Asthma is one of the world's most common chronic diseases, affecting over 500 million people. Despite its prevalence, clinicians lack reliable biomarkers to identify which patients are at high risk for future attacks.
Now, researchers at Mass General Brigham and Karolinska Institutet have identified a new method to predict asthma attacks with a high degree of accuracy.
The study, published in Nature Communications, analyzed data from three large asthma cohorts totaling over 2,500 participants.
Researchers used metabolomics to measure small molecules in the blood of individuals with asthma. They identified an important relationship between two classes of metabolites—sphingolipids and steroids—and asthma control. Specifically, they found that sphingolipid to steroid ratios could predict exacerbation risk over a 5-year period. In some cases, the model could differentiate the time-to-first attack between high- and low-risk groups by nearly a full year with 90% accuracy.
The team also discovered that while individual metabolite levels provided some insight, the ratio between sphingolipids and steroids was the most powerful predictor of future health.
The researchers believe these findings represent a significant step toward precision medicine for asthma. A clinical assay based on these ratios could be implemented in standard laboratories, helping doctors identify patients who appear stable but have underlying metabolic imbalances.
Data from Mass General Brigham