Literature DB >> 30449888

Trajectory of exonic variant discovery in a large clinical population: implications for variant curation.

Uyenlinh L Mirshahi1, Jonathan Z Luo2, Kandamurugu Manickam2, Amr H Wardeh2, Tooraj Mirshahi2, Michael F Murray2, David J Carey2.   

Abstract

PURPOSE: Precision health initiatives and reduced sequencing costs are driving large-scale human genome analyses. Genetic variant curation is a bottleneck in clinical applications. The burden of variant curation can be high for newly discovered variants because they are less likely to have undergone previous clinical annotation; the rate of discovery of genetic variants in large clinical populations has not been empirically determined.
METHODS: We determined the rate of accrual of unique sequence variants in 90,000 exome sequences. Separate analyses were done for 17,267 autosomal genes and a subset of 74 actionable genes; the effect of relatedness in the cohort was also determined.
RESULTS: Variant discovery showed a nonlinear growth pattern. The rate of unique variant accrual decreased as the database size increased; by 90,000 exomes 97% of all projected coding and splicing variants had been observed. Variants in 74 actionable genes showed a similar pattern. Family relatedness slightly reduced the rate of discovery of unique variants.
CONCLUSION: The heaviest burden of interpretation for genetic variants occurs early and diminishes as the database size increases. Our data provide a framework for scaling pathogenic genetic variant discovery and curation, a critical element of patient care in the era of precision health.

Entities:  

Keywords:  exome sequencing; genomic screening; secondary findings; sequence scaling; variant curation

Mesh:

Year:  2018        PMID: 30449888     DOI: 10.1038/s41436-018-0353-5

Source DB:  PubMed          Journal:  Genet Med        ISSN: 1098-3600            Impact factor:   8.822


  5 in total

1.  Future directions for high-throughput splicing assays in precision medicine.

Authors:  Christy L Rhine; Christopher Neil; David T Glidden; Kamil J Cygan; Alger M Fredericks; Jing Wang; Nephi A Walton; William G Fairbrother
Journal:  Hum Mutat       Date:  2019-08-17       Impact factor: 4.878

2.  A data-driven evaluation of the size and content of expanded carrier screening panels.

Authors:  Rotem Ben-Shachar; Ashley Svenson; James D Goldberg; Dale Muzzey
Journal:  Genet Med       Date:  2019-02-28       Impact factor: 8.822

3.  A Genome-First Approach to Characterize DICER1 Pathogenic Variant Prevalence, Penetrance, and Phenotype.

Authors:  Uyenlinh L Mirshahi; Jung Kim; Ana F Best; Zongming E Chen; Ying Hu; Jeremy S Haley; Alicia Golden; Richard Stahl; Kandamurugu Manickam; Ann G Carr; Laura A Harney; Amanda Field; Jessica Hatton; Kris Ann P Schultz; Andrew J Bauer; D Ashley Hill; Philip S Rosenberg; Michael F Murray; David J Carey; Douglas R Stewart
Journal:  JAMA Netw Open       Date:  2021-02-01

4.  Framework From a Multidisciplinary Approach for Transitioning Variants of Unknown Significance From Clinical Genetic Testing in Kidney Disease to a Definitive Classification.

Authors:  Uyenlinh L Mirshahi; Ahana Bhan; Lotte E Tholen; Brian Fang; Guoli Chen; Bryn Moore; Adam Cook; Prince Mohan Anand; Kashyap Patel; Mary E Haas; Luca A Lotta; Peter Igarashi; Jeroen H F de Baaij; Silvia Ferrè; Joost G J Hoenderop; David J Carey; Alexander R Chang
Journal:  Kidney Int Rep       Date:  2022-07-07

5.  Predictive value of genomic screening: cross-sectional study of cystic fibrosis in 50,788 electronic health records.

Authors:  J A Stamm; D J Carey; U L Mirshahi; J P Sugunaraj; H M Brosius; M F Murray; K Manickam
Journal:  NPJ Genom Med       Date:  2019-09-04       Impact factor: 8.617

  5 in total

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