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Systems analysis of inflammatory bowel disease based on comprehensive gene information

BACKGROUND: The rise of systems biology and availability of highly curated gene and molecular information resources has promoted a comprehensive approach to study disease as the cumulative deleterious function of a collection of individual genes and networks of molecules acting in concert. These &qu...

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Autores principales: Suzuki, Satoru, Takai-Igarashi, Takako, Fukuoka, Yutaka, Wall, Dennis P, Tanaka, Hiroshi, Tonellato, Peter J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3368714/
https://www.ncbi.nlm.nih.gov/pubmed/22480395
http://dx.doi.org/10.1186/1471-2350-13-25
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author Suzuki, Satoru
Takai-Igarashi, Takako
Fukuoka, Yutaka
Wall, Dennis P
Tanaka, Hiroshi
Tonellato, Peter J
author_facet Suzuki, Satoru
Takai-Igarashi, Takako
Fukuoka, Yutaka
Wall, Dennis P
Tanaka, Hiroshi
Tonellato, Peter J
author_sort Suzuki, Satoru
collection PubMed
description BACKGROUND: The rise of systems biology and availability of highly curated gene and molecular information resources has promoted a comprehensive approach to study disease as the cumulative deleterious function of a collection of individual genes and networks of molecules acting in concert. These "human disease networks" (HDN) have revealed novel candidate genes and pharmaceutical targets for many diseases and identified fundamental HDN features conserved across diseases. A network-based analysis is particularly vital for a study on polygenic diseases where many interactions between molecules should be simultaneously examined and elucidated. We employ a new knowledge driven HDN gene and molecular database systems approach to analyze Inflammatory Bowel Disease (IBD), whose pathogenesis remains largely unknown. METHODS AND RESULTS: Based on drug indications for IBD, we determined sibling diseases of mild and severe states of IBD. Approximately 1,000 genes associated with the sibling diseases were retrieved from four databases. After ranking the genes by the frequency of records in the databases, we obtained 250 and 253 genes highly associated with the mild and severe IBD states, respectively. We then calculated functional similarities of these genes with known drug targets and examined and presented their interactions as PPI networks. CONCLUSIONS: The results demonstrate that this knowledge-based systems approach, predicated on functionally similar genes important to sibling diseases is an effective method to identify important components of the IBD human disease network. Our approach elucidates a previously unknown biological distinction between mild and severe IBD states.
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spelling pubmed-33687142012-06-07 Systems analysis of inflammatory bowel disease based on comprehensive gene information Suzuki, Satoru Takai-Igarashi, Takako Fukuoka, Yutaka Wall, Dennis P Tanaka, Hiroshi Tonellato, Peter J BMC Med Genet Research Article BACKGROUND: The rise of systems biology and availability of highly curated gene and molecular information resources has promoted a comprehensive approach to study disease as the cumulative deleterious function of a collection of individual genes and networks of molecules acting in concert. These "human disease networks" (HDN) have revealed novel candidate genes and pharmaceutical targets for many diseases and identified fundamental HDN features conserved across diseases. A network-based analysis is particularly vital for a study on polygenic diseases where many interactions between molecules should be simultaneously examined and elucidated. We employ a new knowledge driven HDN gene and molecular database systems approach to analyze Inflammatory Bowel Disease (IBD), whose pathogenesis remains largely unknown. METHODS AND RESULTS: Based on drug indications for IBD, we determined sibling diseases of mild and severe states of IBD. Approximately 1,000 genes associated with the sibling diseases were retrieved from four databases. After ranking the genes by the frequency of records in the databases, we obtained 250 and 253 genes highly associated with the mild and severe IBD states, respectively. We then calculated functional similarities of these genes with known drug targets and examined and presented their interactions as PPI networks. CONCLUSIONS: The results demonstrate that this knowledge-based systems approach, predicated on functionally similar genes important to sibling diseases is an effective method to identify important components of the IBD human disease network. Our approach elucidates a previously unknown biological distinction between mild and severe IBD states. BioMed Central 2012-04-05 /pmc/articles/PMC3368714/ /pubmed/22480395 http://dx.doi.org/10.1186/1471-2350-13-25 Text en Copyright ©2012 Suzuki et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Suzuki, Satoru
Takai-Igarashi, Takako
Fukuoka, Yutaka
Wall, Dennis P
Tanaka, Hiroshi
Tonellato, Peter J
Systems analysis of inflammatory bowel disease based on comprehensive gene information
title Systems analysis of inflammatory bowel disease based on comprehensive gene information
title_full Systems analysis of inflammatory bowel disease based on comprehensive gene information
title_fullStr Systems analysis of inflammatory bowel disease based on comprehensive gene information
title_full_unstemmed Systems analysis of inflammatory bowel disease based on comprehensive gene information
title_short Systems analysis of inflammatory bowel disease based on comprehensive gene information
title_sort systems analysis of inflammatory bowel disease based on comprehensive gene information
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3368714/
https://www.ncbi.nlm.nih.gov/pubmed/22480395
http://dx.doi.org/10.1186/1471-2350-13-25
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