Mapping gene associations in human mitochondria using clinical disease phenotypes.
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 devel...
Guardado en:
| Autores principales: | , , , , , , , , |
|---|---|
| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Public Library of Science (PLoS)
2009
|
| Materias: | |
| Acceso en línea: | https://doaj.org/article/48667a402dcb4150a5edb81eb2bc075d |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| id |
oai:doaj.org-article:48667a402dcb4150a5edb81eb2bc075d |
|---|---|
| record_format |
dspace |
| spelling |
oai:doaj.org-article:48667a402dcb4150a5edb81eb2bc075d2021-11-25T05:42:25ZMapping gene associations in human mitochondria using clinical disease phenotypes.1553-734X1553-735810.1371/journal.pcbi.1000374https://doaj.org/article/48667a402dcb4150a5edb81eb2bc075d2009-04-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/19390613/?tool=EBIhttps://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Nuclear 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.Curt ScharfeHenry Horng-Shing LuJutta K NeuenburgEdward A AllenGuan-Cheng LiThomas KlopstockTina M CowanGregory M EnnsRonald W DavisPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 5, Iss 4, p e1000374 (2009) |
| institution |
DOAJ |
| collection |
DOAJ |
| language |
EN |
| topic |
Biology (General) QH301-705.5 |
| spellingShingle |
Biology (General) QH301-705.5 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 Mapping gene associations in human mitochondria using clinical disease phenotypes. |
| description |
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. |
| format |
article |
| author |
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 |
| author_facet |
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 |
| author_sort |
Curt Scharfe |
| title |
Mapping gene associations in human mitochondria using clinical disease phenotypes. |
| title_short |
Mapping gene associations in human mitochondria using clinical disease phenotypes. |
| title_full |
Mapping gene associations in human mitochondria using clinical disease phenotypes. |
| title_fullStr |
Mapping gene associations in human mitochondria using clinical disease phenotypes. |
| title_full_unstemmed |
Mapping gene associations in human mitochondria using clinical disease phenotypes. |
| title_sort |
mapping gene associations in human mitochondria using clinical disease phenotypes. |
| publisher |
Public Library of Science (PLoS) |
| publishDate |
2009 |
| url |
https://doaj.org/article/48667a402dcb4150a5edb81eb2bc075d |
| work_keys_str_mv |
AT curtscharfe mappinggeneassociationsinhumanmitochondriausingclinicaldiseasephenotypes AT henryhorngshinglu mappinggeneassociationsinhumanmitochondriausingclinicaldiseasephenotypes AT juttakneuenburg mappinggeneassociationsinhumanmitochondriausingclinicaldiseasephenotypes AT edwardaallen mappinggeneassociationsinhumanmitochondriausingclinicaldiseasephenotypes AT guanchengli mappinggeneassociationsinhumanmitochondriausingclinicaldiseasephenotypes AT thomasklopstock mappinggeneassociationsinhumanmitochondriausingclinicaldiseasephenotypes AT tinamcowan mappinggeneassociationsinhumanmitochondriausingclinicaldiseasephenotypes AT gregorymenns mappinggeneassociationsinhumanmitochondriausingclinicaldiseasephenotypes AT ronaldwdavis mappinggeneassociationsinhumanmitochondriausingclinicaldiseasephenotypes |
| _version_ |
1718414514502762496 |