Background At the end of 2019, the world witnessed the emergence and ravages of a viral infection induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Also known as the coronavirus disease 2019 (COVID-19), it has been identified as a public health emergency of international concern (PHEIC) by the World Health Organization (WHO) because of its severity. Methods The gene data of 51 samples were extracted from the GSE150316 and GSE147507 data set and then processed by means of the programming language R, through which the differentially expressed genes (DEGs) that meet the standards were screened. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed on the selected DEGs to understand the functions and approaches of DEGs. The online tool STRING was employed to construct a protein–protein interaction (PPI) network of DEGs and, in turn, to identify hub genes. Results A total of 52 intersection genes were obtained through DEG identification. Through the GO analysis, we realized that the biological processes (BPs) that have the deepest impact on the human body after SARS-CoV-2 infection are various immune responses. By using STRING to construct a PPI network, 10 hub genes were identified, including IFIH1, DDX58, ISG15, EGR1, OASL, SAMD9, SAMD9L, XAF1, IFITM1, and TNFSF10. Conclusion The results of this study will hopefully provide guidance for future studies on the pathophysiological mechanism of SARS-CoV-2 infection. Supplementary Information The online version contains supplementary material available at 10.1186/s40001-021-00609-4.
【저자키워드】 SARS-CoV-2, hub genes, Protein–protein interactions network, Differentially expressed genes, 【초록키워드】 COVID-19, coronavirus disease, viral infection, Coronavirus disease 2019, coronavirus, SARS-COV-2 infection, severity, hub genes, Gene ontology, severe acute respiratory syndrome Coronavirus, Viral, immune responses, International, WHO, genomes, public health emergency, respiratory, Differentially expressed genes, Guidance, function, differentially expressed gene, Protein–protein interaction, IFITM1, DDX58, ISG15, PPI, online tool, human body, data set, Health Organization, World Health Organization, acute respiratory syndrome, supplementary material, biological processes, acute respiratory syndrome coronavirus, acute respiratory syndrome coronavirus 2, approaches, pathophysiological mechanism, GO analysis, functions, STRING, DEGs, Intersection, PPI network, KEGG, PHEIC, IFIH1, EGR1, GSE147507, OASL, SAMD9, SAMD9L, TNFSF10, XAF1, BPS, Genes, programming, Kyoto, Result, selected, identify, performed, approach, screened, analysis, turn, processed, biological processe, 【제목키워드】 Infection, lung, Patient, Bioinformatics analysis, infected with SARS-CoV-2,