Variability in assigning pathogenicity to incidental findings: insights from LDLR sequence linked to the electronic health record in 1013 individuals

Abstract

Knowledge of variant pathogenicity is key to implementing genomic medicine. We describe variability between expert reviewers in assigning pathogenicity to sequence variants in LDLR, the causal gene in the majority of cases of familial hypercholesterolemia. LDLR was sequenced on the Illumina HiSeq platform (average read depth >200 × ) in 1013 Mayo Biobank participants recruited from 2012 to 2013. Variants with a minor allele frequency (MAF) <5% predicted to be functional or referenced in HGMD (Human Gene Mutation Database) or NCBI-ClinVar databases were reviewed. To assign pathogenicity, variant frequency in population data sets, computational predictions, reported observations and patient-level data including electronic health record-based post hoc phenotyping were leveraged. Of 178 LDLR variants passing quality control, 25 were selected for independent review using either an in-house protocol or a disease/gene-specific semi-quantitative framework based on the American College of Medical Genetics and Genomics-recommended lines of evidence. NCBI-ClinVar included interpretations for all queried variants with 74% (14/19) of variants with >1 submitter showing inconsistency in classification and 26% (5/19) appearing with conflicting clinical actionability. The discordance rate (one-step level of disagreement out of five classes in variant interpretation) between the reviewers was 40% (10/25). Two LDLR variants were independently deemed clinically actionable and returnable. Interpretation of LDLR variants was often discordant among ClinVar submitters and between expert reviewers. A quantitative approach based on strength of each predefined criterion in the context of specific genes and phenotypes may yield greater consistency between different reviewers.

DOI: 10.1038/ejhg.2016.193

Cite this paper

@article{Safarova2017VariabilityIA, title={Variability in assigning pathogenicity to incidental findings: insights from LDLR sequence linked to the electronic health record in 1013 individuals}, author={Maya S Safarova and Eric W. Klee and Linnea M. Baudhuin and Erin M Winkler and Michelle L. Kluge and Suzette J. Bielinski and Janet E. Olson and Iftikhar J. Kullo}, journal={European Journal of Human Genetics}, year={2017}, volume={25}, pages={410-415} }