Bioinformatics Analysis to Find Novel Biomarkers for Coronary Heart Disease

Background: Coronary heart disease (CHD), a major cause of death worldwide, is defined as a narrowing or blockage of the coronary arteries that supply oxygen and blood to the heart. We aimed to find potential biomarkers for coronary artery disease, by comparing the expression profile of blood exosomes of both normal and CHD samples. Methods: Datasets of 6 CHD and 6 normal samples of blood exosomes were downloaded, and differentially expressed RNAs, with adjusted P<0.01 and log2FoldChange >= 1 were achieved. Moreover, gene ontology (GO) and pathway analysis were accomplished by PANTHER database for datasets. Results: Our data analysis found 119 differentially expressed genes between two datasets. By comparing transcriptome profiles, we candidate the highest downregulated gene, ACSBG1, and the highest upregulated one, DEFA4, as specific biomarkers for CHD. Furthermore, GO and pathway analysis depicted that aforementioned differentially expressed genes are mostly involved in different molecular metabolic process, inflammation, immune system process and response to stimulus pathways which all cause cardiovascular diseases. Conclusion: We have provided new potential biomarkers for CHD, though experimental validation is still needed to confirm the suitability of the candidate genes for early detection of CHD.