Serum Metabolomic Profiling of Patients with Lipedema.

Lipedema is a chronic condition characterized by disproportionate and symmetrical enlargement of adipose tissue, predominantly affecting the lower limbs of women. This study investigated the use of metabolomics in lipedema research, with the objective of identifying complex metabolic disturbances and potential biomarkers for early detection, prognosis, and treatment strategies. The study group (n = 25) comprised women diagnosed with lipedema. The controls were 25 lean women and 25 obese females, both matched for age. In the patients with lipedema, there were notable changes in the metabolite parameters. Specifically, lower levels of histidine and phenylalanine were observed, whereas pyruvic acid was elevated compared with the weight controls. The receiver operating characteristic (ROC) curves for the diagnostic accuracy of histidine, phenylalanine, and pyruvic acid concentrations in distinguishing between patients with lipedema and those with obesity but without lipedema revealed good diagnostic ability for all parameters, with pyruvic acid being the most promising (area under the curve (AUC): 0.9992). Subgroup analysis within matched body mass index (BMI) ranges (30.0 to 39.9 kg/m2) further revealed that differences in pyruvic acid, phenylalanine, and histidine levels are likely linked to lipedema pathology rather than BMI variations. Changes in low-density lipoprotein (LDL)-6 TG levels and significant reductions in various LDL-2-carried lipids of patients with lipedema, compared with the lean controls, were observed. However, these lipids were similar between the lipedema patients and the obese controls, suggesting that these alterations are related to adiposity. Metabolomics is a valuable tool for investigating lipedema, offering a comprehensive view of metabolic changes and insights into lipedema's underlying mechanisms.

Identification of the New Psychoactive Substance Eutylone.

OBJECTIVES: To establish a method to identify unknown sample based on the combined use of Fourier transform infrared spectroscopy (FTIR), gas chromatography-quadrupole time-of-flight mass spectrometry (GC-QTOF-MS), ultra-high performance liquid chromatography-linear ion trap quadrupole-orbitrap mass spectrometry (UPLC-LTQ-Orbitrap MS) and 1H-nuclear magnetic resonance spectroscopy (1H-NMR) technique. METHODS: The unknown sample was directly analyzed by FTIR. The unknown sample was dissolved in methanol solution containing internal standard SKF525A and the supernatant was detected by GC-QTOF-MS and UPLC-LTQ-Orbitrap MS. The unknown sample was dissolved in methanol-d4 solution for structural analysis of 1H-NMR. RESULTS: The characteristic absorption peaks of FTIR spectra obtained from unknown sample were 1 682 (C=O bond), 1 503, 1 488, 1 436, 1 363, 1 256, 1 092, 1 035, 935, 840 and 800 cm-1, the characteristic fragment ions (m/z) of GC-QTOF-MS were 86.096 4 (base peak), 58.065 1, 149.023 5, 121.028 6 and 65.038 6, the accurate mass [M+H]+ detected by UPLC-LTQ-Orbitrap MS was 236.127 7. The sample was identified as synthetic cathinone new psychoactive substance Eutylone by 1H-NMR. CONCLUSIONS: The method established in this study can be used for structural confirmation of Eutylone.

1H-NMR-based metabolomics study on coronary heart disease with blood-stasis syndrome and phlegm syndrome. / 基于1H-NMRçš„å† å¿ƒç— è¡€ç˜€è¯ã€ç—°æµŠè¯çš„ä»£è°¢ç»„å­¦ç ”ç©¶.

