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

2021 ◽  
Author(s):  
Birte Zurek ◽  
◽  
Kornelia Ellwanger ◽  
Lisenka E. L. M. Vissers ◽  
Rebecca Schüle ◽  
...  
Keyword(s):  
Rare Disease ◽  
Rare Diseases ◽  
Disease Genes ◽  
Minimum Requirement ◽  
Horizon 2020 ◽  
European Reference Networks ◽  
Patient Representatives ◽  
Reference Networks ◽  
Collaborative Analysis ◽  
First Time

AbstractFor 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.

scholarly journals A resource to explore the discovery of rare diseases and their causative genes

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Friederike Ehrhart ◽  
Egon L. Willighagen ◽  
Martina Kutmon ◽  
Max van Hoften ◽  
Leopold M. G. Curfs ◽  
...  
Keyword(s):  
Rare Disease ◽  
Rare Diseases ◽  
Genetic Background ◽  
Gene Discovery ◽  
Google Scholar ◽  
Semantic Model ◽  
Causative Gene ◽  
Scientific Publications ◽  
Monogenic Diseases ◽  
First Time

AbstractHere, we describe a dataset with information about monogenic, rare diseases with a known genetic background, supplemented with manually extracted provenance for the disease itself and the discovery of the underlying genetic cause. We assembled a collection of 4166 rare monogenic diseases and linked them to 3163 causative genes, annotated with OMIM and Ensembl identifiers and HGNC symbols. The PubMed identifiers of the scientific publications, which for the first time described the rare diseases, and the publications, which found the genes causing the diseases were added using information from OMIM, PubMed, Wikipedia, whonamedit.com, and Google Scholar. The data are available under CC0 license as spreadsheet and as RDF in a semantic model modified from DisGeNET, and was added to Wikidata. This dataset relies on publicly available data and publications with a PubMed identifier, but by our effort to make the data interoperable and linked, we can now analyse this data. Our analysis revealed the timeline of rare disease and causative gene discovery and links them to developments in methods.

scholarly journals Orphanet – Information, Education and Expert Centres for Rare Diseases / Orphanet – informovanosť, vzdelávanie a špecializované centrá starostlivosti o pacientov so ZCH

2013 ◽  
Vol 60 (Supplementum-VIII) ◽  
pp. 10-15
Author(s):  
L. Kovács ◽  
E. Hegyi ◽  
G. Nagyová
Keyword(s):  
Rare Diseases ◽  
National Level ◽  
Quality Criteria ◽  
Basic Data ◽  
Current Status ◽  
Paper Briefly ◽  
European Reference Networks ◽  
Reference Networks ◽  
Centres Of Expertise

The paper briefly describes the role of Orphanet as an informational and educational source for rare diseases. Most attention is given to the Centres of Expertise and European Reference Networks. The authors suggest an easy procedure how to get the basic data about the readiness of the clinics to be recognised for Centres of Expertise at the national level. EUCERD recommendations on quality criteria for centres of expertise are introduced. The coordinators of the potential Centres of Expertise should be contacted and asked to fill in the questionnaire designed to check whether the centre matches the EUCERD recommendations or not. In order for the process to be transparent, the selection criteria of expert resources are listed on national website (www.orphanet.sk). The analysis of the questionnaires has to be carried out at the national level, to map the basic data about the current status. One questionnaire per department or clinic shall be filled in order to allow the evaluation. Clinics will be divided in two groups the ones which achieved the threshold and could be recognised as Centres of Expertise at the National level and the ones which need to be further monitored to reach the threshold.

scholarly journals History of rare diseases and their genetic causes - a data driven approach

2019 ◽  
Author(s):  
Friederike Ehrhart ◽  
Egon L. Willighagen ◽  
Martina Kutmon ◽  
Max van Hoften ◽  
Nasim Bahram Sangani ◽  
...  
Keyword(s):  
Rare Disease ◽  
Rare Diseases ◽  
Scientific Publication ◽  
Data Driven ◽  
Semantic Model ◽  
Genetic Causes ◽  
Monogenic Diseases ◽  
Data Driven Approach ◽  
History Of ◽  
First Time

