What Have Metabolomics Approaches Taught Us About Type 2 Diabetes?

1H NMR metabolomics insights into comparative diabesity in male and female zebrafish and the antidiabetic activity of DL-limonene

Zebrafish have been utilized for many years as a model animal for pharmacological studies on diabetes and obesity. High-fat diet (HFD), streptozotocin and alloxan injection, and glucose immersion have all been used to induce diabetes and obesity in zebrafish. Currently, studies commonly used both male and female zebrafish, which may influence the outcomes since male and female zebrafish are biologically different. This study was designed to investigate the difference between the metabolites of male and female diabetic zebrafish, using limonene - a natural product which has shown several promising results in vitro and in vivo in treating diabetes and obesity-and provide new insights into how endogenous metabolites change following limonene treatment. Using HFD-fed male and female zebrafish, we were able to develop an animal model of T2D and identify several endogenous metabolites that might be used as diagnostic biomarkers for diabetes. The endogenous metabolites in males and females were different, even though both genders had high blood glucose levels and a high BMI. Treatment with limonene prevented high blood glucose levels and improved in diabesity zebrafish by limonene, through reversal of the metabolic changes caused by HFD in both genders. In addition, limonene was able to reverse the elevated expression of AKT during HFD.

Role of Epigenetics and Metabolomics in Predicting Endothelial Dysfunction in Type 2 Diabetes

Type 2 diabetes (T2D) is a worldwide health problem and cardiovascular disease (CVD) is a leading cause of morbidity and mortality in T2D patients, making the prevention of CVD onset a major priority. It is therefore crucial to optimize diagnosis and treatment to reduce this burden. Endothelial dysfunction is one of the most important prognostic factors for CVD progression, thus novel approaches to identify the early phase of endothelial dysfunction may lead to specific preventive measures to reduce the occurrence of CVD. Nowadays, multiomics approaches have provided unprecedented opportunities to stratify T2D patients into endotypes, improve therapeutic treatment and outcome and amend the survival prediction. Among omics strategies, epigenetics and metabolomics are gaining increasing interest. Recently, a dynamic correlation between metabolic pathways and gene expression through chromatin remodeling, such as DNA methylation, has emerged, indicating new perspectives on the regulatory networks impacting cellular processes. Thus, a better understanding of epigenetic-metabolite relationships can provide insight into the physiological processes altered early in the endothelium that ultimately head to disease development. Here, recent studies on epigenetics and metabolomics related to CVD prevention potentially useful to identify disease biomarkers, as well as new therapies hopefully targeting the early phase of endothelial dysfunction are highlighted.

Exploring Metabolomic Patterns in Type 2 Diabetes Mellitus and Response to Glucose-Lowering Medications-Review

The spectrum of information related to precision medicine in diabetes generally includes clinical data, genetics, and omics-based biomarkers that can guide personalized decisions on diabetes care. Given the remarkable progress in patient risk characterization, there is particular interest in using molecular biomarkers to guide diabetes management. Metabolomics is an emerging molecular approach that helps better understand the etiology and promises the identification of novel biomarkers for complex diseases. Both targeted or untargeted metabolites extracted from cells, biofluids, or tissues can be investigated by established high-throughput platforms, like nuclear magnetic resonance (NMR) and mass spectrometry (MS) techniques. Metabolomics is proposed as a valuable tool in precision diabetes medicine to discover biomarkers for diagnosis, prognosis, and management of the progress of diabetes through personalized phenotyping and individualized drug-response monitoring. This review offers an overview of metabolomics knowledge as potential biomarkers in type 2 diabetes mellitus (T2D) diagnosis and the response to glucose-lowering medications.

Potential of in vitro nuclear magnetic resonance of biofluids and tissues in clinical research

Body fluids, cells, and tissues contain a wide variety of metabolites that consist of a mixture of various low-molecular-weight compounds, including amino acids, peptides, lipids, nucleic acids, and organic acids, which makes comprehensive analysis more difficult. Quantitative nuclear magnetic resonance (NMR) spectroscopy is a well-established analytical technique for analyzing the metabolic profiles of body fluids, cells, and tissues. It enables fast and comprehensive detection, characterization, a high level of experimental reproducibility, minimal sample preparation, and quantification of various endogenous metabolites. In recent times, NMR-based metabolomics has been appreciably utilized in diverse branches of medicine, including microbiology, toxicology, pathophysiology, pharmacology, nutritional intervention, and disease diagnosis/prognosis. In this review, the utility of NMR-based metabolomics in clinical studies is discussed. The significance of in vitro NMR-based metabolomics as an effective tool for detecting metabolites and their variations in different diseases are discussed, together with the possibility of identifying specific biomarkers that can contribute to early detection and diagnosis of disease.

New Advances in Metabolic Syndrome, from Prevention to Treatment: The Role of Diet and Food

The definition of metabolic syndrome (MetS) has undergone several changes over the years due to the difficulty in establishing universal criteria for it. Underlying the disorders related to MetS is almost invariably a pro-inflammatory state related to altered glucose metabolism, which could lead to elevated cardiovascular risk. Indeed, the complications closely related to MetS are cardiovascular diseases (CVDs) and type 2 diabetes (T2D). It has been observed that the predisposition to metabolic syndrome is modulated by complex interactions between human microbiota, genetic factors, and diet. This review provides a summary of the last decade of literature related to three principal aspects of MetS: (i) the syndrome's definition and classification, pathophysiology, and treatment approaches; (ii) prediction and diagnosis underlying the biomarkers identified by means of advanced methodologies (NMR, LC/GC-MS, and LC, LC-MS); and (iii) the role of foods and food components in prevention and/or treatment of MetS, demonstrating a possible role of specific foods intake in the development of MetS.

The relationship between glucose and the liver-alpha cell axis - A systematic review

Until recently, glucagon was considered a mere antagonist to insulin, protecting the body from hypoglycemia. This notion changed with the discovery of the liver-alpha cell axis (LACA) as a feedback loop. The LACA describes how glucagon secretion and pancreatic alpha cell proliferation are stimulated by circulating amino acids. Glucagon in turn leads to an upregulation of amino acid metabolism and ureagenesis in the liver. Several increasingly common diseases (e.g., non-alcoholic fatty liver disease, type 2 diabetes, obesity) disrupt this feedback loop. It is important for clinicians and researchers alike to understand the liver-alpha cell axis and the metabolic sequelae of these diseases. While most of previous studies have focused on fasting concentrations of glucagon and amino acids, there is limited knowledge of their dynamics after glucose administration. The authors of this systematic review applied PRISMA guidelines and conducted PubMed searches to provide results of 8078 articles (screened and if relevant, studied in full). This systematic review aims to provide better insight into the LACA and its mediators (amino acids and glucagon), focusing on the relationship between glucose and the LACA in adult and pediatric subjects.

