Intensive determination of storage condition effects on human plasma metabolomics

Introduction

Human plasma metabolomics offer powerful tools for understanding disease mechanisms and identifying clinical biomarkers for diagnosis, efficacy prediction and patient stratification. Although storage conditions can affect the reliability of data from metabolites, strict control of these conditions remains challenging, particularly when clinical samples are included from multiple centers. Therefore, it is necessary to consider stability profiles of each analyte.

Objectives

The purpose of this study was to extract unstable metabolites from vast metabolome data and identify factors that cause instability.

Method

Plasma samples were obtained from five healthy volunteers, were stored under ten different conditions of time and temperature and were quantified using leading-edge metabolomics. Instability was evaluated by comparing quantitation values under each storage condition with those obtained after ?80 °C storage.

Result

Stability profiling of the 992 metabolites showed time- and temperature-dependent increases in numbers of significantly changed metabolites. This large volume of data enabled comparisons of unstable metabolites with their related molecules and allowed identification of causative factors, including compound-specific enzymatic activity in plasma and chemical reactivity. Furthermore, these analyses indicated extreme instability of 1-docosahexaenoylglycerol, 1-arachidonoylglycerophosphate, cystine, cysteine and N⁶-methyladenosine.

Conclusion

A large volume of data regarding storage stability was obtained. These data are a contribution to the discovery of biomarker candidates without misselection based on unreliable values and to the establishment of suitable handling procedures for targeted biomarker quantification.

     

Strategies to assess and optimize stability of endogenous amines during cerebrospinal fluid sampling

Introduction

Metabolic profiling of cerebrospinal fluid (CSF) is a promising technique for studying brain diseases. Measurements should reflect the in vivo situation, so ex vivo metabolism should be avoided.

Objective

To investigate the effects of temperature (room temperature vs. 4 °C), centrifugation and ethanol, as anti-enzymatic additive during CSF sampling on concentrations of glutamic acid, glutamine and other endogenous amines.

Methods

CSF samples from 21 individuals were processed using five different protocols. Isotopically-labeled alanine, isoleucine, glutamine, glutamic acid and dopamine were added prior to sampling to trace any degradation. Metabolomics analysis of endogenous amines, isotopically-labeled compounds and degradation products was performed with a validated LC–MS method.

Results

Thirty-six endogenous amines were quantified. There were no statistically significant differences between sampling protocols for 31 out of 36 amines. For GABA there was primarily an effect of temperature (higher concentrations at room temperature than at 4 °C) and a small effect of ethanol (lower concentrations if added) due to possible degradation. O-phosphoethanolamine concentrations were also lower when ethanol was added. Degradation of isotopically-labeled compounds (e.g. glutamine to glutamic acid) was minor with no differences between protocols.

Conclusion

Most amines can be considered stable during sampling, provided that samples are cooled immediately to 4 °C, centrifuged, and stored at ??80 °C within 2 h. The effect of ethanol addition for more unstable metabolites needs further investigation. This was the first time that labeled compounds were used to monitor ex vivo metabolism during sampling. This is a useful strategy to study the stability of other metabolites of interest.

     

A comparison of sample preparation methods for extracting volatile organic compounds (VOCs) from equine faeces using HS-SPME

Introduction

Disturbance to the hindgut microbiota can be detrimental to equine health. Metabolomics provides a robust approach to studying the functional aspect of hindgut microorganisms. Sample preparation is an important step towards achieving optimal results in the later stages of analysis. The preparation of samples is unique depending on the technique employed and the sample matrix to be analysed. Gas chromatography mass spectrometry (GCMS) is one of the most widely used platforms for the study of metabolomics and until now an optimised method has not been developed for equine faeces.

Objectives

To compare a sample preparation method for extracting volatile organic compounds (VOCs) from equine faeces.

Methods

Volatile organic compounds were determined by headspace solid phase microextraction gas chromatography mass spectrometry (HS-SPME-GCMS). Factors investigated were the mass of equine faeces, type of SPME fibre coating, vial volume and storage conditions.

