Microbiota Sensing by Mincle-Syk Axis in Dendritic Cells Regulates Interleukin-17 and -22 Production and Promotes Intestinal Barrier Integrity.

Production of interleukin-17 (IL-17) and IL-22 by T helper 17 (Th17) cells and group 3 innate lymphoid cells (ILC3s) in response to the gut microbiota ensures maintenance of intestinal barrier function. Here, we examined the mechanisms whereby the immune system detects microbiota in the steady state. A Syk-kinase-coupled signaling pathway in dendritic cells (DCs) was critical for commensal-dependent production of IL-17 and IL-22 by CD4+ T cells. The Syk-coupled C-type lectin receptor Mincle detected mucosal-resident commensals in the Peyer's patches (PPs), triggered IL-6 and IL-23p19 expression, and thereby regulated function of intestinal Th17- and IL-17-secreting ILCs. Mice deficient in Mincle or with selective depletion of Syk in CD11c+ cells had impaired production of intestinal RegIIIγ and IgA and increased systemic translocation of gut microbiota. Consequently, Mincle deficiency led to liver inflammation and deregulated lipid metabolism. Thus, sensing of commensals by Mincle and Syk signaling in CD11c+ cells reinforces intestinal immune barrier and promotes host-microbiota mutualism, preventing systemic inflammation.

A novel glucagon-like peptide 1/glucagon receptor dual agonist improves steatohepatitis and liver regeneration in mice.

Because nonalcoholic steatohepatitis (NASH) is associated with impaired liver regeneration, we investigated the effects of G49, a dual glucagon-like peptide-1/glucagon receptor agonist, on NASH and hepatic regeneration. C57Bl/6 mice fed chow or a methionine and choline-deficient (MCD) diet for 1 week were divided into 4 groups: control (chow diet), MCD diet, chow diet plus G49, and M+G49 (MCD diet plus G49). Mice fed a high-fat diet (HFD) for 10 weeks were divided into groups: HFD and H+G49 (HFD plus G49). Following 2 (MCD groups) or 3 (HFD groups) weeks of treatment with G49, partial hepatectomy (PH) was performed, and all mice were maintained on the same treatment schedule for 2 additional weeks. Analysis of liver function, hepatic regeneration, and comprehensive genomic and metabolic profiling were conducted. NASH was ameliorated in the M+G49 group, manifested by reduced inflammation, steatosis, oxidative stress, and apoptosis and increased mitochondrial biogenesis. G49 treatment was also associated with replenishment of intrahepatic glucose due to enhanced gluconeogenesis and reduced glucose use through the pentose phosphate cycle and oxidative metabolism. Following PH, G49 treatment increased survival, restored the cytokine-mediated priming phase, and enhanced the proliferative capacity and hepatic regeneration ratio in mice on the MCD diet. NASH markers remained decreased in M+G49 mice after PH, and glucose use was shifted to the pentose phosphate cycle and oxidative metabolism. G49 administered immediately after PH was also effective at alleviating the pathological changes induced by the MCD diet. Benefits in terms of liver regeneration were also found in mice fed HFD and treated with G49. CONCLUSION: Dual-acting glucagon-like peptide-1/glucagon receptor agonists such as G49 represent a novel therapeutic approach for patients with NASH and particularly those requiring PH. (Hepatology 2017;65:950-968).

Stereochemical and structural effects of (2R,6R)-hydroxynorketamine on the mitochondrial metabolome in PC-12 cells.

