A Solve-RD ClinVar-based reanalysis of 1522 index cases from ERN-ITHACA reveals common pitfalls and misinterpretations in exome sequencing

. 2023 Apr ; 25 (4) : 100018. [epub] 20230120

Jazyk angličtina Země Spojené státy americké Médium print-electronic

Typ dokumentu časopisecké články, práce podpořená grantem

Perzistentní odkaz   https://www.medvik.cz/link/pmid36681873

Grantová podpora
207556/Z/17/Z Wellcome Trust - United Kingdom
G1000848 Medical Research Council - United Kingdom
MR/N025431/2 Medical Research Council - United Kingdom
MR/M008525/1 Medical Research Council - United Kingdom
MR/T046015/1 Medical Research Council - United Kingdom
MC_PC_18031 Medical Research Council - United Kingdom
MR/V009346/1 Medical Research Council - United Kingdom

Odkazy

PubMed 36681873
DOI 10.1016/j.gim.2023.100018
PII: S1098-3600(23)00024-2
Knihovny.cz E-zdroje

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.

CNAG CRG Centre for Genomic Regulation The Barcelona Institute of Science and Technology Barcelona Spain

Department of Biology and Medical Genetics 2nd Faculty of Medicine of Charles University and Motol University Hospital Prague Czech Republic

Department of Genetics Assistance Publique Hôpitaux de Paris Université de Paris Paris France; INSERM UMR 1141 NeuroDiderot Hôpital Robert Debré Paris France

Department of Human Genetics Radboudumc Nijmegen The Netherlands; Donders Institute for Brain Cognition and Behaviour Radboudumc Nijmegen The Netherlands

Department of Human Genetics Radboudumc Nijmegen The Netherlands; Donders Institute for Brain Cognition and Behaviour Radboudumc Nijmegen The Netherlands; Center of Excellence for Neuropsychiatry Vincent van Gogh Institute for Psychiatry Venray The Netherlands

Department of Human Genetics Radboudumc Nijmegen The Netherlands; Radboud Institute for Molecular Life Sciences Radbound University Nijmegen The Netherlands

Department of Human Genetics Radboudumc Nijmegen The Netherlands; Radboud Institute for Molecular Life Sciences Radbound University Nijmegen The Netherlands; Department of Internal Medicine and Radboud Center for Infectious Diseases Radboudumc Nijmegen The Netherlands

Functional Unit for Diagnostic Innovation in Rare Diseases FHU TRANSLAD Dijon Bourgogne University Hospital Dijon France; INSERM UMR1231 GAD Génétique des Anomalies du Développement FHU TRANSLAD University of Burgundy Dijon France

Functional Unit for Diagnostic Innovation in Rare Diseases FHU TRANSLAD Dijon Bourgogne University Hospital Dijon France; INSERM UMR1231 GAD Génétique des Anomalies du Développement FHU TRANSLAD University of Burgundy Dijon France; Department of Genetics and Reference Center for Development Disorders and Intellectual Disabilities FHU TRANSLAD and GIMI Institute Dijon Bourgogne University Hospital Dijon France

INSERM UMR1231 GAD Génétique des Anomalies du Développement FHU TRANSLAD University of Burgundy Dijon France

INSERM UMR1231 GAD Génétique des Anomalies du Développement FHU TRANSLAD University of Burgundy Dijon France; Department of Genetics and Reference Center for Development Disorders and Intellectual Disabilities FHU TRANSLAD and GIMI Institute Dijon Bourgogne University Hospital Dijon France

Institute of Medical Genetics and Applied Genomics University of Tübingen Tübingen Germany; Centre for Rare Diseases University Hospital Tübingen Tübingen Germany

Institute of Rare Diseases Research Spanish Undiagnosed Rare Diseases Cases Program and Undiagnosed Diseases Network International Instituto de Salud Carlos 3 Madrid Spain

Manchester Centre for Genomic Medicine University of Manchester Manchester United Kingdom

MedBiotech Hub and Competence Center Department of Medical Biotechnologies University of Siena Siena Italy

MedBiotech Hub and Competence Center Department of Medical Biotechnologies University of Siena Siena Italy; Medical Genetics University of Siena Siena Italy

MedBiotech Hub and Competence Center Department of Medical Biotechnologies University of Siena Siena Italy; Medical Genetics University of Siena Siena Italy; Medical Genetics Azienda Ospedaliero Universitaria Senese Siena Italy

Medical Genetics Azienda Ospedaliero Universitaria Senese Siena Italy

Molecular Genetics and Functional Genomics Ospedale Pediatrico Bambino Gesù IRCCS Rome Italy

Molecular Genetics Laboratory Medical Genetics Department Bordeaux University Hospital Hôpital Pellegrin Bordeaux France

MRGM INSERM U1211 University of Bordeaux Medical Genetics Department Bordeaux University Hospital Bordeaux France

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