Fusion of the1H NMR data of serum, urine and exhaled breath condensate in order to discriminate chronic obstructive pulmonary disease and obstructive sleep apnea syndrome.
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 using1H 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.
Department of Bioorganic Chemistry, Wroclaw University of Technology, 27 Wybrzeze Wyspianskiego Str., 50-370 Wroclaw, Poland.
Adam
A
Ząbek
Institute of Chemistry, University of Silesia, 9 Szkolna Str., 40-006 Katowice, Poland.
Ivana
I
Stanimirova
Faculty of Chemistry, Opole University, 11a Kopernik Sq., 45-040 Opole, Poland.
Stanisław
S
Deja
Department of Physiology, Wroclaw Medical University, 10 Chalubinskiego Str., 50-368 Wroclaw, Poland.
Wojciech
W
Barg
Department and Clinic of Pulmonology and Lung Cancers, Wroclaw Medical University, 105 Grabiszynska Str., 53-439 Wroclaw, Poland.
Aneta
A
Kowal
Department and Clinic of Pulmonology and Lung Cancers, Wroclaw Medical University, 105 Grabiszynska Str., 53-439 Wroclaw, Poland.
Anna
A
Korzeniewska
Department of Chemistry and Immunochemistry, Wroclaw Medical University, 44a Bujwida Str., 50-345, Wroclaw Poland.
Magdalena
M
Orczyk-Pawiłowicz
Bioorganic Chemistry Institute, Polish Academy of Science, 12 Noskowskiego Str., 61-714 Poznan, Poland.
Daniel
D
Baranowski
Bioorganic Chemistry Institute, Polish Academy of Science, 12 Noskowskiego Str., 61-714 Poznan, Poland.
Zofia
Z
Gdaniec
Department and Clinic of Pulmonology and Lung Cancers, Wroclaw Medical University, 105 Grabiszynska Str., 53-439 Wroclaw, Poland.
Renata
R
Jankowska
Department of Bioorganic Chemistry, Wroclaw University of Technology, 27 Wybrzeze Wyspianskiego Str., 50-370 Wroclaw, Poland.
Piotr
P
Młynarz
Chemometrics; Chronic obstructive pulmonary disease (COPD); Discriminant models; NMR spectroscopy; Obstructive sleep apnea syndrome (OSAS)