Pan-cancer analysis of pre-diagnostic blood metabolite concentrations in the European Prospective Investigation into Cancer and Nutrition

BACKGROUND

Epidemiological studies of associations between metabolites and cancer risk have typically focused on specific cancer types separately. Here, we designed a multivariate pan-cancer analysis to identify metabolites potentially associated with multiple cancer types, while also allowing the investigation of cancer type-specific associations.

METHODS

We analysed targeted metabolomics data available for 5828 matched case-control pairs from cancer-specific case-control studies on breast, colorectal, endometrial, gallbladder, kidney, localized and advanced prostate cancer, and hepatocellular carcinoma nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. From pre-diagnostic blood levels of an initial set of 117 metabolites, 33 cluster representatives of strongly correlated metabolites and 17 single metabolites were derived by hierarchical clustering. The mutually adjusted associations of the resulting 50 metabolites with cancer risk were examined in penalized conditional logistic regression models adjusted for body mass index, using the data-shared lasso penalty.

RESULTS

Out of the 50 studied metabolites, (i) six were inversely associated with the risk of most cancer types: glutamine, butyrylcarnitine, lysophosphatidylcholine a C18:2, and three clusters of phosphatidylcholines (PCs); (ii) three were positively associated with most cancer types: proline, decanoylcarnitine, and one cluster of PCs; and (iii) 10 were specifically associated with particular cancer types, including histidine that was inversely associated with colorectal cancer risk and one cluster of sphingomyelins that was inversely associated with risk of hepatocellular carcinoma and positively with endometrial cancer risk.

CONCLUSIONS

These results could provide novel insights for the identification of pathways for cancer development, in particular those shared across different cancer types.

Newborn screen metabolic panels reflect the impact of common disorders of pregnancy

BACKGROUND

Hypertensive disorders of pregnancy and maternal diabetes profoundly affect fetal and newborn growth, yet disturbances in intermediate metabolism and relevant mediators of fetal growth alterations remain poorly defined. We sought to determine whether there are distinct newborn screen metabolic patterns among newborns affected by maternal hypertensive disorders or diabetes in utero.

METHODS

A retrospective observational study investigating distinct newborn screen metabolites in conjunction with data linked to birth and hospitalization records in the state of California between 2005 and 2010.

RESULTS

A total of 41,333 maternal-infant dyads were included. Infants of diabetic mothers demonstrated associations with short-chain acylcarnitines and free carnitine. Infants born to mothers with preeclampsia with severe features and chronic hypertension with superimposed preeclampsia had alterations in acetylcarnitine, free carnitine, and ornithine levels. These results were further accentuated by size for gestational age designations.

CONCLUSIONS

Infants of diabetic mothers demonstrate metabolic signs of incomplete beta oxidation and altered lipid metabolism. Infants of mothers with hypertensive disorders of pregnancy carry analyte signals that may reflect oxidative stress via altered nitric oxide signaling. The newborn screen analyte composition is influenced by the presence of these maternal conditions and is further associated with the newborn size designation at birth.

IMPACT

Substantial differences in newborn screen analyte profiles were present based on the presence or absence of maternal diabetes or hypertensive disorder of pregnancy and this finding was further influenced by the newborn size designation at birth. The metabolic health of the newborn can be examined using the newborn screen and is heavily impacted by the condition of the mother during pregnancy. Utilizing the newborn screen to identify newborns affected by common conditions of pregnancy may help relate an infant's underlying biological disposition with their clinical phenotype allowing for greater risk stratification and intervention.

Investigation into potential mechanisms of metabolic syndrome by integrative analysis of metabolomics and proteomics

Metabolic syndrome (MetS) is a complex syndrome cluster of metabolic disorders, which greatly increases the risks of diabetic and cardiovascular diseases. Although it has become a significantly worldwide public health burden, its pathogenesis largely remains unknown. In this study, we first performed an integrated analysis of proteomic and metabonomic data of liver tissues of rats between MetS and control groups to reveal possible mechanisms of MetS. A total of 16 significantly perturbed pathways were identified, of which three pathways were shared by patients with MetS and diabetes identified by analysis of serum samples, including alanine, aspartate and glutamate metabolism, valine, leucine and isoleucine biosynthesis, and glycine, serine and threonine metabolism. Additionally, it was found that 18 differential metabolites were closely related with 36 differential proteins, which were considered as significantly discriminant metabolites and proteins between two groups and were mainly involved in metabolic processes of gamma-aminobutyric acid and acetyl-CoA, biosynthetic processes of cholesterol and amino acids. The results of PPI network analysis and topological parameter calculation of four methods revealed that 16 proteins can serve as hub proteins of MetS. Followed by searching the PubMed database and molecular docking of Cyp7a1 and Got1, we concluded that atorvastatin and resveratrol may be potential drugs for MetS.

Ethnic disparities attributed to the manifestation in and response to type 2 diabetes: insights from metabolomics

Type 2 diabetes (T2D) associated health disparities among different ethnicities have long been known. Ethnic variations also exist in T2D related comorbidities including insulin resistance, vascular complications and drug response. Genetic heterogeneity, dietary patterns, nutrient metabolism and gut microbiome composition attribute to ethnic disparities in both manifestation and progression of T2D. These factors differentially regulate the rate of metabolism and metabolic health. Metabolomics studies have indicated significant differences in carbohydrate, lipid and amino acid metabolism among ethnicities. Interestingly, genetic variations regulating lipid and amino acid metabolism might also contribute to inter-ethnic differences in T2D. Comprehensive and comparative metabolomics analysis between ethnicities might help to design personalized dietary regimen and newer therapeutic strategies. In the present review, we explore population based metabolomics data to identify inter-ethnic differences in metabolites and discuss how (a) genetic variations, (b) dietary patterns and (c) microbiome composition may attribute for such differences in T2D.

Trans- and Multigenerational Maternal Social Isolation Stress Programs the Blood Plasma Metabolome in the F3 Generation

Metabolic risk factors are among the most common causes of noncommunicable diseases, and stress critically contributes to metabolic risk. In particular, social isolation during pregnancy may represent a salient stressor that affects offspring metabolic health, with potentially adverse consequences for future generations. Here, we used proton nuclear magnetic resonance (¹H NMR) spectroscopy to analyze the blood plasma metabolomes of the third filial (F3) generation of rats born to lineages that experienced either transgenerational or multigenerational maternal social isolation stress. We show that maternal social isolation induces distinct and robust metabolic profiles in the blood plasma of adult F3 offspring, which are characterized by critical switches in energy metabolism, such as upregulated formate and creatine phosphate metabolisms and downregulated glucose metabolism. Both trans- and multigenerational stress altered plasma metabolomic profiles in adult offspring when compared to controls. Social isolation stress increasingly affected pathways involved in energy metabolism and protein biosynthesis, particularly in branched-chain amino acid synthesis, the tricarboxylic acid cycle (lactate, citrate), muscle performance (alanine, creatine phosphate), and immunoregulation (serine, threonine). Levels of creatine phosphate, leucine, and isoleucine were associated with changes in anxiety-like behaviours in open field exploration. The findings reveal the metabolic underpinnings of epigenetically heritable diseases and suggest that even remote maternal social stress may become a risk factor for metabolic diseases, such as diabetes, and adverse mental health outcomes. Metabolomic signatures of transgenerational stress may aid in the risk prediction and early diagnosis of non-communicable diseases in precision medicine approaches.

