Vitamin D3 levels in women and factors contributing to explain metabolic variations.

The elucidated metabolism of vitamin D3 in humans has been the support to explain the high involvement of this liposoluble vitamin in physiological functions. Clinical studies have associated levels of vitamin D3 metabolites with several disorders. Despite this knowledge, there is a controversy regarding the estimation of deficiency and the physiological and supraphysiological levels of vitamin D3 metabolites. The association between serum concentrations of vitamin D3 metabolites and several potentially influential factors (namely, age and anthropometric, seasonal, spatial and metabolic factors) is analyzed in this study. For this purpose, 558 women were recruited and interviewed in several Spanish provinces before blood sampling. Serum vitamin D3 and its metabolites were determined using an SPE-LC-MS/MS platform. The concentration range for vitamin D3 was 1.7-21.1 nmol/L and was influenced by body mass index (BMI), waist-to-hip ratio (WHR) and seasonal period. 25-hydroxyvitamin D3 levels were within 4.8-147.2 nmol/L and were related to WHR, season, latitude and calcium intake. The range of 24,25-dihydroxyvitamin D3, 0.3-15.0 nmol/L, was associated to BMI, WHR, season, latitude and calcium intake. Finally, energy intake influenced the vitamin D 25-hydroxylase through the 25-hydroxyvitamin D3/vitamin D3 ratio, which regulates the synthesis of the circulating form. According to these results, it is worth emphasizing the relevance of all these factors to explain the variability in serum levels of vitamin D3 and its metabolites. All these factors should be considered in future studies assessing the alteration of vitamin D3 metabolism.

Lipidomics: An omics discipline with a key role in nutrition.

The importance of lipidomics to unveil crucial aspects in the nutrition field is afforded in this article. With this aim, historical facts such as demonization of fats, enthronization of carbohydrates, and subsequent changes in the food pyramid are first discussed. After considering basic and analytical aspects of lipidomics and the upstream information this omics provides, its key role in personalized nutrition (PN), and the importance of lipids as nutrition biomarkers are critically discussed by appropriate examples. Pendent challenges to clarify the role of lipidomics in nutrition are overcome limiting factors, design of new lipidomics-based biomarkers, unveil mechanisms involved in lipidomics processes, and integrate lipidomics with other omics for a more complete and validated information useful in PN. The conclusions of this study also include the scant role of analytical chemists in the lipidomics-nutrition binomial, basically supported on analytical data.

Dry sweat as sample for metabolomics analysis.

Sweat is gaining popularity in clinical metabolomics as this biofluid is non-invasively sampled and its composition is modified by several pathologies. There is a lack of standardized strategies for collection of human sweat. Most studies have been carried out with fresh sweat collected after stimulation. A promising and simple alternative is sampling dry sweat by a solid support impregnated with a suited solvent. This research was aimed at comparing the metabolomics coverage provided by dry sweat collected by two solid supports (gauzes and filter papers) impregnated with different solvents. The dissolved dry sweat was analyzed by a dual approach: gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-tandem mass spectrometry (LC-MS/MS). Among the tested sampling strategies, filter paper impregnated with 1:1 (v/v) ethanol‒phosphate buffer resulted the combination providing the highest metabolomics coverage (tentative identification of one hundred seventy-five compounds). Dry and fresh sweat were compared by using pools from the same individuals to evaluate compositional differences. Families of metabolites such as carnitines, sphingolipids and N-acyl-amino acids, among others, were exclusively identified in dry sweat. Comparison of both samples allowed concluding that dry sweat is better for analysis of low polar metabolites and fresh sweat is more suited for polar compounds. As most of the identified metabolites are involved in key biochemical pathways, this study opens interesting possibilities to the use of dry sweat as a source of metabolite markers for specific disorders. Sampling of dry sweat could provide a standardized approach for collection of this biofluid, thus overcoming the variability limitations of fresh sweat.

Evaluation of short-term storage prior to analysis of vitamin D3 and metabolites in human serum by liquid chromatography coupled to tandem mass spectrometry.