OBJECTIVES: Coronary heart disease (CHD) is a serious threat to human health because of its high morbidity. It is very urgent to study the pathogenesis of CHD and the effective drug target. The purpose of this paper is using the 1H-nuclear magnetic resonance spectroscopy (1H-NMR) metabolomics technology to establish the metabolic fingerprint and find the potential biomarker metabolites of CHD with blood-stasis syndrome and phlegm syndrome, and to reveal the metabolic mechanism of Xuefu Zhuyu Decoction for the treatment of CHD with blood stasis syndrome. METHODS: The plasma samples of 69 patients with CHD blood-stasis syndrome, 60 patients with CHD phlegm syndrome, and 40 healthy volunteers were collected in this study. Based on the 1H-NMR metabolomics technology, the metabolic fingerprint of CHD with blood-stasis syndrome and phlegm syndrome was established. Multivariate statistical analysis methods including principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) were used to find the potential biomarker metabolites of CHD with blood-stasis syndrome and phlegm syndrome. Xuefu Zhuyu Decoction was used to randomly selected blood-stasis syndrome patient. The plasma samples of pre-treatment and post-treatment were collected. 1H-NMR and multivariate statistical analysis were used to analyze the changes of metabolites in patients with CHD blood-stasis syndrome before and after Xuefu Zhuyu Decoction treatment. RESULTS: A total of 15 potential biomarkers were identified in the plasma of patients with CHD blood-stasis syndrome, including 3-hydroxybutyrate (3-HB), lactate, alanine, glutamate, glutamine, pyruvate,phosphatidylcholine (PC), glycerylphosphorylcholine (GPC), glycine, glucose, phenylalanine, citrate,tyrosine, formate,very low density lipoprotein (VLDL). The levels of glucose, 3-HB, and VLDL increased, while the levels of other 12 metabolites decreased. A total of 16 potential biomarkers were identified in the plasma of patients with CHD phlegm syndrome, including valine, lactate, alanine, N-acetyl-ß-glucosaminidase (NAG), glutamate, glutamine, pyruvate, creatine, choline, glycine, glucose, phenylalanine, citrate, histidine, tyrosine, and formate. The levels of glucose and choline increased, while the levels of other 12 metabolites decreased. After treatment with Xuefu Zhuyu Decoction, the levels of choline, phospholipids/glycerolipids, creatine, lipids, and citrate increased, while the level of lactate decreased in patients with CHD blood-stasis syndrome. CONCLUSIONS: 1H-NMR combined with multivariate statistical method could effectively establish the diagnostic model for CHD blood-stasis syndrome and CHD phlegm syndrome, and find the metabolites related to the syndrome type. The metabolic mechanism of Xuefu Zhuyu Decoction on CHD blood-stasis syndrome may be associated with regulation of lipid metabolism and energy metabolism.

Nuclear magnetic resonance-based serum metabolomic analysis reveals different disease evolution profiles between septic shock survivors and non-survivors.

BACKGROUND: Septic shock is the most severe phase of sepsis and is associated with high rates of mortality. However, early stage prediction of septic shock outcomes remains difficult. Metabolomic techniques have emerged as a promising tool for improving prognosis. METHODS: Orthogonal projections to latent structures-discriminant analysis (OPLS-DA) models separating the serum metabolomes of survivors from those of non-survivors were established with samples obtained at the intensive care unit (ICU) admission (H0) and 24 h later (H24). For 51 patients with available H0 and H24 samples, multi-level modeling was performed to provide insight into different metabolic evolutions that occurred between H0 and H24 in the surviving and non-surviving patients. Relative quantification and receiver operational characteristic curves (ROC) were applied to estimate the predictability of key discriminatory metabolites for septic shock mortality. RESULTS: Metabolites that were involved in energy supply and protein breakdown were primarily responsible for differentiating survivors from non-survivors. This was not only seen in the H0 and H24 discriminatory models, but also in the H0-H24 paired models. Reanalysis of extra H0-H24 paired samples in the established multi-level model demonstrated good performance of the model for the classification of samplings. According to the ROC results, nine discriminatory metabolites defined consistently from the unpaired model and the H0-H24 time-trend change (ΔH24-H0) show good prediction of mortality. These results suggest that NMR-based metabolomic analysis is useful for a better overall assessment of septic shock patients. CONCLUSIONS: Dysregulation of the metabolites identified by this study is associated with poor outcomes for septic shock. Evaluation of these compounds during the first 24 h after ICU admission in the septic shock patient may be helpful for estimating the severity of cases and for predicting outcomes. TRIAL REGISTRATION: All human serum samples were collected and stored, provided by the "center of biologic resources for liver disease", in Jean Verdier Hospital, Bondy, France (BB-0033-00027).

Stress transgenerationally programs metabolic pathways linked to altered mental health.

