Amino acid profiling as a method of discovering biomarkers for diagnosis of neurodegenerative diseases

Sportomics Analyses of the Exercise-Induced Impact on Amino Acid Metabolism and Acute-Phase Protein Kinetics in Female Olympic Athletes

BACKGROUND

Exercise can be used as a model to understand immunometabolism. Biological data on elite athletes are limited, especially for female athletes, including relevant data on acute-phase proteins and amino acid metabolism.

METHODS

We analyzed acute-phase proteins and amino acids collected at South American, Pan-American, and Olympic Games for 16 Olympic sports. We compared female and male elite athletes (447 vs. 990 samples) across four states (fasting, pre-exercise, post-exercise, and resting) to understand sex-specific immunometabolic responses in elite athletes.

RESULTS

Considering all states and sports, we found that elite female athletes exhibited higher concentrations of C-reactive protein, lipopolysaccharide-binding protein, myeloperoxidase, haptoglobin, and IGF1, with ratios ranging from 1.2 to 2.0 (p < 0.001). Women exhibited lower concentrations of most amino acids, except for glutamate and alanine. Although almost 30% lower in women, branched-chain amino acids (BCAAs) showed a similar pattern in all states (ρ ≥ 0.9; p < 0.001), while aromatic amino acids (AAAs) showed higher consumption during exercise in women.

CONCLUSION

We established sex dimorphism in elite athletes' metabolic and inflammatory responses during training and competition. Our data suggest that female athletes present a lower amino acid response towards central fatigue development than male athletes. Understanding these differences can lead to insights into sex-related immuno-metabolic responses in sports or other inflammatory conditions.

Quantification of amino acids in small volumes of palm sweat samples

This study investigates the significance of quantifying amino acids in minute sweat volumes using high-performance liquid chromatography with fluorescence detection. Sweat, a valuable biofluid for non-invasive health monitoring, provides real-time insights into physiological changes. Amino acids, which are critical for various physiological processes, are key to protein synthesis and cellular regulation. Therefore, analyzing sweat's amino acid profiles can offer insights into metabolic states, exercise-induced stress, and potential biomarkers for health conditions. For sensitive analysis, amino acids were derivatized with 4-fluoro-7-nitro-2,1,3-benzoxadiazole (NBD-F), followed by liquid chromatographic separation on an octadecylsilyl column and fluorescence detection. The developed method was validated and applied to human sweat samples, enabling the quantification of 14 amino acids. The most abundant amino acids in the samples were serine, glycine, and alanine, which aligns with prior studies. This method offers a non-invasive and efficient way to screen for diseases by detecting amino acids in sweat, even with minimal sweat volumes. The approach could also be used to analyze other biomolecules in sweat, expanding its potential applications.

Comparative Analysis of Serum Amino Acid Profiles in Patients with Myasthenia Gravis and Multiple Sclerosis

Background: Multiple sclerosis (MS) and myasthenia gravis (MG) are autoimmune diseases that attack the central nervous system (CNS) and the neuromuscular junction, respectively. As the common pathogenesis of both diseases is associated with an autoimmune background and the involvement of T and B lymphocytes, the overlapping of selected clinical symptoms may cause difficulties in the differential diagnosis of both diseases. Methods: The aim of the study was to use Liquid Chromatography-Electrospray Ionization-Mass Spectrometry (LC-ESI-MS/MS) in conjunction with multivariate statistical analyses to examine the changes in amino acid metabolic profiles between patients with MG, MS, and a control group. Results: Comparative analysis of amino acids (AA) between patients with MG, MS, and within the control group allowed for the identification of statistically significant differences in the amino acid profile. Comparing the patients (patients with MS and MG) with the control group, and after taking the results of multiple tests into account, it was observed that amino acids such as ARG, PRO, TRP, CIT were significantly different between the groups. When considering the comparison between the AA concentrations in MS and MG patients, we found three AAs that were significantly different in the MS and MG groups, after correcting for multiple testing (CIT, GABA, and AAA). Higher concentrations of amino acids that showed significant differences were observed in patients with myasthenia gravis. Conclusions: Our results have indicated AAs that may prove valuable for improving the diagnostics of MS and MG patients. To better assess the potential utility of these markers, their performance requires further validation in a larger study group and limitation of possible confounding factors, e.g., medications and diet.

CSF amino acid profiles in ICV-streptozotocin-induced sporadic Alzheimer's disease in male Wistar rat: a metabolomics and systems biology perspective

Alzheimer's disease (AD) is an increasingly important public health concern due to the increasing proportion of older individuals within the general population. The impairment of processes responsible for adequate brain energy supply primarily determines the early features of the aging process. Restricting brain energy supply results in brain hypometabolism prior to clinical symptoms and is anatomically and functionally associated with cognitive impairment. The present study investigated changes in metabolic profiles induced by intracerebroventricular-streptozotocin (ICV-STZ) in an AD-like animal model. To this end, male Wistar rats received a single injection of STZ (3 mg·kg-1) by ICV (2.5 μL into each ventricle for 5 min on each side). In the second week after receiving ICV-STZ, rats were tested for cognitive performance using the Morris Water Maze test and subsequently prepared for positron emission tomography (PET) to confirm AD-like symptoms. Tandem Mass Spectrometry (MS/MS) analysis was used to detect amino acid changes in cerebrospinal fluid (CFS) samples. Our metabolomics study revealed a reduction in the concentrations of various amino acids (alanine, arginine, aspartic acid, glutamic acid, glycine, isoleucine, methionine, phenylalanine, proline, serine, threonine, tryptophane, tyrosine, and valine) in CSF of ICV-STZ-treated animals as compared to controls rats. The results of the current study indicate amino acid levels could potentially be considered targets of nutritional and/or pharmacological interventions to interfere with AD progression.

