Preparation of urine samples prior to targeted or untargeted metabolomics mass-spectrometry analysis

Evaluation of polypropylene microporous membranes as extraction devices for determination of carcinogenic aromatic amines in smoker urine by GC-MS/MS

Exposure to tobacco smoke is highly correlated to the incidence of different types of cancer due to various carcinogenic compounds present in such smoke. Aromatic amines, such as 1-naphthylamine (1-NA) and 2-naphthylamine (2-NA), are produced in tobacco burning and are linked to bladder cancer. Miniaturized solid phase extraction techniques, such as microporous membrane solid phase extraction (MMSPE), have shown potential for the extraction of aromatic compounds. In this study, a bioanalytical method for the determination of 1-NA and 2-NA in human urine was developed using polypropylene microporous membranes as a sorptive phase for MMSPE. Urine samples were hydrolyzed with HCl for 1 h at 80 °C, after which pH was adjusted to 10. Ultrasound-assisted MMSPE procedure was optimized by factorial design as follows. To each sample, 750 µL of methanol was added, and ultrasound-assisted MMSPE was conducted for 1 h with four devices containing seven 2 mm polypropylene membrane segments. After extraction, the segments were transferred to 400 µL of hexane, and desorption was conducted for 30 min. Extracts were submitted to a simple and fast microwave-assisted derivatization procedure, by the addition of 10 µL of PFPA and heating at 480 W for 3 min, followed by clean-up with phosphate buffer pH 8.0 and GC-MS/MS analysis. Adequate linearity was obtained for both analytes in a range from 25 to 500 µg L-1, while the multiple reaction monitoring approach provided satisfactory selectivity and specificity. Intra-day (n = 6) and inter-day (n = 5) precision and accuracy were satisfactory, below 15 % and between 85 and 115 %, respectively. Recovery rates found were 91.9 and 58.4 % for 1-NA and 2-NA, respectively, with adequate precision. 1-NA was found in first-hand smokers' urine samples in a concentration range from 20.98 to 89.09 µg in 24 h, while it could be detected in second-hand smoker's urine samples, and 2-NA detected in all first and second-hand smokers' urine samples. The proposed method expands the applicability of low cost MMSPE devices to aromatic amines and biological fluids.

Impact of four different extraction methods and three different reconstitution solvents on the untargeted metabolomics analysis of human and rat urine samples

Unsuitable sample preparation may result in loss of important analytes and consequently affect the outcome of untargeted metabolomics. Due to species differences, different sample preparations may be required within the same biological matrix. The study aimed to compare the in-house sample preparation method for urine with methods from literature and to investigate the transferability of sample preparation from human urine to rat urine. A total of 12 different conditions for protein precipitation were tested, combining four different extraction solvents and three different reconstitution solvents using an untargeted liquid-chromatography high resolution mass spectrometry (LC-HRMS) metabolomics analysis. Evaluation was done based on the impact on feature count, their detectability, as well as the reproducibility of selected compounds. Results showed that a combination of methanol as extraction and acetonitrile/water (75/25) as reconstitution solvent provided improved results at least regarding the total feature count. Additionally, it was found that a higher amount of methanol was most suitable for extraction of rat urine among the tested conditions. In comparison, human urine requires significantly less volume of extraction solvent. Overall, it is recommended to systematically optimize both, the extraction method, and the reconstitution solvent for the used biofluid and the individual analytical settings.

Urinary Metabolomic Differentiation of Infants Fed on Human Breastmilk and Formulated Milk

Human breastmilk is an invaluable nutritional and pharmacological resource with a highly diverse metabolite profile, which can directly affect the metabolism of infants. Application of metabolomics can discriminate the complex relationship between such nutrients and infant health. As the most common biological fluid in metabolomic study, infant urinary metabolomics may provide the physiological impacts of different nutritional resources, namely human breastmilk and formulated milk. In this study, we aimed to identify possible differences in the urine metabolome of 30 infants (1-14 days after birth) fed with breast milk (n = 15) or formulated milk (n = 15). From metabolomic analysis with gas chromatography-mass spectrometry, 163 metabolites from single mass spectrometry (GC-MS), and 383 metabolites from tandem mass spectrometry (GC-MS/MS) were confirmed in urinary samples. Various multivariate statistical analysis were performed to discriminate the differences originating from physiological/nutritional variables, including human breastmilk/formulate milk feeding, sex, and duration of feeding. Both unsupervised and supervised discriminant analyses indicated that feeding resources (human breastmilk/formulated milk) gave marginal but significant differences in urinary metabolomes, while other factors (sex, duration of feeding) did not show notable discrimination between groups. According to the biomarker analyses, several organic acid and amino acids showed statistically significant differences between different feeding resources, such as 2-hydroxyhippurate.

Predicting lameness in dairy cattle using untargeted liquid chromatography-mass spectrometry-based metabolomics and machine learning

Lameness in dairy cattle is a highly prevalent condition that impacts on the health and welfare of dairy cows. Prompt detection and implementation of effective treatment is important for managing lameness. However, major limitations are associated with visual assessment of lameness, which is the most commonly used method to detect lameness. The aims of this study were to investigate the use of metabolomics and machine learning to develop novel methods to detect lameness. Untargeted metabolomics using liquid chromatography-mass spectrometry (LC-MS) alongside machine learning models and a stability selection method were utilized to evaluate the predictive accuracy of differences in the metabolomics profile of first-lactation dairy cows before (during the transition period) and at the time of lameness (based on visual assessment using the 0-3 scale of the Agriculture and Horticulture Development Board). Urine samples were collected from 2 cohorts of dairy heifers and stored at -86°C before analysis using LC-MS. Cohort 1 (n = 90) cows were recruited as current first-lactation cows with weekly mobility scores recorded over a 4-mo timeframe, from which newly lame and nonlame cows were identified. Cohort 2 (n = 30) cows were recruited within 3 wk before calving, and lameness events (based on mobility score) were recorded through lactation until a minimum of 70 d in milk (DIM). All cows were matched paired by DIM ± 14 d. The median DIM at lameness identification was 187.5 and 28.5 for cohort 1 and 2, respectively. The best performing machine learning models predicted lameness at the time of lameness with an accuracy of between 81 and 82%. Using stability selection, the prediction accuracy at the time of lameness was 80 to 81%. For samples collected before and after calving, the best performing machine learning model predicted lameness with an accuracy of 71 and 75%, respectively. The findings from this study demonstrate that untargeted LC-MS profiling combined with machine learning methods can be used to predict lameness as early as before calving and before observable changes in gait in first-lactation dairy cows. The methods also provide accuracies for detecting lameness at the time of observable changes in gait of up to 82%. The findings demonstrate that these methods could provide substantial advancements in the early prediction and prevention of lameness risk. Further external validation work is required to confirm these findings are generalizable; however, this study provides the basis from which future work can be conducted.

