The Undiagnosed Diseases Network: Accelerating Discovery about Health and Disease.


Journal Article

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.

Full Text

Duke Authors

Cited Authors

  • Ramoni, RB; Mulvihill, JJ; Adams, DR; Allard, P; Ashley, EA; Bernstein, JA; Gahl, WA; Hamid, R; Loscalzo, J; McCray, AT; Shashi, V; Tifft, CJ; Undiagnosed Diseases Network, ; Wise, AL

Published Date

  • February 2, 2017

Published In

Volume / Issue

  • 100 / 2

Start / End Page

  • 185 - 192

PubMed ID

  • 28157539

Pubmed Central ID

  • 28157539

Electronic International Standard Serial Number (EISSN)

  • 1537-6605

Digital Object Identifier (DOI)

  • 10.1016/j.ajhg.2017.01.006


  • eng

Conference Location

  • United States