Amino acid levels in nascent metabolic syndrome: A contributor to the pro-inflammatory burden

Grape Seed Proanthocyanidin Extract Attenuates Cafeteria-Diet-Induced Liver Metabolic Disturbances in Rats: Influence of Photoperiod

This study investigated the influence of photoperiod (day length) on the efficacy of grape seed proanthocyanidin extract (GSPE) in mitigating metabolic disorders in obese rats fed a cafeteria diet. Rats were exposed to standard (L12), long (L18), or short (L6) photoperiods and treated with GSPE or vehicle. In the standard photoperiod, GSPE reduced body weight gain (50.5%), total cholesterol (37%), and triglycerides (34.8%), while increasing the expression of hepatic metabolic genes. In the long photoperiod, GSPE tended to decrease body weight gain, increased testosterone levels (68.3%), decreased liver weight (12.4%), and decreased reverse serum amino acids. In the short photoperiod, GSPE reduced glycemia (~10%) and lowered triglyceride levels (38.5%), with effects modified by diet. The standard photoperiod showed the greatest efficacy against metabolic syndrome-associated diseases. The study showed how day length affects GSPE's benefits and underscores considering biological rhythms in metabolic disease therapies.

Untargeted metabolomics and phenotype data indicate the therapeutic and prophylactic potential of Lysimachia candida Lindl. towards high-fat high-fructose-induced metabolic syndrome in rats

The present study evaluated the therapeutic potential of the medicinal plant Lysimachia candida Lindl. against metabolic syndrome in male SD rats fed with a high-fat high-fructose (HFHF) diet. Methanolic extract of Lysimachia candida Lindl. (250 mg kg-1 body weight p.o.) was administrated to the HFHF-fed rats daily for 20 weeks. Blood samples were collected, and blood glucose levels and relevant biochemical parameters were analysed and used for the assessment of metabolic disease phenotypes. In this study, Lysimachia candida decreased HFHF diet-induced phenotypes of metabolic syndrome, i.e., obesity, blood glucose level, hepatic triglycerides, free fatty acids, and insulin resistance. Liquid chromatography-mass spectrometry-based metabolomics was done to study the dynamics of metabolic changes in the serum during disease progression in the presence and absence of the treatment. Furthermore, multivariate data analysis approaches have been employed to identify metabolites responsible for disease progression. Lysimachia candida Lindl. plant extract restored the metabolites that are involved in the biosynthesis and degradation of amino acids, fatty acid metabolism and vitamin metabolism. Interestingly, the results depicted that the treatment with the plant extract restored the levels of acetylated amino acids and their derivatives, which are involved in the regulation of beta cell function, glucose homeostasis, insulin secretion, and metabolic syndrome phenotypes. Furthermore, we observed restoration in the levels of indole derivatives and N-acetylgalactosamine with the treatment, which indicates a cross-talk between the gut microbiome and the metabolic syndrome. Therefore, the present study revealed the potential mechanism of Lysimachia candida Lindl. extract to prevent metabolic syndrome in rats.

Recent insights of obesity-induced gut and adipose tissue dysbiosis in type 2 diabetes

An imbalance in microbial homeostasis, referred to as dysbiosis, is critically associated with the progression of obesity-induced metabolic disorders including type 2 diabetes (T2D). Alteration in gut microbial diversity and the abundance of pathogenic bacteria disrupt metabolic homeostasis and potentiate chronic inflammation, due to intestinal leakage or release of a diverse range of microbial metabolites. The obesity-associated shifts in gut microbial diversity worsen the triglyceride and cholesterol level that regulates adipogenesis, lipolysis, and fatty acid oxidation. Moreover, an intricate interaction of the gut-brain axis coupled with the altered microbiome profile and microbiome-derived metabolites disrupt bidirectional communication for instigating insulin resistance. Furthermore, a distinct microbial community within visceral adipose tissue is associated with its dysfunction in obese T2D individuals. The specific bacterial signature was found in the mesenteric adipose tissue of T2D patients. Recently, it has been shown that in Crohn's disease, the gut-derived bacterium Clostridium innocuum translocated to the mesenteric adipose tissue and modulates its function by inducing M2 macrophage polarization, increasing adipogenesis, and promoting microbial surveillance. Considering these facts, modulation of microbiota in the gut and adipose tissue could serve as one of the contemporary approaches to manage T2D by using prebiotics, probiotics, or faecal microbial transplantation. Altogether, this review consolidates the current knowledge on gut and adipose tissue dysbiosis and its role in the development and progression of obesity-induced T2D. It emphasizes the significance of the gut microbiota and its metabolites as well as the alteration of adipose tissue microbiome profile for promoting adipose tissue dysfunction, and identifying novel therapeutic strategies, providing valuable insights and directions for future research and potential clinical interventions.

Depiction of Branched-Chain Amino Acids (BCAAs) in Diabetes with a Focus on Diabetic Microvascular Complications

Type 2 diabetes mellitus (T2DM) still holds the title as one of the most debilitating chronic diseases with rising prevalence and incidence, including its complications such as retinal, renal, and peripheral nerve disease. In order to develop novel molecules for diagnosis and treatment, a deep understanding of the complex molecular pathways is imperative. Currently, the existing agents for T2DM treatment target only blood glucose levels. Over the past decades, specific building blocks of proteins-branched-chain amino acids (BCAAs) including leucine, isoleucine, and valine-have gained attention because they are linked with insulin resistance, pre-diabetes, and diabetes development. In this review, we discuss the hypothetical link between BCAA metabolism, insulin resistance, T2DM, and its microvascular complications including diabetic retinopathy and diabetic nephropathy. Further research on these amino acids and their derivates may eventually pave the way to novel biomarkers or therapeutic concepts for the treatment of diabetes and its accompanied complications.

Identification of candidate metabolite biomarkers for metabolic syndrome and its five components in population-based human cohorts

BACKGROUND

Metabolic Syndrome (MetS) is characterized by risk factors such as abdominal obesity, hypertriglyceridemia, low high-density lipoprotein cholesterol (HDL-C), hypertension, and hyperglycemia, which contribute to the development of cardiovascular disease and type 2 diabetes. Here, we aim to identify candidate metabolite biomarkers of MetS and its associated risk factors to better understand the complex interplay of underlying signaling pathways.

