Abstract
Autism Spectrum Disorders (ASD) are complex and genetically heterogeneous neurodevelopmental conditions. Although alternative splicing (AS) has emerged as a potential contributor to ASD pathogenesis, its role in large-scale genomic studies has remained relatively unexplored. In this comprehensive study, we utilized computational tools to identify, predict, and validate splicing variants within a Spanish ASD cohort (360 trios), shedding light on their potential contributions to the disorder. We utilized SpliceAI, a newly developed machine-learning tool, to identify high-confidence splicing variants in the Spanish ASD cohort and applied a stringent threshold (Δ ≥ 0.8) to ensure robust confidence in the predictions. The in silico validation was then conducted using SpliceVault, which provided compelling evidence of the predicted splicing effects, using 335,663 reference RNA-sequencing (RNA-seq) datasets from GTEx v8 and the sequence read archive (SRA). Furthermore, ABSplice was employed for additional orthogonal in silico confirmation and to elucidate the tissue-specific impacts of the splicing variants. Notably, our analysis suggested the contribution of splicing variants within CACNA1I, CBLB, CLTB, DLGAP1, DVL3, KIAA0513, OFD1, PKD1, SLC13A3, and SCN2A. Complementary datasets, including more than 42,000 ASD cases, were employed for gene validation and gene ontology (GO) analysis. These analyses revealed potential tissue-specific effects of the splicing variants, particularly in adipose tissue, testis, and the brain. These findings suggest the involvement of these tissues in ASD etiology, which opens up new avenues for further functional testing. Enrichments in molecular functions and biological processes imply the presence of separate pathways and mechanisms involved in the progression of the disorder, thereby distinguishing splicing genes from other ASD-related genes. Notably, splicing genes appear to be predominantly associated with synaptic organization and transmission, in contrast to non-splicing genes (i.e., genes harboring de novo and inherited coding variants not predicted to alter splicing), which have been mainly implicated in chromatin remodeling processes. In conclusion, this study advances our comprehension of the role of AS in ASD and calls for further investigations, including in vitro validation and integration with multi-omics data, to elucidate the functional roles of the highlighted genes and the intricate interplay of the splicing process with other regulatory mechanisms and tissues in ASD.