Network-based elucidation of human disease similarities reveals common functional modules enriched for pluripotent drug targets.
Current work in elucidating relationships between diseases has largely been based on pre-existing knowledge of disease genes. Consequently, these studies are limited in their discovery of new and unknown disease relationships. We present the first quantitative framework to compare and contrast disea...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2010-02-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1000662&type=printable |
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| _version_ | 1850236198271844352 |
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| author | Silpa Suthram Joel T Dudley Annie P Chiang Rong Chen Trevor J Hastie Atul J Butte |
| author_facet | Silpa Suthram Joel T Dudley Annie P Chiang Rong Chen Trevor J Hastie Atul J Butte |
| author_sort | Silpa Suthram |
| collection | DOAJ |
| description | Current work in elucidating relationships between diseases has largely been based on pre-existing knowledge of disease genes. Consequently, these studies are limited in their discovery of new and unknown disease relationships. We present the first quantitative framework to compare and contrast diseases by an integrated analysis of disease-related mRNA expression data and the human protein interaction network. We identified 4,620 functional modules in the human protein network and provided a quantitative metric to record their responses in 54 diseases leading to 138 significant similarities between diseases. Fourteen of the significant disease correlations also shared common drugs, supporting the hypothesis that similar diseases can be treated by the same drugs, allowing us to make predictions for new uses of existing drugs. Finally, we also identified 59 modules that were dysregulated in at least half of the diseases, representing a common disease-state "signature". These modules were significantly enriched for genes that are known to be drug targets. Interestingly, drugs known to target these genes/proteins are already known to treat significantly more diseases than drugs targeting other genes/proteins, highlighting the importance of these core modules as prime therapeutic opportunities. |
| format | Article |
| id | doaj-art-eef939051e6d4ceeb0d84efa371ff8a3 |
| institution | OA Journals |
| issn | 1553-734X 1553-7358 |
| language | English |
| publishDate | 2010-02-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj-art-eef939051e6d4ceeb0d84efa371ff8a32025-08-20T02:02:01ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582010-02-0162e100066210.1371/journal.pcbi.1000662Network-based elucidation of human disease similarities reveals common functional modules enriched for pluripotent drug targets.Silpa SuthramJoel T DudleyAnnie P ChiangRong ChenTrevor J HastieAtul J ButteCurrent work in elucidating relationships between diseases has largely been based on pre-existing knowledge of disease genes. Consequently, these studies are limited in their discovery of new and unknown disease relationships. We present the first quantitative framework to compare and contrast diseases by an integrated analysis of disease-related mRNA expression data and the human protein interaction network. We identified 4,620 functional modules in the human protein network and provided a quantitative metric to record their responses in 54 diseases leading to 138 significant similarities between diseases. Fourteen of the significant disease correlations also shared common drugs, supporting the hypothesis that similar diseases can be treated by the same drugs, allowing us to make predictions for new uses of existing drugs. Finally, we also identified 59 modules that were dysregulated in at least half of the diseases, representing a common disease-state "signature". These modules were significantly enriched for genes that are known to be drug targets. Interestingly, drugs known to target these genes/proteins are already known to treat significantly more diseases than drugs targeting other genes/proteins, highlighting the importance of these core modules as prime therapeutic opportunities.https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1000662&type=printable |
| spellingShingle | Silpa Suthram Joel T Dudley Annie P Chiang Rong Chen Trevor J Hastie Atul J Butte Network-based elucidation of human disease similarities reveals common functional modules enriched for pluripotent drug targets. PLoS Computational Biology |
| title | Network-based elucidation of human disease similarities reveals common functional modules enriched for pluripotent drug targets. |
| title_full | Network-based elucidation of human disease similarities reveals common functional modules enriched for pluripotent drug targets. |
| title_fullStr | Network-based elucidation of human disease similarities reveals common functional modules enriched for pluripotent drug targets. |
| title_full_unstemmed | Network-based elucidation of human disease similarities reveals common functional modules enriched for pluripotent drug targets. |
| title_short | Network-based elucidation of human disease similarities reveals common functional modules enriched for pluripotent drug targets. |
| title_sort | network based elucidation of human disease similarities reveals common functional modules enriched for pluripotent drug targets |
| url | https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1000662&type=printable |
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