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.
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.
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
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
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
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