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Cordyceps fumosorosea is a common species within the Cordyceps genus. In this study, the protective effect of Cordyceps fumosorosea mycelium was investigated to clarify the potential mechanism of alleviating acute lung injury in mice using serum metabolomic analysis, which could provide a theoretical basis for the clinical application of C. fumosorosea. Sixty mice were divided into six groups (NS, LPS, MIX, COR, COC and DMX). Lung cell nuclei were analyzed using hematoxylin and eosin staining and cellular changes were observed using transmission electron microscopy (TEM). Metabolomic analyses using liquid chromatography-mass spectrometry (LC-MS) were used to identify various compounds. In all six groups, lung nuclear inflammation was observed in the COR, COC and DMX groups, whereas the NS, LPS and MIX groups showed no cellular changes, indicating good health. Metabolomic analysis using LC-MS identified 1607 compounds across various classes. Statistical analyses, including the coefficient of variation and OPLS-DA, revealed distinct metabolic proles, indicating significant changes after the consumption of C. fumosorosea mycelia. Lipids constituted the largest proportion (30.37%) of the 30 identified classes and subclasses of metabolites. A total of 617 differentially accumulated metabolites (DAMs) were identified, both unique and shared between comparisons. Metabolite analysis identified 617 differentially accumulated metabolites, with 493 common to the LPS vs. MIX group, 75 in the LPS vs. NS group and 49 in the LPS vs. NS group and LPS vs. MIX group. This comprehensive investigation suggests that C. fumosorosea mycelia treatment holds promise as a therapeutic intervention for lung injury, influencing both the histopathological (lung) features and serum metabolic profiles. [ABSTRACT FROM AUTHOR]

Objective: To profile the serum metabolites and metabolic pathways in colorectal cancer (CRC) patients associated with spleen-deficiency and qistagnation syndrome (SDQSS) or damp-heat syndrome (DHS). Methods: From May 2020 to January 2021, CRC patients diagnosed with traditional Chinese medicine (TCM) syndromes of SDQSS or DHS were enrolled. The clinicopathological data of the SDQSS and DHS groups were compared. The serum samples were analyzed by liquid chromatography-mass spectrometry (LC-MS). The variable importance in the projection >1, fold change ≥3 or ≤0.333, and P value ≤0.05 were used to identify differential metabolites between the two groups. Furthermore, areas under the receiver operating characteristic (ROC) curve > 0.9 were applied to select biomarkers with good predictive performance. The enrichment metabolic pathways were searched through the database of Kyoto Encyclopedia of Genes and Genomes. Results: 60 CRC patients were included (30 SDQSS and 30 DHS). The level of alanine aminotransferase was marginally significantly higher in the DHS group than the SDQSS group (P = 0.051). The other baseline clinicopathological characteristics were all comparable between the two groups. 23 differential serum metabolites were identified, among which 16 were significantly upregulated and 7 were significantly down-regulated in the SDQSS group compared with the DHS group. ROC curve analysis showed that (S)-3-methyl-2-oxopentanoic acid, neocembrene, 1-aminocyclopropanecarboxylic acid, 3- methyl-3-hydroxypentanedioate, and nicotine were symbolic differential metabolites with higher predictive power. The top five enrichment signalling pathways were valine, leucine and isoleucine biosynthesis; lysosome; nicotine addiction; fructose and mannose metabolism; and pertussis. Conclusion: Our study identifies the differential metabolites and characteristic metabolic pathways among CRC patients with SDQSS or DHS, offering the possibility of accurate and objective syndrome differentiation and TCM treatment for CRC patients. [ABSTRACT FROM AUTHOR]

Objective： To analyze the serum metabolite compositions of the patients with esophageal squamous cell carcinoma (ESCC), to screen out the potential differential metabolites, and to explore the relationship between the occurrence of ESCC and energy metabolism, and to provide the useful energy metabolites for the early diagnosis of ESCC. Methods The serum samples of the ESCC patients and healthy volunteers were collected and divided into ESCC group and control group, and there were 7 cases in each group. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was used to detect the serum metabolites of the subjects in two groups；partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA) models were used to identify the differences in serum metabolites of the subjects between ESCC group and control group, and they were classified according to the chemical classification of serum metabolites; targeted metabolomics analysis on serum energy metabolites was conducted based on the multi-response monitoring (MRM) mode to further identify the significantly differential energy metabolites and their pathways. Results A total of 266 metabolites were identified in the serum samples of the subjects in ESCC group and control group with the positive and negative ion modes, and there were 164 and 102 metabolites identified with the above two modes, respectively. The univariate statistical analysis results showed that there were significant differences in serum metabolites of the subjects between ESCC group and control group. Among the metabolites with chemical classification, lipids and lipid-like molecules accounted for the highest proportion (18.421%) . Three significantly different energy metabolites in ESCC group were found, and the expression levels of L-malic acid and isocitric acid were increased and the expression level of cyclic adenosine monophosphate (cAMP) was decreased. Conclusion There are differences in the expressions of serum energy metabolites between the ESCC patients and healthy controls, and the occurrence of ESCC is related to the energy metabolism. [ABSTRACT FROM AUTHOR]

