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Identification of the shared gene signatures and biological mechanism in Atrial Fibrillation and Ischemic cardiomyopathy
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Abstract
Objective the relationship between Atrial fibrillation(AF) and Ischemic cardiomyopathy(ICM) has long been widely recognized, but no previous study explore the interaction mechanisms and method to confirm the casual relation ship of them. this study was aimed to investigate the shared gene signatures and molecular process between AF and ICM.Methods The Gene expression Omnibus(GEO) database was used to retrieve the data of AF and ICM used in this syudy. Weighted gene co-expression network analysis(WGCNA) was performed to discover associated genes with AF and ICM. Than intersecting the correlated genes by venn and filtered out the co-expression gene both AF and ICM, than performed GO enrichmen analysis and PPI network analysis, than usig the cytoscape software screened out the most significant hub genes correlated with AF and ICM, finally validated by other dataset.Result using WGCNA the most correlated module with AF and ICM respectively were identified. By venn the most correlated genes with AF and ICM filtered out 188 genes as the co-expressed genes with AF and ICM. than performed GO enrichmen analysis and PPI network analysis, than usig the cytoscape software screened out the three most significant hub genes(CHD1,MSH2, NIBPL) correlated with AF and ICM, finally validated using other dataset by ROC, all of thre genes has the good discrimination ability both in AF and ICM.Conclusion This work firstly revealed the three co-expression genes correlated with AF and ICM, maybe the expression level of these genes have diagnostic value of AF and ICM and have diagnostic value to confirm the cause of AF is ICM.
Research Square Platform LLC
Title: Identification of the shared gene signatures and biological mechanism in Atrial Fibrillation and Ischemic cardiomyopathy
Description:
Abstract
Objective the relationship between Atrial fibrillation(AF) and Ischemic cardiomyopathy(ICM) has long been widely recognized, but no previous study explore the interaction mechanisms and method to confirm the casual relation ship of them.
this study was aimed to investigate the shared gene signatures and molecular process between AF and ICM.
Methods The Gene expression Omnibus(GEO) database was used to retrieve the data of AF and ICM used in this syudy.
Weighted gene co-expression network analysis(WGCNA) was performed to discover associated genes with AF and ICM.
Than intersecting the correlated genes by venn and filtered out the co-expression gene both AF and ICM, than performed GO enrichmen analysis and PPI network analysis, than usig the cytoscape software screened out the most significant hub genes correlated with AF and ICM, finally validated by other dataset.
Result using WGCNA the most correlated module with AF and ICM respectively were identified.
By venn the most correlated genes with AF and ICM filtered out 188 genes as the co-expressed genes with AF and ICM.
than performed GO enrichmen analysis and PPI network analysis, than usig the cytoscape software screened out the three most significant hub genes(CHD1,MSH2, NIBPL) correlated with AF and ICM, finally validated using other dataset by ROC, all of thre genes has the good discrimination ability both in AF and ICM.
Conclusion This work firstly revealed the three co-expression genes correlated with AF and ICM, maybe the expression level of these genes have diagnostic value of AF and ICM and have diagnostic value to confirm the cause of AF is ICM.
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