Systemic Inflammation in Older Adults With Asthma-COPD Overlap Syndrome

Juan-juan Fu,Vanessa M. McDonald,Peter G. Gibson,Jodie L. Simpson 대한천식알레르기학회 2014 Allergy, Asthma & Immunology Research Vol.6 No.4

Purpose: The role of systemic inflammation on asthma-COPD overlap syndrome is unknown. This study aimed to examine systemic inflammation inasthma-COPD overlap syndrome, and to identify associations between clinical characteristics and inflammatory mediators in asthma-COPD overlapsyndrome. Methods: In 108 adults older than 55 years comprising healthy controls (n=29), asthma (n=16), COPD (n=21) and asthma-COPD overlapsyndrome (n=42), serum high sensitivity C-reactive protein and Interleukin 6 (IL-6) were assayed. Spirometry, induced sputum, quality of life, comorbiditiesand medications were assessed, and their associations with asthma-COPD overlap syndrome were analyzed using logistic regression. Associations between systemic inflammatory mediators and clinical characteristics were tested in multivariate linear regression models. Results:Patients with asthma-COPD overlap syndrome had significantly elevated IL-6 levels compared with healthy controls and asthmatics. Age, comorbidityindex and IL-6 level were independently associated with asthma-COPD overlap syndrome. FEV1% predicted was inversely associated with IL-6level, and cardiovascular disease was associated with an increased IL-6 level. Systemic markers were not associated with airway inflammation. Conclusions: Systemic inflammation is commonly present in asthma-COPD overlap syndrome, and asthma-COPD overlap syndrome resembledCOPD in terms of systemic inflammation. IL-6 is a pivotal inflammatory mediator that may be involved in airflow obstruction and cardiovascular diseaseand may be an independent treatment target.

Hemopexin: A Novel Anti-inflammatory Marker for Distinguishing COPD From Asthma

Winter Natasha A.,Gibson Peter G.,Fricker Michael,Simpson Jodie L.,Wark Peter A.,McDonald Vanessa M. 대한천식알레르기학회 2021 Allergy, Asthma & Immunology Research Vol.13 No.3

Purpose Systemic inflammatory biomarkers can improve diagnosis and assessment of chronic obstructive pulmonary disease (COPD) and asthma. We aimed to validate an airway disease biomarker panel of 4 systemic inflammatory biomarkers, α2-macroglobulin, ceruloplasmin, haptoglobin and hemopexin, to establish their relationship to airway disease diagnosis and inflammatory phenotypes and to identify an optimized biomarker panel for disease differentiation. Methods Participants with COPD or asthma were classified by inflammatory phenotypes. Immunoassay methods were used to measure levels of validation biomarkers in the sera of participants with disease and non-respiratory disease controls. Markers were analyzed individually and in combination for disease differentiation and compared to established biomarkers (C-reactive protein, interleukin-6, and white blood cell/blood eosinophil count). Results The study population comprised of 141 COPD, 127 severe asthma, 54 mild-moderate asthma and 71 control participants. Significant differences in ceruloplasmin, haptoglobin and hemopexin levels between disease groups and between systemic inflammatory phenotypes were observed. However, no differences were found between airway inflammatory phenotypes. Hemopexin was the best performing individual biomarker and could diagnose COPD versus control participants (area under the curve [AUC], 98.3%; 95% confidence interval [CI], 96.7%–99.9%) and differentiate COPD from asthmatic participants (AUC, 97.0%; 95% CI, 95.4%–98.6%), outperforming established biomarkers. A biomarker panel, including hemopexin, haptoglobin and other established biomarkers, could diagnose asthma versus control participants (AUC, 87.5%; 95% CI, 82.8%–92.2%). Conclusions Hemopexin can be a novel biomarker with superior diagnostic ability in differentiating COPD and asthma. We propose an anti-inflammatory axis between the airways and systemic circulation, in which hemopexin is a protective component in airway disease. Purpose Systemic inflammatory biomarkers can improve diagnosis and assessment of chronic obstructive pulmonary disease (COPD) and asthma. We aimed to validate an airway disease biomarker panel of 4 systemic inflammatory biomarkers, α2-macroglobulin, ceruloplasmin, haptoglobin and hemopexin, to establish their relationship to airway disease diagnosis and inflammatory phenotypes and to identify an optimized biomarker panel for disease differentiation. Methods Participants with COPD or asthma were classified by inflammatory phenotypes. Immunoassay methods were used to measure levels of validation biomarkers in the sera of participants with disease and non-respiratory disease controls. Markers were analyzed individually and in combination for disease differentiation and compared to established biomarkers (C-reactive protein, interleukin-6, and white blood cell/blood eosinophil count). Results The study population comprised of 141 COPD, 127 severe asthma, 54 mild-moderate asthma and 71 control participants. Significant differences in ceruloplasmin, haptoglobin and hemopexin levels between disease groups and between systemic inflammatory phenotypes were observed. However, no differences were found between airway inflammatory phenotypes. Hemopexin was the best performing individual biomarker and could diagnose COPD versus control participants (area under the curve [AUC], 98.3%; 95% confidence interval [CI], 96.7%–99.9%) and differentiate COPD from asthmatic participants (AUC, 97.0%; 95% CI, 95.4%–98.6%), outperforming established biomarkers. A biomarker panel, including hemopexin, haptoglobin and other established biomarkers, could diagnose asthma versus control participants (AUC, 87.5%; 95% CI, 82.8%–92.2%). Conclusions Hemopexin can be a novel biomarker with superior diagnostic ability in differentiating COPD and asthma. We propose an anti-inflammatory axis between the airways and systemic circulation, in which hemopexin is a protective component in airway disease.

