Human MutationGenomicsPeer-reviewed journal article
Recommendations for Interpreting the Loss of Function PVS1 ACMG/AMP Variant Criteria
Ahmad N. Abou TayouniD, Tina F. PesaraniD, Marina T. DiStefanoiD, Andrea M. OzaiD, Heidi L. RehmiD, Leslie G. BieseckeriD, Steven M. HarrisoniD, ClinGen Sequence Variant Interpretation Working Group (ClinGen SVI)
Abstract
The 2015 ACMG/AMP sequence variant interpretation guideline provided a framework for classifying variants based on several benign and pathogenic evidence criteria. This guideline includes a pathogenic criterion (PVS1) for predicted loss of function variants. However, the guideline did not elaborate on the specific considerations for the different types of loss of function variants, nor did it provide decision-making pathways assimilating information about the variant type, its location within the gene, or any additional evidence for the likelihood of a true null effect. Furthermore, the ACMG/AMP guideline did not take into account the relative strengths for each evidence type and the final outcome of their combinations with respect to PVS1 strength. Finally, criteria specifying the genes for which PVS1 can be used are still missing. Here, as part of the Clinical Genomic Resource (ClinGen) Sequence Variant Interpretation (SVI) Working Groups goal of refining ACMG/AMP criteria, we provide recommendations for applying the PVS1 rule using detailed guidance addressing all the above-mentioned gaps. We evaluate the performance of the refined rule using heterogeneous types of loss of function variants (n = 56) curated by seven disease-specific groups across ten genes. Our recommendations will facilitate consistent and accurate interpretation of predicted loss of function variants.\n\nGRANT NUMBERSResearch reported in this publication was supported by the National Human Genome Research Institute (NHGRI) under award number U41HG006834. LGB was supported by the Intramural Research Program of the NHGRI grant number HG200359 09.
- assay: GWAS summary statistics
- research focus: benchmarking
- research focus: variant effect prediction
- research focus: variant calling
- research focus: database / resource
- approach: statistical model
- Citations
- 898
- FWCI
- 31.77
- Field percentile
- top 1%
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