Plasma Metabolomic and Lipidomic Profiling of Metabolic Dysfunction-Associated Fatty Liver Disease in Humans Using an Untargeted Multiplatform Approach.

Metabolic dysfunction-associated fatty liver disease (MAFLD) is a complex disorder that is implicated in dysregulations in multiple biological pathways, orchestrated by interactions between genetic predisposition, metabolic syndromes and environmental factors. The limited knowledge of its pathogenesis is one of the bottlenecks in the development of prognostic and therapeutic options for MAFLD. Moreover, the extent to which metabolic pathways are altered due to ongoing hepatic steatosis, inflammation and fibrosis and subsequent liver damage remains unclear. To uncover potential MAFLD pathogenesis in humans, we employed an untargeted nuclear magnetic resonance (NMR) spectroscopy- and high-resolution mass spectrometry (HRMS)-based multiplatform approach combined with a computational multiblock omics framework to characterize the plasma metabolomes and lipidomes of obese patients without (n = 19) or with liver biopsy confirmed MAFLD (n = 63). Metabolite features associated with MAFLD were identified using a metabolome-wide association study pipeline that tested for the relationships between feature responses and MAFLD. A metabolic pathway enrichment analysis revealed 16 pathways associated with MAFLD and highlighted pathway changes, including amino acid metabolism, bile acid metabolism, carnitine shuttle, fatty acid metabolism, glycerophospholipid metabolism, arachidonic acid metabolism and steroid metabolism. These results suggested that there were alterations in energy metabolism, specifically amino acid and lipid metabolism, and pointed to the pathways being implicated in alerted liver function, mitochondrial dysfunctions and immune system disorders, which have previously been linked to MAFLD in human and animal studies. Together, this study revealed specific metabolic alterations associated with MAFLD and supported the idea that MAFLD is fundamentally a metabolism-related disorder, thereby providing new perspectives for diagnostic and therapeutic strategies.

Mining the equine gut metagenome: poorly-characterized taxa associated with cardiovascular fitness in endurance athletes.

Emerging evidence indicates that the gut microbiome contributes to endurance exercise performance. Still, the extent of its functional and metabolic potential remains unknown. Using elite endurance horses as a model system for exercise responsiveness, we built an integrated horse gut gene catalog comprising ~25 million unique genes and 372 metagenome-assembled genomes. This catalog represents 4179 genera spanning 95 phyla and functional capacities primed to exploit energy from dietary, microbial, and host resources. The holo-omics approach shows that gut microbiomes enriched in Lachnospiraceae taxa are negatively associated with cardiovascular capacity. Conversely, more complex and functionally diverse microbiomes are associated with higher glucose concentrations and reduced accumulation of long-chain acylcarnitines and non-esterified fatty acids in plasma, suggesting increased ß-oxidation capacity in the mitochondria. In line with this hypothesis, more fit athletes show upregulation of mitochondrial-related genes involved in energy metabolism, biogenesis, and Ca2+ cytosolic transport, all of which are necessary to improve aerobic work power, spare glycogen usage, and enhance cardiovascular capacity. The results identify an associative link between endurance performance and gut microbiome composition and gene function, laying the basis for nutritional interventions that could benefit horse athletes.

Metabolomics with multi-block modelling of mass spectrometry and nuclear magnetic resonance in order to discriminate Haplosclerida marine sponges.

A comprehensive metabolomic strategy, integrating 1H NMR and MS-based multi-block modelling in conjunction with multi-informational molecular networking, has been developed to discriminate sponges of the order Haplosclerida, well known for being taxonomically contentious. An in-house collection of 33 marine sponge samples belonging to three families (Callyspongiidae, Chalinidae, Petrosiidae) and four different genera (Callyspongia, Haliclona, Petrosia, Xestospongia) was investigated using LC-MS/MS, molecular networking, and the annotations processes combined with NMR data and multivariate statistical modelling. The combination of MS and NMR data into supervised multivariate models led to the discrimination of, out of the four genera, three groups based on the presence of metabolites, not necessarily previously described in the Haplosclerida order. Although these metabolomic methods have already been applied separately, it is the first time that a multi-block untargeted approach using MS and NMR has been combined with molecular networking and statistically analyzed, pointing out the pros and cons of this strategy.