Recent molecularly imprinted polymers applications in bioanalysis

Molecular imprinted polymers (MIPs) as extraordinary compounds with unique features have presented a wide range of applications and benefits to researchers. In particular when used as a sorbent in sample preparation methods for the analysis of biological samples and complex matrices. Its application in the extraction of medicinal species has attracted much attention and a growing interest. This review focus on articles and research that deals with the application of MIPs in the analysis of components such as biomarkers, drugs, hormones, blockers and inhibitors, especially in biological matrices. The studies based on MIP applications in bioanalysis and the deployment of MIPs in high-throughput settings and optimization of extraction methods are presented. A review of more than 200 articles and research works clearly shows that the superiority of MIP techniques lies in high accuracy, reproducibility, sensitivity, speed and cost effectiveness which make them suitable for clinical usage. Furthermore, this review present MIP-based extraction techniques and MIP-biosensors which are categorized on their classes based on common properties of target components. Extraction methods, studied sample matrices, target analytes, analytical techniques and their results for each study are described. Investigations indicate satisfactory results using MIP-based bioanalysis. According to the increasing number of studies on method development over the last decade, the use of MIPs in bioanalysis is growing and will further expand the scope of MIP applications for less studied samples and analytes.

Size characterization of nanomaterials in environmental and biological matrices through non-electron microscopic techniques

Engineered nanomaterials (ENs) can enter the environment, and accumulate in food chains, thereby causing environmental and health problems. Size characterization of ENs is critical for further evaluating the interactions among ENs in biological and ecological systems. Although electron microscope is a powerful tool in obtaining the size information, it has limitations when studying nanomaterials in complex matrices. In this review, we summarized non-electron microscope-based techniques, including chromatography-based, mass spectrometry-based, synchrotron radiation- and neutron-based techniques for detecting the size of ENs in environmental and biological matrices. The advantages and disadvantages of these techniques were highlighted. The perspectives on size characterization of ENs in complex matrices were also presented.

Prostanoid Metabolites as Biomarkers in Human Disease

Prostaglandins (PGD₂, PGE₂, PGF_2α), prostacyclin (PGI₂), and thromboxane A₂ (TXA₂) together form the prostanoid family of lipid mediators. As autacoids, these five primary prostanoids propagate intercellular signals and are involved in many physiological processes. Furthermore, alterations in their biosynthesis accompany a wide range of pathological conditions, which leads to substantially increased local levels during disease. Primary prostanoids are chemically instable and rapidly metabolized. Their metabolites are more stable, integrate the local production on a systemic level, and their analysis in various biological matrices yields valuable information under different pathological settings. Therefore, prostanoid metabolites may be used as diagnostic, predictive, or prognostic biomarkers in human disease. Although their potential as biomarkers is great and extensive research has identified major prostanoid metabolites that serve as target analytes in different biofluids, the number of studies that correlate prostanoid metabolite levels to disease outcome is still limited. We review the metabolism of primary prostanoids in humans, summarize the levels of prostanoid metabolites in healthy subjects, and highlight existing biomarker studies. Since analysis of prostanoid metabolites is challenging because of ongoing metabolism and limited half-lives, an emphasis of this review lies on the reliable measurement and interpretation of obtained levels.

From target analysis to suspect and non-target screening of endocrine-disrupting compounds in human urine

In the present work, a target analysis method for simultaneously determining 24 diverse endocrine-disrupting compounds (EDCs) in urine (benzophenones, bisphenols, parabens, phthalates and antibacterials) was developed. The target analysis approach (including enzymatic hydrolysis, clean-up by solid-phase extraction and analysis by liquid chromatography coupled to tandem mass spectrometry (LC–MS/MS)) was optimized, validated and applied to volunteers’ samples, in which 67% of the target EDCs were quantified. For instance, benzophenone-3 (0.2–13 ng g⁻¹), bisphenol A (7.7–13.7 ng g⁻¹), methyl 3,5-dihydroxybenzoate (8–254 ng g⁻¹), mono butyl phthalate (2–17 ng g⁻¹) and triclosan (0.3–9 ng g⁻¹) were found at the highest concentrations, but the presence of other analogues was detected as well. The developed target method was further extended to suspect and non-target screening (SNTS) by means of LC coupled to high-resolution MS/MS. First, well-defined workflows for SNTS were validated by applying the previously developed method to an extended list of compounds (83), and then, to the same real urine samples. From a list of approximately 4000 suspects, 33 were annotated at levels from 1 to 3, with food additives/ingredients and personal care products being the most abundant ones. In the non-target approach, the search was limited to molecules containing S, Cl and/or Br atoms, annotating 4 pharmaceuticals. The results from this study showed that the combination of the lower limits of detection of MS/MS and the identification power of high-resolution MS/MS is still compulsory for a more accurate definition of human exposome in urine samples.

Selection of appropriate biomatrices for studies of chronic stress in animals: a review

Cortisol and corticosterone, hormones traditionally considered biomarkers of stress, can be measured in fluid biomatrices (e.g., blood, saliva) from live animals to evaluate conditions at sampling time, or in solid biomatrices (e.g., hair, feather) from live or dead animals to obtain information regarding long-term changes. Using these biomarkers to evaluate physiological stress responses in domestic animals may be challenging due to the diverse characteristics of biomatrices for potential measurement. Ideally, a single measurement from the biomatrix should be sufficient for evaluating chronic stress. The availability of appropriate and cost-effective immunoassay methods for detecting the biomarkers should also be considered. This review discusses the strengths and limitations of different biomatrices with regard to ensuring the highest possible reliability for chronic stress evaluation. Overall, solid biomatrices require less frequent sampling than other biomatrices, resulting in greater time- and cost-effectiveness, greater ease of use, and fewer errors. The multiplex immunoassay can be used to analyze interactions and correlations between cortisol and other stress biomarkers in the same biomatrix. In light of the lack of information regarding appropriate biomatrices for measuring chronic stress, this review may help investigators set experimental conditions or design biological research.

