Identification of metabolic biomarkers in patients with type 2 diabetic coronary heart diseases based on metabolomic approach

Metabolomics Characterization of Disease Markers in Diabetes and Its Associated Pathologies

With the change in lifestyle of people, there has been a considerable increase in diabetes, which brings with it certain follow-up pathological conditions, which lead to a substantial medical burden. Identifying biomarkers that aid in screening, diagnosis, and prognosis of diabetes and its associated pathologies would help better patient management and facilitate a personalized treatment approach for prevention and treatment. With the advancement in techniques and technologies, metabolomics has emerged as an omics approach capable of large-scale high throughput data analysis and identifying and quantifying metabolites that provide an insight into the underlying mechanism of the disease and its progression. Diabetes and metabolomics keywords were searched in correspondence with the assigned keywords, including kidney, cardiovascular diseases and critical illness from PubMed and Scopus, from its inception to Dec 2023. The relevant studies from this search were extracted and included in the study. This review is focused on the biomarkers identified in diabetes, diabetic kidney disease, diabetes-related development of CVD, and its role in critical illness.

Exploring Salivary Metabolic Alterations in Type 2 Diabetes: Implications for Dental Caries and Potential Influences of HbA1c and Vitamin D Levels

Diabetes mellitus is considered to be the most common health issue affecting almost 1 in 11 adults globally. Oral health complications including xerostomia, periodontal disease, dental caries, and soft tissue lesions are prevalent among individuals with diabetes, and therefore an understanding of the potential association between salivary metabolites and dental caries progression would enable the early detection and prevention of this non-communicable disease. Therefore, the aim of this study was to compare salivary biomarkers between individuals with type 2 diabetes (T2DM) with those without this disorder (ND) using 1H NMR-based metabolomics strategies. The objectives were to identify T2DM-associated biomarker signatures and their potential impact on dental caries. In addition, HbA1c and vitamin D levels were also analysed for this purpose.

METHODS

Stimulated whole-mouth saliva (SWS) samples were collected from T2DM and ND (n = 30 in each case) participants randomly selected from a group of 128 participants recruited for this case-control study. All participants were advised to refrain from eating, drinking, and smoking for at least 1-2 h prior to sample collection. Following preparation, SWS supernatants underwent 1H NMR analysis at an operating frequency of 800 MHz, and the dataset acquired was analysed using a range of multivariate metabolomics techniques.

RESULTS

Metabolomics analysis of data acquired demonstrated that, together with up- and downregulated blood HbA1c and vitamin D levels, key salivary discriminators between these two classifications included lactate, taurine, creatinine, α-glucose, and formate to a lesser extent. The bacterial catabolites lactate and formate were both significantly upregulated in the T2DM group, and these have previously been implicated in the pathogenesis of dental caries. Significance analysis of metabolites (SAM)-facilitated AUROC analysis yielded an 83% accuracy for this distinction.

CONCLUSION

In conclusion, this study highlights the significant differences in salivary metabolites between individuals with T2DM and healthy controls. Such differences appear to be related to the development and progression of dental caries in T2DM patients.

A pilot study of alternative substrates in the critically Ill subject using a ketogenic feed

Bioenergetic failure caused by impaired utilisation of glucose and fatty acids contributes to organ dysfunction across multiple tissues in critical illness. Ketone bodies may form an alternative substrate source, but the feasibility and safety of inducing a ketogenic state in physiologically unstable patients is not known. Twenty-nine mechanically ventilated adults with multi-organ failure managed on intensive care units were randomised (Ketogenic n = 14, Control n = 15) into a two-centre pilot open-label trial of ketogenic versus standard enteral feeding. The primary endpoints were assessment of feasibility and safety, recruitment and retention rates and achievement of ketosis and glucose control. Ketogenic feeding was feasible, safe, well tolerated and resulted in ketosis in all patients in the intervention group, with a refusal rate of 4.1% and 82.8% retention. Patients who received ketogenic feeding had fewer hypoglycaemic events (0.0% vs. 1.6%), required less exogenous international units of insulin (0 (Interquartile range 0-16) vs.78 (Interquartile range 0-412) but had slightly more daily episodes of diarrhoea (53.5% vs. 42.9%) over the trial period. Ketogenic feeding was feasible and may be an intervention for addressing bioenergetic failure in critically ill patients. Clinical Trials.gov registration: NCT04101071.