Understanding the Holobiont: Crosstalk Between Gut Microbiota and Mitochondria During Long Exercise in Horse.

Endurance exercise has a dramatic impact on the functionality of mitochondria and on the composition of the intestinal microbiome, but the mechanisms regulating the crosstalk between these two components are still largely unknown. Here, we sampled 20 elite horses before and after an endurance race and used blood transcriptome, blood metabolome and fecal microbiome to describe the gut-mitochondria crosstalk. A subset of mitochondria-related differentially expressed genes involved in pathways such as energy metabolism, oxidative stress and inflammation was discovered and then shown to be associated with butyrate-producing bacteria of the Lachnospiraceae family, especially Eubacterium. The mechanisms involved were not fully understood, but through the action of their metabolites likely acted on PPARγ, the FRX-CREB axis and their downstream targets to delay the onset of hypoglycemia, inflammation and extend running time. Our results also suggested that circulating free fatty acids may act not merely as fuel but drive mitochondrial inflammatory responses triggered by the translocation of gut bacterial polysaccharides following endurance. Targeting the gut-mitochondria axis therefore appears to be a potential strategy to enhance athletic performance.

Dichloroacetate-induced metabolic reprogramming improves lifespan in a Drosophila model of surviving sepsis.

Sepsis is the leading cause of death in hospitalized patients and beyond the hospital stay and these long-term sequelae are due in part to unresolved inflammation. Metabolic shift from oxidative phosphorylation to aerobic glycolysis links metabolism to inflammation and such a shift is commonly observed in sepsis under normoxic conditions. By shifting the metabolic state from aerobic glycolysis to oxidative phosphorylation, we hypothesized it would reverse unresolved inflammation and subsequently improve outcome. We propose a shift from aerobic glycolysis to oxidative phosphorylation as a sepsis therapy by targeting the pathways involved in the conversion of pyruvate into acetyl-CoA via pyruvate dehydrogenase (PDH). Chemical manipulation of PDH using dichloroacetic acid (DCA) will promote oxidative phosphorylation over glycolysis and decrease inflammation. We tested our hypothesis in a Drosophila melanogaster model of surviving sepsis infected with Staphylococcus aureus. Drosophila were divided into 3 groups: unmanipulated, sham and sepsis survivors, all treated with linezolid; each group was either treated or not with DCA for one week following sepsis. We followed lifespan, measured gene expression of Toll, defensin, cecropin A, and drosomycin, and levels of lactate, pyruvate, acetyl-CoA as well as TCA metabolites. In our model, metabolic effects of sepsis are modified by DCA with normalized lactate, TCA metabolites, and was associated with improved lifespan of sepsis survivors, yet had no lifespan effects on unmanipulated and sham flies. While Drosomycin and cecropin A expression increased in sepsis survivors, DCA treatment decreased both and selectively increased defensin.

Publisher Correction: Unraveling the effects of the gut microbiota composition and function on horse endurance physiology.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Diagnosis and phenotypic assessment of trimethylaminuria, and its treatment with riboflavin: 1H NMR spectroscopy and genetic testing.

