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Evaluation of CADD Scores in Curated Mismatch Repair Gene Variants Yields a Model for Clinical Validation and Prioritization
Author(s) -
Velde K. Joeri,
Kuiper Joël,
Thompson Bryony A.,
Plazzer JohnPaul,
Valkenhoef Gert,
Haan Mark,
Jongbloed Jan D.H.,
Wijmenga Cisca,
Koning Tom J.,
Abbott Kristin M.,
Sinke Richard,
Spurdle Amanda B.,
Macrae Finlay,
Genuardi Maurizio,
Sijmons Rolf H.,
Swertz Morris A.
Publication year - 2015
Publication title -
human mutation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.981
H-Index - 162
eISSN - 1098-1004
pISSN - 1059-7794
DOI - 10.1002/humu.22798
Subject(s) - biology , in silico , computational biology , genetics , prioritization , pathogenicity , gene , bioinformatics , management science , microbiology and biotechnology , economics
Next‐generation sequencing in clinical diagnostics is providing valuable genomic variant data, which can be used to support healthcare decisions. In silico tools to predict pathogenicity are crucial to assess such variants and we have evaluated a new tool, Combined Annotation Dependent Depletion (CADD), and its classification of gene variants in Lynch syndrome by using a set of 2,210 DNA mismatch repair gene variants. These had already been classified by experts from InSiGHT's Variant Interpretation Committee. Overall, we found CADD scores do predict pathogenicity (Spearman's ρ = 0.595, P < 0.001). However, we discovered 31 major discrepancies between the InSiGHT classification and the CADD scores; these were explained in favor of the expert classification using population allele frequencies, cosegregation analyses, disease association studies, or a second‐tier test. Of 751 variants that could not be clinically classified by InSiGHT, CADD indicated that 47 variants were worth further study to confirm their putative pathogenicity. We demonstrate CADD is valuable in prioritizing variants in clinically relevant genes for further assessment by expert classification teams.