Metabolomics signature of cardiovascular disease in patients with diabetes, a narrative review

Objectives

The exact underlying mechanism of developing diabetes-related cardiovascular disease (CVD) among patients with type 2 diabetes (T2D) is not clear. Metabolomics can provide a platform enabling the prediction, diagnosis, and understanding of the risk of CVD in patients with diabetes mellitus. The aim of this review is to summarize the available evidence on the relationship between metabolomics and cardiovascular diseases in patients with diabetes.

Methods

The literature was searched to find out studies that have investigated the relationship between the alteration of specific metabolites and cardiovascular diseases in patients with diabetes.

Results

Evidence proposed that changes in the metabolism of certain amino acids, lipids, and carbohydrates, independent of traditional CVD risk factors, are associated with increased CVD risk.

Conclusions

Metabolomics can provide a platform to enable the prediction, diagnosis, and understanding of the risk of CVD in patients with diabetes mellitus. The association of the alteration in specific metabolites with CVD may be considered in the investigations for the development of new therapeutic targets for the prevention of CVD in patients with diabetes mellitus.

Identification of Novel Biomarkers for Early Diagnosis of Atherosclerosis Using High-Resolution Metabolomics

Atherosclerosis (AS) is a metabolic disorder and the pre-stage of several cardiovascular diseases, including myocardial infarction, stroke, and angina pectoris. Early detection of AS can provide the opportunity for effective management and better clinical results, along with the prevention of further progression of the disease. In the current study, an untargeted and targeted metabolomic approach was used to identify possible metabolic signatures that have altered levels in AS patients. A total of 200 serum samples from individuals with AS and normal were analyzed via liquid chromatography-high-resolution mass spectrometry. Univariate and multivariate analysis approaches were used to identify differential metabolites. A group of metabolites associated with bile acids, amino acids, steroid hormones, and purine metabolism were identified that are capable of distinguishing AS-risk sera from normal. Further, the targeted metabolomics approach confirmed that six metabolites, namely taurocholic acid, cholic acid, cortisol, hypoxanthine, trimethylamine N-oxide (TMAO), and isoleucine, were found to be significantly upregulated, while the concentrations of glycoursodeoxycholic acid, glycocholic acid, testosterone, leucine, methionine, phenylalanine, tyrosine, and valine were found to be significantly downregulated in the AS-risk sera. The receiver operating characteristic curves of three metabolites, including cortisol, hypoxanthine, and isoleucine, showed high sensitivity and specificity. Taken together, these findings suggest cortisol, hypoxanthine, and isoleucine as novel biomarkers for the early and non-invasive detection of AS. Thus, this study provides new insights for further investigations into the prevention and management of AS.

Insulin resistance in Alzheimer's disease: The genetics and metabolomics links

Alzheimer's disease (AD) is a neurodegenerative disease with significant socioeconomic burden worldwide. Although genetics and environmental factors play a role, AD is highly associated with insulin resistance (IR) disorders such as metabolic syndrome (MS), obesity, and type two diabetes mellitus (T2DM). These findings highlight a shared pathogenesis. The use of metabolomics as a downstream systems' biology (omics) approach can help to identify these shared metabolic traits and assist in the early identification of at-risk groups and potentially guide therapy. Targeting the shared AD-IR metabolic trait with lifestyle interventions and pharmacological treatments may offer promising AD therapeutic approach. In this narrative review, we reviewed the literature on the AD-IR pathogenic link, the shared genetics and metabolomics biomarkers between AD and IR disorders, as well as the lifestyle interventions and pharmacological treatments which target this pathogenic link.

