The prevalence of protein misfolding as a mechanism for hereditary deafness

Hearing loss is the most common sensory deficit impacting ~5% of the world's population. The Deafness Variation Database (DVD) is a public resource of deafness variants, containing 381,924 missense variants across 224 genes, with 303,577 classified as a variant of uncertain significance (VUS). To address the challenge of evaluating each deafness associated VUS, we evaluate a family of probabilistic frameworks to quantify the strength of computational evidence based on ACMG/AMP recommendations. First, CADD and REVEL are compared using Bayesian models parameterized using either a ClinVar 2019 dataset or labeled DVD variants. The REVEL model built using the DVD dataset demonstrates the best accuracy, sensitivity, and specificity. Incorporation of (in)tolerance to missense variation based on sorting each gene into three bins (tolerant, average, intolerant) shows that intolerant DVD genes are consistent with a higher prior probability of being pathogenic (25.7%) than average (10.7%) or tolerant (8.7%) genes. Finally, the impact of protein folding stability was incorporated into the Bayesian model and surpassed the simpler versions while also offering a biophysical rationale for the disease mechanism. The 28,866 VUSs that reach a posterior probability of pathogenicity above 98% based on the protein-folding informed Bayesian model were prioritized as likely to be pathogenic. Overall, 54,752 missense variants (14.3% of 381,924) are predicted to cause modest protein folding destabilization of greater than 1.0 kcal/mol, while 18,706 of these are prioritized VUSs (34% of 54,752). 22,237 missense variants (6.2% of 381,924) are predicted to cause more severe protein folding destabilization of at least 2 kcal/mol with 12,424 being prioritized VUSs (55.8% of 22,237). From these VUSs, we identify twelve probands where the patient's genetic diagnosis is upgraded to likely pathogenic/pathogenic. We highlight two variants that cause clear structural disruption, demonstrating the impact of biophysical characterization on variant evaluation.