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Title
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A Solve-RD ClinVar-based reanalysis of 1522 index cases from ERN-ITHACA reveals common pitfalls and misinterpretations in exome sequencing
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Author
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Institution/Organisation
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Solve-RD DITF-ITHACA
Solve-RD SNV-indel Working Group
Solve-RD Consortia
Orphanomix Group
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Abstract
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| Purpose: Within the Solve-RD project (https://solve-rd.eu/), the European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies aimed to investigate whether a reanalysis of exomes from unsolved cases based on ClinVar annotations could establish additional diagnoses. We present the results of the "ClinVar low-hanging fruit" reanalysis, reasons for the failure of previous analyses, and lessons learned. Methods: Data from the first 3576 exomes (1522 probands and 2054 relatives) collected from European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies was reanalyzed by the Solve-RD consortium by evaluating for the presence of single-nucleotide variant, and small insertions and deletions already reported as (likely) pathogenic in ClinVar. Variants were filtered according to frequency, genotype, and mode of inheritance and reinterpreted. Results: We identified causal variants in 59 cases (3.9%), 50 of them also raised by other ap-proaches and 9 leading to new diagnoses, highlighting interpretation challenges: variants in genes not known to be involved in human disease at the time of the first analysis, misleading genotypes, or variants undetected by local pipelines (variants in off-target regions, low quality filters, low allelic balance, or high frequency). Conclusion: The "ClinVar low-hanging fruit" analysis represents an effective, fast, and easy approach to recover causal variants from exome sequencing data, herewith contributing to the reduction of the diagnostic deadlock. (c) 2023 The Authors. Published by Elsevier Inc. on behalf of American College of Medical Genetics and Genomics. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
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Language
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English
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Source (journal)
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Genetics in medicine. - Philadelphia, Pa.
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Publication
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New york
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2023
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ISSN
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1098-3600
1530-0366
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DOI
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10.1016/J.GIM.2023.100018
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Volume/pages
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25
:4
(2023)
, p. 1-15
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Article Reference
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100018
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ISI
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001000649600001
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Pubmed ID
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36681873
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Medium
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E-only publicatie
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Full text (Publisher's DOI)
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Full text (open access)
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