Differences in the serum metabolic profile to identify potential biomarkers for cyanotic versus acyanotic heart disease

BACKGROUND

Growth retardation, malnutrition, and failure to thrive are some of the consequences associated with congenital heart diseases. Several metabolic factors such as hypoxia, anoxia, and several genetic factors are believed to alter the energetics of the heart. Timely diagnosis and patient management is one of the major challenges faced by the clinicians in understanding the disease and provide better treatment options. Metabolic profiling has shown to be potential diagnostic tool to understand the disease.

OBJECTIVE

The present experiment was designed as a single center observational pilot study to classify and create diagnostic metabolic signatures associated with the energetics of congenital heart disease in cyanotic and acyanotic groups.

METHODS

Metabolic sera profiles were obtained from 35 patients with cyanotic congenital heart disease (TOF) and 23 patients with acyanotic congenital heart disease (ASD and VSD) using high resolution 1D 1H NMR spectra. Univariate and multivariate statistical analysis were performed to classify particular metabolic disorders associated with cyanotic and acyanotic heart disease.

RESULTS

The results show dysregulations in several metabolites in cyanotic CHD patients versus acyanotic CHD patients. The discriminatory metabolites were further analyzed with area under receiver operating characteristic (AUROC) curve and identified four metabolic entities (i.e. mannose, hydroxyacetone, myoinositol, and creatinine) which could differentiate cyanotic CHDs from acyanotic CHDs with higher specificity.

CONCLUSION

An untargeted metabolic approach proved to be helpful for the detection and distinction of disease-causing metabolites in cyanotic patients from acyanotic ones and can be useful for designing better and personalized treatment protocol.

Small extracellular vesicles from young adipose-derived stem cells prevent frailty, improve health span, and decrease epigenetic age in old mice

Aging is associated with an increased risk of frailty, disability, and mortality. Strategies to delay the degenerative changes associated with aging and frailty are particularly interesting. We treated old animals with small extracellular vesicles (sEVs) derived from adipose mesenchymal stem cells (ADSCs) of young animals, and we found an improvement in several parameters usually altered with aging, such as motor coordination, grip strength, fatigue resistance, fur regeneration, and renal function, as well as an important decrease in frailty. ADSC-sEVs induced proregenerative effects and a decrease in oxidative stress, inflammation, and senescence markers in muscle and kidney. Moreover, predicted epigenetic age was lower in tissues of old mice treated with ADSC-sEVs and their metabolome changed to a youth-like pattern. Last, we gained some insight into the microRNAs contained in sEVs that might be responsible for the observed effects. We propose that young sEV treatment can promote healthy aging.

Healthy lifestyle, metabolomics and incident type 2 diabetes in a population-based cohort from Spain

Background

The contribution of metabolomic factors to the association of healthy lifestyle with type 2 diabetes risk is unknown. We assessed the association of a composite measure of lifestyle with plasma metabolite profiles and incident type 2 diabetes, and whether relevant metabolites can explain the prospective association between healthy lifestyle and incident type 2 diabetes.

Methods

A Healthy Lifestyle Score (HLS) (5-point scale including diet, physical activity, smoking status, alcohol consumption and BMI) was estimated in 1016 Hortega Study participants, who had targeted plasma metabolomic determinations at baseline examination in 2001–2003, and were followed-up to 2015 to ascertain incident type 2 diabetes.

Results

The HLS was cross-sectionally associated with 32 (out of 49) plasma metabolites (2.5% false discovery rate). In the subset of 830 participants without prevalent type 2 diabetes, the rate ratio (RR) and rate difference (RD) of incident type 2 diabetes (n cases = 51) per one-point increase in HLS was, respectively, 0.69 (95% CI, 0.51, 0.93), and − 8.23 (95% CI, − 16.34, − 0.13)/10,000 person-years. In single-metabolite models, most of the HLS-related metabolites were prospectively associated with incident type 2 diabetes. In probit Bayesian Kernel Machine Regression, these prospective associations were mostly driven by medium HDL particle concentration and phenylpropionate, followed by small LDL particle concentration, which jointly accounted for ~ 50% of the HLS-related decrease in incident type 2 diabetes.

Conclusions

The HLS showed a strong inverse association with incident type 2 diabetes, which was largely explained by plasma metabolites measured years before the clinical diagnosis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12966-021-01219-3.