High-Coverage Quantitative Metabolomics of Human Urine: Effects of Freeze-Thaw Cycles on the Urine Metabolome and Biomarker Discovery

Urine sample storage after collection at ultra-low-temperature (e.g., -80 °C) is normally required for comparative metabolome analysis of many samples, and therefore, freeze-thaw cycles (FTCs) are unavoidable. However, the reported effects of FTCs on the urine metabolome are controversial. Moreover, there is no report on the study of how urine FTCs affect biomarker discovery. Herein, we present our study of the FTC effects on the urine metabolome and biomarker discovery using a high-coverage quantitative metabolomics platform. Our study involved two centers located in Hangzhou, China, and Edmonton, Canada, to perform metabolome analysis of two separate cohorts of urine samples. The same workflow of sample preparation and dansylation isotope labeling LC-MS was used for in-depth analysis of the amine/phenol submetabolome. The analysis of 320 samples from the Hangzhou cohort consisting of 80 healthy subjects with each urine being subjected to four FTCs resulted in relative quantification of 3682 metabolites with 3307 identified or mass-matched. The analysis of 176 samples from the Edmonton cohort of 44 subjects with four FTCs quantified 3516 metabolites with 3166 identified or mass-matched. Multivariate and univariate analyses indicated that significant variations (fold change ≥ 1.5 with q-value ≤ 0.05) from FTCs were only observed in a very small fraction of the metabolites (<0.3%). Moreover, various metabolites did not show a consistent pattern of concentration changes from one to four FTCs, allowing the use of two separate cohorts of samples to remove these randomly changed metabolites. Three metabolite biomarkers for separating males and females were discovered, and FTC did not influence their discovery.

Development and Application of an LC-MS/MS Untargeted Exposomics Method with a Separated Pooled Quality Control Strategy

Pooled quality controls (QCs) are usually implemented within untargeted methods to improve the quality of datasets by removing features either not detected or not reproducible. However, this approach can be limiting in exposomics studies conducted on groups of exposed and nonexposed subjects, as compounds present at low levels only in exposed subjects can be diluted and thus not detected in the pooled QC. The aim of this work is to develop and apply an untargeted workflow for human biomonitoring in urine samples, implementing a novel separated approach for preparing pooled quality controls. An LC-MS/MS workflow was developed and applied to a case study of smoking and non-smoking subjects. Three different pooled quality controls were prepared: mixing an aliquot from every sample (QC-T), only from non-smokers (QC-NS), and only from smokers (QC-S). The feature tables were filtered using QC-T (T-feature list), QC-S, and QC-NS, separately. The last two feature lists were merged (SNS-feature list). A higher number of features was obtained with the SNS-feature list than the T-feature list, resulting in identification of a higher number of biologically significant compounds. The separated pooled QC strategy implemented can improve the nontargeted human biomonitoring for groups of exposed and nonexposed subjects.

Urinary metabolomics reveals the biological characteristics of early pregnancy in pigs

Background

Embryo implantation in sows is an important event during pregnancy. During this process, blastocysts undergo dramatic morphologic changes, and the endometrium becomes receptive. Studies have shown that developmental changes associated with the crosstalk between peri-implantation embryos and embryo-uterine are driven by various biomolecules secreted by the endometrium and embryos. In sows, changes in the uterus are also reflected in circulating body fluids and urine. Metabolomics reveals the metabolic state of cells, tissues, and organisms. In this study, we collected urine samples from large white sows during the peri-implantation period. The levels of urinary metabolites at different periods were analyzed using ultra-performance liquid chromatography/tandem mass spectrometry (UPLC–MS/MS) analysis techniques.

Results

A total of 32 samples were collected from 8 sows during the estrus period and at each phase of early pregnancy (9, 12, and 15 days of gestation). A total of 530 metabolites were identified with high confidence in all samples. Compared with samples collected during the estrus phase, 269 differential metabolites were found in samples obtained during early pregnancy.

Conclusions

The identified metabolites included lipids and lipid-like molecules, organic acids and their derivatives, organic oxygen compounds, organoheterocyclic compounds, benzenoids, among others. Metabolites, such as choline and pregnanediol-3-glucuronide, play important roles in pregnancy in sows and other animals. These results reveal the metabolic changes in urine of sows during early pregnancy phase. The differential urinary metabolites can be used for assessing peri-implantation status in sows. Understanding these metabolic changes may promote the management of pregnant sows through various interventions such as provision of proper nutrition.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40813-022-00256-z.

Current development of bioanalytical sample preparation techniques in pharmaceuticals

Sample preparation is considered as the bottleneck step in bioanalysis because each biological matrix has its own unique challenges and complexity. Competent sample preparation to extract the desired analytes and remove redundant components is a crucial step in each bioanalytical approach. The matrix effect is a key hurdle in bioanalytical sample preparation, which has gained extensive consideration. Novel sample preparation techniques have advantages over classical techniques in terms of accuracy, automation, ease of sample preparation, storage, and shipment and have become increasingly popular over the past decade. Our objective is to provide a broad outline of current developments in various bioanalytical sample preparation techniques in chromatographic and spectroscopic examinations. In addition, how these techniques have gained considerable attention over the past decade in bioanalytical research is mentioned with preferred examples. Modern trends in bioanalytical sample preparation techniques, including sorbent-based microextraction techniques, are primarily emphasized.

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Bioanalytical sampling techniques are described with suitable applications in pharmaceuticals.

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The pros and cons of each bioanalytical sampling techniques are described.

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Relevant biological matrices are outlined.

Sample preparation techniques for suspect and non-target screening of emerging contaminants

The progress in sensitivity and resolution in mass spectrometers in recent years provides the possibility to detect a broad range of organic compounds in a single procedure. For this reason, suspect and non-target screening techniques are gaining attention since they enable the detection of hundreds of known and unknown emerging contaminants in various matrices of environmental, food and human sources. Sample preparation is a critical step before analysis as it can significantly affect selectivity, sensitivity and reproducibility. The lack of generic sample preparation protocols is obvious in this fast-growing analytical field, and most studies use those of traditional targeted analysis methods. Among them, solvent extraction and solid phase extraction (SPE) are widely used to extract emerging contaminants from solid and liquid sample types, respectively. Sequential solvent extraction and a combination of different SPE sorbents can cover a broad range of chemicals in the samples. Gel permeation chromatography (GPC) and adsorption chromatography, including acidification, are typically used to remove matrix components such as lipids from complex matrices, but usually at the expense of compound losses. Ideally, the purification of samples intended for non-target analysis should be selective of matrix interferences. Recent studies have suggested quality assurance/quality control measures for suspect and non-target screening, based on expansion and extrapolation of target compound lists, but method validations remain challenging in the absence of analytical standards and harmonized sample preparation approaches.

