Abstract
BackgroundThe 2015 American College of Medical Genetics and Genomics (ACMG) and Association for Molecular Pathology (AMP) guidelines articulates that the effects of certain types of variants on gene function can often be seen as a complete absence of the gene product by leading to a lack of transcription or nonsense-mediated decay(NMD). However, detailed information considering different types of loss of function(LOF) variants, refined steps assimilating details concerning location of variant, changes in strength levels, NMD boundary, or any additional information pointing to a true null effect, were all left to expert judgement. As part of its Clinical Genome Resource (ClinGen) initiative, Variant Curation Expert Panels (VCEPs) are designated to make gene/disease-centric specifications in accordance with the ACMG/AMP guidelines, including a more detailed definition of what constitutes an appropriate LOF evidence. Our goal was to evaluate the current LOF guidelines developed by the VCEPs and analyse the prior curated variants concerning the PVS1 criteria, bringing people occupied in genetic data analysis a comprehensive understanding of this code. MethodsOur study evaluated 7 VCEPs for their LOF criteria (PVS1). Subsequently, we assessed the predictive criteria by considering the underlying disease mechanism, protein transcript, and variant types delineated. Then, we meticulously curated the LOF evidence referenced by each VCEP in their preliminary variant classification, thereby scrutinizing the recommendations put forth by VCEPs and their application in the interpretation of the aforementioned predictive criteria. Based on these, an extensive curation of evidence summary considering PVS1 applied by VCEPs according to their classification of pilot variants for the purpose of analyzing VCEP criteria specifications and their use in the understanding of LOF was conducted. ResultsWe observed in this article that the VCEPs discussed followed the majority of Sequence Variant Interpretation (SVI) recommendations concerning the application of this LOF criteria, except for some disease/gene specific considerations. We highlighted the wide range of PVS1 strength levels approved by VCEP, reflecting the diversity of evidence for each variants type. In addition, we observed substantial differences in the approach used to determine relative strengths for different types of null variants and in the attitude towards these principles concerning variant location, NMD and influence to protein function between VCEPs. ConclusionsIt is difficult to understand the intricacies of the predictive data(PVS1), which often requires expert-level knowledge of disease/gene. The VCEP criteria specifications for the predictive evidence play an important role in making it more accessible for the curators to apply the predictive data by providing details concerning this complex criteria. Despite this, we believe there is a need for more guidance on standardizing this process and ensuring consistency in the application of this predictive evidence.
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