In silico based analysis to explore genetic linkage between atherosclerosis and its potential risk factors

Hossain Mohammad Hridoy; Md Nasim Haidar; Chadni Khatun; Arnob Sarker; Md Pervez Hossain; Md Abdul Aziz; Md Tofazzal Hossain

doi:10.1016/j.bbrep.2023.101574

In silico based analysis to explore genetic linkage between atherosclerosis and its potential risk factors

Biochem Biophys Rep. 2023 Nov 7:36:101574. doi: 10.1016/j.bbrep.2023.101574. eCollection 2023 Dec.

Authors

Hossain Mohammad Hridoy¹, Md Nasim Haidar², Chadni Khatun^{3

1}, Arnob Sarker¹, Md Pervez Hossain¹, Md Abdul Aziz^{3

1}, Md Tofazzal Hossain^{3

1}

Affiliations

¹ Department of Biochemistry and Molecular Biology, University of Rajshahi, Rajshahi, Bangladesh.
² Department of Electrical and Electronic Engineering, Rangpur Engineering College, Rangpur, Bangladesh.
³ Bioinformatics and Structural Biology Lab, Department of Biochemistry and Molecular Biology, University of Rajshahi, Rajshahi, Bangladesh.

Abstract

Atherosclerosis (ATH) is a chronic cardiovascular disease characterized by plaque formation in arteries, and it is a major cause of illness and death. Although therapeutic advances have significantly improved the prognosis of ATH, missing therapeutic targets pose a significant residual threat. This research used a systems biology approach to identify the molecular biomarkers involved in the onset and progression of ATH, analysing microarray gene expression datasets from ATH and tissues impacted by risk factors such as high cholesterol, adipose tissue, smoking, obesity, sedentary lifestyle, stress, alcohol consumption, hypertension, hyperlipidaemia, high fat, diabetes to find the differentially expressed genes (DEGs). Bioinformatic analyses of Protein-Protein Interaction (PPI), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) were conducted on differentially expressed genes, revealing metabolic and signaling pathways (the chemokine signaling pathway, cytokine-cytokine receptor interaction, the cytosolic DNA-sensing pathway, the peroxisome proliferator-activated receptors signaling pathway, and the nuclear factor-kappa B signaling pathway), ten hubs proteins (CCL5, CCR1, TLR1, CCR2, FCGR2A, IL1B, CD163, AIF1, CXCL-1 and TNF), five transcription factors (YY1, FOXL1, FOXC1, SRF, and GATA2), and five miRNAs (mir-27a-3p, mir-124-3p, mir-16-5p, mir-129-2-3p, mir-1-3p). These findings identify potential biomarkers that may increase knowledge of the mechanisms underlying ATH and their connection to risk factors, aiding in the development of new therapies.

Keywords: Atherosclerosis; Biomarkers; Cardiovascular disease; Genetic linkage; Hub proteins; Risk factors.