Development of a validated LC- MS/MS method for the quantification of 19 endogenous asthma/COPD potential urinary biomarkers

Challenges and recent advances in quantitative mass spectrometry-based metabolomics

The field of metabolomics has gained tremendous interest in recent years. Whether the goal is to discover biomarkers related to certain pathologies or to better understand the impact of a drug or contaminant, numerous studies have demonstrated how crucial it is to understand variations in metabolism. Detailed knowledge of metabolic variabilities can lead to more effective treatments, as well as faster or less invasive diagnostics. Exploratory approaches are often employed in metabolomics, using relative quantitation to look at perturbations between groups of samples. Most metabolomics studies have been based on metabolite profiling using relative quantitation, with very few studies using an approach for absolute quantitation. Using accurate quantitation facilitates the comparison between different studies, as well as enabling longitudinal studies. In this review, we discuss the most widely used techniques for quantitative metabolomics using mass spectrometry (MS). Various aspects will be addressed, such as the use of external and/or internal standards, derivatization techniques, in vivo isotopic labelling, or quantitative MS imaging. The principles, as well as the associated limitations and challenges, will be described for each approach.

Straightforward quantification of endogenous steroids with liquid chromatography-tandem mass spectrometry: Comparing calibration approaches

Different calibration strategies are used in liquid chromatography hyphenated to mass spectrometry (LC-MS) bioanalysis. Currently, the surrogate matrix and surrogate analyte represent the most widely used approaches to compensate for the lack of analyte-free matrices in endogenous compounds quantification. In this context, there is a growing interest in rationalizing and simplifying quantitative analysis using a one-point concentration level of stable isotope-labeled (SIL) standards as surrogate calibrants. Accordingly, an internal calibration (IC) can be applied when the instrument response is translated into analyte concentration via the analyte-to-SIL ratio performed directly in the study sample. Since SILs are generally used as internal standards to normalize variability between authentic study sample matrix and surrogate matrix used for the calibration, IC can be calculated even if the calibration protocol was achieved for an external calibration (EC). In this study, a complete dataset of a published and fully validated method to quantify an extended steroid profile in serum was recomputed by adapting the role of SIL internal standards as surrogate calibrants. Using the validation samples, the quantitative performances for IC were comparable with the original method, showing acceptable trueness (79%-115%) and precision (0.8%-11.8%) for the 21 detected steroids. The IC methodology was then applied to human serum samples (n = 51) from healthy women and women diagnosed with mild hyperandrogenism, showing high agreement (R² > 0.98) with the concentrations obtained using the conventional quantification based on EC. For IC, Passing-Bablok regression showed proportional biases between -15.0% and 11.3% for all quantified steroids, with an average difference of -5.8% compared to EC. These results highlight the reliability and the advantages of implementing IC in clinical laboratories routine to simplify quantification in LC-MS bioanalysis, especially when a large panel of analytes is monitored.

Standard addition method (SAM) in LC-MS/MS to quantify gluten-derived metabolites in urine samples

A tight adherence to a gluten-free diet (GFD), the most effective treatment currently available for celiac disease, is important to reduce symptoms, avoid nutritional deficiencies and improve quality of life in celiac patients. The development of analytical methods allowing detecting gluten exposure due to occasional or involuntary food transgressions could represent a useful tool to monitor patient habits and conditions and prevent long-term complications. The aim of this work was to develop and validate an approach based on the standard addition methodology (SAM) for the detection and quantification of two main metabolites of alkylresorcinols, 3,5-dihydroxybenzoic acid (DHBA) and 3-(3,5-dihydroxyphenyl)-propanoic acid (DHPPA), whose presence in urine samples is related to the intake of gluten-containing foods. Analytically, the method consisted of a protein precipitation step followed by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) analysis. The chromatographic method involved the use of a hydrophilic interaction liquid chromatography (HILIC) in a direct phase approach; LC-MS/MS analyses were performed in selected reaction monitoring (SRM) mode. Manipulation and instrumental errors were normalised using stable isotopic standards (ISs). The SAM approach here described requires less than 1 mL of urine per sample, thus greatly reducing the sample volume needed. Noteworthy, despite the small cohort of samples analysed, our data allowed to identify a potential "threshold" value, around 200 ng/mL for DHBA and 400 ng/mL for DHPPA, to discriminate between a GFD and a gluten rich diet (GRD).

