However, the team emphasized the need for further studies and direct clinical trials to confirm the results and assess the economic viability before the test can be officially adopted in medical practice.
The researchers explained that this innovative technology represents, for the first time, a relatively reliable biomarker that can predict asthma attacks years in advance, not just weeks or months. The study's findings were published Monday in the journal Nature Communications.
Asthma is one of the most common chronic diseases worldwide, affecting more than 500 million people. Severe asthma attacks place a significant burden on patients and healthcare systems, both in terms of medical complications and treatment costs. Despite the disease's widespread prevalence, there are currently no accurate biomarkers that enable doctors to identify patients most at risk of future severe attacks, as traditional methods fail to distinguish between stable cases and those prone to exacerbation.
The study was based on an analysis of data from three large groups of asthma patients, comprising more than 2,500 participants, supported by decades of electronic medical records. Researchers used a high-throughput, advanced technique known as metabolomics to measure small molecules in the blood of asthma patients.
The team discovered a crucial relationship between two classes of bioactive metabolites, sphingolipids and steroids, and the level of asthma control.
The results showed that the sphingolipid-to-steroid ratio in the blood is a strong predictor of the risk of attacks over a five-year period with an accuracy of up to 90 percent.
In some cases, the predictive model was able to differentiate the timing of the first attack in high- and low-risk patients by nearly a full year.
The researchers noted that one of the biggest challenges in asthma treatment is the difficulty in predicting severe attacks.
They emphasized that measuring the balance between sphingolipids and steroids allows for the identification of high-risk patients and early intervention before an attack occurs.
The team added that focusing on the interaction ratio between sphingolipids and steroids gives the model high predictive accuracy and allows for the development of a practical, low-cost clinical test that can be easily implemented in conventional laboratories.
The researchers believe these results represent a significant step toward applying the concept of precision medicine to asthma treatment, as a simple blood test could be developed to detect hidden metabolic abnormalities in patients whose condition appears outwardly stable.
However, the team emphasized the need for further studies and direct clinical trials to confirm the results and assess the economic feasibility before the test can be officially adopted in medical practice.