Molecular Biomarker Identification Using a Network-Based Bioinformatics Approach That Links COVID-19 With Smoking

Md Anisur Rahman; Md Al Amin; Most Nilufa Yeasmin; Md Zahidul Islam

doi:10.1177/11779322231186481

Molecular Biomarker Identification Using a Network-Based Bioinformatics Approach That Links COVID-19 With Smoking

Bioinform Biol Insights. 2023 Jul 14:17:11779322231186481. doi: 10.1177/11779322231186481. eCollection 2023.

Authors

Md Anisur Rahman¹, Md Al Amin², Most Nilufa Yeasmin³, Md Zahidul Islam³

Affiliations

¹ Department of Pharmacy, Islamic University, Kushtia, Bangladesh.
² Department of Computer Science & Engineering, Prime University, Dhaka, Bangladesh.
³ Department of Information & Communication Technology, Islamic University, Kushtia, Bangladesh.

Abstract

The COVID-19 coronavirus, which primarily affects the lungs, is the source of the disease known as SARS-CoV-2. According to "Smoking and COVID-19: a scoping review," about 32% of smokers had a severe case of COVID-19 pneumonia at their admission time and 15% of non-smokers had this case of COVID-19 pneumonia. We were able to determine which genes were expressed differently in each group by comparing the expression of gene transcriptomic datasets of COVID-19 patients, smokers, and healthy controls. In all, 37 dysregulated genes are common in COVID-19 patients and smokers, according to our analysis. We have applied all important methods namely protein-protein interaction, hub-protein interaction, drug-protein interaction, tf-gene interaction, and gene-MiRNA interaction of bioinformatics to analyze to understand deeply the connection between both smoking and COVID-19 severity. We have also analyzed Pathways and Gene Ontology where 5 significant signaling pathways were validated with previous literature. Also, we verified 7 hub-proteins, and finally, we validated a total of 7 drugs with the previous study.

Keywords: COVID-19; GSEA; Smoking; bio-informatics; gene ontology.