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

Abstract

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.

Metabolomics in Sleep, Insomnia and Sleep Apnea

“…Metabolomic approaches have been applied in the study of OSA, whereby they can be categorized into two types of studies, including (1) metabolomic studies of exhaled breath [ 38 , 39 , 40 ], and (2) studies of the blood and/or urine metabolome [ 41 , 42 , 43 , 44 ].…”

“…More specifically, aromatic hydrocarbons (phenylacetic acid, ethylbenzene, toluene and p-xylene), saturated hydrocarbons (hexane, octane, heptane, nonane and decane), acetone and isoprene were elevated, which have been suggested as potential biomarkers. However, studies have shown that changes in the metabolomics profile of exhaled breath might not be specific enough to differentiate between patients with different respiratory disorders, such as chronic obstructive pulmonary disease and OSA [ 42 ]. Therefore, the second group of studies (studies of the blood and/or urine metabolome) might provide a more specific characterization of OSA.…”

Metabolomics Profiling for Obstructive Sleep Apnea and Simple Snorers

“…To date, a limited number of small-sample-size metabolomics studies have been performed to explore metabolomics profiling and the underlying mechanisms in OSA 13 14 15 . Thus, we utilized a combination of ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) and gas chromatography coupled with time-of-flight mass spectrometry (GC-TOF-MS) to investigate: the metabolic changes occurring during the development of OSA, the mechanistic pathways involved in OSA, and candidate metabolite markers useful for diagnosing OSA.…”

Biomarkers in allergic asthma: Which matrix should we use?

“…Accordingly, in an animal model, NMR‐based profiling studies on different biological matrix (e.g. serum, urine, and others) consistently detected distinct biomarker signatures with respect to controls and in patients affected by COPD and OSA, specific biomarkers were identified in distinct matrices …”