The anti-diabetic potential of betaine. Mechanisms of action in rodent models of type 2 diabetes

Betaine (N, N, N-trimethylglycine) is an amino-acid derivative exerting numerous beneficial effects on the organism. This compound is found in human and animal diets but is also endogenously generated. However, its synthesis may be insufficient to maintain or improve health. Moreover, the tissue content of betaine reduces under some pathological conditions, such as type 2 diabetes. This decrease may be, however, easily alleviated by dietary betaine supplementation. Rodent studies provided evidence that betaine effectively limits many diabetes-related disturbances. Betaine therapy improves glucose tolerance and insulin action, which is strongly associated with changes in insulin-sensitive tissues, such as skeletal muscle, adipose tissue, and liver. Betaine supplementation positively affects multiple genes, which expression is dysregulated in diabetes. AMP-activated protein kinase is thought to play a central role in the mechanism underlying the anti-diabetic betaine action. Moreover, studies with animal models of type 2 diabetes have shown that betaine exerts anti-inflammatory and anti-oxidant effects, and also alleviates endoplasmic reticulum stress. These changes contribute to improved insulin sensitivity and better blood glucose clearance. The results of animal studies encourage the exploration of the therapeutic betaine efficacy in humans with type 2 diabetes.

Serological Phenotyping Analysis Uncovers a Unique Metabolomic Pattern Associated With Early Onset of Type 2 Diabetes Mellitus

Background: Type 2 diabetes mellitus (T2DM) is a multifaceted disorder affecting epidemic proportion at global scope. Defective insulin secretion by pancreatic β-cells and the inability of insulin-sensitive tissues to respond effectively to insulin are the underlying biology of T2DM. However, circulating biomarkers indicative of early diabetic onset at the asymptomatic stage have not been well described. We hypothesized that global and targeted mass spectrometry (MS) based metabolomic discovery can identify novel serological metabolic biomarkers specifically associated with T2DM. We further hypothesized that these markers can have a unique pattern associated with latent or early asymptomatic stage, promising an effective liquid biopsy approach for population T2DM risk stratification and screening.

Methods: Four independent cohorts were assembled for the study. The T2DM cohort included sera from 25 patients with T2DM and 25 healthy individuals for the biomarker discovery and sera from 15 patients with T2DM and 15 healthy controls for the testing. The Pre-T2DM cohort included sera from 76 with prediabetes and 62 healthy controls for the model training and sera from 35 patients with prediabetes and 27 healthy controls for the model testing. Both global and targeted (amino acid, acylcarnitine, and fatty acid) approaches were used to deep phenotype the serological metabolome by high performance liquid chromatography-high resolution mass spectrometry. Different machine learning approaches (Random Forest, XGBoost, and ElasticNet) were applied to model the unique T2DM/Pre-T2DM metabolic patterns and contrasted with their effectiness to differentiate T2DM/Pre-T2DM from controls.

Results: The univariate analysis identified unique panel of metabolites (n = 22) significantly associated with T2DM. Global metabolomics and subsequent structure determination led to the identification of 8 T2DM biomarkers while targeted LCMS profiling discovered 14 T2DM biomarkers. Our panel can effectively differentiate T2DM (ROC AUC = 1.00) or Pre-T2DM (ROC AUC = 0.84) from the controls in the respective testing cohort.

Conclusion: Our serological metabolite panel can be utilized to identifiy asymptomatic population at risk of T2DM, which may provide utility in identifying population at risk at an early stage of diabetic development to allow for clinical intervention. This early detection would guide ehanced levels of care and accelerate development of clinical strategies to prevent T2DM.

Glutamine Regulates Skeletal Muscle Immunometabolism in Type 2 Diabetes

Dysregulation of skeletal muscle metabolism influences whole-body insulin sensitivity and glucose homeostasis. We hypothesized that type 2 diabetes-associated alterations in the plasma metabolome directly contribute to skeletal muscle immunometabolism and the subsequent development of insulin resistance. To this end, we analyzed the plasma and skeletal muscle metabolite profile and identified glutamine as a key amino acid that correlates inversely with BMI and insulin resistance index (HOMA-IR) in men with normal glucose tolerance or type 2 diabetes. Using an in vitro model of human myotubes and an in vivo model of diet-induced obesity and insulin resistance in male mice, we provide evidence that glutamine levels directly influence the inflammatory response of skeletal muscle and regulate the expression of the adaptor protein GRB10, an inhibitor of insulin signaling. Moreover, we demonstrate that a systemic increase in glutamine levels in a mouse model of obesity improves insulin sensitivity and restores glucose homeostasis. We conclude that glutamine supplementation may represent a potential therapeutic strategy to prevent or delay the onset of insulin resistance in obesity by reducing inflammatory markers and promoting skeletal muscle insulin sensitivity.

Environmental risk factors of type 2 diabetes-an exposome approach

Type 2 diabetes is one of the major chronic diseases accounting for a substantial proportion of disease burden in Western countries. The majority of the burden of type 2 diabetes is attributed to environmental risks and modifiable risk factors such as lifestyle. The environment we live in, and changes to it, can thus contribute substantially to the prevention of type 2 diabetes at a population level. The 'exposome' represents the (measurable) totality of environmental, i.e. nongenetic, drivers of health and disease. The external exposome comprises aspects of the built environment, the social environment, the physico-chemical environment and the lifestyle/food environment. The internal exposome comprises measurements at the epigenetic, transcript, proteome, microbiome or metabolome level to study either the exposures directly, the imprints these exposures leave in the biological system, the potential of the body to combat environmental insults and/or the biology itself. In this review, we describe the evidence for environmental risk factors of type 2 diabetes, focusing on both the general external exposome and imprints of this on the internal exposome. Studies provided established associations of air pollution, residential noise and area-level socioeconomic deprivation with an increased risk of type 2 diabetes, while neighbourhood walkability and green space are consistently associated with a reduced risk of type 2 diabetes. There is little or inconsistent evidence on the contribution of the food environment, other aspects of the social environment and outdoor temperature. These environmental factors are thought to affect type 2 diabetes risk mainly through mechanisms incorporating lifestyle factors such as physical activity or diet, the microbiome, inflammation or chronic stress. To further assess causality of these associations, future studies should focus on investigating the longitudinal effects of our environment (and changes to it) in relation to type 2 diabetes risk and whether these associations are explained by these proposed mechanisms.

