Abstract
SARS-CoV-2, the virus responsible for COVID-19, exhibits structural differences compared to other coronaviruses that impact transmission dynamics and host response. Although vaccines have reduced severe hospitalizations and deaths, understanding the infection remains challenging, and finding viable biomarkers for disease severity would be beneficial. In this context, microRNAs (miRNAs) are a set of small non-coding RNAs that have emerged as potential biomarkers for numerous diseases. However, assessing miRNA expression requires the normalization of RT-qPCR data using appropriate endogenous reference genes. The selection of these reference genes remains a major challenge, directly impacting the accuracy of expression analyses. Although several small RNAs, including snRNAs, have been evaluated, there is still no consensus regarding the optimal reference genes for the normalization of plasma miRNA expression data in COVID-19 infection. This study evaluated five candidate genes-including RNU6B, snRNA U6 (small nuclear RNAs) and three miRNAs (miR-320a, miR-342-3p, and miR-328) as potential endogenous normalizers for analyzing miRNA expression in the plasma of COVID-19 patients. The snRNA U6 showed greater stability using a combination of statistical algorithms (NormFinder, RefFinder, BestKeeper, and GeNorm), indicating that this snRNA can be used as a robust internal reference for analysis in the plasma of COVID-19 patients.