J Genet Eng Biotechnol. 2026 Mar;24(1):100650. doi: 10.1016/j.jgeb.2025.100650. Epub 2025 Dec 24.
ABSTRACT
BACKGROUND: SARS-CoV-2 causes mortality in a considerable number of patients with COVID-19. The association of comorbidities and gender with the expression of lncRNAs and mRNAs in COVID-19 patients is not fully understood. The purpose of the present study was to explore this association.
METHOD: We used Transcriptomics data for lncRNAs and mRNAs from the integrated Gene Expression Omnibus (GEO) to identify Differentially Expressed Genes (DEGs) using R software for statistical and data analysis. Then, we carried out Gene Ontology (GO) analysis and constructed a Protein-Protein Interaction (PPI) network to identify interactions between the genes.
RESULTS: In this study, we divided samples into four groups and compared Differentially Expressed lncRNAs (DEls) and DEGs. Genes enriched in immune response and cytokine pathways were identified by GO analysis. By considering the protein-protein interaction network, the hub genes were ALAS2, CCL2, AHSP, and IL5.
CONCLUSION: mRNAs and lncRNAs could be used to identify the effects of SARS-CoV-2 on defined parameters (such as gender, main comorbidities in recovery, and treatment stages). Heme/hemoglobin metabolism was enriched in groups 1, 2, and 4, with four common genes (ALAS2, AHSP, HBD, and CA1) that are associated with the immune response to infection. CCL2 was enriched in group 3 and its expression was remarkably high in patients with an unfavorable outcome compared to other cases. Also, while both IL-5 and ALAS2 were enriched in group 4, IL-5 appeared to have no significant role in COVID-19. Overall, we conducted a bioinformatics analysis to predict how mRNAs and lncRNAs interact in patients with different characteristics such as gender, underlying disease, and treatment or recovery stages. mRNAs and lncRNAs can be potential biomarkers to examine the effect of SARS-CoV-2 on defined parameters.
PMID:41839673 | DOI:10.1016/j.jgeb.2025.100650