Old and New Biomarkers Associated with Endothelial Dysfunction in Chronic Hyperglycemia

Chronic hyperglycemia and vascular damage are strictly related. Biomarkers of vascular damage have been intensively studied in the recent years in the quest of reliable cardiovascular risk assessment tools able to facilitate risk stratification and early detection of vascular impairment. The present study is a narrative review with the aim of revising the available evidence on current and novel markers of hyperglycemia-induced vascular damage. After a discussion of classic tools used to investigate endothelial dysfunction, we provide an in-depth description of novel circulating biomarkers (chemokines, extracellular vesicles, and epigenetic and metabolomic biomarkers). Appropriate use of a single as well as a cluster of the discussed biomarkers might enable in a near future (a) the prompt identification of targeted and customized treatment strategies and (b) the follow-up of cardiovascular treatment efficacy over time in clinical research and/or in clinical practice.

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).

Aqueous Metabolite Trends for the Progression of Nonalcoholic Fatty Liver Disease in Female Bariatric Surgery Patients by Targeted 1H-NMR Metabolomics

Determining biomarkers and better characterizing the biochemical progression of nonalcoholic fatty liver disease (NAFLD) remains a clinical challenge. A targeted ¹H-NMR study of serum, combined with clinical variables, detected and localized biomarkers to stages of NAFLD in morbidly obese females. Pre-surgery serum samples from 100 middle-aged, morbidly obese female subjects, grouped on gold-standard liver wedge biopsies (non-NAFLD; steatosis; and fibrosis) were collected, extracted, and analyzed in aqueous (D₂O) buffer (¹H, 600 MHz). Profiled concentrations were subjected to exploratory statistical analysis. Metabolites varying significantly between the non-NAFLD and steatosis groups included the ketone bodies 3-hydroxybutyrate (↓; p = 0.035) and acetone (↓; p = 0.012), and also alanine (↑; p = 0.004) and a putative pyruvate signal (↑; p = 0.003). In contrast, the steatosis and fibrosis groups were characterized by 2-hydroxyisovalerate (↑; p = 0.023), betaine (↓; p = 0.008), hypoxanthine (↓; p = 0.003), taurine (↓; p = 0.001), 2-hydroxybutyrate (↑; p = 0.045), 3-hydroxyisobutyrate (↑; p = 0.046), and increasing medium chain fatty acids. Exploratory classification models with and without clinical variables exhibited overall success rates ca. 75–85%. In the study conditions, inhibition of fatty acid oxidation and disruption of the hepatic urea cycle are supported as early features of NAFLD that continue in fibrosis. In fibrosis, markers support inflammation, hepatocyte damage, and decreased liver function. Complementarity of NMR concentrations and clinical information in classification models is shown. A broader hypothesis that standard-of-care sera can yield metabolomic information is supported.

Emerging Applications of Metabolomics to Assess the Efficacy of Traditional Chinese Medicines for Treating Type 2 Diabetes Mellitus

Diabetes is a common and complex disease that can exacerbate the complications related to cardiovascular disease, and this is especially true for type 2 diabetes mellitus (T2DM). In addition to the standard pharmacological therapies, T2DM has also been treated with nonconventional regimens such as traditional Chinese medicine (TCM), e.g., herbal medicines and TCM prescriptions, although the mechanisms underlying the therapeutic benefits remain unclear. In this regard, many studies have used metabolomics technology to elucidate the basis for the efficacy of TCM for T2DM. Metabolomics has recently attracted much attention with regard to drug discovery and pharmacologically relevant natural products. In this review, we summarize the application of metabolomics to the assessment of TCM efficacy for treating T2DM. Increasing evidence suggests that the metabolic profile of an individual patient may reflect a specific type of T2DM syndrome, which may provide a new perspective for disease diagnosis. In addition, TCM has proved effective for countering the metabolic disorders related to T2DM, and this may constitute the basis for TCM efficacy. Therefore, further determining how TCM contributes to the reversal of metabolic disorders, such as using network pharmacology or by assessing the contribution of host–gut microbiota interactions, will also provide researchers with new potential targets for pharmacologic-based therapies.

The liver-alpha-cell axis after a mixed meal and during weight loss in type 2 diabetes

OBJECTIVE

Glucagon and amino acids may be regulated in a feedback loop called the liver-alpha-cell axis with alanine or glutamine as suggested signal molecules. We assessed this concept in individuals with type 2 diabetes in the fasting state, after ingestion of a protein-rich meal, and during weight loss. Moreover, we investigated if postprandial glucagon secretion and hepatic insulin sensitivity were related.

METHODS

This is a secondary analysis of a 12-week weight-loss trial (Paleolithic diet ± exercise) in 29 individuals with type 2 diabetes. Before and after the intervention, plasma glucagon and amino acids were measured in the fasting state and during 180 min after a protein-rich mixed meal. Hepatic insulin sensitivity was measured using the hyperinsulinemic-euglycemic clamp with [6,6-2H2]glucose as a tracer.

RESULTS

The postprandial increase of plasma glucagon was associated with the postprandial increase of alanine and several other amino acids but not glutamine. In the fasted state and after the meal, glucagon levels were negatively correlated with hepatic insulin sensitivity (rS = -0.51/r = -0.58, respectively; both P < 0.05). Improved hepatic insulin sensitivity with weight loss was correlated with decreased postprandial glucagon response (r = -0.78; P < 0.001).

CONCLUSIONS

Several amino acids, notably alanine, but not glutamine could be key signals to the alpha cell to increase glucagon secretion. Amino acids may be part of a feedback mechanism as glucagon increases endogenous glucose production and ureagenesis in the liver. Moreover, postprandial glucagon secretion seems to be tightly related to hepatic insulin sensitivity.