Metabolomics of asthma, COPD, and asthma-COPD overlap: an overview

The two common progressive lung diseases, asthma and chronic obstructive pulmonary disease (COPD), are the leading causes of morbidity and mortality worldwide. Asthma-COPD overlap, referred to as ACO, is another complex pulmonary disease that manifests itself with features of both asthma and COPD. The disease has no clear diagnostic or therapeutic guidelines, thereby making both diagnosis and treatment challenging. Though a number of studies on ACO have been documented, gaps in knowledge regarding the pathophysiologic mechanism of this disorder exist. Addressing this issue is an urgent need for improved diagnostic and therapeutic management of the disease. Metabolomics, an increasingly popular technique, reveals the pathogenesis of complex diseases and holds promise in biomarker discovery. This comprehensive narrative review, comprising 99 original research articles in the last five years (2017-2022), summarizes the scientific advances in terms of metabolic alterations in patients with asthma, COPD, and ACO. The analytical tools, nuclear magnetic resonance (NMR), gas chromatography-mass spectrometry (GC-MS), and liquid chromatography-mass spectrometry (LC-MS), commonly used to study the expression of the metabolome, are discussed. Challenges frequently encountered during metabolite identification and quality assessment are highlighted. Bridging the gap between phenotype and metabotype is envisioned in the future.

From fundamentals in calibration to modern methodologies: A tutorial for small molecules quantification in liquid chromatography-mass spectrometry bioanalysis

Over the last two decades, liquid chromatography coupled to mass-spectrometry (LC‒MS) has become the gold standard to perform qualitative and quantitative analyses of small molecules. When quantitative analysis is developed, an analyst usually refers to international guidelines for analytical method validation. In this context, the design of calibration curves plays a key role in providing accurate results. During recent years and along with instrumental advances, strategies to build calibration curves have dramatically evolved, introducing innovative approaches to improve quantitative precision and throughput. For example, when a labeled standard is available to be spiked directly into the study sample, the concentration of the unlabeled analog can be easily determined using the isotopic pattern deconvolution or the internal calibration approach, eliminating the need for multipoint calibration curves. This tutorial aims to synthetize the advances in LC‒MS quantitative analysis for small molecules in complex matrices, going from fundamental aspects in calibration to modern methodologies and applications. Different work schemes for calibration depending on the sample characteristics (analyte and matrix nature) are distinguished and discussed. Finally, this tutorial outlines the importance of having international guidelines for analytical method validation that agree with the advances in calibration strategies and analytical instrumentation.

Quantification of endogenous aminoacids and aminoacid derivatives in urine by hydrophilic interaction liquid chromatography tandem mass spectrometry

Aminoacids and their derivatives are key biologically important metabolites and reliable, rapid and accurate, quantification for these analytes in urine remains an important analytical challenge. Here a fast and reliable HILIC-tandem MS method is presented for application in clinical or nutritional studies. The developed method was validated according to existing guidelines adapted for endogenous analytes. The validation strategy provided evidence of linearity, LOD and LOQ, accuracy, precision, matrix effect and recovery. The surrogate matrix approach was applied for calibration proving satisfactory accuracy and precision based on standard criteria over the working concentration ranges. Intra and inter day accuracy was found to range between 0.8 and 20% for the LQC (low QC) and between 0.05 and 15 % for MQC (medium QC) and HQC (high QC). Inter and intraday precision were found to be between 3 and 20 % for the LQC and between 1 and 15% for the MQC and HQC. The stability of the analytes, in both surrogate and pooled urine QC samples, was found to be within 15% over a short period at 4 °C or after a up to 3 freeze-thaw cycles. The uncertainty of the method was also assessed to provide increased confidence for the acquired measurements. The method was successfully applied to a subset of human urine samples involved in a study of amino acids dietary uptake. This method may provide a valuable tool for many applications or studies where amino acid metabolic signatures in the excreted urine are under investigation.