METHODS

We quantified serum samples of the KORA F4 study participants (N = 2815) and analyzed 121 metabolites. Multiple regression models adjusted for clinical and lifestyle covariates were used to identify metabolites that were Bonferroni significantly associated with MetS. These findings were replicated in the SHIP-TREND-0 study (N = 988) and further analyzed for the association of replicated metabolites with the five components of MetS. Database-driven networks of the identified metabolites and their interacting enzymes were also constructed.

RESULTS

We identified and replicated 56 MetS-specific metabolites: 13 were positively associated (e.g., Val, Leu/Ile, Phe, and Tyr), and 43 were negatively associated (e.g., Gly, Ser, and 40 lipids). Moreover, the majority (89%) and minority (23%) of MetS-specific metabolites were associated with low HDL-C and hypertension, respectively. One lipid, lysoPC a C18:2, was negatively associated with MetS and all of its five components, indicating that individuals with MetS and each of the risk factors had lower concentrations of lysoPC a C18:2 compared to corresponding controls. Our metabolic networks elucidated these observations by revealing impaired catabolism of branched-chain and aromatic amino acids, as well as accelerated Gly catabolism.

CONCLUSION

Our identified candidate metabolite biomarkers are associated with the pathophysiology of MetS and its risk factors. They could facilitate the development of therapeutic strategies to prevent type 2 diabetes and cardiovascular disease. For instance, elevated levels of lysoPC a C18:2 may protect MetS and its five risk components. More in-depth studies are necessary to determine the mechanism of key metabolites in the MetS pathophysiology.

Chronometabolism: The Timing of the Consumption of Meals Has a Greater Influence Than Glycemic Index (GI) on the Postprandial Metabolome

Eating late in the day is associated with circadian desynchrony, resulting in dysregulated metabolism and increased cardiometabolic disease risk. However, the underlying mechanisms remain unclear. Using targeted metabolomics of postprandial plasma samples from a secondary analysis of a randomised 2 × 2 crossover study in 36 healthy older Chinese adults, we have compared postprandial metabolic responses between high (HI) glycemic index (GI) or low-GI (LO) meals, consumed either at breakfast (BR) or at dinner (DI). 29 out of 234 plasma metabolites exhibited significant differences (p < 0.05) in postprandial AUC between BR and DI sessions, whereas only five metabolites were significantly different between HI and LO sessions. There were no significant interactions between intake timing and meal GI. Lower glutamine: glutamate ratio, lower lysine and higher trimethyllysine (TML) levels were found during DI compared with BR, along with greater postprandial reductions (δAUC) in creatine and ornithine levels during DI, indicating a worse metabolic state during the evening DI period. Greater reductions (δAUC) in postprandial creatine and ornithine were also observed during HI compared with LO (both p < 0.05). These metabolomic changes may indicate potential molecular signatures and/or pathways linking metabolic responses with cardiometabolic disease risk between different meal intake timings and/or meals with variable GI.

Identification of Biomarkers Related to Metabolically Unhealthy Obesity in Korean Obese Adolescents: A Cross-Sectional Study

BACKGROUND

The current study aimed to screen for relationships and different potential metabolic biomarkers involved between metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO) in adolescents.

METHODS

The study included 148 obese adolescents aged between 14 and 16. The study participants were divided into MUO and MHO groups based on the age-specific adolescent metabolic syndrome (MetS) criteria of the International Diabetes Federation. The current study was conducted to investigate the clinical and metabolic differences between the MHO and MUO groups. Multivariate analyses were conducted to investigate the metabolites as independent predictors for the odds ratio and the presence of the MetS.

RESULTS

There were significant differences in the three acylcarnitines, five amino acids, glutamine/glutamate ratio, three biogenic amines, two glycerophospholipids, and the triglyceride-glucose index between the MUO group and those in the MHO group. Moreover, several metabolites were associated with the prevalence of MUO. Additionally, several metabolites were inversely correlated with MHO in the MUO group.

CONCLUSIONS

In this study, the biomarkers found in this study have the potential to reflect the clinical outcomes of the MUO group. These biomarkers will lead to a better understanding of MetS in obese adolescents.

Prospective Metabolomic Studies in Precision Medicine: The AKRIBEA Project

For a long time, conventional medicine has analysed biomolecules to diagnose diseases. Yet, this approach has proven valid only for a limited number of metabolites and often through a bijective relationship with the disease (i.e. glucose relationship with diabetes), ultimately offering incomplete diagnostic value. Nowadays, precision medicine emerges as an option to improve the prevention and/or treatment of numerous pathologies, focusing on the molecular mechanisms, acting in a patient-specific dimension, and leveraging multiple contributing factors such as genetic, environmental, or lifestyle. Metabolomics grasps the required subcellular complexity while being sensitive to all these factors, which results in a most suitable technique for precision medicine. The aim of this chapter is to describe how NMR-based metabolomics can be integrated in the design of a precision medicine strategy, using the Precision Medicine Initiative of the Basque Country (the AKRIBEA project) as a case study. To that end, we will illustrate the procedures to be followed when conducting an NMR-based metabolomics study with a large cohort of individuals, emphasizing the critical points. The chapter will conclude with the discussion of some relevant biomedical applications.

Dual Classification Approach for the Rapid Discrimination of Metabolic Syndrome by FTIR

Metabolic syndrome is a complex of interrelated risk factors for cardiovascular disease and diabetes. Thus, new point-of-care diagnostic tools are essential for unambiguously distinguishing MetS patients, providing results in rapid time. Herein, we evaluated the potential of Fourier transform infrared spectroscopy combined with chemometric tools to detect spectra markers indicative of metabolic syndrome. Around 105 plasma samples were collected and divided into two groups according to the presence of at least three of the five clinical parameters used for MetS diagnosis. A dual classification approach was studied based on selecting the most important spectral variable and classification methods, linear discriminant analysis (LDA) and SIMCA class modelling, respectively. The same classification methods were applied to measured clinical parameters at our disposal. Thus, the classification's performance on reduced spectra fingerprints and measured clinical parameters were compared. Both approaches achieved excellent discrimination results among groups, providing almost 100% accuracy. Nevertheless, SIMCA class modelling showed higher classification performance between MetS and no MetS for IR-reduced variables compared to clinical variables. We finally discuss the potential of this method to be used as a supportive diagnostic or screening tool in clinical routines.

