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VUS Classification Improved Using In Silico Protein Structural Variant Profiles

For a paper in Genome Medicine, a team from Royal Devon University's Exeter Genomics Laboratory and the University of Exeter School of Medicine considers the effectiveness of in silico protein structure-based approaches for classifying variants of uncertain significance (VUS). Tapping into five years of data generated at a UK National Health Service genomic medicine diagnostic laboratory, the researchers focused on protein structure-based re-analyses of novel missense, in-frame variants, which led to pathogenic or likely pathogenic variant calls for 47 of the 64 VUS analyzed — classifications that enhanced disease mechanism predictions in several cases. "We have shown that using in silico protein structural analysis can aid classification of VUS and give insights into the mechanisms of pathogenicity," the authors note. "Based on our experience, we propose a generic evidence-based workflow for incorporating protein structural information into diagnostic practice to facilitate variant classification."

The Scan

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