Differential diagnosis of asthma and COPD: Established and emerging biomarkers and technologies

Asthma and chronic obstructive pulmonary disease (COPD) represent the two most prevalent chronic respiratory conditions worldwide, affecting hundreds of millions of individuals and imposing substantial morbidity and mortality. Despite their distinct biological mechanisms, these diseases frequently exhibit overlapping clinical features-including dyspnea, cough, and wheezing-that complicate differential diagnosis, particularly in smoking adults, older patients, and those with mild or fluctuating airflow obstruction. Spirometry remains the cornerstone of diagnostic evaluation, yet its limitations, including dependence on patient effort, reduced sensitivity for early disease, and inability to fully capture small airways involvement, contribute to persistent underdiagnosis and overdiagnosis in clinical practice. This review examines current diagnostic approaches for asthma and COPD, their inherent limitations, and the emerging biomarkers and functional technologies that may improve diagnostic precision. Established biomarkers, including blood eosinophils, fractional exhaled nitric oxide (FeNO), and induced sputum analysis, provide complementary information that refines clinical characterization but lack sufficient disease specificity for standalone use. Novel approaches, including lipidomics, metabolomics, and extracellular vesicle profiling, demonstrate potential for identifying disease-specific molecular signatures and biologically distinct phenotypes, particularly in asthma-COPD overlap. Concurrently, new functional tools-including novel spirometric indices such as Parameter D or FEV3/FEV6, respiratory oscillometry, and artificial intelligence-driven tidal breathing analysis-are enabling more sensitive, effort-independent, and multidimensional assessment of airway disease. The integration of these clinical, functional, inflammatory, and molecular approaches supports a transition toward multimodal diagnostic frameworks that may substantially improve the recognition and differential diagnosis of asthma and COPD, particularly in challenging clinical scenarios and early disease states.