Protein-Altering Variants' Analysis in Autism Subgroups Uncovers Early Brain-Expressed Gene Modules Relevant to Autism Pathophysiology

Understanding the functional implications of genes' variants in autism heterogeneity is challenging. Gene set analysis examines the cumulative effect of multiple functionally converging genes. Here we explored whether a multi-step analysis could identify gene sets with different loads of protein-altering variants (PAVs) between two subgroups of autistic children. After subdividing our sample (n = 71, 3–12 years) based on higher (> 80; n = 43) and lower ($⩽$ 80; n = 28) intelligence quotient (IQ), a gene set variant enrichment analysis identified gene sets with significantly different incidence of PAVs between the two subgroups of autistic children. Significant gene sets were then clustered into modules of genes. Their brain expression was investigated according to the BrainSpan Atlas of the Developing Human Brain. Next, we extended each module by selecting the genes that were spatio-temporally co-expressed in the developing brain and physically interacting with those in modules. Last, we explored the incidence of autism susceptibility genes within original and extended modules. Our analysis identified 38 significant gene sets (FDR, q < 0.05). They clustered in four modules involved in ion cell communication, neurocognition, gastrointestinal function, and immune system. Those modules were highly expressed in specific brain structures across development. Spatio-temporal brain co-expression and physical interactions identified extended genes' clusters with over-represented autism susceptibility genes. Overall, our unbiased approach identified modules of genes functionally relevant to autism pathophysiology, possibly implicating them in phenotypic variability across subgroups. The findings also suggest that autism diversity likely originates from multiple interacting pathways. Future research could leverage this approach to identify genetic pathways relevant to autism subtyping.