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Fusion of the 1H NMR data of serum urine and exhaled breath condensate in order to discriminate chronic obstructive pulmonary disease and obstructive sleep apnea syndrome

机译:融合血清尿液和呼出气冷凝液的1H NMR数据以区分慢性阻塞性肺疾病和阻塞性睡眠呼吸暂停综合征

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摘要

Chronic obstructive pulmonary disease, COPD, affects the condition of the entire human organism and causes multiple comorbidities. Pathological lung changes lead to quantitative changes in the composition of the metabolites in different body fluids. The obstructive sleep apnea syndrome, OSAS, occurs in conjunction with chronic obstructive pulmonary disease in about 10–20 % of individuals who have COPD. Both conditions share the same comorbidities and this makes differentiating them difficult. The aim of this study was to investigate whether it is possible to diagnose a patient with either COPD or the OSA syndrome using a set of selected metabolites and to determine whether the metabolites that are present in one type of biofluid (serum, exhaled breath condensate or urine) or whether a combination of metabolites that are present in two biofluids or whether a set of metabolites that are present in all three biofluids are necessary to correctly diagnose a patient. A quantitative analysis of the metabolites in all three biofluid samples was performed using 1H NMR spectroscopy. A multivariate bootstrap approach that combines partial least squares regression with the variable importance in projection score (VIP-score) and selectivity ratio (SR) was adopted in order to construct discriminant diagnostic models for the groups of individuals with COPD and OSAS. A comparison study of all of the discriminant models that were constructed and validated showed that the discriminant partial least squares model using only ten urine metabolites (selected with the SR approach) has a specificity of 100 % and a sensitivity of 86.67 %. This model (AUCtest = 0.95) presented the best prediction performance. The main conclusion of this study is that urine metabolites, among the others, present the highest probability for correctly identifying patents with COPD and the lowest probability for an incorrect identification of the OSA syndrome as developed COPD. Another important conclusion is that the changes in the metabolite levels of exhaled breath condensates do not appear to be specific enough to differentiate between patients with COPD and OSAS.Electronic supplementary materialThe online version of this article (doi:10.1007/s11306-015-0808-5) contains supplementary material, which is available to authorized users.
机译:慢性阻塞性肺疾病,COPD,会影响整个人类机体的状况,并导致多种合并症。病理性肺部变化导致不同体液中代谢物组成的定量变化。阻塞性睡眠呼吸暂停综合症(OSAS)与慢性阻塞性肺疾病一起发生在约10-20%的COPD患者中。两种情况共有相同的合并症,因此很难区分它们。这项研究的目的是调查是否有可能使用一组选定的代谢物诊断患有COPD或OSA综合征的患者,并确定一种生物流体(血清,呼出气冷凝物或尿液)或两种生物流体中是否存在代谢产物的组合,或者所有三种生物流体中是否存在一组代谢产物才能正确诊断患者。使用 1 H NMR光谱法对所有三个生物流体样品中的代谢物进行了定量分析。采用多变量bootstrap方法,将偏最小二乘回归与投影得分(VIP得分)和选择性比(SR)的可变重要性结合起来,以构建针对COPD和OSAS个体的判别诊断模型。对所有已构建和验证的判别模型的比较研究表明,仅使用十种尿液代谢物(通过SR方法选择)的判别偏最小二乘模型具有100%的特异性和86.67%的敏感性。该模型(AUCtest = 0.95)表现出最佳的预测性能。该研究的主要结论是,尿液中的代谢物,除其他外,代表正确识别COPD专利的可能性最高,而错误识别OSA综合征为发展中的COPD的可能性最低。另一个重要的结论是,呼出气冷凝物的代谢物水平变化似乎不足以区分COPD和OSAS患者。电子补充材料本文的在线版本(doi:10.1007 / s11306-015-0808- 5)包含补充材料,授权用户可以使用。

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