Oral L-Arginine (5 g/day) for 14 Days Improves Microcirculatory Function in Healthy Young Women and Healthy and Type 2 Diabetes Mellitus Elderly Women

OBJECTIVE

The aim of this study was to investigate the effect of oral supplementation with L-arginine on serum biochemical profile, blood pressure, microcirculation, and vasoreactivity/endothelial function in young controls, and elderly women with and without type 2 diabetes mellitus (T2DM).

METHODS

Healthy young (n = 25), healthy elderly (n = 25), and elderly women with type 2 diabetes mellitus (T2DME, n = 23, glycated Hb ≥6.4% and mean of 7.7 years for duration of the disease), aged 18-30 and older than 65 years, respectively, were included in the study. All patients underwent biochemical analysis (fasting glycemia and lipidogram), arterial blood pressure, nailfold videocapillaroscopy (capillary diameters, functional capillary density [FCD], peak red blood cell velocity [RBCVmax] after 1 min ischemia, time to reach peak RBCV [TRBCVmax]), and venous occlusion plethysmography (vasoreactivity), before and after 14 days of oral supplementation with L-arginine (5 g/day).

RESULTS

L-Arginine did not change fasting glycemia and lipidogram, but it decreased systolic, diastolic, and mean arterial pressure in elderly women, increased RBCVmax in all groups, and did not decrease TRBCVmax in T2DME. Capillary diameters and FCD remained unchanged in all groups. L-Arginine improved vasoreactivity during reactive hyperemia and after sublingual nitroglycerin (0.4 mg) in all groups.

CONCLUSION

L-Arginine supplementation (5g/day during 14 days) was able to improve vascular/microvascular health in the elderly women with or without T2DM.

Histone H4 lysine 16 acetylation controls central carbon metabolism and diet-induced obesity in mice

Noncommunicable diseases (NCDs) account for over 70% of deaths world-wide. Previous work has linked NCDs such as type 2 diabetes (T2D) to disruption of chromatin regulators. However, the exact molecular origins of these chronic conditions remain elusive. Here, we identify the H4 lysine 16 acetyltransferase MOF as a critical regulator of central carbon metabolism. High-throughput metabolomics unveil a systemic amino acid and carbohydrate imbalance in Mof deficient mice, manifesting in T2D predisposition. Oral glucose tolerance testing (OGTT) reveals defects in glucose assimilation and insulin secretion in these animals. Furthermore, Mof deficient mice are resistant to diet-induced fat gain due to defects in glucose uptake in adipose tissue. MOF-mediated H4K16ac deposition controls expression of the master regulator of glucose metabolism, Pparg and the entire downstream transcriptional network. Glucose uptake and lipid storage can be reconstituted in MOF-depleted adipocytes in vitro by ectopic Glut4 expression, PPARγ agonist thiazolidinedione (TZD) treatment or SIRT1 inhibition. Hence, chronic imbalance in H4K16ac promotes a destabilisation of metabolism triggering the development of a metabolic disorder, and its maintenance provides an unprecedented regulatory epigenetic mechanism controlling diet-induced obesity.

Circulating amino acids as fingerprints of visceral adipose tissue independent of insulin resistance: a targeted metabolomic research in women

Introduction: Although obesity and its biomarkers have been intensively studied, little is known about the metabolomic signature of visceral adiposity independent of insulin resistance that frequently accompanies increased levels of visceral fat. Our study aimed to investigate specific changes in amino acid (AA) levels as biomarkers of increased visceral adiposity independent of insulin resistance, in healthy subjects.

Methods: Forty-two adult women were included in this cross-sectional study. Serum samples were analyzed by AAs targeted metabolomics according to their visceral fat area (<100 cm2 and ≥100 cm2).