Results

The resultant method was unique to those developed for other species. Aliquots of 1000 or 2000 mg in 10 ml or 20 ml SPME headspace were optimal. From those tested, the extraction of VOCs should ideally be performed using a divinylbenzene-carboxen-polydimethysiloxane (DVB-CAR-PDMS) SPME fibre. Storage of faeces for up to 12 months at ? 80 °C shared a greater percentage of VOCs with a fresh sample than the equivalent stored at ? 20 °C.

Conclusions

An optimised method for extracting VOCs from equine faeces using HS-SPME-GCMS has been developed and will act as a standard to enable comparisons between studies. This work has also highlighted storage conditions as an important factor to consider in experimental design for faecal metabolomics studies.

     

Sample storage conditions induce post-collection biases in microbiome profiles

Background

Here we investigated the influence of different stabilization and storage strategies on the quality and composition of the fecal microbial community. Namely, same-day isolated murine DNA was compared to samples stored for 1 month in air at ambient temperature, with or without preservative buffers (i.e. EDTA and lysis buffer), different temperatures (i.e. 4?°C, ??20?°C, and???80?°C), and hypoxic conditions.

Results

Only storage in lysis buffer significantly reduced DNA content, yet without integrity loss. Storage in EDTA affected alpha diversity the most, which was also reflected in cluster separation. Distinct changes were also seen in the phyla and bacterial species abundance per storage strategy. Metabolic function analysis showed 22 pathways not significantly affected by storage conditions, whereas the tyrosine metabolism pathway was significantly changed in all strategies except by EDTA.

Conclusion

Each long-term storage strategy introduced a unique post-collection bias, which is important to take into account when interpreting data.

     

The association of fecal microbiota and fecal,blood serum and urine metabolites in myalgic encephalomyelitis/chronic fatigue syndrome

Introduction

The human gut microbiota has the ability to modulate host metabolism. Metabolic profiling of the microbiota and the host biofluids may determine associations significant of a host–microbe relationship. Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a long-term disorder of fatigue that is poorly understood, but has been linked to gut problems and altered microbiota.

Objectives

Find changes in fecal microbiota and metabolites in ME/CFS and determine their association with blood serum and urine metabolites.

Methods

A workflow was developed that correlates microbial counts with fecal, blood serum and urine metabolites quantitated by high-throughput ¹H NMR spectroscopy. The study consists of thirty-four females with ME/CFS (34.9?±?1.8 SE years old) and twenty-five non-ME/CFS female (33.0?±?1.6 SE years old).

Results

The workflow was validated using the non-ME/CFS cohort where fecal short chain fatty acids (SCFA) were associated with serum and urine metabolites indicative of host metabolism changes enacted by SCFA. In the ME/CFS cohort a decrease in fecal lactate and an increase in fecal butyrate, isovalerate and valerate were observed along with an increase in Clostridium spp. and a decrease in Bacteroides spp. These differences were consistent with an increase in microbial fermentation of fiber and amino acids to produce SCFA in the gut of ME/CFS patients. Decreased fecal amino acids positively correlated with substrates of gluconeogenesis and purine synthesis in the serum of ME/CFS patients.

Conclusion

Increased production of SCFA by microbial fermentation in the gut of ME/CFS patients may be associated with deleterious effects on the host energy metabolism.

     

Comprehensive <Superscript>1</Superscript>H NMR metabolic profiling of body fluids for differentiation of meningitis in adults

Introduction

Meningitis, a morbidly infectious central nervous system pathology is accompanied by acute inflammation of the meninges, causing raised intracranial pressure linked with serious neurological sequelae.

Objective

To observe the variation in the metabolic profile, that may occur in serum and urine along with CSF in adults using ¹H NMR spectroscopy, with an attempt of appropriate and timely treatment regimen.

Methods

The ¹H NMR-based metabolomics has been performed in 115 adult subjects for differentiating bacterial meningitis (BM) and tubercular meningitis (TBM).

Results

The discriminant function analysis (DFA) of the three bio-fluids collectively identified 3-hydroxyisovalerate, lactate, glucose, formate, valine, alanine, ketonic bodies, malonate and choline containing compounds (choline and GPC) as significant metabolites among cases versus control group. The differentiation of bacterial meningitis and tuberculous meningitis (BM vs. TBM) can be done on the basis of identification of 3-hydroxyisovalerate, isobutyrate and formate in case of CSF (with a correct classification of 78 %), alanine in serum (correct classification 60 %), valine and acetone in case of urine (correct classification 89.1 %). The NMR spectral bins based orthogonal signal correction principal component analysis score plots of significant metabolites obtained from DFA also provided group classification among cases versus control group in CSF, serum and urine samples. The variable importance in projection scores also identified similar significant metabolites as obtained from DFA, collectively in CSF, serum and urine samples, responsible for differentiation of meningitis.