Use of Poly(vinyl alcohol)-Malic Acid (CLHPMA) Hydrogels and Chitosan Coated Calcium Alginate (CCCA) Microparticles as Potential Sorbent Phases for the Extraction and Quantitative Determination of Pesticides from Aqueous Solutions

Pesticides are used worldwide to increase crop yields in agriculture. However, their toxicity and accumulation capacity can make them toxic to the environment, animals and humans. In the case of workers chronically exposed to these substances, they must be sampled continuously, so urine is an excellent option. In this sense, this study proposes to use poly(vinyl alcohol)-malic acid hydrogels, and chitosan-coated calcium alginate as new sorbent phases to be used in pesticide determination processes in urine. To better understand the behavior of these materials in the capture and desorption process, molecular dynamics simulations (MDS) were used, and desorption experiments were performed, using mechanical agitation, ultrasound, and pH variation in the desorption process, in order to optimize the parameters to obtain better recoveries. Under the optimal experimental conditions, the maximum recoveries were of the order of 11% (CFN), 3% (KCF), 53% (DMT), 18% (MTD) and 35% (MTL). Although the recoveries were not exhaustive, they are a first approximation for the use of these new sorbent phases in the determination of this type of compound in aqueous solutions and urine.

Spot urine collection: A valid alternative to total urine collection for metabolomic studies in dairy cattle

Urine is a highly suitable biological matrix for metabolomics studies. Total collection for 24-h periods is the gold standard as it ensures the presence of all metabolites excreted throughout the day. However, in animal studies, it presents limitations related to animal welfare and also due to alterations of the metabolome originating from the use of acid for preventing microbial growth or microbial contamination. In this study, we investigated whether spot urine collection is a practical alternative to total collection for metabolomic studies in lactating cows. For this purpose, we collected urine samples from 4 lactating Holstein cows fed 4 diets in a 4 × 4 Latin square design. Urine was collected for 24 h using a collecting device (i.e., total collection) or collected once per day 4 h after the morning feeding (i.e., spot urine collection). Dietary treatments differed by the amount of nitrogen content (high vs. low) and by the nature of the energy (starch vs. fiber). Urine metabolome was analyzed by 2 untargeted complementary methods, nuclear magnetic resonance and hydrophilic-interaction liquid chromatography (HILIC) coupled to a time-of-flight mass spectrometer, and by 1 targeted method, HILIC-tandem mass spectrometry. Although sampling technique had an effect on the abundance of metabolites detected, spot urine samples were equally capable of showing differences in urine metabolome than samples from total collection. When considering nitrogen levels in the diet, the robustness and precision for discriminating high- and low-nitrogen diets was equally achieved with both sampling techniques. A total of 22 discriminant metabolites associated with the N level of diets were identified from untargeted HILIC coupled to a time-of-flight mass spectrometer (n = 9) and nuclear magnetic resonance (n = 11), and 2 from targeted HILIC-tandem mass spectrometry. Alternatively, starch or fiber in the diet induced less changes in the metabolome that were not clearly discriminated independently of the sampling technique. We concluded that spot urine collection can successfully reveal differences in the urine metabolome elicited by dietary N levels and be used as a substitute of total urinary 24-h collection for metabolomic studies.

Current applications of capillary electrophoresis-mass spectrometry for the analysis of biologically important analytes in urine (2017 to mid-2021): A review

Capillary electrophoresis coupled online with mass detection is a modern tool for analyzing wide ranges of compounds in complex samples, including urine. Capillary electrophoresis with mass spectrometry allows the separation and identification of various analytes spanning from small ions to high molecular weight protein complexes. Similarly to the much more common liquid chromatography‐mass spectrometry techniques, the capillary electrophoresis separation reduces the complexity of the mixture of analytes entering the mass spectrometer resulting in reduced ion suppression and a more straightforward interpretation of the mass spectrometry data. This review summarizes capillary electrophoresis with mass spectrometry studies published between the years 2017 and 2021, aiming at the determination of various compounds excreted in urine. The properties of the urine, including its diagnostical and analytical features and chemical composition, are also discussed including general protocols for the urine sample preparation. The mechanism of the electrophoretic separation and the instrumentation for capillary electrophoresis with mass spectrometry coupling is also included. This review shows the potential of the capillary electrophoresis with mass spectrometry technique for the analyses of different kinds of analytes in a complex biological matrix. The discussed applications are divided into two main groups (capillary electrophoresis with mass spectrometry for the determination of drugs and drugs of abuse in urine and capillary electrophoresis with mass spectrometry for the studies of urinary metabolome).

METABOLOMICS REVEALS BIOMARKERS IN HUMAN URINE AND PLASMA TO PREDICT CYP2D6 ACTIVITY

Background and Purpose

Individualized assessment of cytochrome P450 2D6 (CYP2D6) activity is usually performed through phenotyping following administration of a probe drug to measure the enzyme's activity. To avoid any iatrogenic harm (allergic drug reaction, dosing error) related to the probe drug, the development of non‐burdensome tools for real‐time phenotyping of CYP2D6 could significantly contribute to precision medicine. This study focuses on the identification of markers of the CYP2D6 enzyme in human biofluids using an LC‐high‐resolution mass spectrometry‐based metabolomic approach.

Experimental Approach

Plasma and urine samples from healthy volunteers were analysed before and after intake of a daily dose of paroxetine 20 mg over 7 days. CYP2D6 genotyping and phenotyping, using single oral dose of dextromethorphan 5 mg, were also performed in all participants.

Key Results

We report four metabolites of solanidine and two unknown compounds as possible novel CYP2D6 markers. Mean relative intensities of these features were significantly reduced during the inhibition session compared with the control session (n = 37). Semi‐quantitative analysis showed that the largest decrease (−85%) was observed for the ion m/z 432.3108 normalized to solanidine (m/z 398.3417). Mean relative intensities of these ions were significantly higher in the CYP2D6 normal–ultrarapid metabolizer group (n = 37) compared with the poor metabolizer group (n = 6). Solanidine intensity was more than 15 times higher in CYP2D6‐deficient individuals compared with other volunteers.

