Revisiting the biomarkers for Coronary Artery Disease and Stroke using a bioinformatics perspective

Abstract

Background: Cardiovascular and cerebrovascular diseases (CVDs), respectively, coronary artery disease (CAD) and stroke, are the leading causes of death and morbidity. Atherosclerosis is implicated in the pathophysiology of both these diseases. Early diagnosis may be the answer to reduce the health and economic burden of CVDs. Objective: We aim to uncover potential biomarkers to determine the risk of CAD and stroke by analyzing proteins associated with both diseases and their potential of being used in clinical practice. Methods: Two separate literature searches were used to obtain the articles that combined CAD or stroke with omics terms. The data was analyzed by automatic text mining using the VOSviewer software, which identified proteins associated with both diseases. These proteins were compared with genes previously associated with CAD and stroke as disclosed in the DisGeNET database. ProteomeXchange datasets were used to confirm our results and STRING for functional enrichment analysis. Results: This study resulted in 22 proteins associated with both diseases. Protein-protein interaction analysis revealed that these proteins were associated with many biological processes related to atherosclerosis. ADIPOQ, ALB, APOE, CRP, CST3, MMP1, MMP2, MMP3, MMP7, MMP8, MMP9, SAA1, and TNF are secreted and can be measured in biofluids. The genes identified with the highest level of evidence, according to DisGeNET, are ADIPOQ, APOE, CRP, MMP9, NOS3, PPARG, PTGS2, and TNF. Conclusion: In conclusion, the most promising biomarkers seem to be ADIPOQ, APOE, CRP, MMP9, and TNF and they should be studied as a panel of potential predictors of CVDs.