Impact of Phenol-Enriched Olive Oils on Serum Metabonome and Its Relationship with Cardiometabolic Parameters: A Randomized, Double-Blind, Cross-Over, Controlled Trial

Phenol-rich foods consumption such as virgin olive oil (VOO) has been shown to have beneficial effects on cardiovascular diseases. The broader biochemical impact of VOO and phenol-enriched OOs remains, however, unclear. A randomized, double-blind, cross-over, controlled trial was performed with thirty-three hypercholesterolemic individuals who ingested for 3-weeks (25 mL/day): (1) an OO enriched with its own olive oil phenolic compounds (PCs) (500 ppm; FOO); (2) an OO enriched with its own olive oil PCs (250 ppm) plus thyme PCs (250 ppm; FOOT); and (3) a VOO with low phenolic content (80 ppm). Serum lipid and glycemic profiles, serum ¹H-NMR spectroscopy-based metabolomics, endothelial function, blood pressure, and cardiovascular risk were measured. We combined OPLS-DA with machine learning modelling to identify metabolites discrimination of the treatment groups. Both phenol-enriched OO interventions decreased the levels of glutamine, creatinine, creatine, dimethylamine, and histidine in comparison to VOO one. In addition, FOOT decreased the plasma levels of glycine and DMSO2 compared to VOO, while FOO decreased the circulating alanine concentrations but increased the plasma levels of acetone and 3-HB compared to VOO. Based on these findings, phenol-enriched OOs were shown to result in a favorable shift in the circulating metabolic phenotype, inducing a reduction in metabolites associated with cardiometabolic diseases.

Multiomics technologies: role in disease biomarker discoveries and therapeutics

 

Medical research has been revolutionized after the publication of the full human genome. This was the major landmark that paved the way for understanding the biological functions of different macro and micro molecules. With the advent of different high-throughput technologies, biomedical research was further revolutionized. These technologies constitute genomics, transcriptomics, proteomics, metabolomics, etc. Collectively, these high-throughputs are referred to as multi-omics technologies. In the biomedical field, these omics technologies act as efficient and effective tools for disease diagnosis, management, monitoring, treatment and discovery of certain novel disease biomarkers. Genotyping arrays and other transcriptomic studies have helped us to elucidate the gene expression patterns in different biological states, i.e. healthy and diseased states. Further omics technologies such as proteomics and metabolomics have an important role in predicting the role of different biological molecules in an organism. It is because of these high throughput omics technologies that we have been able to fully understand the role of different genes, proteins, metabolites and biological pathways in a diseased condition. To understand a complex biological process, it is important to apply an integrative approach that analyses the multi-omics data in order to highlight the possible interrelationships of the involved biomolecules and their functions. Furthermore, these omics technologies offer an important opportunity to understand the information that underlies disease. In the current review, we will discuss the importance of omics technologies as promising tools to understand the role of different biomolecules in diseases such as cancer, cardiovascular diseases, neurodegenerative diseases and diabetes.

SUMMARY POINTS

Simultaneous analysis of amino acids based on discriminative 19F NMR spectroscopy

The simultaneous analysis of amino acids (AAs) is crucial for human health, diagnosis and treatment of disease, and nutritional quality evaluation in foodstuffs. Here, we establish an easy and rapid method for the simultaneous analysis of AAs using a single reagent 2-(trifluoromethyl)benzaldehyde (oTFMBA) based on spectral-separation-enabled ¹⁹F NMR spectroscopy. oTFMBA, a highly sensitive chemosensor, is capable of analyzing 19 proteinogenic AAs or non-amino acid amines (non-AAs) in a complex mixture by adjusting the pH in a toilless way. The ¹⁹F signals of oTFMBA-labeled AAs are distributed over a wide range of ∼ 0.7 ppm, demonstrating oTFMBA with higher resolution for simultaneous analysis of AAs compared to the o-phthaldialdehyde (OPA) method (<0.6 ppm). Additionally, 12 AAs were unambiguously identified in human urine, including Asp, Ser, Gly, Thr, Glu, Arg, Ala, Val, Ile, Tyr, His, and Phe. Furthermore, our method's detection limit for AAs is 5.83 μM, illustrating sensitivity with an ∼100-fold improvement over the OPA method. This work represents an approach to the analysis of AAs or non-AAs in a complicated mixture (even biofluid) using a ¹⁹F NMR probe with high sensitivity, which is of great significance for the simultaneous analysis of multiple analytes.

Branched Chain Amino Acids are associated with Metabolic Complications in Liver Transplant Recipients

BACKGROUND

Obesity, dyslipidemia and type 2 diabetes (T2D) contribute substantially to increased cardiovascular morbidity and mortality in patients after orthotopic liver transplantation (OLTx). Elevated plasma branched chain amino acids (BCAA) are linked to metabolic disturbances and cardiovascular disease (CVD) risk profiles in several non-OLTx populations.

METHODS

Cross-sectional analysis of liver transplant recipients from TransplantLines, a single-center biobank and cohort study. BCAA plasma levels were measured by means of nuclear-magnetic resonance spectroscopy. CVD and cardiometabolic factors were collected by using data from electronic patient records. Associations were determined between BCAA plasma levels and T2D, Metabolic Syndrome (MetS), CVD as well as mTOR inhibition in liver transplant recipients.

