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哮喘的呼吸代谢组学通过核磁共振光谱分析。

Breath metabolomic profiling by nuclear magnetic resonance spectroscopy in asthma.

机构信息

The University of Manchester, Manchester Academic Health Science Centre, NIHR South Manchester Respiratory and Allergy Clinical Research Facility, University Hospital of South Manchester, Manchester, UK.

出版信息

Allergy. 2013 Aug;68(8):1050-6. doi: 10.1111/all.12211. Epub 2013 Jul 29.

Abstract

BACKGROUND

Metabolomic profiling of exhaled breath condensate offers opportunities for the development of noninvasive diagnostics in asthma. We aimed to determine and validate discriminatory metabolomic profiles in adult asthma and to explore profiles in clinically relevant disease phenotypes.

METHODS

Nuclear magnetic resonance spectroscopy was used to analyse breath condensate samples from 82 subjects with asthma and 35 healthy volunteers. Multivariate modelling was performed on a 'training set' (70% of the total sample) in order to produce a discriminatory model classifying asthmatics from healthy controls, and the model tested in the remaining subjects. Secondary analyses were performed to determine the models for the identification of asthmatic subgroups based on sputum eosinophilia, neutrophilia, asthma control and inhaled corticosteroid use.

RESULTS

A classification model consisting of five discriminating spectral regions was derived using data from the training set with an area under the receiver operating curve (AUROC) of 0.84. In the test set (the remaining 30% of subjects), the AUROC was 0.91, thus providing external validation for the model. The success of the technique for classifying asthma phenotypes was variable, with AUROC for: sputum eosinophilia (3% cut-off) 0.69; neutrophilia (65% cut-off) 0.88; asthma control (cut-off Asthma Control Questionnaire score of 1) 0.63; and inhaled corticosteroid use 0.89.

CONCLUSION

Nuclear magnetic resonance spectroscopy of breath condensate successfully differentiates asthmatics from healthy subjects. With identification of the discriminatory compounds, this technique has the potential to provide novel diagnostics and identify novel pathophysiological mechanisms, biomarkers and therapeutic targets.

摘要

背景

呼出气冷凝物的代谢组学分析为哮喘的无创诊断提供了机会。我们旨在确定和验证成人哮喘中具有鉴别能力的代谢组学特征,并探索在临床相关疾病表型中的特征。

方法

采用核磁共振波谱法分析 82 例哮喘患者和 35 例健康志愿者的呼出气冷凝物样本。对“训练集”(总样本的 70%)进行多变量建模,以生成一个可将哮喘患者与健康对照者区分开的判别模型,并在其余受试者中进行测试。进行二次分析以确定基于痰液嗜酸性粒细胞、中性粒细胞、哮喘控制和吸入皮质激素使用情况来识别哮喘亚组的模型。

结果

使用训练集的数据得出了一个包含五个有区别的光谱区域的分类模型,其接受者操作特征曲线下面积(AUROC)为 0.84。在测试集(其余 30%的受试者)中,AUROC 为 0.91,从而为模型提供了外部验证。该技术对哮喘表型进行分类的成功率不一,其 AUROC 为:痰液嗜酸性粒细胞(3%截断值)为 0.69;中性粒细胞(65%截断值)为 0.88;哮喘控制(哮喘控制问卷评分 1 的截断值)为 0.63;以及吸入皮质激素使用为 0.89。

结论

呼出气冷凝物的核磁共振波谱分析可成功地区分哮喘患者和健康受试者。通过识别有区别的化合物,该技术有可能提供新的诊断方法,并确定新的病理生理机制、生物标志物和治疗靶点。

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