Neuropathic pain (NP) is a chronic and intractable disease that is widely present in the general population. It causes painful behavior and even mood changes such as anxiety and depression by altering the metabolism of substances. However, there have been limited metabolomics studies conducted in relation to neuropathic pain. Therefore, in this study, the effects of NP on metabolites in serum and the dorsal root ganglion (DRG) were investigated using a non-targeted metabolomics approach detected by gas chromatography–mass spectrometry (GC-MS) and liquid chromatography–mass spectrometry (LC-MS) to uncover differential metabolites and affected metabolic pathways associated with NP. Sixty mice were divided into the following two groups: a chronic constriction injury (CCI) of the sciatic nerve group and a sham group (n = 30, each). After 7 days of CCI modeling, the metabolite profiles of serum and the DRG were analyzed using GC/LC-MS for both the CCI and sham groups of mice. Multivariate analysis revealed differential metabolites and altered metabolic pathways between the CCI and sham groups. In the CCI group, our findings provided insights into the complex phospholipid, amino acid and acylcarnitine metabolic perturbations of DRG metabolism. In addition, phospholipid metabolic disorders and impaired glucose metabolism were observed in the serum. Moreover, the metabolic differences in the DRG and serum were correlated with each other. The results from this untargeted metabolomics study provide a perspective on the metabolic impact of NP on serum and the DRG. [ABSTRACT FROM AUTHOR]

Differential diagnosis of pulmonary nodules detected by computed tomography (CT) remains a challenge in clinical practice. Here, we characterize the global metabolomes of 480 serum samples including healthy controls, benign pulmonary nodules, and stage I lung adenocarcinoma. The adenocarcinoma demonstrates a distinct metabolomic signature, whereas benign nodules and healthy controls share major similarities in metabolomic profiles. A panel of 27 metabolites is identified in the discovery cohort (n = 306) to distinguish between benign and malignant nodules. The discriminant model achieves an AUC of 0.915 and 0.945 in the internal validation (n = 104) and external validation cohort (n = 111), respectively. Pathway analysis reveals elevation in glycolytic metabolites associated with decreased tryptophan in serum of lung adenocarcinoma vs benign nodules and healthy controls, and demonstrates that uptake of tryptophan promotes glycolysis in lung cancer cells. Our study highlights the value of the serum metabolite biomarkers in risk assessment of pulmonary nodules detected by CT screening. Detection of lung adenocarcinoma through serum sampling could be an alternative to CT scanning. Here, the authors use global metabolomics to create a 27 metabolite signature, which showed accuracy in detection in an external validation cohort. [ABSTRACT FROM AUTHOR]

• Pathophysiological mechanism of pure coronary artery ectasia. • The metabolomic analysis revealed 10 potential biomarkers that can provide an early diagnosis of pure coronary artery ectasia. • Systemic inflammation and oxidative stress in CAE. Coronary artery ectasia (CAE) is a cardiovascular disorder characterized by abnormal coronary artery dilation and disturbed coronary flow. The exact pathophysiology of CAE is still unclear. We aimed to investigate differences in metabolomic profiles between CAE patients and healthy controls. Radial artery blood samples were collected from 14 pure CAE patients, 12 mixed CAE patients with atherosclerosis, and 14 controls with normal angiography. Differential serum metabolites were analyzed by untargeted ultra-high performance liquid chromatography-mass spectrometry. Serum ICAM-1, VEGF, ROS, and glutathione levels were also measured. Ten metabolites distinguished pure CAE patients from controls and mixed CAE, including 1-cyano-2-hydroxy-3-butene, 2,3-dihydro-6-methyl-5-(5-methyl-2-furanyl)-1H-pyrrolizine, 2-propionylpyrrole, 2-pyrrolidinone, 3-(2-furanylmethylene)pyrrolidine, D-alanine, furanofukinin, o-ethyltoluene, rotundine A, and SM(d18:1/18:1(9Z)). Related metabolic pathways include amino acid metabolism, sphingolipid dysfunction, energy metabolism, mitochondrial dysfunction, and oxidative stress. Serum concentrations of ICAM-1, VEGF and ROS were significantly elevated in CAE patients compared to controls, while glutathione decreased significantly in CAE patients. Moreover, ICAM-1 levels were negatively correlated with 2-propionylpyrrole, and VEGF levels were negatively correlated with SM(d18:1/18:1(9Z)), while GSH and ROS levels were correlated with the abundance of SM(d18:1/18:1(9Z)), further confirming systemic inflammation and oxidative stress in CAE. This is the first report describing differential serum metabolomic profiles of pure CAE patients compared to mixed CAE and healthy controls, which revealed 10 potential biomarkers that can provide an early diagnosis of pure CAE. These discriminatory metabolites and related metabolic pathways can help to better understand the pathogenesis of pure CAE. [ABSTRACT FROM AUTHOR]

