Exploratory metabolomics of nascent metabolic syndrome

MetSCORE: a molecular metric to evaluate the risk of metabolic syndrome based on serum NMR metabolomics

BACKGROUND

Metabolic syndrome (MetS) is a cluster of medical conditions and risk factors correlating with insulin resistance that increase the risk of developing cardiometabolic health problems. The specific criteria for diagnosing MetS vary among different medical organizations but are typically based on the evaluation of abdominal obesity, high blood pressure, hyperglycemia, and dyslipidemia. A unique, quantitative and independent estimation of the risk of MetS based only on quantitative biomarkers is highly desirable for the comparison between patients and to study the individual progression of the disease in a quantitative manner.

METHODS

We used NMR-based metabolomics on a large cohort of donors (n = 21,323; 37.5% female) to investigate the diagnostic value of serum or serum combined with urine to estimate the MetS risk. Specifically, we have determined 41 circulating metabolites and 112 lipoprotein classes and subclasses in serum samples and this information has been integrated with metabolic profiles extracted from urine samples.

RESULTS

We have developed MetSCORE, a metabolic model of MetS that combines serum lipoprotein and metabolite information. MetSCORE discriminate patients with MetS (independently identified using the WHO criterium) from general population, with an AUROC of 0.94 (95% CI 0.920-0.952, p < 0.001). MetSCORE is also able to discriminate the intermediate phenotypes, identifying the early risk of MetS in a quantitative way and ranking individuals according to their risk of undergoing MetS (for general population) or according to the severity of the syndrome (for MetS patients).

CONCLUSIONS

We believe that MetSCORE may be an insightful tool for early intervention and lifestyle modifications, potentially preventing the aggravation of metabolic syndrome.

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.

Plasma metabolic fingerprints for large-scale screening and personalized risk stratification of metabolic syndrome

Direct diagnosis and accurate assessment of metabolic syndrome (MetS) allow for prompt clinical interventions. However, traditional diagnostic strategies overlook the complex heterogeneity of MetS. Here, we perform metabolomic analysis in 13,554 participants from the natural cohort and identify 26 hub plasma metabolic fingerprints (PMFs) associated with MetS and its early identification (pre-MetS). By leveraging machine-learning algorithms, we develop robust diagnostic models for pre-MetS and MetS with convincing performance through independent validation. We utilize these PMFs to assess the relative contributions of the four major MetS risk factors in the general population, ranked as follows: hyperglycemia, hypertension, dyslipidemia, and obesity. Furthermore, we devise a personalized three-dimensional plasma metabolic risk (PMR) stratification, revealing three distinct risk patterns. In summary, our study offers effective screening tools for identifying pre-MetS and MetS patients in the general community, while defining the heterogeneous risk stratification of metabolic phenotypes in real-world settings.

Cross-sectional relationships between general and central adiposity and plasma amino acids in Chinese adults

Adiposity is an important determinant of blood metabolites, but little is known about the variations of blood amino acids according to general and central adiposity status among Chinese population. This study included 187 females and 322 males who were cancer-free subjects randomly selected from two cohorts in Shanghai, China. Participants' plasma concentrations of amino acids were measured by ultra-performance liquid chromatography coupled to tandem mass spectrometry. Linear regression models were used to examine the cross-sectional correlations between general and central adiposity and amino acid levels. A total of 35 amino acids in plasma were measured in this study. In females, alanine, aspartic acid and pyroglutamic acid were positively correlated with general adiposity. In males, glutamic acid, aspartic acid, valine and pyroglutamic acid showed positive correlations, and glutamine, serine and glycine showed negative correlations with both general and central adiposity; phenylalanine, isoleucine and leucine were positively correlated and N-phenylacetylglutamine was negatively correlated with general adiposity; asparagine was negatively correlated with central adiposity. In summary, general adiposity and central adiposity were correlated with the concentrations of specific plasma amino acids among cancer-free female and male adults in China. Adiposity-metabolite characteristics and relationships should be considered when studying blood biomarkers for adiposity-related health outcomes.

Curcuminoids for Metabolic Syndrome: Meta-Analysis Evidences Toward Personalized Prevention and Treatment Management

The metabolic syndrome (MS) is a multifactorial syndrome associated with a significant economic burden and healthcare costs. MS management often requires multiple treatments (polydrug) to ameliorate conditions such as diabetes mellitus, insulin resistance, obesity, cardiovascular diseases, hypertension, and non-alcoholic fatty liver disease (NAFLD). However, various therapeutics and possible drug-drug interactions may also increase the risk of MS by altering lipid and glucose metabolism and promoting weight gain. In addition, the medications cause side effects such as nausea, flatulence, bloating, insomnia, restlessness, asthenia, palpitations, cardiac arrhythmias, dizziness, and blurred vision. Therefore, is important to identify and develop new safe and effective agents based on a multi-target approach to treat and manage MS. Natural products, such as curcumin, have multi-modalities to simultaneously target several factors involved in the development of MS. This review discusses the recent preclinical and clinical findings, and up-to-date meta-analysis from Randomized Controlled Trials regarding the effects of curcumin on MS, as well as the metabonomics and a pharma-metabolomics outlook considering curcumin metabolites, the gut microbiome, and environment for a complementary personalized prevention and treatment for MS management.

