1. Semiautomated approach focused on new genomic information results in time and effort-efficient reannotation of negative exome data.
- Author
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Ferrer A, Duffy P, Olson RJ, Meiners MA, Schultz-Rogers L, Macke EL, Safgren S, Morales-Rosado JA, Cousin MA, Oliver GR, Rider D, Williams M, Pichurin PN, Deyle DR, Morava E, Gavrilova RH, Dhamija R, Wierenga KJ, Lanpher BC, Babovic-Vuksanovic D, Kaiwar C, Vitek CR, McAllister TM, Wick MJ, Schimmenti LA, Lazaridis KN, Vairo FPE, and Klee EW
- Subjects
- Humans, Exome genetics, Exome Sequencing methods, Databases, Genetic, Genetic Testing methods, Genome, Human, Whole Genome Sequencing methods, Phenotype, Genomics methods
- Abstract
Most rare disease patients (75-50%) undergoing genomic sequencing remain unsolved, often due to lack of information about variants identified. Data review over time can leverage novel information regarding disease-causing variants and genes, increasing this diagnostic yield. However, time and resource constraints have limited reanalysis of genetic data in clinical laboratories setting. We developed RENEW, (REannotation of NEgative WES/WGS) an automated reannotation procedure that uses relevant new information in on-line genomic databases to enable rapid review of genomic findings. We tested RENEW in an unselected cohort of 1066 undiagnosed cases with a broad spectrum of phenotypes from the Mayo Clinic Center for Individualized Medicine using new information in ClinVar, HGMD and OMIM between the date of previous analysis/testing and April of 2022. 5741 variants prioritized by RENEW were rapidly reviewed by variant interpretation specialists. Mean analysis time was approximately 20 s per variant (32 h total time). Reviewed cases were classified as: 879 (93.0%) undiagnosed, 63 (6.6%) putatively diagnosed, and 4 (0.4%) definitively diagnosed. New strategies are needed to enable efficient review of genomic findings in unsolved cases. We report on a fast and practical approach to address this need and improve overall diagnostic success in patient testing through a recurrent reannotation process., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)
- Published
- 2024
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