RESULTS

336 Patients were divided into sex-stratified tertiles of total BCAA. MetS (P<0.001) and T2D (P=0.002) were significantly more frequent in subjects in the highest BCAA tertile. In logistic regression analyses, the multivariable adjusted odds ratio (OR) per 1 standard deviation increase in BCAA was 1.68 (95%CI: 1.18-2.20, P=0.003) for MetS and 1.60 (95%CI: 1.14-2.23, P=0.006) for T2D. Use of Sirolimus (mTOR inhibitor) was significantly associated with higher BCAA plasma levels, independent of age, sex, time after OLTx, MetS and other immunosuppressive medication (adjusted P=0.002).

CONCLUSION

Elevated BCAA plasma levels are associated with T2D, MetS and use of Sirolimus in liver transplant recipients. BCAA plasma levels may represent a valuable biomarker for cardiometabolic complications after OLTx.

Multi-stage metabolomics and genetic analyses identified metabolite biomarkers of metabolic syndrome and their genetic determinants

Background

Metabolic syndrome (MetS) is a cluster of multiple cardiometabolic risk factors that increase the risk of type 2 diabetes and cardiovascular diseases. Identifying novel biomarkers of MetS and their genetic associations could provide insights into the mechanisms of cardiometabolic diseases.

Methods

Potential MetS-associated metabolites were screened and internally validated by untargeted metabolomics analyses among 693 patients with MetS and 705 controls. External validation was conducted using two well-established targeted metabolomic methods among 149 patients with MetS and 253 controls. The genetic associations of metabolites were determined by linear regression using our previous genome-wide SNP data. Causal relationships were assessed using a one-sample Mendelian Randomization (MR) approach.

Findings

Nine metabolites were ultimately found to be associated with MetS or its components. Five metabolites, including LysoPC(14:0), LysoPC(15:0), propionyl carnitine, phenylalanine, and docosapentaenoic acid (DPA) were selected to construct a metabolite risk score (MRS), which was found to have a dose-response relationship with MetS and metabolic abnormalities. Moreover, MRS displayed a good ability to differentiate MetS and metabolic abnormalities. Three SNPs (rs11635491, rs7067822, and rs1952458) were associated with LysoPC(15:0). Two SNPs, rs1952458 and rs11635491 were found to be marginally correlated with several MetS components. MR analyses showed that a higher LysoPC(15:0) level was causally associated with the risk of overweight/obesity, dyslipidaemia, high uric acid, high insulin and high HOMA-IR.

Interpretation

We identified five metabolite biomarkers of MetS and three SNPs associated with LysoPC(15:0). MR analyses revealed that abnormal LysoPC metabolism may be causally linked the metabolic risk.

Funding

This work was supported by grants from the National Key Research and Development Program of China (2017YFC0907004).

Branched-chain Amino Acids and Relationship With Inflammation in Youth With Obesity: A Randomized Controlled Intervention Study

CONTEXT

Elevated concentrations of branched-chain amino acids (BCAA) are strong predictors of type 2 diabetes mellitus (T2DM). Their association with cardiovascular disease (CVD) remains uncertain, particularly in youth.

OBJECTIVE

We investigated the role of BCAA and aromatic amino acids (AAA) in obesity, their relationships with novel biomarkers of CVD, and response to a physical activity-based lifestyle intervention (PAL-I) in a randomized controlled study in youth with normal weight (NW) and obesity (OB).

METHODS

Age (14-18 years) and Tanner stage (≥IV) matched youth (OB, n = 15 and NW, n = 6) were studied; the 15 participants with OB underwent a 3-month randomized controlled PAL-I. Circulating amino acid profile, glucose, insulin, lipids, adiponectin, retinol binding protein-4, fibrinogen, high-sensitivity C-reactive protein, interleukin-6, and 25-hydroxy vitamin-D, along with body composition, were measured at baseline and after PAL-I. Independent t tests, analysis of covariance, and mixed-effect models were used for analysis of the data.

RESULTS

Compared with NW, the concentration of various amino acids, including BCAA and AAA, were altered in OB (P < 0.05). BCAA and AAA showed baseline correlations with body composition and novel biomarkers of CVD, particularly inflammatory factors (all P < 0.05). The PAL-I produced only negligible effects (P > 0.05) on BCAA and AAA. Glutamine, glycine, and aspartic acid decreased with PAL-I (all P < 0.05).

CONCLUSION

The novel finding of the BCAA-inflammation relationship, along with strong correlations with nontraditional biomarkers of CVD, may raise the prospect of BCAA as a biomarker of CVD and evoke a potential link between obesity, T2DM, and CVD.

Multi-omics profiling: the way towards precision medicine in metabolic diseases

Metabolic diseases including type 2 diabetes mellitus (T2DM), non-alcoholic fatty liver disease (NAFLD), and metabolic syndrome (MetS) are alarming health burdens around the world, while therapies for these diseases are far from satisfying as their etiologies are not completely clear yet. T2DM, NAFLD, and MetS are all complex and multifactorial metabolic disorders based on the interactions between genetics and environment. Omics studies such as genetics, transcriptomics, epigenetics, proteomics, and metabolomics are all promising approaches in accurately characterizing these diseases. And the most effective treatments for individuals can be achieved via omics pathways, which is the theme of precision medicine. In this review, we summarized the multi-omics studies of T2DM, NAFLD, and MetS in recent years, provided a theoretical basis for their pathogenesis and the effective prevention and treatment, and highlighted the biomarkers and future strategies for precision medicine.

Metabolomic connections between schizophrenia, antipsychotic drugs and metabolic syndrome: A variety of players

