Solving unsolved rare neurological diseases-a Solve-RD viewpoint.
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ABSTRACT:
SUBMITTER: Schule R
PROVIDER: S-EPMC8440537 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Solve-RD – solving the unsolved rare diseases is a research project funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 779257 from 1 January 2018 to 31 March 2024. Six European Reference Networks (ERNs; ERN-RND, -ITHACA, -EuroNMD, -GENTURIS, -RITA and -EpiCare) contributed data and samples to one or more of the four cohorts for data re-analysis and novel omics. For more information see https://solve-rd.eu/results/solve-rd-data/.
| EGAS00001003851 | EGA
Project description: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.
| S-EPMC8440542 | biostudies-literature
Project description:Although individually uncommon, rare diseases (RDs) collectively affect 6-8% of the population. The unmet need of the rare disease community was recognized by the European Commission which in 2012 funded three flagship projects, RD-Connect, NeurOmics, and EURenOmics, to help move the field forward with the ambition of advancing -omics research and data sharing at their core in line with the goals of IRDiRC (International Rare Disease Research Consortium). NeurOmics and EURenOmics generate -omics data and improve diagnosis and therapy in rare renal and neurological diseases, with RD-Connect developing an infrastructure to facilitate the sharing, systematic integration and analysis of these data. Here, we summarize the achievements of these three projects, their impact on the RD community and their vision for the future. We also report from the Joint Outreach Day organized by the three projects on the 3rd of May 2017 in Berlin. The workshop stimulated an open, multi-stakeholder discussion on the challenges of the rare diseases, and highlighted the cross-project cooperation and the common goal: the use of innovative genomic technologies in rare disease research.
| S-EPMC5974013 | biostudies-literature
Project description:Tripartite motif (TRIM) proteins are RING E3 ubiquitin ligases defined by a shared domain structure. Several of them are implicated in rare genetic diseases, and mutations in TRIM32 and TRIM-like malin are associated with Limb-Girdle Muscular Dystrophy R8 and Lafora disease, respectively. These two proteins are evolutionary related, share a common ancestor, and both display NHL repeats at their C-terminus. Here, we revmniew the function of these two related E3 ubiquitin ligases discussing their intrinsic and possible common pathophysiological pathways.
| S-EPMC8067510 | biostudies-literature
Project description: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.
| S-EPMC8440686 | biostudies-literature
Project description:The development of personalised medicine is of considerable importance for paediatric patient populations, and represents a move away from the use of treatment dosages based on experience with the same compounds in adults. Currently, however, we know little about developmental pharmacogenomics and, although many biomarkers are available for clinical research use, there have been few applications in the management of paediatric diseases. This paper reviews where we are in the journey towards achieving paediatric personalised medicine and describes a group of diseases requiring such an approach. The personalised medicine approach is particularly relevant for the treatment of rare childhood diseases, and the group of life-threatening neurological disorders known as lysosomal storage diseases represents a potential study population. The genetic bases of these disorders are generally well defined, there is the potential for diagnosis at birth or prenatally, and there are a range of therapeutic options available or under development.
| S-EPMC3405387 | biostudies-other
Project description:BackgroundIn 2017, the German Academy for Rare Neurological Diseases (Deutsche Akademie für Seltene Neurologische Erkrankungen; DASNE) was founded to pave the way for an optimized personalized management of patients with rare neurological diseases (RND) in all age groups. Since then a dynamic national network for rare neurological disorders has been established comprising renowned experts in neurology, pediatric neurology, (neuro-) genetics and neuroradiology. DASNE has successfully implemented case presentations and multidisciplinary discussions both at yearly symposia and monthly virtual case conferences, as well as further educational activities covering a broad spectrum of interdisciplinary expertise associated with RND. Here, we present recommendation statements for optimized personalized management of patients with RND, which have been developed and reviewed in a structured Delphi process by a group of experts.MethodsAn interdisciplinary group of 37 RND experts comprising DASNE experts, patient representatives, as well as healthcare professionals and managers was involved in the Delphi process. First, an online collection was performed of topics considered relevant for optimal patient care by the expert group. Second, a two-step Delphi process was carried out to rank the importance of the selected topics. Small interdisciplinary working groups then drafted recommendations. In two consensus meetings and one online review round these recommendations were finally consented.Results38 statements were consented and grouped into 11 topics: health care structure, core neurological expertise and core mission, interdisciplinary team composition, diagnostics, continuous care and therapy development, case conferences, exchange / cooperation between Centers for Rare Diseases and other healthcare partners, patient advocacy group, databases, translation and health policy.ConclusionsThis German interdisciplinary Delphi expert panel developed consented recommendations for optimal care of patients with RND in a structured Delphi process. These represent a basis for further developments and adjustments in the health care system to improve care for patients with RND and their families.
| S-EPMC10863275 | biostudies-literature
Project description:The complex biology of neurological diseases calls for collaborative efforts that may increase the success rate of clinical research. Models have been proposed, but concrete actions remain insufficient. Based on recent considerations from basic science, from science of patient input and from an analysis of scientific resources in Italy, we here explain why our country may represent an appropriate environment for such actions. Furthermore, we sketch operational framework and business model to be applied in order to accelerate, in parallel, the development of therapies in common and rare diseases.
| S-EPMC7160195 | biostudies-literature
Project description:Structural variants (SVs), including large deletions, duplications, inversions, translocations, and more complex events have the potential to disrupt gene function resulting in rare disease. Nevertheless, current pipelines and clinical decision support systems for exome sequencing (ES) tend to focus on small alterations such as single nucleotide variants (SNVs) and insertions-deletions shorter than 50 base pairs (indels). Additionally, detection and interpretation of large copy-number variants (CNVs) are frequently performed. However, detection of other types of SVs in ES data is hampered by the difficulty of identifying breakpoints in off-target (intergenic or intronic) regions, which makes robust identification of SVs challenging. In this paper, we demonstrate the utility of SV calling in ES resulting in a diagnostic yield of 0.4% (23 out of 5825 probands) for a large cohort of unsolved patients collected by the Solve-RD consortium. Remarkably, 8 out of 23 pathogenic SV were not found by comprehensive read-depth-based CNV analysis, resulting in a 0.13% increased diagnostic value.
| S-EPMC11291474 | biostudies-literature