STRATEGIES AND CHALLENGES IN METHOD DEVELOPMENT AND VALIDATION FOR THE ABSOLUTE QUANTIFICATION OF ENDOGENOUS BIOMARKER METABOLITES USING LIQUID CHROMATOGRAPHY-TANDEM MASS SPECTROMETRY

Metabolomics is a dynamically evolving field, with a major application in identifying biomarkers for drug development and personalized medicine. Numerous metabolomic studies have identified endogenous metabolites that, in principle, are eligible for translation to clinical practice. However, few metabolomic-derived biomarker candidates have been qualified by regulatory bodies for clinical applications. Such interruption in the biomarker qualification process can be largely attributed to various reasons including inappropriate study design and inadequate data to support the clinical utility of the biomarkers. In addition, the lack of robust assays for the routine quantification of candidate biomarkers has been suggested as a potential bottleneck in the biomarker qualification process. In fact, the nature of the endogenous metabolites precludes the application of the current validation guidelines for bioanalytical methods. As a result, there have been individual efforts in modifying existing guidelines and/or developing alternative approaches to facilitate method validation. In this review, three main challenges for method development and validation for endogenous metabolites are discussed, namely matrix effects evaluation, alternative analyte-free matrices, and the choice of internal standards (ISs). Some studies have modified the equations described by the European Medicines Agency for the evaluation of matrix effects. However, alternative strategies were also described; for instance, calibration curves can be generated in solvents and in biological samples and the slopes can be compared through ratios, relative standard deviation, or a modified Stufour suggested approaches while quantifying mainly endogenous metabolitesdent t-test. ISs, on the contrary, are diverse; in which seven different possible types, used in metabolomics-based studies, were identified in the literature. Each type has its advantages and limitations; however, isotope-labeled ISs and ISs created through isotope derivatization show superior performance. Finally, alternative matrices have been described and tested during method development and validation for the quantification of endogenous entities. These alternatives are discussed in detail, highlighting their advantages and shortcomings. The goal of this review is to compare, apprise, and debate current knowledge and practices in order to aid researchers and clinical scientists in developing robust assays needed during the qualification process of candidate metabolite biomarkers. © 2019 John Wiley & Sons Ltd. Mass Spec Rev.

Chemical Isotope Labeling LC-MS for Metabolomics

Due to the great diversity of chemical and physical properties of metabolites as well as a wide range of concentrations of metabolites present in metabolomic samples, performing comprehensive and quantitative metabolome analysis is a major analytical challenge. Conventional approach of combining various techniques and methods with each detecting a fraction of the metabolome can lead to the increase in overall metabolomic coverage. However, this approach requires extensive investment in equipment and analytical expertise with still relatively low coverage and low sample throughput. Chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS) offers an alternative means of increasing metabolomic coverage while maintaining high quantification precision and accuracy. This chapter describes the CIL LC-MS method and its key features for metabolomic analysis.

