B22-05 Toward Precision Biologic Selection: Metabolite Ratios Predict Omalizumab Response in Severe Asthma

Rationale Severe asthma remains a major clinical challenge, with multiple biologics available but no reliable biomarkers to guide therapy selection. Circulating metabolites are associated with asthma pathobiology and treatment response, but their value in predicting response to biologic therapy has not been established. Objectives To create a metabolite-based pre-treatment clinical biomarker for omalizumab response. Methods Longitudinal plasma samples from 168 participants enrolled in the Study of Mechanisms of Action of Omalizumab in Severe Asthma (SoMOSA) underwent global and targeted metabolomic profiling. Treatment response outcomes included ≥50% reduction in oral corticosteroid (OCS) use, exacerbations, and Asthma Control Test (ACT) improvement at 52 weeks. Logistic, elastic net, and mixed-effects regression models assessed the relationship between metabolites and these outcomes. The primary findings were validated in an independent cohort from the Mass General Brigham Biobank (MGBB). Measurements and Main Results Individual metabolites did not pass multiple-testing correction for association with outcomes. In contrast, multiple week-52 metabolite ratios, particularly sphingolipid-to-steroid and ceramide-to-steroid measures, were significantly associated with OCS reduction (p = 0.041 to 0.05, Meff corrected) and ACT improvement (fdr p = 0.043 to 0.05). Models built from a subset of week-52 metabolite ratios identified via regularized feature selection achieved high accuracy in classifying treatment response (median AUC=0.86). Surrogate measures of these ratios using baseline metabolites predicted treatment response with nearly the same accuracy (median AUC=0.85). Strong associations between these metabolite ratios and treatment response were replicated in the MGBB cohort (p = 0.046 to 0.05). Conclusions Sphingolipid-to-steroid and ceramide-to-steroid ratios are highly predictive of omalizumab response after a year of use. These findings establish a framework for metabolomics-guided precision medicine in severe asthma and support the development of translatable biomarker panels to optimize biologic therapy for omalizumab.