Stability of amino acids and related amines in human serum under different preprocessing and pre-storage conditions based on iTRAQ®-LC-MS/MS

Preoperative profiles of plasma amino acids and derivatives distinguish periampullary cancer and benign disease

Periampullary cancers, including pancreatic ductal adenocarcinoma, ampullary-, cholangio-, and duodenal carcinoma, are frequently diagnosed in an advanced stage and are associated with poor overall survival. They are difficult to differentiate from each other and challenging to distinguish from benign periampullary disease preoperatively. To improve the preoperative diagnostics of periampullary neoplasms, clinical or biological markers are warranted.In this study, 28 blood plasma amino acids and derivatives from preoperative patients with benign (N = 45) and malignant (N = 72) periampullary disease were analyzed by LC-MS/MS.Principal component analysis and consensus clustering both separated the patients with cancer and the patients with benign disease. Glutamic acid had significantly higher plasma expression and 15 other metabolites significantly lower plasma expression in patients with malignant disease compared with patients having benign disease. Phenylalanine was the only metabolite associated with improved overall survival (HR = 0.50, CI 0.30-0.83, P < 0.01).Taken together, plasma metabolite profiles from patients with malignant and benign periampullary disease were significantly different and have the potential to distinguish malignant from benign disease preoperatively.

Targeted ultra performance liquid chromatography tandem mass spectrometry procedures for the diagnosis of inborn errors of metabolism: validation through ERNDIM external quality assessment schemes

OBJECTIVES

Early diagnosis of inborn errors of metabolism (IEM) is crucial to ensure early detection of conditions which are treatable. This study reports on targeted metabolomic procedures for the diagnosis of IEM of amino acids, acylcarnitines, creatine/guanidinoacetate, purines/pyrimidines and oligosaccharides, and describes its validation through external quality assessment schemes (EQA).

METHODS

Analysis was performed on a Waters ACQUITY UPLC H-class system coupled to a Waters Xevo triple-quadrupole (TQD) mass spectrometer, operating in both positive and negative electrospray ionization mode. Chromatographic separation was performed on a CORTECS C18 column (2.1 × 150, 1.6 µm). Data were collected by multiple reaction monitoring.

RESULTS

The internal and EQA results were generally adequate, with a few exceptions. We calculated the relative measurement error (RME) and only a few metabolites displayed a RME higher than 30 % (asparagine and some acylcarnitine species). For oligosaccharides, semi-quantitative analysis of an educational panel clearly identified the 8 different diseases included.

CONCLUSIONS

Overall, we have validated our analytical system through an external quality control assessment. This validation will contribute to harmonization between laboratories, thus improving identification and management of patients with IEM.

Demographic, Health and Lifestyle Factors Associated with the Metabolome in Older Women

Demographic and clinical factors influence the metabolome. The discovery and validation of disease biomarkers are often challenged by potential confounding effects from such factors. To address this challenge, we investigated the magnitude of the correlation between serum and urine metabolites and demographic and clinical parameters in a well-characterized observational cohort of 444 post-menopausal women participating in the Women’s Health Initiative (WHI). Using LC-MS and lipidomics, we measured 157 aqueous metabolites and 756 lipid species across 13 lipid classes in serum, along with 195 metabolites detected by GC-MS and NMR in urine and evaluated their correlations with 29 potential disease risk factors, including demographic, dietary and lifestyle factors, and medication use. After controlling for multiple testing (FDR < 0.01), we found that log-transformed metabolites were mainly associated with age, BMI, alcohol intake, race, sample storage time (urine only), and dietary supplement use. Statistically significant correlations were in the absolute range of 0.2–0.6, with the majority falling below 0.4. Incorporation of important potential confounding factors in metabolite and disease association analyses may lead to improved statistical power as well as reduced false discovery rates in a variety of data analysis settings.