Determination of estrogens by solid-phase quadruplex stable isotope dansylation coupled with liquid chromatography-high resolution mass spectrometry in environmental samples

Estrogens distribute widely in the environment as endocrine-disrupting chemicals (EDCs), which have to be monitored to evaluate their environmental impact. Aim to improve the analytical throughput of liquid chromatography-high resolution mass spectrometry (LC-HRMS), a quadruplex stable isotope dansylation method was developed, with which three real samples could be quantitatively analyzed in one injection. As the estrogens were at trace level in complex matrices, magnetic solid-phase extraction (MSPE) was applied to enrich these analytes and remove the interfaces. By integrating MSPE and quadruplex stable isotope dansylation, a solid-phase quadruplex labeling method was developed for the LC-HRMS analysis of estrogen analogues. For the tested seven estrogens, the developed method showed low detection limits (0.1-0.5 ng/L for pond water and 0.01-0.05 μg/kg for poultry manure), good precision (RSD < 5.5%) and accuracy (96.8-108.3%). The method was applied in the determination of estrogens in environmental samples, and the results revealed that all the tested estrogens were present in the estuary water (unquantifiable to 71.2 ng/L) and chicken manure (undetectable to 25.43 μg/kg).

Perturbations of Metabolomic Profiling of Spleen From Rats Infected With Clonorchis sinensis Determined by LC-MS/MS Method

Clonorchiasis is an important zoonotic parasitic disease worldwide. In view of the fact that parasite infection affects host metabolism, and there is an intricate relationship between metabolism and immunity. Metabolic analysis of the spleen could be helpful for understanding the pathophysiological mechanisms in clonorchiasis. A non-targeted ultra high performance liquid tandem chromatography quadrupole time of flight mass spectrometry (UHPLC-QTOF MS) approach was employed to investigate the metabolic profiles of spleen in rats at 4 and 8 weeks post infection with Clonorchis sinensis (C. sinensis). Then a targeted ultra-high performance liquid chromatography multiple reaction monitoring mass spectrometry (UHPLC-MRM-MS/MS) approach was used to further quantify amino acid metabolism. Multivariate data analysis methods, such as principal components analysis and orthogonal partial least squares discriminant analysis, were used to identify differential metabolites. Finally, a total of 396 and 242 significant differential metabolites were identified in ESI+ and ESI− modes, respectively. These metabolites included amino acids, nucleotides, carboxylic acids, lipids and carbohydrates. There were 38 significantly different metabolites shared in the two infected groups compared with the control group through the Venn diagram. The metabolic pathways analysis revealed that pyrimidine metabolism, aminoacyl-tRNA biosynthesis, purine metabolism and phenylalanine, tyrosine and tryptophan biosynthesis were significantly enriched in differential metabolites, which was speculated to be related to the disease progression of clonorchiasis. Furthermore, 15 amino acids screened using untargeted profiling can be accurately quantified and identifed by targeted metabolomics during clonrochiasis. These results preliminarily revealed the perturbations of spleen metabolism in clonorchiasis. Meanwhile, this present study supplied new insights into the molecular mechanisms of host-parasite interactions.

Compensate for or Minimize Matrix Effects? Strategies for Overcoming Matrix Effects in Liquid Chromatography-Mass Spectrometry Technique: A Tutorial Review

In recent decades, mass spectrometry techniques, particularly when combined with separation methods such as high-performance liquid chromatography, have become increasingly important in pharmaceutical, bio-analytical, environmental, and food science applications because they afford high selectivity and sensitivity. However, mass spectrometry has limitations due to the matrix effects (ME), which can be particularly marked in complex mixes, when the analyte co-elutes together with other molecules, altering analysis results quantitatively. This may be detrimental during method validation, negatively affecting reproducibility, linearity, selectivity, accuracy, and sensitivity. Starting from literature and own experience, this review intends to provide a simple guideline for selecting the best operative conditions to overcome matrix effects in LC-MS techniques, to obtain the best result in the shortest time. The proposed methodology can be of benefit in different sectors, such as pharmaceutical, bio-analytical, environmental, and food sciences. Depending on the required sensitivity, analysts may minimize or compensate for ME. When sensitivity is crucial, analysis must try to minimize ME by adjusting MS parameters, chromatographic conditions, or optimizing clean-up. On the contrary, to compensate for ME analysts should have recourse to calibration approaches depending on the availability of blank matrix. When blank matrices are available, calibration can occur through isotope labeled internal standards and matrix matched calibration standards; conversely, when blank matrices are not available, calibration can be performed through isotope labeled internal standards, background subtraction, or surrogate matrices. In any case, an adjusting of MS parameters, chromatographic conditions, or a clean-up are necessary.