Vitamin D has been widely determined in clinical trials to elucidate its biochemical involvement in a great number of pathologies. The analysis of vitamin D and its hydroxymetabolites in biofluids such as serum or plasma is a challenging task due to limitations associated to the low concentrations of some metabolites (typically, dihydroxymetabolites), methodological interferences, and the low stability of the compounds. Among these limitations, efforts have been targeted at optimizing instrumental improvements to develop more sensitive and selective methods, while the stability of vitamin D and metabolites has not been exhaustively evaluated. In this research, several aspects regarding the short-term storage conditions of human serum have been studied to evaluate their influence on the determination of vitamin D3 and metabolites. An experimental plan has been applied to assess the influence of two relevant parameters: the storage temperature for a period of two months and the number of freeze-thaw cycles. The storage temperature affected in a different manner to vitamin D3 and its metabolites, being vitamin D3 and 1,25-dihydroxyvitamin D3 the two analytes more affected by this parameter. Concerning the freeze-thaw cycles, this variable must be limited to two cycles owing to its significant influence on the variability for quantitation of dihydroxymetabolites in human serum. Finally, lyophilization was also tested to check if serum concentrations of vitamin D3 and its metabolites were affected by this preprocessing step. The results revealed that only vitamin D3 experienced a decrease in serum concentration after two months, which does not constitute a real problem as vitamin D3 is not currently a crucial parameter to be determined in clinical trials due to its scant biological activity.

Determination of primary fatty acid amides in different biological fluids by LC-MS/MS in MRM mode with synthetic deuterated standards: Influence of biofluid matrix on sample preparation.

The recent growing interest in primary fatty acid amides (PFAMs) is due to the broad range of physiological effects they exhibit as bioindicator of pathological states. These bioactive lipids are usually in biological samples at the nanomolar level, making their detection and identification a challenging task. A method for quantitative analysis of seven main PFAMs (lauramide, myristamide, linoleamide, palmitamide, oleamide, stearamide and behenamide) in four human biofluids -namely, urine, plasma, saliva and sweat- is here reported. Two sample preparation procedures were compared to test their efficiency in each biofluid: solid-phase extraction (SPE) and protein precipitation. The latter was the best for plasma and urine, while the analysis of saliva and sweat required an SPE step for subsequent suited determination of PFAMs. Detection of the seven metabolites was performed by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) in multiple reaction monitoring (MRM) mode. Quantitative analysis was supported on the use of stable isotopically labeled internal standards (SIL-ISs) in the calibration method, which required the synthesis of each IS from the precursor deuterated fatty acids. Detection limits for the target analytes were within 0.3-3 ng mL-1. The method was applied to a small cohort of male and female volunteers (n = 6) to estimate the relative concentration profiles in the different biofluids. The analytical features of the method supported its applicability in clinical studies aimed at elucidating the role of PFAMs metabolism.

Study of sample preparation for determination of endocannabinoids and analogous compounds in human serum by LC-MS/MS in MRM mode.

Endocannabinoids are lipids with a key role in physiological processes such as the immune response or the metabolism. This involvement explains their association to pathologies such as cancer, obesity or multiple sclerosis. The determination of endocannabinoids constitutes a challenge for clinical laboratories due to the variety of biological matrices and the wide range of concentrations at which they can be found. This research deals with the comparison of three sample preparation strategies (viz., on-line SPE, off-line SPE for interferents removal, and protein precipitation) for subsequent LC-MS/MS analysis of 14 endocannabinoids and analogous compounds in serum. As a result, the on-line coupling between SPE and LC-MS/MS is proposed as the best approach for this determination. The proposed method allows full automation of the overall process, shortening of the analysis time, and avoidance of errors associated with sample preparation steps. The improvement in sensitivity and selectivity thus achieved allows obtaining quantification limits at the pg mL-1 level, which makes possible the application of the method for clinical studies.

Metabolomics analysis of human sweat collected after moderate exercise.

Sweat is a promising biofluid scarcely used in clinical analysis despite its non-invasive sampling. A more frequent clinical use of sweat requires to know its whole composition, especially concerning to non-polar compounds, and the development of analytical strategies for its characterization. The aim of the present study was to compare different sample preparation strategies to maximize the detection of metabolites in sweat from humans collected after practicing moderate exercise. Special emphasis was put on non-polar compounds as they have received scant attention in previous studies dealing with this biofluid. Sample preparation by liquid-liquid extraction (LLE) using extractants with different polarity index was compared to deproteination. Then, derivatization by methoxymation with subsequent silylation was compared to direct analysis of sweat extracts to check the influence of derivatization on the subsequent determination of volatile organic compounds (VOCs). 135 compounds were tentatively identified by combining spectral and retention time information after analysis by gas chromatography coupled to mass spectrometry in high resolution mode (GC-TOF/MS). Lipids, VOCs, benzenoids and other interesting metabolites such as alkaloids and ethanolamines were identified. Among the tested protocols, methyoxiamination plus silylation after LLE with dichloromethane was the best option to obtain a representative snapshot of sweat metabolome collected from different body parts after moderate exercise. Passive and active sweat pools from a cohort of volunteers (n = 6) were compared to detect compositional differences which can be explained by the sampling process and sweating induction. As most of the identified compounds are metabolites involved in key biochemical pathways, this study opens new opportunities to extend the applicability of human sweat as a source of metabolite biomarkers of pathologies or specific processes such as dehydration or nutritional unbalance.

