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Identifying Common Genes and Networks in Multi-Organ Fibrosis

Fibroproliferative diseases of organs are poorly understood and generally lack effective anti-fibrotic treatments. Our goal was to identify the key regulatory factors in pathologic fibrosis, common between organ-based fibrotic disease. We analyzed 9 microarray datasets publicly available in the GEO...

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Autores principales: Wenzke, Kevin E., Cantemir-Stone, Carmen, Zhang, Jie, Marsh, Clay B., Huang, Kun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Informatics Association 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3392050/
https://www.ncbi.nlm.nih.gov/pubmed/22779061
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author Wenzke, Kevin E.
Cantemir-Stone, Carmen
Zhang, Jie
Marsh, Clay B.
Huang, Kun
author_facet Wenzke, Kevin E.
Cantemir-Stone, Carmen
Zhang, Jie
Marsh, Clay B.
Huang, Kun
author_sort Wenzke, Kevin E.
collection PubMed
description Fibroproliferative diseases of organs are poorly understood and generally lack effective anti-fibrotic treatments. Our goal was to identify the key regulatory factors in pathologic fibrosis, common between organ-based fibrotic disease. We analyzed 9 microarray datasets publicly available in the GEO datasets from lung, heart, liver and kidney fibrotic disease tissue (489 microarrays total, disease and control). We identified a set of 90 genes differentially expressed in at least five microarray datasets. We used IPA and DAVID analysis to identify gene networks and their molecular functions. A mutual information based network work activity analysis showed that a connective tissue disorders network was the most active for all types of fibrosis included in this analysis. Conclusion: Our analysis indicates that despite different disease manifestation, organ fibrosis share a specific set of genes suggesting the potential for a common origin.
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spelling pubmed-33920502012-07-09 Identifying Common Genes and Networks in Multi-Organ Fibrosis Wenzke, Kevin E. Cantemir-Stone, Carmen Zhang, Jie Marsh, Clay B. Huang, Kun AMIA Jt Summits Transl Sci Proc Articles Fibroproliferative diseases of organs are poorly understood and generally lack effective anti-fibrotic treatments. Our goal was to identify the key regulatory factors in pathologic fibrosis, common between organ-based fibrotic disease. We analyzed 9 microarray datasets publicly available in the GEO datasets from lung, heart, liver and kidney fibrotic disease tissue (489 microarrays total, disease and control). We identified a set of 90 genes differentially expressed in at least five microarray datasets. We used IPA and DAVID analysis to identify gene networks and their molecular functions. A mutual information based network work activity analysis showed that a connective tissue disorders network was the most active for all types of fibrosis included in this analysis. Conclusion: Our analysis indicates that despite different disease manifestation, organ fibrosis share a specific set of genes suggesting the potential for a common origin. American Medical Informatics Association 2012-03-19 /pmc/articles/PMC3392050/ /pubmed/22779061 Text en ©2012 AMIA - All rights reserved. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose
spellingShingle Articles
Wenzke, Kevin E.
Cantemir-Stone, Carmen
Zhang, Jie
Marsh, Clay B.
Huang, Kun
Identifying Common Genes and Networks in Multi-Organ Fibrosis
title Identifying Common Genes and Networks in Multi-Organ Fibrosis
title_full Identifying Common Genes and Networks in Multi-Organ Fibrosis
title_fullStr Identifying Common Genes and Networks in Multi-Organ Fibrosis
title_full_unstemmed Identifying Common Genes and Networks in Multi-Organ Fibrosis
title_short Identifying Common Genes and Networks in Multi-Organ Fibrosis
title_sort identifying common genes and networks in multi-organ fibrosis
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3392050/
https://www.ncbi.nlm.nih.gov/pubmed/22779061
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