The causal relationship between blood metabolites and rosacea: A Mendelian randomization

BACKGROUND

An increasing amount of research demonstrates that metabolic disorders are related to rosacea. However, the correlations and causal relationships among them remain unknown.

METHODS

We conducted not only forward 2-sample MR (Mendelian randomization) analyses but also reverse MR analyses which showed positive results in the forward MR analysis. In the forward MR analyses, inverse-variance weighted (IVW) and MR-Egger were performed as MR analyses. Cochran's Q test and the MR-Egger Intercept were used for sensitivity analyses. Concerning reverse MR analyses, IVW, MR-Egger, weighted median, simple mode, and weighted mode were applied. Cochran's Q test, MR-Egger Intercept, and MR pleiotropy residual sum and outlier (MR-PRESSO) outlier test were applied as sensitivity analyses.

RESULTS

A total of 24 metabolites and 1 metabolite ratio were shown to have a causal effect on rosacea. N-lactoyl phenylalanine (N-Lac-Phe) was estimated as statistically significant by Bonferroni correction. Interestingly, we found three metabolites that were negatively associated with rosacea, especially caffeine, which are in line with the results of a large cohort study of females. For reverse MR analysis, we revealed that rosacea could potentially decrease the generation of two metabolites: octadecenedioate (C18:1-DC) and methyl vanillate sulfate.

CONCLUSION

This study identified blood metabolites that may be associated with the development of rosacea. However, the exact mechanism by which these positive metabolites influence rosacea remains uncertain due to the paucity of experimental investigations. The combination of genetics and metabolomics offers novel viewpoints on the research of underlying mechanisms of rosacea and has significant value in screening and prevention of rosacea.

Serum amino acid profiles in patients with myasthenia gravis

Myasthenia gravis (MG) is an autoimmune disease characterized by weakness and rapid fatigue. Diagnostic methods used for myasthenia gravis are not conclusive and satisfactory, therefore it is necessary to develop reliable tools to help diagnose myasthenia gravis as early as possible. The aim of the study was to use HPLC-MS in conjunction with multivariate statistical analyses to investigate changes in the amino acid metabolic profiles between myasthenia gravis patients compared and controls. In addition, the effect of treatment regimens and myasthenia gravis type, on the observed changes in amino acid metabolic profiles were assessed. Serum levels of 29 amino acids were determined in 2 groups of individuals-28 patients with myasthenia gravis and 53 control subjects (CS). The results of our study indicate that serum levels of several amino acids in patients with myasthenia gravis changed significantly compared to the control group. Statistical analysis revealed differences between amino acids concentration in patients with different therapeutic scheme. In conclusion, amino acids may be involved in mechanisms underlying myasthenia gravis pathogenesis as well as may be potential biomarkers in MG patients diagnosis. However, considering the multifactorial, heterogenous and complex nature of this disease, validation on a larger study sample in further research is required before application into diagnostic practice.

Determination of creatinine in urine and blood serum human samples by CZE-UV using on-column internal standard injection

Creatinine is a well-stablished biomarker for kidney malfunctions and for normalization parameter of urinary quantitative information. Recently, metabolic studies have been discovering other functionalities for creatinine tests in human urine and blood serum. In this work we present an enhanced capillary electrophoresis (CE) based protocol for determination of creatinine. CE is a high-throughput separation technique that have been getting attention through the last decades and might be considered to be adopted as an analytical instrumentation for clinical purposes. In the proposed method, we performed a short injection program with on-column addition of internal standard. Additionally, the method allows a simultaneous screening of non-proteinogenic amino acids that could be considered for metabolomics purposes. We design a pilot study that successfully estimated the creatinine value in 100 urine samples with (2.85 ± 1.78) mg dL^-1 LOD; (8.24 ± 5.93) mg dL^-1 LOQ and 82.4% accuracy. Considering that serum creatinine is also included in the clinical laboratory routines for estimated Glomerular Filtration Rate dosage, the method was complementary applied to 10 blood serum samples, which resulted in a model with (0.4 ± 0.2) mg dL^-1 LOD; (2.0 ± 0.6) mg dL^-1 LOQ and 83.8% of accuracy. All results were in agreement with reference values. The proposed method promotes a great analytical frequency and reproducibility with enhanced specificity compared with the ongoing protocol by Jaffe's reaction, thereby proving to be useful as an alternative for creatinine exams that might help complete a diagnosis of a series of health-related issues.

Diagnostic metabolomic profiling of Parkinson's disease biospecimens

BACKGROUND

Reliable and sensitive biomarkers are needed for enhancing and predicting Parkinson's disease (PD) diagnosis.

OBJECTIVE

To investigate comprehensive metabolomic profiling of biochemicals in CSF and serum for determining diagnostic biomarkers of PD.

