Scientists find new truth about COVID-19 infection and why the disease impacts people differently

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In a new study, researchers are searching for how the SARS-CoV-2 virus infects the lungs – and they’re challenging what has become an accepted truth about the virus.

The research was conducted by a team at McMaster University and the University of Waterloo

Previously, scientists have determined that entry of SARS-CoV-2 into cells occurs through a receptor on the cell surface, known as ACE2.

But the team has found that the ACE2 receptor is at very low levels in human lung tissue.

The finding suggests that there must be other ways, other receptors for the virus, that regulate its infection of the lungs.

Finding such low levels of ACE2 in lung tissue has important implications for how we think about this virus. The team says ACE2 is not the full story and maybe more relevant in other tissues such as the vascular system.

Their findings have been confirmed independently by other researchers in Molecular Systems Biology.

Now, to explore alternate additional infection pathways and different patient responses to infection, the team is 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.

The ongoing study will better identify and treat patients who are at risk of developing serious complications and provide predictive capacity for hospitals.

The team says 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 individual patient, with their unique characteristics, heavily influences COVID-19 disease severity.

The researchers think it is the lung immune system that differs between COVID-19 patients, and by understanding which patients’ lung immune systems are helpful and which are harmful, they may be able to help physicians pro-actively manage the most at-risk patients.

They will correlate positive and negative COVID-19 cases with clinical outcomes and ultimately use this data to generate predictive algorithms related to morbidity and mortality.

The aim is to use this predictive information to optimize health care delivery.

One author of the study is Jeremy Hirota, an Assistant Professor of Medicine at McMaster.

The study is published in the European Respiratory Journal.

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