AATD is a rare monogenic disorder predisposing individuals to liver and lung disease. Yet, even within the same genotype, AATD is very heterogeneous regarding clinical presentation.
To identify clinical phenotypes, we performed a cluster analysis using baseline EARCO data (n=1238) and identified six clusters (C1-6) using K-prototypes. With a Random Forest model, we identified age at diagnosis, lung function and smoking history as most important variables in differentiating the clusters.
C1-3 grouped individuals with normal lung function and low CAT scores. C1 and C2 grouped rare or never-smokers, with a markedly different age at diagnosis, whereas individuals of C3 have a notable smoking history.
C4-6 grouped individuals with COPD diagnosis based on low lung function and high CAT scores. Individuals of C4 were older at diagnosis and reported higher smoking history compared to C5 and C6. Individuals of C6 had the lowest lung function, with ±80% of individuals on AAT augmentation therapy compared to ±30% in C5.
The SS, SZ and ZZ genotype were present in C1-4, but shifted to ZZ in C5-6.
Altogether, we identified six clinical AATD phenotypes mainly differentiated by lung function and smoking history rather than genotype. Longitudinal follow-up of these clusters will help to better understand disease progression and potential benefits of augmentation therapy.
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