Evaluating the impact of in silico predictors on clinical variant classification.

Autor:	Wilcox EH; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA., Sarmady M; Spark Therapeutics, Philadelphia, PA., Wulf B; Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA., Wright MW; Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA., Rehm HL; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA., Biesecker LG; Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD., Abou Tayoun AN; Al Jalila Genomics Center, Al Jalila Children's Specialty Hospital, Dubai, United Arab Emirates; Center for Genomic Discovery, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, United Arab Emirates. Electronic address: Ahmad.Tayoun@ajch.ae.
Jazyk:	angličtina
Zdroj:	Genetics in medicine : official journal of the American College of Medical Genetics [Genet Med] 2022 Apr; Vol. 24 (4), pp. 924-930. Date of Electronic Publication: 2021 Dec 23.
DOI:	10.1016/j.gim.2021.11.018
Abstrakt:	Purpose: According to the American College of Medical Genetics and Genomics/Association of Medical Pathology (ACMG/AMP) guidelines, in silico evidence is applied at the supporting strength level for pathogenic (PP3) and benign (BP4) evidence. Although PP3 is commonly used, less is known about the effect of these criteria on variant classification outcomes. Methods: A total of 727 missense variants curated by Clinical Genome Resource expert groups were analyzed to determine how often PP3 and BP4 were applied and their impact on variant classification. The ACMG/AMP categorical system of variant classification was compared with a quantitative point-based system. The pathogenicity likelihood ratios of REVEL, VEST, FATHMM, and MPC were calibrated using a gold standard set of 237 pathogenic and benign variants (classified independent of the PP3/BP4 criteria). Results: The PP3 and BP4 criteria were applied by Variant Curation Expert Panels to 55% of missense variants. Application of those criteria changed the classification of 15% of missense variants for which either criterion was applied. The point-based system resolved borderline classifications. REVEL and VEST performed best at a strength level consistent with moderate evidence. Conclusion: We show that in silico criteria are commonly applied and often affect the final variant classifications. When appropriate thresholds for in silico predictors are established, our results show that PP3 and BP4 can be used at a moderate strength. Competing Interests: Conflict of Interest The authors declare that they have no competing interests. L.G.B. reports serving as an advisor for the Illumina, Inc and receiving in-kind research support from Merck & Co, Inc. (Copyright © 2021 American College of Medical Genetics and Genomics. All rights reserved.)
Databáze:	MEDLINE
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