Conclusion and Implications

The applied untargeted metabolomic strategy identified potential novel markers capable of semi‐quantitatively predicting CYP2D6 activity, a promising discovery for personalized medicine.

Metabolic Evaluation of Urine from Patients Diagnosed with High Grade (HG) Bladder Cancer by SPME-LC-MS Method

Bladder cancer (BC) is a common malignancy of the urinary system and a leading cause of death worldwide. In this work, untargeted metabolomic profiling of biological fluids is presented as a non-invasive tool for bladder cancer biomarker discovery as a first step towards developing superior methods for detection, treatment, and prevention well as to further our current understanding of this disease. In this study, urine samples from 24 healthy volunteers and 24 BC patients were subjected to metabolomic profiling using high throughput solid-phase microextraction (SPME) in thin-film format and reversed-phase high-performance liquid chromatography coupled with a Q Exactive Focus Orbitrap mass spectrometer. The chemometric analysis enabled the selection of metabolites contributing to the observed separation of BC patients from the control group. Relevant differences were demonstrated for phenylalanine metabolism compounds, i.e., benzoic acid, hippuric acid, and 4-hydroxycinnamic acid. Furthermore, compounds involved in the metabolism of histidine, beta-alanine, and glycerophospholipids were also identified. Thin-film SPME can be efficiently used as an alternative approach to other traditional urine sample preparation methods, demonstrating the SPME technique as a simple and efficient tool for urinary metabolomics research. Moreover, this study's results may support a better understanding of bladder cancer development and progression mechanisms.

Untargeted metabolomics of prostate cancer zwitterionic and positively charged compounds in urine

Prostate cancer, a leading cause of cancer-related deaths worldwide, principally occurs in over 50-year-old men. Nowadays there is urgency to discover biomarkers alternative to prostate-specific antigen, as it cannot discriminate patients with benign prostatic hyperplasia from clinically significant forms of prostatic cancer. In the present paper, 32 benign prostatic hyperplasia and 41 prostatic cancer urine samples were collected and analyzed. Polar and positively charged metabolites were therein investigated using an analytical platform comprising an up to 40-fold analyte enrichment step by graphitized carbon black solid-phase extraction, HILIC separation, and untargeted high-resolution mass spectrometry analysis. These classes of compounds are often neglected in common metabolomics experiments even though previous studies reported their significance in cancer biomarker discovery. The complex metabolomics big datasets, generated by the UHPLC-HRMS, were analyzed with the ROIMCR procedure, based on the selection of the MS regions of interest data and their analysis by the Multivariate Curve-Resolution Alternating Least Squares chemometrics method. This approach allowed the resolution and tentative identification of the metabolites differentially expressed by the two data sets. Among these, amino acids and carnitine derivatives were tentatively identified highlighting the importance of the proposed methodology for cancer biomarker research.

Recent applications of microextraction sample preparation techniques in biological samples analysis

Analysis of biological samples is affected by interfering substances with chemical properties similar to those of the target analytes, such as drugs. Biological samples such as whole blood, plasma, serum, urine and saliva must be properly processed for separation, purification, enrichment and chemical modification to meet the requirements of the analytical instruments. This causes the sample preparation stage to be of undeniable importance in the analysis of such samples through methods such as microextraction techniques. The scope of this review will cover a comprehensive summary of available literature data on microextraction techniques playing a key role for analytical purposes, methods of their implementation in common biological samples, and finally, the most recent examples of application of microextraction techniques in preconcentration of analytes from urine, blood and saliva samples. The objectives and merits of each microextration technique are carefully described in detail with respect to the nature of the biological samples. This review presents the most recent and innovative work published on microextraction application in common biological samples, mostly focused on original studies reported from 2017 to date. The main sections of this review comprise an introduction to the microextraction techniques supported by recent application studies involving quantitative and qualitative results and summaries of the most significant, recently published applications of microextracion methods in biological samples. This article considers recent applications of several microextraction techniques in the field of sample preparation for biological samples including urine, blood and saliva, with consideration for extraction techniques, sample preparation and instrumental detection systems.

An exploratory approach for an oriented development of an untargeted hydrophilic interaction liquid chromatography-mass spectrometry platform for polar metabolites in biological matrices

The analysis of polar metabolites based on liquid chromatography-mass spectrometry (LC-MS) methods should take into consideration the complexity of interactions in LC columns to be able to cover a broad range of metabolites of key biological pathways. Therefore, in this study, different chromatographic columns were tested for polar metabolites including reversed-phase and hydrophilic interaction liquid chromatography (HILIC) columns. Based on a column screening, two new generations of zwitterionic HILIC columns were selected for further evaluation. A tree-based method optimization was applied to investigate the chromatographic factors affecting the retention mechanisms of polar metabolites with zwitterionic stationary phases. The results were evaluated based on a scoring system which was applied for more than 80 polar metabolites with a high coverage of key human metabolic pathways. The final optimized methods showed high complementarity to analyze a wide range of metabolic classes including amino acids, small peptides, sugars, amino sugars, phosphorylated sugars, organic acids, nucleobases, nucleosides, nucleotides and acylcarnitines. Optimized methods were applied to analyze different biological matrices, including human urine, plasma and liver cell extracts using an untargeted approach. The number of high-quality features (< 30% median relative standard deviation) ranged from 3,755 for urine to 5,402 for the intracellular metabolome of liver cells, showing the potential of the methods for untargeted purposes.

HPLC methods for quantifying anticancer drugs in human samples: A systematic review

Pharmacokinetic (PK) study of anticancer drugs in cancer patients is highly crucial for dose selection and dosing intervals in clinical applications. Once an anticancer drug is administered, it undergoes various metabolic pathways; to determine these pathways, it is necessary to follow the administered drug in biological samples via different analytical methods. In addition, multi-drug quantification methods in patients undergoing multi-drug regimens of cancer therapy can have several benefits, such as reduced sampling time and analysis costs. In order to collect and categorize these studies, we conducted a systematic review of HPLC methods reported for the analysis of anticancer drugs in biological samples. A systematic search was performed on PubMed Medline, Scopus, and Web of Science databases, and 116 studies were included. In summary of included studies, when the objective of a method was to quantify a single drug, MS, or UV detectors were utilized equivalently. On the other hand, in methods with the aim of quantifying drug and metabolite(s) in a single run, MS detectors were the most utilized. This review can provide a comprehensive insight for researchers prior to developing a quantification method and selecting a detector.

