TY - JOUR
T1 - Solving patients with rare diseases through programmatic reanalysis of genome-phenome data
AU - Matalonga, Leslie
AU - Hernandez-Ferrer, Carles
AU - Piscia, Davide
AU - Solve RD SNV Indel Working Group
AU - Schuele, Rebecca
AU - Synofzik, Matthis
AU - Topf, Ana
AU - Vissers, Lisenka E. L. M.
AU - de Voer, Richarda
AU - Solve RD DITF GENTURIS
AU - Solve-RD DITF-ITHACA
AU - Solve RD DITF-euroNMD
AU - Solve-RD-DITF-RND
AU - Tonda, Raul
AU - Laurie, Steven
AU - Fernandez-Callejo, Marcos
AU - Pico, Daniel
AU - Garcia-Linares, Carles
AU - Papakonstantinou, Anastasios
AU - Corvo, Alberto
AU - Joshi, Ricky
AU - Diez, Hector
AU - Gut, Ivo
AU - Hoischen, Alexander
AU - Graessner, Holm
AU - Beltran, Sergi
AU - Solve-RD Consortia
AU - Brunner, Han
N1 - Funding Information:
Funding The Solve-RD project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 779257. Data were analysed using the RD‐ Connect Genome‐Phenome Analysis Platform, which received funding from EU projects RD‐Connect, Solve-RD and EJP-RD (grant numbers FP7 305444, H2020 779257, H2020 825575), Instituto de Salud Carlos III (grant numbers PT13/0001/0044, PT17/0009/0019; Instituto Nacional de Bioinformática, INB) and ELIXIR Implementation Studies. We acknowledge support of the Spanish Ministry of Economy, Industry and Competitiveness (MEIC) to the EMBL partnership, the Centro de Excelencia Severo Ochoa and the CERCA Programme/Generalitat de Catalunya. We also acknowledge the support of the Generalitat de Catalunya through Departament de Salut and Departament d’Empresa i Coneixement and the Co-financing by the Spanish Ministry of Economy, Industry and Competitiveness (MEIC) with funds from the European Regional Development Fund (ERDF) corresponding to the 2014-2020 Smart Growth Operating Program.
Publisher Copyright:
© 2021, The Author(s).
PY - 2021/9
Y1 - 2021/9
N2 - Reanalysis of inconclusive exome/genome sequencing data increases the diagnosis yield of patients with rare diseases. However, the cost and efforts required for reanalysis prevent its routine implementation in research and clinical environments. The Solve-RD project aims to reveal the molecular causes underlying undiagnosed rare diseases. One of the goals is to implement innovative approaches to reanalyse the exomes and genomes from thousands of well-studied undiagnosed cases. The raw genomic data is submitted to Solve-RD through the RD-Connect Genome-Phenome Analysis Platform (GPAP) together with standardised phenotypic and pedigree data. We have developed a programmatic workflow to reanalyse genome-phenome data. It uses the RD-Connect GPAP's Application Programming Interface (API) and relies on the big-data technologies upon which the system is built. We have applied the workflow to prioritise rare known pathogenic variants from 4411 undiagnosed cases. The queries returned an average of 1.45 variants per case, which first were evaluated in bulk by a panel of disease experts and afterwards specifically by the submitter of each case. A total of 120 index cases (21.2% of prioritised cases, 2.7% of all exome/genome-negative samples) have already been solved, with others being under investigation. The implementation of solutions as the one described here provide the technical framework to enable periodic case-level data re-evaluation in clinical settings, as recommended by the American College of Medical Genetics.
AB - Reanalysis of inconclusive exome/genome sequencing data increases the diagnosis yield of patients with rare diseases. However, the cost and efforts required for reanalysis prevent its routine implementation in research and clinical environments. The Solve-RD project aims to reveal the molecular causes underlying undiagnosed rare diseases. One of the goals is to implement innovative approaches to reanalyse the exomes and genomes from thousands of well-studied undiagnosed cases. The raw genomic data is submitted to Solve-RD through the RD-Connect Genome-Phenome Analysis Platform (GPAP) together with standardised phenotypic and pedigree data. We have developed a programmatic workflow to reanalyse genome-phenome data. It uses the RD-Connect GPAP's Application Programming Interface (API) and relies on the big-data technologies upon which the system is built. We have applied the workflow to prioritise rare known pathogenic variants from 4411 undiagnosed cases. The queries returned an average of 1.45 variants per case, which first were evaluated in bulk by a panel of disease experts and afterwards specifically by the submitter of each case. A total of 120 index cases (21.2% of prioritised cases, 2.7% of all exome/genome-negative samples) have already been solved, with others being under investigation. The implementation of solutions as the one described here provide the technical framework to enable periodic case-level data re-evaluation in clinical settings, as recommended by the American College of Medical Genetics.
KW - AMERICAN-COLLEGE
KW - EXOME
KW - INHERITANCE
KW - MEDICAL GENETICS
KW - VARIANTS
U2 - 10.1038/s41431-021-00852-7
DO - 10.1038/s41431-021-00852-7
M3 - Article
C2 - 34075210
SN - 1018-4813
VL - 29
SP - 1337
EP - 1347
JO - European Journal of Human Genetics
JF - European Journal of Human Genetics
IS - 9
ER -