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- Title
Semiautomated approach focused on new genomic information results in time and effort-efficient reannotation of negative exome data.
- Authors
Ferrer, Alejandro; Duffy, Patrick; Olson, Rory J.; Meiners, Michael A.; Schultz-Rogers, Laura; Macke, Erica L.; Safgren, Stephanie; Morales-Rosado, Joel A.; Cousin, Margot A.; Oliver, Gavin R.; Rider, David; Williams, Megan; Pichurin, Pavel N.; Deyle, David R.; Morava, Eva; Gavrilova, Ralitza H.; Dhamija, Radhika; Wierenga, Klass J.; Lanpher, Brendan C.; Babovic-Vuksanovic, Dusica
- 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.
- Subjects
ONLINE databases; INDIVIDUALIZED medicine; RARE diseases; PATHOLOGICAL laboratories; GENETIC variation
- Publication
Human Genetics, 2024, Vol 143, Issue 5, p649
- ISSN
0340-6717
- Publication type
Article
- DOI
10.1007/s00439-024-02664-3