Mass spectrometry-based metabolomics for an in-depth questioning of human health

Today, metabolomics is becoming an indispensable tool to get a more comprehensive analysis of complex living systems, providing insights on multiple aspects of physiology. Although its application in large scale population-based studies is very challenging due to the processing of large sample sets as well as the complexity of data information, its potential to characterize human health is well recognized. Technological advances in metabolomics pave the way for the efficient biomarker discovery of disease etiology, diagnosis and prognosis. Here, different steps of the metabolomics workflow, particularly mass spectrometry-based approaches, are discussed to demonstrate the potential of metabolomics to address biological questioning in human health. First an overview of metabolomics is provided with its interest in human health studies. Analytical development and advances in mass spectrometry instrumentation and computational tools are discussed regarding their application limits. Advancing metabolomics for applicability in human health and large-scale studies is presented and discussed in conclusion.

Introducing a novel procedure for peak alignment in one-dimensional 1H-NMR spectroscopy: a prerequisite for chemometric analyses of wine samples

Shifted peak positions in 1H-nuclear magnetic resonance (1H-NMR) spectroscopy of wine samples are inevitably occurring mainly due to variations in the sample matrix, which consists of ethanol, glycerol, carbohydrates, acids, phenolic compounds, minerals, and aroma compounds. Slight variations in pH during sample preparation or fluctuations in instrumental factors may contribute to shifted peak positions that need to be corrected before subjecting the NMR data to chemometric techniques to ensure samples are compared on the correct chemical shift scale. In the current work, a novel procedure for correcting 1H-NMR spectroscopy peak positions was developed by mapping of the raw NMR spectra on a common chemical shift axis using a simple interpolation approach. The mapping allowed a substantial correction of peak positions and subsequently reduced the computational burden in further spectral processing. Fine-tuning of the peak alignments was carried out efficiently by interval-wisely applying the correlation optimized warping (COW) algorithm. Our preceding mapping approach enabled the use of substantially simpler alignment parameters of the COW algorithm, thereby accelerating the whole peak alignment process. The developed procedure may also be suitable for facilitating NMR analyses of other sample types, such as agricultural, clinical or pharmaceutical samples in targeted or untargeted analytical approaches.

Metabolomic Insight into Polycystic Ovary Syndrome-An Overview

Searching for the mechanisms of the polycystic ovary syndrome (PCOS) pathophysiology has become a crucial aspect of research performed in the last decades. However, the pathogenesis of this complex and heterogeneous endocrinopathy remains unknown. Thus, there is a need to investigate the metabolic pathways, which could be involved in the pathophysiology of PCOS and to find the metabolic markers of this disorder. The application of metabolomics gives a promising insight into the research on PCOS. It is a valuable and rapidly expanding tool, enabling the discovery of novel metabolites, which may be the potential biomarkers of several metabolic and endocrine disorders. The utilization of this approach could also improve the process of diagnosis and therefore, make treatment more effective. This review article aims to summarize actual and meaningful metabolomic studies in PCOS and point to the potential biomarkers detected in serum, urine, and follicular fluid of the affected women.

Developing community-based urine sampling methods to deploy biomarker technology for the assessment of dietary exposure

OBJECTIVE

Obtaining objective, dietary exposure information from individuals is challenging because of the complexity of food consumption patterns and the limitations of self-reporting tools (e.g., FFQ and diet diaries). This hinders research efforts to associate intakes of specific foods or eating patterns with population health outcomes.

DESIGN

Dietary exposure can be assessed by the measurement of food-derived chemicals in urine samples. We aimed to develop methodologies for urine collection that minimised impact on the day-to-day activities of participants but also yielded samples that were data-rich in terms of targeted biomarker measurements.

SETTING

Urine collection methodologies were developed within home settings.

PARTICIPANTS

Different cohorts of free-living volunteers.

RESULTS

Home collection of urine samples using vacuum transfer technology was deemed highly acceptable by volunteers. Statistical analysis of both metabolome and selected dietary exposure biomarkers in spot urine collected and stored using this method showed that they were compositionally similar to urine collected using a standard method with immediate sample freezing. Even without chemical preservatives, samples can be stored under different temperature regimes without any significant impact on the overall urine composition or concentration of forty-six exemplar dietary exposure biomarkers. Importantly, the samples could be posted directly to analytical facilities, without the need for refrigerated transport and involvement of clinical professionals.

CONCLUSIONS

This urine sampling methodology appears to be suitable for routine use and may provide a scalable, cost-effective means to collect urine samples and to assess diet in epidemiological studies.

Recommendations and Best Practices for Standardizing the Pre-Analytical Processing of Blood and Urine Samples in Metabolomics

Metabolomics can be significantly influenced by a range of pre-analytical factors, such as sample collection, pre-processing, aliquoting, transport, storage and thawing. This therefore shows the crucial need for standardizing the pre-analytical phase with the aim of minimizing the inter-sample variability driven by these technical issues, as well as for maintaining the metabolic integrity of biological samples to ensure that metabolomic profiles are a direct expression of the in vivo biochemical status. This review article provides an updated literature revision of the most important factors related to sample handling and pre-processing that may affect metabolomics results, particularly focusing on the most commonly investigated biofluids in metabolomics, namely blood plasma/serum and urine. Finally, we also provide some general recommendations and best practices aimed to standardize and accurately report all these pre-analytical aspects in metabolomics research.

Suspect and non-targeted screening of chemicals of emerging concern for human biomonitoring, environmental health studies and support to risk assessment: From promises to challenges and harmonisation issues

Large-scale suspect and non-targeted screening approaches based on high-resolution mass spectrometry (HRMS) are today available for chemical profiling and holistic characterisation of biological samples. These advanced techniques allow the simultaneous detection of a large number of chemical features, including markers of human chemical exposure. Such markers are of interest for biomonitoring, environmental health studies and support to risk assessment. Furthermore, these screening approaches have the promising capability to detect chemicals of emerging concern (CECs), document the extent of human chemical exposure, generate new research hypotheses and provide early warning support to policy. Whilst of growing importance in the environment and food safety areas, respectively, CECs remain poorly addressed in the field of human biomonitoring. This shortfall is due to several scientific and methodological reasons, including a global lack of harmonisation. In this context, the main aim of this paper is to present an overview of the basic principles, promises and challenges of suspect and non-targeted screening approaches applied to human samples as this specific field introduce major specificities compared to other fields. Focused on liquid chromatography coupled to HRMS-based data acquisition methods, this overview addresses all steps of these new analytical workflows. Beyond this general picture, the main activities carried out on this topic within the particular framework of the European Human Biomonitoring initiative (project HBM4EU, 2017-2021) are described, with an emphasis on harmonisation measures.

