Phenotyping, Precision Medicine, and Asthma

Abstract The traditional one-size-fits all approach based on asthma severity is archaic. Asthma is a heterogenous syndrome rather than a single disease entity. Studies evaluating observable characteristics called phenotypes have elucidated this heterogeneity. Asthma clusters demonstrate overlapping features, are generally stable over time and are reproducible. What the identification of clusters may have failed to do, is move the needle of precision medicine meaningfully in asthma. This may be related to the lack of a straightforward and clinically meaningful way to apply what we have learned about asthma clusters. Clusters are based on both clinical factors and biomarkers. The use of biomarkers is slowly gaining popularity, but phenotyping based on biomarkers is generally greatly underutilized even in subspecialty care. Biomarkers are more often used to evaluate type 2 (T2) inflammatory signatures and eosinophils (sputum and blood), fractional exhaled nitric oxide (FeNO) and serum total and specific immunoglobulin (Ig) E reliably characterize the underlying inflammatory pathways. Biomarkers perform variably and clinicians must be familiar with their advantages and disadvantages to accurately apply them in clinical care. In addition, it is increasingly clear that clinical features are critical in understanding not only phenotypic characterization but in predicting response to therapy and future risk of poor outcomes. Strategies for asthma management will need to leverage our knowledge of biomarkers and clinical features to create composite scores and risk prediction tools that are clinically applicable. Despite significant progress, many questions remain, and more work is required to accurately identify non-T2 biomarkers. Adoption of phenotyping and more consistent use of biomarkers is needed, and we should continue to encourage this incorporation into practice.