METHODS

Fifty subjects, symptomatic with PD for ≥5 years, were matched to 50 healthy controls (HCs). We used ultrahigh-performance liquid chromatography linked to tandem mass spectrometry (UHPLC-MS/MS) for measuring relative concentrations of ≤1.5 kDalton biochemicals. A reference library created from authentic standards facilitated chemical identifications. Analytes underwent univariate analysis for PD association, with false discovery rate-adjusted p-value (≤0.05) determinations. Multivariate analysis (for identifying a panel of biochemicals discriminating PD from HCs) used several biostatistical methods, including logistic LASSO regression.

RESULTS

Comparing PD and HCs, strong differentiation was achieved from CSF but not serum specimens. With univariate analysis, 21 CSF compounds exhibited significant differential concentrations. Logistic LASSO regression led to selection of 23 biochemicals (11 shared with those determined by the univariate analysis). The selected compounds, as a group, distinguished PD from HCs, with Area-Under-the-Receiver-Operating-Characteristic (ROC) curve of 0.897. With optimal cutoff, logistic LASSO achieved 100% sensitivity and 96% specificity (and positive and negative predictive values of 96% and 100%). Ten-fold cross-validation gave 84% sensitivity and 82% specificity (and 82% positive and 84% negative predictive values). From the logistic LASSO-chosen regression model, 2 polyamine metabolites (N-acetylcadaverine and N-acetylputrescine) were chosen and had the highest fold-changes in comparing PD to HCs. Another chosen biochemical, acisoga (N-(3-acetamidopropyl)pyrrolidine-2-one), also is a polyamine metabolism derivative.

CONCLUSIONS

UHPLC-MS/MS assays provided a metabolomic signature highly predictive of PD. These findings provide further evidence for involvement of polyamine pathways in the neurodegeneration of PD.

Targeted F 19 - tags to detect amino acids in complex mixtures using NMR spectroscopy

Nuclear magnetic resonance spectroscopy of fluorine-19 nucleus ( F 19 -NMR) emerges as a powerful tool because of the high sensitivity due to its high natural abundance, broad spectral range, and the simplicity of a spin-half system. However, it is still seldom utilized in the chemistry classroom or research. This article thus aims to demonstrate the power of NMR by investigating the kinetics when a F 19 - tag reacts with individual amino acids (AA) and eventually utilizing the approach to identify and quantify various AAs from a complex mixture such as a metabolomics sample. The F 19 - tag named 2,5-dioxopyrrolidin-1-yl-2-(trifluoromethyl)benzoate was synthesized following a previously established method. The reaction kinetics of the tag was then continuously measured using F 19 NMR in the presence of selected AAs. The estimated reaction rate constants to form the F 19 - tags with each AA differ, which could be used as an identification tool. The tag formations were typically completed in 24-48 h in water for all the samples. These demonstrations suggest that F 19 - tags could form the basis for chemical kinetics and AA detection using F 19 -NMR.

Vending-Machine-Style Skin Excretion Sensing

Skin metabolites show huge potential for use in clinical diagnostics. However, skin sampling and analysis workflows are tedious and time-consuming. Here, we demonstrate a vending-machine-style skin excretion sensing platform based on hydrogel-assisted sampling of skin metabolites. In this sensing platform, a sampling probe with hydrogel is held by a robotic arm. The robotic arm manoeuvres the probe to press it onto the forearm of a human subject. Due to the highly hydrophilic nature of the hydrogel, water-soluble metabolites─released by skin─are collected into the hydrogel, leaving behind the nonpolar metabolites. The probe is then inserted into a custom-made open port sampling interface coupled to an electrospray ion source of a high-resolution quadrupole-time-of-flight mass spectrometer. Metabolites in the hydrogel are immediately extracted by a solvent liquid junction in the interface and analyzed using the mass spectrometer. The ion current of the target analyte is displayed on a customized graphical user interface, which can also be used to control the key components of the analytical platform. The automated sampling and analysis workflow starts after the user inserts coins or presents an insurance card, presses a button, and extends an arm on the sampling area. The platform relies on low-cost mechanical and electronic modules (a robotic arm, a single-board computer, and two microcontroller boards). The limits of detection for standard analytes─arginine, citrulline, and histidine─embedded in agarose gel beds were 148, 205, and 199 nM, respectively. Various low-molecular-weight metabolites from human skin have been identified with the high-resolution mass spectrometer.

An integrated targeted metabolomics and network pharmacology approach to exploring the mechanism of ellagic acid against sleep deprivation-induced memory impairment and anxiety

Background

As a neuroprotective agent, ellagic acid (EA) is extremely beneficial. Our previous study found that EA can alleviate sleep deprivation (SD)-induced abnormal behaviors, although the mechanisms underlying this protective effect have not yet been fully elucidated.

Objective

An integrated network pharmacology and targeted metabolomics approach was utilized in this study to investigate the mechanism of EA against SD-induced memory impairment and anxiety.

Methods

Behavioral tests were conducted on mice after 72 h of SD. Hematoxylin and eosin staining and nissl staining were then carried out. Integration of network pharmacology and targeted metabolomics was performed. Eventually, the putative targets were further verified using molecular docking analyses and immunoblotting assays.

Results

The present study findings confirmed that EA ameliorated the behavioral abnormalities induced by SD and prevented histopathological and morphological damage to hippocampal neurons. Through multivariate analysis, clear clustering was obtained among different groups, and potential biomarkers were identified. Four key targets, catechol-O-methyltransferase (COMT), cytochrome P450 1B1 (CYP1B1), glutathione S-transferase A2 (GSTA2), and glutathione S-transferase P1 (GSTP1), as well as the related potential metabolites and metabolic pathways, were determined by further integrated analysis. Meanwhile, in-silico studies revealed that EA is well located inside the binding site of CYP1B1 and COMT. The experimental results further demonstrated that EA significantly reduced the increased expression of CYP1B1 and COMT caused by SD.