The simultaneous quantification of phytosterols and tocopherols in liposomal formulations using validated atmospheric pressure chemical ionization- liquid chromatography -tandem mass spectrometry

A novel liquid chromatography tandem mass spectrometry (LC-MS/MS) method was developed and validated to simultaneously quantify phytosterols (brassicasterol, campesterol, stigmasterol and β-sitosterol) and tocopherols (alpha, beta, gamma and delta) entrapped in the lipid bilayer of a liposomal formulation. Apart from liposomes (a pharmaceutical product), the developed method was able to quantify target analytes in agricultural products, thus showing wide applications. Atmospheric pressure chemical ionization (APCI) was employed due to the enhanced ionization of phytosterols and tocopherols in comparison to electrospray ionization. Unlike published work, the chromatographic conditions were modified to simplify the analytical approach. For the first time, a simple isocratic elution (acetonitrile:methanol 99:1 v/v) was utilized for the separation of four phytosterols and four tocopherols in a single run. A substantially better baseline separation of phytosterols were obtained in comparison to reported methods by using poroshell C18 column. The method has a total run time of 7 min, which is the shortest run time among all reported quantitative methods for the simultaneous determination of four phytosterols and four tocopherols. Calibration curves for all phytosterols were linear in the range of 0.05-10 μg/mL. In the case of tocopherols, alpha tocopherol showed linear response in the range of 0.25-10 μg/mL. However, gamma and delta tocopherols exhibited quadratic relationship in the same concentration range (0.25-10 μg/mL). Validation parameters met the International Conference on Harmonization (ICH) guidelines in terms of selectivity, accuracy, precision, repeatability, sensitivity, matrix effects, dilution integrity and stability. The method was, for the first time, successfully applied for the quantifying phytosterols and tocopherols entrapped inside liposomes. An interesting chromatographic phenomenon was observed during sample analysis. Alpha tocopherol (entrapped in the liposomal lipid bilayer) was found to elute at two retention times, 2.53 min and 3.60 min. Such dual separation was not observed in calibration standards and quality controls. It was concluded that the chiral recognition ability of liposomes made up of phosphatidylcholine separated the enantiomers of alpha tocopherol, giving rise to two peaks at two different retention time. To sum, the reported novel LC-MS/MS method addresses three major analytical shortcomings, namely i)longer run time, ii)complex gradient elution and iii)poor baseline separation of phytosterols and tocopherols.

Metabolomics for Investigating Physiological and Pathophysiological Processes

Metabolomics uses advanced analytical chemistry techniques to enable the high-throughput characterization of metabolites from cells, organs, tissues, or biofluids. The rapid growth in metabolomics is leading to a renewed interest in metabolism and the role that small molecule metabolites play in many biological processes. As a result, traditional views of metabolites as being simply the "bricks and mortar" of cells or just the fuel for cellular energetics are being upended. Indeed, metabolites appear to have much more varied and far more important roles as signaling molecules, immune modulators, endogenous toxins, and environmental sensors. This review explores how metabolomics is yielding important new insights into a number of important biological and physiological processes. In particular, a major focus is on illustrating how metabolomics and discoveries made through metabolomics are improving our understanding of both normal physiology and the pathophysiology of many diseases. These discoveries are yielding new insights into how metabolites influence organ function, immune function, nutrient sensing, and gut physiology. Collectively, this work is leading to a much more unified and system-wide perspective of biology wherein metabolites, proteins, and genes are understood to interact synergistically to modify the actions and functions of organelles, organs, and organisms.

