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Published on: August 24, 2013
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Computational evaluation of exome sequence data using human and model organism phenotypes improves diagnostic
William P Bone1, Nicole L Washington2, Orion J Buske3,4
1Undiagnosed Diseases Program, Common Fund, Office of the Director, National Institutes of Health, Bethesda, Maryland, USA.
Summary
Computational analysis of patient phenotypes using Human Phenotype Ontology (HPO) terms significantly improves the diagnosis of rare genetic disorders, especially for complex cases. This approach aids clinicians in identifying disease-associated variants more effectively.
Area of Science:
- Genomics
- Medical Genetics
- Computational Biology
Background:
- Clinical diagnosis of rare diseases often relies on clinician expertise, which is challenging for atypical presentations.
- Accurate identification of disease-causing genetic variants is crucial for diagnosing genetic disorders.
Purpose of the Study:
- To test the hypothesis that using Human Phenotype Ontology (HPO) terms and computational variant ranking improves rare disease diagnosis.
- To evaluate the effectiveness of the Exomiser tool in identifying disease-associated variants.
Main Methods:
- Utilized simulated exomes and the National Institutes of Health Undiagnosed Diseases Program (UDP) patient cohort.
- Employed Exomiser to rank candidate variants based on phenotype similarity to known disease-gene associations, model organism orthologs, and protein-protein interaction neighbors.
Main Results:
- Exomiser ranked the causal variant as the top hit in 97% of known disease-gene associations.
- For previously undiagnosed UDP cases, Exomiser identified causative variants within the top 10 for 11 patients and aided in diagnosing 4 out of 23 undiagnosed cases.
Conclusions:
- Structured patient phenotyping with Human Phenotype Ontology (HPO) terms and computational variant analysis are valuable tools for diagnosing genetic disorders.
- This integrated approach enhances diagnostic yield, particularly for patients with complex or atypical clinical profiles.
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