Elizabeth Emma Palmer, Helene Cederroth, Mikk Cederroth, Angelica Maria Delgado-Vega, Natalie Roberts, Fulya Taylan, Ann Nordgren, Lorenzo D Botto
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引用次数: 0
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.
NPJ Genomic MedicineBiochemistry, Genetics and Molecular Biology-Molecular Biology
CiteScore
9.40
自引率
1.90%
发文量
67
审稿时长
17 weeks
期刊介绍:
npj Genomic Medicine is an international, peer-reviewed journal dedicated to publishing the most important scientific advances in all aspects of genomics and its application in the practice of medicine.
The journal defines genomic medicine as "diagnosis, prognosis, prevention and/or treatment of disease and disorders of the mind and body, using approaches informed or enabled by knowledge of the genome and the molecules it encodes." Relevant and high-impact papers that encompass studies of individuals, families, or populations are considered for publication. An emphasis will include coupling detailed phenotype and genome sequencing information, both enabled by new technologies and informatics, to delineate the underlying aetiology of disease. Clinical recommendations and/or guidelines of how that data should be used in the clinical management of those patients in the study, and others, are also encouraged.