BACKGROUND: Trimethylaminuria (TMAU) is a metabolic disorder characterized by the excessive excretion of the malodorous compound trimethylamine (TMA). The diagnosis of TMAU is challenging because this disorder is situated at the boundary between biochemistry and psychiatry. Here, we used nuclear magnetic resonance spectroscopy to assess TMAU in 13 patients. We also sequenced the FMO3 gene in 11 of these patients. Treatment with vitamin B2 was prescribed. RESULTS: Two patients (aged 3 and 9 years at the initial consultation) had a particularly unpleasant body odor, as assessed by their parents and the attending physicians. The presence of high urine TMA levels confirmed the presence of a metabolic disorder. The two (unrelated) children carried compound heterozygous variants in the FMO3 gene. In both cases, vitamin B2 administration decreased TMA excretion and reduced body odor. The 11 adults complained of an unpleasant body odor, but the physicians did not confirm this. In all adult patients, the urine TMA level was within the normal range reported for control (non-affected) subjects, although two of the patients displayed an abnormally high proportion of oxidized TMA. Seven of the 9 tested adult patients had a hypomorphic variant of the FMO3 gene; the variant was found in the homozygous state, in the heterozygous state or combined with another hypomorphic variant. All 11 adults presented a particular psychological or psychiatric phenotype, with a subjective perception of unpleasant odor. CONCLUSIONS: The results present the clinical and biochemical data of patients complaining of unpleasant body odor. Contrary to adult patients, the two children exhibited all criteria of recessively inherited trimethylaminuria, suspected by parents in infancy. B2 vitamin treatment dramatically improved the unpleasant body odor and the ratio of TMA/Cr vs TMAO/Cr in the urine in the children. Other patients presented a particular psychological or psychiatric phenotype.

Unraveling the effects of the gut microbiota composition and function on horse endurance physiology.

An integrated analysis of gut microbiota, blood biochemical and metabolome in 52 endurance horses was performed. Clustering by gut microbiota revealed the existence of two communities mainly driven by diet as host properties showed little effect. Community 1 presented lower richness and diversity, but higher dominance and rarity of species, including some pathobionts. Moreover, its microbiota composition was tightly linked to host blood metabolites related to lipid metabolism and glycolysis at basal time. Despite the lower fiber intake, community type 1 appeared more specialized to produce acetate as a mean of maintaining the energy supply as glucose concentrations fell during the race. On the other hand, community type 2 showed an enrichment of fibrolytic and cellulolytic bacteria as well as anaerobic fungi, coupled to a higher production of propionate and butyrate. The higher butyrate proportion in community 2 was not associated with protective effects on telomere lengths but could have ameliorated mucosal inflammation and oxidative status. The gut microbiota was neither associated with the blood biochemical markers nor metabolome during the endurance race, and did not provide a biomarker for race ranking or risk of failure to finish the race.

A First Step Toward Unraveling the Energy Metabolism in Endurance Horses: Comparison of Plasma Nuclear Magnetic Resonance Metabolomic Profiles Before and After Different Endurance Race Distances.

Endurance racing places high demands on energy metabolism pathways. Metabolomics can be used to investigate biochemical responses to endurance exercise in humans, laboratory animals, and horses. Although endurance horses have previously been assessed in the field (i.e., during races) using broad-window Nuclear Magnetic Resonance metabolomics, these studies included several different race locations, race distances, age classes, and race statuses (finisher or elimination). The present NMR metabolomics study focused on 40 endurance horses racing in three race categories over 90, 120, or 160 km. The three races took place in the same location. Given that energy metabolism is closely related to exercise intensity and duration (and therefore distance covered), the study's objective was to determine whether the metabolic pathways recruited during the race varied as a function of the total ride distance. For each horse, a plasma sample was collected the day before the race, and another was collected at the end of the race. Sixteen, 15, and 9 horses raced over 90, 120, and 160 km, respectively. Proton NMR spectra (500 MHz) were acquired for these 80 plasma samples. After processing, the spectra were divided into bins representing the NMR variables and then classified using orthogonal projection on latent structure models supervised by the sampling time (pre- or post-race) or the distance covered. The models revealed that the post-race metabolomic profiles are associated to the total ride distance groups. By combining biochemical assay results and NMR data in multiblock models, we further showed that enzymatic activities and metabolites are significantly associated to the race category. In the highest race category (160 km), there appears to be a metabolic switch from carbohydrate consumption to lipid consumption in order to maintain glycaemia. Furthermore, signs of protein breakdown were more apparent in the longest race category. The metabolic shift seen in the different racing categories could be related to a mixture of three important factors that are the ride distance, the training status and the inherited endurance capacity of the various horses competing.