Conclusion

The findings of this study extended our understanding of the underlying mechanisms by which EA treats SD-induced memory impairment and anxiety, and suggested a novel approach to address the increased health risks associated with sleep loss.

Insight into Early Diagnosis of Multiple Sclerosis by Targeting Prognostic Biomarkers

Multiple sclerosis (MS) is a central nervous system (CNS) immune-mediated disease that mainly strikes young adults and leaves them disabled. MS is an autoimmune illness that causes the immune system to attack the brain and spinal cord. The myelin sheaths, which insulate the nerve fibers, are harmed by our own immune cells, and this interferes with brain signal transmission. Numbness, tingling, mood swings, memory problems, exhaustion, agony, vision problems, and/or paralysis are just a few of the symptoms. Despite technological advancements and significant research efforts in recent years, diagnosing MS can still be difficult. Each patient's MS is distinct due to a heterogeneous and complex pathophysiology with diverse types of disease courses. There is a pressing need to identify markers that will allow for more rapid and accurate diagnosis and prognosis assessments to choose the best course of treatment for each MS patient. The cerebrospinal fluid (CSF) is an excellent source of particular indicators associated with MS pathology. CSF contains molecules that represent pathological processes such as inflammation, cellular damage, and loss of blood-brain barrier integrity. Oligoclonal bands, neurofilaments, MS-specific miRNA, lncRNA, IgG-index, and anti-aquaporin 4 antibodies are all clinically utilised indicators for CSF in MS diagnosis. In recent years, a slew of new possible biomarkers have been presented. In this review, we look at what we know about CSF molecular markers and how they can aid in the diagnosis and differentiation of different MS forms and treatment options, and monitoring and predicting disease progression, therapy response, and consequences during such opportunistic infections.

A high performance liquid chromatography tandem mass spectrometry protocol for detection of neurotransmitters in the rat brain tissue

The detection of neurotransmitters has extensively been applied to the study of the pathogenesis, diagnosis, and therapeutic effect of drugs on many neuropsychiatric diseases. High-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) has been employed to determine neurotransmitters levels due to its distinct advantages. However, neurotransmitter detection still presents some challenges. A rapid and sensitive HPLC-MS/MS protocol has been established in our lab, which can simultaneously detect 5 neurotransmitters with an easy pretreatment procedure. The protocol provides demanded reference value for the lab using an Agilent HPLC-MS/MS system with a triple quadrupole analyzer.

Electrodetection of Small Molecules by Conformation-Mediated Signal Enhancement

Electrochemical biosensors allow the rapid, selective, and sensitive transduction of critical biological parameters into measurable signals. However, current electrochemical biosensors often fail to selectively and sensitively detect small molecules because of their small size and low molecular complexity. We have developed an electrochemical biosensing platform that harnesses the analyte-dependent conformational change of highly selective solute-binding proteins to amplify the redox signal generated by analyte binding. Using this platform, we constructed and characterized two biosensors that can sense leucine and glycine, respectively. We show that these biosensors can selectively and sensitively detect their targets over a wide range of concentrations-up to 7 orders of magnitude-and that the selectivity of these sensors can be readily altered by switching the bioreceptor's binding domain. Our work represents a new paradigm for the design of a family of modular electrochemical biosensors, where access to electrode surfaces can be controlled by protein conformational changes.

Capacitance-Based Biosensor for the Measurement of Total Loss of L-Amino Acids in Human Serum during Hemodialysis

In this paper, we present a biosensor based on a gold nanoparticle (AuNP)-modified Pt electrode with an adjusted membrane containing cross-linked L-amino acid oxidase for the detection and quantification of total L-amino acids. The designed biosensor was tested and characterized using the capacitance-based principle, capacitance measurements after electrode polarization, disconnection from the circuit, and addition of the respective amount of the analyte. The method was implemented using the capacitive and catalytic properties of the Pt/AuNP electrode; nanostructures were able to store electric charge while at the same time catalyzing the oxidation of the redox reaction intermediate H₂O₂. In this way, the Pt/AuNP layer was charged after the addition of analytes, allowing for much more accurate measurements for samples with low amino acid concentrations. The combined biosensor electrode with the capacitance-based measurement method resulted in high sensitivity and a low limit of detection (LOD) for hydrogen peroxide (4.15 μC/μM and 0.86 μM, respectively) and high sensitivity, a low LOD, and a wide linear range for L-amino acids (0.73 μC/μM, 5.5 μM and 25-1500 μM, respectively). The designed biosensor was applied to measure the relative loss of amino acids in patients undergoing renal replacement therapy by analyzing amino acid levels in diluted serum samples before and after entering/leaving the hemodialysis apparatus. In general, the designed biosensor in conjunction with the proposed capacitance-based method was clinically tested and could also be applied for the detection of other analytes using analyte-specific oxidases.