BACKGROUND: Impairment in mitochondrial biogenesis and function plays a key role in depression and anxiety, both of which being associated with changes in fatty acid and phospholipid metabolism. The antidepressant effects of (R,S)-ketamine have been linked to its conversion into (2S,6S;2R,6R)-hydroxynorketamine (HNK); however, the connection between structure and stereochemistry of ketamine and HNK in the mitochondrial homeostatic response has not yet been fully elucidated at a metabolic level. METHODS: We used a multi-platform, non-targeted metabolomics approach to study the change in mitochondrial metabolome of PC-12 cells treated with ketamine and HNK enantiomers. The identified metabolites were grouped into pathways in order to assess global responses. RESULTS: Treatment with (2R,6R)-HNK elicited the significant change in 49 metabolites and associated pathways implicated in fundamental mitochondrial functions such as TCA cycle, branched-chain amino acid biosynthetic pathway, glycoxylate metabolic pathway, and fatty acid ß-oxidation. The affected metabolites included glycerate, citrate, leucine, N,N-dimethylglycine, 3-hexenedioic acid, and carnitine and attenuated signals associated with 9 fatty acids and elaidic acid. Important metabolites involved in the purine and pyrimidine pathways were also affected by (2R-6R)-HNK. This global metabolic profile was not as strongly impacted by treatment with (2S,6S)-HNK, (R)- and (S)-ketamine and in some instances opposite effects were observed. CONCLUSIONS: The present data provide an overall view of the metabolic changes in mitochondrial function produced by (2R,6R)-HNK and related ketamine compounds and offer an insight into the source of the observed variance in antidepressant response elicited by the compounds.

Discriminant biomarkers of acute respiratory distress syndrome associated to H1N1 influenza identified by metabolomics HPLC-QTOF-MS/MS platform.

Acute respiratory distress syndrome (ARDS) is a serious complication of influenza A (H1N1) virus infection. Its pathogenesis is unknown and biomarkers are lacking. Untargeted metabolomics allows the analysis of the whole metabolome in a biological compartment, identifying patterns associated with specific conditions. We hypothesized that LC-MS could help identify discriminant metabolites able to define the metabolic alterations occurring in patients with influenza A (H1N1) virus infection that developed ARDS. Serum samples from patients diagnosed with 2009 influenza A (H1N1) virus infection with (n = 25) or without (n = 32) ARDS were obtained on the day of hospital admission and analyzed by LC-MS/MS. Metabolite identification was determined by MS/MS analysis and analysis of standards. The specificity of the patterns identified was confirmed in patients without 2009 influenza A(H1N1) virus pneumonia (15 without and 17 with ARDS). Twenty-three candidate biomarkers were found to be significantly different between the two groups, including lysophospholipids and sphingolipids related to inflammation; bile acids, tryptophan metabolites, and thyroxine, related to the metabolism of the gut microflora. Confirmation results demonstrated the specificity of major alterations occurring in ARDS patients with influenza A (H1N1) virus infection.

New insight on obesity and adipose-derived stem cells using comprehensive metabolomics.

Obesity affects the functional capability of adipose-derived stem cells (ASCs) and their effective use in regenerative medicine through mechanisms that are still poorly understood. In the present study we used a multiplatform [LC/MS, GC/MS and capillary electrophoresis/MS (CE/MS)], metabolomics, untargeted approach to investigate the metabolic alteration underlying the inequalities observed in obesity-derived ASCs. The metabolic fingerprint (metabolites within the cells) and footprint (metabolites secreted in the culture medium), from obesity- and non-obesity-derived ASCs of humans or mice, were characterized to provide valuable information. Metabolites associated with glycolysis, the tricarboxylic acid cycle, the pentose phosphate pathway and the polyol pathway were increased in the footprint of obesity-derived human ASCs, indicating alterations in carbohydrate metabolism, whereas, from the murine model, deep differences in lipid and amino acid catabolism were highlighted. Therefore, new insights on the ASCs' metabolome were provided that enhance our understanding of the processes underlying ASCs' stemness capacity and its relationship with obesity, in different cell models.

A Single In-Vial Dual Extraction Strategy for the Simultaneous Lipidomics and Proteomics Analysis of HDL and LDL Fractions.

