Current Clinical Perspectives of Biomarkers in Respiratory Diseases: A Narrative Review

Respiratory medicine is transitioning from symptom-driven, standardized care to a more precise, patient-specific approach guided by molecular profiling. This evolution is being enabled by advances in liquid biopsy, multiomics, and artificial intelligence (AI) analytics. Fractional exhaled nitric oxide (FeNO) and blood eosinophils, the two commonly used markers in asthma, are now being joined by more precise airway markers such as galectin-10, which could aid clinicians in making more informed decisions for biological treatments. In chronic obstructive pulmonary disease (COPD) similar progress is underway, with treatment now emphasizing inflammation endotypes, especially eosinophilic patterns, to direct therapeutic choices. Alongside these developments, routine blood-based ratios (e.g., platelet-to-lymphocyte and neutrophil-to-lymphocyte) are being explored as predictors of exacerbation risk, and forced oscillation testing (FOT) is proving useful for picking up early disease shifts. In more severe conditions, biomarkers are linked to an early and better prognosis, enabling timely intervention. Markers like Matrix metalloproteinase-7 (MMP-7) and CC chemokine ligand 18 (CCL18) have proven to be reliable indicators of mortality and disease progression in idiopathic pulmonary fibrosis. Meanwhile, in lung cancer, liquid biopsies, especially those measuring circulating tumor DNA and micro-RNA (miRNA) panels, are enhancing screening accuracy while helping to cut down on the high false-positive rates seen with low-dose computerised tomography (CT). Other respiratory conditions such as bronchiectasis, pulmonary embolism, pneumonia, and acute respiratory distress syndrome (ARDS) are also benefiting from biomarker advances. At the same time there is a growing push to standardize how these biomarkers are measured. AI-based clinical decision support systems are also playing an increasingly important role in the translation of all these complicated data into actionable clinical insights. Together these developments pave the way for improved respiratory care that is precise and responsive to individual patient needs.