Variability in gene-based knowledge impacts variant classification: an analysis of FBN1 missense variants in ClinVar

作者
Linnea M. Baudhuin,Michelle L. Kluge,Katrina E. Kotzer,Susan A. Lagerstedt
出处
期刊:European Journal of Human Genetics [Springer Nature]
卷期号:27 (10): 1550-1560 被引量:26
标识
DOI:10.1038/s41431-019-0440-3
摘要

Gene-specific knowledge can enhance genetic variant classification, but may not be routinely incorporated into clinical laboratory practice. For example, FBN1 variants associated with Marfan syndrome may be variably classified depending on knowledge of FBN1-specific critical regions. In order to assess variability in classification of FBN1 variants, 674 FBN1 missense variants from 18 ClinVar submitters were compared and reanalyzed using FBN1-specific criteria and ACMG/AMP 2015 guidelines for variant interpretation. Conflicting variant classifications occurred in 30.7% of the missense variants that had multiple submitters. There were 451 classifications of 361 critical residue missense variants, with 80.0% (361/451) classified as likely pathogenic or pathogenic [(L)P]. Non-cysteine critical residue variants were less likely to be classified as (L)P [55.3% (78/141)] than cysteine variants [91.3% (283/310)] and were more likely to lack evidence citing the functional significance of the amino acid impacted. Application of FBN1-specific knowledge allowed for reclassification or discrepancy resolution in 65/361 (18.0%) critical residue variants. There were 522 classifications of 313 unique missense variants not known to impact a critical residue. Of these, 31.6% (165/522) were likely overclassified as either (L)P or uncertain significance (VUS), especially when minor allele frequency (MAF) was taken into account, and we reclassified or resolved classification discrepancies in 128/313 (40.9%) of these variants. Our results provide a refined framework and resource for FBN1 variant classification, and further supports the more global implications of combining gene-based knowledge with ACMG/AMP criteria and appropriate MAF cutoffs for variant classification that extend beyond FBN1.

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