A single in-vial dual extraction (IVDE) procedure for the subsequent analysis of lipids and proteins in the high-density lipoprotein (HDL) and low-density lipoprotein (LDL) fractions derived from the same biological sample is presented. On the basis of methyl-tert-butyl ether (MTBE) extraction, IVDE leads to the formation of three phases: a protein pellet at the bottom, an aqueous phase with polar compounds, and an ether phase with lipophilic compounds. After sample extraction, performed within a high-performance liquid chromatography vial insert, the ether phase was directly injected for lipid fingerprinting, while the protein pellet, after evaporation of the remaining sample, was used for proteomics analysis. Human HDL and LDL isolates were used to test the suitability of the IVDE methodology for lipid and protein analysis from a single sample in terms of data quality and matching composition to that of HDL and LDL. Subsequently, HDL and LDL fractions isolated from ApoE-KO and wild-type mice were used to validate the capacity of IVDE for revealing changes in lipid and protein abundance. Results indicate that IVDE can be successfully used for the subsequent analysis of lipids and proteins with the advantages of time saving, simplicity, and reduced sample amount.

Unveiling differences between patients with acute coronary syndrome with and without ST elevation through fingerprinting with CE-MS and HILIC-MS targeted analysis.

Differences in the degree and severity of Acute Coronary Syndrome, associated to differences in the electrocardiogram, together with blood tests of biomarkers classify patients for diagnosis and treatment. Cases where the electrocardiogram and/or biomarkers are not conclusive still appear, and there is a need for complementary biomarkers for routine determinations. Metabolomics approaches with blind fingerprinting could reveal differences in metabolites, which must be confirmed by means of targeted determinations. CE-MS and HILIC-MS are well suited for the determination of highly polar compounds, like those from to the intermediate metabolism, altered due to acute stress induced by myocardial infarction. Serum from patients with ST-elevated and non-ST elevated myocardial infarction was collected at intensive care and emergency units, and fingerprinted with CE-MS. Data pretreatment and analysis showed up carnitine-related compounds and amino acids differentially present in both groups. Acylcarnitines and amino acids were then quantitatively measured with HILIC-MS-QqQ. The significance of the differences and the sensitivity/specificity of each compound were individually evaluated. The ratio of free carnitine to acylcarnitines, together with the ratios of acetylcarnitine to betaine, to threonine, and to citrulline, showed high significance and area under the curve in the respective receiver operating characteristic curves. This study opens new possibilities for defining new sets of biomarkers for refining the diagnosis of the patients with difficult classification.

Metabolomics reveals metabolite changes in acute pulmonary embolism.

Pulmonary embolism (PE) is a common cardiovascular emergency which can lead to pulmonary hypertension (PH) and right ventricular failure as a consequence of pulmonary arterial bed occlusion. The diagnosis of PE is challenging due to nonspecific clinical presentation, which results in relatively high mortality. Moreover, the pathological factors associated with PE are poorly understood. Metabolomics can provide new highlights which can help in the understanding of the processes and even propose biomarkers for its diagnosis. In order to obtain more information about PE and PH, acute PE was induced in large white pigs and plasma was obtained before and after induction of PE. Metabolic fingerprints from plasma were obtained with LC-QTOF-MS (positive and negative ionization) and GC-Q-MS. Data pretreatment and statistical analysis (uni- and multivariate) were performed in order to compare metabolic fingerprints and to select the metabolites that showed higher loading for the classification (28 from LC and 19 from GC). The metabolites found differentially distributed among groups are mainly related to energy imbalance in hypoxic conditions, such as glycolysis-derived metabolites, ketone bodies, and TCA cycle intermediates, as well as a group of lipidic mediators that could be involved in the transduction of the signals to the cells such as sphingolipids and lysophospholipids, among others. Results presented in this report reveal that combination of LC-MS- and GC-MS-based metabolomics could be a powerful tool for diagnosis and understanding pathophysiological processes due to acute PE.

Metabolic profiling reveals the nutraceutical effect of Gongolaria abies-marina and Rosmarinus officinalis extracts in a type 1 diabetes animal model.