Conclusion

The CSF contained metabolites which are formed during infection and inflammation, and these were also found in significant quantity in serum and urine samples.

     

Investigations into,and development of,a lyophilized and formulated recombinant human factor IX produced from CHO cells

Objectives

To develop a recombinant human factor IX (rFIX) formulation equivalent to commercially available products in terms of cake appearance, residual moisture, proportion of soluble aggregates and activity maintenance for 3 months at 4–8 °C.

Results

NaCl and low bulking agent/cryoprotectant mass ratio had a negative impact on cake quality upon lyophilisation for a wide range of formulations tested. Particular devised formulations maintained rFIX activity after lyophilization with a similar performance when compared with the rFIX formulated using the excipients reported for a commercially available FIX formulation (Benefix). rFIX remained active after 3 months when stored at 4 °C, though this was not the case with samples stored at 40 °C. Interestingly, particular formulations had an increase in residual moisture after 3 months storage, but not above a 3% threshold. All four formulations tested were equivalent to the Benefix formulation in terms of particle size distribution and cake appearance.

Conclusions

Three specific formulations, consisting of surfactant polysorbate-80, sucrose or trehalose as cryoprotectant, mannitol or glycine as bulking agent, l-histidine as buffering agent, and NaCl added in the reconstitution liquid at 0.234% (w/v) were suitable for use with a CHO cell-derived recombinant FIX.

     

Metabolomic study of the response to cold shock in a strain of <Emphasis Type="Italic">Pseudomonas syringae</Emphasis> isolated from cloud water

Introduction

Active microorganisms have been recently discovered in clouds, thus demonstrating the capacity of microorganisms to exist in harsh environments, including exposure to UV and oxidants, osmotic and cold shocks, etc. It is important to understand how microorganisms respond to and survive such stresses at the metabolic level.

Objectives

The objective of this work is to assess metabolome modulation in a strain of Pseudomonas syringae isolated from cloud water and facing temperature downshift from 17 to 5 °C by identifying key molecules and pathways of the response/adaptation to cold shock.

Methods

Bacterial extracts from suspensions of cells grown at 17 °C and further incubated in microcosms at 5 and 17 °C to mimic cloud conditions were analysed by combining LC-MS and NMR; the results were evaluated in comparison to similar suspensions kept at constant temperature. The differences in the metabolome profiles were deciphered using multivariate statistics (PLS-DA).

Results

Key cold shock biomarkers were observed, including cryoprotectants (trehalose, glucose, glycerol, carnitine, glutamate), antioxidants (glutathione and carnitine) and their precursors, alkaloids (bellendine and slaframine) and metabolites involved in energy metabolism (ATP, carbohydrates). Furthermore, new short peptides (nine dipeptides and a tetrapeptide) were found that have no known function.

Conclusions

This study shows that in response to cold temperatures, Pseudomonas syringae PDD-32b-74 demonstrates numerous metabolism modifications to counteract the impacts of low temperatures.

     

Bile acid quantification of 20 plasma metabolites identifies lithocholic acid as a putative biomarker in Alzheimer’s disease

Introduction

There is still a clear need for a widely available, inexpensive and reliable method to diagnose Alzheimer’s disease (AD) and monitor disease progression. Liquid chromatography–mass spectrometry (LC-MS) is a powerful analytic technique with a very high sensitivity and specificity.

Objectives

The aim of the present study is to measure concentrations of 20 bile acids using the novel Kit from Biocrates Life Sciences based on LC-MS technique.

Methods

Twenty bile acid metabolites were quantitatively measured in plasma of 30 cognitively healthy subjects, 20 patients with mild cognitive impairment (MCI) and 30 patients suffering from AD.