Results: By corrected t-test and supervised partial least-squares discriminant analysis (PLS-DA) we identified 4 AAs that were significantly higher in the group with higher visceral fat: proline (variable importance in the projection [VIP] predicted value: 1.97), tyrosine (VIP: 2.21), cysteine (VIP: 1.19), isoleucine (VIP: 1.04; p-values <0.05). Also, glycine was significantly lower in the group with higher visceral fat (VIP: 1.65; p-value <0.05). All AAs identified were associated with visceral fat independent of homeo-static model assessment for insulin resistance (p-value for regression coefficients <0.05).

Conclusion: Metabolic pathways that might be disrupted in persons with increased visceral fat are phenylalanine, tyrosine, and tryptophan biosynthesis; tyrosine metabolism; glycine, serine, and threonine metabolism; glyoxylate and dicarboxylate metabolism, and cysteine and methionine metabolism.

Metabolomics in Diabetes and Diabetic Complications: Insights from Epidemiological Studies

The increasing prevalence of diabetes and its complications, such as cardiovascular and kidney disease, remains a huge burden globally. Identification of biomarkers for the screening, diagnosis, and prognosis of diabetes and its complications and better understanding of the molecular pathways involved in the development and progression of diabetes can facilitate individualized prevention and treatment. With the advancement of analytical techniques, metabolomics can identify and quantify multiple biomarkers simultaneously in a high-throughput manner. Providing information on underlying metabolic pathways, metabolomics can further identify mechanisms of diabetes and its progression. The application of metabolomics in epidemiological studies have identified novel biomarkers for type 2 diabetes (T2D) and its complications, such as branched-chain amino acids, metabolites of phenylalanine, metabolites involved in energy metabolism, and lipid metabolism. Metabolomics have also been applied to explore the potential pathways modulated by medications. Investigating diabetes using a systems biology approach by integrating metabolomics with other omics data, such as genetics, transcriptomics, proteomics, and clinical data can present a comprehensive metabolic network and facilitate causal inference. In this regard, metabolomics can deepen the molecular understanding, help identify potential therapeutic targets, and improve the prevention and management of T2D and its complications. The current review focused on metabolomic biomarkers for kidney and cardiovascular disease in T2D identified from epidemiological studies, and will also provide a brief overview on metabolomic investigations for T2D.

Metabolic Interactions and Differences between Coronary Heart Disease and Diabetes Mellitus: A Pilot Study on Biomarker Determination and Pathogenesis

Comprehensive understanding of plasma metabotype of diabetes mellitus (DM), coronary heart disease (CHD), and especially diabetes mellitus with coronary heart disease (CHDDM) is still lacking. In this work, the plasma metabolic differences and links of DM, CHD, and CHDDM patients were investigated by the strategy of comparative metabolomics based on ¹H NMR spectroscopy combined with network analysis for revealing their metabolic differences. A total of 17 metabolites are related to three diseases, among which valine, alanine, leucine, isoleucine, and N-acetyl-glycoprotein are positively correlated with CHD and CHDDM (odds ratios (OR) > 1). The trimethylamine oxide, glycerol, lactose, indoleacetate, and scyllo-inositol are closely related to the development of DM to CHDDM (OR > 1), and indoleactate (OR: 1.06, 95% confidence interval (CI): 1.01-1.12) and lactose (OR: 2.46, 95% CI: 1.67-3.25) are particularly prominent in CHDDM. We identified three multi-biomarkers types that were significantly associated with glycosylated hemoglobin (HbA1C) at baseline. All diseases demonstrated dysregulated glycolysis/gluconeogenesis and amino acid biosynthesis pathway. In addition, enrichment in tryptophan metabolism observed in CHDDM, enrichment in inositol phosphate metabolism observed in DM, and the metabolites related to microbiota metabolism were dysregulated in both DM and CHDDM. The comparative metabolomics strategy of multi-diseases offers a new perspective in disease-specific markers and pathogenic pathways.

Metabolite biomarkers of type 2 diabetes mellitus and pre-diabetes: a systematic review and meta-analysis

BACKGROUND

We aimed to explore metabolite biomarkers that could be used to identify pre-diabetes and type 2 diabetes mellitus (T2DM) using systematic review and meta-analysis.

