SnoRNAs and miRNAs Networks Underlying COVID-19 Disease Severity
Aijaz Parray, Fayaz Ahmad Mir, Asmma Doudin, Ahmad Iskandarani, Mohammed Danjuma, Raheem Ayadathil, Alaaedin Abdelmajid, Ibrahim Abdelhafez, Rida Arif, Mohammad Mulhim, Mohammed Abukhattab, Shoukat Rashhid Dar, Ala‐Eddin Al Moustafa, Eyad Elkord, Abdul Latif Al Khal, Abdel‐Naser Elzouki, Farhan Cyprian
Abstract
There is a lack of predictive markers for early and rapid identification of disease progression in COVID-19 patients. Our study aims at identifying microRNAs (miRNAs)/small nucleolar RNAs (snoRNAs) as potential biomarkers of COVID-19 severity. Using differential expression analysis of microarray data (n = 29), we identified hsa-miR-1246, ACA40, hsa-miR-4532, hsa-miR-145-5p, and ACA18 as the top five differentially expressed transcripts in severe versus asymptomatic, and ACA40, hsa-miR-3609, ENSG00000212378 (SNORD78), hsa-miR-1231, hsa-miR-885-3p as the most significant five in severe versus mild cases. Moreover, we found that white blood cell (WBC) count, absolute neutrophil count (ANC), neutrophil (%), lymphocyte (%), red blood cell (RBC) count, hemoglobin, hematocrit, D-Dimer, and albumin are significantly correlated with the identified differentially expressed miRNAs and snoRNAs. We report a unique miRNA and snoRNA profile that is associated with a higher risk of severity in a cohort of SARS-CoV-2 infected patients. Altogether, we present a differential expression analysis of COVID-19-associated microRNA (miRNA)/small nucleolar RNA (snoRNA) signature, highlighting their importance in SARS-CoV-2 infection.