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).

Determination of candidate metabolite biomarkers associated with recurrence of HCV-related hepatocellular carcinoma.

Hepatitis C virus (HCV) infection is associated with a high risk of developing hepatocellular carcinoma (HCC) and HCC recurrence remains the primary threat to outcomes after curative therapy. In this study, we compared recurrent and non-recurrent HCC patients treated with radiofrequency ablation (RFA) in order to identify characteristic metabolic profile variations associated with HCC recurrence. Gas chromatography-mass spectrometry (GC-MS) -based metabolomic analyses were conducted on serum samples obtained before and after RFA therapy. Significant variations were observed in metabolites in the glycerolipid, tricarboxylic acid (TCA) cycle, fatty acid, and amino acid pathways between recurrent and non-recurrent patients. Observed differences in metabolites associated with recurrence did not coincide before and after treatment except for fatty acids. Based on the comparison of serum metabolomes between recurrent and non-recurrent patients, key discriminatory metabolites were defined by a random forest (RF) test. Two combinations of these metabolites before and after RFA treatment showed outstanding performance in predicting HCV-related HCC recurrence, they were further confirmed by an external validation set. Our study showed that the determined combination of metabolites may be potential biomarkers for the prediction of HCC recurrence before and after RFA treatment.

NMR metabolomic signatures reveal predictive plasma metabolites associated with long-term risk of developing breast cancer.

Background: Combination of metabolomics and epidemiological approaches opens new perspectives for ground-breaking discoveries. The aim of the present study was to investigate for the first time whether plasma untargeted metabolomic profiles, established from a simple blood draw from healthy women, could contribute to predict the risk of developing breast cancer within the following decade and to better understand the aetiology of this complex disease. Methods: A prospective nested case-control study was set up in the Supplémentation en Vitamines et Minéraux Antioxydants (SU.VI.MAX) cohort, including 206 breast cancer cases diagnosed during a 13-year follow-up and 396 matched controls. Untargeted nuclear magnetic resonance (NMR) metabolomic profiles were established from baseline plasma samples. Multivariable conditional logistic regression models were computed for each individual NMR variable and for combinations of variables derived by principal component analysis. Results: Several metabolomic variables from 1D NMR spectroscopy were associated with breast cancer risk. Women characterized by higher fasting plasma levels of valine, lysine, arginine, glutamine, creatine, creatinine and glucose, and lower plasma levels of lipoproteins, lipids, glycoproteins, acetone, glycerol-derived compounds and unsaturated lipids had a higher risk of developing breast cancer. P-values ranged from 0.00007 [odds ratio (OR)T3vsT1=0.37 (0.23-0.61) for glycerol-derived compounds] to 0.04 [ORT3vsT1=1.61 (1.02-2.55) for glutamine]. Conclusion: This study highlighted associations between baseline NMR plasma metabolomic signatures and long-term breast cancer risk. These results provide interesting insights to better understand complex mechanisms involved in breast carcinogenesis and evoke plasma metabolic disorders favourable for carcinogenesis initiation. This study may contribute to develop screening strategies for the identification of at-risk women for breast cancer well before symptoms appear.

Identification of a discriminative metabolomic fingerprint of potential clinical relevance in saliva of patients with periodontitis using 1H nuclear magnetic resonance (NMR) spectroscopy.

