TY - JOUR
T1 - A Solve-RD ClinVar-based reanalysis of 1,522 index cases from ERN-ITHACA reveals common pitfalls and misinterpretations in exome sequencing
AU - Solve-RD DITF-ITHACA
AU - Solve-RD SNV-indel working group
AU - Solve-RD Consortia
AU - Orphanomix Group
AU - Denommé-Pichon, Anne-Sophie
AU - Matalonga, Leslie
AU - de Boer, Elke
AU - Jackson, Adam
AU - Benetti, Elisa
AU - Banka, Siddharth
AU - Bruel, Ange-Line
AU - Ciolfi, Andrea
AU - Clayton-Smith, Jill
AU - Dallapiccola, Bruno
AU - Duffourd, Yannis
AU - Ellwanger, Kornelia
AU - Fallerini, Chiara
AU - Gilissen, Christian
AU - Graessner, Holm
AU - Haack, Tobias B
AU - Havlovicova, Marketa
AU - Hoischen, Alexander
AU - Jean-Marçais, Nolwenn
AU - Kleefstra, Tjitske
AU - López-Martín, Estrella
AU - Macek, Milan
AU - Mencarelli, Maria Antonietta
AU - Moutton, Sébastien
AU - Pfundt, Rolph
AU - Pizzi, Simone
AU - Posada, Manuel
AU - Radio, Francesca Clementina
AU - Renieri, Alessandra
AU - Rooryck, Caroline
AU - Ryba, Lukas
AU - Safraou, Hana
AU - Tartaglia, Marco
AU - Thauvin-Robinet, Christel
AU - Thevenon, Julien
AU - Mau-Them, Frédéric Tran
AU - Trimouille, Aurélien
AU - Votypka, Pavel
AU - de Vries, Bert B A
AU - Willemsen, Marjolein H
AU - Zurek, Birte
AU - Verloes, Alain
AU - Philippe, Christophe
AU - Vitobello, Antonio
AU - Vissers, Lisenka E L M
AU - Faivre, Laurence
N1 - Copyright © 2023. Published by Elsevier Inc.
PY - 2023/4/1
Y1 - 2023/4/1
N2 - 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 approaches 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.
AB - 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 approaches 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.
KW - ClinVar
KW - Developmental disorder
KW - Exome reanalysis
KW - Rare diseases
UR - https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=pure_starter&SrcAuth=WosAPI&KeyUT=WOS:001000649600001&DestLinkType=FullRecord&DestApp=WOS
UR - http://www.scopus.com/inward/record.url?scp=85152173255&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/9959afaf-ac88-325c-bfdd-9c5f58b11ca5/
U2 - 10.1016/j.gim.2023.100018
DO - 10.1016/j.gim.2023.100018
M3 - Article
C2 - 36681873
SN - 1098-3600
VL - 25
JO - Genetics in medicine : official journal of the American College of Medical Genetics
JF - Genetics in medicine : official journal of the American College of Medical Genetics
IS - 4
M1 - 100018
ER -