Amina Kurtovic-Kozaric Lejla Delalic Belma Mutapcic Lejla Comor Eric Siciliano Mark Julin Kiel ^*

• Genomenon, Inc, Ann Arbor, United States

Accurate variant classification is critical for genetic diagnosis. Variants without clear classification, known as variants of uncertain significance (VUS), pose a significant diagnostic challenge. This study examines AlphaMissense performance in variant classification, specifically for VUS. A systematic comparison between AlphaMissense predictions and and predictions based on curated evidence according to the ACMG/AMP classification guidelines was conducted for 5845 missense variants in 59 genes associated with representative Mendelian disorders. A framework for quantifying and modeling VUS pathogenicity was used to facilitate comparison. Manual review classified 5845 variants as 4085 VUS, 1576 pathogenic/likely pathogenic, and 184 benign/likely benign. Pathogenicity predictions based on AlphaMissense and ACMG guidelines were concordant for 1887 variants (1352 pathogenic, 132 benign, and 403 VUS/ambiguous).The sensitivity and specificity of AlphaMissense predictions for pathogenicity were 92% and 78%.Moreover, quantification of VUS evidence and heatmaps weakly correlated with AlphaMissense score. For VUS without computational evidence, AlphaMissense incorporation changed VUS quantification for 878 variants, while 56 were reclassified to likely pathogenic. When AlphaMissense replaced existing computational evidence for all VUS, 1709 variants changed quantified criteria, while 63 were reclassified to likely pathogenic. Our research suggests augmenting AlphaMissense with empirical evidence may improve performance through incorporation of a quantitative framework aiding in VUS classification.