Identification of markers that distinguish adipose tissue and glucose and insulin metabolism using a multi-modal machine learning approach

The study of metabolomics has improved our knowledge of the biology behind type 2 diabetes and its related metabolic physiology. We aimed to investigate markers of adipose tissue morphology, as well as insulin and glucose metabolism in 53 non-obese male individuals. The participants underwent extensive clinical, biochemical and magnetic resonance imaging phenotyping, and we also investigated non-targeted serum metabolites. We used a multi-modal machine learning approach to evaluate which serum metabolomic compounds predicted markers of glucose and insulin metabolism, adipose tissue morphology and distribution. Fasting glucose was associated with metabolites of intracellular insulin action and beta-cell dysfunction, namely cysteine-s-sulphate and n-acetylgarginine, whereas fasting insulin was predicted by myristoleoylcarnitine, propionylcarnitine and other metabolites of beta-oxidation of fatty acids. OGTT-glucose levels at 30 min were predicted by 7-Hoca, a microbiota derived metabolite, as well as eugenol, a fatty acid. Both insulin clamp and HOMA-IR were predicted by metabolites involved in beta-oxidation of fatty acids and biodegradation of triacylglycerol, namely tartrate and 3-phosphoglycerate, as well as pyruvate, xanthine and liver fat. OGTT glucose area under curve (AUC) and OGTT insulin AUC, was associated with bile acid metabolites, subcutaneous adipocyte cell size, liver fat and fatty chain acids and derivates, such as isovalerylcarnitine. Finally, subcutaneous adipocyte size was associated with long chain fatty acids, markers of sphingolipid metabolism, increasing liver fat and dopamine-sulfate 1. Ectopic liver fat was predicted by methylmalonate, adipocyte cell size, glutathione derived metabolites and fatty chain acids. Ectopic heart fat was predicted visceral fat, gamma-glutamyl tyrosine and 2-acetamidophenol sulfate. Adipocyte cell size, age, alpha-tocopherol and blood pressure were associated with visceral fat. We identified several biomarkers associated with adipose tissue pathophysiology and insulin and glucose metabolism using a multi-modal machine learning approach. Our approach demonstrated the relative importance of serum metabolites and they outperformed traditional clinical and biochemical variables for most endpoints.

Metabolomic profiles are reflective of hypoxia-induced insulin resistance during exercise in healthy young adult males

Hypoxia-induced insulin resistance appears to suppress exogenous glucose oxidation during metabolically matched aerobic exercise during acute (<8 h) high-altitude (HA) exposure. However, a better understanding of this metabolic dysregulation is needed to identify interventions to mitigate these effects. The objective of this study was to determine if differences in metabolomic profiles during exercise at sea level (SL) and HA are reflective of hypoxia-induced insulin resistance. Native lowlanders (n = 8 males) consumed 145 g (1.8 g/min) of glucose while performing 80-min of metabolically matched treadmill exercise at SL (757 mmHg) and HA (460 mmHg) after 5-h exposure. Exogenous glucose oxidation and glucose turnover were determined using indirect calorimetry and dual tracer technique ([¹³C]glucose and [6,6-²H₂]glucose). Metabolite profiles were analyzed in serum as change (Δ), calculated by subtracting postprandial/exercised state SL (ΔSL) and HA (ΔHA) from fasted, rested conditions at SL. Compared with SL, exogenous glucose oxidation, glucose rate of disappearance, and glucose metabolic clearance rate (MCR) were lower (P < 0.05) during exercise at HA. One hundred and eighteen metabolites differed between ΔSL and ΔHA (P < 0.05, Q < 0.10). Differences in metabolites indicated increased glycolysis, tricarboxylic acid cycle, amino acid catabolism, oxidative stress, and fatty acid storage, and decreased fatty acid mobilization for ΔHA. Branched-chain amino acids and oxidative stress metabolites, Δ3-methyl-2-oxobutyrate (r = -0.738) and Δγ-glutamylalanine (r = -0.810), were inversely associated (P < 0.05) with Δexogenous glucose oxidation. Δ3-Hydroxyisobutyrate (r = -0.762) and Δ2-hydroxybutyrate/2-hydroxyisobutyrate (r = -0.738) were inversely associated (P < 0.05) with glucose MCR. Coupling global metabolomics and glucose kinetic data suggest that the underlying cause for diminished exogenous glucose oxidative capacity during aerobic exercise is acute hypoxia-mediated peripheral insulin resistance.

Amino Acid Signature of Oxidative Stress in Patients with Type 2 Diabetes: Targeted Exploratory Metabolomic Research

Oxidative stress plays a key role in the development of chronic diabetes-related complications. Previous metabolomic studies showed a positive association of diabetes and insulin resistance with branched-chain amino acids (AAs) and aromatic AAs. The purpose of this research is to identify distinct metabolic changes associated with increased oxidative stress, as assessed by nitrotyrosine levels, in type 2 diabetes (T2DM). Serum samples of 80 patients with insulin-treated T2DM are analyzed by AA-targeted metabolomics using ultrahigh-performance liquid chromatography/mass spectrometry. Patients are divided into two groups based on their nitrotyrosine levels: the highest level of oxidative stress (Q4 nitrotyrosine) and lower levels (Q1–Q3 nitrotyrosine). The identification of biomarkers is performed in MetaboAnalyst version 5.0 using a t-test corrected for false discovery rate, unsupervised principal component analysis and supervised partial least-squares discriminant analysis (PLS-DA). Four AAs have significantly different levels between the groups for highest and lower oxidative stress. Cysteine, phenylalanine and tyrosine are substantially increased while citrulline is decreased (p-value <0.05 and variable importance in the projection [VIP] >1). Corresponding pathways that might be disrupted in patients with high oxidative stress are phenylalanine, tyrosine and tryptophan biosynthesis, arginine biosynthesis, phenylalanine metabolism, cysteine and methionine metabolism and tyrosine metabolism.

Glycolysis/gluconeogenesis- and tricarboxylic acid cycle-related metabolites, Mediterranean diet, and type 2 diabetes

BACKGROUND

Glycolysis/gluconeogenesis and tricarboxylic acid (TCA) cycle metabolites have been associated with type 2 diabetes (T2D). However, the associations of these metabolites with T2D incidence and the potential effect of dietary interventions remain unclear.

OBJECTIVES

We aimed to evaluate the association of baseline and 1-y changes in glycolysis/gluconeogenesis and TCA cycle metabolites with insulin resistance and T2D incidence, and the potential modifying effect of Mediterranean diet (MedDiet) interventions.

METHODS

We included 251 incident T2D cases and 638 noncases in a nested case-cohort study within the PREDIMED Study during median follow-up of 3.8 y. Participants were allocated to MedDiet + extra-virgin olive oil, MedDiet + nuts, or control diet. Plasma metabolites were measured using a targeted approach by LC-tandem MS. We tested the associations of baseline and 1-y changes in glycolysis/gluconeogenesis and TCA cycle metabolites with subsequent T2D risk using weighted Cox regression models and adjusting for potential confounders. We designed a weighted score combining all these metabolites and applying the leave-one-out cross-validation approach.

