How To Predict Who Is Most Likely To Develop Long COVID

A pair of new studies have homed in on key biomarkers that could help identify, at the point of initial infection, those most at risk of developing long COVID. The studies suggest a combination of immune biomarkers and acute symptoms can be used to predict a person’s likelihood of long COVID. Anywhere from 10 to 70 percent of COVID-19 cases can display persistent symptoms lasting weeks, or even months, past an initial acute infection.

The study identified a number of factors that could be measured during the initial illness and correlated with subsequent long COVID. In particular, the research found patients with higher SARS-CoV-2 RNA levels in the blood during their acute illness were more likely to go on to develop long COVID. Levels of immune cells known as autoantibodies were also found to correlate with lingering symptoms.

A recent Ceders-Sinai study also found elevated levels of autoantibodies in long COVID patients over six months past their initial infection.

Elevated blood levels during a COVID-19 infection could be linked to the immune system abnormalities some researchers have connected to long COVID. Jim Heath, president of the Institute for Systems Biology and co-corresponding author on the study, said these kinds of investigations into the early biomarkers of long COVID will not only help identify and treat those patients experiencing persistent disease, but should also shed light on other post-viral syndromes.

Around half of those initially mild COVID cases and 82 percent of severe cases experienced persistent long COVID symptoms.

Two immune biomarkers specifically stood out to the researchers as predictive of long COVID. Low levels of immunoglobulin M and immunoglobulin G3 during primary infection correlated with an increased likelihood of long COVID. The researchers then created a model that could generate a long COVID risk score for a patient experiencing acute illness.

Each patient was given a risk score calculating their chances of going on to develop long COVID. Called a PASC score, the study indicated this model was more accurate than any current protocol for predicting which patients would develop long COVID. Further work is needed to validate these predictive signs of long COVID in larger cohorts of patients, but if those most susceptible to the chronic condition can be identified early, then treatments can be tested to hopefully prevent it from developing.