Relevance of TMPRSS2 , CD163/CD206, and CD33 in clinical severity stratification of COVID-19

Approximately 13.8% and 6.1% of coronavirus disease 2019 (COVID-19) patients require hospitalization and sometimes intensive care unit (ICU) admission, respectively. There is no biomarker to predict which of these patients will develop an aggressive stage that we could improve their quality of life and healthcare management. Our main goal is to include new markers for the classification of COVID-19 patients. Two tubes of peripheral blood were collected from a total of 66 (n = 34 mild and n = 32 severe) samples (mean age 52 years). Cytometry analysis was performed using a 15-parameter panel included in the Maxpar Human Monocyte/Macrophage Phenotyping Panel Kit. Cytometry by time-of-flight mass spectrometry (CyTOF) panel was performed in combination with genetic analysis using TaqMan probes for (rs2285666), (rs469390), and (rs2070788) variants. GemStone™ and OMIQ software were used for cytometry analysis. The frequency of CD163 /CD206 population of transitional monocytes (T-Mo) was decreased in the mild group compared to that of the severe one, while T-Mo CD163 /CD206 were increased in the mild group compared to that of the severe one. In addition, we also found differences in CD11b expression in CD14 monocytes in the severe group, with decreased levels in the female group (p = 0.0412). When comparing mild and severe disease, we also found that CD45 [p = 0.014; odds ratio (OR) = 0.286, 95% CI 0.104-0.787] and CD14 /CD33 (p = 0.014; OR = 0.286, 95% CI 0.104-0.787) monocytes were the best options as biomarkers to discriminate between these patient groups. CD33 was also indicated as a good biomarker for patient stratification by the analysis of GemStone™ software. Among genetic markers, we found that G carriers of (rs2070788) have an increased risk (p = 0.02; OR = 3.37, 95% CI 1.18-9.60) of severe COVID-19 compared to those with A/A genotype. This strength is further increased when combined with CD45 , T-Mo CD163 /CD206 , and C14 /CD33 . Here, we report the interesting role of , CD45 , CD163/CD206, and CD33 in COVID-19 aggressiveness. This strength is reinforced for aggressiveness biomarkers when and CD45 , and CD163/CD206, and and CD14 /CD33 are combined.