PURPOSE: This report describes the National Institutes of Health Undiagnosed Diseases Program, details the Program's application of genomic technology to establish diagnoses, and details the Program's success rate during its first 2 years. METHODS: Each accepted study participant was extensively phenotyped. A subset of participants and selected family members (29 patients and 78 unaffected family members) was subjected to an integrated set of genomic analyses including high-density single-nucleotide polymorphism arrays and whole exome or genome analysis. RESULTS: Of 1,191 medical records reviewed, 326 patients were accepted and 160 were admitted directly to the National Institutes of Health Clinical Center on the Undiagnosed Diseases Program service. Of those, 47% were children, 55% were females, and 53% had neurologic disorders. Diagnoses were reached on 39 participants (24%) on clinical, biochemical, pathologic, or molecular grounds; 21 diagnoses involved rare or ultra-rare diseases. Three disorders were diagnosed based on single-nucleotide polymorphism array analysis and three others using whole exome sequencing and filtering of variants. Two new disorders were discovered. Analysis of the single-nucleotide polymorphism array study cohort revealed that large stretches of homozygosity were more common in affected participants relative to controls. CONCLUSION: The National Institutes of Health Undiagnosed Diseases Program addresses an unmet need, i.e., the diagnosis of patients with complex, multisystem disorders. It may serve as a model for the clinical application of emerging genomic technologies and is providing insights into the characteristics of diseases that remain undiagnosed after extensive clinical workup.
PURPOSE: This report describes the National Institutes of Health Undiagnosed Diseases Program, details the Program's application of genomic technology to establish diagnoses, and details the Program's success rate during its first 2 years. METHODS: Each accepted study participant was extensively phenotyped. A subset of participants and selected family members (29 patients and 78 unaffected family members) was subjected to an integrated set of genomic analyses including high-density single-nucleotide polymorphism arrays and whole exome or genome analysis. RESULTS: Of 1,191 medical records reviewed, 326 patients were accepted and 160 were admitted directly to the National Institutes of Health Clinical Center on the Undiagnosed Diseases Program service. Of those, 47% were children, 55% were females, and 53% had neurologic disorders. Diagnoses were reached on 39 participants (24%) on clinical, biochemical, pathologic, or molecular grounds; 21 diagnoses involved rare or ultra-rare diseases. Three disorders were diagnosed based on single-nucleotide polymorphism array analysis and three others using whole exome sequencing and filtering of variants. Two new disorders were discovered. Analysis of the single-nucleotide polymorphism array study cohort revealed that large stretches of homozygosity were more common in affected participants relative to controls. CONCLUSION: The National Institutes of Health Undiagnosed Diseases Program addresses an unmet need, i.e., the diagnosis of patients with complex, multisystem disorders. It may serve as a model for the clinical application of emerging genomic technologies and is providing insights into the characteristics of diseases that remain undiagnosed after extensive clinical workup.
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Authors: Jessica X Chong; Kati J Buckingham; Shalini N Jhangiani; Corinne Boehm; Nara Sobreira; Joshua D Smith; Tanya M Harrell; Margaret J McMillin; Wojciech Wiszniewski; Tomasz Gambin; Zeynep H Coban Akdemir; Kimberly Doheny; Alan F Scott; Dimitri Avramopoulos; Aravinda Chakravarti; Julie Hoover-Fong; Debra Mathews; P Dane Witmer; Hua Ling; Kurt Hetrick; Lee Watkins; Karynne E Patterson; Frederic Reinier; Elizabeth Blue; Donna Muzny; Martin Kircher; Kaya Bilguvar; Francesc López-Giráldez; V Reid Sutton; Holly K Tabor; Suzanne M Leal; Murat Gunel; Shrikant Mane; Richard A Gibbs; Eric Boerwinkle; Ada Hamosh; Jay Shendure; James R Lupski; Richard P Lifton; David Valle; Deborah A Nickerson; Michael J Bamshad Journal: Am J Hum Genet Date: 2015-07-09 Impact factor: 11.025
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