The analytical process to search for metabolomics biomarkers.

The scant number of available metabolomics biomarkers does not reflect the extent of the research in this field. Looking for the reasons of failure, the authors, as analytical chemists, critically discuss each of the steps in the analytical process that requires improvements. They find insufficient information about how the experimental part is developed. After revising the steps from sampling to obtainment of the analytical sample (from typical samples such as blood and urine to others less common such as sweat or saliva), the need for data and metadata for either reproduction of a given study or for taking the study as starting point after biomarker discovery is criticized. The separation and analysis steps are also revised as does data treatment. After the sources of errors from the analytical process are overcome, subsequent steps in the implementation of biomarkers to reach the final aim of clinical adoption should be supported as required.

Changes in the composition of the polar fraction of Persian lime (Citrus latifolia) during fruit growth by LC-QTOF MS/MS analysis.

Citrus possess a large number of bioactive compounds mainly studied in ripe fruits. Few studies have focused on evolution of metabolites during fruit growth. In this study, fruits were sampled from weeks 1-14 of the ripening process. Polar extracts were obtained from all collected samples and analysed by liquid chromatography-tandem mass spectrometry. Analysis of variance applied to the dataset indicated that the relative concentration of 394 out of 423 molecular entities changed significantly during maturation. Principal component analysis showed a clear separation among samples from different weeks and revealed the main compounds responsible for differentiation. Additionally, 72 metabolites were tentatively identified and changes in their relative concentration during growth were individually analysed. The observed trends in relative concentrations of representative metabolites during the growth process are discussed.

Exhaled breath condensate to discriminate individuals with different smoking habits by GC-TOF/MS.

Smoking is a crucial factor in respiratory diseases and lung inflammation, which are the reasons for high mortality worldwide. Despite the negative impact that tobacco consumption causes on health, few metabolomics studies have compared the composition of biofluids from smoker and non-smoker individuals. Exhaled breath condensate (EBC) is one of the biofluids less employed for clinical studies despite its non-invasive sampling and the foreseeable relationship between its composition and respiratory diseases. EBC was used in this research as clinical sample to compare three groups of individuals: current smokers (CS), former smokers (FS) and never smokers (NS). Special attention was paid to the cumulative consumption expressed as smoked pack-year. The levels of 12 metabolites found statistically significant among the three groups of individuals were discussed to find an explanation to their altered levels. Significant compounds included monoacylglycerol derivatives, terpenes and other compounds, the presence of which could be associated to the influence of smoking on the qualitative and quantitative composition of the microbiome.

An overview on forensic analysis devoted to analytical chemists.

The present article has as main aim to show analytical chemists interested in forensic analysis the world they will face if decision in favor of being a forensic analytical chemist is adopted. With this purpose, the most outstanding aspects of forensic analysis in dealing with sampling (involving both bodily and no bodily samples), sample preparation, and analytical equipment used in detection, identification and quantitation of key sample components are critically discussed. The role of the great omics in forensic analysis, and the growing role of the youngest of the great omics -metabolomics- are also discussed. The foreseeable role of integrative omics is also outlined.

Characterization of Stevia leaves by LC-QTOF MS/MS analysis of polar and non-polar extracts.

Stevia is currently a well-known plant thanks to its sweeting power. Numerous studies that elucidate its composition were exclusively focused on determination of steviol and its glycosides. Untargeted analysis was applied to obtain a profile of main compounds present in extracts from Stevia (Stevia rebaudiana Bertoni) leaves using LC-MS in high resolution mode with a quadrupole-time of flight analyzer. Eighty-nine compounds were tentatively identified and classified into different families: flavonoids; quinic and caffeic acids and derivatives; diterpenoids (including steviol and glycosides); sesquiterpenoids; amino acids and derivatives; fatty amides and derivatives; fatty acids and derivatives; oligosaccharides; glycerolipids; purines; and retinoids. New steviol glycosides were tentatively identified and their possible structures proposed. Other compounds were tentatively identified in Stevia for the first time, such as fatty acid amides. These results reveal the wide range of compounds present in Stevia, which could be responsible for the nutraceutical effects ascribed to their leaves.

Prostate Cancer Patients-Negative Biopsy Controls Discrimination by Untargeted Metabolomics Analysis of Urine by LC-QTOF: Upstream Information on Other Omics.

