Identification of key molecules in COVID-19 patients significantly correlated with clinical outcomes by analyzing transcriptomic data.

BACKGROUND

Although several key molecules have been identified to modulate SARS-CoV-2 invasion of human host cells, the molecules correlated with outcomes in COVID-19 caused by SARS-CoV-2 infection remain insufficiently explored.

METHODS

This study analyzed three RNA-Seq gene expression profiling datasets for COVID-19 and identified differentially expressed genes (DEGs) between COVID-19 patients and normal people, commonly in the three datasets. Furthermore, this study explored the correlation between the expression of these genes and clinical features in COVID-19 patients.

RESULTS

This analysis identified 13 genes significantly upregulated in COVID-19 patients' leukocyte and SARS-CoV-2-infected nasopharyngeal tissue compared to normal tissue. These genes included , , , , , , , , , , , , and , all of which are involved in antiviral immune regulation. We found that these genes' downregulation was associated with worse clinical outcomes in COVID-19 patients, such as intensive care unit (ICU) admission, mechanical ventilatory support (MVS) requirement, elevated D-dimer levels, and increased viral loads. Furthermore, this analysis identified two COVID-19 clusters based on the expression profiles of the 13 genes, termed COV-C1 and COV-C2. Compared with COV-C1, COV-C2 more highly expressed the 13 genes, had stronger antiviral immune responses, were younger, and displayed more favorable clinical outcomes.

CONCLUSIONS

A strong antiviral immune response is essential in reducing severity of COVID-19.