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Updated: Aug 1, 2025
An Integrated Approach for Microprotein Identification and Sequence Analysis
Published on: July 12, 2022
Identification of Signature Genes of Dilated Cardiomyopathy Using Integrated Bioinformatics Analysis
Zhimin Wu1, Xu Wang1, Hao Liang1
1Department of Pharmacy, Hebei Medical University, Shijiazhuang 050017, China.
Insights
Researchers identified three key genes (BEX1, RGCC, VSIG4) linked to dilated cardiomyopathy (DCM) by analyzing public data and a doxorubicin-induced mouse model. These findings offer insights into DCM pathogenesis and potential therapeutic targets.
Area of Science:
- Cardiovascular Research
- Molecular Biology
- Genomics
Background:
- Dilated cardiomyopathy (DCM) involves ventricular enlargement and impaired systolic function, with underlying molecular mechanisms still under investigation.
- Understanding the genetic and molecular basis of DCM is crucial for developing effective treatments.
Purpose of the Study:
- To identify significant genes and biological pathways involved in dilated cardiomyopathy pathogenesis.
- To validate findings using both public microarray data and a doxorubicin-induced mouse model.
Main Methods:
- Utilized six DCM-related microarray datasets from the GEO database, applying LIMMA for differential gene expression analysis.
- Integrated results using Robust Rank Aggregation (RRA) and validated with a doxorubicin-induced DCM mouse model analyzed by DESeq2.
- Cross-validated findings through intersection analysis and employed binary logistic regression to confirm gene significance.
Main Results:
- Identified three key differentially expressed genes: BEX1, RGCC, and VSIG4, strongly associated with DCM.
- Highlighted significant biological processes including extracellular matrix organization and sulfur compound binding.
- Uncovered the involvement of the HIF-1 signaling pathway in DCM pathogenesis.
Conclusions:
- The study elucidates key molecular players and pathways in DCM pathogenesis, including BEX1, RGCC, and VSIG4.
- Findings provide a foundation for understanding DCM and suggest potential targets for future clinical interventions.
- Integrated bioinformatics and experimental approaches enhance the reliability of identified DCM-associated genes.
Abstract:
Dilated cardiomyopathy (DCM) is characterized by left ventricular or biventricular enlargement with systolic dysfunction. To date, the underlying molecular mechanisms of dilated cardiomyopathy pathogenesis have not been fully elucidated, although some insights have been presented. In this study, we combined public database resources and a doxorubicin-induced DCM mouse model to explore the significant genes of DCM in full depth. We first retrieved six DCM-related microarray datasets from the GEO database using several keywords. Then we used the "LIMMA" (linear model for microarray data) R package to filter each microarray for differentially expressed genes (DEGs). Robust rank aggregation (RRA), an extremely robust rank aggregation method based on sequential statistics, was then used to integrate the results of the six microarray datasets to filter out the reliable differential genes. To further improve the reliability of our results, we established a doxorubicin-induced DCM model in C57BL/6N mice, using the "DESeq2" software package to identify DEGs in the sequencing data. We cross-validated the results of RRA analysis with those of animal experiments by taking intersections and identified three key differential genes (including BEX1, RGCC and VSIG4) associated with DCM as well as many important biological processes (extracellular matrix organisation, extracellular structural organisation, sulphur compound binding, and extracellular matrix structural components) and a signalling pathway (HIF-1 signalling pathway). In addition, we confirmed the significant effect of these three genes in DCM using binary logistic regression analysis. These findings will help us to better understand the pathogenesis of DCM and may be key targets for future clinical management.
