Obesity’s Impact on Asthma Extends to Diagnostic Criteria

• Published in: Journal of allergy and clinical immunology Vol. 141; no. 3; pp. 1096 - 1104
• Main Authors: Lugogo, Njira, MD, Green, Cynthia L., PhD, Agada, Noah, MD, Zhang, Siyi, MS, Meghdadpour, Susanne, PhD, Zhou, Run, MS, Yang, Siyun, MS, Anstrom, Kevin J., PhD, Israel, Elliot, MD, Martin, Richard, MD, Lemanske, Robert F., MD, Boushey, Homer, MD, Lazarus, Stephen C., MD, Wasserman, Stephen I., MD, Castro, Mario, MD, Calhoun, William, MD, Peters, Stephen P., MD PhD, DiMango, Emily, MD, Chinchilli, Vernon, PhD, Icitovic, Nikolina, MAS, Kunselman, Susan, MA, King, Tonya S., PhD, Kraft, Monica, MD
• Format: Journal Article
• Language: English
• Published: 15.06.2017
• Subjects: Allergy and Immunology; ACRN; FeNO; IgE; Interleukin; Forced vital capacity; Fraction of exhaled nitric oxide; Immunoglobulin E; PC 20; Inflammatory Markers and FeNO; AUC; DPP4; Asthma Clinical Research Network; Body mass index; Dipeptidyl peptidase 4; Area under the curve; ASUI; Asthma Symptom Utility Index; BMI; Obesity; IL; Forced expiratory volume in one second; OR; Inhaled corticosteroids; AEQ; Asthma; ACQ; Asthma Control Questionnaire; CD4; FVC; FEV 1; Cluster of differentiation 4; ICS; Odds ratio; Asthma Evaluation Questionnaire; Eosinophils; provocative concentration of methacholine that causes a 20% drop in FEV 1
• ISSN: 0091-6749; 1097-6825
• DOI: 10.1016/j.jaci.2017.04.047

Abstract Background The use of inflammatory biomarkers to delineate the type of lung inflammation present in asthma is increasingly common. However, the impact of obesity on these markers is unknown. Objectives We aimed to determine the impact of obesity on conventional markers of inflammation in asthma. Methods We performed secondary analysis of data from 652 patients previously enrolled in two ACRN trials. We performed linear correlations between biomarkers and logistic regression analysis to determine the predictive value of IgE, blood eosinophils and FeNO in relationship to sputum eosinophils (>2%), as well as to determine if cut points existed that would maximize the sensitivity and specificity for predicting sputum eosinophilia in the three weight groups. Results Overall, statistically significant but relatively weak correlations were observed among all four markers of inflammation. Within obese subjects, the only significant correlation found was between IgE and blood eosinophils (r=0.33, p<0.001); furthermore, all other correlations between inflammatory markers were approximately 0, including correlations with sputum eosinophils. In addition, the predictive value of each biomarker alone or in combination was poor in obese subjects. In fact in obese subjects, none of the inflammation biomarkers significantly predicted the presence of high sputum eosinophils. Obese asthma subjects have lower cut points for IgE, (268IU), FeNO (14.5ppb) and blood eosinophils (96 cells/ul) than all other groups. Conclusions In obese asthma, conventional biomarkers of inflammation are poorly predictive of eosinophilic airway inflammation. As such, biomarkers currently used to delineate eosinophilic inflammation in asthma should be approached with caution in these patients.