The majority of metabolomics studies to date have utilised blood serum or plasma, biofluids that do not necessarily address the full range of patient pathologies. Here, correlations between serum metabolites, salivary metabolites and sebum lipids are studied for the first time. 83 COVID-19 positive and negative hospitalised participants provided blood serum alongside saliva and sebum samples for analysis by liquid chromatography mass spectrometry. Widespread alterations to serum-sebum lipid relationships were observed in COVID-19 positive participants versus negative controls. There was also a marked correlation between sebum lipids and the immunostimulatory hormone dehydroepiandrosterone sulphate in the COVID-19 positive cohort. The biofluids analysed herein were also compared in terms of their ability to differentiate COVID-19 positive participants from controls; serum performed best by multivariate analysis (sensitivity and specificity of 0.97), with the dominant changes in triglyceride and bile acid levels, concordant with other studies identifying dyslipidemia as a hallmark of COVID-19 infection. Sebum performed well (sensitivity 0.92; specificity 0.84), with saliva performing worst (sensitivity 0.78; specificity 0.83). These findings show that alterations to skin lipid profiles coincide with dyslipidaemia in serum. The work also signposts the potential for integrated biofluid analyses to provide insight into the whole-body atlas of pathophysiological conditions. [ABSTRACT FROM AUTHOR]

Background: Gallic acid (GA) is a natural small-molecule polyphenol having a wide range of pharmacological activities. Until now, some works have studied the effect and the mechanisms of GA against inflammation. However, whether or how gallic acid regulates the downstream metabolic disorder against acute inflammation remains unclear. The present study explored the protective effect and the potential mechanism of GA on acute inflammation through the metabolomics approach. Methods: An acute inflammation rat model was induced by local injection of carrageenin. Local swelling on paw and serum tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6) were assessed in Control, Model and Gallic acid groups, respectively. Serum metabolomics based on high-performance liquid chromatography coupled with mass spectrometry (HPLC-MS) was also established to collect rats' metabolic profiles and explore the metabolic changes related to GA pretreatment. Results: Compared to the Modal group, local pain, redness, and swelling induced by carrageenin were significantly alleviated in GA groups in addition to the dose-dependent decreases of TNF-α and IL-6. Metabolomics analysis found significant alterations in metabolic signatures between the carrageenin-induced inflammation and control groups. Twelve potential biomarkers were further identified in acute inflammation by principal component analysis (PCA) and partial least squares discrimination analysis (PLS-DA). In addition, when rats were pretreated with gallic acid, serum levels of eleven biomarkers were observed to restore partially. Metabolic pathway and networks analysis revealed that GA might invert the pathological process of acute inflammation by regulating the key biomarkers involved in linoleic acid metabolism, ascorbate and aldarate metabolism, pentose and glucuronate interconversions, and arachidonic acid (AA) metabolism pathways. Conclusion: The study elucidates the protective effect of gallic acid against acute inflammation and its possible regulating mechanism from a metabolomic perspective. These results could provide a theoretical basis for clarifying gallic acid's mechanism and potential medicinal value in curing inflammation disorder in the clinic. [ABSTRACT FROM AUTHOR]

Background: Nonalcoholic fatty liver disease (NAFLD) is a common metabolic disease that affects 20-30% of individuals worldwide. Liver puncture remains the gold standard for the diagnosis of liver diseases despite limitations regarding invasive nature and sample variability. It is of great clinical significance to find noninvasive biomarkers to detect and predict NAFLD.Objective: The aims of this study were to identify potential serum markers in individuals with early-stage NAFLD and to advance the mechanistic understanding of this disease using a high-throughput mass spectrometry-based untargeted metabolomics approach.Methods: One hundred and twelve patients with early-stage NAFLD aged 18-55 were recruited according to the guidelines. The control group included 112 healthy participants. The demographic, anthropometric, clinical and laboratory data of all participants were systematically collected. Serum samples were obtained after an overnight fast. The comprehensive serum metabolomic analysis was performed by ultra-performance liquid chromatography-Orbitrap mass spectrometry. The resultant data was processed by Compound Discover and SIMCA-P software to validate the potential biomarkers. Significantly altered metabolites were evaluated by variable importance in projection value (VIP > 1) and ANOVA (p < 0.01). Pathway analysis was performed using MetaboAnalyst 4.0.Results: The liver function test of early NAFLD patients showed no statistical differences to control group (p > 0.05). However, obvious differences in blood lipids were observed between subjects with NAFLD and controls (p < 0.001). In total, 55 metabolites showed significant changes in experimental group were identified. The area under curve (AUC) values deduced by receiver operating curve (ROC) analysis indicated that these newly identified biomarkers have high predictability and reliability. Of these, 15 metabolites with AUC greater than 0.9 were of great diagnostic value in early NAFLD patients.Conclusion: In this study, a total of 15 serum metabolites were found to strongly associate with early NAFLD. These biomarkers may have great clinical significance in the early diagnosis of NAFLD, as well as to follow response to therapeutic interventions. [ABSTRACT FROM AUTHOR]