RESULTS

Baseline circulating concentrations of hexose monophosphate, pyruvate, lactate, alanine, glycerol-3 phosphate, and isocitrate were significantly associated with higher T2D risk (17-44% higher risk for each 1-SD increment). The weighted score including all metabolites was associated with a 30% (95% CI: 1.12, 1.51) higher relative risk of T2D for each 1-SD increment. Baseline lactate and alanine were associated with baseline and 1-y changes of homeostasis model assessment of insulin resistance. One-year increases in most metabolites and in the weighted score were associated with higher relative risk of T2D after 1 y of follow-up. Lower risks were observed in the MedDiet groups than in the control group although no significant interactions were found after adjusting for multiple comparisons.

CONCLUSIONS

We identified a panel of glycolysis/gluconeogenesis-related metabolites that was significantly associated with T2D risk in a Mediterranean population at high cardiovascular disease risk. A MedDiet could counteract the detrimental effects of these metabolites.This trial was registered at controlled-trials.com as ISRCTN35739639.

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.

A Cross-Sectional Study of Obesity Effects on the Metabolomic Profile of a Leptin-Resistant Swine Model

Identifying metabolite signatures associated with obesity and related diseases might represent a valuable preventive and therapeutic tool to predict subjects at risk, establish an accurate prognosis, and monitor treatment success. The current cross-sectional study is aimed to evaluate the metabolite profile of diet-induced obesity in a porcine model of leptin resistance. Six Iberian female pigs prone to develop obesity (OB) were ad libitum fed a fat-enriched diet (HFD) for 82 days. Five lean Iberian sows (CON) in a maintenance diet served as controls. At the end of the dietary treatments, all animals were sacrificed, and plasma, liver, and muscle samples were immediately collected for nuclear magnetic resonance analysis. In plasma, signals corresponding to betaine, glycerophosphocholine/phosphocholine, glycine, and glutamate were decreased; and the valine signal was increased in OB sows compared to controls. Similarly, the betaine signal was decreased in the liver. No differences were detected in muscle. The observed metabolite changes suggest alterations in branched chain amino-acid metabolism and the methionine-homocysteine cycle, which have been previously associated with obesity-related diseases and type 2 diabetes in human observational studies. The current study supports the utilization of the leptin resistant Iberian pig for further interventional research in the field.

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.

Nutrient Sensor mTOR and OGT: Orchestrators of Organelle Homeostasis in Pancreatic β-Cells

The purpose of this review is to integrate the role of nutrient-sensing pathways into β-cell organelle dysfunction prompted by nutrient excess during type 2 diabetes (T2D). T2D encompasses chronic hyperglycemia, hyperlipidemia, and inflammation, which each contribute to β-cell failure. These factors can disrupt the function of critical β-cell organelles, namely, the ER, mitochondria, lysosomes, and autophagosomes. Dysfunctional organelles cause defects in insulin synthesis and secretion and activate apoptotic pathways if homeostasis is not restored. In this review, we will focus on mTORC1 and OGT, two major anabolic nutrient sensors with important roles in β-cell physiology. Though acute stimulation of these sensors frequently improves β-cell function and promotes adaptation to cell stress, chronic and sustained activity disturbs organelle homeostasis. mTORC1 and OGT regulate organelle function by influencing the expression and activities of key proteins, enzymes, and transcription factors, as well as by modulating autophagy to influence clearance of defective organelles. In addition, mTORC1 and OGT activity influence islet inflammation during T2D, which can further disrupt organelle and β-cell function. Therapies for T2D that fine-tune the activity of these nutrient sensors have yet to be developed, but the important role of mTORC1 and OGT in organelle homeostasis makes them promising targets to improve β-cell function and survival.

High plasma glutamate and low glutamine-to-glutamate ratio are associated with type 2 diabetes: Case-cohort study within the PREDIMED trial

BACKGROUND AND AIMS

Glutamate, glutamine are involved in energy metabolism, and have been related to cardiometabolic disorders. However, their roles in the development of type-2 diabetes (T2D) remain unclear. The aim of this study was to examine the effects of Mediterranean diet on associations between glutamine, glutamate, glutamine-to-glutamate ratio, and risk of new-onset T2D in a Spanish population at high risk for cardiovascular disease (CVD).

METHODS AND RESULTS

The present study was built within the PREDIMED trial using a case-cohort design including 892 participants with 251 incident T2D cases and 641 non-cases. Participants (mean age 66.3 years; female 62.8%) were non diabetic and at high risk for CVD at baseline. Plasma levels of glutamine and glutamate were measured at baseline and after 1-year of intervention. Higher glutamate levels at baseline were associated with increased risk of T2D with a hazard ratio (HR) of 2.78 (95% CI, 1.43-5.41, P for trend = 0.0002). In contrast, baseline levels of glutamine (HR: 0.64, 95% CI, 0.36-1.12; P for trend = 0.04) and glutamine-to-glutamate ratio (HR: 0.31, 95% CI, 0.16-0.57; P for trend = 0.0001) were inversely associated with T2D risk when comparing extreme quartiles. The two Mediterranean diets (MedDiet + EVOO and MedDiet + mixed nuts) did not alter levels of glutamine and glutamate after intervention for 1 year. However, MedDiet mitigated the positive association between higher baseline plasma glutamate and T2D risk (P for interaction = 0.01).

CONCLUSION

Higher levels of glutamate and lower levels of glutamine were associated with increased risk of T2D in a Spanish population at high risk for CVD. Mediterranean diet might mitigate the association between the imbalance of glutamine and glutamate and T2D risk. This trial is registered at http://www.controlled-trials.com, ISRCTN35739639.

Metabolomics and Lipidomics Profiling Reveals Hypocholesterolemic and Hypolipidemic Effects of Arabinoxylan on Type 2 Diabetic Rats

Type 2 diabetes (T2D) is a pandemic disease chiefly characterized by hyperglycemia. In this study, the combination of serum lipidomic and metabolomic approach was employed to investigate the effect of arabinoxylan on type 2 diabetic rats and identify the critical biomarkers of T2D. Metabolomics analysis revealed that branched-chain amino acids, 12α-hydroxylated bile acids, ketone bodies, and several short- and long-chain acylcarnitines were significantly increased in T2D, whereas lysophosphatidylcholines (LPCs) were significantly decreased. Lipidomics analysis indicated T2D-related dyslipidemia was mainly associated with the increased levels of acetylcarnitine, free fatty acids (FFA), diacylglycerols, triacylglycerols, and cholesteryl esters and the decreased levels of some unsaturated phosphatidylcholines (less than 22 carbons). These variations indicated the disturbed amino acid and lipid metabolism in T2D, and the accumulation of incompletely oxidized lipid species might eventually contribute to impaired insulin action and glucose homeostasis. Arabinoxylan treatment decreased the concentrations of 12α-hydroxylated bile acids, carnitines, and FFAs and increased the levels of LPCs. The improved bile acid and lipid metabolism by arabinoxylan might be involved in the alleviation of hypercholesterolemia and hyperlipidemia in T2D.