Amino acid profiling to predict prognosis in patients with heart failure: an expert review

Heart failure is a complex disease with a poor prognosis. A number of widely used prognostic tools have limitations, so efforts to identify novel predictive markers and measures are important. As a metabolomics tool, amino acid profiling has shown promise in predicting heart failure prognosis; however, the evidence has not yet been sufficiently evaluated. We describe the utilization of amino acids in the healthy heart and in heart failure before reviewing the literature on amino acid profiling for prognostic prediction. We expertly interpret the findings and provide suggestions for future research to advance the understanding of the prognostic potential of amino acid profiling in heart failure. Our analysis revealed correlations between amino acid biomarkers and traditional prognostic factors, the additional prognostic value of amino acid biomarkers over traditional prognostic factors, and the successful use of amino acid biomarkers to distinguish heart failure aetiology. Although certain amino acid biomarkers have demonstrated additional prognostic value over traditional measures, such as New York Heart Association functional class, these measures are deeply rooted in clinical practice; thus, amino acid biomarkers may be best placed as additional prognostic tools to improve current risk stratification rather than as surrogate tools. Once the metabolic profiles of different heart failure aetiologies have been clearly delineated, the amino acid biomarkers with the most value in prognostic prediction should be determined. Amino acid profiling could be useful to evaluate the pathophysiology and metabolic status of different heart failure cohorts, distinguish heart failure aetiologies, and improve risk stratification and prognostic prediction.

The gut microbiota affects the social network of honeybees

The gut microbiota influences animal neurodevelopment and behaviour but has not previously been documented to affect group-level properties of social organisms. Here, we use honeybees to probe the effect of the gut microbiota on host social behaviour. We found that the microbiota increased the rate and specialization of head-to-head interactions between bees. Microbiota colonization was associated with higher abundances of one-third of the metabolites detected in the brain, including amino acids with roles in synaptic transmission and brain energetic function. Some of these metabolites were significant predictors of the number of social interactions. Microbiota colonization also affected brain transcriptional processes related to amino acid metabolism and epigenetic modifications in a brain region involved in sensory perception. These results demonstrate that the gut microbiota modulates the emergent colony social network of honeybees and suggest changes in chromatin accessibility and amino acid biosynthesis as underlying processes.

A comprehensive review on LED-induced fluorescence in diagnostic pathology

Sensitivity, specificity, mobility, and affordability are important criteria to consider for developing diagnostic instruments in common use. Fluorescence spectroscopy has been demonstrating substantial potential in the clinical diagnosis of diseases and evaluating the underlying causes of pathogenesis. A higher degree of device integration with appropriate sensitivity and reasonable cost would further boost the value of the fluorescence techniques in clinical diagnosis and aid in the reduction of healthcare expenses, which is a key economic concern in emerging markets. Light-emitting diodes (LEDs), which are inexpensive and smaller are attractive alternatives to conventional excitation sources in fluorescence spectroscopy, are gaining a lot of momentum in the development of affordable, compact analytical instruments of clinical relevance. The commercial availability of a broad range of LED wavelengths (255-4600 nm) has opened up new avenues for targeting a wide range of clinically significant molecules (both endogenous and exogenous), thereby diagnosing a range of clinical illnesses. As a result, we have specifically examined the uses of LED-induced fluorescence (LED-IF) in preclinical and clinical evaluations of pathological conditions, considering the present advancements in the field.

Amino acids in inflammatory bowel diseases: Modern diagnostic tools and methodologies

Amino acids are crucial building blocks of living organisms. Together with their derivatives, they participate in many intracellular processes to act as hormones, neuromodulators, and neurotransmitters. For several decades amino acids have been studied for their potential as markers of various diseases, including inflammatory bowel diseases. Subsequent improvements in sample pretreatment, separation, and detection methods have enabled the specific and very sensitive determination of these molecules in multicomponent matrices-biological fluids and tissues. The information obtained from targeted amino acid analysis (biomarker-based analytical strategy) can be further used for early diagnostics, to monitor the course of the disease or compliance of the patients. This review will provide an insight into current knowledge about inflammatory bowel diseases, the role of proteinogenic amino acids in intestinal inflammation and modern analytical techniques used in its diagnosis and disease activity monitoring. Current advances in the analysis of amino acids focused on sample pretreatment, separation strategy, or detection methods are highlighted, and their potential in clinical laboratories is discussed. In addition, the latest clinical data obtained from the metabolomic profiling of patients suffering from inflammatory bowel diseases are summarized with a focus on proteinogenic amino acids.

High Resolution Magic Angle Spinning Proton NMR Study of Alzheimer's Disease with Mouse Models

Alzheimer's disease (AD) is a crippling condition that affects millions of elderly adults each year, yet there remains a serious need for improved methods of diagnosis. Metabolomic analysis has been proposed as a potential methodology to better investigate and understand the progression of this disease; however, studies of human brain tissue metabolomics are challenging, due to sample limitations and ethical considerations. Comprehensive comparisons of imaging measurements in animal models to identify similarities and differences between aging- and AD-associated metabolic changes should thus be tested and validated for future human non-invasive studies. In this paper, we present the results of our highresolution magic angle spinning (HRMAS) nuclear magnetic resonance (NMR) studies of AD and wild-type (WT) mouse models, based on animal age, brain regions, including cortex vs. hippocampus, and disease status. Our findings suggest the ability of HRMAS NMR to differentiate between AD and WT mice using brain metabolomics, which potentially can be implemented in in vivo evaluations.

