Artificial intelligence may explain why each COVID-19 wave affects people differently

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Researchers have identified what they believe are robust metabolic markers of COVID, a discovery that could lead to better understanding and treatments for people who experience symptoms of the disease months after diagnosis.

Scientists at the University of Surrey collected blood samples from hospital patients and found that COVID-19 altered people’s metabolism. The team noted that the effects of COVID-19 changed over time, with the first wave disrupting metabolites differently than the second.

While researchers noted that many patients’ metabolites relaxed back to normal levels after recovering from COVID-19, a small number remained disrupted for several months after infection.

dr. Holly-May Lewis, lead author of the study from the University of Surrey, says that “about 2 million people are thought to develop symptoms of COVID-19 a month after infection, and 800,000 people still experience symptoms a year later. So it is It is clear that this virus will be with us for a while and that is why the scientific community is obligated to better understand COVID-19 and why the symptoms seem to last longer than average for some.”

The Surrey study analyzed the blood samples from 164 hospitalized patients – 123 with COVID-19 and 41 who delivered a negative PCR test – during the first two waves of infection. Nineteen positive patients also provided samples two to seven months after infection.

Using an artificial intelligence model, the Surrey team identified six metabolites that can be used to identify COVID-19 with 91% accuracy.

Professor Melanie Bailey, corresponding author of the study from the University of Surrey, says that “to our knowledge, this is the first time that COVID-19 has been shown to affect patients’ metabolism differently than in the first wave – which we “We think it’s due to emerging variants. Different COVID variants are known to have different associated symptoms, so it makes sense that this is related to changes in blood chemistry.”

“With this in mind, we then leveraged artificial intelligence to identify biomarkers characteristic of COVID-19 regardless of the COVID wave. This can help us better understand the limitations of the treatments being given and make better ones.”

The article was published in the magazine metabolites.


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More information:
Holly-May Lewis et al, Metabolomics markers of COVID-19 depend on collection wave, metabolites (2022). DOI: 10.3390/metabo12080713

Provided by the University of Surrey

Quote: Artificial intelligence may explain why each COVID-19 wave affects people differently (2022, August 16) retrieved August 16, 2022 from https://medicalxpress.com/news/2022-08-artificial-intelligence-covid-impacts-people .html

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