BACKGROUND

Diagnosis of schizophrenia lacks of reliable medical diagnostic tests and robust biomarkers applied to clinical practice. Schizophrenic patients undergoing treatment with antipsychotics suffer a reduced life expectancy due to metabolic disarrangements that co-exist with their mental illness and predispose them to develop metabolic syndrome, also exacerbated by medication. Metabolomics is an emerging and potent technology able to accelerate this biomedical research. <P> Aim: This review focus on a detailed vision of the molecular mechanisms involved both in schizophrenia and antipsychotic-induced metabolic syndrome, based on innovative metabolites that consistently change in nascent metabolic syndrome, drug-naïve, first episode psychosis and/or schizophrenic patients compared to healthy subjects. <P> Main lines: Supported by metabolomic approaches, although not exclusively, noteworthy variations are reported mainly through serum samples of patients and controls in several scenes: 1) alterations in fatty acids, inflammatory response indicators, amino acids and biogenic amines, biometals and gut microbiota metabolites (schizophrenia); 2) alterations in metabolites involved in carbohydrate and gut microbiota metabolism, inflammation and oxidative stress (metabolic syndrome), some of them shared with the schizophrenia scene; 3) alterations of cytokines secreted by adipose tissue, phosphatidylcholines, acylcarnitines, Sirtuin 1, orexin-A and changes in microbiota composition (antipsychotic-induced metabolic syndrome). <P> Conclusion: Novel insights into the pathogenesis of schizophrenia and metabolic side-effects associated to its antipsychotic treatment, represent an urgent request for scientifics and clinicians. Leptin, carnitines, adiponectin, insulin or interleukin-6 represent some examples of candidate biomarkers. Cutting-edge technologies like metabolomics have the power of strengthen research for achieving preventive, diagnostic and therapeutical solutions for schizophrenia.

Urine organic acids may be useful biomarkers for metabolic syndrome and its components in Korean adults

OBJECTIVES

Although metabolic syndrome (MetS) and its components are defined clinically, those with MetS may have various derangements in metabolic pathways. Thus, this study aimed to evaluate the traits of urine organic acid metabolites indicating the metabolic intermediates of the pathways in the subjects with MetS.

METHODS

This cross-sectional study included 246 men and 283 women in a hospital health check-up setting. Urine organic acid metabolites were assayed via high-performance liquid chromatography-mass spectrometry analyses. A high level of each metabolite was defined as the fifth quintile of the distribution.

RESULTS

The subjects with MetS had high levels of pyruvate, α-ketoglutarate, α-ketoisovalerate, α-ketoisocaproate, formiminoglutamate, and quinolinate (odds ratios from 1.915 to 2.809 in logistic models adjusted for age and sex). Among the metabolites, pyruvate, formiminoglutamate, and quinolinate were not independent of homeostatic model assessment of insulin resistance (HOMA2-IR). Several metabolites were associated with one or more components of MetS and HOMA2-IR.

CONCLUSIONS

Urine organic acid metabolites in MetS are characterized in altered carbohydrate and amino acid metabolism. MetS shared some traits in insulin resistance. These findings may promote the understanding of the pathophysiology of MetS.

A molecular signature for the metabolic syndrome by urine metabolomics

Background

Metabolic syndrome (MetS) is a multimorbid long-term condition without consensual medical definition and a diagnostic based on compatible symptomatology. Here we have investigated the molecular signature of MetS in urine.

Methods

We used NMR-based metabolomics to investigate a European cohort including urine samples from 11,754 individuals (18–75 years old, 41% females), designed to populate all the intermediate conditions in MetS, from subjects without any risk factor up to individuals with developed MetS (4–5%, depending on the definition). A set of quantified metabolites were integrated from the urine spectra to obtain metabolic models (one for each definition), to discriminate between individuals with MetS.

Results

MetS progression produces a continuous and monotonic variation of the urine metabolome, characterized by up- or down-regulation of the pertinent metabolites (17 in total, including glucose, lipids, aromatic amino acids, salicyluric acid, maltitol, trimethylamine N-oxide, and p-cresol sulfate) with some of the metabolites associated to MetS for the first time. This metabolic signature, based solely on information extracted from the urine spectrum, adds a molecular dimension to MetS definition and it was used to generate models that can identify subjects with MetS (AUROC values between 0.83 and 0.87). This signature is particularly suitable to add meaning to the conditions that are in the interface between healthy subjects and MetS patients. Aging and non-alcoholic fatty liver disease are also risk factors that may enhance MetS probability, but they do not directly interfere with the metabolic discrimination of the syndrome.

Conclusions

Urine metabolomics, studied by NMR spectroscopy, unravelled a set of metabolites that concomitantly evolve with MetS progression, that were used to derive and validate a molecular definition of MetS and to discriminate the conditions that are in the interface between healthy individuals and the metabolic syndrome.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-021-01349-9.

Amino Acid-Induced Impairment of Insulin Signaling and Involvement of G-Protein Coupling Receptor

Amino acids are needed for general bodily function and well-being. Despite their importance, augmentation in their serum concentration is closely related to metabolic disorder, insulin resistance (IR), or worse, diabetes mellitus. Essential amino acids such as the branched-chain amino acids (BCAAs) have been heavily studied as a plausible biomarker or even a cause of IR. Although there is a long list of benefits, in subjects with abnormal amino acids profiles, some amino acids are correlated with a higher risk of IR. Metabolic dysfunction, upregulation of the mammalian target of the rapamycin (mTOR) pathway, the gut microbiome, 3-hydroxyisobutyrate, inflammation, and the collusion of G-protein coupled receptors (GPCRs) are among the indicators and causes of metabolic disorders generating from amino acids that contribute to IR and the onset of type 2 diabetes mellitus (T2DM). This review summarizes the current understanding of the true involvement of amino acids with IR. Additionally, the involvement of GPCRs in IR will be further discussed in this review.

Metabolites that activate the inflammasome in nascent metabolic syndrome

BACKGROUND

Metabolic Syndrome (MetS) is a cardio-metabolic cluster that increases the risk of type 2 diabetes mellitus (T2DM) and atherosclerotic cardiovascular disease (ASCVD). Whilst it affects 35% of the American adult population, its pathogenesis remains to be elucidated. Both insulin resistance and increased inflammation appear to be pivotal mechanisms. The NOD-like receptor family pyrin domain containing protein 3 (NLRP3) inflammasome, an intracellular multi-protein complex, is crucial in the activation of Caspase 1, resulting in an increase in both IL-1and IL-18. In this preliminary report we examined the relationship between metabolites from our exploratory metabolomics studies with the NLRP3 inflammasome activity in the adipose tissue of patients with nascent MetS.

PATIENT AND METHODS

This study comprised patients with nascent MetS matched with controls. All patients in this study had normal renal and hepatic function. Metabolites were analyzed from frozen early morning urine samples and correlated with adipose tissue Caspase 1, interleukin-1, and interleukin-18 density.

