Purpose Alpha 1 antitrypsin deficiency (AATD) is a genetic risk factor for chronic obstructive pulmonary disease (COPD). Whilst testing for the condition is relatively simple, there is a disconnect in published literature between genetic epidemiology and numbers of patients known to specialists. This makes planning services for patients difficult. We aimed to estimate the number of patients likely to have lung disease eligible for specific AATD therapy within the UK. Patients and Methods The THIN database was used to determine the prevalence of AATD and symptomatic COPD. This, and published rates of AATD were used to extrapolate THIN data to the population size of the UK to give an indicative population size for symptomatic AATD patients who have lung disease. The Birmingham AATD registry was used to describe age at diagnosis, rate of lung disease and symptomatic lung disease for patients with PiZZ (or equivalent) AATD, together with the time from symptom onset to diagnosis, in order to aid interpretation of the THIN data and improve modeling. Results THIN data showed COPD prevalence of 3%, and AATD prevalence of 0.005–0.2%, depending on how stringently AATD diagnostic codes were applied. The majority of Birmingham AATD patients were diagnosed between the ages 46–55, whilst patients recorded in THIN tended to be older. The rate of COPD was similar in the THIN and Birmingham patients diagnosed with AATD. Modelling to the size of the UK demonstrated a likely symptomatic AATD population of between 3016 and 9866 people. Conclusion AATD is likely to be under-diagnosed in the UK. Based on projected patient numbers an expansion to specialist services is desirable, in particular if specific therapy for AATD such as augmentation were to be introduced to the healthcare system.

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 (p = 0.018). An addition of biomarkers to the predictive model for TLco added significant value over covariates alone (R2 0.13 vs. 0.02, p = 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.