Stress is among the primary causes of mental health disorders, which are the most common reason for disability worldwide. The ubiquity of these disorders, and the costs associated with them, lends a sense of urgency to the efforts to improve prediction and prevention. Down-stream metabolic changes are highly feasible and accessible indicators of pathophysiological processes underlying mental health disorders. Here, we show that remote and cumulative ancestral stress programs central metabolic pathways linked to mental health disorders. The studies used a rat model consisting of a multigenerational stress lineage (the great-great-grandmother and each subsequent generation experienced stress during pregnancy) and a transgenerational stress lineage (only the great-great-grandmother was stressed during pregnancy). Urine samples were collected from adult male F4 offspring and analyzed using 1H NMR spectroscopy. The results of variable importance analysis based on random variable combination were used for unsupervised multivariate principal component analysis and hierarchical clustering analysis, as well as metabolite set enrichment analysis (MSEA) and pathway analysis. We identified distinct metabolic profiles associated with the multigenerational and transgenerational stress phenotype, with consistent upregulation of hippurate and downregulation of tyrosine, threonine, and histamine. MSEA and pathway analysis showed that these metabolites are involved in catecholamine biosynthesis, immune responses, and microbial host interactions. The identification of metabolic signatures linked to ancestral programming assists in the discovery of gene targets for future studies of epigenetic regulation in pathogenic processes. Ultimately, this research can lead to biomarker discovery for better prediction and prevention of mental health disorders.

Serum Metabolite Profiles Are Altered by Erlotinib Treatment and the Integrin α1-Null Genotype but Not by Post-Traumatic Osteoarthritis.

The risk of developing post-traumatic osteoarthritis (PTOA) following joint injury is high. Furthering our understanding of the molecular mechanisms underlying PTOA and/or identifying novel biomarkers for early detection may help to improve treatment outcomes. Increased expression of integrin α1ß1 and inhibition of epidermal growth factor receptor (EGFR) signaling protect the knee from spontaneous OA; however, the impact of the integrin α1ß1/EGFR axis on PTOA is currently unknown. We sought to determine metabolic changes in serum samples collected from wild-type and integrin α1-null mice that underwent surgery to destabilize the medial meniscus and were treated with the EGFR inhibitor erlotinib. Following (1)H nuclear magnetic resonance spectroscopy, we generated multivariate statistical models that distinguished between the metabolic profiles of erlotinib- versus vehicle-treated mice and the integrin α1-null versus wild-type mouse genotype. Our results show the sex-dependent effects of erlotinib treatment and highlight glutamine as a metabolite that counteracts this treatment. Furthermore, we identified a set of metabolites associated with increased reactive oxygen species production, susceptibility to OA, and regulation of TRP channels in α1-null mice. Our study indicates that systemic pharmacological and genetic factors have a greater effect on serum metabolic profiles than site-specific factors such as surgery.

Transacylation and hydrolysis of the acyl glucuronides of ibuprofen and its α-methyl-substituted analogues investigated by 1H NMR spectroscopy and computational chemistry: Implications for drug design.

Drugs and drug metabolites containing a carboxylic-acid moiety can undergo in vivo conjugation to form 1-ß-O-acyl-glucuronides (1-ß-O-AGs). In addition to hydrolysis, these conjugates can undergo spontaneous acyl migration, and anomerisation reactions, resulting in a range of positional isomers. Facile transacylation has been suggested as a mechanism contributing to the toxicity of acyl glucuronides, with the kinetics of these processes thought to be a factor. Previous 1H NMR spectroscopic and HPLC-MS studies have been conducted to measure the degradation rates of the 1-ß-O-AGs of three nonsteroidal anti-inflammatory drugs (ibufenac, R-ibuprofen, S-ibuprofen) and a dimethyl-analogue (termed here as "bibuprofen"). These studies have also determined the relative contributions of hydrolysis and acyl migration in both buffered aqueous solution, and human plasma. Here, a detailed kinetic analysis is reported, providing the individual rate constants for the acyl migration and hydrolysis reactions observed in buffer for each of the 4 AGs, together with the overall degradation rate constants of the parent 1-ß-O-AGs. Computational modelling of the reactants and transition states of the transacylation reaction using density functional theory indicated differences in the activation energies that reflected the influence of both substitution and stereochemistry on the rate of transacylation/hydrolysis.

Magnetic resonance spectroscopy investigation in the right human hippocampus following spinal cord injury.

