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Solving the unsolved Rare Diseases

Periodic Reporting for period 2 - Solve-RD (Solving the unsolved Rare Diseases)

Reporting period: 2019-07-01 to 2020-12-31

“Solve-RD – solving the unsolved rare diseases” is a research project funded by the European Commission for five years (2018-2022). It echoes the ambitious goals set out by the International Rare Diseases Research Consortium (IRDiRC) to deliver diagnostic tests for most rare diseases by 2020. The current diagnostic and subsequent therapeutic management of rare diseases is still highly unsatisfactory for a large proportion of rare disease patients – the unsolved rare disease cases. For these unsolved rare diseases, we are unable to explain the etiology responsible for the disease phenotype, predict the individual disease risk and/or rate of disease progression, and/or quantitate the risk of relatives to develop the same disorder.
Our main ambitions are thus
• to solve large numbers of rare diseases, for which a molecular cause is not known yet by sophisticated combined omics approaches, and
• to improve diagnostics of rare disease patients through contribution to, participation in and implementation of a “genetic knowledge web” based on shared knowledge about genes, genomic variants and phenotypes.
Solve-RD fully integrates with the newly formed European Reference Networks (ERNs) for rare diseases. Four ERNs (ERN-RND, -EURO-NMD, -ITHACA, and -GENTURIS) build the core of Solve-RD but we will reach out to patient cohorts across all 24 ERNs as well as the undiagnosed disease programs in order to achieve our aims.
Solve-RD identified 3 main challenges and will deliver 7 implementation steps to address these challenges in work packages 1-3:
Challenge 1: Accessibility of unsolved rare disease cohorts with comprehensive genetic and phenotypic data
Challenge 2: New and improved approaches for the discovery of novel molecular causes
Challenge 3: Translate discoveries to patients’ live and clinical practice
From July 2019 to December 2020, Solve-RD continued to implement the activities addressing the three challenges.
We collected 10,340 datasets (phenotypic and exome/genome sequencing data) from unsolved rare disease patients and their family members. Standardised phenotypic information (HPO, ORDO and OMIM encoded) has been collected via the newly released RD-Connect GPAP PhenoStore module. HPO terms have been extended to cover Solve-RD ERNs’ needs.
We have continued producing and enriching the Rare Disease Case Ontology (RDCO). Up to now, RDCO has been populated with >150,000 similarity associations.
The Data Analysis Task Force (DATF) working groups established the latest data analysis tools and re-analysed 8,346 exomes and genomes (4,459 index cases) from unsolved rare disease patients and their family members submitted by Solve-RD partners. The four Data Interpretation Task Forces (DITFs) – one per core ERN – conduct interpretation of the variants delivered by the working groups. This collaborative effort has led to the diagnosis of 178 cases included in freeze 1. This is already a 4 % additional diagnostic rate although many of the analyses and evaluations are still ongoing.
Service providers have been chosen for all novel omics technologies (except LR-RNAseq). SR-WGS analyses started in 2020. SOPs for biomaterials have been shared with the DITFs andthe DITFs have been active in identifying their ultra-rare RDs, by exchanging for the ‘most special RD cases within their ERN’. First cases have been identified and send for WGS analysis.
The RDMM-Europe brokerage service established a two committee process to select novel RD genes discovered by Solve-RD partners and to find model organism investigators to functionally validate these genes. So far, 14 Seeding Grants have been awarded.
In order to co-design interventions and services to support health professionals effectively sharing genomic sequencing information with families, we identified areas of current services in need of improvement and co-designed interventions/service models to address these needs. This had resulted in the production of two short films on families’ experiences and recommendations and four prototypes of quality improvement interventions.
A workshop has been organized to discuss genomic medicine in health economics but also in sociology. Based on this workshop and on a systematic literature review the “European Conference on the Diffusion of Genomic Medicine: Health Economics & Policy” was planned but had to be postponed to 2021.
The Treatabolome database has been established to make information about treatable genes and variants of RDs accessible and to improve the visibility of existing variant-specific treatment options at the time of diagnosis to clinicians and their patients.
The data flow system has been adapted and generalized involving GPAP, the EGA, omics service providers and the sandbox/RD3. The data analysis sandbox has been upgraded considerably. A ‘FUSE’ connection to EGA allows remote data access for data analysis. The sandbox data architecture/model called RD3 has been extended to accommodate additional metadata, especially to meet the needs of managing novel omics data. Finally, to bring all datasets into clearer vision and allow powerful ways to find related cases, a data discovery layer has been assembled and launched.
Solve-RD meets the biggest challenge of diagnosing patients with rare diseases since the implementation of NGS technology. Despite extensive studies of Whole Exome Sequencing (WES) in numerous rare disease patient cohorts, ~50% of all patients remain unsolved. By applying comprehensive advanced bioinformatics algorithms in four major patient cohorts we anticipate to increase diagnostic yield by about 3-5%. So far, we have managed to solve 178 cases among the 4,459 cases included in freeze 1. This is already a 4 % additional diagnostic rate although many of the analyses and evaluations are still ongoing.
The extension of DNA analysis from WES to Whole Genome Sequencing (WGS) in >2,500 well characterized patients will raise this sensitivity to about 60-70%. WGS bioinformatics developed together with RD-Connect will lead to a world-wide not yet available, standardised analytical tool on how to approach genome data for structural variants. Also, no standardised multi-omics approach exists so far; neither at the experimental nor at the bioinformatics level. Solve-RD will develop specific strategies for the different patient cohorts to cope with these complex analyses and addressing simultaneously cost-effective issues. The connection of sophisticated diagnostic approaches will only be successful with deep phenotyping of patient cohorts. The participating and the associated ERNs will select cohorts of >800 unsolved patients with highly peculiar (ultra-rare) phenotypes, increasing the chance to find novel disease genes and novel disease mechanisms. We anticipate to solve >2,000 cases which will translate in a number of new genes and disease mechanisms to be discovered in the course of Solve-RD. Finding further patients with mutations in the newly discovered disease genes will be secured by newly developed matchmaking approaches and by screening in the >20,000 unclassified patients of the ERNs. For the first time in Europe we established a novel brokerage structure connecting clinicians, gene discoverer and basic researchers in a highly flexible and efficient way to quickly verify novel genes and disease mechanisms. To communicate genomic sequencing information with families, an evidence based approach has been conducted.
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