0
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Equity in action: The Diagnostic Working Group of The Undiagnosed Diseases Network International

      review-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Rare diseases are recognized as a global public health priority. A timely and accurate diagnosis is a critical enabler for precise and personalized health care. However, barriers to rare disease diagnoses are especially steep for those from historically underserved communities, including low- and middle-income countries. The Undiagnosed Diseases Network International (UDNI) was launched in 2015 to help fill the knowledge gaps that impede diagnosis for rare diseases, and to foster the translation of research into medical practice, aided by active patient involvement. To better pursue these goals, in 2021 the UDNI established the Diagnostic Working Group of the UDNI (UDNI DWG) as a community of practice that would (a) accelerate diagnoses for more families; (b) support and share knowledge and skills by developing Undiagnosed Diseases Programs, particularly those in lower resource areas; and (c) promote discovery and expand global medical knowledge. This Perspectives article documents the initial establishment and iterative co-design of the UDNI DWG.

          Related collections

          Most cited references34

          • Record: found
          • Abstract: found
          • Article: not found

          Standards and Guidelines for the Interpretation of Sequence Variants: A Joint Consensus Recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology

          The American College of Medical Genetics and Genomics (ACMG) previously developed guidance for the interpretation of sequence variants. 1 In the past decade, sequencing technology has evolved rapidly with the advent of high-throughput next generation sequencing. By adopting and leveraging next generation sequencing, clinical laboratories are now performing an ever increasing catalogue of genetic testing spanning genotyping, single genes, gene panels, exomes, genomes, transcriptomes and epigenetic assays for genetic disorders. By virtue of increased complexity, this paradigm shift in genetic testing has been accompanied by new challenges in sequence interpretation. In this context, the ACMG convened a workgroup in 2013 comprised of representatives from the ACMG, the Association for Molecular Pathology (AMP) and the College of American Pathologists (CAP) to revisit and revise the standards and guidelines for the interpretation of sequence variants. The group consisted of clinical laboratory directors and clinicians. This report represents expert opinion of the workgroup with input from ACMG, AMP and CAP stakeholders. These recommendations primarily apply to the breadth of genetic tests used in clinical laboratories including genotyping, single genes, panels, exomes and genomes. This report recommends the use of specific standard terminology: ‘pathogenic’, ‘likely pathogenic’, ‘uncertain significance’, ‘likely benign’, and ‘benign’ to describe variants identified in Mendelian disorders. Moreover, this recommendation describes a process for classification of variants into these five categories based on criteria using typical types of variant evidence (e.g. population data, computational data, functional data, segregation data, etc.). Because of the increased complexity of analysis and interpretation of clinical genetic testing described in this report, the ACMG strongly recommends that clinical molecular genetic testing should be performed in a CLIA-approved laboratory with results interpreted by a board-certified clinical molecular geneticist or molecular genetic pathologist or equivalent.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            Estimating cumulative point prevalence of rare diseases: analysis of the Orphanet database

            Rare diseases, an emerging global public health priority, require an evidence-based estimate of the global point prevalence to inform public policy. We used the publicly available epidemiological data in the Orphanet database to calculate such a prevalence estimate. Overall, Orphanet contains information on 6172 unique rare diseases; 71.9% of which are genetic and 69.9% which are exclusively pediatric onset. Global point prevalence was calculated using rare disease prevalence data for predefined geographic regions from the ‘Orphanet Epidemiological file’ (http://www.orphadata.org/cgi-bin/epidemio.html). Of the 5304 diseases defined by point prevalence, 84.5% of those analysed have a point prevalence of <1/1 000 000. However 77.3–80.7% of the population burden of rare diseases is attributable to the 4.2% (n = 149) diseases in the most common prevalence range (1–5 per 10 000). Consequently national definitions of ‘Rare Diseases’ (ranging from prevalence of 5 to 80 per 100 000) represent a variable number of rare disease patients despite sharing the majority of rare disease in their scope. Our analysis yields a conservative, evidence-based estimate for the population prevalence of rare diseases of 3.5–5.9%, which equates to 263–446 million persons affected globally at any point in time. This figure is derived from data from 67.6% of the prevalent rare diseases; using the European definition of 5 per 10 000; and excluding rare cancers, infectious diseases, and poisonings. Future registry research and the implementation of rare disease codification in healthcare systems will further refine the estimates.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Mendelian Gene Discovery: Fast and Furious with No End in Sight

              Gene discovery for Mendelian conditions (MCs) offers a direct path to understanding genome function. Approaches based on next-generation sequencing applied at scale have dramatically accelerated gene discovery and transformed genetic medicine. Finding the genetic basis of ∼6,000–13,000 MCs yet to be delineated will require both technical and computational innovation, but will rely to a larger extent on meaningful data sharing.
                Bookmark

                Author and article information

                Contributors
                Elizabeth.palmer@unsw.edu.au
                Journal
                NPJ Genom Med
                NPJ Genom Med
                NPJ Genomic Medicine
                Nature Publishing Group UK (London )
                2056-7944
                5 July 2024
                5 July 2024
                2024
                : 9
                : 37
                Affiliations
                [1 ]Discipline of Paediatrics and Child Health, School of Clinical Medicine, Faculty of Medicine and Health, University of New South Wales, ( https://ror.org/03r8z3t63) Sydney, NSW Australia
                [2 ]Centre for Clinical Genetics, Sydney Childrens’ Hospitals Network, ( https://ror.org/04d87y574) Sydney, NSW Australia
                [3 ]Wilhelm Foundation, Stockholm, Sweden
                [4 ]Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, ( https://ror.org/056d84691) Stockholm, Sweden
                [5 ]Department of Clinical Genetics and Genomics, Karolinska University Hospital, ( https://ror.org/00m8d6786) Stockholm, Sweden
                [6 ]Institute of Biomedicine, Department of Laboratory Medicine, University of Gothenburg, ( https://ror.org/01tm6cn81) Gothenburg, Sweden
                [7 ]Department of Clinical Genetics and Genomics, Sahlgrenska University Hospital, ( https://ror.org/04vgqjj36) Gothenburg, Sweden
                [8 ]Division of Medical Genetics, Department of Pediatrics, University of Utah, ( https://ror.org/03r0ha626) Salt Lake City, Utah USA
                Author information
                http://orcid.org/0000-0003-1844-215X
                http://orcid.org/0009-0004-0295-5545
                http://orcid.org/0009-0000-9906-4589
                http://orcid.org/0000-0002-2907-0235
                http://orcid.org/0000-0003-3285-4281
                Article
                422
                10.1038/s41525-024-00422-y
                11224220
                38965249
                13e401d2-f0ef-4b94-8568-a5c2571dce85
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 30 November 2023
                : 29 May 2024
                Categories
                Perspective
                Custom metadata
                © Springer Nature Limited and Centre of Excellence in Genomic Medicine Research, King Abdulaziz University 2024

                molecular medicine,genetic testing
                molecular medicine, genetic testing

                Comments

                Comment on this article