The key points in the pre-analytical procedures of blood and urine samples in metabolomics studies

BACKGROUND

Metabolomics provides measurement of numerous metabolites in human samples, which can be a useful tool in clinical research. Blood and urine are regarded as preferred subjects of study because of their minimally invasive collection and simple preprocessing methods. Adhering to standard operating procedures is an essential factor in ensuring excellent sample quality and reliable results.

AIM OF REVIEW

In this review, we summarize the studies about the impacts of various preprocessing factors on metabolomics studies involving clinical blood and urine samples in order to provide guidance for sample collection and preprocessing.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Clinical information is important for sample grouping and data analysis which deserves attention before sample collection. Plasma and serum as well as urine samples are appropriate for metabolomics analysis. Collection tubes, hemolysis, delay at room temperature, and freeze-thaw cycles may affect metabolic profiles of blood samples. Collection time, time between sampling and examination, contamination, normalization strategies, and storage conditions may alter analysis results of urine samples. Taking these collection and preprocessing factors into account, this review provides suggestions of standard sample preprocessing.

A review of strategies for untargeted urinary metabolomic analysis using gas chromatography-mass spectrometry

BACKGROUND

Human urine gives evidence of the metabolism in the body and contains different metabolites at various concentrations. A number of analytical techniques including mass spectrometry (MS) and nuclear magnetic resonance (NMR) have been used to obtain metabolites levels in urine samples. However, gas chromatography-mass spectrometry (GC-MS) is one of the most widely used techniques for urinary metabolomics studies due to its higher sensitivity, resolution, reproducibility, reliability, relatively low cost and ease of operation compared to liquid chromatography-mass spectrometry and NMR.

AIM OF REVIEW

This review looks at various aspects of urine preparation prior to analysis by GC-MS including sample storage, urease pretreatment, derivatization, use of internal standard and quality control samples for data correction. In addition, most common types of inlet liners, ionization techniques and columns are discussed and a summary of mass analyzers are also highlighted. Lastly, the role of retention index in metabolite identification and data normalization methods are presented.

KEY SCIENTIFIC CONCEPTS OF REVIEW

The purpose of this review is summarizing methods of sample storage, pretreatment, and GC-MS analysis that are mostly used in urine metabolomics studies. Specific emphasis is given to the critical steps within the GC-MS urine metabolomics that those new to this field need to be aware of and the remaining challenges that require further attention and studies.

Important Considerations for Sample Collection in Metabolomics Studies with a Special Focus on Applications to Liver Functions

Metabolomics has found numerous applications in the study of liver metabolism in health and disease. Metabolomics studies can be conducted in a variety of biological matrices ranging from easily accessible biofluids such as urine, blood or feces, to organs, tissues or even cells. Sample collection and storage are critical steps for which standard operating procedures must be followed. Inappropriate sample collection or storage can indeed result in high variability, interferences with instrumentation or degradation of metabolites. In this review, we will first highlight important general factors that should be considered when planning sample collection in the study design of metabolomic studies, such as nutritional status and circadian rhythm. Then, we will discuss in more detail the specific procedures that have been described for optimal pre-analytical handling of the most commonly used matrices (urine, blood, feces, tissues and cells).

Assessment of human plasma and urine sample preparation for reproducible and high-throughput UHPLC-MS clinical metabolic phenotyping

In this study we assess multiple sample preparation methods for UHPLC-MS metabolic phenotyping analysis of human urine and plasma. All methods are discussed in terms of metabolite and lipid coverage and reproducibility.

Recent developments in DNA adduct analysis using liquid chromatography coupled with mass spectrometry

The formation of DNA adducts by genotoxic agents is an early event in cancer development, and it may lead to gene mutations, thereby initiating tumor development. The measurement of DNA adducts can provide critical information about the genotoxic potential of a chemical and its mechanism of carcinogenesis. In recent decades, liquid chromatography coupled with mass spectrometry has become the most important technique for analyzing DNA adducts. The improvements in resolution achievable with new chromatographic separation techniques coupled with the high specificity and sensitivity and wide dynamic range of new mass spectrometry systems have been used for both qualitative and quantitative analyses of DNA adducts. This review discusses the challenges in qualitative and quantitative analyses of DNA adducts by liquid chromatography coupled with mass spectrometry and highlights recent developments towards overcoming the limitations of liquid chromatography coupled with mass spectrometry methods. The key steps and new solutions, such as sample preparation, mass spectrometry fragmentation, and method validation, are summarized. In addition, the fundamental principles and latest advances in DNA adductomic approaches are reviewed.

Gradient extractive phase prepared by controlled rate infusion method: An applicable approach in solid phase microextraction for non-targeted analysis

The aim of this study is to introduce an extractive phase based on gradient concept by continuous changing in chemical functional groups for non-targeted analysis. For this purpose, three different two-component coatings containing (3-aminopropyl)trimethoxysilane (APTES) as polar and either phenyltriethoxysilane (PTES), octyl-trimethoxysilane (OTMS) or methyltrimethoxysilane (MTMS) as nonpolar precursors were formed on the modified stainless steel wires using controlled rate infusion (CRI) method. The presence of polar and/or non-polar functional groups on the surface of substrate was evaluated by Fourier-transform infrared spectroscopy (FTIR) together with contact angles determined alongside the gradient surface. The morphology and thickness of the prepared fibers were also investigated by scanning electron microscopy (SEM). Furthermore, uniform single-component fibers from polar (APTES) and nonpolar (PTES) coatings were fabricated in order to be compared with the gradient sorbent. The gradient phase was implemented as a fiber coating in headspace- or immersed-solid phase microextraction of various compounds including chlorobenzenes, polycyclic aromatic hydrocarbons, chlorophenols and volatile organic compounds (Log K_ow range: -0.77 to 4.64). Under the optimized condition, the limits of detection and quantification were obtained in the range of 0.01-0.5 μg L^-1 and 0.05-1.5 μg L^-1, respectively. The intra-day and inter-day relative standard deviations of 2-10% and 11-17% were achieved, respectively. The method was successfully applied to the extraction of VOCs from real water sample and relative recoveries were between 89 and 105%. The capability and efficiency of the gradient coating appears to be quite appropriate for non-targeted analysis.