Hemoglobin normalization outperforms other methods for standardizing dried blood spot metabolomics: A comparative study

Dried blood spot (DBS) metabolomics has numerous applications in newborn health screening, exposomics, and biomonitoring of environmental chemicals in pregnant women and the elderly. However, accurate metabolite quantification is hindered by several challenges: notably the "hematocrit effect" and unknown blood-spotting volumes. Different techniques have been employed to overcome these issues but there is no consensus on the optimal normalization method for DBS metabolomics, and in some cases no normalization is used. We compared five normalization methods (hemoglobin (Hb), specific gravity (SG), protein, spot weight, potassium (K+)) to unnormalized data, and assessed sex-related differences in the DBS metabolome in 21 adults (group 1, n = 10 males, n = 11 females). The performance of each normalization method was evaluated using multiple criteria: (a) reduction of intragroup variation (pooled median absolute deviation, pooled estimate of variance, pooled coefficient of variation, NMDS and principal component analysis), (b) effect on differential metabolic analysis (dendrogram, heatmap, p-value distribution), and (c) influence on classification accuracy (partial least squares discriminant analysis, sparse partial least squares discriminant analysis error rates, receiver operating curve, random forest out of bag error rate). Our results revealed that Hb normalization outperformed all the other methods based on the three criteria and 13 different parameters; the performance of Hb was further demonstrated in an independent group of DBS from 18 neonates (group 2, n = 9 males, n = 9 females). Furthermore, we showed that SG and Hb are correlated in adults (rs = 0.86, p < 0.001), and validated this relationship in an independent group of 18 neonates and infants (group 3) (rs = 0.84, p < 0.001). Using the equation, SG = -0.4814Hb2 + 2.44Hb + 0.005, SG can be used as a surrogate for normalization by Hb. This is the first comparative study to concurrently evaluate multiple normalization methods for DBS metabolomics which will serve as a robust methodological platform for future environmental epidemiological studies.

Isolated Effects of Plasma Freezing versus Thawing on Metabolite Stability

Freezing and thawing plasma samples is known to perturb metabolite stability. However, no study has systematically tested how different freezing and thawing methods affect plasma metabolite levels. The objective of this study was to isolate the effects of freezing from thawing on mouse plasma metabolite levels, by comparing a matrix of freezing and thawing conditions through 10 freeze–thaw cycles. We tested freezing with liquid nitrogen (LN2), at −80 °C, or at −20 °C, and thawing quickly in room temperature water or slowly on ice. Plasma samples were extracted and the relative abundance of 87 metabolites was obtained via liquid chromatography–mass spectrometry (LC–MS). Observed changes in metabolite abundance by treatment group correlated with the amount of time it took for samples to freeze or thaw. Thus, snap-freezing with LN2 and quick-thawing with water led to minimal changes in metabolite levels. Conversely, samples frozen at −20 °C exhibited the most changes in metabolite levels, likely because freezing required about 4 h, versus freezing instantaneously in LN2. Overall, our results show that plasma samples subjected to up to 10 cycles of LN2 snap-freezing with room temperature water quick-thawing exhibit remarkable metabolomic stability.

Novel Apparatuses for Incorporating Natural Selection Processes into Origins-of-Life Experiments to Produce Adaptively Evolving Chemical Ecosystems

Origins-of-life chemical experiments usually aim to produce specific chemical end-products such as amino acids, nucleic acids or sugars. The resulting chemical systems do not evolve or adapt because they lack natural selection processes. We have modified Miller origins-of-life apparatuses to incorporate several natural, prebiotic physicochemical selection factors that can be tested individually or in tandem: freezing-thawing cycles; drying-wetting cycles; ultraviolet light-dark cycles; and catalytic surfaces such as clays or minerals. Each process is already known to drive important origins-of-life chemical reactions such as the production of peptides and synthesis of nucleic acid bases and each can also destroy various reactants and products, resulting selection within the chemical system. No previous apparatus has permitted all of these selection processes to work together. Continuous synthesis and selection of products can be carried out over many months because the apparatuses can be re-gassed. Thus, long-term chemical evolution of chemical ecosystems under various combinations of natural selection may be explored for the first time. We argue that it is time to begin experimenting with the long-term effects of such prebiotic natural selection processes because they may have aided biotic life to emerge by taming the combinatorial chemical explosion that results from unbounded chemical syntheses.

Analytical Validation of an Assay for Concurrent Measurement of Amino Acids in Dog Serum and Comparison of Amino Acid Concentrations between Whole Blood, Plasma, and Serum from Dogs

