Comprehensive reanalysis for CNVs in ES data from unsolved rare disease cases results in new diagnoses

We report the results of a comprehensive copy number variant (CNV) reanalysis of 9171 exome sequencing datasets from 5757 families affected by a rare disease (RD). The data reanalysed was extremely heterogeneous, having been generated using 28 different enrichment kits by 42 different research groups across Europe partnering in the Solve-RD project. Each research group had previously undertaken their own analysis of the data but failed to identify disease-causing variants. We applied three CNV calling algorithms to maximise sensitivity, and rare CNVs overlapping genes of interest, provided by four partner European Reference Networks, were taken forward for interpretation by clinical experts. This reanalysis has resulted in a molecular diagnosis being provided to 51 families in this sample, with ClinCNV performing the best of the three algorithms. We also identified partially explanatory pathogenic CNVs in a further 34 individuals. This work illustrates the value of reanalysing ES cold cases for CNVs.

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Publication Details

Journal
npj Genomic Medicine
Published
2024-10-26
DOI
https://doi.org/10.1038/s41525-024-00436-6
Citations
5
Primary Topic
Genomic variations and chromosomal abnormalities
Type
article
Field-Weighted Citation Impact
2.75

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article

Comprehensive reanalysis for CNVs in ES data from unsolved rare disease cases results in new diagnoses

Francesco Musacchia, German Demidov, Elisa Benetti, Christian Gilissen et al.
5 citations
npj Genomic Medicine
Genomic variations and chromosomal abnormalities
2.75
article

Comprehensive reanalysis for CNVs in ES data from unsolved rare disease cases results in new diagnoses

Francesco Musacchia, German Demidov, Elisa Benetti, Christian Gilissen, Richarda M. de Voer, Alexander Hoischen, Lisenka E.L.M. Vissers, Nika Schuermans, José Garcia‐Pelaez, Carla Oliveíra, Sergi Beltrán, Gemma Bullich, Liedewei Van de Vondel, Ana Töpf, Lennart Johansson, Ida Paramonov, Stephan Ossowski, Burcu Yaldiz, Elke de Boer, Katja Lohmann, Karolis Sablauskas
article en
5 citations

Abstract

We report the results of a comprehensive copy number variant (CNV) reanalysis of 9171 exome sequencing datasets from 5757 families affected by a rare disease (RD). The data reanalysed was extremely heterogeneous, having been generated using 28 different enrichment kits by 42 different research groups across Europe partnering in the Solve-RD project. Each research group had previously undertaken their own analysis of the data but failed to identify disease-causing variants. We applied three CNV calling algorithms to maximise sensitivity, and rare CNVs overlapping genes of interest, provided by four partner European Reference Networks, were taken forward for interpretation by clinical experts. This reanalysis has resulted in a molecular diagnosis being provided to 51 families in this sample, with ClinCNV performing the best of the three algorithms. We also identified partially explanatory pathogenic CNVs in a further 34 individuals. This work illustrates the value of reanalysing ES cold cases for CNVs.

npj Genomic MedicineVol. 9(1)
University of Siena (IT), University Medical Center Groningen (NL), Radboud University Nijmegen (NL), University of Antwerp (BE), University of Groningen (NL), Vilnius University (LT), Universidade do Porto (PT), Ghent University Hospital (BE), Erasmus MC (NL), Radboud University Medical Center (NL), Italian Institute of Technology (IT), Maastricht University (NL), Radboud Institute for Molecular Life Sciences (NL), Centro Nacional de Análisis Genómico (ES), Telethon Institute Of Genetics And Medicine (IT), i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto (PT), Universitat de Barcelona (ES), University of Tübingen (DE), Newcastle University (GB), University of Lübeck (DE)
Centres de Recerca de Catalunya, European Commission, Eberhard Karls Universität Tübingen, Generalitat de Catalunya, Ministerio de Asuntos Económicos y Transformación Digital, Gobierno de España, Horizon 2020 Framework Programme, Instituto de Salud Carlos III, European Regional Development Fund
Partnerships for the goals
Openalex Percentile: Top 9%
Genomic variations and chromosomal abnormalities
2.75
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