Periodontitis is characterized by the loss of the supporting tissues of the teeth in an inflammatory-infectious context. The diagnosis relies on clinical and X-ray examination. Unfortunately, clinical signs of tissue destruction occur late in the disease progression. Therefore, it is mandatory to identify reliable biomarkers to facilitate a better and earlier management of this disease. To this end, saliva represents a promising fluid for identification of biomarkers as metabolomic fingerprints. The present study used high-resolution 1H-nuclear magnetic resonance (NMR) spectroscopy coupled with multivariate statistical analysis to identify the metabolic signature of active periodontitis. The metabolome of stimulated saliva of 26 patients with generalized periodontitis (18 chronic and 8 aggressive) was compared to that of 25 healthy controls. Principal Components Analysis (PCA), performed with clinical variables, indicated that the patient population was homogeneous, demonstrating a strong correlation between the clinical and the radiological variables used to assess the loss of periodontal tissues and criteria of active disease. Orthogonal Projection to Latent Structure (OPLS) analysis showed that patients with periodontitis can be discriminated from controls on the basis of metabolite concentrations in saliva with satisfactory explained variance (R2X = 0.81 and R2Y = 0.61) and predictability (Q2Y = 0.49, CV-AUROC = 0.94). Interestingly, this discrimination was irrespective of the type of generalized periodontitis, i.e. chronic or aggressive. Among the main discriminating metabolites were short chain fatty acids as butyrate, observed in higher concentrations, and lactate, γ-amino-butyrate, methanol, and threonine observed in lower concentrations in periodontitis. The association of lactate, GABA, and butyrate to generate an aggregated variable reached the best positive predictive value for diagnosis of periodontitis. In conclusion, this pilot study showed that 1H-NMR spectroscopy analysis of saliva could differentiate patients with periodontitis from controls. Therefore, this simple, robust, non-invasive method, may offer a significant help for early diagnosis and follow-up of periodontitis.

The impact of moderate altitude on exercise metabolism in recreational sportsmen: a nuclear magnetic resonance metabolomic approach.

Although it is known that altitude impairs performance in endurance sports, there is no consensus on the involvement of energy substrates in this process. The objective of the present study was to determine whether the metabolomic pathways used during endurance exercise differ according to whether the effort is performed at sea level or at moderate altitude (at the same exercise intensity, using proton nuclear magnetic resonance, 1H NMR). Twenty subjects performed two 60-min endurance exercise tests at sea level and at 2150 m at identical relative intensity on a cycle ergometer. Blood plasma was obtained from venous blood samples drawn before and after exercise. 1H NMR spectral analysis was then performed on the plasma samples. A multivariate statistical technique was applied to the NMR data. The respective relative intensities of the sea level and altitude endurance tests were essentially the same when expressed as a percentage of the maximal oxygen uptake measured during the corresponding incremental maximal exercise test. Lipid use was similar at sea level and at altitude. In the plasma, levels of glucose, glutamine, alanine, and branched-chain amino acids had decreased after exercise at altitude but not after exercise at sea level. The decrease in plasma glucose and free amino acid levels observed after exercise at altitude indicated that increased involvement of the protein pathway was necessary but not sufficient for the maintenance of glycaemia. Metabolomics is a powerful means of gaining insight into the metabolic changes induced by exercise at altitude.

Nuclear magnetic resonance metabolomics and human liver diseases: The principles and evidence associated with protein and carbohydrate metabolism.

During the last decade, metabolomics has become widely used in the field of human diseases. Numerous studies have demonstrated that this is a powerful technique for improving the understanding, diagnosis and management of various types of liver disease, such as acute and chronic liver diseases, and liver transplantation. Nuclear magnetic resonance (NMR) spectroscopy is one of the two most commonly applied methods for metabolomics. The aim of the present review was to investigate the results from recent key publications focusing on aspects of protein and carbohydrate metabolism. The review includes existing procedures, which are currently used for NMR data acquisition and statistical analysis. In addition, notable results obtained by these studies on protein and carbohydrate metabolism concerning human liver diseases are presented.

Understanding the response to endurance exercise using a systems biology approach: combining blood metabolomics, transcriptomics and miRNomics in horses.

