The concept of “pre-autism” represents an innovation in the early diagnosis and management of autism spectrum disorder (ASD), emphasizing the importance of identifying subtle signs before the full clinical manifestation of the disorder. The study conducted by Al-Beltagi (2024) presents a comprehensive review of diagnostic strategies and interventions aimed at this preclinical phase, focusing on emerging biomarkers, diagnostic tools and challenges faced in clinical practice.
Methods and Tools
The article reviews advances in genetic markers, neuroimaging, biochemical biomarkers, and behavioral assessments. Genomic studies have identified genetic variants associated with ASD, including mutations in genes related to synaptic function and neuronal development. Neuroimaging techniques, such as functional magnetic resonance imaging (fMRI) and diffusion tensor imaging, have revealed atypical patterns of brain connectivity. Biochemical alterations, including metabolic profiles and markers of oxidative stress, have also been explored as potential diagnostic tools. In addition, the development of digital technologies, such as apps and wearable devices, offers scalable solutions for early screening.
Results and discussion
The findings highlight the heterogeneity of ASD, which requires individualized approaches to diagnosis and intervention. Integrating biomarkers with traditional screening tools may improve diagnostic sensitivity and specificity. However, the study cautions against overreliance on markers that have not yet been validated, emphasizing the need for comprehensive clinical assessments. Barriers to early detection, such as the lack of standardized screening programs and inequalities in access to specialized services, were widely discussed.
Clinical Implications and Future Research
Implementing culturally sensitive screening programs and collaboration between researchers and technology developers are essential to overcome current challenges. The author advocates prioritizing public policies that increase funding for biomarker research and the development of diagnostic tools. The creation of artificial intelligence-based algorithms using multimodal biomarkers is suggested as a promising strategy to improve early detection.
Conclusion
The study highlights the transformative potential of early detection and intervention in the course of ASD. Although significant challenges remain, integrating emerging biomarkers with traditional clinical approaches may improve developmental outcomes and quality of life for individuals on the autism spectrum.
Reference :
Al-Beltagi, M. (2024). Pre-autism: Advancing early identification and intervention in autism. World Journal of Clinical Cases, 12(34), 6748-6753. DOI: 10.12998/wjcc.v12.i34.6748