Nutraceuticals have gained increasing interest, prompting the need to investigate plant extracts for their beneficial properties and potential side effects. This study aimed to assess the nutraceutical effects of environmentally clean extracts from Rosmarinus officinalis and Gongolaria abies-marina (formerly Cystoseira abies-marina (Phaeophyceae)) on the metabolic profile of streptozotocin-induced diabetic rats. We conducted untargeted LC-QTOF-MS metabolic profiling on six groups of rats: three diabetic groups receiving either a placebo, R. officinalis, or G. abies-marina extracts, and three corresponding control groups. The metabolic analysis revealed significant alterations in the levels of various glycerophospholipids, sterol lipids, and fatty acyls. Both extracts influenced the metabolic profile, partially mitigating diabetes-induced changes. Notably, G. abies-marina extract had a more pronounced impact on the animals' metabolic profiles compared to R. officinalis. In conclusion, our findings suggest that environmentally clean extracts from R. officinalis and G. abies-marina possess nutraceutical potential, as they were able to modulate the metabolic profile in streptozotocin-induced diabetic rats. G. abies-marina extract exhibited a more substantial effect on metabolic alterations induced by diabetes compared to R. officinalis. These results warrant further exploration of these plant extracts for their potential in managing diabetes-related metabolic disturbances.

Metabolomic insights in advanced cardiomyopathy of chronic chagasic and idiopathic patients that underwent heart transplant.

Heart failure (HF) studies typically focus on ischemic and idiopathic heart diseases. Chronic chagasic cardiomyopathy (CCC) is a progressive degenerative inflammatory condition highly prevalent in Latin America that leads to a disturbance of cardiac conduction system. Despite its clinical and epidemiological importance, CCC molecular pathogenesis is poorly understood. Here we characterize and discriminate the plasma metabolomic profile of 15 patients with advanced HF referred for heart transplantation - 8 patients with CCC and 7 with idiopathic dilated cardiomyopathy (IDC) - using gas chromatography/quadrupole time-of-flight mass spectrometry. Compared to the 12 heart donor individuals, also included to represent the control (CTRL) scenario, patients with advanced HF exhibited a metabolic imbalance with 21 discriminating metabolites, mostly indicative of accumulation of fatty acids, amino acids and important components of the tricarboxylic acid (TCA) cycle. CCC vs. IDC analyses revealed a metabolic disparity between conditions, with 12 CCC distinctive metabolites vs. 11 IDC representative metabolites. Disturbances were mainly related to amino acid metabolism profile. Although mitochondrial dysfunction and loss of metabolic flexibility may be a central mechanistic event in advanced HF, metabolic imbalance differs between CCC and IDC populations, possibly explaining the dissimilar clinical course of Chagas' patients.

Eplerenone attenuated cardiac steatosis, apoptosis and diastolic dysfunction in experimental type-II diabetes.

BACKGROUND: Cardiac steatosis and apoptosis are key processes in diabetic cardiomyopathy, but the underlying mechanisms have not been elucidated, leading to a lack of effective therapy. The mineralocorticoid receptor blocker, eplerenone, has demonstrated anti-fibrotic actions in the diabetic heart. However, its effects on the fatty-acid accumulation and apoptotic responses have not been revealed. METHODS: Non-hypertensive Zucker Diabetic Fatty (ZDF) rats received eplerenone (25 mg/kg) or vehicle. Zucker Lean (ZL) rats were used as control (n = 10, each group). After 16 weeks, cardiac structure and function was examined, and plasma and hearts were isolated for biochemical and histological approaches. Cultured cardiomyocytes were used for in vitro assays to determine the direct effects of eplerenone on high fatty acid and high glucose exposed cells. RESULTS: In contrast to ZL, ZDF rats exhibited hyperglycemia, hyperlipidemia, insulin-resistance, cardiac steatosis and diastolic dysfunction. The ZDF myocardium also showed increased mitochondrial oxidation and apoptosis. Importantly, eplerenone mitigated these events without altering hyperglycemia. In cultured cardiomyocytes, high-concentrations of palmitate stimulated the fatty-acid uptake (in detriment of glucose assimilation), accumulation of lipid metabolites, mitochondrial dysfunction, and apoptosis. Interestingly, fatty-acid uptake, ceramides formation and apoptosis were also significantly ameliorated by eplerenone. CONCLUSIONS: By blocking mineralocorticoid receptors, eplerenone may attenuate cardiac steatosis and apoptosis, and subsequent remodelling and diastolic dysfunction in obese/type-II diabetic rats.

Fingerprinting-based metabolomic approach with LC-MS to sleep apnea and hypopnea syndrome: a pilot study.