BACKGROUND: Endurance exercise in horses requires adaptive processes involving physiological, biochemical, and cognitive-behavioral responses in an attempt to regain homeostasis. We hypothesized that the identification of the relationships between blood metabolome, transcriptome, and miRNome during endurance exercise in horses could provide significant insights into the molecular response to endurance exercise. For this reason, the serum metabolome and whole-blood transcriptome and miRNome data were obtained from ten horses before and after a 160 km endurance competition. RESULTS: We obtained a global regulatory network based on 11 unique metabolites, 263 metabolic genes and 5 miRNAs whose expression was significantly altered at T1 (post- endurance competition) relative to T0 (baseline, pre-endurance competition). This network provided new insights into the cross talk between the distinct molecular pathways (e.g. energy and oxygen sensing, oxidative stress, and inflammation) that were not detectable when analyzing single metabolites or transcripts alone. Single metabolites and transcripts were carrying out multiple roles and thus sharing several biochemical pathways. Using a regulatory impact factor metric analysis, this regulatory network was further confirmed at the transcription factor and miRNA levels. In an extended cohort of 31 independent animals, multiple factor analysis confirmed the strong associations between lactate, methylene derivatives, miR-21-5p, miR-16-5p, let-7 family and genes that coded proteins involved in metabolic reactions primarily related to energy, ubiquitin proteasome and lipopolysaccharide immune responses after the endurance competition. Multiple factor analysis also identified potential biomarkers at T0 for an increased likelihood for failure to finish an endurance competition. CONCLUSIONS: To the best of our knowledge, the present study is the first to provide a comprehensive and integrated overview of the metabolome, transcriptome, and miRNome co-regulatory networks that may have a key role in regulating the metabolic and immune response to endurance exercise in horses.

Case Studies in Physiology: Maximal oxygen consumption and performance in a centenarian cyclist.

The purpose of this study was to examine the physiological characteristics of an elite centenarian cyclist who, at 101 yr old, established the 1-h cycling record for individuals ≥100 yr old (24.25 km) and to determine the physiological factors associated with his performance improvement 2 yr later at 103 yr old (26.92 km; +11%). Before each record, he performed an incremental test on a cycling ergometer. For 2 yr, he trained 5,000 km/yr with a polarized training that involved cycling 80% of mileage at "light" rate of perceived exertion (RPE) ≤12 and 20% at "hard" RPE ≥15 at a cadence between 50 and 70 rpm. His body weight and lean body mass did not change, while his maximal oxygen consumption (V̇o2max) increased (31-35 ml·kg-1·min-1; +13%). Peak power output increased from 90 to 125 W (+39%), mainly because of increasing the maximal pedaling frequency (69-90 rpm; +30%). Maximal heart rate did not change (134-137 beats/min) in contrast to the maximal ventilation (57-70 l/min, +23%), increasing with both the respiratory frequency (38-41 cycles/min; +8%) and the tidal volume (1.5-1.7 liters; +13%). Respiratory exchange ratio increased (1.03-1.14) to the same extent as tolerance to V̇co2 In conclusion, it is possible to increase performance and V̇o2max with polarized training focusing on a high pedaling cadence even after turning 100 yr old.NEW & NOTEWORTHY This study shows, for the first time, that maximal oxygen consumption (+13%) and performance (+11%) can still be increased between 101 and 103 yr old with 2 yr of training and that a centenarian is able, at 103 yr old, to cover 26.9 km/h in 1 h.

Metabolomics with Nuclear Magnetic Resonance Spectroscopy in a Drosophila melanogaster Model of Surviving Sepsis.

