Changes in urine headspace composition as an effec

Authors: Devasena Samudrala Brigitte Geurts Phil A Brown Ewa Szymańska Julien Mandon Jeroen Jansen Lutgarde Buydens Frans J M Harren Simona M Cristescu

Publish Date: 2015/05/31

Volume: 11, Issue: 6, Pages: 1656-1666

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Abstract

The present investigation uses proton transfer reaction mass spectrometry PTRMS combined with multivariate and univariate statistical analyses to study potential biomarkers for altered metabolism in urine due to strenuous walking Urine samples in concurrence with breath and blood samples were taken from 51 participants 23 controls 11 type1 diabetes 17 type2 diabetes during the Dutch endurance walking event the International Four Days Marches Multivariate analysis allowed for discrimination of before and after exercise for all three groups control type1 and type2 diabetes and on three out of 4 days The analysis highlighted 12 molecular ions contributing to this discrimination Of these acetic acid in urine is identified as a significant marker for exercise effects induced by walking an increase is observed as an effect of walking Analysis of acetone concentration with univariate tools resulted in different information when compared to breath as a function of exercise revealing an interesting effect of time over the 4 days In breath acetone provides an immediate snapshot of metabolism whereas urinary acetone will result from longer term diffusion processes providing a time averaged view of metabolism The potential to use PTRMS measurements of urine to monitor exercise effects is exhibited and may be utilized to monitor subjects in mass participation exercise eventsDue to a persistent absence of phenotypic symptoms during progression many chronic diseases like diabetes can remain undiagnosed during the early stages of development Even after diagnosis the suitability and effectiveness of medication or lifestyle interventions diet exercise etc are difficult to interpret yet critically important for managing the treatment of a chronic disease Personal omics profiling POP aims to tackle these challenges by scanning individuals in detail to identify the genetic basis for disease risk or treatment efficacy and using this knowledge to enable daily monitoring with postgenomic technology Chen et al 2012 Roukos 2008 Largescale implementation of this approach would however put a disproportionate burden on healthcare resources as this requires extensive use of highly advanced technology Likewise this would require considerable effort of the healthy examinee as he/she would need to regularly visit the appropriate medical infrastructure for a relatively invasive procedure typically the provision of blood samples Although highly sensitive to detect and monitor a broad range of potential diseases in its current state POP is too impractical to be viably implementedA truly feasible implementation would be to collect samples in locations where many members of the target group are voluntarily present Several samples breath urine can then be obtained considerably lessinvasively without requirement for specifically trained personnel However metabolomics technology is put to the challenge for such scenarios as the sheer number of samples generated on such highly populated locations requires rapid analysis and the diluted state of specifically volatile samples requires highly sensitive analysis platformsThe volatile organic compounds VOCs emitted from the skin Turner et al 2008 exhaled in breath Buszewski et al 2007 Schwarz et al 2009 Lourenço and Turner 2014 or present in urine Huang et al 2013 Mochalski et al 2012 have been well characterized in healthy people in the literature Costello et al 2014 Changes in the concentration of specific VOCs can indicate particular diseases Smolinska et al 2014 and changes in metabolic state such as nitric oxide in airway inflammation Barnes et al 2010 or acetone for diabetes Storer et al 2011 and as such they are considered biomarkers Mazzatenta et al 2013 Proton transfer reaction mass spectrometry PTRMS Lindinger et al 1998 Blake et al 2009 is a popular highly sensitive online tool used to measure concentrations of excreted metabolites particularly in breath Herbig et al 2009 Schwarz et al 2009 but also urine Pinggera et al 2005 The technique allows rapid analysis of VOCs due to its online capability Accurate measurements of VOC concentrations are possible in seconds The present study aims to use PTRMS coupled with multivariate and univariate statistical techniques to investigate potential biomarkers for exercise altered metabolism in urine In a previous publication breath acetone which was measured with proton transfer reaction ion trap mass spectrometry correlated positively with both nonesterified fatty acids and betahydroxybutyrate BOHB markers in blood for fatty acid metabolism providing realtime information on fat burning Samudrala et al 2014 We now examine the relation between urine acetone and breath acetone and evaluate the VOCs in urine as possible biomarkers for the effect of 4 days strenuous walking as well as their interplay with medicated type 1 and type 2 diabetes mellitusAll subjects participated in the International Four Days Marches July 2012 an annual walking event in Nijmegen the Netherlands organized by the Dutch Walking Organization KNBLONL In total 51 participants gave urine samples Among them 23 were control CT 11 type1 diabetes mellitus T1DM and 17 type2 diabetes mellitus T2DM Participants included 28 males and 23 females with an age range of 25–85 years Depending on their age and gender participants walked 30 40 or 50 km per day The details of the subjects who participated in this study are shown elsewhere Samudrala et al 2014 This study was approved by the Medical Ethical Committee of the Radboud University Nijmegen Medical Centre Informed consent was obtained from all individual participants included in the study and the study was conducted in accordance with the Declaration of HelsinkiAfter collection the samples were transported via a cooler ~6 °C to a storage freezer of temperature −80 °C Samples were without any centrifuge separation and without any antibacterial additives The samples were later defrosted separated into two vials and refrozen One vial was used for VOCs analysis with PTRMS and the other was used for creatinine measurements Creatinine was measured via an enzymatic method using an ARCHITECT clinical chemistry analyzer Abbott Laboratories Abbott Park Illinois USA

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