Sleep apnea and hypopnea syndrome (SAHS) is a multicomponent disorder, with associated cardiovascular and metabolic alterations, second in order of frequency among respiratory disorders. Sleep apnea is diagnosed with an overnight sleep test called a polysomnogram, which requires having the patient in hospital. In addition, a more clear classification of patients according to mild and severe presentations would be desirable. The aim of the present study was to assess the relative metabolic changes in SAHS to identify new potential biomarkers for diagnosis, able to evaluate disease severity to establish response to therapeutic interventions and outcomes. For this purpose, metabolic fingerprinting represents a valuable strategy to monitor, in a nontargeted manner, the changes that are at the base of the pathophysiological mechanism of SAHS. Plasma samples of 33 SAHS patients were collected after polysomnography and analyzed with LC coupled to MS (LC-QTOF-MS). After data treatment and statistical analysis, signals differentiating nonsevere and severe patients were detected. Putative identification of 14 statistically significant features was obtained and changes that can be related to the episodes of hypoxia/reoxygenation (inflammation) have been highlighted. Among them, the patterns of variation of platelet activating factor and lysophospholipids, together with some compounds related to differential activity of the gut microflora (bile pigments and pipecolic acid) open new lines of research that will benefit our understanding of the alterations, offering new possibilities for adequate monitoring of the stage of the disease.

Impact of renal tubular Cpt1a overexpression on the kidney metabolome in the folic acid-induced fibrosis mouse model.

Background: Chronic kidney disease (CKD) is characterized by the progressive and irreversible deterioration of kidney function and structure with the appearance of renal fibrosis. A significant decrease in mitochondrial metabolism, specifically a reduction in fatty acid oxidation (FAO) in tubular cells, is observed in tubulointerstitial fibrosis, whereas FAO enhancement provides protection. Untargeted metabolomics offers the potential to provide a comprehensive analysis of the renal metabolome in the context of kidney injury. Methodology: Renal tissue from a carnitine palmitoyl transferase 1a (Cpt1a) overexpressing mouse model, which displays enhanced FAO in the renal tubule, subjected to folic acid nephropathy (FAN) was studied through a multiplatform untargeted metabolomics approach based on LC-MS, CE-MS and GC-MS analysis to achieve the highest coverage of the metabolome and lipidome affected by fibrosis. The expression of genes related to the biochemical routes showing significant changes was also evaluated. Results: By combining different tools for signal processing, statistical analysis and feature annotation, we were able to identify variations in 194 metabolites and lipids involved in many metabolic routes: TCA cycle, polyamines, one-carbon metabolism, amino acid metabolism, purine metabolism, FAO, glycerolipids and glycerophospholipids synthesis and degradation, glycosphingolipids interconversion, and sterol metabolism. We found several metabolites strongly altered by FAN, with no reversion induced by Cpt1a overexpression (v.g. citric acid), whereas other metabolites were influenced by CPT1A-induced FAO (v.g. glycine-betaine). Conclusion: It was implemented a successful multiplatform metabolomics approach for renal tissue analysis. Profound metabolic changes accompany CKD-associated fibrosis, some associated with tubular FAO failure. These results highlight the importance of addressing the crosstalk between metabolism and fibrosis when undertaking studies attempting to elucidate the mechanism of CKD progression.

Identifying subgroups of childhood obesity by using multiplatform metabotyping.

