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Upper airway gene expression is an effective surrogate biomarker for Th2-driven inflammation in the lower airway

ABSTRACT: Molecular profiling studies in asthma cohorts have identified a Th2-driven asthma subtype, characterized by elevated lower airway expression of POSTN, CLCA1 and SERPINB2. To assess upper airway gene expression as a potential biomarker for lower airway Th2 inflammation, we assayed upper airway (nasal) and lower airway (bronchial) epithelial gene expression, serum total IgE, blood eosinophils and serum periostin in a cohort of 54 allergic asthmatics and 30 matched healthy controls. 23 of 51 asthmatics in our cohort were classified as ‘Th2 high’ based on lower airway Th2 gene signature expression. Consistent with this classification, ‘Th2 high’ subjects displayed elevated total IgE and blood eosinophil levels relative to ‘Th2 low’ subjects. Upper airway Th2 signature expression was significantly correlated with lower airway Th2 signature expression (r=0.44), with similar strength of association as serum total IgE and blood eosinophils, known biomarkers of Th2 inflammation. In an unbiased genome-wide scan, we identified 8 upper airway genes more strongly correlated with lower airway Th2 gene signature expression (r=0.58), including Eotaxin-3 (CCL26), Galectin-10 (CLC) and Cathepsin-C (CTSC). Asthmatics classified as ‘Th2 high’ using this 8-gene signature show similar serum total IgE and blood eosinophil levels as ‘Th2 high’ asthmatics classified using lower airway Th2 gene signature expression. We have identified an 8-gene upper airway signature correlated with lower airway Th2 inflammation, which may be used as a diagnostic biomarker for Th2-driven asthma.

ORGANISM(S): Homo sapiens

PROVIDER: GSE41861 | GEO | 2015/10/23

SECONDARY ACCESSION(S): PRJNA178960

REPOSITORIES: GEO

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Project description:Background: The first step in SARS-CoV-2 infection is binding of the virus to angiotensin converting enzyme 2 (ACE2) on the airway epithelium. Asthma affects over 300 million people world-wide, many of whom may encounter SARS-CoV-2. Epidemiologic data suggests that asthmatics who get infected may be at increased risk of more severe disease. Our objective was to assess whether maintenance inhaled corticosteroids (ICS), a major treatment for asthma, is associated with airway ACE2 expression in asthmatics. Methods: Large airway epithelium (LAE) of asthmatics treated with maintenance ICS (ICS+), asthmatics not treated with ICS (ICS-), and healthy controls (controls) was analyzed for expression of ACE2 and other coronavirus infection-related genes using microarrays. Results: AsResults: As a group, there was no difference in LAE ACE2 expression in all asthmatics vs controls. In contrast, subgroup analysis demonstrated that LAE ACE2 expression was higher in asthmatics ICS+ compared to ICS‾ and ACE2 expression was higher in male ICS+ compared to female ICS+ and ICS‾ of either sex. ACE2 expression did not correlate with serum IgE, absolute eosinophil level, or change in FEV1 in response to bronchodilators in either ICS- or ICS+. Conclusion: Airway ACE2 expression is increased in asthmatics on long-term treatment with ICS, an observation that should be taken into consideration when assessing the use of inhaled corticosteroids during the pandemic. a group, there was no difference in LAE ACE2 expression in all asthmatics vs controls. In contrast, subgroup analysis demonstrated that LAE ACE2 expression was higher in asthmatics ICS+ compared to ICS‾ and ACE2 expression was higher in male ICS+ compared to female ICS+ and ICS‾ of either sex. ACE2 expression did not correlate with serum IgE, absolute eosinophil level, or change in FEV1 in response to bronchodilators in either ICS- or ICS+. Conclusion: Airway ACE2 expression is increased in asthmatics on long-term treatment with ICS, an observation that should be taken into consideration when assessing the use of inhaled corticosteroids during the pandemic.

Project description:Background: Most asthmatic patients have high serum levels of IgE directed against common environmental allergens such as house dust mite, animal danders and moulds. However the presence of specific IgE against individual allergens alone does not account for asthma. Many individuals are atopic but not asthmatic. Precise knowledge of the serum IgE specificity repertoire in asthmatic and non-asthmatic patients would substantially help in understanding the pathogenesis of the disease and at the same time facilitate the treatment and the implementation of preventive measures. Methods: We developed a microarray immunoassay containing 103 common allergens to study the IgE reactivity profiles of 485 asthmatic and 342 non-asthmatic individuals from families whose members had a documented history of asthma and atopy. The results were analyzed using k-means clustering to investigate whether IgE reactivity profiles correlated with asthma, disease severity and age of onset as well as with other atopic conditions such as rhinitis, conjunctivitis and eczema. We trained an artificial neural network (ANN) using the serum reactivity data to identify individuals as asthmatic and non-asthmatic. Results: Individual sera showed clear differences in the number and the combinations of allergens recognized as well as in the level of specific IgE. While the presence of specific IgE against single allergens correlated poorly with the pathological conditions examined k-means clustering analysis unraveled that a particular profile was significantly associated with asthma (p <1E-8). An ANN-based algorithm, calibrated with the profile reactivity data correctly classified as asthmatic or non-asthmatic 78% of the individual examined. Conclusions: Our analysis demonstrates that asthma may be a higher-order phenomenon related to patterns of response and not attributable to single antibody reactions. This information sheds new light on the risk of developing the disease and can be readily utilized in combination with an ANN-based tool to distinguish asthmatic and non-asthmatic individuals on the basis of their serum reactivity profile. The study consisted of a total of 872 sera samples: 485 individuals were diagnosed with asthma, 342 were classified as non asthmatic, a remaining 45 were classified as unconfirmed asthma diagnosis. The serum IgE reactivity profiles were analyzed against 103 allergens representative of 11 distinct allergen classes. Quantification of bound IgE: The fluorescence signal was acquired using ProScanArray Express™ version 3.0 software. PMC reading values of individual spots were corrected against the internal negative control to identify signals above background. Duplicate measurements of individual allergens were utilized. The signal collected from the allergens was interpolated with an external calibration curve to obtain the IU/ml value (see supplementary file GSE20020_IU_ml values.txt), and translated into a Class Score by plotting the data in a standard reactivity scale (see Sample data tables). Class Score values: (CLASS 0 (less than 0.35 IU/ml); CLASS 1 (0.35-0.7 IU/ml); CLASS 2 (0.71-3.5 IU/ml); CLASS 3 (3.51-17.5 IU/ml); CLASS 4 (17.51-50 IU/ml); CLASS 5 (50.01-100 IU/ml).

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Upper airway gene expression is an effective surrogate biomarker for Th2-driven inflammation in the lower airway

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