Flat Disc-Shaped Sampling Probe and Online Re-extraction Apparatus for Mass Spectrometric Analysis of Skin Metabolites: A Proof of Concept

Sweat analysis provides an alternative and noninvasive way of clinical diagnostics. However, sampling and transferring sweat-derived samples to analytical instruments is challenging. In this report, we demonstrate a method utilizing a flat disc-shaped sampling probe, and a compatible re-extraction apparatus coupled online with extractive electrospray ionization (EESI) mass spectrometry (MS). The probe enables sampling of metabolites from a skin area of ∼2.2 cm². The subsequent online re-extraction and analysis by EESI-MS further mitigates matrix effects caused by sweat components, thus eliminating sample preparation steps. The total analysis time is only 6 min. We have optimized the key parameters of the system, including flow rate of the nebulizing gas in ESI, pressure of the nebulizing gas in pneumatic sample nebulizer, flow rate of the solvent in ESI, and composition of extractant. The standard solutions (0.1 mL) were supplemented with 0.04 M sodium chloride to mimic the matrix effect normally observed in sweat samples. The method has been characterized with four chemical standards (positive-ion mode of histidine, leucine, urocanic acid; negative-ion mode of lactic acid). The limits of detection range from 1.09 to 95.9 nmol. We have further demonstrated the suitability of the method for analysis of sweat. An attempt was made to identify some of the recorded signals by product-ion scan and accurate/exact mass matching.

Sample-to-analysis platform for rapid intracellular mass spectrometry from small numbers of cells

Real-time, advanced diagnostics of the biochemical state within cells remains a significant challenge for research and development, production, and application of cell-based therapies. The fundamental biochemical processes and mechanisms of action of such advanced therapies are still largely unknown, including the critical quality attributes that correlate to therapeutic function, performance, and potency and the critical process parameters that impact quality throughout cell therapy manufacturing. An integrated microfluidic platform has been developed for in-line analysis of a small number of cells via direct infusion nano-electrospray ionization mass spectrometry. Central to this platform is a microfabricated cell processing device that prepares cells from limited sample volumes removed directly from cell culture systems. The sample-to-analysis workflow overcomes the labor intensive, time-consuming, and destructive nature of existing mass spectrometry approaches for analysis of cells. By providing rapid, high-throughput analyses of the intracellular state, this platform enables untargeted discovery of critical quality attributes and their real-time, in-process monitoring.

Association of Plasma Branched-Chain and Aromatic Amino Acids with Reduction in Kidney Function Evaluated in Apparently Healthy Adults

The published literature on the association of circulatory branched-chain amino acids (BCAAs) and aromatic amino acids (AAAs) with reduced kidney function is inconsistent or conflicting. Clarification of it might help to better understand the underlying pathophysiology and to determine potential biomarkers for early detection and evaluation of kidney function decline. Our main purpose was to explore and clarify the potential relationships of individual BCAAs and AAAs with estimated glomerular filtration rate (eGFR) decline. We included the data from 2804 healthy subjects and categorized them into three groups based on eGFR tertiles. The associations between individual amino acids and eGFR were explored by covariate-adjusted logistic regression models. There was a progressive increase in the concentrations of BCAAs and AAAs from the upper to the lower tertiles. We revealed significant positive associations of isoleucine, leucine, and phenylalanine with lower tertiles of eGFR in the adjusted models (p < 0.01-0.001). The findings hold a promising potential of using plasma isoleucine, leucine, and phenylalanine levels for evaluation of kidney function decline. Future longitudinal studies should investigate the causal association between altered levels of these amino acids and impaired kidney function and also the utility of the former as potential biomarkers for evaluating the risk and early detection of the latter.

Lipid and metabolite correlation networks specific to clinical and biochemical covariate show differences associated with sexual dimorphism in a cohort of nonagenarians

This study defines and estimates the metabolite-lipidic component association networks constructed from an array of 20 metabolites and 114 lipids identified and quantified via NMR spectroscopy in the serum of a cohort of 355 Italian nonagenarians and ultra-nonagenarian. Metabolite-lipid association networks were built for men and women and related to an array of 101 clinical and biochemical parameters, including the presence of diseases, bio-humoral parameters, familiarity diseases, drugs treatments, and risk factors. Different connectivity patterns were observed in lipids, branched chains amino acids, alanine, and ketone bodies, suggesting their association with the sex-related and sex-clinical condition-related intrinsic metabolic changes. Furthermore, our results demonstrate, using a holistic system biology approach, that the characterization of metabolic structures and their dynamic inter-connections is a promising tool to shed light on the dimorphic pathophysiological mechanisms of aging at the molecular level.

Plasma metabolites changes in male heroin addicts during acute and protracted withdrawal

BACKGROUND

Heroin addiction and withdrawal have been associated with an increased risk for infectious diseases and psychological complications. However, the changes of metabolites in heroin addicts during withdrawal remain largely unknown.

METHODS

A total of 50 participants including 20 heroin addicts with acute abstinence stage, 15 with protracted abstinence stage and 15 healthy controls, were recruited. We performed metabolic profiling of plasma samples based on ultraperformance liquid chromatography coupled to tandem mass spectrometry to explore the potential biomarkers and mechanisms of heroin withdrawal.

RESULTS

Among the metabolites analyzed, omega-6 polyunsaturated fatty acids (linoleic acid, dihomo-gamma-linolenic acid, arachidonic acid, n-6 docosapentaenoic acid), omega-3 polyunsaturated fatty acids (docosahexaenoic acid, docosapentaenoic acid), aromatic amino acids (phenylalanine, tyrosine, tryptophan), and intermediates of the tricarboxylic acid cycle (oxoglutaric acid, isocitric acid) were significantly reduced during acute heroin withdrawal. Although majority of the metabolite changes could recover after months of withdrawal, the levels of alpha-aminobutyric acid, alloisoleucine, ketoleucine, and oxalic acid do not recover.