Objective: The objective of this study was to report CYB5A deficiency, to discuss the contribution of steroid metabolomics to diagnosis and interpretation, and to highlight the presence of testicular microlithiasis. Methods: Two siblings with ambiguous genitalia at birth were later found to carry novel CYB5A variants, with resulting isolated 17, 20 lyase deficiency. We compared urine steroid data obtained between birth and adulthood with that from other cases. Results: Neonatal urine steroid profiles show a relative increase of 16-hydroxylated pregnenolone metabolites. Thereafter, there are no distinguishing features until puberty, when sex steroid deficiency drives gonadotrophin production, resulting in marked increases of 17-hydroxyprogesterone metabolites derived from the gonads. This excess may be revealed pre-pubertally by gonadotrophin stimulation testing. Novel findings are first, a considerable capacity for DHEA synthesis in the neonatal period compared to childhood and adulthood, suggesting that DHEAS production is much less dependent on CYB5A at birth; second, no consistent change in "backdoor pathway" intermediates; third, side chain cleavage of cortisol is largely unaffected, supporting the existence of a different lyase not dependent on CYB5A; fourth, increased 17-hydroxyprogesterone metabolites and very low androgen metabolites are diagnostic post-pubertally. Conclusion: This is the fourth disease-causing variant in CYB5A in isolated 17, 20 lyase deficiency and the first associated with testicular microlithiasis. Establishing a biochemical diagnosis pre-pubertally should now be possible using urine steroid profiling, supported by synacthen and gonadotrophin stimulation testing. We recommend liquid chromatography-mass spectrometry/mass spectrometry rather than immunoassay for serum steroid analysis, early methaemoglobin measurement and surveillance should testicular microlithiasis be detected. [ABSTRACT FROM AUTHOR]

Abstract Gut microbiota–host co-metabolites play an essential role in maintaining homeostasis, and their concentration changes are closely related to a variety of diseases. Developing a targeted metabolomics analytical platform for these co-metabolites will help to elucidate the relationship between intestinal flora and host. Here we present a simple and sensitive liquid chromatography–tandem mass spectrometry method for the analysis of nine gut microbiota–host co-metabolites in rat serum, urine and feces. The compounds were separated on a reversed-phase C 18 column using gradient elution with a solvent system consisting of methanol and water (containing 0.05% formic acid) and a 7-min run time. All of the calibration curves exhibited good linear relationships (R2 ≥ 0.9984, Percent Residual Accuracy ≥93.27%). The intra- and interday precision, expressed as relative standard deviation (RSD), was ≤ 14.84%. The accuracy was within 100 ± 13.16% for all analytes. The recovery of the nine compounds in biological samples was ≥ 85.80% with an appropriate RSD (≤12.04%). The validated method was successfully applied to monitor the global changes of these metabolites in obesity. Taken together, these results demonstrate that the method can simultaneously determine the nine co-metabolites in multiple biological matrices and is an essential part of the targeted metabolomics analytical platform, which may become an approach to evaluate the occurrence, development and therapeutic effects of metabolic diseases. Highlights • Targeted analysis was developed for 9 gut microbiota–host co-metabolites. • The developed LC-MS/MS method is suitable for high-throughput quantitative analysis. • Changes of 9 metabolites in serum, urine and feces can be depicted with this method. • The method is helpful for the study of mechanisms of gut microbiota–host interaction. • Development of this method improved the targeted metabolomics analytical platform. [ABSTRACT FROM AUTHOR]

Abstract Objective To compare the serum glycerophospholipid levels in the inflammatory subtypes of asthma by using targeted metabolomic analysis. Methods Demographic and clinical data were collected from 51 patients with asthma between January 2015 and December 2015. Routine blood and sputum induction tests were performed. Eosinophilic asthma was defined as induced sputum containing ≥ 3% eosinophils, and neutrophilic asthma, as induced sputum containing ≥ 71% neutrophils. Serum metabolic glycerophospholipid profile was determined by liquid chromatography-mass spectrometry. Differences in glycerophospholipid levels between eosinophilic and non-eosinophilic asthma and between neutrophilic and non-neutrophilic asthma were analyzed using partial least squares discriminant analysis. Results The serum lysophosphatidylglycerol level was significantly higher in the group with ≥ 3% eosinophils in sputum than in the group with < 3% eosinophils in sputum. The area under the receiver-operating characteristic curve was ≥ 70%. There was no significant difference in the serum metabolic glycerophospholipid profile between the group with sputum neutrophils ≥ 71% and the group with sputum neutrophils < 71%. Conclusion Serum lysophosphatidylglycerol is produced abundantly in eosinophilic asthma and may be a biomarker of eosinophilic asthma. This information is helpful for identifying and tailoring treatment for the common asthma subtypes. [ABSTRACT FROM AUTHOR]

