Assessing inflammatory protein biomarkers in COPD subjects with and without alpha-1 antitrypsin deficiency

• Published in: Respiratory research Vol. 26; no. 1; pp. 247 - 11
• Main Authors: Moll, Matthew, Hobbs, Brian D., Pratte, Katherine A., Zhang, Chengyue, Ghosh, Auyon J., Bowler, Russell P., Lomas, David A., Silverman, Edwin K., DeMeo, Dawn L.
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 15.07.2025; BioMed Central; BMC
• Subjects: Aged; Alpha 1-antitrypsin; alpha 1-Antitrypsin - genetics; alpha 1-Antitrypsin Deficiency - blood; alpha 1-Antitrypsin Deficiency - diagnosis; alpha 1-Antitrypsin Deficiency - epidemiology; alpha 1-Antitrypsin Deficiency - genetics; Antihistamines; Biological markers; Biomarkers - blood; Blood proteins; Female; Health aspects; Humans; Inflammation; Inflammation Mediators - blood; Lung diseases, Obstructive; Machine learning; Male; Medical research; Medicine, Experimental; Middle Aged; Physiological aspects; Protein-protein interactions; Proteins; Pulmonary Disease, Chronic Obstructive - blood; Pulmonary Disease, Chronic Obstructive - diagnosis; Pulmonary Disease, Chronic Obstructive - epidemiology; Pulmonary Disease, Chronic Obstructive - genetics; Rankings; United States
• ISSN: 1465-993X; 1465-9921; 1465-993X
• DOI: 10.1186/s12931-025-03320-8

Individuals homozygous for the Alpha-1 Antitrypsin (AAT) Z allele (Pi*ZZ) exhibit heterogeneity in COPD risk. COPD occurrence in non-smokers with AAT deficiency (AATD) suggests that inflammatory processes may contribute to COPD risk independently of smoking. We hypothesized that inflammatory protein biomarkers in non-AATD COPD are associated with moderate-to-severe COPD in AATD individuals, after accounting for clinical factors. Participants from the COPDGene (Pi*MM) and AAT Genetic Modifiers Study (Pi*ZZ) were included. Proteins associated with FEV /FVC were identified, adjusting for confounders and familial relatedness. Lung-specific protein-protein interaction (PPI) networks were constructed. Proteins associated with AAT augmentation therapy were identified, and drug repurposing analyses performed. A protein risk score (protRS) was developed in COPDGene and validated in AAT GMS using AUROC analysis. Machine learning ranked proteomic predictors, adjusting for age, sex, and smoking history. Among 4,446 Pi*MM and 352 Pi*ZZ individuals, sixteen blood proteins were associated with airflow obstruction, fourteen of which were highly expressed in lung. PPI networks implicated regulation of immune system function, cytokine and interleukin signaling, and matrix metalloproteinases. Eleven proteins, including IL4R, were linked to augmentation therapy. Drug repurposing identified antibiotics, thyroid medications, hormone therapies, and antihistamines as potential adjunctive AATD treatments. Adding protRS improved COPD prediction in AAT GMS (AUROC 0.86 vs. 0.80, p = 0.0001). AGER was the top-ranked protein predictor of COPD. Sixteen proteins are associated with COPD and inflammatory processes that predict airflow obstruction in AATD after accounting for age and smoking. Immune activation and inflammation are modulators of COPD risk in AATD.