Results

Levels of lithocholic acid were significantly enhanced in plasma of AD patients (50?±?6 nM, p?=?0.004) compared to healthy controls (32?±?3 nM). Lithocholic acid plasma levels of MCI patients (41?±?4 nM) were not significantly different from healthy subjects or AD patients. Levels of glycochenodeoxycholic acid, glycodeoxycholic acid and glycolithocholic acid were significantly higher in AD patients compared to MCI patients (p?<?0.05). All other cholic acid metabolites were not significantly different between healthy subjects, MCI patients and AD patients. ROC analysis shows an overall accuracy of about 66%. Discriminant analysis was used to classify patients and we found that 15/23 were correctly diagnosed. We further showed that LCA levels increased by about 3.2 fold when healthy subjects converted to AD patients within a 8–9 year follow up period. Pathway analysis linked these changes to a putative toxic cholesterol pathway.

Conclusion

In conclusion, 4 bile acids may be useful to diagnose AD in plasma samples despite limitations in diagnostic accuracy.

     

Organic washes of tissue sections for comprehensive analysis of small molecule metabolites by MALDI MS imaging of rat brain following status epilepticus

Introduction

In-situ detection and in particular comprehensive analysis of small molecule metabolites (SMMs, m/z?<?500) using matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI MSI) remain a challenge, mainly due to ion suppression effects from more abundant molecules in tissue section like lipids.

Objective

A strategy based on organic washes to remove most ionization-suppressing lipids from tissue section was firstly explored for improved analysis of SMMs by MALDI MSI.

Methods

The tissue sections after rinse with different organic solvents were analyzed by MALDI MSI, and the results were compared for the optimized washing conditions.

Results

The rinse with chloroform for 15 s at ??20 °C significantly removed most glycerophospholipids and glycerolipids from tissue section. Consequentially, ATP-related energy metabolites, amino acids and derivatives, glucose derivatives, glycolysis pathway metabolites and other SMMs were able to be well-visualized with enhanced ion intensity and good reproducibility. The organic washes-based MALDI MSI was applied to the metabolic pathway analysis in rat brain following status epilepticus (SE) model, which was, as far as we know, the first report about in-situ detection of a broad range of metabolites in the model of SE by MALDI MSI technique. The alterations of cyclic adenosine monophosphate (cyclic AMP), inosine, glutamine, glutathione, taurine and spermine during SE were observed.

Conclusion

A simple organic washing protocol enables comprehensive analysis of tissue SMMs in MALDI MSI by removing ionization-suppressing lipids. The application in the SE model indicates that MALDI MSI analysis potentially provides new insight for understanding the disease mechanism.

     

Urine metabolic fingerprinting can be used to predict the risk of metritis and highlight the pathobiology of the disease in dairy cows

Introduction

Metritis is an uterine pathology that causes economic losses for the dairy industry. It is associated with lower reproductive efficiency, increased culling rates, decreased milk production and increased veterinary costs.

Objectives

To gain a more detailed view of the urine metabolome and to detect metabolite signature in cows with metritis. In addition, we aimed to identify early metabolites which can help to detect cows at risk to develop metritis in the future.

Methods

We used nuclear magnetic resonance spectroscopy starting at 8 and 4 weeks prior to the expected day of parturition, during the week of diagnosis of metritis, and at 4 and 8 weeks after diagnosis of metritis in Holstein dairy cows.

Results

At 8 weeks before parturition, pre-metritic cows had a total of 30 altered metabolites. Interestingly, 28 of them increased in urine when compared with control cows (P?<?0.05). At 4 weeks before parturition, 34 metabolites were altered. At the week of diagnosis of metritis a total of 20 metabolites were altered (P?<?0.05). The alteration continued at 4 and 8 weeks after diagnosis.

Conclusions

The metabolic fingerprints in the urine of pre-metritic and metritic cows point toward excretion of multiple amino acids, tricarboxylic acid cycle metabolites and monosaccharides. Combination of galactose, leucine, lysine and panthotenate at 8 weeks before parturition might serve as predictive biomarkers for metritis.

     

Impact of post-collection freezing delay on the reliability of serum metabolomics in samples reflecting the California mid-term pregnancy biobank

Background

Population-based biorepositories are important resources, but sample handling can affect data quality.

Objective

Identify metabolites of value for clinical investigations despite extended postcollection freezing delays, using protocols representing a California mid-term pregnancy biobank.

