Predicting Lung Function Using Biomarkers in Alpha-1 Antitrypsin Deficiency

• Published in: Biomedicines Vol. 11; no. 7; p. 2001
• Main Authors: Spittle, Daniella A, Mansfield, Alison, Pye, Anita, Turner, Alice M, Newnham, Michael
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 01-07-2023; MDPI
• Subjects: alpha-1 antitrypsin deficiency; Biological markers; Biomarkers; Chronic obstructive pulmonary disease; Development and progression; Emphysema; Genotypes; Longitudinal studies; Lung diseases; Lung diseases, Obstructive; lung function; Mortality; Prediction models; Proteins; Proteomics; Research ethics; Respiratory function; Smoking; Spirometry; Tumor necrosis factor-TNF; Variance analysis; United Kingdom; Minneapolis Minnesota; United States > US; alpha-1 antitrypsin deficiency; lung function; biomarkers; chronic obstructive pulmonary disease
• ISSN: 2227-9059; 2227-9059
• DOI: 10.3390/biomedicines11072001

Lung disease progression in alpha-1 antitrypsin deficiency (AATD) is heterogenous and manifests in different ways. Blood biomarkers are an attractive method of monitoring diseases as they are easy to obtain and repeatable. In non-AATD COPD, blood biomarker panels have predicted disease severity, progression, and mortality. We measured a panel of seven serum biomarkers in 200 AATD patients and compared levels between those with COPD and those without. We assessed whether biomarkers were associated with baseline lung function parameters (FEV1 and TLco) or absolute change in these parameters. In total, 111 patients with a severely deficient genotype of AATD (PiZZ) and COPD were included in the analyses. Pearson's correlation coefficient was measured for biomarker correlations and models were compared using ANOVA. CRP and CCL18 were significantly higher in the serum of AATD COPD versus AATD with no COPD. Biomarkers were not predictive of cross-sectional lung function measurements, however, CC16 was significantly associated with an absolute change in TLco (
= 0.018). An addition of biomarkers to the predictive model for TLco added significant value over covariates alone (R
0.13 vs. 0.02,
= 0.028). Our findings suggest that CC16 is predictive of emphysema progression in AATD COPD. Proteomics data may reveal alternative candidate biomarkers and further work should include the use of longitudinal biomarker measurements.