Variability in assigning pathogenicity to incidental findings: insights from LDLR sequence linked to the electronic health record in 1013 individuals. Eur J Hum Genet 2017 Apr;25(4):410-415
Date
02/02/2017Pubmed ID
28145427Pubmed Central ID
PMC5386413DOI
10.1038/ejhg.2016.193Scopus ID
2-s2.0-85011292251 (requires institutional sign-in at Scopus site) 11 CitationsAbstract
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.
Author List
Safarova MS, Klee EW, Baudhuin LM, Winkler EM, Kluge ML, Bielinski SJ, Olson JE, Kullo IJAuthor
Maya S. Safarova MD, PhD Assistant Professor in the Medicine department at Medical College of WisconsinMESH terms used to index this publication - Major topics in bold
AgedDatabases, Genetic
Electronic Health Records
Female
Gene Frequency
Genetic Testing
Humans
Hyperlipoproteinemia Type II
Incidental Findings
Male
Middle Aged
Observer Variation
Polymorphism, Genetic
Receptors, LDL