Metabolomics and Cell Therapy in Diabetes Mellitus

Diabetes with a broad spectrum of complications has become a global epidemic metabolic disorder. Till now, several pharmaceutical and non-pharmaceutical therapeutic approaches were applied for its treatment. Cell-based therapies have become promising methods for diabetes treatment. Better understanding of diabetes pathogenesis and identification of its specific biomarkers along with evaluation of different treatments efficacy, can be possible by clarification of specific metabolic modifications during the diabetes progression. Subsequently, metabolomics technology can support this goal as an effective tool. The present review tried to show how metabolomics quantifications can be useful for diabetic monitoring before and after cell therapy. Cell therapy is an alternative approach to achieve diabetes treatments goals including insulin resistance amelioration, insulin independence reparation, and control of glycemia. OMICs approaches provide a comprehensive insight into the molecular mechanisms of cells features and functional mechanism of their genomics, transcriptomics, proteomics, and metabolomics profile which can be useful for their therapeutic application. As a modern technology for the detection and analysis of metabolites in biological samples, metabolomica can identify many of the metabolic and molecular pathways associated with diabetes and its following complications.

NMR-Based Metabolomic Approach Tracks Potential Serum Biomarkers of Disease Progression in Patients with Type 2 Diabetes Mellitus

Type 2 diabetes mellitus (T2DM) is a metabolic disorder characterized by chronic hyperglycemia associated with alterations in carbohydrate, lipid, and protein metabolism. The prognosis of T2DM patients is highly dependent on the development of complications, and therefore the identification of biomarkers of T2DM progression, with minimally invasive techniques, is a huge need. In the present study, we applied a ¹H-Nuclear Magnetic Resonance (¹H-NMR)-based metabolomic approach coupled with multivariate data analysis to identify serum metabolite profiles associated with T2DM development and progression. To perform this, we compared the serum metabolome of non-diabetic subjects, treatment-naïve non-complicated T2DM patients, and T2DM patients with complications in insulin monotherapy. Our analysis revealed a significant reduction of alanine, glutamine, glutamate, leucine, lysine, methionine, tyrosine, and phenylalanine in T2DM patients with respect to non-diabetic subjects. Moreover, isoleucine, leucine, lysine, tyrosine, and valine levels distinguished complicated patients from patients without complications. Overall, the metabolic pathway analysis suggested that branched-chain amino acid (BCAA) metabolism is significantly compromised in T2DM patients with complications, while perturbation in the metabolism of gluconeogenic amino acids other than BCAAs characterizes both early and advanced T2DM stages. In conclusion, we identified a metabolic serum signature associated with T2DM stages. These data could be integrated with clinical characteristics to build a composite T2DM/complications risk score to be validated in a prospective cohort.

Linking of metabolomic biomarkers with cardiometabolic health in Chinese population

Due to rapid nutrition transitions, the prevalence of cardiometabolic diseases, such as metabolic syndrome, type 2 diabetes, and cardiovascular diseases, has been increasing at an alarming rate in the Chinese population. Moreover, Asians, including Chinese, have been hypothesized to have a higher susceptibility to cardiometabolic diseases than Caucasians. Early prediction and prevention are key to controlling this epidemic trend; to this end, the identification of novel biomarkers is critical to reflect environmental exposure, as well as to reveal endogenous metabolic and pathophysiologic mechanisms. The emerging "omics" technologies, especially metabolomics, offer a unique opportunity to provide novel signatures or fingerprints to understand the effects of genetic and non-genetic factors on cardiometabolic health. During the past two decades, metabolomic approaches have been increasingly used in various epidemiological studies, primarily in Western populations. Although the field is still in its early stages, some studies have tried to identify novel compounds or confirm their metabolites and associations with cardiometabolic diseases in Chinese populations, including amino acids, fatty acids, acylcarnitines and other metabolites. Despite major efforts to discover novel biomarkers for disease prediction or intervention, the limits in current study design, analytical platforms, and data processing approaches are challenges in metabolomic research worldwide. Therefore, future research with more advanced technologies, rigorous study designs, standardized detection and analytic approaches, and integrated data from multiomics approaches are essential to evaluate the feasibility of using metabolomics in clinical settings. Finally, the functional roles and underlying biological mechanisms of metabolomic biomarkers should be elucidated by future mechanistic research.

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.

Interorgan Metabolic Crosstalk in Human Insulin Resistance

Excessive energy intake and reduced energy expenditure drive the development of insulin resistance and metabolic diseases such as obesity and type 2 diabetes mellitus. Metabolic signals derived from dietary intake or secreted from adipose tissue, gut, and liver contribute to energy homeostasis. Recent metabolomic studies identified novel metabolites and enlarged our knowledge on classic metabolites. This review summarizes the evidence of their roles as mediators of interorgan crosstalk and regulators of insulin sensitivity and energy metabolism. Circulating lipids such as free fatty acids, acetate, and palmitoleate from adipose tissue and short-chain fatty acids from the gut effectively act on liver and skeletal muscle. Intracellular lipids such as diacylglycerols and sphingolipids can serve as lipotoxins by directly inhibiting insulin action in muscle and liver. In contrast, fatty acid esters of hydroxy fatty acids have been recently shown to exert a series of beneficial effects. Also, ketoacids are gaining interest as potent modulators of insulin action and mitochondrial function. Finally, branched-chain amino acids not only predict metabolic diseases, but also inhibit insulin signaling. Here, we focus on the metabolic crosstalk in humans, which regulates insulin sensitivity and energy homeostasis in the main insulin-sensitive tissues, skeletal muscle, liver, and adipose tissue.

Predictive biomarkers for type 2 of diabetes mellitus: Bridging the gap between systems research and personalized medicine

The global incidence of metabolic disorders like type 2 diabetes mellitus (DM2) has assumed epidemic proportions, leading to adverse health and socio-economic impacts. It is therefore of critical importance the early diagnosis of DM2 patients and the detection of those at increased risk of disease. In this respect, Precision Medicine (PM) is an emerging approach that includes practices, tests, decisions and treatments adapted to the characteristics of each patient. With regard to DM2, PM manages a wealth of "omics" data (genomic, metabolic, proteomic, environmental, clinical and paraclinical) to increase the number of clinically validated biomarkers in order to identify patients in early stage even before the prediabetic phase.