AbstractThis dataset provides information about monogenic, rare diseases with a known genetic cause supplemented with manually extracted provenance of both the disease and the discovery of the underlying genetic cause of the disease.We collected 4166 rare monogenic diseases according to their OMIM identifier, linked them to 3163 causative genes which are annotated with Ensembl identifiers and HGNC symbols. The PubMed identifier of the scientific publication, which for the first time describes the rare disease, and the publication which found the gene causing this disease were added using information from OMIM, Wikipedia, Google Scholar, Whonamedit, and PubMed. The data is available as a spreadsheet and as RDF in a semantic model modified from DisGeNET.This dataset relies on publicly available data and publications with a PubMed IDs but this is to our knowledge the first time this data has been linked and made available for further study under a liberal license. Analysis of this data reveals the timeline of rare disease and causative genes discovery and links them to developments in methods and databases.

scholarly journals The context for the thematic grouping of rare diseases to facilitate the establishment of European Reference Networks

2016 ◽  
Vol 11 (1) ◽  
Author(s):  
Teresinha Evangelista ◽  
Victoria Hedley ◽  
Antonio Atalaia ◽  
Matt Johnson ◽  
Stephen Lynn ◽  
...  
Keyword(s):  
Rare Diseases ◽  
European Reference Networks ◽  
Reference Networks

scholarly journals Shaping the Future of Rare Diseases after a Global Health Emergency: Organisational Points to Consider

2020 ◽  
Vol 17 (22) ◽  
pp. 8694
Author(s):  
Rosaria Talarico ◽  
Diana Marinello ◽  
Sara Cannizzo ◽  
Andrea Gaglioti ◽  
Simone Ticciati ◽  
...  
Keyword(s):  
Rare Diseases ◽  
Routine Care ◽  
Lessons Learned ◽  
Negative Effects ◽  
Future Health ◽  
Appropriate Care ◽  
European Reference Networks ◽  
Health Related ◽  
Reference Networks ◽  
Multi Stakeholder

The unexpected outbreak of the COVID-19 disease had significant and enormous repercussions on the healthcare systems, such as the need to reorganise healthcare organisations in order to concentrate resources needed to the care of COVID-19 patients and to respond in general to this health emergency. Due to these challenges, the care of several chronic conditions was in many cases discontinued and patients and healthcare professionals treating these conditions had to cope with this new scenario. This was the case of the world rare diseases (RDs) that had to face this global emergency despite the vulnerability of people with RDs and the well-known need for high expertise required to treat and manage them. The numerous lessons learned so far regarding health emergencies and RDs should represent the basis for the establishment of new healthcare policies and plans aimed at ensuring the preparedness of our health systems in providing appropriate care to people living with RDs in the case of eventual new emergencies. This paper aims at providing pragmatic considerations that might be useful in designing future actions to create or optimise existing organisational models for the care of RDs in case of future emergencies or any other situation that might threaten the provision of routine care. These policies and plans should benefit from the multi-stakeholder RDs networks (such as the European Reference Networks), that should join forces at European, national, and local levels to minimise the economic, organisational, and health-related impact and the negative effects of potential emergencies on the RDs community. In order to design and develop these policies and plans, a decalogue of points to consider were developed to ensure appropriate care for people living with RDs in the case of eventual future health emergencies.

scholarly journals The EuRRECa Project as a Model for Data Access and Governance Policies for Rare Disease Registries That Collect Clinical Outcomes

2020 ◽  
Vol 17 (23) ◽  
pp. 8743
Author(s):  
Salma R. Ali ◽  
Jillian Bryce ◽  
Li En Tan ◽  
Olaf Hiort ◽  
Alberto M. Pereira ◽  
...  
Keyword(s):  
Rare Disease ◽  
Health Care Professionals ◽  
Good Practice ◽  
Data Access ◽  
Data Governance ◽  
European Reference Networks ◽  
International Setting ◽  
Reference Networks ◽  
Improving Patient Care ◽  
Governance Infrastructure

Rare disease (RD) registries are important platforms that facilitate communication between health care professionals, patients and other members of the multidisciplinary team. RD registries enable data sharing and promotion of research and audits, often in an international setting, with the overall aim of improving patient care. RD registries also have a fundamental role in supporting the work of clinical networks such as the European Reference Networks (ERNs) for rare diseases. With the recent expansion of RD registries, it has become even more essential to outline standards of good practice in relation to governance, infrastructure, documentation, training, audits and adopting the Findable, Accessible, Interoperable and Reusable (FAIR) data principles to maintain registries of high quality. For the purpose of this paper, we highlight vital aspects of data access and data governance policies for RD registries, using the European Registries for Rare Endocrine Conditions (EuRRECa) as an example of a project that aims to promote good standards of practice for improving the quality of utilization of RD registries.

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