Sputum Metabolomic Profiling Reveals Metabolic Pathways and Signatures Associated With Inflammatory Phenotypes in Patients With Asthma

Liu Ying,Zhang Xin,Zhang Li,Oliver Brian G,Wang Hong Guang,Liu Zhi Peng,Chen Zhi Hong,Wood Lisa,Hsu Alan Chen-Yu,Xie Min,McDonald Vanessa,Wan Hua Jing,Luo Feng Ming,Liu Dan,Li Wei Min,Wang Gang 대한천식알레르기학회 2022 Allergy, Asthma & Immunology Research Vol.14 No.4

Purpose: The molecular links between metabolism and inflammation that drive different inflammatory phenotypes in asthma are poorly understood. We aimed to identify the metabolic signatures and underlying molecular pathways of different inflammatory asthma phenotypes. Methods: In the discovery set (n = 119), untargeted ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS) was applied to characterize the induced sputum metabolic profiles of asthmatic patients with different inflammatory phenotypes using orthogonal partial least-squares discriminant analysis (OPLS-DA), and pathway topology enrichment analysis. In the validation set (n = 114), differential metabolites were selected to perform targeted quantification. Correlations between targeted metabolites and clinical indices in asthmatic patients were analyzed. Logistic and negative binomial regression models were established to assess the association between metabolites and severe asthma exacerbations. Results: Seventy-seven differential metabolites were identified in the discovery set. Pathway topology analysis uncovered that histidine metabolism, glycerophospholipid metabolism, nicotinate and nicotinamide metabolism, linoleic acid metabolism as well as phenylalanine, tyrosine and tryptophan biosynthesis were involved in the pathogenesis of different asthma phenotypes. In the validation set, 24 targeted quantification metabolites were significantly expressed between asthma inflammatory phenotypes. Finally, adenosine 5′-monophosphate (adjusted relative risk [adj RR] = 1.000; 95% confidence interval [CI] = 1.000–1.000; P = 0.050), allantoin (adj RR = 1.000; 95% CI = 1.000–1.000; P = 0.043) and nicotinamide (adj RR = 1.001; 95% CI = 1.000–1.002; P = 0.021) were demonstrated to predict severe asthma exacerbation rates. Conclusions: Different inflammatory asthma phenotypes have specific metabolic profiles in induced sputum. The potential metabolic signatures may identify therapeutic targets in different inflammatory asthma phenotypes.