Objective: Preclinical studies have shown that cognitive impairments following spinal cord injury (SCI), such as impaired spatial memory, are linked to inflammation, neurodegeneration, and reduced neurogenesis in the right hippocampus. This cross-sectional study aims to characterize metabolic and macrostructural changes in the right hippocampus and their association to cognitive function in traumatic SCI patients. Methods: Within this cross-sectional study, cognitive function was assessed in 28 chronic traumatic SCI patients and 18 age-, sex-, and education-matched healthy controls by a visuospatial and verbal memory test. A magnetic resonance spectroscopy (MRS) and structural MRI protocol was performed in the right hippocampus of both groups to quantify metabolic concentrations and hippocampal volume, respectively. Group comparisons investigated changes between SCI patients and healthy controls and correlation analyses investigated their relationship to memory performance. Results: Memory performance was similar in SCI patients and healthy controls. The quality of the recorded MR spectra was excellent in comparison to the best-practice reports for the hippocampus. Metabolite concentrations and volume of the hippocampus measured based on MRS and MRI were not different between two groups. Memory performance in SCI patients and healthy controls was not correlated with metabolic or structural measures. Conclusion: This study suggests that the hippocampus may not be pathologically affected at a functional, metabolic, and macrostructural level in chronic SCI. This points toward the absence of significant and clinically relevant trauma-induced neurodegeneration in the hippocampus.

The effects of ambient temperature exposure on feline fecal metabolome.

Introduction: The fecal metabolome provides insight into overall gastrointestinal and microbial health. Methods for fecal sample storage in metabolomics research vary, however, making comparisons within current literature difficult. This study investigated the effect of ambient temperature exposure on microbial-derived metabolites of feline fecal samples. Methods: Fecal samples were collected from 11 healthy cats from a local boarding facility. Samples were manually homogenized and aliquoted. The first aliquot was frozen at -80°C within 1 hour of defecation, and remaining samples were exposed to ambient temperature for 2, 4, 6, 8, 12, and 24 h prior to freezing at -80°C. Fecal metabolites were quantified using 1H NMR spectroscopy. Fifty metabolites were grouped into six categories (27 amino acids, 8 fatty acids, 5 sugars, 3 alcohols, 2 nitrogenous bases, 5 miscellaneous). Results: Concentrations of 20 out of 50 metabolites significantly differed due to ambient temperature exposure (7 amino acids, 6 fatty acids, 2 alcohols, 1 nitrogenous base, 4 miscellaneous). The earliest detected changes occurred 6 h post-defecation for cadaverine and fumaric acid. Discussion: This study shows ambient temperature exposure alters the composition of the feline fecal metabolome, but short-term (up to 4 h) exposure prior to storage in the freezer seems to be acceptable.

Effects of Methylphenidate on the Dopamine Transporter and Beyond.

The dopamine transporter (DAT) is the main target of methylphenidate (MPH), which remains the number one drug prescribed worldwide for the treatment of Attention-Deficit Hyperactivity Disorder (ADHD). In addition, abnormalities of the DAT have been widely associated with ADHD. Based on clinical and preclinical studies, the direction of DAT abnormalities in ADHD are, however, still unclear. Moreover, chronic treatment of MPH has been shown to increase brain DAT expression in both animals and ADHD patients, suggesting that findings of overexpressed levels of DAT in ADHD patients are possibly attributable to the effects of long-term MPH treatment rather than the pathology of the condition itself. In this chapter, we will discuss some of the effects exerted by MPH, which are related to its actions on catecholamine protein targets and brain metabolites, together with genes and proteins mediating neuronal plasticity. For this purpose, we present data from biochemical, proton nuclear magnetic resonance spectroscopy (1H-NMR) and gene/protein expression studies. Overall, results of the studies discussed in this chapter show that MPH has a complex biological/pharmacological action well beyond the DAT.

Delineating metabolic dysfunction in cellular metabolism of oral submucous fibrosis using 1H nuclear magnetic resonance spectroscopy.

OBJECTIVE: To delineate the metabolism involved in oral submucous fibrosis progression towards carcinogenesis by 1H nuclear magnetic resonance spectroscopy. METHODS: The proposed study was designed using 1H-NMR by comparing the metabolites in the serum sample of oral submucous fibrosis (n = 20) compared to the normal group (n = 20) using 1H nuclear magnetic resonance spectroscopy. Various statistical analysis like multivariate statistical analysis, Principle component analysis, Partial least squares Discriminant Analysis, Hierarchical cluster analysis was applied to analyze potential serum metabolites. RESULTS: The results generated from the principle component analysis, partial least squares discriminant analysis and hierarchical cluster analysis are sufficient to distinguish between oral submucous fibrosis group and normal group. A total of 15 significant metabolites associated with main pathways were identified, which correlated with the progression of cancer. Up-regulation of glucose metabolism-related metabolites indicated the high energy demand due to enhanced cell division rate in the oral submucous fibrosis group. A significant increase in lipid metabolism-related metabolites revealed the reprogramming of the fatty acids metabolic pathway to fulfilling the need for cell membrane formation in cancer cells. On the other hand, metabolites related to choline phosphocholine, the metabolic pathway was also altered. CONCLUSION: Our findings could identify the differentiating metabolites in the oral submucous fibrosis group. Significant alteration in metabolites in the oral submucous fibrosis group exhibited deregulation in metabolic events. The findings reported in the study can be beneficial to further explain the molecular aspects that lead to the progression of oral submucous fibrosis towards carcinogenesis.

