New Delhi, Sep 28 (IANS) As long Covid becomes a burden for health care providers globally, researchers now report that a blood test taken at the time of Covid-19 infection could predict who is most likely to develop long Covid.
The study by a team from University College London in the UK, published in Lancet eBioMedicine, analysed proteins in the blood of healthcare workers infected with SARS-CoV-2, comparing them to samples from healthcare workers who had not been infected.
Usually protein levels in the body are stable, but they found a dramatic difference in levels of some of the proteins up to six weeks following infection, suggesting disruption to a number of important biological processes.
Using an artificial intelligence (AI) algorithm, they identified a 'signature' in the abundance of different proteins that successfully predicted whether or not the person would go on to report persistent symptoms a year after infection.
If these findings are repeated in a larger, independent group of patients, a test could potentially be offered alongside a polymerase chain reaction (PCR) test that could predict people's likelihood of developing long Covid.
'The study shows that even mild or asymptomatic Covid-19 disrupts the profile of proteins in our blood plasma. This means that even mild Covid-19 affects normal biological processes in a dramatic way, up to at least six weeks after infection,' said lead author Dr Gaby Captur.
The tool predicting long Covid still needs to be validated in an independent, larger group of patients.
'However, using our approach, a test that predicts long Covid at the time of initial infection could be rolled out quickly and in a cost-effective way,' Captur added.
More than 40 per cent of Covid-19 survivors across the world, or over 100 million, have or had long-term effects after recovering, according to a recent study by researchers at the University of Michigan.
For the UK study, researchers analysed blood plasma samples from 54 healthcare workers who had PCR- or antibody-confirmed infection, taken every week for six weeks in spring 2020, comparing them to samples taken over the same period from 102 healthcare workers who were not infected.
The researchers found abnormally high levels of 12 proteins out of the 91 studied among those infected by SARS-CoV-2, and that the degree of abnormality tracked with the severity of symptoms.
A machine learning algorithm, trained on the protein profiles of the participants, was able to distinguish all of the 11 healthcare workers who reported at least one persistent symptom at one year, from infected healthcare workers who did not report persistent symptoms after a year.
'If we can identify people who are likely to develop long Covid, this opens the door to trialling treatments such as antivirals at this earlier, initial infection stage, to see if it can reduce the risk of later long Covid,' said senior author Dr Wendy Heywood.
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