Previously, it was known that SARS=CoV-2 enters cells through a receptor on the cell surface, known as ACE2. A new study by the scientists at McMaster University and the University of Waterloo demonstrates that the ACE2 receptor is at very low levels in human lung tissue.
Scientists are now investigating how the SARS-CoV-2 virus infects the lungs.
To explore alternate additional infection pathways and different patient responses to infection, scientists are using nasal swabs that were collected for clinical diagnoses of COVID-19. These samples offer the opportunity to determine which genes are expressed by patients’ cells and associate this information with the development of the patients’ disease.
Jeremy Hirota, co-lead scientist of the team from the Research Institute of St. Joe’s Hamilton and an Assistant Professor of Medicine at McMaster said, “Our finding is somewhat controversial, as it suggests that there must be other ways, other receptors for the virus, that regulate its infection of the lungs.”
“We were surprised that the fundamental characterization of the candidate receptors in human lung tissue had not yet been done systematically with modern technologies.”
Co-lead Andrew Doxey, Professor of Biology at the University of Waterloo, said, “Finding such low levels of ACE2 in lung tissue has important implications for how we think about this virus. ACE2 is not the full story and maybe more relevant in other tissues such as the vascular system.”
The study is expected to identify better and treat patients who are at risk of developing severe complications. It will provide a predictive capacity for hospitals.
Hirota said, “It is clear that some individuals respond better than others to the same SARS-CoV-2 virus. The differential response to the same virus suggests that each patient, with their unique characteristics, heavily influences COVID-19 disease severity.”
“We think it is the lung immune system that differs between COVID-19 patients. By understanding which patients’ lung immune systems are helpful and which are harmful, we may be able to help physicians proactively manage the most at risk-patients.”
Analysts will correlate positive and negative COVID-19 cases with clinical results, and at last, utilize this data to create prescient algorithms identified with morbidity and mortality. The point is to use predictive data to improve health care delivery.
Hirota said, “We’re looking for additional partners to collaborate with us in moving this research forward, as we believe there is an opportunity to develop diagnostic devices with this information.”