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08-24-2021

Enzyme driving COVID-19 mortality can shred membranes of vital organs

A new study suggests that an enzyme with a mysterious role in severe inflammation may be the most important predictor of COVID-19 mortality. The research was a collaboration between scientists at the University of Arizona, Stony Brook University and the Wake Forest University School of Medicine. 

The scientists analyzed blood samples from COVID-19 patients and found that the enzyme sPLA2-IIA seems to serve as a reliable indicator of whether a patient will die from their infection. The enzyme has similarities to an enzyme in rattlesnake venom that often plays the role of destroying microbial membranes.

In healthy people, sPLA2-IIA is present at low levels. At higher levels, the enzyme can “shred” the membranes of otherwise healthy organs. 

“It’s a bell-shaped curve of disease resistance versus host tolerance. In other words, this enzyme is trying to kill the virus, but at a certain point it is released in such high amounts that things head in a really bad direction, destroying the patient’s cell membranes and thereby contributing to multiple organ failure and death,” explained study senior author Dr. Floyd (Ski) Chilton 

Understanding the possible problems caused by the enzyme allows doctors a possible treatment with an sPLA2-IIA inhibitor that has already been tested. 

According to Dr. Maurizio Del Poeta of the Renaissance School of Medicine, the study supports a new therapeutic target to reduce or even prevent COVID-19 mortality.

The research took place under stressful medical emergency conditions, which means it was not tested as thoroughly as normal drug research, yet it still has real applicability. 

“These are small cohorts, admittedly, but it was a heroic effort to get them and all associated clinical parameters from each patient under these circumstances,” said Dr. Chilton.

“As opposed to most studies that are well planned out over the course of years, this was happening in real time on the ICU floor.”

The researchers used machine learning algorithms to analyze thousands of patient data points. Beyond traditional risk factors, such as preexisting conditions, the analysis was focused on biochemical enzymes and individual levels of lipid metabolites.

“In this study, we were able to identify patterns of metabolites that were present in individuals who succumbed to the disease,” said lead study author Justin Snider, an assistant research professor in the UArizona Department of Nutrition.

“The metabolites that surfaced revealed cell energy dysfunction and high levels of the sPLA2-IIA enzyme. The former was expected but not the latter.”

This heroic effort by fast working scientists could save lives by reducing COVID-19 mortality as the pandemic continues.  

The study is published in Journal of Clinical Investigation.

By Zach Fitzner, Earth.com Staff Writer

 

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