RESULTS

Caspase 1, a marker of NLRP3 inflammasome activity, was significantly elevated in patients with nascent MetS compared to controls. Isoleucine, GABA, Carnitine and PC34: 2 were also significantly increased in patients with MetS. Caspase1 correlated positively with Isoleucine, GABA, Carnitine, and PC34:2.

CONCLUSION

We make the novel observation that the NLRP3 inflammasome activity is correlated with certain metabolites (Isoleucine, GABA, Carnitine and PC34:2) and hypothesize that they could trigger increased NLRP3 Inflammasome activity in MetS. However, these preliminary ,hypothesis generating novel findings need confirmation in larger studies of the metabolome and inflammasome.

Gut microbiota and metabolic health among overweight and obese individuals

Although obesity is associated with numerous diseases, the risks of disease may depend on metabolic health. Associations between the gut microbiota, obesity, and metabolic syndrome have been reported, but differences in microbiomes according to metabolic health in the obese population have not been explored in previous studies. Here, we investigated the composition of gut microbiota according to metabolic health status in obese and overweight subjects. A total of 747 overweight or obese adults were categorized by metabolic health status, and their fecal microbiota were profiled using 16S ribosomal RNA gene sequencing. We classified these adults into a metabolically healthy group (MH, N = 317) without any components of metabolic syndrome or a metabolically unhealthy group (MU, N = 430) defined as having at least one metabolic abnormality. The phylogenetic and non-phylogenetic alpha diversity for gut microbiota were lower in the MU group than the MH group, and there were significant differences in gut microbiota bacterial composition between the two groups. We found that the genus Oscillospira and the family Coriobacteriaceae were associated with good metabolic health in the overweight and obese populations. This is the first report to describe gut microbial diversity and composition in metabolically healthy and unhealthy overweight and obese individuals. Modulation of the gut microbiome may help prevent metabolic abnormalities in the obese population.

Urinary metabolic signatures reflect cardiovascular risk in the young, middle-aged, and elderly populations

The predictive value of traditional cardiovascular risk estimators is limited, and young and elderly populations are particularly underrepresented. We aimed to investigate the urine metabolome and its association with cardiovascular risk to identify novel markers that might complement current estimators based on age. Urine samples were collected from 234 subjects categorized into three age-grouped cohorts: 30-50 years (cohort I, young), 50-70 years (cohort II, middle-aged), and > 70 years (cohort III, elderly). Each cohort was further classified into three groups: (a) control, (b) individuals with cardiovascular risk factors, and (c) those who had a previous cardiovascular event. Novel urinary metabolites linked to cardiovascular risk were identified by nuclear magnetic resonance in cohort I and then evaluated by target mass spectrometry quantification in all cohorts. A previously identified metabolic fingerprint associated with atherosclerosis was also analyzed and its potential risk estimation investigated in the three aged cohorts. Three different metabolic signatures were identified according to age: 2-hydroxybutyrate, gamma-aminobutyric acid, hypoxanthine, guanidoacetate, oxaloacetate, and serine in young adults; citrate, cyclohexanol, glutamine, lysine, pantothenate, pipecolate, threonine, and tyramine shared by middle-aged and elderly adults; and trimethylamine N-oxide and glucuronate associated with cardiovascular risk in all three cohorts. The urinary metabolome contains a metabolic signature of cardiovascular risk that differs across age groups. These signatures might serve to complement existing algorithms and improve the accuracy of cardiovascular risk prediction for personalized prevention. KEY MESSAGES: • Cardiovascular risk in the young and elderly is underestimated. • The urinary metabolome reflects cardiovascular risk across all age groups. • Six metabolites constitute a metabolic signature of cardiovascular risk in young adults. • Middle-aged and elderly adults share a cardiovascular risk metabolic signature. • TMAO and glucuronate levels reflect cardiovascular risk across all age groups.

Decreased homoserine levels in metabolic syndrome

BACKGROUND AND AIMS

The pathogenesis Metabolic Syndrome (MetS), a common global problem, remains to be elucidated. As part of our exploratory metabolomics research we determined if homoserine levels are an early biomarker of nascent MetS.

METHODS

An exploratory study involving 28 patients with nascent MetS and 20 matched controls. Metabolites were studied from early morning urine samples and assayed by the NIH Western Metabolomics Center using gas chromatography time-of-flight mass spectrometry and were standardized to urine creatinine. All of the patients enrolled in the study had normal renal and hepatic function.

RESULTS

Patients with MetS had statistically significant increases in overall waist circumference, blood pressure, glucose, HOMA-IR, HbA1C in comparison to the control group. Additionally, increases in IL-1b, IL-6, TLR-4, endotoxin, and leptin were also seen in the MetS group subjects compared to the control group. The concentrations of homoserine were significantly decreased 3-fold in patients with MetS in comparison to the matched controls, p = 0.0027. Furthermore, levels of homoserine were inversely correlated to multiple biomarkers of inflammation and cardio-metabolic risk factors such as HbA1C, blood pressure, TLR-4, leptin, endotoxin, and SAT secreted fetuin A. In addition, homoserine was positively correlated with lysine and NAT.

CONCLUSIONS

In conclusion, low levels of homoserine could potentially contribute to the proinflammatory state in MetS.

Detection of Early Disease Risk Factors Associated with Metabolic Syndrome: A New Era with the NMR Metabolomics Assessment

The metabolic syndrome is a multifactorial disease developed due to accumulation and chronification of several risk factors associated with disrupted metabolism. The early detection of the biomarkers by NMR spectroscopy could be helpful to prevent multifactorial diseases. The exposure of each risk factor can be detected by traditional molecular markers but the current biomarkers have not been enough precise to detect the primary stages of disease. Thus, there is a need to obtain novel molecular markers of pre-disease stages. A promising source of new molecular markers are metabolomics standing out the research of biomarkers in NMR approaches. An increasing number of nutritionists integrate metabolomics into their study design, making nutrimetabolomics one of the most promising avenues for improving personalized nutrition. This review highlight the major five risk factors associated with metabolic syndrome and related diseases including carbohydrate dysfunction, dyslipidemia, oxidative stress, inflammation, and gut microbiota dysbiosis. Together, it is proposed a profile of metabolites of each risk factor obtained from NMR approaches to target them using personalized nutrition, which will improve the quality of life for these patients.

