Obese asthma phenotypes display distinct plasma biomarker profiles.

BACKGROUND: Obese asthma is a complex phenotype and further characterization of the pathophysiology is needed. This study aimed to explore inflammation-related plasma biomarkers in lean and overweight/obese asthmatics. METHODS: We elucidated levels of inflammation-related plasma proteins in obese asthma phenotypes in the population-based cohort BAMSE (Swedish: Children, Allergy, Milieu, Stockholm, Epidemiology) using data from 2069 24-26-year-olds. Subjects were divided into lean asthma (n = 166), lean controls (n = 1440), overweight/obese asthma (n = 73) and overweight/obese controls (n = 390). Protein levels (n = 92) were analysed using the Olink Proseek Multiplex Inflammation panel. RESULTS: Of the 92 included proteins, 41 were associated with lean and/or overweight/obese asthma. The majority of proteins associated with overweight/obese asthma also associated with overweight/obesity among non-asthmatics. Beta-nerve growth factor (BetaNGF), interleukin 10 (IL-10), and matrix metalloproteinase 10 (MMP10) were associated only with lean asthma while C-C motif chemokine 20 (CCL20), fibroblast growth factor 19 (FGF19), interleukin 5 (IL-5), leukemia inhibitory factor (LIF), tumor necrosis factor ligand superfamily member 9 (TNFRSF9), and urokinase-type plasminogen activator (uPA) were associated only with overweight/obese asthma. Overweight/obesity modified the association between asthma and 3 of the proteins: fibroblast growth factor 21 (FGF21), interleukin 4 (IL-4), and urokinase-type plasminogen activator (uPA). In the overweight/obese group, interleukin-6 (IL-6) was associated with non-allergic asthma but not allergic asthma. CONCLUSION: These data indicate distinct plasma protein phenotypes in lean and overweight/obese asthmatics which, in turn, can impact upon therapeutic approaches.

Exploring proteomic plasma biomarkers in eosinophilic and neutrophilic asthma.

BACKGROUND: Few biomarkers identify eosinophilic and neutrophilic asthma beyond cell concentrations in blood or sputum. Finding novel biomarkers for asthma endotypes could give insight about disease mechanisms and guide tailored treatment. Our aim was to investigate clinical characteristics and inflammation-related plasma proteins in relation to blood eosinophil and neutrophil concentrations in subjects with and without asthma. METHODS: We included 24-26-year-old subjects (n = 2063) from the Swedish population-based cohort BAMSE. Subjects with asthma (n = 239) and without asthma (n = 1824) were subdivided based on blood eosinophil and neutrophil concentrations (cut-offs 0.3 × 109 /L and 5.0 × 109 /L, respectively). We measured the levels of 92 plasma proteins using Olink Proseek Multiplex Inflammation Panel Assay. Group statistics tests were used to analyse the data, as well as adjusted multiple logistic regression models. RESULTS: Among subjects with asthma, 21.8% had eosinophilic asthma and 20.5% neutrophilic asthma. Eosinophilic asthma, but not neutrophilic asthma, was associated with a distinct clinical phenotype with, for example, higher proportions of eczema and sensitization. Most plasma proteins that associated with high eosinophil and/or neutrophil blood concentrations in subjects with asthma showed similar associations in subjects without asthma. However, out of these proteins, MMP10 levels were associated with eosinophilic asthma and were significantly higher as compared to controls with high eosinophilic concentration, while CCL4 levels associated with high neutrophil concentration only in subjects with asthma. CONCLUSIONS: Eosinophilic asthma was associated with a clear clinical phenotype. With our definitions, we identified MMP10 as a possible plasma biomarker for eosinophilic asthma and CCL4 was linked to neutrophilic asthma. These proteins should be evaluated further in clinical settings and using sputum granulocytes to define the asthma endotypes.

Gene-environment interactions in childhood asthma revisited; expanding the interaction concept.

Investigation of gene-environment interactions (GxE) may provide important insights into the gene regulatory framework in response to environmental factors of relevance for childhood asthma. Over the years, different methodological strategies have been applied, more recently using genome-wide approaches. The best example to date is the major asthma locus on the 17q12-21 chromosome region, viral infections, and airway epithelium processes where recent studies have shed much light on mechanisms in childhood asthma. However, there are challenges with the traditional single variant-single exposure interaction models, as they do not encompass the complexity and cumulative effects of multiple exposures or multiple genetic variants. As such, we need to redefine our traditional GxE thinking, and we propose in this review to expand the GxE concept by also evaluating other omics layers, such as epigenetics, transcriptomics, metabolomics, and proteomics. In addition, host factors such as age, gender, and other exposures are very likely to influence GxE effects and need firmly to be considered in future studies.