Patients surviving sepsis demonstrate sustained inflammation, which has been associated with long-term complications. One of the main mechanisms behind sustained inflammation is a metabolic switch in parenchymal and immune cells, thus understanding metabolic alterations after sepsis may provide important insights to the pathophysiology of sepsis recovery. In this study, we explored metabolomics in a novel Drosophila melanogaster model of surviving sepsis using Nuclear Magnetic Resonance (NMR), to determine metabolite profiles. We used a model of percutaneous infection in Drosophila melanogaster to mimic sepsis. We had three experimental groups: sepsis survivors (infected with Staphylococcus aureus and treated with oral linezolid), sham (pricked with an aseptic needle), and unmanipulated (positive control). We performed metabolic measurements seven days after sepsis. We then implemented metabolites detected in NMR spectra into the MetExplore web server in order to identify the metabolic pathway alterations in sepsis surviving Drosophila. Our NMR metabolomic approach in a Drosophila model of recovery from sepsis clearly distinguished between all three groups and showed two different metabolomic signatures of inflammation. Sham flies had decreased levels of maltose, alanine, and glutamine, while their level of choline was increased. Sepsis survivors had a metabolic signature characterized by decreased glucose, maltose, tyrosine, beta-alanine, acetate, glutamine, and succinate.

Nuclear magnetic resonance spectroscopic analysis of salivary metabolome in sarcoidosis.

BACKGROUND: Sarcoidosis is a systemic granulomatous disease of unknown cause which has diverse clinical impacts, ranging from benign to very severe, which may therefore require systemic treatment. Only a few tools are currently available to monitor management in these patients. OBJECTIVES: As sarcoidosis is known to affect salivary glands, we hypothesized that analysis of saliva could reveal valuable biomarkers for disease management. We designed a comparative analysis of salivary metabolomics in patients and controls using Nuclear Magnetic Resonance (NMR). METHODS: Metabolomic profiles of saliva collected from 24 sarcoidosis patients and 45 controls were obtained by proton NMR spectroscopy with multivariate statistical analysis, followed by metabolite identification and pathway analysis. Oral and dental examinations were performed concomitantly, together with assessment of smoking habits. RESULTS: A predictive salivary metabolomic signature associated with sarcoidosis was computed with the Orthogonal Partial least squares discriminant analysis (OPLS) model. Six metabolites were altered in samples from sarcoidosis patients compared to controls, including decreased levels of methanol and butyrate and increased levels of lactate, acetate and N-butyrate. CONCLUSION: This study showed that NMR metabolomics can discriminate saliva samples from sarcoidosis patients and controls. According to these preliminary results, saliva studies in sarcoidosis patients would be particularly useful to identify potentially relevant biomarkers. A study based on a larger number of patients at different stages of the disease or with treated patients is needed to assess the clinical relevance of NMR metabolomics in sarcoidosis.

Sequential Serum Metabolomic Profiling after Radiofrequency Ablation of Hepatocellular Carcinoma Reveals Different Response Patterns According to Etiology.

Radiofrequency ablation (RFA) is commonly performed as a curative approach in patients with hepatocellular carcinoma (HCC); however, the risk of tumor recurrence is difficult to predict due to a lack of reliable clinical and biological markers, and identification of new biomarkers poses a major challenge for improving prognoses. Metabolomics is a promising technique that may lead to the identification and characterization of new disease fingerprints. The objective of the present study was to explore, preoperatively and at various time points post-RFA, the metabolic profile of serum samples from HCC patients to identify factors associated with treatment response and recurrence. Sequential sera obtained before and after RFA procedures for 120 patients with HCC due to cirrhosis were investigated using nuclear magnetic resonance metabolomics. A multilevel orthogonal projection to latent structure analysis was used to discriminate intraindividual metabolic changes in response to RFA treatment. Recurrence-free survival differed depending on the underlying cause of cirrhosis. The statistical model showed significant differences depending on whether the liver disease had a viral or nonviral etiology before RFA intervention (explained variance of R(2)Y = 0.89 and predictability of Q(2)Y = 0.34). These profiles were also associated with specific and distinct metabolic responses after RFA.