Cerebrovascular stenosis (CVS) is the main cause of ischemic stroke, which greatly threatens human life. Hence, it's important to perform early screenings for CVS. Metabolomics is an emerging omics approach that has great advantages in disease screening and diagnosis. Therefore, we aim to elucidate the correlation between CVS and metabolomics, which can aid in conducting CVS screening at an early stage. Patients with CVS in Beijing Hospital were included in the study. A total of 36 participants, including 18 patients diagnosed with CVS and 18 healthy individuals, were recruited at Beijing Hospital between May 2022 and October 2021. The serum samples were analyzed for liquid chromatography-tandem mass spectrometry (LC-MS/MS). Then, multivariate statistical methods, including principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) were performed. Differential metabolites were obtained and demonstrated by volcano plot and heatmap. The study recruited 36 participants, including 18 patients with CVS and 18 healthy participants. A total of 150 metabolites were identified. Multivariate statistical analysis revealed significant differences between patients and healthy participants. Furthermore, 30 serum metabolites levels differed significantly between two groups. Differential metabolites were enriched in phenylalanine, tyrosine, and tryptophan biosynthesis; primary bile acid biosynthesis, and other pathways. This study identified differential metabolites in patients with CVS and elucidated the relevant metabolic pathways. Thus, these findings aid in the study of the pathogenesis of CVS and its early diagnosis. The datasets generated for this study are available on request to the corresponding author. ● Early screening for cerebrovascular stenosis (CVS) is important to prevent stroke-related mortality. ● Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to identify differential metabolites in CVS patients. ● Significant metabolic differences were found between CVS patients and healthy participants. ● Differential metabolites enrichment analysis provides valuable insights into CVS pathogenesis and early management. [ABSTRACT FROM AUTHOR]

Identification of the metabolites is an essential step in metabolomics study to interpret the regulatory mechanism of pathological and physiological processes. However, it is still difficult in LC-MSn-based studies because of the complexity of mass spectrometry, chemical diversity of metabolites, and deficiency of standards database. In this work, a comprehensive strategy is developed for accurate and batch metabolite identification in nontargeted metabolomics studies. First, a well-defined procedure was applied to generate reliable and standard LC-MS2 data, including tR, MS1, and MS2 information at a standard operational procedure. An in-house database including about 2000 metabolites was constructed and used to identify the metabolites in nontargeted metabolic profiling by retention time calibration using internal standards, precursor ion alignment and ion fusion, auto-MS2 information extraction and selection, and database batch searching and scoring. As an application example, a pooled serum sample was analyzed to deliver the strategy, and 202 metabolites were identified in the positive ion mode. It shows our strategy is useful for LC-MSn-based nontargeted metabolomics study. [ABSTRACT FROM AUTHOR]

Abstract Migraine is a highly disabling primary headache associated with a high socioeconomic burden and a generally high prevalence. The clinical management of migraine remains a challenge. This study was undertaken to identify potential serum biomarkers of migraine. Using Liquid Chromatography coupled to Mass Spectrometry (LC-MS), the metabolomic profile of migraine was compared with healthy individuals. Principal component analysis (PCA) and Orthogonal partial least squares-discriminant analysis (orthoPLS-DA) showed the metabolomic profile of migraine is distinguishable from controls. Volcano plot analysis identified 10 serum metabolites significantly decreased during migraine. One of these was serotonin, and the other 9 were amino acids. Pathway analysis and enrichment analysis showed tryptophan metabolism (serotonin metabolism), arginine and proline metabolism, and aminoacyl-tRNA biosynthesis are the three most prominently altered pathways in migraine. ROC curve analysis indicated Glycyl- l -proline, N -Methyl- dl -Alanine and l -Methionine are potential sensitive and specific biomarkers for migraine. Our results show Glycyl- l -proline, N -Methyl- dl -Alanine and l -Methionine may be as specific or more specific for migraine than serotonin which is the traditional biomarker of migraine. We propose that therapeutic manipulation of these metabolites or metabolic pathways may be helpful in the prevention and treatment of migraine. Graphical abstract Image 1 Highlights • Serotonin and 9 amino acids are significantly decreased during migraine. • Tryptophan metabolism, arginine and proline metabolism, and aminoacyl-tRNA biosynthesis are the three most prominently pathways in migraine. • Glycyl- l -proline, N -Methyl- dl -Alanine and l -Methionine are potential sensitive and specific biomarkers for migraine. [ABSTRACT FROM AUTHOR]

Objectives Data from studies performed in Japanese and Korean populations suggest that free amino acid profiles have the potential to aid in non-small cell lung cancer (NSCLC) detection. However, there is still no data regarding abnormalities of free amino acids and their usefulness in NSCLC detection in European populations. The aim of the study was an evaluation of utility of amino acid profiles in NSCLC detection in Polish patients. Materials and methods Levels of 31 free amino acids were determined in 153 serum samples applying a liquid chromatography-tandem mass spectrometry-based methodology. Patients with I stage lung cancer represented a significant part of the studied group (46.7%). The obtained metabolite profiles along with clinical data were subjected to multivariate statistical tests. Results The presented study indicated that the increased serum level of phenylalanine and decreased level of citrulline are among the most robust cancer signatures in blood of NSCLC group. In addition, increased levels of aspartic acid and β-alanine were also recognized as important features of NSCLC. Amino acid selected based on studies of Asian patients were found to have insufficient specificity in NSCLC detection in the studied population. Therefore, we proposed a new set of 6 amino acids (aspartic acid, β-alanine, histidine, asparagine, phenylalanine and serine), which ensured higher accuracy in sample classification (from 90.3% to 77.1% depending of histological type). Conclusion We indicated that some of the free amino acid alterations occur in serum of NSCLC patients in early stage of disease and thus they can be valuable components of a blood multi-marker panel for NSCLC detection. [ABSTRACT FROM AUTHOR]

