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. Dubbed PASC (Post Acute Sequelae of COVID-19), the condition is more informally known as long COVID and often includes symptoms such as fatigue, shortness of breath, and brain fog.
It is currently a mystery as to which acute COVID patients will go on to experience lingering symptoms. The more severe an initial bout of COVID-19 is, the more likely that person will experience long COVID, but that is one of the few measures doctors currently have to assess a patient’s likelihood of the condition.
“Long COVID is causing significant morbidity in survivors of COVID-19, yet the pathobiology is poorly understood,” explained Jason Goldman, co-corresponding author on one of the new studies. “Our study pairs clinical data and patient-reported outcomes with deep multi-omic analyses to unravel important biological associations that occur in patients with PASC.”
Goldman and colleagues followed more than 300 COVID-19 patients, collecting blood samples at various points both during their acute infection and in the months that followed. 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.
One of the more curious findings in this first study was the detection of increased Epstein-Barr virus (EBV) activity in the blood of COVID-19 patients more likely to experience long COVID. EBV infection commonly occurs in most people while they are young and the virus is known to remain dormant in most people for the rest of their lives.
EBV infection has also recently been linked to multiple sclerosis and is commonly associated with chronic fatigue syndrome. 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.
“Identifying these PASC factors is a major step forward for not only understanding long COVID and potentially treating it, but also which patients are at highest risk for the development of chronic conditions,” said Heath. “These findings are also helping us frame our thinking around other chronic conditions, such as post-acute Lyme syndrome, for example.”
The second new study comes from a team led by researchers from the University of Zurich who followed more than 100 COVID-19 cases for up to a year. 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 (IgM) and immunoglobulin G3 (IgG3) 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. The model combined levels of these two blood-based biomarkers with age, history of asthma, and presence of five key symptoms during the first week of illness (fever, fatigue, cough, shortness of breath, and gastrointestinal symptoms).
The model was tested in an independent cohort of 395 COVID-19 patients. 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.
Source: Institute for Systems Biology