Introduction: Obesity results from an interplay between genetic predisposition and environmental factors such as diet, physical activity, culture, and socioeconomic status. Personalized treatments for obesity would be optimal, thus necessitating the identification of individual characteristics to improve the effectiveness of therapies. For example, genetic impairment of the leptin-melanocortin pathway can result in rare cases of severe early-onset obesity. Metabolomics has the potential to distinguish between a healthy and obese status; however, differentiating subsets of individuals within the obesity spectrum remains challenging. Factor analysis can integrate patient features from diverse sources, allowing an accurate subclassification of individuals. Methods: This study presents a workflow to identify metabotypes, particularly when routine clinical studies fail in patient categorization. 110 children with obesity (BMI > +2 SDS) genotyped for nine genes involved in the leptin-melanocortin pathway (CPE, MC3R, MC4R, MRAP2, NCOA1, PCSK1, POMC, SH2B1, and SIM1) and two glutamate receptor genes (GRM7 and GRIK1) were studied; 55 harboring heterozygous rare sequence variants and 55 with no variants. Anthropometric and routine clinical laboratory data were collected, and serum samples processed for untargeted metabolomic analysis using GC-q-MS and CE-TOF-MS and reversed-phase U(H)PLC-QTOF-MS/MS in positive and negative ionization modes. Following signal processing and multialignment, multivariate and univariate statistical analyses were applied to evaluate the genetic trait association with metabolomics data and clinical and routine laboratory features. Results and Discussion: Neither the presence of a heterozygous rare sequence variant nor clinical/routine laboratory features determined subgroups in the metabolomics data. To identify metabolomic subtypes, we applied Factor Analysis, by constructing a composite matrix from the five analytical platforms. Six factors were discovered and three different metabotypes. Subtle but neat differences in the circulating lipids, as well as in insulin sensitivity could be established, which opens the possibility to personalize the treatment according to the patients categorization into such obesity subtypes. Metabotyping in clinical contexts poses challenges due to the influence of various uncontrolled variables on metabolic phenotypes. However, this strategy reveals the potential to identify subsets of patients with similar clinical diagnoses but different metabolic conditions. This approach underscores the broader applicability of Factor Analysis in metabotyping across diverse clinical scenarios.

In-vial dual extraction for direct LC-MS analysis of plasma for comprehensive and highly reproducible metabolic fingerprinting.

Metabolic fingerprinting of biological tissues has become an important area of research, particularly in the biomarker discovery field. Methods have inherent analytical variation, and new approaches are necessary to ensure that the vast numbers of intact metabolites present in biofluids are detected. Here, we describe an in-vial dual extraction (IVDE) method and a direct injection method that shows the total number of features recovered to be over 4500 from a single 20 µL plasma aliquot. By applying a one-step extraction consisting of a lipophilic and hydrophilic layer within a single vial insert, we showed that analytical variation was decreased. This was achieved by reducing sample preparation stages including procedures of drying and transfers. The two phases in the vial, upper and lower, underwent HPLC-QTOF analysis on individually customized LC gradients in both positive and negative ionization modes. A 60 min lipid profiling HPLC-QTOF method for the lipophilic phase was specifically developed, enabling the separation and putative identification of fatty acids, glycerolipids, glycerophospholipids, sphingolipids, and sterols. The aqueous phase of the extract underwent direct injection onto a 45 min gradient, enabling the detection of both polarities. The IVDE method was compared to two traditional extraction methods. The first method was a two-step ether evaporation and IPA resuspension, and the second method was a methanol precipitation typically used in fingerprinting studies. The IVDE provided a 378% increase in reproducible features when compared to evaporation and a 269% increase when compared to the precipitate and inject method. As a proof of concept, the method was applied to an animal model of diabetes. A 2-fold increase in discriminant metabolites was found when comparing diabetic and control rats with IVDE. These discriminant metabolites accounted for around 600 entities, out of which 388 were identified in available databases.

Metabolomic study of plasma of patients with abdominal aortic aneurysm.

Abdominal aortic aneurysm (AAA) is an important health problem, both because of AAA rupture and death and because of increased cardiovascular mortality. Identification of new biomarkers of AAA may suggest novel pathological mechanisms and targets for new medical treatments to slow AAA progression. Metabolic changes in AAA patients were mainly related to carbohydrate and lipid metabolism and many of these changes can be associated with a situation of insulin resistance (which can be related to metabolic syndrome) together with altered amino acid metabolism. For the first time, metabolites that can be associated with differential metabolism by the gut microflora of AAA patients have also been found. Moreover, aminomalonic acid in plasma has been shown to be the metabolite with the biggest difference between patients suffering from large aneurysm (>5 cm) and controls.

Metabolomic approach with LC-QTOF to study the effect of a nutraceutical treatment on urine of diabetic rats.