CONCLUSIONS

In conclusion, the plasma metabolites undergo tremendous changes during heroin withdrawal. Through metabolomic analysis, we have identified links between a framework of metabolic perturbations and withdrawal stages in heroin addicts.

Homocysteine fibrillar assemblies display cross-talk with Alzheimer's disease β-amyloid polypeptide

High levels of homocysteine are reported as a risk factor for Alzheimer's disease (AD). Correspondingly, inborn hyperhomocysteinemia is associated with an increased predisposition to the development of dementia in later stages of life. Yet, the mechanistic link between homocysteine accumulation and the pathological neurodegenerative processes is still elusive. Furthermore, despite the clear association between protein aggregation and AD, attempts to develop therapy that specifically targets this process have not been successful. It is envisioned that the failure in the development of efficacious therapeutic intervention may lie in the metabolomic state of affected individuals. We recently demonstrated the ability of metabolites to self-assemble and cross-seed the aggregation of pathological proteins, suggesting a role for metabolite structures in the initiation of neurodegenerative diseases. Here, we provide a report of homocysteine crystal structure and self-assembly into amyloid-like toxic fibrils, their inhibition by polyphenols, and their ability to seed the aggregation of the AD-associated β-amyloid polypeptide. A yeast model of hyperhomocysteinemia indicates a toxic effect, correlated with increased intracellular amyloid staining that could be rescued by polyphenol treatment. Analysis of AD mouse model brain sections indicates the presence of homocysteine assemblies and the interplay between β-amyloid and homocysteine. This work implies a molecular basis for the association between homocysteine accumulation and AD pathology, potentially leading to a paradigm shift in the understanding of AD initial pathological processes.

Metabolomic Profiling of Aqueous Humor and Plasma in Primary Open Angle Glaucoma Patients Points Towards Novel Diagnostic and Therapeutic Strategy

Glaucoma is the second leading cause of blindness globally characterized by progressive loss of retinal ganglion cells (RGCs) and irreversible visual deficiency. As the most common type of glaucoma, primary open angle glaucoma (POAG) is currently an unmet medical need with limited therapy by lowering intraocular pressure (IOP). However, some patients continue to progress even though their IOP are controlled. Although early diagnosis and prompt treatment are crucial in preventing irreversible visual impairment, there are currently no biomarkers for screening POAG. Metabolomics has the advantages of illustrating the final downstream products of the genome and establishing the closest link to the phenotype. So far, there is no study investigating the metabolomic profiles in both aqueous humor and plasma of POAG patients. Therefore, to explore diagnostic biomarkers, unveil underlying pathophysiology and potential therapeutic strategies, a widely targeted metabolomic approach was applied using ultrahigh-resolution mass spectrometry with C18 liquid chromatography to characterize the metabolomic profiles in both aqueous humor and plasma of 28 POAG patients and 25 controls in our study. Partial least squares-discriminant analysis (PLS-DA) was performed to determine differentially expressed metabolites (DEMs) between POAG and age-matched controls. The area under the receiver operating characteristic curve (AUC) was calculated to assess the prediction accuracy of the DEMs. The correlation of DEMs with the clinical parameters was determined by Pearson correlation, and the metabolic pathways were analyzed using MetaboAnalyst 4.0. PLS-DA significantly separated POAG from controls with 22 DEMs in the aqueous humor and 11 DEMs in the plasma. Additionally, univariate ROC analysis and correlation analysis with clinical parameters revealed cyclic AMP (AUC = 0.87), 2-methylbenzoic acid (AUC = 0.75), 3'-sialyllactose (AUC = 0.73) in the aqueous humor and N-lac-phe (AUC = 0.76) in the plasma as potential biomarkers for POAG. Moreover, the metabolic profiles pointed towards the alteration in the purine metabolism pathway. In conclusion, the study identified potential and novel biomarkers for POAG by crosslinking the metabolomic profiles in aqueous humor and plasma and correlating with the clinical parameters. These findings have important clinical implications given that no biomarkers are currently available for glaucoma in the clinic, and the study provided new insights in exploring diagnostic biomarkers and potential therapeutic strategies of POAG by targeting metabolic pathways.

Metabolic profiling of 19 amino acids in triptolide-induced liver injured rats by gas chromatography-triple quadrupole mass spectrometry

The liver is an important organ for amino acid metabolism, and its damage can be reflected in the changes of amino acid level in the body. Triptolide (TP) has broad anti-inflammatory and anti-tumor activities, but its clinical application is limited due to hepatotoxicity. In this work, a simple, accurate and sensitive gas chromatography-triple quadrupole mass spectrometry (GC-QqQ-MS/MS) method was developed and validated for evaluating the serum levels of amino acids from control and TP-induced liver injured rats, and chemometric analysis was employed for amino acid metabolic profiles analysis. It was found that 11 amino acids showed significant changes after TP administration, and they were mainly involved in 5 metabolic pathways that are phenylalanine, tyrosine and tryptophan biosynthesis, alanine, aspartate and glutamate metabolism, glutamine and glutamate metabolism, phenylalanine metabolism and arginine biosynthesis. Five amino acids including tyrosine, glutamine, glutamic acid, tryptophan and alanine were identified as biomarkers of TP hepatotoxicity by further analysis. These results indicated that the novel amino acid metabolic profiling study based on the GC-QqQ-MS/MS provided not only exact concentrations of serum amino acids, but also a prospective methodology for evaluation of chemically induced liver injury.