Metabolic Characterization of Peripheral Host Responses to Drainage-Resistant Klebsiella pneumoniae Liver Abscesses by Serum 1H-NMR Spectroscopy.

Purpose: To explore the metabolic characterization of host responses to drainage-resistant Klebsiella pneumoniae liver abscesses (DRKPLAs) with serum 1H-nuclear magnetic resonance (NMR) spectroscopy. Materials and Methods: The hospital records of all patients with a diagnosis of a liver abscess between June 2015 and December 2016 were retrieved from an electronic hospital database. Eighty-six patients with Klebsiella pneumoniae (K. pneumoniae) liver abscesses who underwent percutaneous drainage were identified. Twenty patients with confirmed DRKPLAs were studied. Moreover, we identified 20 consecutive patients with drainage-sensitive Klebsiella pneumoniae liver abscesses (DSKPLAs) as controls. Serum samples from the two groups were analyzed with 1H NMR spectroscopy. Partial least squares discriminant analysis (PLS-DA) was used to perform 1H NMR metabolic profiling. Metabolites were identified using the Human Metabolome Database, and pathway analysis was performed with MetaboAnalyst 3.0. Results: The PLS-DA test was able to discriminate between the two groups. Five key metabolites that contributed to their discrimination were identified. Glucose, lactate, and 3-hydroxybutyrate were found to be upregulated in DRKPLAs, whereas glutamine and alanine were downregulated compared with the DSKPLAs. Pathway analysis indicated that amino acid metabolisms were significantly different between the DRKPLAs and the DSKPLAs. The D-glutamine and D-glutamate metabolisms exhibited the greatest influences. Conclusions: The five key metabolites identified in our study may be potential targets for guiding novel therapeutics of DRKPLAs and are worthy of additional investigation.

[Link between sortase A function and cariogenicity of Streptococcus mutans: a preliminary metabolomics analysis].

OBJECTIVE: This study intends to explore the mechanism underlying the support of sortase A (SrtA) of the cariogenicity of Streptococcus mutans (S. mutans). METHODS: We performed a metabonomics study based on ¹H nuclear magnetic resonance spectroscopy (NMR), in which we compared the extracellular metabolites of wild-type S. mutans UA159 with those of its SrtA-deficient strain. Metabolite differences among strains were identified using a combination of principal component analysis and orthogonality partial least square discriminant analysis. RESULTS: Several differences corresponding mostly to unknown metabolites were identified. Some amino acids such as leucine and valine (δ 0.92×10⁻6-1.20×10⁻6), lactic acid ( δ1.28×10⁻6), oxoglutaric acid (δ 3.00×10⁻6), and glycine (δ 3.60×10⁻6) differed among strains. CONCLUSIONS: This work establishes the feasibility of using ¹H NMR-based metabonomics to provide leads for research into molecular factors that promote caries. The database of microbial metabolites should be also improved in further studies.

1 H-NMR with Multivariate Analysis for Automobile Lubricant Comparison.

Identification of suspected automobile-related lubricants could provide valuable information in forensic cases. We examined that automobile lubricants might exhibit the chemometric characteristics to their individual usages. To compare the degree of clustering in the plots, we co-plotted general industrial oils that were highly dissimilar with automobile lubricants in additive compositions. 1 H-NMR spectroscopy was used with multivariate statistics as a tool for grouping, clustering, and identification of automobile lubricants in laboratory conditions. We analyzed automobile lubricants including automobile engine oils, automobile transmission oils, automobile gear oils, and motorcycle oils. In contrast to the general industrial oils, automobile lubricants showed relatively high tendencies of clustering to their usages. Our pilot study demonstrated that the comparison of known and questioned samples to their usages might be possible in forensic fields.