The relationship between tyramine levels and inflammation in metabolic syndrome

Background Metabolic syndrome (MetS) is an important contributor to both type 2 diabetes mellitus (T2DM) and atherosclerotic cardiovascular disease (ASCVD). Although MetS affects one third of American adults, its pathogenesis remains to be elucidated. Tyramine, a derivative of tyrosine, has been shown to act as a catecholamine releasing agent in the human body. The aim of this study is to investigate the role of tyramine as an early biomarker for nascent MetS without the confounding of T2DM, ASCVD or smoking. Patients and methods This was an exploratory study of 28 patients with nascent MetS and 20 matched controls carried out in 2018. Metabolites were evaluated from patient's frozen early morning urine samples and were correlated with biomarkers of inflammation and adipokines. They were assayed by the National Institutes of Health (NIH) Western Metabolomics Center using liquid chromatography/mass spectrometry (LC/MS) and standardized to urinary creatinine. All patients had normal hepatic and renal function. Results Tyramine concentrations were significantly reduced in patients with MetS compared to controls, p = 0.0009. In addition, tyramine was significantly inversely correlated with multiple biomarkers of inflammation and cardiometabolic risk factors such as RBP4, monocyte TLR-4 abundance and P38MAPKinase activity, body mass index (BMI) and blood pressure (BP) (both systolic and diastolic). Conclusion In conclusion, low levels of tyramine could contribute to the proinflammatorty state of MetS.

Comparative nutritional characteristics of the three major Chinese Dendrobium species with different growth years

Dendrobium, an important medicinal plant, is a source of widely used herbal medicine to nourish the stomach and treat throat inflammation. The present study is aimed at distinguishing and evaluating three major Dendrobium species by comparing physiochemical characteristics and understanding differences between different growth years in the Ta-pieh Mountains. Polysaccharides and total alkaloids of Dendrobium were determined, and the amino acids and trace elements were determined by UPLC (Ultra High-Performance Liquid Chromatography) and ICP-MS (Inductively coupled plasma mass spectrometry). It can be seen from the results that the polysaccharide content of these three kinds of Dendrobium in different growth years ranges from 249.31 mg·g^-1 to 547.66 mg·g^-1, and the highest content is in the 3-year-old Dendrobium huoshanense. The total alkaloid content ranges from 0.21 mg·g^-1 to 0.54 mg·g^-1, and the highest content is also the 3-year-old Dendrobium huoshanense. We determined the amino acid content of these three Dendrobium in different growth years, and we can see that each of the three kinds of Dendrobium contain seven kinds of amino acids required by the human body. We conducted a safety evaluation of the essential trace elements of Dendrobium, and the results showed that the dosage of 12g·d^-1Dendrobium prescribed in China Pharmacopoeia is in accordance with the recommended daily intake of trace elements recommended by the Food and Drug Administration of the United States, and will not cause trace element poisoning. Linear discriminant analysis was carried out on the basis of amino acids and trace elements and confirmed the applicability of multi-elemental analysis for identifying different Dendrobium species.

Application of l-methionine γ-lyase in chiral amino acid analysis

Here, a conventional chiral amino acid analysis method using high-performance liquid chromatography was coupled with a sample pretreatment using l-methionine γ-lyase from Pseudomonas putida ICR 3460 for the selective analysis of l-methionine and l-tryptophan. The sample was analyzed after the degradation of l-methionine with l-methionine γ-lyase, as l-methionine coelutes with l-tryptophan under the standard chiral amino acid analytical conditions used for precolumn derivatization with o-phthalaldehyde and N-acetyl-l-cysteine. The l-tryptophan in the sample was then eluted as a clearly separated peak and analyzed further. Since the l-methionine γ-lyase did not act on l-tryptophan, we were able to calculate the l-methionine or l-tryptophan concentration based on the data obtained from 2 individual runs: the sample with and without l-methionine γ-lyase pretreatment. The concentration of l-tryptophan was calculated from the data obtained from the sample with l-methionine γ-lyase pretreatment, while the concentration of l-methionine was calculated using the following equation: l-methionine concentration = {the data from the sample without l-methionine γ-lyase pretreatment}-{the data from the sample with l-methionine γ-lyase pretreatment}. Model samples containing authentic amino acids and a fermented food sample were analyzed by our method, and the calculated concentrations of l-methionine and l-tryptophan were consistently in agreement with the theoretical values.

Metabolic syndrome is an inflammatory disorder: A conspiracy between adipose tissue and phagocytes

Metabolic syndrome (MetS) describes a cluster of cardio-metabolic factors that predispose to type 2 diabetes mellitus (T2DM) and atherosclerotic cardiovascular disease (ASCVD). While 35% of Americans suffer from this disorder, the specific pathways related to this disease are largely underexplored. The prevailing consensus is that inflammatory pathways contribute to the pathogenesis of this disease, and therefore new research has uncovered how inflammation plays a critical role in the development and progression of MetS. The purpose of this review is to understand the role of major inflammatory mechanisms and their role in MetS. Our review identifies that adipose tissue (AT) contributes to the inflammatory pathways through the release of pro-inflammatory adipokines such as leptin and chemerin and dysregulation of anti-inflammatory adiponectin. Chemokines and cytokines deriving from monocytes are also altered and promote inflammation and insulin resistance. Circulating inflammatory biomarkers including C-reactive protein (CRP), fibrinogen, Serum amyloid A (SAA), cytokines, and chemokines have also been linked to the pathogenesis of MetS. Researchers have identified the significance of CRP levels in predicting future sequelae of MetS such as ASCVD. Mast cells in subcutaneous adipose tissue (SAT) promote both inflammation and fibrosis. Thus, both AT and phagocyte activity define MetS as an inflammatory disorder.