Nutrimetabolomics: An Integrative Action for Metabolomic Analyses in Human Nutritional Studies

The life sciences are currently being transformed by an unprecedented wave of developments in molecular analysis, which include important advances in instrumental analysis as well as biocomputing. In light of the central role played by metabolism in nutrition, metabolomics is rapidly being established as a key analytical tool in human nutritional studies. Consequently, an increasing number of nutritionists integrate metabolomics into their study designs. Within this dynamic landscape, the potential of nutritional metabolomics (nutrimetabolomics) to be translated into a science, which can impact on health policies, still needs to be realized. A key element to reach this goal is the ability of the research community to join, to collectively make the best use of the potential offered by nutritional metabolomics. This article, therefore, provides a methodological description of nutritional metabolomics that reflects on the state-of-the-art techniques used in the laboratories of the Food Biomarker Alliance (funded by the European Joint Programming Initiative "A Healthy Diet for a Healthy Life" (JPI HDHL)) as well as points of reflections to harmonize this field. It is not intended to be exhaustive but rather to present a pragmatic guidance on metabolomic methodologies, providing readers with useful "tips and tricks" along the analytical workflow.

Comparative analysis of creatinine and osmolality as urine normalization strategies in targeted metabolomics for the differential diagnosis of asthma and COPD

INTRODUCTION

Urine is an ideal matrix for metabolomics investigation due to its non-invasive nature of collection and its rich metabolite content. Despite the advancements in mass spectrometry and ¹H-NMR platforms in urine metabolomics, the statistical analysis of the generated data is challenged with the need to adjust for the hydration status of the person. Normalization to creatinine or osmolality values are the most adopted strategies, however, each technique has its challenges that can hinder its wider application. We have been developing targeted urine metabolomic methods to differentiate two important respiratory diseases, namely asthma and chronic obstructive pulmonary disease (COPD).

OBJECTIVE

To assess whether the statistical model of separation of diseases using targeted metabolomic data would be improved by normalization to osmolality instead of creatinine.

METHODS

The concentration of 32 metabolites was previously measured by two liquid chromatography-tandem mass spectrometry methods in 51 human urine samples with either asthma (n = 25) or COPD (n = 26). The data was normalized to creatinine or osmolality. Statistical analysis of the normalized values in each disease was performed using partial least square discriminant analysis (PLS-DA). Models of separation of diseases were compared.

RESULTS

We found that normalization to creatinine or osmolality did not significantly change the PLS-DA models of separation (R²Q² = 0.919, 0.705 vs R²Q² = 0.929, 0.671, respectively). The metabolites of importance in the models remained similar for both normalization methods.

CONCLUSION

Our findings suggest that targeted urine metabolomic data can be normalized for hydration using creatinine or osmolality with no significant impact on the diagnostic accuracy of the model.

Metabolomics in chronic kidney disease: Strategies for extended metabolome coverage

Chronic kidney disease (CKD) is becoming a major public health issue as prevalence is increasing worldwide. It also represents a major challenge for the identification of new early biomarkers, understanding of biochemical mechanisms, patient monitoring and prognosis. Each metabolite contained in a biofluid or tissue may play a role as a signal or as a driver in the development or progression of the pathology. Therefore, metabolomics is a highly valuable approach in this clinical context. It aims to provide a representative picture of a biological system, making exhaustive metabolite coverage crucial. Two aspects can be considered: analytical and biological coverage. From an analytical point of view, monitoring all metabolites within one run is currently impossible. Multiple analytical techniques providing orthogonal information should be carried out in parallel for coverage improvement. The biological aspect of metabolome coverage can be enhanced by using multiple biofluids or tissues for in-depth biological investigation, as the analysis of a single sample type is generally insufficient for whole organism extrapolation. Hence, recording of signals from multiple sample types and different analytical platforms generates massive and complex datasets so that chemometric tools, including data fusion approaches and multi-block analysis, are key tools for extracting biological information and for discovery of relevant biomarkers. This review presents the recent developments in the field of metabolomic analysis, from sampling and analytical strategies to chemometric tools, dedicated to the generation and handling of multiple complementary metabolomic datasets enabling extended metabolite coverage to improve our biological knowledge of CKD.

Predictive metabolomic signatures of end-stage renal disease: A multivariate analysis of population-based data

The variability of molecular signatures and predictive low molecular weight markers of chronic kidney disease (CKD) in different populations are poorly understood. Thus, in a large sample with 4763 people we compare the molecular signatures and metabolites with diagnostic relevance in plasma and urine of CKD patients of different geographical origins. From an integrated model based on dynamic networks and multivariate statistics, metabolites with predictive value obtained from targeted and untargeted molecular analysis, interactions between metabolic pathways affected by CKD, and the methodological quality of metabolomic studies were analyzed. The metabolites 3-methylhistidine, citrulline, kynurenine, p-cresol sulfate, urea, and citrate presented consistent expression in all population groups. Only increased kynurenine and p-cresol sulfate in plasma samples obtained acceptable scores as CKD biomarkers, independent of geographic origin. Metabolites such as leucine, alanine, isoleucine, serine, histidine, and citrate were nodal points, indicating that protein metabolism pathways are similarly impaired in Asian, European and North American patients. Based on our integrated model, we show that the metabolome of CKD patients exhibits a strong geographic influence, leading to unique metabolic signatures. Contrary to the likelihood of molecular similarities between geographically distinct populations, metabolic convergences in protein metabolism pathways and the molecules kynurenine and p-cresol sulfate were relevant as general predictors of CKD. In general, the quality assessment indicated that the current evidence is based on research models with variable methodological quality, whose limitations described in this study should be considered in the refinement of molecular approaches.

Targeting human urinary metabolome by LC-MS/MS: a review

Urine is a biological matrix that contains hundreds of metabolic end products which constitute the urinary metabolome. The development and advances on LC-MS/MS have revolutionized the analytical study of biomolecules by enabling their accurate identification and quantification in an unprecedented manner. Nowadays, LC-MS/MS is helping to unveil the complexity of urine metabolome, and the results obtained have multiple biomedical applications. This review focuses on the targeted LC-MS/MS analysis of the urine metabolome. In the first part, we describe general considerations (from sample collection to quantitation) required for a proper targeted metabolic analysis. In the second part, we address the urinary analysis and recent applications of four relevant families: amino acids, catecholamines, lipids and steroids.