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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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Detalles Bibliográficos
Autores principales: Suthram, Silpa, Dudley, Joel T., Chiang, Annie P., Chen, Rong, Hastie, Trevor J., Butte, Atul J.
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2816673/
https://www.ncbi.nlm.nih.gov/pubmed/20140234
http://dx.doi.org/10.1371/journal.pcbi.1000662
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author Suthram, Silpa
Dudley, Joel T.
Chiang, Annie P.
Chen, Rong
Hastie, Trevor J.
Butte, Atul J.
author_facet Suthram, Silpa
Dudley, Joel T.
Chiang, Annie P.
Chen, Rong
Hastie, Trevor J.
Butte, Atul J.
author_sort Suthram, Silpa
collection PubMed
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.
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spelling pubmed-28166732010-02-07 Network-Based Elucidation of Human Disease Similarities Reveals Common Functional Modules Enriched for Pluripotent Drug Targets Suthram, Silpa Dudley, Joel T. Chiang, Annie P. Chen, Rong Hastie, Trevor J. Butte, Atul J. PLoS Comput Biol Research Article 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. Public Library of Science 2010-02-05 /pmc/articles/PMC2816673/ /pubmed/20140234 http://dx.doi.org/10.1371/journal.pcbi.1000662 Text en Suthram et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Suthram, Silpa
Dudley, Joel T.
Chiang, Annie P.
Chen, Rong
Hastie, Trevor J.
Butte, Atul J.
Network-Based Elucidation of Human Disease Similarities Reveals Common Functional Modules Enriched for Pluripotent Drug Targets
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
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2816673/
https://www.ncbi.nlm.nih.gov/pubmed/20140234
http://dx.doi.org/10.1371/journal.pcbi.1000662
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