study: The ratio of circulating levels of sphingolipids to steroids predicts asthma exacerbation. Image credit: Prostock-studio / Shutterstock

In a recent study published in the journal nature communicationsresearchers analyzed medical records and blood samples of more than 2,500 biobank participants with asthma and identified a new predictive method. biomarker Prepare for future asthma worsening. The study used a metabolomics approach and found that the ratio of circulating sphingolipids (a type of fat) to steroids (hormones) was a strong discriminator of subsequent disease risk.

The identified metabolite ratio has a discriminatory performance (area under the curve, AUC) When combined with selected clinical variables, it significantly exceeds current clinical standards such as pulmonary function tests and blood eosinophil counts when used alone. These findings may advance risk stratification in asthma management and, although the clinical benefit of early intervention has not been directly tested, they may allow clinicians to identify individuals at high risk for future exacerbations long before clinical worsening becomes apparent.

Limitations of current asthma risk assessment

Asthma is a chronic lung disease characterized by severe inflammation, narrowing of the airways, or excessive mucus production, resulting in wheezing, coughing, and difficulty breathing. Despite decades of research, asthma remains notoriously heterogeneous (patient-specific variation in disease manifestation).

While some people can manage their symptoms with occasional use of an inhaler, others suffer from recurrent “exacerbations,” severe flare-ups that lead to progressive lung damage, airway remodeling, and emergency room visits.

Surprisingly, although asthma exacerbations are a major cause of disease morbidity and hospitalization, clinicians currently lack reliable biomarkers to prospectively predict exacerbation risk. Currently, patient risk is forced expiratory volume (FEV1) A test that measures the amount of air a person can exhale in one second, or a test that counts eosinophils (a type of white blood cell) and tests immunoglobulin E (IgE) Antibodies in the blood.

Unfortunately, while these indicators capture the current state of the disease, they have been shown to be inadequate at predicting future instability. Although previous studies have revealed these limitations and disruptions in metabolic pathways associated with respiratory diseases, mechanistic studies of the interactions between these pathways and their contribution to future asthma exacerbations are still lacking.

Research design and metabolomics framework

This study aims to address these knowledge gaps and aid future asthma interventions by leveraging metabolomics, the study of metabolites left behind by cellular processes. Metabolites have been shown to provide a unique snapshot of health status, reflecting the combined influence of a patient’s genetics and environment.

This study specifically utilized metabolomics data from three independent cohorts of 2,513 adults at the Massachusetts General Brigham Biobank. This study design included longitudinal electronic medical records (EMR) Collect participants’ serum and plasma samples within a single integrated health care system, with follow-up extending up to 25 years for some individuals.

Analytical strategies and predictive modeling

The research analysis was conducted in three stages.

Global profiling: First, an untargeted “global” analysis of the discovery cohort (MGBB-KAS, n = 1,080) was performed to identify metabolic pathways that are commonly disrupted in asthma patients with a history of exacerbations.

Targeted assay: Based on the initial hits, targeted mass spectrometry was performed to quantify 166 specific metabolites (77 sphingolipids, 18 steroids, and 71 microbial-derived metabolites). These include sphingolipids (bioactive lipids involved in cells). cell signaling), steroids (endogenous hormones), and metabolites derived from intestinal bacteria.

Predictive Modeling: Finally, using advanced statistical methods (elastic net and Cox regression), we built a predictive model that can predict asthma exacerbations over a 5-year period. This predictive model was defined using EMR-documented oral corticosteroid treatment, a practical but indirect surrogate for exacerbation events.

In contrast to previous attempts to identify asthma biomarkers, which prioritize absolute concentrations of potential biomarkers, the present analysis calculated and evaluated metabolite ratios based on the hypothesis that the balance between biological pathways is better indicative of disease status than single molecules alone.

Key metabolic signatures associated with risk

Analysis of studies revealed sphingolipid to steroid ratios as a consistent biological imbalance in participants prone to asthma attacks. Specifically, it’s a combination of high levels of sphingolipids (such as ceramides and sphingomyelins) and low levels of steroids (such as dehydroepiandrosterone sulfate). Deesor cortisone) pinpointed an increased risk of future exacerbations.

Utilizing 21 sphingolipid-to-steroid ratios identified in a multivariate 5-year predictive model, this study revealed that these ratios can predict future asthma exacerbation risk with high discriminatory power (AUC = 0.90 in the discovery cohort and 0.89 in the replication cohort), which was significantly higher than the current “gold standard” clinical approach when these clinical markers were used without metabolomic ratios. The authors note that past exacerbation history remains a strong predictor and may partially overlap with metabolomic risk signals.

The model was also able to successfully differentiate time to first exacerbation. Patients identified as high-risk were shown to have their first attack significantly earlier, often by more than 100 days, compared to the low-risk group.

Of note, this study also identified microbial-derived metabolites associated with asthma exacerbations, but their relative contribution was significantly lower than that of sphingolipids and the body’s endogenous steroid pathways.

Implications for accurate asthma management

This study represents a major advance in precision medicine for respiratory health and demonstrates that the interplay between inflammatory lipid signaling (sphingolipids) and hormonal regulation (steroids) is important for understanding susceptibility to asthma exacerbations.

Future research should aim to leverage these findings to develop new clinical tests that allow clinicians to identify individuals at high risk for future exacerbations months or years in advance and potentially guide early risk-tailored management strategies, pending future prospective validation, assessment of clinical utility, and confirmation of generalizability across diverse populations and healthcare settings.