Blood Test Predicts Risk for Developing COPD and Other Severe Respiratory Diseases

By LabMedica International staff writers
Posted on 16 Sep 2024

Chronic respiratory diseases, such as chronic obstructive pulmonary disease (COPD), impact millions of adults worldwide and were the third leading cause of death in 2019. Major risk factors include smoking, air pollution, and occupational exposure to chemicals or lung irritants like gas, fumes, and dust. A year-over-year decline in lung function is associated with poor respiratory health outcomes, yet clinicians currently lack an easy method to determine if a patient is experiencing a rapid deterioration in lung function. There is a pressing need for an easy-to-implement clinical tool that can capture an individual's lung function trajectory at a single point in time, which would enable earlier interventions that could improve long-term lung health. Now, researchers have developed a preclinical blood test to identify adults most likely to develop severe respiratory conditions, including COPD.

The blood test was developed by a scientific team supported by the National Institutes of Health (NIH) and comprising investigators from Northwestern University Feinberg School of Medicine (Chicago, IL, USA) and University of California, Davis Medical Center (Sacramento, CA, USA). The test analyzes 32 proteins that scientists identified as accurate predictors of an adult's increased likelihood of requiring medical care for or dying from severe respiratory illness. The risk score was based on lung health data collected from nearly 2,500 U.S. adults over a 30-year period. To create this risk score, investigators first reviewed lung health data from 2,470 adults aged 18 to 30 who participated in a 30-year cardiovascular health study. They then screened thousands of proteins from blood samples provided by participants at the 25-year mark and selected 32 that best predicted which participants were experiencing a rapid decline in lung function. These 32 proteins were compiled into a score to predict how likely a person would need medical treatment for or die from a lung condition or severe respiratory event.


Image: The blood test analyzes 32 proteins to predict the risk for developing severe respiratory conditions (Photo courtesy of Adobe Stock)

Adults with higher scores had a 17% increased chance of requiring hospital care for respiratory illness, an 84% increased risk of developing COPD, and at least an 81% higher chance of dying from a respiratory disease such as COPD or pneumonia. Those with higher scores also had a 10% increased likelihood of experiencing respiratory exacerbations—such as cough, mucus production, or shortness of breath—that required treatment. Participants in the decades-long study underwent breathing tests to measure their lung function up to six times throughout the study and provided additional lung health data. During this period, 2,332 participants experienced a normal decline in lung function, while 138 experienced a sharp decline. To test the risk score, researchers retrospectively assessed respiratory disease risks in more than 40,000 adults from two earlier observational studies. The findings, published in the American Journal of Respiratory and Critical Care Medicine, show that the prediction model successfully identified adults who had the greatest chance of having severe respiratory conditions after accounting for multiple factors, including sex, race, body weight, asthma, and a history of smoking. This type of blood test still needs to be studied in clinical trials before it can be considered for approval by the Food and Drug Administration as a screening tool to help predict risks for chronic respiratory diseases.

“We are still not ready for this test to be used in practice, but it’s a promising advance,” said James P. Kiley, Ph.D., director of the Division of Lung Diseases at NIH’s National Heart, Lung, and Blood Institute (NHLBI), which funded the study. “It consolidates insights from decades of breathing tests and medical evaluations into a single tool that has the potential to identify patients at risk for severe disease and complications.”

Related Links:
Northwestern University Feinberg School of Medicine
University of California


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