The national institutes of health undiagnosed diseases program: Insights into rare diseases

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Abstract

Purpose: This report describes the National Institutes of Health Undiagnosed Diseases Program, details the Programs application of genomic technology to establish diagnoses, and details the Programs 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. © 2012 American College of Medical Genetics.

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Gahl, W. A., Markello, T. C., Toro, C., Fajardo, K. F., Sincan, M., Gill, F., … Adams, D. (2012). The national institutes of health undiagnosed diseases program: Insights into rare diseases. Genetics in Medicine, 14(1), 51–59. https://doi.org/10.1038/gim.0b013e318232a005

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