Abstract
Respiratory diseases are amongst the most complex pathophysiological entities in medicine. There is no such thing as a one-item disease in our field, which brings the appeal of respiratory diseases for basic and clinical scientists. The most prevalent respiratory diseases are chronic, exhibiting multiple mechanistic pathways that can vary during the course of the disease. This has not only hampered pathogenetic research, but has also impeded adequate disease phenotyping [1]. Apparently, it takes more than a few clinical and serum markers to establish the true biomedical entity of complex diseases. The good news is that, as we speak, medicine is making a step-change in achieving exactly that [2]. It is now increasingly recognised that the clinical, physiological, cellular and molecular mechanisms of disease cannot be addressed separately. Instead, it is more likely that an integrative approach that links these various domains of disease will get closer to a true understanding of disease [1, 2]. The problem in chronic respiratory medicine has been that each of the disease domains by itself is characterised by multiple perturbed mechanisms in parallel or in series, so that adequately describing various disease states requires capturing this seeming “chaos” by: 1) high-throughput measurements in each of these disease domains; 2) sophisticated multi-scale mathematical integration of these data [3] to come to; 3) unbiased discovery of (changes in) mechanistic pathways. “Omics” techniques follow this approach [4–6]. Based on developments in molecular medicine and bioinformatics during the past decade [7], a “systems medicine” approach has now become a very powerful option for capturing the complexity of diseases in general [1] and respiratory diseases in particular [3]. The required high-throughput “omics” tools are now available for use in blood, secretions …
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