Department of Pediatrics, University of Alberta, Magnetic Resonance Diagnostics Centre, Edmonton, Alberta, Canada.
J Allergy Clin Immunol. 2011 Mar;127(3):757-64.e1-6. doi: 10.1016/j.jaci.2010.12.1077.
The ability to diagnose and monitor asthma on the basis of noninvasive measurements of airway cellular dysfunction is difficult in the typical clinical setting.
Metabolomics is the study of molecules created by cellular metabolic pathways. We hypothesized that the metabolic activity of children with asthma would differ from healthy children without asthma. Furthermore, children having an asthma exacerbation would be different compared with children with stable asthma in outpatient clinics. Finally, we hypothesized that (1)H-nuclear magnetic resonance (NMR) would measure such differences using urine samples, one of the least invasive forms of biofluid sampling.
Children (135 total, ages 4-16 years) were enrolled, having met the criteria of healthy controls (C), stable asthma in the outpatient clinic (AO), or unstable asthma in the emergency department (AED). Partial least squares discriminant analysis was performed on the NMR data to create models of separation (70 metabolites were measured/urine sample). Some NMR data were withheld from modeling to be run blindly to determine possible diagnostic accuracy.
On the basis of the model of AO versus C, 31 of 33 AO samples were correctly diagnosed with asthma (94% accuracy). Only 1 of 20 C samples was incorrectly labeled as asthma (5% misclassification). On the basis of the AO versus AED model, 31 of the 33 AO samples were correctly diagnosed as outpatient asthma (94% accurate).
This is the first report suggesting that (1)H-NMR analysis of human urine samples has the potential to be a useful clinical tool for physicians treating asthma.
在典型的临床环境中，基于对气道细胞功能障碍的无创测量来诊断和监测哮喘的能力具有挑战性。
代谢组学是研究细胞代谢途径产生的分子的科学。我们假设哮喘儿童的代谢活性与没有哮喘的健康儿童不同。此外，与在门诊接受治疗的稳定型哮喘儿童相比，处于哮喘加重期的儿童会有所不同。最后，我们假设（1）H 核磁共振（NMR）将使用尿液样本（生物流体采样的最无创形式之一）来测量这种差异。
共纳入了 135 名儿童（年龄 4-16 岁），符合健康对照（C）、门诊稳定型哮喘（AO）或急诊科不稳定型哮喘（AED）的标准。对 NMR 数据进行偏最小二乘判别分析，以创建分离模型（测量了 70 种代谢物/尿液样本）。一些 NMR 数据被保留用于建模，以便进行盲法运行以确定可能的诊断准确性。
基于 AO 与 C 的模型，33 个 AO 样本中有 31 个被正确诊断为哮喘（94%的准确率）。只有 20 个 C 样本中的 1 个被错误标记为哮喘（5%的误分类）。基于 AO 与 AED 的模型，33 个 AO 样本中有 31 个被正确诊断为门诊哮喘（准确率为 94%）。
这是第一个表明（1）H-NMR 分析人类尿液样本有可能成为治疗哮喘的医生的有用临床工具的报告。
