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. 2021 Sep;29(9):1325-1331.
doi: 10.1038/s41431-021-00859-0. Epub 2021 Jun 1.

Solve-RD: systematic pan-European data sharing and collaborative analysis to solve rare diseases

Birte Zurek  1 , Kornelia Ellwanger  1 , Lisenka E L M Vissers  2   3 , Rebecca Schüle  4   5 , Matthis Synofzik  4   5 , Ana Töpf  6 , Richarda M de Voer  2   7 , Steven Laurie  8 , Leslie Matalonga  8 , Christian Gilissen  2   7 , Stephan Ossowski  1 , Peter A C 't Hoen  7   9 , Antonio Vitobello  10 , Julia M Schulze-Hentrich  1 , Olaf Riess  1   11 , Han G Brunner  2   3   12 , Anthony J Brookes  13 , Ana Rath  14 , Gisèle Bonne  15 , Gulcin Gumus  16 , Alain Verloes  17 , Nicoline Hoogerbrugge  2   7 , Teresinha Evangelista  15 , Tina Harmuth  1 , Morris Swertz  18 , Dylan Spalding  19 , Alexander Hoischen  2   7   20 , Sergi Beltran  8   21   22 , Holm Graessner  23   24 ; Solve-RD consortium
Collaborators, Affiliations

Solve-RD: systematic pan-European data sharing and collaborative analysis to solve rare diseases

Birte Zurek et al. Eur J Hum Genet. 2021 Sep.

Erratum in

  • Correction to: Solve-RD: systematic pan-European data sharing and collaborative analysis to solve rare diseases.
    Zurek B, Ellwanger K, Vissers LELM, Schüle R, Synofzik M, Töpf A, de Voer RM, Laurie S, Matalonga L, Gilissen C, Ossowski S, 't Hoen PAC, Vitobello A, Schulze-Hentrich JM, Riess O, Brunner HG, Brookes AJ, Rath A, Bonne G, Gumus G, Verloes A, Hoogerbrugge N, Evangelista T, Harmuth T, Swertz M, Spalding D, Hoischen A, Beltran S, Graessner H; Solve-RD consortium. Zurek B, et al. Eur J Hum Genet. 2021 Sep;29(9):1459-1461. doi: 10.1038/s41431-021-00936-4. Eur J Hum Genet. 2021. PMID: 34385672 Free PMC article. No abstract available.

Abstract

For the first time in Europe hundreds of rare disease (RD) experts team up to actively share and jointly analyse existing patient's data. Solve-RD is a Horizon 2020-supported EU flagship project bringing together >300 clinicians, scientists, and patient representatives of 51 sites from 15 countries. Solve-RD is built upon a core group of four European Reference Networks (ERNs; ERN-ITHACA, ERN-RND, ERN-Euro NMD, ERN-GENTURIS) which annually see more than 270,000 RD patients with respective pathologies. The main ambition is to solve unsolved rare diseases for which a molecular cause is not yet known. This is achieved through an innovative clinical research environment that introduces novel ways to organise expertise and data. Two major approaches are being pursued (i) massive data re-analysis of >19,000 unsolved rare disease patients and (ii) novel combined -omics approaches. The minimum requirement to be eligible for the analysis activities is an inconclusive exome that can be shared with controlled access. The first preliminary data re-analysis has already diagnosed 255 cases form 8393 exomes/genome datasets. This unprecedented degree of collaboration focused on sharing of data and expertise shall identify many new disease genes and enable diagnosis of many so far undiagnosed patients from all over Europe.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1. Solve-RD data infrastructure.
Key components of the Solve-RD infrastructure for multi-omics data analysis, illustrating main use and data available.
Fig. 2
Fig. 2. The Solve-RD data analysis structure ‘in action’.
Consisting of the Data Analysis Task Force (DATF) and four Data Interpretation Task Forces (DITF)—one per core ERN involved. The DATF established working groups (WGs) for specific analyses. Working groups and DITFs jointly work on analysis projects based on use cases described by the DITF members.
Fig. 3
Fig. 3. Organisation of new result flow in Solve-RD.
Working groups (WG) 1–5 will re-analyse existing sequencing data. Novel omics data will be analysed by all working groups (as appropriate). RD-REAL refers to Rare Disease - REAnalysis Logistics.
See this image and copyright information in PMC

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