Deciphering key genes in cardio-renal syndrome using network analysis.

Romana Ishrat

doi:10.6026/97320630017086

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.

Highlights

The incidence of cardiac and chronic renal dysfunction gave a term Cardiorenal Syndrome (CRS), which has been widely used without well-known definition
The literature based data mining of key genes and their further gene ontology, pathways enrichment and complex protein-protein interaction analysis revealing these genes may be potent as biomarkers of CRS
Natriuretic peptides that are developed as cardiac biomarkers, and many more novel biomarkers have been identified that are significant for CRS [10]

Summary

Introduction

The incidence of cardiac and chronic renal dysfunction gave a term Cardiorenal Syndrome (CRS), which has been widely used without well-known definition. Dysfunctional links of both organs makes it a more complex condition, so it needs a multidisciplinary health management system to optimize disease actual condition to diagnose, better treatment and to enhance patient outcomes as well [3] Cardiac and renal both functions are essential for stable hemodynamic system, where neurohormonal mechanism plays important role in hemodynamic stability the mechanism involves autonomic nervous system, reninangiotensin- aldosterone system (RAAS), arginine vasopressin (AVP), and endothelin-1 (ET-1) [4]. The literature based data mining of key genes and their further gene ontology, pathways enrichment and complex protein-protein interaction analysis revealing these genes may be potent as biomarkers of CRS They play a wide role in HF, unlike either acute or chronic renal failure. The results may provide information for further investigation of the mechanisms underlying CRS and for the development of potential treatment approaches

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