Effect of ecosystem type and fire on chemistry of WEOM as measured by LDI-TOF-MS and NMR.

Soil organic matter (SOM) and its water-soluble components play an important role in terrestrial carbon cycling and associated ecosystem functions. Chemically, they are complex mixtures of organic compounds derived from decomposing plant material, microbial residues, as well as root exudates, and soil biota. To test the effect of the ecosystem type (forest and grassland) and fires events on the chemistry of dissolved organic matter (DOM), we applied a combination of laser-desorption/ionization time-of-flight mass spectrometry (LDI-TOF-MS) and 2D (1H and 13C) nuclear magnetic resonance (NMR) spectroscopy to water-extractable organic matter (WEOM) from a range of top soil samples. The aim was to assess the suitability of LDI-TOF-MS for the rapid characterization of WEOM. Therefore, we evaluated the effects of sample (pH and dilution) conditions and use of positive or negative reflector mode to identify the conditions under which LDI-TOF-MS best distinguished between WEOM from different sources. Thirty-six samples were measured with both analytical techniques and their chemical patterns were statistically evaluated to distinguish firstly the effect of the type of ecosystem (forest versus grassland) on WEOM characteristics, and secondly the impact of fire on the chemical composition of WEOM. The nonmetric multidimensional scaling (NMDS) analysis of the most suitable experimental LDI-TOF-MS conditions showed a clear separation between the type of vegetation and fire-induced changes, mostly reflecting the presence of poly(ethylene glycol) in grassland soils. Discrimination among WEOM from different vegetation types was preserved in the fire treated samples. The calculation of the relative abundance of certain functional structures in the WEOM samples revealed a common composition of forest and grassland WEOM, with polysaccharides and proteins making up to 60%. The compositional impact of forest fire on WEOM was more pronounced compared to the one of grassland, leading to a decline in the main components, and an increase in amino-sugars, fatty acids, and sterols. The recorded 1H NMR and heteronuclear single quantum coherence (HSQC) spectra showed a decrease of the carbohydrate signal in WEOM from fire-treated samples, which was more pronounced in forest than in grassland soils.

Identification of the New Psychoactive Substance Eutylone / 法医学杂志

OBJECTIVES@#To establish a method to identify unknown sample based on the combined use of Fourier transform infrared spectroscopy (FTIR), gas chromatography-quadrupole time-of-flight mass spectrometry (GC-QTOF-MS), ultra-high performance liquid chromatography-linear ion trap quadrupole-orbitrap mass spectrometry (UPLC-LTQ-Orbitrap MS) and 1H-nuclear magnetic resonance spectroscopy (1H-NMR) technique.@*METHODS@#The unknown sample was directly analyzed by FTIR. The unknown sample was dissolved in methanol solution containing internal standard SKF525A and the supernatant was detected by GC-QTOF-MS and UPLC-LTQ-Orbitrap MS. The unknown sample was dissolved in methanol-d4 solution for structural analysis of 1H-NMR.@*RESULTS@#The characteristic absorption peaks of FTIR spectra obtained from unknown sample were 1 682 (C=O bond), 1 503, 1 488, 1 436, 1 363, 1 256, 1 092, 1 035, 935, 840 and 800 cm-1, the characteristic fragment ions (m/z) of GC-QTOF-MS were 86.096 4 (base peak), 58.065 1, 149.023 5, 121.028 6 and 65.038 6, the accurate mass [M+H]+ detected by UPLC-LTQ-Orbitrap MS was 236.127 7. The sample was identified as synthetic cathinone new psychoactive substance Eutylone by 1H-NMR.@*CONCLUSIONS@#The method established in this study can be used for structural confirmation of Eutylone.

Metabolic analysis of knee synovial fluid as a potential diagnostic approach for osteoarthritis.

Osteoarthritis (OA) is a leading cause of chronic joint pain in the older human population. Diagnosis of OA at an earlier stage may enable the development of new treatments to one day effectively modify the progression and prognosis of the disease. In this work, we explore whether an integrated metabolomics approach could be utilized for the diagnosis of OA. Synovial fluid (SF) samples were collected from symptomatic chronic knee OA patients and normal human cadaveric knee joints. The samples were analyzed using (1)H nuclear magnetic resonance (NMR) spectroscopy and gas chromatography-mass spectrometry (GC-MS) followed by multivariate statistical analysis. Based on the metabolic profiles, we were able to distinguish OA patients from the controls and validate the statistical models. Moreover, we have integrated the (1)H NMR and GC-MS results and we found that 11 metabolites were statistically important for the separation between OA and normal SF. Additionally, statistical analysis showed an excellent predictive ability of the constructed metabolomics model (area under the receiver operating characteristic curve = 1.0). Our findings indicate that metabolomics might serve as a promising approach for the diagnosis and prognosis of degenerative changes in the knee joint and should be further validated in clinical settings.

