Investigating Dysregulated Pathways in Dilated Cardiomyopathy from Pathway Interaction Network

Investigating Dysregulated Pathways in Dilated Cardiomyopathy from Pathway Interaction Network The aim of this study was to identify dysregulated pathways for the diagnosis and treatment of dilated cardiomyopathy (DCM) using pathway interaction network analysis. Methods: Transcriptome data of DCM, protein-protein interaction (PPI) data, and pathway data were recruited and preprocessed. Then, the pathway interaction network was constructed based on the gene expression analysis and gene co-expression analysis. Meanwhile, pathway activity analysis was performed, and the pathway with the greatest activity change was defined as the seed pathway. Staring from the seed pathway, the dysregulated pathways that could serve as diagnostic biomarker was extracted from the pathway interaction network using support vector machines. Results: Combining gene expression and co-expression data, we constructed the pathway interaction network, covering 4175 pathway interactions. Via pathway activity analysis, cap-dependent translation initiation with the greatest activity change was defined as the seed pathway. Staring from cap-dependent translation initiation, a total of 21 dysregulated pathways were obtained, which could discriminate DCM samples from controls with the area under the curve value of 0.95. Conclusion: A pathway interaction network was implemented to identify dysrgulated pathways that can best discriminate DCM samples from controls. We identified a total of 21 dysregulated pathways in DCM, which can serve as diagnostic biomarkers for DCM. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Russian Journal of Genetics Springer Journals

Investigating Dysregulated Pathways in Dilated Cardiomyopathy from Pathway Interaction Network

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Publisher
Pleiades Publishing
Copyright
Copyright © 2018 by Pleiades Publishing, Inc.
Subject
Biomedicine; Human Genetics; Animal Genetics and Genomics; Microbial Genetics and Genomics
ISSN
1022-7954
eISSN
1608-3369
D.O.I.
10.1134/S1022795418020151
Publisher site
See Article on Publisher Site

Abstract

The aim of this study was to identify dysregulated pathways for the diagnosis and treatment of dilated cardiomyopathy (DCM) using pathway interaction network analysis. Methods: Transcriptome data of DCM, protein-protein interaction (PPI) data, and pathway data were recruited and preprocessed. Then, the pathway interaction network was constructed based on the gene expression analysis and gene co-expression analysis. Meanwhile, pathway activity analysis was performed, and the pathway with the greatest activity change was defined as the seed pathway. Staring from the seed pathway, the dysregulated pathways that could serve as diagnostic biomarker was extracted from the pathway interaction network using support vector machines. Results: Combining gene expression and co-expression data, we constructed the pathway interaction network, covering 4175 pathway interactions. Via pathway activity analysis, cap-dependent translation initiation with the greatest activity change was defined as the seed pathway. Staring from cap-dependent translation initiation, a total of 21 dysregulated pathways were obtained, which could discriminate DCM samples from controls with the area under the curve value of 0.95. Conclusion: A pathway interaction network was implemented to identify dysrgulated pathways that can best discriminate DCM samples from controls. We identified a total of 21 dysregulated pathways in DCM, which can serve as diagnostic biomarkers for DCM.

Journal

Russian Journal of GeneticsSpringer Journals

Published: Mar 12, 2018

References

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