SIGNIFICANCE

In this paper, we discuss the epidemic dimension of metabolic disorders like type 2 diabetes mellitus (DM2) and the urgent demand for novel biomarkers to reduce the incidence or even delay the onset of DM2. Recent research data produced by "multi-omics" technologies (genomics/epigenomics, transcriptomics, proteomics and metabolomics), suggest that many potential biomarkers might be helpful in the prediction and early diagnosis of DM2. Predictive, Preventive and Personalized Medicine (PPPM) manages and integrates these data to apply personalized, preventive, and therapeutic approaches. This is significant because there is an emerging need for establishing channels for communication and personalized consultation between systems research and precision medicine, as the medicine of the future.

Changes in glucose metabolism after distal pancreatectomy: a nationwide database study

Background

This population-based study evaluated changes in glucose metabolism after distal pancreatectomy (DP).

Methods

Data from the Taiwan National Health Insurance Research Database was collected from 2001 to 2010. Of 1,980 patients who underwent DP, 507 had diabetes and 1,410 did not.

Results

Of the 1,410 non-diabetic pre-DP patients, 312 (22.1%) developed newly-diagnosed diabetes after DP. Multiple logistic regression analysis revealed that dyslipidemia [hazard ratio = 1.940; 95% confidence interval = 1.362–2.763; P < 0.001] and chronic pancreatitis (hazard ratio = 2.428; 95% confidence interval = 1.889–3.121; P < 0.001) were significantly associated with the development of diabetes after DP. On the other hand, analysis of changes in glucose metabolism among 289 pre-DP diabetes without the use of insulin revealed that 173 (59.9%) had deteriorated glucose metabolism after DP.

Conclusion

Dyslipidemia and chronic pancreatitis are risk factors for the development of diabetes. Further, more than half of the pre-DP diabetes patients without the use of insulin had deterioration of glucose metabolism after DP. Therefore, clinicians should monitor glucose metabolism and clinical symptoms of hyperglycemia among DP patients.

Antidiabetic and Lipid-Lowering Effects of the Polyphenol Extracts from the Leaves of Clausena lansium (Lour.) Skeels on Streptozotocin-Induced Type 2 Diabetic Rats

Clausena lansium (Lour.) Skeels (Wampee) is widely grown in China and considered as a healthy fruit. Its leaves are also considered as traditional herbs. This study analyzed polyphenol compounds in polyphenol extracts of the leaves C. lansium (lour.) Skeels (PEL) and investigated the protective effect of PEL against hyperglycemia and hyperlipidemia in T2DM rats. The result showed that PEL is composed mainly of gallic acid, chlorogenic acid, coffee acid, ferulic acid, and rutin. PEL could obviously relieve some symptoms of T2DM rats, including emaciation, hyperhidrosis, polyphagia, diuresis, liver swelling, kidney, and pancreas hypertrophy, as well as reduce fasting blood glucose. Moreover, the supplementation of PEL significantly ameliorated lipids disorder and protected liver in T2DM rats, including fat accumulation, improvement of lipid distribution and hepatocyte protection. These results indicate that the Oral of PEL have potential effects of against hyperglycemia and hyperlipidemia in diabetic disorders.

PRACTICAL APPLICATION

The leaves Clausena lansium (lour.) Skeels is rich in polyphenol and other ingredients. In this research, the preliminary study shows that PEL can reduce fasting blood glucose and improve lipids disorder in rats, which will bring to diabetic patients a way to improve the disease and enhance the quality of life. The PEL therefore can be used for the production of pharmaceutical raw materials and the design of novel functional foods by simple conversion.

Metabolomics applied to diabetes-lessons from human population studies

The 'classical' distribution of type 2 diabetes (T2D) across the globe is rapidly changing and it is no longer predominantly a disease of middle-aged/elderly adults of western countries, but it is becoming more common through Asia and the Middle East, as well as increasingly found in younger individuals. This global altered incidence of T2D is most likely associated with the spread of western diets and sedentary lifestyles, although there is still much debate as to whether the increased incidence rates are due to an overconsumption of fats, sugars or more generally high-calorie foods. In this context, understanding the interactions between genes of risk and diet and how they influence the incidence of T2D will help define the causative pathways of the disease. This review focuses on the use of metabolomics in large cohort studies to follow the incidence of type 2 diabetes in different populations. Such approaches have been used to identify new biomarkers of pre-diabetes, such as branch chain amino acids, and associate metabolomic profiles with genes of known risk in T2D from large scale GWAS studies. As the field develops, there are also examples of meta-analysis across metabolomics cohort studies and cross-comparisons with different populations to allow us to understand how genes and diet contribute to disease risk. Such approaches demonstrate that insulin resistance and T2D have far reaching metabolic effects beyond raised blood glucose and how the disease impacts systemic metabolism.

Comprehensive Metabolomic Analysis in Blood, Urine, Fat, and Muscle in Men with Metabolic Syndrome: A Randomized, Placebo-Controlled Clinical Trial on the Effects of Resveratrol after Four Months' Treatment

Resveratrol possesses several beneficial metabolic effects in rodents, while the effects of resveratrol in humans remain unclear. Therefore, we performed a non-targeted comprehensive metabolomic analysis on blood, urine, adipose tissue, and skeletal muscle tissue in middle-aged men with metabolic syndrome randomized to either resveratrol or placebo treatment for four months. Changes in steroid hormones across all four matrices were the most pronounced changes observed. Resveratrol treatment reduced sulfated androgen precursors in blood, adipose tissue, and muscle tissue, and increased these metabolites in urine. Furthermore, markers of muscle turnover were increased and lipid metabolism was affected, with increased intracellular glycerol and accumulation of long-chain saturated, monounsaturated, and polyunsaturated (n3 and n6) free fatty acids in resveratrol-treated men. Finally, urinary derivatives of aromatic amino acids, which mainly reflect the composition of the gut microbiota, were altered upon resveratrol treatment. In conclusion, the non-targeted metabolomics approach applied to four different matrices provided evidence of subtle but robust effects on several metabolic pathways following resveratrol treatment for four months in men with metabolic syndrome—effects that, for the most part, would not have been detected by routine analyses. The affected pathways should be the focus of future clinical trials on resveratrol’s effects, and perhaps particularly the areas of steroid metabolism and the gut microbiome.

Technical Challenges in Mass Spectrometry-Based Metabolomics

Metabolomics is a strategy for analysis, and quantification of the complete collection of metabolites present in biological samples. Metabolomics is an emerging area of scientific research because there are many application areas including clinical, agricultural, and medical researches for the biomarker discovery and the metabolic system analysis by employing widely targeted analysis of a few hundred preselected metabolites from 10-100 biological samples. Further improvement in technologies of mass spectrometry in terms of experimental design for larger scale analysis, computational methods for tandem mass spectrometry-based elucidation of metabolites, and specific instrumentation for advanced bioanalysis will enable more comprehensive metabolome analysis for exploring the hidden secrets of metabolism.