Methods

Blood collected from non-pregnant healthy female volunteers (n?=?20) underwent three handling protocols after 30 min clotting at room temperature: (1) ideal—samples frozen (??80 °C) within 2 h of collection; (2) delayed freezing—samples held at room temperature for 3 days, then 4 °C for 9 days, the median times for biobank samples, and then frozen; (3) delayed freezing with freeze–thaw—the delayed freezing protocol with a freeze–thaw cycle simulating retrieved sample sub-aliquoting. Mass spectrometry-based untargeted metabolomic analyses of primary metabolism and complex lipids and targeted profiling of oxylipins, endocannabinoids, ceramides/sphingoid-bases, and bile acids were performed. Metabolite concentrations and intraclass correlation coefficients (ICC) were compared, with the ideal protocol as the reference.

Results

Sixty-two percent of 428 identified compounds had good to excellent ICCs, a metric of concordance between measurements of samples handled with the different protocols. Sphingomyelins, phosphatidylcholines, cholesteryl esters, triacylglycerols, bile acids and fatty acid diols were the least affected by non-ideal handling, while sugars, organic acids, amino acids, monoacylglycerols, lysophospholipids, N-acylethanolamides, polyunsaturated fatty acids, and numerous oxylipins were altered by delayed freezing. Freeze–thaw effects were assay-specific with lipids being most stable.

Conclusions

Despite extended post-collection freezing delays characteristic of some biobanks of opportunistically collected clinical samples, numerous metabolomic compounds had both stable levels and good concordance.

     

Postprandial metabolite profiles associated with type 2 diabetes clearly stratify individuals with impaired fasting glucose

Introduction

Fasting metabolite profiles have been shown to distinguish type 2 diabetes (T2D) patients from normal glucose tolerance (NGT) individuals.

Objectives

We investigated whether, besides fasting metabolite profiles, postprandial metabolite profiles associated with T2D can stratify individuals with impaired fasting glucose (IFG) by their similarities to T2D.

Methods

Three groups of individuals (age 45–65 years) without any history of IFG or T2D were selected from the Netherlands Epidemiology of Obesity study and stratified by baseline fasting glucose concentrations (NGT (n?=?176), IFG (n?=?186), T2D (n?=?171)). 163 metabolites were measured under fasting and postprandial states (150 min after a meal challenge). Metabolite profiles specific for a high risk of T2D were identified by LASSO regression for fasting and postprandial states. The selected profiles were utilised to stratify IFG group into high (T2D probability?≥?0.7) and low (T2D probability?≤?0.5) risk subgroups. The stratification performances were compared with clinically relevant metabolic traits.

Results

Two metabolite profiles specific for T2D (n_fasting = 12 metabolites, n_postprandial = 4 metabolites) were identified, with all four postprandial metabolites also being identified in the fasting state. Stratified by the postprandial profile, the high-risk subgroup of IFG individuals (n?=?72) showed similar glucose concentrations to the low-risk subgroup (n?=?57), yet a higher BMI (difference: 3.3 kg/m² (95% CI 1.7–5.0)) and postprandial insulin concentrations (21.5 mU/L (95% CI 1.8–41.2)).

Conclusion

Postprandial metabolites identified T2D patients as good as fasting metabolites and exhibited enhanced signals for IFG stratification, which offers a proof of concept that metabolomics research should not focus on the fasting state alone.

     

Small temperature differences can improve the performance of mesophilic sludge-based digesters

Objective

To assess the effect of small temperature increases in mesophilic sludge-based digesters in order to develop and evaluate strategies for improving the biogas production in full-scale digesters.

Results

Methane production was strongly affected by small temperature differences, and this result was consistent across samples from 15 full-scale digesters. The specific methane yield varied between 42 and 97.5 ml g VS^?1 after 15 days of incubation at 35 °C, and improved when increasing the digester temperature to 39 °C. Only a limited quantity of additional gas was required to balance out the cost of heating and a positive energy balance was obtained. Further increases in temperature, in some cases, negatively affected the production when operated at 42 °C compared to 39 °C.

Conclusions

Small temperature increases should be applied to mesophilic sludge-based digesters to optimize the biogas production and is applicable to digesters operated in the lower mesophilic temperature range.

