic biomarkers. Moving forward, international collaborations may help develop multimodal datasets to identify biomarkers, ensure reproducibility, and support clinical translation.
More information
Identifiers
Catalogue record
Export record
Altmetrics
Contributors
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.