Berberine, a Herbal Metabolite in the Metabolic Syndrome: The Risk Factors, Course, and Consequences of the Disease

In recent years, the health of patients exposed to the consequences of the metabolic syndrome still requires the search for new solutions, and plant nutraceuticals are currently being intensively investigated. Berberine is a plant alkaloid possessing scientifically determined mechanisms of the prevention of the development of atherosclerosis, type 2 diabetes, and obesity, as well as cardiovascular complications and cancer. It positively contributes to elevated levels of fasting, postprandial blood glucose, and glycosylated hemoglobin, while decreasing insulin resistance. It stimulates glycolysis, improving insulin secretion, and inhibits gluconeogenesis and adipogenesis in the liver; by reducing insulin resistance, berberine also improves ovulation. The anti-obesity action of berberine has been also well-documented. Berberine acts as an anti-sclerotic, lowering the LDL and testosterone levels. The alkaloid exhibits an anti-inflammatory property by stalling the expression of cyclooxygenase 2 (COX-2) and prostaglandin E2. Berberine is neuroprotective and acts as an antidepressive. However, the outcomes in psychiatric patients are nonspecific, as it has been shown that berberine improves metabolic parameters in schizophrenic patients, acting as an adjuvant during antipsychotic treatment. Berberine acts as an anticancer option by inducing apoptosis, the cell cycle arrest, influencing MAPK (mitogen-activated protein kinase), and influencing transcription regulation. The inhibition of carcinogenesis is also combined with lipid metabolism.

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).

The central role of the glutamate metabolism in long-term antiretroviral treated HIV-infected individuals with metabolic syndrome

Metabolic syndrome (MetS) is a significant factor for cardiometabolic comorbidities in people living with HIV (PLWH) and a barrier to healthy aging. The long-term consequences of HIV-infection and combination antiretroviral therapy (cART) in metabolic reprogramming are unknown. In this study, we investigated metabolic alterations in well-treated PLWH with MetS to identify potential mechanisms behind the MetS phenotype using advanced statistical and machine learning algorithms. We included 200 PLWH from the Copenhagen Comorbidity in HIV-infection (COCOMO) study. PLWH were grouped into PLWH with MetS (n = 100) defined according to the International Diabetes Federation (IDF) consensus worldwide definition of the MetS or without MetS (n = 100). The untargeted plasma metabolomics was performed using ultra-high-performance liquid chromatography/mass spectrometry (UHPLC/MS/MS) and immune-phenotyping of Glut1 (glucose transporter), xCT (glutamate/cysteine transporter) and MCT1 (pyruvate/lactate transporter) by flow cytometry. We applied several conventional approaches, machine learning algorithms, and linear classification models to identify the biologically relevant metabolites associated with MetS in PLWH. Of the 877 identified biochemicals, 9% (76/877) differed significantly between PLWH with and without MetS (false discovery rate < 0.05). The majority belonged to amino acid metabolism (43%). A consensus identification by combining supervised and unsupervised methods indicated 11 biomarkers of MetS phenotype in PLWH. A weighted co-expression network identified seven communities of positively intercorrelated metabolites. A single community contained six of the potential biomarkers mainly related to glutamate metabolism. Transporter expression identified altered xCT and MCT in both lymphocytic and monocytic cells. Combining metabolomics and immune-phenotyping indicated altered glutamate metabolism associated with MetS in PLWH, which has clinical significance.

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.

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.

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.

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.

Metabolomic and Lipidomic Signatures of Metabolic Syndrome and its Physiological Components in Adults: A Systematic Review

The aim of this work was to conduct a systematic review of human studies on metabolite/lipid biomarkers of metabolic syndrome (MetS) and its components, and provide recommendations for future studies. The search was performed in MEDLINE, EMBASE, EMB Review, CINHAL Complete, PubMed, and on grey literature, for population studies identifying MetS biomarkers from metabolomics/lipidomics. Extracted data included population, design, number of subjects, sex/gender, clinical characteristics and main outcome. Data were collected regarding biological samples, analytical methods, and statistics. Metabolites were compiled by biochemical families including listings of their significant modulations. Finally, results from the different studies were compared. The search yielded 31 eligible studies (2005–2019). A first category of articles identified prevalent and incident MetS biomarkers using mainly targeted metabolomics. Even though the population characteristics were quite homogeneous, results were difficult to compare in terms of modulated metabolites because of the lack of methodological standardization. A second category, focusing on MetS components, allowed comparing more than 300 metabolites, mainly associated with the glycemic component. Finally, this review included also publications studying type 2 diabetes as a whole set of metabolic risks, raising the interest of reporting metabolomics/lipidomics signatures to reflect the metabolic phenotypic spectrum in systems approaches.

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.

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 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.