Threshold-Triggered Immune Dysregulation Precedes Clinical COPD: A Stage-Specific Diagnostic Model Combining Cytokine...

To establish a stage-specific diagnostic model for chronic obstructive pulmonary disease (COPD) high-risk individuals by characterizing immune dysregulation through integrated cytokine and lymphocyte profiling.

In this cross-sectional study, 116 participants (34 healthy controls, 56 high-risk individuals, and 26 stable COPD patients) underwent comprehensive immunological evaluation. Peripheral blood cytokine levels (IL-6, IL-8, TNF-α) and lymphocyte subsets-including programmed cell death protein 1-positive (PD-1⁺) CD4⁺ T cells and effector memory regulatory T cells (emTregs)-were quantified via flow cytometry and multiplex immunoassays. A multivariable logistic regression model was developed to identify predictors of high-risk COPD, incorporating variables selected through hierarchical likelihood ratio testing and variance inflation factor (VIF)-based multicollinearity adjustment. Statistical validation included receiver operating characteristic (ROC) curve analysis, sensitivity-specificity assessment, and effect size calculations (Cohen's f).

Threshold-driven immunological alterations were identified in high-risk individuals, marked by a 7.8-fold elevation in PD-1⁺CD4⁺ T cells (p < 0.001) and increased IL-6 levels (median difference: 1.064 pg/mL, p < 0.001). Effector memory Tregs exhibited progressive depletion from healthy to stable COPD stages (p < 0.001). The final regression model-incorporating PD-1⁺CD4⁺ T cells, age, and emTregs-demonstrated robust diagnostic accuracy (AUC = 0.912; 95% CI: 0.848-0.975), with 80.9% sensitivity and 79.3% specificity. PD-1+CD4+ T cells and age independently predicted high-risk status (adjusted odds ratio = 1.17, 95% CI: 1.05-1.30, p = 0.005; adjusted odds ratio = 1.11, 95% CI: 1.03-1.20, p = 0.007).

This study delineates a threshold-triggered immune signature preceding clinical COPD, providing a validated diagnostic framework for early detection. By integrating lymphocyte exhaustion markers and cytokine dynamics, the model bridges a critical gap in identifying subclinical immune dysfunction, enabling targeted interventions prior to irreversible lung damage.