Asthma has a significant degree of variability in both aetiology and therapeutic response, resulting in many asthma patients receiving inappropriate treatment. Biomarkers suggestive of underlying pathological processes might be utilised to identify disease subtypes, predict or monitor therapy response, and assess prognosis. However, the uses and limits of newly found biomarkers differ from those of previously recognised biomarkers. Despite their strong associations, conventional indicators for type 2-high asthma, such as blood eosinophils, percentage of exhaled nitric oxide, serum IgE, and periostin, have poor sensitivity and specificity. By integrating biomarkers and/or employing omics methods, more unique models have been constructed. A model with a 100% positive predictive value for identifying type 2-high asthma was recently created using a combination of minimally invasive biomarkers.

Individualizing asthma treatment regimens based on biomarkers is required to enhance asthma management. However, the currently known conventional biomarkers’ poor characteristics restrict their clinical usefulness. Before new biomarkers and models based on combinations and/or omics analysis can be widely used in clinical practise, they must be verified and standardised. The discovery of robust biomarkers will enable the development of more effective precision medicine-based asthma treatment methods.