The newly described severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for a pandemic (coronavirus disease 2019 [COVID-19]). It is now well established that certain comorbidities define high-risk patients. They include hypertension, diabetes, and coronary artery disease. In contrast, the context with bronchial asthma is controversial and shows marked regional differences. Because asthma is the most prevalent chronic inflammatory lung disease worldwide and SARS-CoV-2 primarily affects the upper and lower airways leading to marked inflammation, the question arises about the possible clinical and pathophysiological association between asthma and SARS-CoV-2/COVID-19. Here, we analyze the global epidemiology of asthma among patients with COVID-19 and propose the concept that patients suffering from different asthma endotypes (type 2 asthma vs non–type 2 asthma) present with a different risk profile in terms of SARS-CoV-2 infection, development of COVID-19, and progression to severe COVID-19 outcomes. This concept may have important implications for future COVID-19 diagnostics and immune-based therapy developments.

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Obesity has been well recognized as an important comorbidity in patients with asthma, representing a unique phenotype and endotype. This association indicates a close relationship between metabolic and inflammatory dysregulation. However, the detailed organ-organ, cellular, and molecular interactions are not completely resolved. Because of that, the relationship between obesity and asthma remains unclear. In this article, clinical and epidemiological studies, as well as data from experimental animal work, are being summarized to provide a state of the art update on this important topic. Much more work is needed, particularly mechanistic, to fully understand the interaction between obesity and asthma and to develop novel preventive and therapeutic strategies.

Extracellular DNA trap formation is a cellular function of neutrophils, eosinophils, and basophils that facilitates the immobilization and killing of invading microorganisms in the extracellular milieu. To form extracellular traps, granulocytes release a scaffold consisting of mitochondrial DNA in association with granule proteins. As we understand more about the molecular mechanism for the formation of extracellular DNA traps, the in vivo function of this phenomenon under pathological conditions remains an enigma. In this article, we critically review the literature to summarize the evidence for extracellular DNA trap formation under in vivo conditions. Extracellular DNA traps have not only been detected in infectious diseases but also in chronic inflammatory diseases, as well as in cancer. While on the one hand, extracellular DNA traps clearly exhibit an important function in host defense, it appears that they can also contribute to the maintenance of inflammation and metastasis, suggesting that they may represent an interesting drug target for such pathological conditions. Facts •The demonstration of extracellular DNA traps in vivo requires sections of affected tissues, which are to be investigated with special staining techniques. These structures are seen in multiple inflammatory and cancer diseases.Is there a simple biomarker that reflects extracellular DNA trap formation?• What is the contribution of extracellular microbe killing compared to intracellular killing following phagocytosis?• The mechanism of DNA trap formation is unknown.

SARS-CoV-2 infection represents a global threat to human health. Various approaches were employed to reveal the pathogenetic mechanisms of COVID-19. Mathematical and computational modelling is a powerful tool to describe and analyze the infection dynamics in relation to a plethora of processes contributing to the observed disease phenotypes. In our study here, we formulate and calibrate a deterministic model of the SARS-CoV-2 life cycle. It provides a kinetic description of the major replication stages of SARS-CoV-2. Sensitivity analysis of the net viral progeny with respect to model parameters enables the identification of the life cycle stages that have the strongest impact on viral replication. These three most influential parameters are (i) degradation rate of positive sense vRNAs in cytoplasm (negative effect), (ii) threshold number of non-structural proteins enhancing vRNA transcription (negative effect), and (iii) translation rate of non-structural proteins (positive effect). The results of our analysis could be used for guiding the search for antiviral drug targets to combat SARS-CoV-2 infection.