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Published on: May 2, 2025
Deciphering key genes in cardio-renal syndrome using network analysis
Mohd Murshad Ahmed1, Safia Tazyeen1, Aftab Alam1
1Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi-110025, India.
Insights
Cardio-renal syndrome (CRS) involves linked heart and kidney damage. This study identifies 12 key genes as potential biomarkers for earlier diagnosis and better management of CRS.
Area of Science:
- Biomedical research
- Genetics
- Cardiology
- Nephrology
Background:
- Cardio-renal syndrome (CRS) is a complex condition where heart and kidney dysfunction are interconnected.
- Early diagnosis of CRS is crucial for effective clinical management.
- Biological markers are essential for understanding CRS pathophysiology and improving diagnostic accuracy.
Purpose of the Study:
- To identify novel target genes and pathways associated with Cardio-renal Syndrome (CRS).
- To discover potential biomarkers for the early diagnosis and improved management of CRS.
Main Methods:
- Extraction of 119 CRS-related genes from existing literature.
- Construction of a protein-protein interaction network (PPIN) using the extracted genes.
- Identification of key gene modules using the MCODE tool.
- Analysis of 12 essential genes within the most significant modules.
Main Results:
- Identification of 12 essential genes implicated in CRS pathophysiology.
- Functional enrichment analysis revealed these genes are rich in protease binding and endo-peptidase inhibitor activity.
- These genes represent potential novel biomarkers for CRS.
Conclusions:
- The identified 12 genes offer new insights into the molecular mechanisms of CRS.
- These biomarkers can aid in the early diagnosis and enhance the clinical management of Cardio-renal Syndrome.
- Further research into these genes may improve patient outcomes for CRS.
Abstract:
Cardio-renal syndrome (CRS) is a rapidly recognized clinical entity which refers to the inextricably connection between heart and renal impairment, whereby abnormality to one organ directly promotes deterioration of the other one. Biological markers help to gain insight into the pathological processes for early diagnosis with higher accuracy of CRS using known clinical findings. Therefore, it is of interest to identify target genes in associated pathways implicated linked to CRS. Hence, 119 CRS genes were extracted from the literature to construct the PPIN network. We used the MCODE tool to generate modules from network so as to select the top 10 modules from 23 available modules. The modules were further analyzed to identify 12 essential genes in the network. These biomarkers are potential emerging tools for understanding the pathophysiologic mechanisms for the early diagnosis of CRS. Ontological analysis shows that they are rich in MF protease binding and endo-peptidase inhibitor activity. Thus, this data help increase our knowledge on CRS to improve clinical management of the disease.
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