The rat treated with streptozotocin has been proposed as the most appropriate model of systemic oxidative stress for studying antioxidant therapies. In that sense, rosemary extracts have long been recognized as having antioxidant properties, and folic acid may be able to improve endothelial progenitor cell function. A mixture containing both has been tested as a possible nutraceutical to improve health complications in diabetes. We have developed the methodology to evaluate metabolic changes in the urine of streptozotocin-induced diabetic rats after supplementing their diet with rosemary extract obtained with supercritical fluids (SFE) containing 10% folic acid in an acute but short-term study. It has been done with a metabolomics approach using LC-QTOF as an analytical tool. About 20 endogenous metabolites have been identified by databases and MS/MS showing statistically significant changes. Among them, several amino acids and their metabolites point to changes due to the effect of the gut microbiota. In addition, the comparison between control and streptozotocin-diabetic rats has permitted the showing of some metabolic coincidences between type 1 diabetes and other (possible) autoimmune diseases such as autism and/or Crohn's disease, and the nutraceutical intervention has succeeded in inducing changes in such biomarkers.

Unveiling Metabolic Phenotype Alterations in Anorexia Nervosa through Metabolomics.

Anorexia nervosa (AN) is a mental disorder characterized by an intense fear of weight gain that affects mainly young women. It courses with a negative body image leading to altered eating behaviors that have devastating physical, metabolic, and psychological consequences for the patients. Although its origin is postulated to be multifactorial, the etiology of AN remains unknown, and this increases the likelihood of chronification and relapsing. Thus, expanding the available knowledge on the pathophysiology of AN is of enormous interest. Metabolomics is proposed as a powerful tool for the elucidation of disease mechanisms and to provide new insights into the diagnosis, treatment, and prognosis of AN. A review of the literature related to studies of AN patients by employing metabolomic strategies to characterize the main alterations associated with the metabolic phenotype of AN during the last 10 years is described. The most common metabolic alterations are derived from chronic starvation, including amino acid, lipid, and carbohydrate disturbances. Nonetheless, recent findings have shifted the attention to gut-microbiota metabolites as possible factors contributing to AN development, progression, and maintenance. We have identified the areas of ongoing research in AN and propose further perspectives to improve our knowledge and understanding of this disease.

Lipidomic and Metabolomic Signature of Progression of Chronic Kidney Disease in Patients with Severe Obesity.

Severe obesity is a major risk for chronic kidney disease (CKD). Early detection and careful monitoring of renal function are critical for the prevention of CKD during obesity, since biopsies are not performed in patients with CKD and diagnosis is dependent on the assessment of clinical parameters. To explore whether distinct lipid and metabolic signatures in obesity may signify early stages of pathogenesis toward CKD, liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-high resolution accurate mass-mass spectrometry (GC-HRAM-MS) analyses were performed in the serum and the urine of severely obese patients with and without CKD. Moreover, the impact of bariatric surgery (BS) in lipid and metabolic signature was also studied, through LC-MS and GC-HRAM-MS analyses in the serum and urine of patients with severe obesity and CKD before and after undergoing BS. Regarding patients with severe obesity and CKD compared to severely obese patients without CKD, serum lipidome analysis revealed significant differences in lipid signature. Furthermore, serum metabolomics profile revealed significant changes in specific amino acids, with isoleucine and tyrosine, increased in CKD patients compared with patients without CKD. LC-MS and GC-HRAM-MS analysis in serum of patients with severe obesity and CKD after BS showed downregulation of levels of triglycerides (TGs) and diglycerides (DGs) as well as a decrease in branched-chain amino acid (BCAA), lysine, threonine, proline, and serine. In addition, BS removed most of the correlations in CKD patients against biochemical parameters related to kidney dysfunction. Concerning urine analysis, hippuric acid, valine and glutamine were significantly decreased in urine from CKD patients after surgery. Interestingly, bariatric surgery did not restore all the lipid species, some of them decreased, hence drawing attention to them as potential targets for early diagnosis or therapeutic intervention. Results obtained in this study would justify the use of comprehensive mass spectrometry-based lipidomics to measure other lipids aside from conventional lipid profiles and to validate possible early markers of risk of CKD in patients with severe obesity.