Mohammad K. Eldomery , Jamie L. Maciaszek , Taylor Cain , Victor Pastor Loyola , Suraj Sarvode Mothi , David A. Wheeler , Li Tang , Lu Wang , Jeffery M. Klco , Patrick R. Blackburn
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引用次数: 0
Abstract
Purpose
To assess the differences in variant classifications using the American College of Medical Genetics and Genomics and the Association for Molecular Pathology 2015 guidelines and the Bayesian point-based classification system (here referred to as the point system) in 115 hereditary cancer predisposition genes and explore variant sub-tiering by the point system.
Methods
Germline variant classifications for 721 pediatric patients from an in-house panel were retrospectively evaluated using the 2 scoring systems.
Results
A total of 2376 unique variants were identified, with ∼23.5% exhibiting discordant classifications. Unique variants classified by the point system demonstrated a lower rate of variants of uncertain significance (VUS; ∼15%) compared with American College of Medical Genetics and Genomics and the Association for Molecular Pathology 2015 guidelines (∼36%). This change is attributed to unique variants with 1 benign supporting evidence (∼12%) or 1 benign strong evidence (∼4%) being classified as likely benign by the point system. Additionally, variants with conflicting/modified evidence (∼5% of 2376) are also resolved by the point system. Sub-tiering unique variants classified by the point system as VUS (n = 354) indicates ∼77.4% were VUS-Low (0-1 points), whereas the remaining ∼22.6% were VUS-Mid (2-3 points) and VUS-High (4-5 points).
Conclusion
The point system reduces the VUS rate and facilitates their sub-tiering. Future large-scale studies are warranted to explore the impact of the point system on improving VUS reporting and/or VUS clinical management.
期刊介绍:
Genetics in Medicine (GIM) is the official journal of the American College of Medical Genetics and Genomics. The journal''s mission is to enhance the knowledge, understanding, and practice of medical genetics and genomics through publications in clinical and laboratory genetics and genomics, including ethical, legal, and social issues as well as public health.
GIM encourages research that combats racism, includes diverse populations and is written by authors from diverse and underrepresented backgrounds.