Replication of COPD susceptibility loci in a large Chinese elderly population using a validated, multi-setting EHR phenotype

Validated frameworks for defining chronic obstructive pulmonary disease (COPD) using real-world electronic health records (EHR) data in non-European populations and across multiple healthcare settings and remain limited. This study aimed to develop and validate an EHR-based phenotype for COPD in a large Chinese elderly cohort and assess its utility by replicating known COPD loci. We analyzed EHR and genetic data from over 130,000 adults enrolled in the Kunshan Aging Research with E-health (KARE) cohort. An iterative, validation-driven process was used to develop the algorithm for identifying COPD case using EHR data from primary care, hospital outpatient and inpatient, and disease registries. Positive predictive value (PPV) was assessed via independent chart review by two respiratory physicians. We then tested associations between COPD and 5 established COPD susceptibility loci using logistic regression adjusted for age, sex, ever-smoking history, smoking duration, and genetic principal components. The final algorithm achieved a PPV of 88.3%. We identified 4,944 COPD cases using this algorithm and selected 86,561 controls. Four COPD loci were successfully replicated: FAM13A (OR = 1.143, P = 6.53*10− 7), AGER (OR = 1.130, P = 1.24*10− 4), DSP (OR = 1.066, P = 0.014), TGFB2 (OR = 1.052, P = 0.046). We present a validated, multi-setting EHR-based COPD definition that replicates known genetic associations in a large Chinese elderly population. These results support the integration of biorepositories and real-world clinical data as a scalable strategy to enhance population diversity of COPD genetic research.