Allergic and eosinophilic asthma in the era of biomarkers and biologics: similarities, differences and misconceptions

Abstract

Objective: Severe asthma is associated with substantial personal and economic burden; maintaining disease control is the key management goal. Increased understanding of asthma heterogeneity and development of type 2 (T2)-targeting biologics has substantially advanced disease management and outcomes; however, despite both being driven by T2 inflammation, allergic and eosinophilic asthma have different treatment recommendations. We sought to better understand the similarities and differences between allergic and eosinophilic asthma and highlight where misconceptions may arise.

Data sources: Published articles, pivotal trials, post hoc analyses, and asthma clinical guidelines sourced from PubMed.

Study selections: Sources reporting allergic and eosinophilic asthma classifications, disease mechanisms, and biomarkers associated with treatment response.

Results: This review highlights that severe allergic and eosinophilic asthma are both driven by T2 inflammation with eosinophils playing a cardinal role. Despite this overlap, treatment recommendations differ based on asthma classification. T2 cytokine gene expression is a reasonably well-established research tool, but not a well-established biomarker in clinical practice, unlike blood eosinophil counts, fractional exhaled nitric oxide, and immunoglobulin E; the clinical relevance of immunoglobulin E as a predictive biomarker remains unclear.

Conclusion: Asthma classifications that can be easily characterized at patient level to ensure accurate diagnosis, predict disease trajectory, and treatment response are required. The current dichotomy of allergic and eosinophilic asthma classifications is likely too simplistic, given the similar eosinophil-mediated disease pathophysiology in both classifications. Our results provide future directions to guide clinically meaningful interpretation of asthma endophenotypes, which may improve understanding of severe asthma characterization and aid future advances in defining responders more precisely with personalized medicine approaches.