肥胖对哮喘的影响延伸到了诊断标准。
Obesity's effect on asthma extends to diagnostic criteria.
机构信息
Department of Medicine, Division of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor, Mich.
Department of Biostatistics and BioInformatics, Duke University, Durham, NC.
出版信息
J Allergy Clin Immunol. 2018 Mar;141(3):1096-1104. doi: 10.1016/j.jaci.2017.04.047. Epub 2017 Jun 15.
BACKGROUND
The use of inflammatory biomarkers to delineate the type of lung inflammation present in asthmatic subjects is increasingly common. However, the effect of obesity on these markers is unknown.
OBJECTIVES
We aimed to determine the effect of obesity on conventional markers of inflammation in asthmatic subjects.
METHODS
We performed secondary analysis of data from 652 subjects previously enrolled in 2 Asthma Clinical Research Network trials. We performed linear correlations between biomarkers and logistic regression analysis to determine the predictive value of IgE levels, blood eosinophil counts, and fraction of exhaled nitric oxide values in relationship to sputum eosinophil counts (>2%), as well as to determine whether cut points existed that would maximize the sensitivity and specificity for predicting sputum eosinophilia in the 3 weight groups.
RESULTS
Overall, statistically significant but relatively weak correlations were observed among all 4 markers of inflammation. Within obese subjects, the only significant correlation found was between IgE levels and blood eosinophil counts (r = 0.33, P < .001); furthermore, all other correlations between inflammatory markers were approximately 0, including correlations with sputum eosinophil counts. 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 biomarkers of inflammation significantly predicted the presence of high sputum eosinophil counts. Obese asthmatic subjects have lower cut points for IgE levels (268 IU), fraction of exhaled nitric oxide values (14.5 ppb), and blood eosinophil counts (96 cells/μL) than all other groups.
CONCLUSIONS
In obese asthmatic subjects conventional biomarkers of inflammation are poorly predictive of eosinophilic airway inflammation. As such, biomarkers currently used to delineate eosinophilic inflammation in asthmatic subjects should be approached with caution in these subjects.
背景
越来越多的研究使用炎症生物标志物来区分哮喘患者肺部炎症的类型。然而，肥胖对这些标志物的影响尚不清楚。
目的
本研究旨在确定肥胖对哮喘患者炎症常规标志物的影响。
方法
我们对先前纳入 2 项哮喘临床研究网络试验的 652 例患者的数据进行了二次分析。我们对生物标志物进行线性相关性分析，并进行逻辑回归分析，以确定 IgE 水平、血嗜酸性粒细胞计数和呼出气一氧化氮分数与痰嗜酸性粒细胞计数（>2%）之间的预测价值，以及确定是否存在切点可以最大限度地提高 3 个体重组中预测痰嗜酸性粒细胞的敏感性和特异性。
结果
总体而言，所有 4 种炎症标志物之间均存在统计学上显著但相对较弱的相关性。在肥胖组中，仅发现 IgE 水平与血嗜酸性粒细胞计数之间存在显著相关性（r=0.33，P<0.001）；此外，其他所有炎症标志物之间的相关性几乎为 0，包括与痰嗜酸性粒细胞计数的相关性。此外，每种生物标志物单独或联合的预测价值在肥胖组中均较差。实际上，在肥胖组中，没有一种炎症生物标志物能显著预测痰嗜酸性粒细胞计数高的情况。肥胖哮喘患者的 IgE 水平（268 IU）、呼出气一氧化氮分数（14.5 ppb）和血嗜酸性粒细胞计数（96 个/μL）的切点值均低于其他所有组。
结论
在肥胖的哮喘患者中，炎症的常规生物标志物对嗜酸性气道炎症的预测作用较差。因此，在这些患者中，目前用于区分哮喘患者嗜酸性炎症的生物标志物的应用应谨慎。
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