(Open access funding provided by Semmelweis University)
Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by
social and communication difficulties, along with repetitive behaviors. While genetic
factors play a significant role in ASD, the precise genetic landscape remains complex
and not fully understood, particularly in non-syndromic cases. The study performed
an in silico comparison of three genetic databases. ClinVar, SFARI Gene, and AutDB
were utilized to identify relevant gene subset and genetic variations associated with
non-syndromic ASD. Gene set enrichment analysis (GSEA) and protein–protein interaction
(PPI) network analysis were conducted to elucidate the biological significance of
the identified genes. The integrity of ASD-related gene subset and the distribution
of their variations were statistically assessed. A subset of twenty overlapping genes
potentially specific for non-syndromic ASD was identified. GSEA revealed enrichment
of biological processes related to neuronal development and differentiation, synaptic
function, and social skills, highlighting their importance in ASD pathogenesis. PPI
network analysis demonstrated functional relationships among the identified genes.
Analysis of genetic variations showed predominance of rare variants and database-specific
distribution patterns. The results provide valuable insights into the genetic landscape
of ASD and outline the genes and biological processes involved in the condition, while
taking into account that the study relied exclusively on in silico analyses, which
may be subject to biases inherent to database methodologies. Further research incorporating
multi-omics data and experimental validation is warranted to enhance our understanding
of non-syndromic ASD genetics and facilitate the development of targeted research,
interventions and therapies.
