Acute exacerbations of COPD (AECOPD) are episodes of acute worsening of respiratory symptoms that require additional therapy. Exacerbations play a pivotal role in the burden and progressive course of COPD (1). Each event contributes to a progressive decline in lung function (2), reduced health status, low physical activity level (3) and increased health care costs (4). As such, disease management is predominantly based on the prevention of these episodes (1). Yet, in the Netherlands, 30.000 people are admitted to the hospital for an AECOPD every year (5). Although most AECOPD have an infectious origin (6), the underlying mechanisms are heterogeneous and predicting their occurrence in individual patients currently remains unsuccessful (7-9). Furthermore, there is a lack of our understanding in the longitudinal alterations in microbial composition and host-microbiome interactions in the stable state, at AECOPD and during recovery in patients with COPD. This knowledge is essential to improve the early and accurate diagnosis of (the different types of) AECOPD, and for the development of novel antimicrobial and other therapeutic targets and subsequent personalized treatment. These challenges need to be addressed in order to reduce the future impact of these events, avoid unnecessary treatments of individual patients, reduce healthcare utilization and improve overall care for patients with COPD. The current 'Early diagnostic BioMARKers in Exacerbations of COPD' (MARKED) study was designed to investigate several of these gaps in the management of COPD exacerbations. It is anticipated that complex biomarker panels, rather than a single biomarker, will be identified. Since AECOPD are heterogeneous events in terms of origin, trigger, severity, duration, need for treatment and overall clinical presentation (1, 6, 10-15), we expect to identify different biomarker panels for different subtypes of AECOPD. Furthermore, AECOPD diagnosis relies heavily on the exclusion of differential diagnoses (1), which further rules out the potential of a single predictive AECOPD biomarker.