Amino acids, neurotransmitters, purines, and pyrimidines are bioactive molecules that play fundamental roles in maintaining various physiological functions. Their metabolism is closely related to the health, growth, development, reproduction, and homeostasis of organisms. Most recently, comprehensive measurements of these metabolites have shown their potential as innovative approaches in disease surveillance or drug intervention. However, simultaneous measurement of these metabolites presents great difficulties. Here, we report a novel quantitative method that uses hydrophilic interaction ultra-high-performance liquid chromatography-tandem mass spectrometry (HILIC-UPLC-MS/MS), which is highly selective, high throughput, and exhibits better chromatographic behavior than existing methods. The developed method enabled the rapid quantification of 37 metabolites, spanning amino acids, neurotransmitters, purines, and pyrimidines pathways, within 6.5 min. The compounds were separated on an ACQUITY UPLC® BEH Amide column. Serum and brain homogenate were extracted by protein precipitation. The intra- and interday precision of all of the analytes was less than 11.34 %, and the accuracy was between −11.74 and 11.51 % for all quality control (QC) levels. The extraction recoveries of serum ranged from 84.58 % to 116.43 % and those of brain samples from 80.80 % to 119.39 %, while the RSD was 14.61 % or less for all recoveries. This method was used to successfully characterize alterations in the rat brain and, in particular, their dynamics in serum. The following study was performed to simultaneously test global changes of these metabolites in a serotonin antagonist p-chlorophenylalanine (PCPA)-induced anxiety and insomnia rat model to understand the effect and mechanism of PCPA. Taken together, these results show that the method is able to simultaneously monitor a large panel of metabolites and that this protocol may represent a metabolomic method to diagnose toxicological and pathophysiological states. [Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]

Microbiota-host co-metabolites are well-known to play important physiological roles, and their dysregulation has been found to be closely related to various diseases, including but not limited to inflammatory disorders. We developed herein an original and feasible method using ultra performance liquid chromatography—tandem mass spectrometry (UPLC–MS/MS). The method developed enables rapid quantification of 11 key gut microbiota-host co-metabolites spanning the succinate, phenylacetylglutamine, hippurate and trimethylamine metabolic pathways within 10 min. With this method, we were able to simultaneously monitor inflammation-induced alterations of these metabolites in rat serum, urine and feces matrices. The measured levels for this panel of endogenous metabolites ranged from 0.001 to 172.8 μg mL −1 . The intra- and inter-day precision of three analytes was less than 13.1% and the accuracy was between −13.0 to 11.2% for all QC levels. The extraction recoveries in serum ranged from 85.4 to 103.2%, while the RSD was 9.0% or less for all recoveries. In addition, extraction recoveries of 11 analytes in urine and feces samples were between 85.7% and 102.0% and RSD was less than 9.5%. The method developed here has been successfully applied to the analysis of real samples from 2,4,6-trinitrobenzenesulfonic acid-induced Crohn’s disease in rats. All of these results suggest that the presently developed method is sufficiently sensitive and robust to simultaneously monitor co-metabolites with diverse properties and a range of different concentrations. Therefore, this method will be expected to be useful for comprehensive studies of the pathophysiological roles and mechanisms of these key microbiota-host co-metabolites, which reflect the function of the intestine, consequently offering novel opportunities for evaluating the occurrence, development and therapeutic effects of diseases related to microbiota disturbances. [ABSTRACT FROM AUTHOR]

Colorectal cancer (CRC) is one of the most prevalent cancers worldwide and a major cause of human morbidity and mortality. In addition to early detection, close monitoring of disease progression in CRC can be critical for patient prognosis and treatment decisions. Efforts have been made to develop new methods for improved early detection and patient monitoring; however, research focused on CRC surveillance for treatment response and disease recurrence using metabolomics has yet to be reported. In this proof of concept study, we applied a targeted liquid chromatography tandem mass spectrometry (LC-MS/MS) metabolic profiling approach focused on sequential metabolite ratio analysis of serial serum samples to monitor disease progression from 20 CRC patients. The use of serial samples reduces patient to patient metabolic variability. A partial least squares-discriminant analysis (PLS-DA) model using a panel of five metabolites (succinate, N2, N2-dimethylguanosine, adenine, citraconic acid, and 1-methylguanosine) was established, and excellent model performance (sensitivity = 0.83, specificity = 0.94, area under the receiver operator characteristic curve (AUROC) = 0.91 was obtained, which is superior to the traditional CRC monitoring marker carcinoembryonic antigen (sensitivity = 0.75, specificity = 0.76, AUROC = 0.80). Monte Carlo cross validation was applied, and the robustness of our model was clearly observed by the separation of true classification models from the random permutation models. Our results suggest the potential utility of metabolic profiling for CRC disease monitoring. [ABSTRACT FROM AUTHOR]

