Evaluation of altered miRNA expression pattern to predict COVID-19 severity

Abstract

Outbreak of COVID-19 pandemic in December 2019 affected millions of people globally. After substantial research, several biomarkers for COVID-19 have been validated however no specific and reliable biomarker for the prognosis of patients with COVID-19 infection exists. Present study was designed to identify specific biomarkers to predict COVID-19 severity and tool for formulating treatment. A small cohort of subjects (n = 43) were enrolled and categorized in four study groups; Dead (n = 16), Severe (n = 10) and Moderate (n = 7) patients and healthy controls (n = 10). Small RNA sequencing was done on Illumina platform after isolation of microRNA from peripheral blood. Differential expression (DE) of miRNA (patients groups compared to control) revealed 118 down-regulated and 103 up-regulated known miRNAs with fold change (FC) expression ≥2 folds and p ≤ 0.05. DE miRNAs were then subjected to functional enrichment and network analysis. Bioinformatic analysis resulted in 31 miRNAs (24 Down-regulated; 7 up-regulated) significantly associated with COVID-19 having AUC>0.8 obtained from ROC curve. Seventeen out of 31 DE miRNAs have been linked to COVID-19 in previous studies. Three miRNAs, hsa-miR-147b-5p and hsa-miR-107 (down-regulated) and hsa-miR-1299 (up-regulated) showed significant unique DE in Dead patients. Another set of 4 miRNAs, hsa-miR-224-5p (down-regulated) and hsa-miR-4659b-3p, hsa-miR-495-3p and hsa-miR-335-3p were differentially up-regulated uniquely in Severe patients. Members of three miRNA families, hsa-miR-20, hsa-miR-32 and hsa-miR-548 were significantly down-regulated in all patients group in comparison to healthy controls. Thus a distinct miRNA expression profile was observed in Dead, Severe and Moderate COVID-19 patients. Present study suggests a panel of miRNAs which identified in COVID-19 patients and could be utilized as potential diagnostic biomarkers for predicting COVID-19 severity.