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Expression of ACE2 and TMPRSS2 and the severity of COVID-19
Samantha Sanches De Carvalho1, Anna Carolina Blanco Capassi Santos1, Marcos Yuji Shiroma Graziano2
1Clinical Analysis Laboratory, FMABC University Center, Santo André, São Paulo 09060-870, Brazil.
Abstract:
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for coronavirus disease 2019 (COVID-19), uses the angiotensin-converting enzyme 2 (ACE2) receptor and transmembrane serine protease 2 (TMPRSS2) to enter host cells. Variability in gene expression of these entry factors has been hypothesized to influence susceptibility and disease severity. The present study aimed to evaluate the expression of ACE2 and TMPRSS2 in nasopharyngeal cells and their association with COVID-19 infection and clinical outcomes. Nasopharyngeal samples from 491 individuals (aged 18-80 years) treated in public hospitals in Brazil during 2020 were analyzed. Patients were categorized based on SARS-CoV-2 reverse transcription-quantitative polymerase chain reaction (RT-qPCR) results and disease severity (including intensive care unit admission). Gene expression levels of ACE2 and TMPRSS2 were quantified using RT-qPCR, and statistical analyses assessed associations with infection status, age, sex, and disease severity. The findings revealed that infected individuals were significantly older (P=0.0010) and predominantly male (52.9%). ACE2 expression was significantly reduced in SARS-CoV-2-positive individuals compared with negative individuals (P<0.001), but no association with severity or sex was observed. By contrast, high ACE2 levels were found in moderately symptomatic SARS-CoV-2-negative individuals. TMPRSS2 expression did not significantly differ by infection status or disease severity. In summary, ACE2 downregulation appeared to be associated with SARS-CoV-2 infection, potentially reflecting viral evasion mechanisms. However, neither ACE2 nor TMPRSS2 gene expression in the nasopharynx served as a reliable biomarker for predicting COVID-19 severity. These findings underscore the need for multifactorial models integrating host, viral, and clinical factors to improve our understanding disease progression.
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