Lipid Ratio Score May Predict Asthma Exacerbation Risk

A metabolomics-based score using sphingolipid and steroid levels could help identify high-risk asthma patients.

Apr. 3, 2026 at 6:20am

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A translucent X-ray-style image revealing the intricate internal structures of an asthmatic lung, with ghostly lines and shapes conveying the complex biological processes underlying exacerbation risk.A novel biomarker-based model could help identify asthma patients at high risk for exacerbations, enabling targeted interventions to prevent devastating lung damage.Boston Today

Researchers have developed a metabolomics-derived model that uses sphingolipid-to-steroid ratios to predict the risk of asthma exacerbations. The model showed strong predictive performance across multiple cohorts, with the potential to inform early intervention and treatment optimization for high-risk patients.

Why it matters

Asthma exacerbations are a major healthcare burden and cause of disease morbidity, leading to progressive lung damage and enhanced disease severity. However, the heterogeneity of asthma makes it difficult to identify individuals at high risk for future exacerbations. This new biomarker-based model could address this critical unmet need by enabling clinicians to better stratify asthma patients and implement preventative measures for those at greatest risk.

The details

The study used metabolomic profiling to identify predictive biomarkers, finding that sphingolipid and steroid profiles may support clinically actionable risk stratification. Specifically, the researchers identified sphingolipid-to-steroid ratios, such as Cer(d18:1/20:1):cortisone and HexCer(d18:1/24:1):cortisone, as key discriminators of asthma exacerbation risk. These ratios were able to separate high- and low-risk patients for up to 366 days, with strong predictive accuracy.

  • The study included three cohorts totaling 2,513 individuals with asthma.

The players

Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, and Harvard Medical School

The research team that conducted the study and developed the metabolomics-based model to predict asthma exacerbation risk.

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What’s next

If further validation studies confirm the model's accuracy, the sphingolipid and steroid biomarkers could be developed into a clinical test to help identify asthma patients at high risk for exacerbations, enabling clinicians to implement preventative measures and optimize treatment for these individuals.

The takeaway

This metabolomics-based model represents a significant advancement in asthma risk stratification, providing a potential solution to a longstanding challenge in managing this complex and heterogeneous disease. By leveraging sphingolipid and steroid biomarkers, clinicians may gain a powerful new tool to identify high-risk patients and intervene early to prevent devastating asthma exacerbations.