Metabolomics has become an important tool in clinical research and the diagnosis of human disease. Intratracheal instillation of trans- trans 2,4-decadienal ( tt-DDE), a major component in cooking oil fumes, has been demonstrated to cause lung lesions in mice at 8 weeks after treatment. The objective of this study was to identify any changes in metabolite profiles associated with the development of tt-DDE-induced lung lesions. Using a metabolomics strategy involving a liquid chromatography-mass spectrometry-based approach in conjunction with principal component analysis and confirmation by liquid chromatography triple quadrupole tandem mass spectrometry, we have demonstrated that the amino acid profiles of the urine and serum of tt-DDE-treated mice are changed. Ten amino acids were significantly reduced in serum of tt-DDE-treated mice at 8 weeks after treatment. Our results suggest that amino acid profiles may be useful as an early indicator of the presence of tt-DDE-induced lung lesions. [Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]

Acute anaphylaxis caused by food allergy is a potentially life-threatening allergic reaction that results in thousands of hospitalizations in North America every year. There are currently no effective means of treatment for anaphylaxis beyond the administration of epinephrine which is only given after a reaction has already started. Furthermore, knowledge regarding the underlying physico-chemical basis of anaphylaxis is largely incomplete. Arguably, the study of anaphylaxis by comprehensive metabolomics offers a unique opportunity to study this phenomenon due to its ability to provide a snap-shot of the chemical state of a subject experiencing anaphylaxis encompassing both endogenous and exogenous factors including dietary and environmental effects. In this study, we sought to apply a comprehensive metabolomics approach using liquid chromatography-mass spectrometry to a murine model of peanut-induced anaphylaxis. The results of this study revealed that the metabolomic profiles of mice experiencing peanut-induced anaphylaxis followed a distinct pattern that mirrors the time-stage of anaphylaxis being experienced. Direct comparison of anaphylactic mice to time-matched control mice showed that the metabolomic profiles changed considerably as the anaphylactic reaction progressed. This comparison also revealed changes in both known biomarkers of anaphylaxis such as histamine and methylhistamine as well as a suite of metabolites chemically similar to known anaphylaxis mediators but whose biological functions are not well understood. These metabolites include a number of phospholipids such as a variety of phosphatidylcholines and lyso-phosphatidylcholines that may be of interest for further investigation regarding their potential as anaphylaxis mediators or chemical precursors to mediators. [ABSTRACT FROM AUTHOR]

Highlights: [•] A method for paclitaxel and its metabolites in serum and peritoneal tissue is reported. [•] The method is based on LC–ESI-MS/MS in SRM mode. [•] Serum and peritoneal tissue from women with ovarian cancer were the samples. [•] Plasma can also been used as sample. [Copyright &y& Elsevier]

Metabolomic profiling has identified, sarcosine, a derivative of the amino acid glycine, as an important metabolite involved in the etiology or natural history of prostate cancer. We examined the association between serum sarcosine levels and risk of prostate cancer in 1122 cases (813 non-aggressive and 309 aggressive) and 1112 controls in the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. Sarcosine was quantified using high-throughput liquid chromatography–mass spectrometry. A significantly increased risk of prostate cancer was observed with increasing levels of sarcosine (odds ratio [OR] for the highest quartile of exposure [Q4] versus the lowest quartile [Q1] = 1.30, 95% confidence interval [CI]: 1.02, 1.65; P-trend 0.03). When stratified by disease aggressiveness, we observed a stronger association for non-aggressive cases (OR for Q4 versus Q1 = 1.44, 95% CI: 1.11, 1.88; P-trend 0.006) but no association for aggressive prostate cancer (OR for Q4 versus Q1 = 1.03, 95% CI: 0.73, 1.47; P-trend 0.89). Although not statistically significant, temporal analyses showed a stronger association between sarcosine and prostate cancer for serum collected closer to diagnosis, suggesting that sarcosine may be an early biomarker of disease. Interestingly, the association between sarcosine and prostate cancer risk was stronger among men with diabetes (OR = 2.66, 95% CI: 1.04, 6.84) compared with those without reported diabetes (OR = 1.23, 95% CI: 0.95–1.59, P-interaction = 0.01). This study found that elevated levels of serum sarcosine are associated with an increased prostate cancer risk and evidence to suggest that sarcosine may be an early biomarker for this disease. [ABSTRACT FROM PUBLISHER]

