Table 1.

Biomarkers in type 2 COPD.

Biomarkers	Strengths	Limitations	Predictive value	Clinical interpretation
BEC	Widely accessible and standardized; Validated correlate of sputum eosinophilia (r=0.57); Robust clinical trial evidence for efficacy prediction.	Subject to variability (circadian, steroids, infection); Unclear relationship with long-term lung function decline; Drug-specific thresholds; not interchangeable	High. Key predictive biomarker for treatment response	Drug-specific; Trial-validated thresholds; Monitor longitudinally
FeNO	Non-invasive; Easily reproducible; Reflects airway eosinophilic inflammation.	Subject to variability (smoking status and body weight); Limited predictive data specifically for COPD biologics.	Moderate. Predicts exacerbation risk and ICS response; Potential marker for IL-13 targeted therapy	A supplementary biomarker to BEC; Requires cautious interpretation in smokers.
Serum Periostin	Elevated in COPD patients vs. controls	Conflicting results regarding association with Type 2 inflammation & ICS response in COPD; Limited value in predicting future risk (exacerbation, death).	Low. Not a reliable standalone predictive biomarker in COPD	Currently has limited clinical utility in COPD management.
Genetic Polymorphisms (e.g., IL-13)	Reveals underlying disease mechanisms and susceptibility.	Relationship with eosinophilic COPD endotype not yet validated	To be determined. Associated with COPD risk and lung function decline, but therapeutic predictive value is unclear.	Primarily a research tool at present
Sputum Multi-omics	Provides deep molecular phenotyping; Identifies gene signatures (e.g., GAL3ST2, ALOX15) with high predictive power.	Not routinely available; operational complexity.	Potentially High. May surpass eosinophil count in predicting outcomes (e.g., exacerbations after ICS withdrawal).	A promising tool for future precision medicine; Not yet for routine clinical use.