The existing clinical biomarkers for prostate cancer (PCa) diagnosis are far from ideal (e.g., the prostate specific antigen (PSA) serum level suffers from lack of specificity, providing frequent false positives leading to over-diagnosis). A key step in the search for minimum invasive tests to complement or replace PSA should be supported on the changes experienced by the biochemical pathways in PCa patients as compared to negative biopsy control individuals. In this research a comprehensive global analysis by LC-QTOF was applied to urine from 62 patients with a clinically significant PCa and 42 healthy individuals, both groups confirmed by biopsy. An unpaired t-test (p-value < 0.05) provided 28 significant metabolites tentatively identified in urine, used to develop a partial least squares discriminant analysis (PLS-DA) model characterized by 88.4 and 92.9% of sensitivity and specificity, respectively. Among the 28 significant metabolites 27 were present at lower concentrations in PCa patients than in control individuals, while only one reported higher concentrations in PCa patients. The connection among the biochemical pathways in which they are involved (DNA methylation, epigenetic marks on histones and RNA cap methylation) could explain the concentration changes with PCa and supports, once again, the role of metabolomics in upstream processes.

Present and foreseeable future of metabolomics in forensic analysis.

The revulsive publications during the last years on the precariousness of forensic sciences worldwide have promoted the move of major steps towards improvement of this science. One of the steps (viz. a higher involvement of metabolomics in the new era of forensic analysis) deserves to be discussed under different angles. Thus, the characteristics of metabolomics that make it a useful tool in forensic analysis, the aspects in which this omics is so far implicit, but not mentioned in forensic analyses, and how typical forensic parameters such as the post-mortem interval or fingerprints take benefits from metabolomics are critically discussed in this review. The way in which the metabolomics-forensic binomial succeeds when either conventional or less frequent samples are used is highlighted here. Finally, the pillars that should support future developments involving metabolomics and forensic analysis, and the research required for a fruitful in-depth involvement of metabolomics in forensic analysis are critically discussed.

Two-dimensional liquid chromatography coupled to tandem mass spectrometry for vitamin D metabolite profiling including the C3-epimer-25-monohydroxyvitamin D3.

A method based on automated on-line solid phase extraction coupled to two-dimensional liquid chromatography with tandem mass spectrometry detection (SPE-2DLC-MS/MS) is here reported for vitamin D metabolite profiling in human serum with absolute quantitation. Two-dimensional LC was configured with two complementary analytical columns, pentafluorophenyl (PFP) and C18 phases, for determination of 25 hydroxyvitamin D3 epimers and the resting bioactive metabolites of vitamin D (D3 and D2)-25-hydroxyvitamin D2, 1,25-dihydroxyvitamin D3, 1,25-dihydroxyvitamin D2 and 24,25-dihydroxyvitamin D3. Quantitative determination was supported on the use of a stable isotopic labelled internal standard for each analyte and the resulting method was validated by analysis of a standard reference material certified by the National Institute of Standards & Technology (NIST-972a) and 5 samples provided by the vitamin D External Quality Assurance Scheme (DEQAS). The limits of detection were between 9 and 90pg/mL for the eight analytes, and precision, expressed as relative standard deviation, was lower than 11.6%. Two-dimensional LC has shown to be the key to discriminate between 25 hydroxyvitamin D3 epimers in a quantitative analysis also involving dihydroxyvitamin D metabolites.

Development and application of a quantitative method based on LC-QqQ MS/MS for determination of steviol glycosides in Stevia leaves.

Stevia is a currently well-known plant thanks to the presence of steviol glycosides, which are considered as sweeteners obtained from a natural source. In this research, a method based on LC-MS/MS by using a triple quadrupole detector was developed for quantitation of 8 steviol glycosides in extracts from Stevia leaves. The ionization and fragmentation parameters for selected reaction monitoring were optimized. Detection and quantitation limits ranging from 0.1 to 0.5ng/mL and from 0.5 to 1ng/mL, respectively, were achieved: the lowest attained so far. The steviol glycosides were quantified in extracts from leaves of seven varieties of Stevia cultivated in laboratory, greenhouse and field. Plants cultivated in field presented higher concentration of steviol glycosides than those cultivated in greenhouse. Thus, the way of cultivation clearly influences the concentration of these compounds. The inclusion of branches together with leaves as raw material was also evaluated, showing that this inclusion modifies, either positively or negatively, the concentration of steviol glycosides.

Identification of metabolomics panels for potential lung cancer screening by analysis of exhaled breath condensate.