Development of a new quantification method for organic acids in urine as potential biomarkers for respiratory illness

Asthma and chronic obstructive pulmonary disease (COPD) are common respiratory disorders that have similar clinical presentation and misdiagnosis may lead to improper treatment. There is a need for a better, non-invasive test for the differentiation of asthma and COPD. In this study, we developed a new validated LC-MS/MS method for 17 urinary organic acids that could serve as potential biomarkers. Human urine samples were collected from adults with asthma or COPD. LC-MS/MS was performed using the differential isotope labeling approach. 4-(Dimethylamino) phenacyl bromide (DmPA) was used for derivatization using two different carbon isotopes, allowing for the formation of internal standard for each metabolite. Gradient elution was employed on a C₁₈ column while the LC-MS/MS operated in the multiple reaction monitoring mode (MRM). Regulatory guidelines were used for method validation. Partial Least Squares Discriminative Analysis (PLS-DA) was applied to the log-transformed values of metabolites in each group of asthma and COPD subjects. Full validation in targeted metabolomics is scarce with usually limited number of metabolites, unlike fit-for-purpose approach. Due to the endogenous nature of the metabolites, numerous challenges were encountered during method development and validation, such as the lactic acid interference from the surrounding environment. The required specificity, accuracy and precision was successfully achieved. The method was fully validated, ensuring robustness and reproducibility when analyzing patient samples. The method was applied to analyze human urine samples and PLS-DA analysis showed differentiation of asthma and COPD subjects (R2 0.89, Q2 0.68). As targeted metabolomics is expanding to the clinical sphere, more validated methods/strategies are needed. Our work will expand the current knowledge-base regarding targeted metabolomics.

Quantitative determination of potential urine biomarkers of respiratory illnesses using new targeted metabolomic approach

The diagnosis of asthma and chronic obstructive pulmonary disease (COPD) can be challenging due to the overlap in their clinical presentations in some patients. There is a need for a more objective clinical test that can be routinely used in primary care settings. Through an untargeted ¹H NMR urine metabolomic approach, we identified a set of endogenous metabolites as potential biomarkers for the differentiation of asthma and COPD. A subset of these potential biomarkers contains 7 highly polar metabolites of diverse physicochemical properties. To the best of our knowledge, there is no liquid chromatography-tandem mass spectrometry (LC-MS/MS) method that evaluated more than two of the target metabolites in a single analytical run. The target metabolites belong to the families of monosaccharides, organic acids, amino acids, quaternary ammonium compounds and nucleic acids, rendering hydrophilic interaction liquid chromatography (HILIC) an ideal technology for their quantification. Since a clinical decision is to be made from patients data, a fully validated analytical method is required for biomarker validation. Method validation for endogenous metabolites is a daunting task since current guidelines were designed for exogenous compounds. As such, innovative approaches were adopted to meet the validation requirements. Herein, we describe a sensitive HILIC-MS/MS method for the quantification of the 7 endogenous urinary metabolites. Detection was achieved in the multiple reaction monitoring (MRM) mode with polarity switching, using quadrupole-linear ion trap instrument (QTRAP 6500) as well as single ion monitoring in the negative-ion mode. The method was fully validated according to the regulatory guidelines. Linearity was established between 6 and 21000 ng/mL and quality control samples demonstrated acceptable intra- and inter-day accuracy (85.7%-112%), intra- and inter-day precision (CV% <11.5%) as well as stability under various storage and sample processing conditions. To illustrate the method's applicability, the validated method was applied to the analysis of a small set of urine samples collected from asthma and COPD patients. Preliminary modelling of separation was generated using partial least square discriminant analysis (R² 0.752 and Q² 0.57). The adequate separation between patient samples confirms the diagnostic potential of these target metabolites as a proof-of-concept for the differentiation between asthma and COPD. However, more patient urine samples are needed in order to increase the statistical power of the analytical model.

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.