Journal
GENETICS IN MEDICINE
Volume 20, Issue 11, Pages 1334-1345Publisher
ELSEVIER SCIENCE INC
DOI: 10.1038/gim.2018.3
Keywords
ClinGen; Noonan; Ras/MAPK; RASopathy; variant interpretation
Categories
Funding
- National Human Genome Research Institute
- Eunice Kennedy Shriver National Institute of Child Health and Human Development [U41HG006834]
- German Ministry for Education and Research [FKZ 01GM1602A, FKZ 01GM1519A]
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Purpose: Standardized and accurate variant assessment is essential for effective medical care. To that end, Clinical Genome (ClinGen) Resource clinical domain working groups (CDWGs) are systematically reviewing disease-associated genes for sufficient evidence to support disease causality and creating disease-specific specifications of American College of Medical Genetics and Genomics-Association for Molecular Pathology (ACMG-AMP) guidelines for consistent and accurate variant classification. Methods: The ClinGen RASopathy CDWG established an expert panel to curate gene information and generate gene- and disease-specific specifications to ACMG-AMP variant classification framework. These specifications were tested by classifying 37 exemplar pathogenic variants plus an additional 66 variants in ClinVar distributed across nine RASopathy genes. Results: RASopathy-related specifications were applied to 16 ACMG-AMP criteria, with 5 also having adjustable strength with availability of additional evidence. Another 5 criteria were deemed not applicable. Key adjustments to minor allele frequency thresholds, multiple de novo occurrence events and/or segregation, and strength adjustments impacted 60% of variant classifications. Unpublished case-level data from participating laboratories impacted 45% of classifications supporting the need for data sharing. Conclusion: RAS-specific ACMG-AMP specifications optimized the utility of available clinical evidence and Ras/MAPK pathway-specific characteristics to consistently classify RASopathy-associated variants. These specifications highlight how grouping genes by shared features promotes rapid multigenic variant assessment without sacrificing specificity and accuracy.
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