Untargeted analysis performed using full-scan mass spectrometry (MS) coupled with liquid chromatography (LC) is commonly used in metabolomics. Although they are commonly employed, full-scan MS methods such as quadrupole-time-of-flight (Q-TOF) MS have been restricted by various factors including their limited linear range and complicated data processing. LC coupled with triple quadrupole (QQQ) MS operated in the multiple reaction monitoring (MRM) mode is the gold standard for metabolite quantification; however, only known metabolites are generally quantified, limiting its applications in metabolomic analysis. In this study, a pseudotargeted approach was proposed to perform serum metabolomic analysis using an ultra high-performance liquid chromatography (UHPLC)/QQQ MS system operated in the MRM mode, for which the MRM ion pairs were acquired from the serum samples through untargeted tandem MS using UHPLC/Q-TOF MS. The UHPLC/QQQ MRM MS-based pseudotargeted method displayed better repeatability and wider linear range than the traditional UHPLC/Q-TOF MS-based untargeted metabolomics method, and no complicated peak alignment was required. The developed method was applied to discover serum biomarkers for patients with hepatocellular carcinoma (HCC). Patients with HCC had decreased lysophosphatidylcholine, increased long-chain and decreased medium-chain acylcarnitines, and increased aromatic and decreased branched-chain amino acid levels compared to healthy controls. The novelty of this work is that it provides an approach to acquire MRM ion pairs from real samples, is not limited to metabolite standards, and it provides a foundation to achieve pseudotargeted metabolomic analysis on the widely used LC/QQQ MS platform. [ABSTRACT FROM AUTHOR]

Taxifolin (TFN) is an important natural compound with antifibrotic activity; however, its pharmacological mechanism is not clear. In this study, our aim is to gain insight into the effects of TFN and its potential mechanisms in unilateral ureteral obstruction (UUO) animal model using metabolomics approach to identify the metabolic biomarkers and perturbed pathways. Serum metabolomics analysis by UPLC-Q-TOF/MS was carried out to discover the changes in the metabolic profile. It showed that TFN has a significant protective effect on UUO-induced renal fibrosis and a total of 32 potential biomarkers were identified and related to RF progression. Of note, 27 biomarkers were regulated by TFN treatment, which participate in eight metabolic pathways, including phenylalanine, tyrosine and tryptophan biosynthesis, and phenylalanine metabolism. It also showed that metabolomics was a promising strategy to better dissect metabolic characteristics and pharmacological mechanisms of natural compounds by multivariate approach and ultra-performance liquid chromatography coupled with mass spectrometry. [ABSTRACT FROM AUTHOR]

• Serum metabolomics was useful to identify biomarkers predicting efficacy of SLIT. • Serum lactic acid, ornithine, linolenic acid, etc, could predict the efficacy of SLIT. • Metabolism pathways dysfunction might underlie the mechanism of SLIT in AR patients. Allergen-specific immunotherapy (ASIT) is currently the only therapy for allergic rhinitis (AR) that can induce immune tolerance to allergens. However, the course of ASIT is long and there is no objective biomarker to predict treatment efficacy. The present study aimed to explore potential biomarkers predictive of efficacy of AIT based on serum metabolomics profiles. This prospective study recruited 72 consecutive eligible patients who were assigned to receive sublingual immunotherapy (SLIT). Serum samples were collected prior to SLIT and utilized to obtain metabolomics profiling by applying ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS). Treatment response was determined 3 years after SLIT, and patients were divided into effective group and ineffective group. Orthogonal partial least square-discriminate analysis (OPLS-DA) was performed to evaluate the metabolite differences between two groups. Sixty-eight patients completed the whole SLIT, 39 patients were categorized into effective group and 29 patients were classified into ineffective group. A total of 539 metabolites were obtained, and 197 of which were identified as known substances. Using these 197 known metabolites, the OPLS-DA results showed that effective group and ineffective group exhibited distinctive metabolite signatures and metabolic pathways. Six metabolites including lactic acid, ornithine, linolenic acid, creatinine, arachidonic acid and sphingosine were identified to exhibit good performance in predicting the efficacy of SLIT, and these metabolite changes mainly involved glycolysis and pyruvate metabolism, arginine and proline metabolism and fatty acid metabolism pathways. By metabolomics analysis, we identified several serum biomarkers that can reliably and accurately predict the efficacy of SLIT in AR patients. The discriminative metabolites and related metabolic pathways contributed to better understand the mechanisms of SLIT in AR patients. [ABSTRACT FROM AUTHOR]

Exercise plays a beneficial role in the treatment of metabolic syndrome (MetS). Metabolomics can provide new insights and facilitate the optimization of exercise prescription. This study aimed to investigate whether the response of the human serum metabolic fingerprint to exercise depends on exercise mode or the presence of MetS. Twenty-three sedentary men (nine with MetS and fourteen healthy) completed four trials: Resting, high-intensity interval exercise (HIIE), continuous moderate-intensity exercise (CME), and resistance exercise (RE). Blood samples were collected pre-exercise, immediately after exercise, and 1 h post-exercise for targeted metabolomic analysis in serum by liquid chromatography–mass spectrometry. Time exerted the strongest differentiating effect, followed by exercise mode. The largest changes from baseline were found in the immediate post-exercise samples. RE caused the strongest responses overall, followed by HIIE, while CME had minimal effect. Unlike previous results in urine, no valid model could separate the two groups in serum. Exercise exerted a beneficial effect on prominent serum biomarkers of metabolic risks, such as branched-chain amino acids, alanine, acetylcarnitine, choline, and betaine. These findings contribute to the ongoing research efforts to map the molecular responses to exercise and to optimize exercise guidelines for individuals at cardiometabolic risk. [ABSTRACT FROM AUTHOR]