Abstract
BACKGROUND: Currently, the prevalence of autism spectrum disorder (ASD) is increasing, which widely spurs the interest in the molecular investigation. Thereby, a better understanding of the given disorder mechanisms is likely to be achieved. Bioinformatics suiting protein-protein interactions analysis via the application of high-throughput studies, such as protein array, is one of these achievements. MATERIALS AND METHODS: The gene expression data from Gene Expression Omnibus (GEO) database were downloaded, and the expression profile of patients with developmental delay and autistic features were analyzed via Cytoscape and its relevant plug-ins. RESULTS: Our findings indicated that EGFR, ACTB, RHOA, CALM1, MAPK1, and JUN genes as the hub-bottlenecks and their related terms could be important in ASD risk. In other words, any expression modification in these genes could trigger dysfunctions in the corresponding biological processes. CONCLUSION: We suggest that differentially expressed genes could be used as suitable targets for ASD after being validated.