Solving the unsolved Rare Diseases

Project Information

Solve-RD

Grant agreement ID: 779257

DOI

10.3030/779257

Project closed

EC signature date 27 November 2017

Start date 1 January 2018

End date 31 March 2024

Funded under

• SOCIETAL CHALLENGES - Health, demographic change and well-being

Total cost

€ 15 361 621,25

EU contribution

€ 15 361 621,25

Coordinated by

EBERHARD KARLS UNIVERSITAET TUEBINGEN
Germany

Periodic Reporting for period 5 - Solve-RD (Solving the unsolved Rare Diseases)

Reporting period: 2023-10-01 to 2024-03-31

Summary of the context and overall objectives of the project

Rare diseases (RD) are individually rare but collectively frequent, affecting the lives of 30 million people in Europe. These disorders cause a variety of medical problems and are associated with high morbidity, mortality, and economic burden. Time to diagnosis often takes years and initial diagnoses are incorrect in up to 40% of families. Molecularly confirmed diagnoses have not been found yet for ~50% of RD patients.
Solve-RD’ s main aim is to solve unsolved RD. This is not only associated with the improvement of diagnostic yield but also with the discovery of novel disease mechanisms which will allow comprehensive pathogenicity studies including disease modeling, biomarker development, pathogenicity-based subgrouping of patients for clinical trials, and the targeted approach to interfere with disease pathways.
“Solve-RD – solving the unsolved rare diseases” has been a research project funded by the European Commission from 01.01.2018 to 31.03.2024. It pursued two major approaches: (i) data reanalysis of >20,000 unsolved RD patients and (ii) novel combined -omics approaches.
In order to achieve its main aim, Solve-RD has tightly collaborated with the European Reference Networks (ERNs) for rare diseases and partnered with 6 ERNs as well as 2 national undiagnosed disease programs.
Solve-RD has addressed the associated research challenges across the entire value chain of the RD diagnostic research path and has delivered in terms of increase of diagnostic yield, by developing novel improved workflows that are being transferred in to the diagnostic setting but also infrastructurally by establishing a European RD diagnostic research platform.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

In summary, the following results have been achieved by Solve-RD:
24,519 datasets (phenotypic & exome/genome sequencing data) from unsolved RD patients and family members have been collected and processed through the RD-Connect GPAP standard analysis pipeline. Phenotypic information is standardized (HPO, ORDO & OMIM encoded).
The RD cases ontology (RDCO) has been developed. A phenotypic similarity-based approach for variant prioritization for unsolved RD has been applied. Clusters of similarity can be visualized in the newly developed OrphaScape tool which is included in the RD-Connect GPAP.
Data Analysis Task Force (DATF) working groups have been established to reanalyse exome and/or genome data and to analyse newly generated omics data. The Data Interpretation Task Forces (DITFs) – one per ERN – conduct interpretation of the variants delivered by the DATF. The reanalysis approach as well as the structures established have been published in a series of papers in the EJHG. A manuscript with results of reanalysis of data freeze 1 and 2 has been provisionally accepted by Nature Medicine: reanalysis and ad-hoc expert review for about 10,000 undiagnosed individuals from more than 6,000 families resulted in overall diagnostic yield of 12.6%. Systematic reanalysis contributed to this by establishing a genetic diagnosis in 8.5% of the families.
The Solvathon concept has been established as a new and successful format of DATF-DITF-interaction.
Following a market consultation, service providers have been chosen for all novel omics technologies. In total >4,700 samples have centrally been collected, processed and raw data has been returned and analysed by DATF working groups. A promising new technology termed ‘optical genome mapping’ (OGM) was added to the Solve-RD novel omics portfolio. Data analysis and interpretation continues also after the Solve-RD project end as core partners remain committed.
The RDMM-Europe brokerage service connected Solve-RD partners with model organism scientists and provided Seeding Grant funding for 33 functional gene validation projects. An overview paper has been published in Nature LabAnimal; 5 projects have already been published and 2 received follow-up funding.
The co-designed models for the communication of genomic results for RD have been published. The main finding at both study sites in the CZ and the UK was the identification of post-test care as the shared priority for improvement for both health professionals and families.
The conference ECOgenomics brought together researchers from the human sciences (mainly health economics), but also researchers from other disciplines.
A clinical utility study assessing whether WGS is a better first-tier genetic diagnostic test than current standard of care for neurodevelopmental disorders has been published.
The Treatabolome database has been established and linked to the RD-Connect GPAP. It makes information about treatable genes and variants of RDs accessible and improves the visibility of existing variant-specific treatment options at the time of diagnosis. The Treatabolome includes data from 10 systematic literature reviews.
A data infrastructure, with scalable potential, has been employed to fully support the needs of the project. It uses and adapts software, databases, standards and analysis tools from RD-Connect GPAP (for genomics data processing), the EGA (for archival and sharing purposes), the MOLGENIS and Café Variome platforms (for discovery, access and analytical method development using the sandbox and RD3), along with omics service providers and local analysis clusters (for integrative case diagnostics). A manuscript that describes the design concept and progressive maturation of the Solve-RD data infrastructure has been accepted for publication in GigaScience.
Recommendations for whole genome sequencing in diagnostics for RD have been developed and published.
EURORDIS organised two Winter Schools with the aim to deepen patient representatives’ understanding of how pre-clinical research translates into real benefits for RD patients. The Patient Journey Diagram developed by the CETF is now available in 29 languages.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

Solve-RD addresses the biggest challenge of diagnosing patients with RD since the implementation of NGS technology. Despite extensive studies of WES in numerous RD patient cohorts, at least 50% of all patients remain unsolved.
Solve-RD addresses this challenge across the entire value chain of the RD diagnostic research path. This starts by transferring unsolved RD patients to Solve-RD and includes (i) logistics and processes of a European RD diagnostic research platform, (ii) novel omics data generation and data (re-)analysis and interpretation, (iii) development and validation of novel optimised workflows for RD diagnosis that adopt innovative sequencing methodologies such as OGM and long read WGS, and (iv) return of research results and research in patient-centred communication of genomic test results.
Ultimately, these approaches led to an increase in diagnostic yield of >14.25% for the Solve-RD cohort. The diagnostic yield can not only be raised to at least 65% but also enables the identification of patients eligible for innovative treatments or therapy developments.
By developing and implementing the Solve-RD diagnostic research platform and associated diagnostic research workflows the requirements for a systematic European use and scale-up of these achievements in the European Rare Disease Research Alliance (ERDERA) have been met and provide the basis for a successful transition of optimised workflows into the standard diagnostic setting.

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