Bronchiectasis is a chronic pulmonary disease characterized by irreversible airway dilation and caused by a variety of underlying conditions: chronic infections, immunodeficiencies, cystic fibrosis, primary ciliary dyskinesia among others. In up to 50% of the patients no obvious cause can be identified and the disease is defined as idiopathic. Heterogeneity is a key feature in bronchiectasis with patients differing in comorbidity profiles, clinical features, and microbiome. In the attempt of disentangling patients’ heterogeneity, the scientific community has recently tried to stratify patients based on common clinical features. However, clinical phenotypes provide little information about the underlying pathophysiology of the disease, and therefore poorly support the development of novel drugs. No licensed bronchiectasis-specific therapies are available at present, current treatments target lung infections and mucus, short- and long-term antibiotics and physiotherapy for airway clearance are routinely used. Development of new treatments is needed urgently and there is a consensus on moving towards precision medicine to change the scenario in bronchiectasis. Genome-Wide Association Studies have provided insights into the genetic basis of complex diseases. The standard approach of genetic association studies is to analyze a single trait, in our study design we proposed to implement the GWAS meta-analysis with cross-trait analysis. As previously demonstrated, the novel approach is a capable of discovering genes that were not previously identified with the standard GWAS analysis. The obtained genetic information will be integrated with proteomic and transcriptomic data for causality analysis. Finally, cell-type specificity of gene expression will be estimated. The results obtained will improve the understanding of key pathways driving pathophysiology of bronchiectasis and set the basis for advancing our knowledge of inter-patients’ heterogeneity.
