Research Background
Chronic Obstructive Pulmonary Disease (COPD) is a progressive inflammatory lung disease for which no curative treatment exists. The clinical course of COPD is defined by exacerbations. These are characterized by an acute worsening of symptoms, contributing to the progression of lung function deterioration and in turn are associated with an increased mortality risk. Respiratory tract infections are predominantly the cause of exacerbations. Prevention and early detection are crucial goals in COPD treatment, but remain largely ineffective. The pathobiology and heterogeneity of exacerbations and the lack of validated biomarkers contribute to this gap in knowledge. However, the onset of exacerbations was recently shown to be associated with a shift in the respiratory microbiome. Currently, no adequate tool exists that enables a detailed clinically validated assessment of the full spectrum of the respiratory microbiota.

Design
In this prospective, longitudinal, observational two-centred study we aim to recruit n=150 eligible patients from University Hospital Frankfurt as well as n=150 patients from Maastricht University Medical Center who will be followed up for one year. Throat swabs, sputum and blood samples and several clinical parameters such as symptoms and comorbidities will be collected at different time points. Additional visits and sample collection are required in case of an acute exacerbation. Microbiota composition will be determined with the innovative interspace profiling (IS-Pro) technology, in which bacteria profiles are identified by specific length polymorphisms of the 16S-23S IS regions. This will be combined with phylum/species specific polymorphisms of the 16S rRNA by Next Generation Sequencing. Thereafter, predictive models will be formulated, trained and tested based on all available data by the geneXplain Artificial Intelligence platform. The goal of this study is to develop an innovative algorithm based on the combination of shifts in the respiratory microbiome composition and clinical parameters to improve individualised risk assessment of COPD exacerbations.