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Mapping Gene Associations in Human Mitochondria using Clinical Disease Phenotypes

Overview of attention for article published in PLoS Computational Biology, April 2009
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Title
Mapping Gene Associations in Human Mitochondria using Clinical Disease Phenotypes
Published in
PLoS Computational Biology, April 2009
DOI 10.1371/journal.pcbi.1000374
Pubmed ID
Authors

Curt Scharfe, Henry Horng-Shing Lu, Jutta K. Neuenburg, Edward A. Allen, Guan-Cheng Li, Thomas Klopstock, Tina M. Cowan, Gregory M. Enns, Ronald W. Davis

Abstract

Nuclear genes encode most mitochondrial proteins, and their mutations cause diverse and debilitating clinical disorders. To date, 1,200 of these mitochondrial genes have been recorded, while no standardized catalog exists of the associated clinical phenotypes. Such a catalog would be useful to develop methods to analyze human phenotypic data, to determine genotype-phenotype relations among many genes and diseases, and to support the clinical diagnosis of mitochondrial disorders. Here we establish a clinical phenotype catalog of 174 mitochondrial disease genes and study associations of diseases and genes. Phenotypic features such as clinical signs and symptoms were manually annotated from full-text medical articles and classified based on the hierarchical MeSH ontology. This classification of phenotypic features of each gene allowed for the comparison of diseases between different genes. In turn, we were then able to measure the phenotypic associations of disease genes for which we calculated a quantitative value that is based on their shared phenotypic features. The results showed that genes sharing more similar phenotypes have a stronger tendency for functional interactions, proving the usefulness of phenotype similarity values in disease gene network analysis. We then constructed a functional network of mitochondrial genes and discovered a higher connectivity for non-disease than for disease genes, and a tendency of disease genes to interact with each other. Utilizing these differences, we propose 168 candidate genes that resemble the characteristic interaction patterns of mitochondrial disease genes. Through their network associations, the candidates are further prioritized for the study of specific disorders such as optic neuropathies and Parkinson disease. Most mitochondrial disease phenotypes involve several clinical categories including neurologic, metabolic, and gastrointestinal disorders, which might indicate the effects of gene defects within the mitochondrial system. The accompanying knowledgebase (http://www.mitophenome.org/) supports the study of clinical diseases and associated genes.

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Geographical breakdown

Country Count As %
United States 3 2%
United Kingdom 2 2%
China 2 2%
Spain 2 2%
Singapore 1 <1%
Denmark 1 <1%
Switzerland 1 <1%
Japan 1 <1%
Luxembourg 1 <1%
Other 0 0%
Unknown 108 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 34 28%
Student > Ph. D. Student 25 20%
Student > Bachelor 17 14%
Student > Master 9 7%
Professor 6 5%
Other 17 14%
Unknown 14 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 51 42%
Medicine and Dentistry 20 16%
Biochemistry, Genetics and Molecular Biology 15 12%
Computer Science 9 7%
Psychology 2 2%
Other 11 9%
Unknown 14 11%