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The Undiagnosed Diseases Network: Accelerating Discovery about Health and Disease.
Ramoni, Rachel B; Mulvihill, John J; Adams, David R; Allard, Patrick; Ashley, Euan A; Bernstein, Jonathan A; Gahl, William A; Hamid, Rizwan; Loscalzo, Joseph; McCray, Alexa T; Shashi, Vandana; Tifft, Cynthia J; Wise, Anastasia L.
Afiliação
  • Ramoni RB; Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA; Department of Epidemiology and Health Promotion, New York University College of Dentistry, New York, NY 10010, USA. Electronic address: rachelramoni@nyu.edu.
  • Mulvihill JJ; National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA.
  • Adams DR; National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA.
  • Allard P; Institute for Society and Genetics, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Environmental Health Sciences, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA 90095 USA.
  • Ashley EA; Departments of Medicine and Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.
  • Bernstein JA; Department of Pediatrics, Stanford University School of Medicine, Stanford, CA 94305, USA.
  • Gahl WA; National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA.
  • Hamid R; Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN 37232, USA.
  • Loscalzo J; Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA.
  • McCray AT; Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA.
  • Shashi V; Department of Pediatrics, Duke University School of Medicine, Durham, NC 27707, USA.
  • Tifft CJ; National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA.
  • Wise AL; National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA.
Am J Hum Genet ; 100(2): 185-192, 2017 02 02.
Article em En | MEDLINE | ID: mdl-28157539
ABSTRACT
Diagnosis at the edges of our knowledge calls upon clinicians to be data driven, cross-disciplinary, and collaborative in unprecedented ways. Exact disease recognition, an element of the concept of precision in medicine, requires new infrastructure that spans geography, institutional boundaries, and the divide between clinical care and research. The National Institutes of Health (NIH) Common Fund supports the Undiagnosed Diseases Network (UDN) as an exemplar of this model of precise diagnosis. Its goals are to forge a strategy to accelerate the diagnosis of rare or previously unrecognized diseases, to improve recommendations for clinical management, and to advance research, especially into disease mechanisms. The network will achieve these objectives by evaluating patients with undiagnosed diseases, fostering a breadth of expert collaborations, determining best practices for translating the strategy into medical centers nationwide, and sharing findings, data, specimens, and approaches with the scientific and medical communities. Building the UDN has already brought insights to human and medical geneticists. The initial focus has been on data sharing, establishing common protocols for institutional review boards and data sharing, creating protocols for referring and evaluating patients, and providing DNA sequencing, metabolomic analysis, and functional studies in model organisms. By extending this precision diagnostic model nationally, we strive to meld clinical and research objectives, improve patient outcomes, and contribute to medical science.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Doenças Raras Tipo de estudo: Guideline / Prognostic_studies Limite: Humans País/Região como assunto: America do norte Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Doenças Raras Tipo de estudo: Guideline / Prognostic_studies Limite: Humans País/Região como assunto: America do norte Idioma: En Ano de publicação: 2017 Tipo de documento: Article