Asthma phenotypes: the evolution from clinical to molecular approaches
By Sally E. Wenzel. Nature Medicine, 2012
2,309 citations recorded by the source corpus.
Subfields: Immunology, Physiology, Surgery
View Paper: https://www.semanticscholar.org/paper/5534b9bee8446273eb81fe30ef23e5679688b0ad
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Citations in the corpus
- PEBP1 Wardens Ferroptosis by Enabling Lipoxygenase Generation of Lipid Death Signals (2017, background): “Asthma A type-2 (IL-13) signature is known to exist in 50% of asthma patients (Wenzel, 2012).”
- Dupilumab in persistent asthma with elevated eosinophil levels. (2013, background): “Study discontinuation owing to adverse event 3 (6) 3 (6)”
- Exposure to traffic-related air pollution and risk of development of childhood asthma: A systematic review and meta-analysis. (2017, background): “Asthma is a complex and heterogeneous chronic inflammatory disease of the airways (Wenzel, 2012; Xie and Wenzel, 2013).”
- Computational Phenotype Discovery Using Unsupervised Feature Learning over Noisy, Sparse, and Irregular Clinical Data (2013, result): “This perspective is supported by recent results indicating that long-recognized diseases such as asthma or heart failure are not really single entities, but instead are collections of many different phenotypes that may or may not coincide with historical disease boundaries [1–3].”
- Mepolizumab treatment in patients with severe eosinophilic asthma. (2014, neutral): “Oropharyngeal pain 15 (8) 12 (6) 7 (4)”
- Inflammatory endotypes of chronic rhinosinusitis based on cluster analysis of biomarkers. (2016, background): “In a hierarchical cluster analysis of variables (illustrated in figure 1C), these were optimally clustered in the 6 following clusters: (1) IgE, ECP, IL-5, albumin, SE-IgE (2) IL1, IL6, IL8, MPO, (3) IL17, TNF-α, (4) TGF-β1 (5) IL-22 and (6) IFN-γ.”