Metabolic profiling of synovial fluid in a unilateral ovine model of anterior cruciate ligament reconstruction of the knee suggests biomarkers for early osteoarthritis.

Joint injuries and subsequent osteoarthritis (OA) are the leading causes of chronic joint disease. In this work, we explore the possibility of applying magnetic resonance spectroscopy-based metabolomics to detect host responses to an anterior cruciate ligament (ACL) reconstruction injury in synovial fluid in an ovine model. Using multivariate statistical analysis, we were able to distinguish post-injury joint samples (ACL and sham surgery) from the uninjured control samples, and as well the ACL surgical samples from sham surgery. In all samples there were 65 metabolites quantified, of which six could be suggested as biomarkers for early post-injury degenerative changes in the knee joints: isobutyrate, glucose, hydroxyproline, asparagine, serine, and uridine. Our results raise a cautionary note indicating that surgical interventions into the knee can result in metabolic alterations that need to be distinguished from those caused by the early onset of OA. Our findings illustrate the potential application of metabolomics as a diagnostic and prognostic tool for detection of injuries to the knee joint. The ability to detect a unique pattern of metabolic changes in the synovial fluid of sheep offers the possibility of extending the approach to precision medicine protocols in patient populations in the future.

A phytochemical comparison of saw palmetto products using gas chromatography and (1) H nuclear magnetic resonance spectroscopy metabolomic profiling.

OBJECTIVES: Preparations containing saw palmetto berries are used in the treatment of benign prostatic hyperplasia (BPH). There are many products on the market, and relatively little is known about their chemical variability and specifically the composition and quality of different saw palmetto products notwithstanding that in 2000, an international consultation paper from the major urological associations from the five continents on treatments for BPH demanded further research on this topic. Here, we compare two analytical approaches and characterise 57 different saw palmetto products. METHODS: An established method - gas chromatography - was used for the quantification of nine fatty acids, while a novel approach of metabolomic profiling using (1) H nuclear magnetic resonance (NMR) spectroscopy was used as a fingerprinting tool to assess the overall composition of the extracts. KEY FINDINGS: The phytochemical analysis determining the fatty acids showed a high level of heterogeneity of the different products in the total amount and of nine single fatty acids. A robust and reproducible (1) H NMR spectroscopy method was established, and the results showed that it was possible to statistically differentiate between saw palmetto products that had been extracted under different conditions but not between products that used a similar extraction method. Principal component analysis was able to determine those products that had significantly different metabolites. CONCLUSIONS: The metabolomic approach developed offers novel opportunities for quality control along the value chain of saw palmetto and needs to be followed further, as with this method, the complexity of a herbal extract can be better assessed than with the analysis of a single group of constituents.

Link between sortase A function and cariogenicity of Streptococcus mutans: a preliminary metabolomics analysis / 华西口腔医学杂志

<p><b>OBJECTIVE</b>This study intends to explore the mechanism underlying the support of sortase A (SrtA) of the cariogenicity of Streptococcus mutans (S. mutans).</p><p><b>METHODS</b>We performed a metabonomics study based on ¹H nuclear magnetic resonance spectroscopy (NMR), in which we compared the extracellular metabolites of wild-type S. mutans UA159 with those of its SrtA-deficient strain. Metabolite differences among strains were identified using a combination of principal component analysis and orthogonality partial least square discriminant analysis.</p><p><b>RESULTS</b>Several differences corresponding mostly to unknown metabolites were identified. Some amino acids such as leucine and valine (δ 0.92×10⁻⁶-1.20×10⁻⁶), lactic acid ( δ1.28×10⁻⁶), oxoglutaric acid (δ 3.00×10⁻⁶), and glycine (δ 3.60×10⁻⁶) differed among strains.</p><p><b>CONCLUSIONS</b>This work establishes the feasibility of using ¹H NMR-based metabonomics to provide leads for research into molecular factors that promote caries. The database of microbial metabolites should be also improved in further studies.</p>