     

Weight loss and weight maintenance obtained with or without GLP-1 analogue treatment decrease branched chain amino acid levels

Introduction

Increased levels of circulating branched chain amino acids (BCAAs), as well as phenylalanine, and tyrosine have been suggested to be involved in the pathogenesis of insulin resistance and type 2 diabetes. However, it is unknown how these metabolites are affected by weight loss, and during weight-maintaining treatment with glucagon-like peptide-1 receptor agonist (GLP-1 RA).

Objective

We aimed to characterize changes in metabolites related to protein turnover and glycolysis after a weight loss intervention followed by long term weight maintenance with/without GLP-1 RA.

Methods

Fifty-eight obese individuals underwent a diet-induced 12 % body weight loss during 8 weeks. Participants were randomized to weight maintenance with or without administration of the GLP-1 RA liraglutide (1.2 mg/day) for 52 weeks. Metabolomic profiling by high-throughput proton nuclear magnetic resonance spectroscopy was used for quantification of metabolites.

Results

The weight loss was maintained in both groups and was associated with 9–20 % decreases in plasma concentrations of alanine, phenylalanine, histidine, tyrosine and the BCAAs leucine, isoleucine and valine (p < 0.05). Plasma citrate levels increased during weight loss (p = 5.2 × 10^?15) and showed inverse correlation with insulin resistance measured by HOMA–IR levels (r = ?0.318, p = 0.025). Valine concentrations were lower in the control group compared to the GLP-1RA group during weight maintenance (p = 0.005).

Conclusion

Weight loss is associated with marked changes in plasma concentrations of eight amino acids and glycolysis-related metabolites. Levels of the suggested type 2 diabetes risk markers (BCAAs) remain low during long-term weight maintenance.

     

Mid- and long-term correlations of plasma metabolite concentrations measured by a targeted metabolomics approach

Introduction

Plasma metabolites measured by metabolomics techniques have been shown to be associated with chronic disease risk in epidemiological studies. However, in most prospective studies metabolomic profiles can only be obtained at a single time point and data on intra-individual variation in metabolite levels over time are sparse.

Objectives

Here, we evaluated the intra-individual variation in the concentrations of 177 metabolites over time using repeat blood samples of 104 adults (50% female).

Methods

Blood samples were obtained at a baseline visit between 1994 and 1998 and during two further examinations 14 and 15 years later. Plasma metabolite levels were quantified by tandem mass spectrometry with the MetaDisIDQ? p180 Kit. Intra-individual variation was assessed by Spearman’s correlation coefficients (ρ).

Results

Mid-term correlations over 1 year were good (ρ ≥ 0.7) for 5.1% and reasonable (ρ ≥ 0.4 < 0.7) for 61.0% of the metabolites, while long-term correlations over 15 years were good for 2.8% and reasonable for 27.1%. The strongest mid-term correlations between metabolite concentrations were observed for the acylcarnitine C₃–OH (0.72) and metabolites from the amino acid/biogenic amine groups, i.e. creatinine (0.83), proline (0.79), lysine (0.77), isoleucine (0.76), and ornithine (0.74). C₃–OH (0.78) as well as several amino acids/biogenic amines, i.e. ornithine (0.76), sarcosine (0.76), lysine (0.75), spermine (0.73), and glutamine (0.69) showed the strongest long-term correlations.

Conclusions

The biological reproducibility of plasma concentrations of a majority of metabolites occurs reasonable over 1 year. In contrast, concentrations of many metabolites seem to be affected by substantial intra-individual variation over 15 years.

     

Urine metabolites are associated with glomerular lesions in type 2 diabetes

Introduction

Little is known about the association of urine metabolites with structural lesions in persons with diabetes.

Objectives

We examined the relationship between 12 urine metabolites and kidney structure in American Indians with type 2 diabetes.

Methods

Data were from a 6-year clinical trial that assessed renoprotective efficacy of losartan, and included a kidney biopsy at the end of the treatment period. Metabolites were measured in urine samples collected within a median of 6.5 months before the research biopsy. Associations of the creatinine-adjusted urine metabolites with kidney structural variables were examined by Pearson’s correlations and multivariable linear regression after adjustment for age, sex, diabetes duration, hemoglobin A_1c, mean arterial pressure, glomerular filtration rate (iothalamate), and losartan treatment.

