Abstract
In this article, we comment on the study by Yang et al, which demonstrated significant cross-sectional associations between heart rate variability (HRV) indices, depressive symptoms, and lung function in patients with chronic obstructive pulmonary disease (COPD). Building on these findings, we further explore the underlying mechanisms, particularly inflammatory-autonomic-oxidative stress pathways, as key causal mediators. Moreover, analyzing genetic polymorphisms alongside environmental factors may uncover susceptibility pathways explaining interindividual differences in HRV and comorbidity risk. Additionally, longitudinal studies tracking HRV trajectories could identify thresholds predictive of accelerated lung function decline or cardiovascular events, informing personalized prevention strategies. Integrating longitudinal HRV data with multi-omics biomarkers and machine learning models could enable real-time prediction of depression relapses or COPD exacerbations, facilitating proactive interventions such as personalized biofeedback training or precision anti-inflammatory therapies. By synthesizing these perspectives, this integrative approach promises to advance precision medicine for COPD patients, particularly those with comorbid depression, by addressing both mechanistic insights and clinical translation.