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Identifying common genes and networks in multi-organ fibrosis.

作者信息

Wenzke Kevin E, Cantemir-Stone Carmen, Zhang Jie, Marsh Clay B, Huang Kun

机构信息

Department of Biomedical Informatics, The Ohio State University, Columbus, OH;

出版信息

AMIA Jt Summits Transl Sci Proc. 2012;2012:106-15. Epub 2012 Mar 19.

Abstract

UNLABELLED

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.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7a97/3392050/0ac46ebc4c52/106-joint_summit_t2012f1.jpg

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