健康人群和哮喘队列参与者基于测定肺功能波动测定显示的功能表型
2018/03/05
背景:哮喘以慢性气道炎症和可逆性气流阻塞为特征。然而,这些特征并不总是密切相关的。每日肺功能水平的波动包含哮喘表型、恶化风险和对长效β-受体激动剂的反应的信息。
目的:通过哮喘受试者具体肺功能特点的探查,我们开发和验证了一种新的哮喘表型的聚类方法,它利用了包含在每日两次肺功能测定的波动特点中隐藏的信息。
方法:在4周中前瞻性地测量来自PASTURE/ EFRAIM(防过敏-农村环境研究)队列中的696例健康和哮喘的学龄儿童的第1秒用力呼气量(FEV1)和呼气峰流速(PEF)值,在1 年的时间中测量来自BIOAIR(泛欧洲的纵向评估的临床过程和生物标志物在重度慢性气道疾病)队列中的138例轻度至中度或重度成人哮喘患者的FEV1和PEF值。利用富集分析,我们探讨了该方法是否能识别具有不同肺功能波动模式的、临床意义明确的类群。
结果:在PASTURE/EFRAIM数据集中,我们发现了四个类群。其中2种在具有哮喘临床特征的儿童中常见。在第3种中,来自农村环境的儿童占多数,而第4种主要由健康对照组组成。第三种中,携带哮喘风险等位基因17q21位点的rs7216389的人占79%。在BIOAIR数据集中,我们发现了两种不同的类群,能够明确鉴别轻度至中度和重度哮喘的个体。
结论:我们的方法确定了动态功能性哮喘和健康表型,在一定程度上独立于过敏和炎症反应机制,但与在17q21位点的遗传标记相关。该方法可被用于疾病的表型的测定,也可能被用于测定内在表型。它可能识别具有特定功能异常的受试者,对此类患者可能需要不同的治疗方法。
(Thorax. 2018 Feb;73(2):107-115.)
Functional phenotypes determined by fluctuation-based clustering of lung function measurements in healthy and asthmatic cohort participants
Delgado-Eckert E, Fuchs O, Kumar N, Pekkanen J, Dalphin JC, Riedler J, Lauener R
Abstract
RATIONALE:Asthma is characterised by inflammation and reversible airway obstruction. However, these features are not always closely related. Fluctuations of daily lung function contain information on asthma phenotypes, exacerbation risk and response to long-acting β-agonists.
OBJECTIVES: In search of subgroups of asthmatic participants with specific lung functional features, we developed and validated a novel clustering approach to asthma phenotyping, which exploits the information contained within the fluctuating behaviour of twice-daily lung function measurements.
METHODS: Forced expiratory volume during the first second (FEV1) and peak expiratory flow (PEF) were prospectively measured over 4 weeks in 696 healthy and asthmatic school children (Protection Against Allergy - Study in Rural Environments (PASTURE)/EFRAIM cohort), and over 1year in 138 asthmatic adults with mild-to-moderate or severe asthma (Pan-European Longitudinal Assessment of Clinical Course and Biomarkers in Severe Chronic Airway Disease (BIOAIR) cohort). Using enrichment analysis, we explored whether the method identifies clinically meaningful, distinct clusters of participants with different lung functional fluctuation patterns.
MEASUREMENTS AND MAIN RESULTS: In the PASTURE/EFRAIM dataset, we found four distinct clusters. Two clusters were enriched in children with well-known clinical characteristics of asthma. In cluster 3, children from a farming environment predominated, whereas cluster 4 mainly consisted of healthy controls. About 79% of cluster 3 carried the asthma-risk allele rs7216389 of the 17q21 locus. In the BIOAIR dataset, we found two distinct clusters clearly discriminating between individuals with mild-to-moderate and severe asthma.
CONCLUSIONS: Our method identified dynamic functional asthma and healthy phenotypes, partly independent of atopy and inflammation but related to genetic markers on the 17q21 locus. The method can be used for disease phenotyping and possibly endotyping. It may identify participants with specific functional abnormalities, potentially needing a different therapeutic approach.
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