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

Front Immunol. 2023 Mar 8:13:1094644. doi: 10.3389/fimmu.2022.1094644. eCollection 2022.

Abstract

Background: 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.

Methods: 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 ACE2 (rs2285666), MX1 (rs469390), and TMPRSS2 (rs2070788) variants. GemStone™ and OMIQ software were used for cytometry analysis.

Results: 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 CD14dim 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 CD14dim/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 TMPRSS2 (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 C14dim/CD33+.

Conclusions: Here, we report the interesting role of TMPRSS2, CD45-, CD163/CD206, and CD33 in COVID-19 aggressiveness. This strength is reinforced for aggressiveness biomarkers when TMPRSS2 and CD45-, TMPRSS2 and CD163/CD206, and TMPRSS2 and CD14dim/CD33+ are combined.

Keywords: COVID-19; CyTOF; SNPs; biomarkers; cytometry.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Antigens, CD / metabolism
  • Biomarkers
  • COVID-19*
  • Female
  • Humans
  • Middle Aged
  • Quality of Life*
  • Receptors, Cell Surface / metabolism
  • Serine Endopeptidases / genetics
  • Sialic Acid Binding Ig-like Lectin 3

Substances

  • CD163 antigen
  • Antigens, CD
  • Receptors, Cell Surface
  • Biomarkers
  • TMPRSS2 protein, human
  • Serine Endopeptidases
  • CD33 protein, human
  • Sialic Acid Binding Ig-like Lectin 3

Grants and funding

This project is partially funded by “Desarrollo e Innovación (I+D+i) en Biomedicina y en Ciencias de la Salud en Andalucía, ´ FEDER”, internal code PECOVID-0006-2020, by Consejería de ´ Salud, Junta de Andalucía and ´ “Uso de la metodologíá NGS y CYTOF para caracterizar a los pacientes con COVID-19”, internal code CV20-36740, by Secretaria General Universidades, Investigación y Tecnología, Junta de Andalucía