Can a simple blood test be used to predict long-COVID-19 outcomes in high-risk populations?
That’s the question researchers at UCLA Health are hoping to answer after receiving a $3.5 million grant from the National Institutes of Health to conduct a five-year, multicenter study.
The study is designed to look at outcomes one year after admission for severe COVID-19 in 500 adult patients. The cohort includes 250 civilian patients at Ronald Reagan UCLA Medical Center, Harbor-UCLA Medical Center and Olive View-UCLA Medical Center representative of Los Angeles County, the most populous county in the U.S.
A second cohort of 250 veteran patients - who are at higher than average U.S. population risk of adverse outcomes - from large Veterans Affairs hospitals in Los Angeles, Atlanta, Houston and New York City, also will be studied.
An algorithm to predict the outcome at the end of one year following hospital admission for COVID-19 will be constructed from 300 patients, with 200 independent patients used to validate the results.
The study fills an urgent need to develop prediction tests for adverse short- and long-term outcomes for high-risk COVID-19 patients, says Mario Deng, MD, FACC, FESC, professor of medicine at the David Geffen School of Medicine at UCLA.
“We’re particularly interested in long-COVID outcomes in those 20% of patients admitted to the hospital out of whom another 20% either go on a respirator or die, meaning 2% to 4% of the total COVID-19-infected population,” says Dr. Deng, overall project director and the study’s principal investigator, along with Dr. David Beenhouwer from the Greater Los Angeles VA system.
“We want to test the hypothesis that, at the time of admission, one singular blood sample based on information of the activity of the 37,000 genes in our white blood cells, help us predict better than with clinical data alone what happens a year later,” Dr. Deng says. “The system's biological precision medicine test development follows the same technology we used for our heart failure survival blood test MyLeukoMAP and the heart transplant rejection test AlloMAP.”
Clinical organ function assessment and prediction tools such as respiratory, cardiovascular and other scores were designed for other illnesses, so they can’t precisely predict the long-term prognosis of COVID-19, he says.
Several high-risk populations have been identified for the study including older adults, males, people of color and those with certain underlying health conditions such as diabetes or obesity.
“I think at this point in time no one has really identified the answer to the question: Why do between 10% and 50% of people who have acute COVID develop long-COVID (termed Post-Acute Sequelae of SARS-CoV-2 infection, or PASC, by Francis S. Collins, MD, PhD., director of the National Institutes of Health), meaning not only lung problems but problems across different organ systems, including heart, kidney and brain problems?” Dr. Deng says.
Diagnostic blood tests
While at Columbia University, Dr. Deng was a key member of a multi-investigator team of academic and bio-tech (CareDx Inc.) researchers that developed AlloMAP, the first noninvasive, Food and Drug Administration-approved molecular diagnostic blood test that helps rule out acute cellular rejection in heart transplant recipients without taking biopsy samples from the patient’s heart using an invasive heart catheter. The test has reduced the need for routine protocol heart biopsies by more than 50%, Dr. Deng says.
After moving to UCLA as director of the advanced heart failure, mechanical support and heart transplant program in 2011, Dr. Deng initiated the development of an advanced heart failure survival prediction test called MyLeukoMAP, which is now part of a national study by a molecular diagnostics company he co-founded called LeukoLifeDx Inc.
“We hypothesize that we as humans use similar immunological pathways in various organ failure syndromes across the board,” he says. “And that’s why we believe our test concept can work in immune system failure syndromes such as long-COVID.”
Test could reduce deaths, inform treatment
Researchers hope that a prediction test that performs well in this hospitalized group will reduce morbidity and mortality rates by helping physicians make better overall recommendations and guide triaging and treatment decisions for their patients, enabling patients and their families to make more informed decisions about their care.
In addition, a prediction test could help hospitals more meaningfully allocate resources in short supply, such as ventilators or therapeutics with limited availability, Dr. Deng says.
It also could have implications for how future health care professionals are trained to communicate with families.
“If someone has severe COVID and is admitted and the prognosis from molecular testing is grim, how does one communicate treatment preferences including a potential end-of-life scenario in a meaningful way?” Dr. Deng says, pointing to the expanding collaborative UCLA Education & Medicine Relational Medicine Project led by .
Dr. Deng hopes this grant will pave the way for studies with additional cohorts, including non-hospitalized patients treated in emergency departments, children under 18 and populations outside the U.S.
“We need to see this as a global pandemic and think about collaboration with other regions in the world,” he says, “because there might be a benefit to comparing the clinical and molecular profiles across different regions of the globe.”
Jennifer Karmarkar is the author of this article.
