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Advisor(s)
Abstract(s)
Purpose: In 2015, the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) published consensus standardized guidelines for sequence-level variant classification in Mendelian disorders. To increase accuracy and consistency, the Clinical Genome Resource Familial Hypercholesterolemia (FH) Variant Curation Expert Panel was tasked with optimizing the existing ACMG/AMP framework for disease-specific classification in FH. In this study, we provide consensus recommendations for the most common FH-associated gene, LDLR, where >2300 unique FH-associated variants have been identified.
Methods: The multidisciplinary FH Variant Curation Expert Panel met in person and through frequent emails and conference calls to develop LDLR-specific modifications of ACMG/AMP guidelines. Through iteration, pilot testing, debate, and commentary, consensus among experts was reached.
Results: The consensus LDLR variant modifications to existing ACMG/AMP guidelines include (1) alteration of population frequency thresholds, (2) delineation of loss-of-function variant types, (3) functional study criteria specifications, (4) cosegregation criteria specifications, and (5) specific use and thresholds for in silico prediction tools, among others.
Conclusion: Establishment of these guidelines as the new standard in the clinical laboratory setting will result in a more evidence-based, harmonized method for LDLR variant classification worldwide, thereby improving the care of patients with FH.
Description
The online version of this article (https://doi.org/10.1016/j.
gim.2021.09.012) contains supplementary material, which
is available to authorized users.
Keywords
ACMG/AMP ClinGen Familial Hypercholesterolemia LDLR Variant Classification Doenças Cardio e Cérebro-vasculares Colesterol Hipercolesterolemia Familiar
Pedagogical Context
Citation
Genet Med. 2022 Feb;24(2):293-306. doi: 10.1016/j.gim.2021.09.012. Epub 2021 Nov 30
Publisher
Elsevier/ American College of Medical Genetics and Genomics