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.

Detection of Glycine as a Model Protein in Blood Serum Using 2D-IR Spectroscopy

Glycine (Gly) is used as a model system to evaluate the ability of ultrafast two-dimensional infrared (2D-IR) spectroscopy to detect and quantify the low-molecular-weight proteinaceous components of blood serum. Combining data acquisition schemes to suppress absorption bands of H₂O that overlap with the protein amide I band with analysis of peak patterns appearing in the off-diagonal region of the 2D-IR spectrum allows separation of the Gly spectral signature from that of the dominant protein fraction of serum in a transmission-mode 2D-IR measurement without any sample manipulation, e.g., filtration or drying. 2D-IR spectra of blood serum samples supplemented with varying concentrations of Gly were obtained, and a range of data analysis methods compared, leading to a detection limit of ∼3 mg/mL for Gly. The reported methodology provides a platform for a critical assessment of the sensitivity of 2D-IR for measuring the concentrations of amino acids, peptides, and low-molecular-weight proteins present in serum samples. We conclude that, in the case of several clinically relevant diagnostic molecules and their combinations, the potential exists for 2D-IR to complement IR absorption methods as the benefits of the second frequency dimension offered by 2D-IR spectroscopy outweigh the added technical complexity of the measurement.

Metabolic profiling reveals dysregulated lipid metabolism and potential biomarkers associated with the development and progression of Fragile X-Associated Tremor/Ataxia Syndrome (FXTAS)

Fragile X-associated Tremor/Ataxia Syndrome (FXTAS) is a neurodegenerative disorder associated with the FMR1 premutation. It is currently unknown when, and if, individual premutation carriers will develop FXTAS. Thus, with the aim of identifying biomarkers for early diagnosis, development, and progression of FXTAS, we performed global metabolomic profiling of premutation carriers (PM) who, as part of an ongoing longitudinal study, emerged into two distinct categories: those who developed symptoms of FXTAS (converters, CON) at subsequent visits and those who did not (non-converters, NCON) and we compared to age-matched healthy controls (HC). We assessed CGG repeat allele size by Southern Blot and PCR analysis. Metabolomic profile was obtained by ultra-performance liquid chromatography, accurate mass spectrometer, and an Orbitrap mass analyzer. In this study we found 47 metabolites were significantly dysregulated between HC and the premutation groups (PM). Importantly, we identified 24 metabolites that showed significant changes in expression in the CON as compared to the NCON both at V1 and V2, and 70 metabolites in CON as compared to NCON but only at V2. These findings suggest the potential role of the identified metabolites as biomarkers for early diagnosis and for FXTAS disease progression, respectively. Interestingly, the majority of the identified metabolites were lipids, followed by amino acids. To our knowledge, this the first report of longitudinal metabolic profiling and identification of unique biomarkers of FXTAS. The lipid metabolism and specifically the sub pathways involved in mitochondrial bioenergetics, as observed in other neurodegenerative disorders, are significantly altered in FXTAS.

Integrative Metabolomic and Metallomic Analysis in a Case-Control Cohort With Parkinson's Disease

Parkinson's disease (PD) is a neurodegenerative disease with a complex etiology. Several factors are known to contribute to the disease onset and its progression. However, the complete underlying mechanisms are still escaping our understanding. To evaluate possible correlations between metabolites and metallomic data, in this research, we combined a control study measured using two different platforms. For the different data sources, we applied a Block Sparse Partial Least Square Discriminant Analysis (Block-sPLS-DA) model that allows for proving their relation, which in turn uncovers alternative influencing factors that remain hidden otherwise. We found two groups of variables that trace a strong relationship between metallomic and metabolomic parameters for disease development. The results confirmed that the redox active metals iron (Fe) and copper (Cu) together with fatty acids are the major influencing factors for the PD. Additionally, the metabolic waste product p-cresol sulfate and the trace element nickel (Ni) showed up as potentially important factors in PD. In summary, the data integration of different types of measurements emphasized the results of both stand-alone measurements providing a new comprehensive set of information and interactions, on PD disease, between different variables sources.

Reduction of Glycolysis Intermediate Concentrations in the Cerebrospinal Fluid of Alzheimer's Disease Patients

The profile of 122 metabolites in the cerebrospinal fluid (CSF) of patients suffering from Alzheimer's disease (AD) and controls was studied. Among the 122 metabolites analyzed, 61 could be detected. Statistically significant differences between the AD and control group were only detected for metabolites of the glycolysis. Thus, accurate quantification of 11 glycolytic metabolites was done. We detected a significant reduction of five of them, namely phosphoenolpyruvate, 2-phosphoglycerate, 3-phosphoglycerate, pyruvate and dihydroxyacetone phosphate in the AD CSF compared to controls. These results correlate with the known reduction of glucose metabolism in the brain of patients with AD and indicate that metabolic analysis of the central carbon metabolism can be a potential tool in AD diagnostic. Although the Receiver operating characteristic (ROC) analyses of the metabolites do not reach the level of the diagnostic informativity of AD biomarkers, the combination of specific glycolysis metabolites with the established biomarkers may lead to an improvement in sensitivity and specificity.