The Undiagnosed Diseases Network (UDN) will expand the highly successful Undiagnosed Diseases Program of the NIH by increasing access for patients with undiagnosed diseases to the nation's leading clinicians and scientists. Stanford Medicine is uniquely placed to advance the mission of the Undiagnosed Disease Program through the establishment of a Center for Undiagnosed Diseases at Stanford (CUDS). We propose a program that will (1) facilitate timely, accurate diagnosis of patients with undiagnosed diseases; (2) advance research into underlying mechanisms of disease; and (3) foster cooperation and collaboration both within and outside the UDN.
In Aim 1, patients referred by the Coordinating Center will be evaluated through a protocol including pre-visit video consultation and genetic counseling, a week-long visit during which phenotypic, biochemical, genomic and environmental data will be collected and video conference follow up. Blood will be collected for generation of inducible pluripotent stem cells from patients and relatives. A site-wide Diagnosis Board will review case progress and identify internal and external experts for live or virtual video consultation. Use of a telepresence will enable 'virtual consultation' with experts in specific rare diseases from wherever they are across the world.
Aim 2 is focused on genomic analysis that will take advantage of our mature pipeline for genome interpretation and may include Stanford's 'clinical grade' genome capture and sequencing technology. De-identified datasets will be shared across network sites, and with scientific collaborators, using both local and coordinating center computing infrastructure. Genomic data will be analyzed in concert with structured analysis of individual phenotypic characteristics via a phenotype interaction map to narrow the search space for genetic variants of interest. An Informatics Board will review progress on data analysis and determine the need for further investigation including multi-omics data collection and analysis.
Aim 3 takes advantage of the walking distance co-localization of Stanford Hospitals with the University labs, which will allow the Undiagnosed Diseases Network to utilize unique Stanford resources such as the Stem Cell Institute and the Human Immune Monitoring Center. A Pathogenesis Board will review progress on determination of pathogenesis in individual cases and identify avenues and experts for exploration of causality of individual variants. Each case and disease hypothesis will be presented at the Center's Molecular Mechanisms of Disease weekly conference which will be recorded for dissemination within the network. Working documents will be shared with other sites on a weekly basis via a secure web portal.
We propose to establish a Center for Undiagnosed Diseases at Stanford that would coordinate closely with the national Undiagnosed Diseases Network. Our Center would bring Stanford's long history in technology development, genomic data analysis, stem cell biology, and translational science to the team- based diagnosis and care of patients with undiagnosed disease.
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| Dainis, Alexandra M; Ashley, Euan A (2018) Cardiovascular Precision Medicine in the Genomics Era. JACC Basic Transl Sci 3:313-326 |
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| Oláhová, Monika; Yoon, Wan Hee; Thompson, Kyle et al. (2018) Biallelic Mutations in ATP5F1D, which Encodes a Subunit of ATP Synthase, Cause a Metabolic Disorder. Am J Hum Genet 102:494-504 |
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| Zastrow, Diane B; Zornio, Patricia A; Dries, Annika et al. (2017) Exome sequencing identifies de novo pathogenic variants in FBN1 and TRPS1 in a patient with a complex connective tissue phenotype. Cold Spring Harb Mol Case Stud 3:a001388 |
| Chao, Hsiao-Tuan; Davids, Mariska; Burke, Elizabeth et al. (2017) A Syndromic Neurodevelopmental Disorder Caused by De Novo Variants in EBF3. Am J Hum Genet 100:128-137 |
| Ramoni, Rachel B; Mulvihill, John J; Adams, David R et al. (2017) The Undiagnosed Diseases Network: Accelerating Discovery about Health and Disease. Am J Hum Genet 100:185-192 |
| Shashi, Vandana; Pena, Loren D M; Kim, Katherine et al. (2016) De Novo Truncating Variants in ASXL2 Are Associated with a Unique and Recognizable Clinical Phenotype. Am J Hum Genet 99:991-999 |
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