Interpretation of variants identified during genetic testing is a significant clinical challenge. In this study, we developed a high-throughput CDKN2A functional assay and characterized all possible human CDKN2A missense variants. We found that 17.7% of all missense variants were functionally deleterious. We also used our functional classifications to assess the performance of in silico models that predict the effect of variants, including recently reported models based on machine learning. Notably, we found that all in silico models performed similarly when compared to our functional classifications with accuracies of 39.5-85.4%. Furthermore, while we found that functionally deleterious variants were enriched within ankyrin repeats, we did not identify any residues where all missense variants were functionally deleterious. Our functional classifications are a resource to aid the interpretation of CDKN2A variants and have important implications for the application of variant interpretation guidelines, particularly the use of in silico models for clinical variant interpretation.
Functional characterization of all CDKN2A missense variants and comparison to in silico models of pathogenicity.
对所有 CDKN2A 错义变异进行功能表征,并与致病性的计算机模型进行比较
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作者:Kimura Hirokazu, Lahouel Kamel, Tomasetti Cristian, Roberts Nicholas Jason
| 期刊: | Elife | 影响因子: | 6.400 |
| 时间: | 2025 | 起止号: | 2025 Apr 16; 13:RP95347 |
| doi: | 10.7554/eLife.95347 | 研究方向: | 其它 |
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