Genetic association studies have identified numerous genes harboring protein-disrupting variants in individuals with profound autism, but identifying convergent points of vulnerability remains challenging. We discuss how brain transcriptomic resources help decode the cellular consequences of these rare gene-disrupting variants. The functional interpretation of genetic associations has largely relied on gene ontologies and protein-interaction networks, with newer approaches leveraging single-cell expression to estimate cellular enrichment. However, the broad expression of many autism-associated genes confounds cell-type-specific effects. We therefore propose a framework quantifying the trade-off between a gene's cell-type specificity and sensitivity. The limited overlap between genetic associations and transcriptomic alterations in autistic brains prompts a discussion about causality. We examine whether foundation models linking genetic variation to cell-type transcriptomes could clarify the cellular functions affected by autism-associated variants. By combining experimental perturbations, artificial-intelligence-driven inference, and postmortem validation, we propose a unifying mechanistic framework for rare-variant liability in autism.
Dubuc et al. (Wed,) studied this question.