Risk Beyond the Variant: A Composite Metric for Autism Gene Pathogenicity
Background: Variant-based pathogenicity predictors such as REVEL evaluate missense variants in isolation, discarding the gene-length and allele-frequency context needed to compare collections of genes. Methods: We introduce a composite gene-level metric integrating Hardy–Weinberg heterozygosity, coding-sequence length, and REVEL scores. The metric returns a single value per gene expressing variant burden per unit of coding sequence within a given cohort, so that the ratio between a case and a control cohort quantifies gene-level enrichment. It was evaluated on 55 high-confidence autism genes, defined as the intersection of three large-scale ASD sequencing studies, against the 1000 Genomes reference. Results: It identifies elevated pathogenic burden in 48 of 55 genes, removes gene-length and variant-count confounds, and substantially outperforms naive gene-level aggregation of REVEL scores. Bootstrap resampling and a label-permutation control confirm the enrichment is stable and not an artefact of the scoring construction. Conclusions: The metric allows genes to be ranked within a set and aggregate burden to be compared across gene sets. We present it as a complementary gene-level layer for case–control and gene-set comparisons, with a nonlinear successor outlined as future work.