Increased urinary osmolyte excretion indicates chronic kidney disease severity and progression rate.

Background: Chronic kidney disease (CKD) is a recognized global health problem. While some CKD patients remain stable after initial diagnosis, others can rapidly progress towards end-stage renal disease (ESRD). This makes biomarkers capable of detecting progressive forms of CKD extremely valuable, especially in non-invasive biofluids such as urine. Screening for metabolite markers using non-targeted metabolomic techniques like nuclear magnetic resonance spectroscopy is increasingly applied to CKD research. Methods: A cohort of CKD patients (n = 227) with estimated glomerular filtration rates (eGFRs) ranging from 9.4-130 mL/min/1.73 m2 was evaluated and urine metabolite profiles were characterized in relation to declining eGFR. Nested in this cohort, a retrospective subset (n = 57) was investigated for prognostic metabolite markers of CKD progression, independent of baseline eGFR. A transcriptomic analysis of murine models of renal failure was performed to validate selected metabolomic findings. Results: General linear modeling revealed 11 urinary metabolites with significant associations to reduced eGFR. Linear modelling specifically showed that increased urine concentrations of betaine (P < 0.05) and myo-inositol (P < 0.05) are significant prognostic markers of CKD progression. Conclusions: Renal organic osmolytes, betaine and myo-inositol play a critical role in protecting renal cells from hyperosmotic stress. Kidney tissue transcriptomics of murine preclinical experimentation identified decreased expression of Slc6a12 and Slc5a11 mRNA in renal tissue consistent with defective tubular transport of these osmolytes. Imbalances in renal osmolyte regulation lead to increased renal cell damage and thus more progressive forms of CKD. Increases in renal osmolytes in urine could provide clinical diagnostic and prognostic information on CKD outcomes.

(1)H NMR-based metabolite profiling workflow to reduce inter-sample chemical shift variations in urine samples for improved biomarker discovery.

Metabolite profiling of urine has seen much advancement in recent years, and its analysis by nuclear magnetic resonance (NMR) spectroscopy has become well established. However, the highly variable nature of human urine still requires improved protocols despite some standardization. In particular, diseases such as kidney disease can have a profound effect on the composition of urine and generate a highly diverse sample set for clinical studies. Large variations in pH and the cationic concentration of urine play an important role in creating positional noise within datasets generated from NMR. We demonstrate positional noise to be a confounding variable for multivariate statistical tools such as statistical total correlation spectroscopy (STOCSY), thereby hindering the process of biomarker discovery. We present a two-dimensional buffering system using potassium fluoride (KF) and phosphate buffer to reduce positional noise in metabolomic data generated from urine samples with various levels of proteinuria. KF reduces positional noise in citrate peaks, by decreasing the mean relative standard deviation (RSD) from 0.17 to 0.09. By reducing positional noise with KF, STOCSY analysis of citrate peaks saw significant improvement. We further aligned spectral data using a recursive segment-wise peak alignment (RSPA) method, which leads to further improvement of the positional noise (RSD = 0.06). These results were validated using diverse selection of metabolites which lead to an overall improvement in positional noise using the suggested protocol. In summary, we provide an improved workflow for urine metabolite biomarker discovery to achieve higher data quality for better pathophysiological understanding of human diseases. Graphical abstract Citrate peaks in the range 2.75-2.5 ppm from datasets with different sample preparation protocols and with/without in silico alignment. A Citrate peaks with standard phosphate buffering and without in silico alignment. B citrate peaks with standard phosphate buffering and with in silico alignment. C citrate peak with additional potassium fluoride and standard phosphate buffering without in silico alignment. D citrate peaks with additional potassium fluoride and standard phosphate buffering with in silico alignment. Below the respective spectrum are displayed the percent relative standard deviation (RSD) of the respective citrate peaks. This is a measure of the positional noise of peaks within a (1)H NMR analysis. It can be seen that D performs the best in reducing positional noise of citrate peaks. E-H STOCSY analysis of correlating spectral features with the driver peak at 2.675 ppm (see red arrow) to identify structural correlations. As a, b, c, and d are known to be structurally correlated, STOCSY analysis should reveal r (2) = 1 if data is perfectly aligned and can therefore be used as a measure of peak alignment. E Strong positional noise does not allow identifying the c and d peaks of the AB system to be correlated. F, G Neither in silico alignment or KF addition alone can completely improve the alignment and therefore increase the correlations. H Highly improved alignment by combining both KF addition and in silico alignment reduces positional noise and elucidates all four citrate peaks to be strongly correlated.

Natural oxygenation of Champagne wine during ageing on lees: A metabolomics picture of hormesis.

The oxygenation of Champagne wine after 4 and 6 years of aging on lees in bottle was investigated by FTICR-MS and UPLC-Q-TOF-MS. Three levels of permeability were considered for the stoppers, ranging from 0.2 to 1.8 mg/L/year of oxygen transfer rate. Our results confirmed a good repeatability of ultra-high resolution FTICR-MS, both in terms of m/z and coefficient of variation of peak intensities among biological replicates. Vintages appeared to be the most discriminated features, and metabolite annotations suggested that the oldest wines (2006) were characterized by a higher sensitivity towards oxygenation. Within each vintage, the oxygenation mechanisms appeared to be different for low and high ingresses of oxygen, in agreement with the hormesis character of wine oxygenation. In the particular case of single variety wines and for a given level of stopper permeability, our results also showed that variety discrimination could be easily achieved among wines.

Metabolic determinants of electrical failure in ex-vivo canine model of cardiac arrest: evidence for the protective role of inorganic pyrophosphate.

RATIONALE: Deterioration of ventricular fibrillation (VF) into asystole or severe bradycardia (electrical failure) heralds a fatal outcome of cardiac arrest. The role of metabolism in the timing of electrical failure remains unknown. OBJECTIVE: To determine metabolic factors of early electrical failure in an ex-vivo canine model of cardiac arrest (VF+global ischemia). METHODS AND RESULTS: Metabolomic screening was performed in left ventricular biopsies collected before and after 0.3, 2, 5, 10 and 20 min of VF and global ischemia. Electrical activity was monitored via plunge needle electrodes and pseudo-ECG. Four out of nine hearts exhibited electrical failure at 10.1±0.9 min (early-asys), while 5/9 hearts maintained VF for at least 19.7 min (late-asys). As compared to late-asys, early-asys hearts had more ADP, less phosphocreatine, and higher levels of lactate at some time points during VF/ischemia (all comparisons p<0.05). Pre-ischemic samples from late-asys hearts contained ∼25 times more inorganic pyrophosphate (PPi) than early-asys hearts. A mechanistic role of PPi in cardioprotection was then tested by monitoring mitochondrial membrane potential (ΔΨ) during 20 min of simulated-demand ischemia using potentiometric probe TMRM in rabbit adult ventricular myocytes incubated with PPi versus control group. Untreated myocytes experienced significant loss of ΔΨ while in the PPi-treated myocytes ΔΨ was relatively maintained throughout 20 min of simulated-demand ischemia as compared to control (p<0.05). CONCLUSIONS: High tissue level of PPi may prevent ΔΨm loss and electrical failure at the early phase of ischemic stress. The link between the two protective effects may involve decreased rates of mitochondrial ATP hydrolysis and lactate accumulation.