Exhaled breath condensate (EBC) is one of the less employed biofluids when searching for clinical markers, despite its non-invasive sampling and the potential relationship between its composition and respiratory disease phenotypes such as lung cancer. The advanced stage at which lung cancer is usually detected is the main reason for the high mortality rate of this carcinogenic disease. In this preliminary research, EBC was used as clinical sample to develop a screening tool for lung cancer discrimination from two control groups (with and without risk factor). Three panels of metabolites were configured using the PanelomiX tool to minimize false negatives (specificity) and false positives (sensitivity). The combination of five metabolites led to three panels providing a sensitivity above 77.9%, specificity above 67.5% and the area under the curve (AUC) above 77.5% for the three panels. An additional study was developed as a first approach to study the statistical significance of metabolites at different stages of lung cancer.

Metabolomics analysis of exhaled breath condensate for discrimination between lung cancer patients and risk factor individuals.

The search for new clinical tests aimed at diagnosing chronic respiratory diseases is a current research line motivated by the lack of efficient screening tools and the severity of some of these pathologies. Alternative biological samples can open the door to new screening tools. A promising biofluid that is rarely used for diagnostic purposes is exhaled breath condensate (EBC), the composition of which has been inadequately studied. In this research, untargeted analysis of EBC using gas chromatography time-of-flight mass spectrometry has been applied to a cohort of patients with lung cancer (n = 48), risk factor individuals (active smokers and ex-smokers, n = 130) and control healthy individuals (non-smokers without respiratory diseases, n = 61). An identical protocol was applied to the two EBC fractions provided by the sampling device (upper and central airways and distal airway) from each individual, which allowed the compositional differences between the two EBC fractions to be detected. Tentative compounds that contribute to discrimination between the three groups were identified, and a relevant role for lipids such as monoacylglycerols and squalene was found. These results could support the ability of metabolomics to go inside the study of lung cancer.

Influence of the collection tube on metabolomic changes in serum and plasma.

Major threats in metabolomics clinical research are biases in sampling and preparation of biological samples. Bias in sample collection is a frequently forgotten aspect responsible for uncontrolled errors in metabolomics analysis. There is a great diversity of blood collection tubes for sampling serum or plasma, which are widely used in metabolomics analysis. Most of the existing studies dealing with the influence of blood collection on metabolomics analysis have been restricted to comparison between plasma and serum. However, polymeric gel tubes, which are frequently proposed to accelerate the separation of serum and plasma, have not been studied. In the present research, samples of serum or plasma collected in polymeric gel tubes were compared with those taken in conventional tubes from a metabolomics perspective using an untargeted GC-TOF/MS approach. The main differences between serum and plasma collected in conventional tubes affected to critical pathways such as the citric acid cycle, metabolism of amino acids, fructose and mannose metabolism and that of glycerolipids, and pentose and glucuronate interconversion. On the other hand, the polymeric gel only promoted differences at the metabolite level in serum since no critical differences were observed between plasma collected with EDTA tubes and polymeric gel tubes. Thus, the main changes were attributable to serum collected in gel and affected to the metabolism of amino acids such as alanine, proline and threonine, the glycerolipids metabolism, and two primary metabolites such as aconitic acid and lactic acid. Therefore, these metabolite changes should be taken into account in planning an experimental protocol for metabolomics analysis.

Development of a method for enhancing metabolomics coverage of human sweat by gas chromatography-mass spectrometry in high resolution mode.

Sweat has recently gained popularity as clinical sample in metabolomics analysis as it is a non-invasive biofluid the composition of which could be modified by certain pathologies, as is the case with cystic fibrosis that increases chloride levels in sweat. However, the whole composition of sweat is still unknown and there is a lack of analytical strategies for sweat analysis. The aim of the present study was to develop and validate a method for metabolomic analysis of human sweat by gas chromatography-time of flight/mass spectrometry (GC-TOF/MS) in high resolution mode. Thus, different sample preparation strategies were compared to check their effect on the profile of sweat metabolites. Sixty-six compounds were tentatively identified by the obtained MS information. Amino acids, dicarboxylic acids and other interesting metabolites such as myo-inositol and urocanic acid were identified. Among the tested protocols, methyoxiamination plus silylation after deproteinization was the most suited option to obtain a representative snapshot of sweat metabolome. The intra-day repeatability of the method ranged from 0.60 to 16.99% and the inter-day repeatability from 2.75 to 31.25%. As most of the identified metabolites are involved in key biochemical pathways, this study opens new possibilities to the use of sweat as a source of metabolite biomarkers of specific disorders.