Exploratory metabolomics of nascent metabolic syndrome

INTRODUCTION

Metabolic syndrome (MetS) is a disorder defined by having three of five features: increased waist circumference (WC), hypertriglyceridemia, decreased high-density lipoprotein-cholesterol, hypertension and an elevated blood glucose (BG). Metabolic Syndrome ( MetS) affects 35% of American adults and significantly increases risk for Atherosclerotic cardiovascular disease (ASCVD) and type-2 diabetes (T2DM). An understanding of the metabolome will help elucidate the pathogenesis of MetS and lead to better management. We hypothesize that the metabolites, gamma-aminobutyric acid (GABA), d-pyroglutamic acid (PGA) and N-acetyl-d-tryptophan (NAT) will be altered in nascent MetS patients without the confounding of ASCVD or T2DM. We also correlated these metabolites with biomarkers of inflammation.

PATIENTS AND METHODS

This was an exploratory study of 30 patients with nascent MetS and 20 matched controls undertaken in 2018. Metabolites were evaluated from patient's frozen early morning urine samples and were correlated with biomarkers of inflammation and adipokines. They were assayed by the NIH Western Metabolomics Center using liquid chromatography/mass spectrometry and standardized to urinary creatinine. All patients had normal hepatic and renal function.

RESULTS

GABA and PGA levels were significantly increased in MetS patients compared to controls: 2.8-fold and 2.9-fold median increases respectively with p < 0.0001 and p = 0.004, possibly deriving from glutamate. NAT was significantly decreased by 90% in MetS patients compared to controls, p < 0.001. GABA correlates significantly with cardio-metabolic (CM) features including WC, blood pressure systolic (BP-S) while NAT correlated inversely with WC, BP-S, blood glucose (BG) and triglycerides (TG). GABA correlated positively with chemerin, leptin, Fetuin A and endotoxin. NAT correlated inversely with WC, BP-S, BG, TG, high sensitivity C - reactive protein (hsCRP), toll-like receptor-4 (TLR-4), lipopolysaccharide binding protein (LBP), chemerin and retinol binding protein-4 (RBP-4).

CONCLUSIONS

We make the novel observation of increased GABA and PGA with decreased NAT in patients with MetS. While GABA and PGA correlates positively with CM features and biomediators of inflammation, the metabolite NAT correlated inversely. Thus, GABA and PGA could contribute to the pro-inflammatory state of MetS while NAT could mitigate this pro-inflammatory response.

Metabolomic Salivary Signature of Pediatric Obesity Related Liver Disease and Metabolic Syndrome

Pediatric obesity-related metabolic syndrome (MetS) and nonalcoholic fatty liver disease (NAFLD) are increasingly frequent conditions with a still-elusive diagnosis and low-efficacy treatment and monitoring options. In this study, we investigated the salivary metabolomic signature, which has been uncharacterized to date. In this pilot-nested case-control study over a transversal design, 41 subjects (23 obese patients and 18 normal weight (NW) healthy controls), characterized based on medical history, clinical, anthropometric, and laboratory data, were recruited. Liver involvement, defined according to ultrasonographic liver brightness, allowed for the allocation of the patients into four groups: obese with hepatic steatosis ([St+], n = 15) and without hepatic steatosis ([St–], n = 8), and with (n = 10) and without (n = 13) MetS. A partial least squares discriminant analysis (PLS-DA) model was devised to classify the patients’ classes based on their salivary metabolomic signature. Pediatric obesity and its related liver disease and metabolic syndrome appear to have distinct salivary metabolomic signatures. The difference is notable in metabolites involved in energy, amino and organic acid metabolism, as well as in intestinal bacteria metabolism, possibly reflecting diet, fatty acid synthase pathways, and the strict interaction between microbiota and intestinal mucins. This information expands the current understanding of NAFLD pathogenesis, potentially translating into better targeted monitoring and/or treatment strategies in the future.

Exploratory metabolomics of metabolic syndrome: A status report

Metabolic syndrome (MetS) is as a cluster of cardio-metabolic factors that greatly increase the risk of chronic diseases such as type II diabetes mellitus and atherosclerotic cardiovascular disease. In the United States, obesity, physical inactivity, aging, and genetics (to a minor extent) have arisen as risk factors for developing MetS. Although 35% of American adults suffer from MetS, its pathogenesis largely remains unknown. Worse, there is a lack of screening and optimum therapy for this disease. Researchers have consequently turned towards metabolomics to identify biomarkers to better understand MetS. The purpose of this review is to characterize various metabolites and their potential connections to MetS. Numerous studies have also characterized MetS as a disease of increased inflammation, and therefore this review also explores how metabolites play a role in various inflammatory pathways. Our review explores a broad range of metabolites including biogenic amines, branched chain amino acids, aromatic amines, phosphatidylcholines, as well as a variety of other molecules. We will explore their biochemical pathways and their potential role in serving as biomarkers.

Simultaneous determination of amino acids, purines and derivatives in serum by ultrahigh-performance liquid chromatography/tandem mass spectrometry

RATIONALE

Amino acids, purines and derivatives play a key role in physiological and pathological processes, such as the development of gestational diabetes mellitus. However, little literature has reported the simultaneous quantification of amino acids and purines. Therefore, a reliable and robust method for the determination of amino acids and purines is necessary.

METHODS

A rapid and simple method based on ultrahigh-performance liquid chromatography/tandem mass spectrometry (UHPLC/MS/MS) was developed to determine the concentrations of twenty amino acids or derivatives and three purines or derivatives in serum.

RESULTS

The method was validated for linearity of calibration curve, limit of detection, limit of quantification, inter-day and intra-day precision, recovery, stability and matrix effect. The correlation coefficients of calibration curves were higher than 0.993 except for isoleucine. The recoveries ranged from 78.4% to 128.0% for three different concentrations of the spiked analytes. The matrix effect value ranged from -7.3% to 9.2%.

CONCLUSIONS

A rapid and simple UHPLC/MS/MS method for the simultaneous measurement of amino acids, purines and derivatives in serum samples was developed. The method was successfully applied to determine and compare the concentrations of analytes between gestational diabetes mellitus samples and controls.