Results

Participants (n?=?62, mean age 45?±?10 years) had mean?±?standard deviation glomerular filtration rate of 137?±?50 ml/min and median (interquartile range) urine albumin:creatinine ratio of 34 (14–85) mg/g near the time of the biopsy. Urine aconitic and glycolic acids correlated positively with glomerular filtration surface density (partial r?=?0.29, P?=?0.030 and r?=?0.50, P?<?0.001) and total filtration surface per glomerulus (partial r?=?0.32, P?=?0.019 and r?=?0.43, P?=?0.001). 2-ethyl 3-OH propionate correlated positively with the percentage of fenestrated endothelium (partial r?=?0.32, P?=?0.019). Citric acid correlated negatively with mesangial fractional volume (partial r=-0.36, P?=?0.007), and homovanillic acid correlated negatively with podocyte foot process width (partial r=-0.31, P?=?0.022).

Conclusions

Alterations of urine metabolites may associate with early glomerular lesions in diabetic kidney disease.

     

Reproducibility of non-fasting plasma metabolomics measurements across processing delays

Introduction

Processing delays after blood collection is a common pre-analytical condition in large epidemiologic studies. It is critical to evaluate the suitability of blood samples with processing delays for metabolomics analysis as it is a potential source of variation that could attenuate associations between metabolites and disease outcomes.

Objectives

We aimed to evaluate the reproducibility of metabolites over extended processing delays up to 48 h. We also aimed to test the reproducibility of the metabolomics platform.

Methods

Blood samples were collected from 18 healthy volunteers. Blood was stored in the refrigerator and processed for plasma at 0, 15, 30, and 48 h after collection. Plasma samples were metabolically profiled using an untargeted, ultrahigh performance liquid chromatography–tandem mass spectrometry (UPLC–MS/MS) platform. Reproducibility of 1012 metabolites over processing delays and reproducibility of the platform were determined by intraclass correlation coefficients (ICCs) with variance components estimated from mixed-effects models.

Results

The majority of metabolites (approximately 70% of 1012) were highly reproducible (ICCs?≥?0.75) over 15-, 30- or 48-h processing delays. Nucleotides, energy-related metabolites, peptides, and carbohydrates were most affected by processing delays. The platform was highly reproducible with a median technical ICC of 0.84 (interquartile range 0.68–0.93).

Conclusion

Most metabolites measured by the UPLC–MS/MS platform show acceptable reproducibility up to 48-h processing delays. Metabolites of certain pathways need to be interpreted cautiously in relation to outcomes in epidemiologic studies with prolonged processing delays.

     

Metallotyping of ketotic dairy cows reveals major alterations preceding,associating, and following the disease occurrence

Introduction

Ketosis is a common metabolic disorder, which is characterized by elevated concentrations of ketone bodies or ketoacids in three body fluids including blood, urine, and milk. Two of the ketones including β-hydroxybutyric acid and acetoacetic acid are strong acids which at high concentrations trigger ketoacidosis influencing physiological functions of various tissues and organs.

Objectives

The objectives of this study were to: (1) investigate mineral alterations in both serum and urine of preketotic, ketotic, and postketotic cows, (2) identify potential predictive and diagnostic mineral biomarkers for ketosis in serum and urine, and (3) better understand the role of minerals in the pathobiology of the disease.

Methods

Inductively coupled plasma mass spectrometry metallotyping was performed in the serum and urine of six cases of ketosis and 20 healthy controls cows at ?8 and ?4 weeks prepartum, at disease diagnosis week, and at +4 and +8 weeks postpartum.

Results

Data showed that concentrations of aluminum (Al), iron (Fe), manganese (Mn), and arsenic (As) were greater (P?<?0.001) in the serum of preketotic, ketotic and postketotic cows at most of the tested time points. Moreover, boron (B) and Al as well as calcium (Ca), phosphorus (P), potassium (K), and magnesium (Mg) were found to be elevated in the urine of preketotic and postketotic cows (P?<?0.001).

Conclusions

It is concluded that alterations of mineral elements observed in the serum and urine of preketotic, ketotic, and postketotic cows might be related to the state of chronic acidosis in those cows. The mineral elements identified in both serum and urine can be used as biomarkers to early diagnose ketosis at its pre-subclinical state and develop preventive interventions in the future.