Amino acids play an important role in metabolism. Comprehensive analytical validation of an assay for the concurrent measurement of a large number of amino acids in dogs is lacking, which precludes its usefulness in a clinical setting. Amino acids are often measured in plasma or whole blood. However, serum is commonly used for gastrointestinal diagnostic testing in dogs and is therefore convenient to use. This study aimed to analytically validate an assay for the concurrent measurement of amino acids in dog serum and to evaluate differences in amino acid concentrations in whole blood, plasma, and serum in dogs. Analytical validation of the assay (Biochrom 30+ Amino Acid Analyzer) was performed on fresh or banked serum samples from dogs. Whole blood, plasma, and serum from 36 healthy dogs were analyzed, and concentrations of the three sample types were compared. The assay was demonstrated to be precise, reproducible, accurate, linear, and stable for the measurement of the majority of compounds detected in dog serum. Cystine, glutamic acid, and ethanolamine were shown to be unstable at conditions commonly encountered in clinical settings. Significant differences in concentrations were identified between whole blood, plasma, and serum for 33 of 42 compounds. Amino acid profiles in serum and plasma were more similar to each other than to those in whole blood. While some amino acids are present in similar concentrations in whole blood, plasma, and serum, others are highly dependent on the type of biofluid, and measurements warrant strict adherence to sample type-based reference intervals.

Long time stability of 35 small endogenous biomolecules in dried urine spotted on various surfaces and environmental conditions

Analysis of endogenous biomolecules is an important aspect of many forensic investigations especially with focus on DNA analysis for perpetrator/victim identification and protein analysis for body fluid identification. Recently, small endogenous biomolecules have been used for differentiation of synthetic "fake" urine from authentic urine and might be also useful for biofluid identification. Therefore, the aim of this study was to adapt and optimize a method for analysis of small EBs and to investigate long time stability of 35 small endogenous biomolecules (including acylcarnitines with their isomers and metabolites as well as amino acids with their metabolites) in spotted urine samples. Urine samples were spotted on seven different surfaces (Whatman 903 Protein Saver Cards, cotton swabs, cotton glove, denim, underwear, and smooth and rough flagstone) and stored under six environmental conditions (reference condition, sunlight, LED light, 4 °C, 37 °C, humidity of 95%). At certain time points (d0, d7, d28 and d56) samples were analyzed in triplicates by an optimized extraction and LC-HRMS approach. In addition, the urine marker Tamm-Horsfall-Protein was determined on cotton swabs at the same time points using a commercial lateral flow test. Twenty-one of 35 small endogenous biomolecules were stable on most materials/surfaces and under most storage conditions. Significant lower endogenous biomolecule peak areas were found for rough flagstone and underwear as well as for high humidity storage. Kynurenic acid proved to be photo labile. While high long time stabilities were found for 19 of 28 acylcarnitines, nine acylcarnitines showed aberrant stability patterns without evident structural reason. For Tamm-Horsfall-Protein degradation within 28 days was observed even under reference conditions. The presented study demonstrated the value of sensitive LC-HRMS analysis for small endogenous biomolecules / pattern. However, further studies will be indispensable for unambiguous body fluid identification by small endogenous biomolecules.

Serum metabolomic profiles in dogs with chronic enteropathy

BACKGROUND

Metabolic profiles differ between healthy humans and those with inflammatory bowel disease. Few studies have examined metabolic profiles in dogs with chronic enteropathy (CE).

HYPOTHESIS

Serum metabolic profiles of dogs with CE are significantly different from those of healthy dogs.

ANIMALS

Fifty-five dogs with CE and 204 healthy controls.

METHODS

A cross-sectional study. The serum concentrations of 99 metabolites measured using a canine-specific proton nuclear magnetic resonance spectroscopy platform were studied. A 2-sample unpaired t-test was used to compare the 2 study samples. The threshold for significance was set at P < .05 with a Bonferroni correction for each metabolite group.

RESULTS

Nineteen metabolites and 18 indices of lipoprotein composition were significantly different between the CE and healthy dogs. Four metabolites were significantly higher in dogs with CE, including phenylalanine (mean and SD) (healthy: 0.0417 mmol/L; [SD] 0.0100; CE: 0.0480 mmol/L; SD: 0.0125; P value: <.001) and lactate (healthy: 1.8751 mmol/L; SD: 0.7808; CE: 2.4827 mmol/L; SD CE: 1.4166; P value: .003). Fifteen metabolites were significantly lower in dogs with CE, including total fatty acids, and glycine (healthy: 0.2273 mmol/L; SD: 0.0794; CE: 0.1828 mmol/L; SD CE: 0.0517; P value: <.001).

CONCLUSIONS AND CLINICAL IMPORTANCE

The metabolic profile of dogs with CE is significantly different from that of healthy dogs, this opens novel research avenues to develop better diagnostic and prognostic approaches as well as therapeutic trials.