METHODS

Four databases, the Cochrane Library, EMBASE, PubMed and Scopus were selected. A random effect model and a fixed effect model were applied to the results of forest plot analyses to determine the standardized mean difference (SMD) and 95% confidence interval (95% CI) for each metabolite. The SMD for every metabolite was then converted into an odds ratio to create an metabolite biomarker profile.

RESULTS

Twenty-four independent studies reported data from 14,131 healthy individuals and 3499 patients with T2DM, and 14 included studies reported 4844 healthy controls and a total of 2139 pre-diabetes patients. In the serum and plasma of patients with T2DM, compared with the healthy participants, the concentrations of valine, leucine, isoleucine, proline, tyrosine, lysine and glutamate were higher and that of glycine was lower. The concentrations of isoleucine, alanine, proline, glutamate, palmitic acid, 2-aminoadipic acid and lysine were higher and those of glycine, serine, and citrulline were lower in prediabetic patients. Metabolite biomarkers of T2DM and pre-diabetes revealed that the levels of alanine, glutamate and palmitic acid (C16:0) were significantly different in T2DM and pre-diabetes.

CONCLUSIONS

Quantified multiple metabolite biomarkers may reflect the different status of pre-diabetes and T2DM, and could provide an important reference for clinical diagnosis and treatment of pre-diabetes and T2DM.

Zanthoxylum alkylamides improve amino acid metabolism in type 2 diabetes mellitus rats

To investigate the effect of Zanthoxylum alkylamides (ZA) on amino acid metabolism of type 2 diabetes mellitus (T2DM), the present study was performed with T2DM rats model induced with high fat and sugar fodder combined with low-dose of streptozotocin. ZA were fed to rats at three different doses of 2, 4, and 8 mg/kg for 28 days and metformin was fed to rats at 135 mg/kg as positive control. The results showed that compared with the normal control, the amino acid levels and the expression of related carrier genes were disordered in T2DM rats. Compared with the model, different doses of ZA could significantly resist (p < .05) the decrease in body weight of T2DM rats and improve hyperglycemia, with the best result observed with the high dose (8 mg/kg). Different doses of ZA could ameliorate the levels of 19 kinds of amino acid in the plasma, jejunum, liver, and skeletal muscle of T2DM rats by regulating the expression of related amino acid transporters including LAT1, SNAT2, CAT1, et al. to thereby ameliorating amino acid metabolism disorder in T2DM rats. PRACTICAL APPLICATIONS: Previous studies showed that Zanthoxylum alkylamides (ZA) could promote the amino acid metabolism in the jejunum of healthy SD rats, improve protein metabolism disorder of type 1 diabetic rats, and also reduce the risk of metabolic syndrome in fat rats model. Herein, we investigated the effect of ZA on amino acid metabolism in type 2 diabetes mellitus (T2DM) rats. The results indicated that ZA could remarkably improve the abnormal expression of amino acid carriers in the jejunum, liver, and skeletal muscle, thereby ameliorating the disorder of amino acid metabolism in the plasma, jejunum, liver, and skeletal muscle of T2DM rats. Therefore, ZA are potential antidiabetic food/medicine product for the T2DM treatment.

Metabolomics applications in coronary artery disease personalized medicine

Coronary artery disease (CAD), the most common cardiovascular disease (CVD), contributes to significant mortality worldwide. CAD is a multifactorial disease wherein various factors contribute to its pathogenesis often complicating management. Biomarker based personalized medicine may provide a more effective way to individualize therapy in multifactorial diseases in general and CAD specifically. Systems' biology "Omics" biomarkers have been investigated for this purpose. These biomarkers provide a more comprehensive understanding on pathophysiology of the disease process and can help in identifying new therapeutic targets and tailoring therapy to achieve optimum outcome. Metabolomics biomarkers usually reflect genetic and non-genetic factors involved in the phenotype. Metabolomics analysis may provide better understanding of the disease pathogenesis and drug response variation. This will help in guiding therapy, particularly for multifactorial diseases such as CAD. In this chapter, advances in metabolomics analysis and its role in personalized medicine will be reviewed with comprehensive focus on CAD. Assessment of risk, diagnosis, complications, drug response and nutritional therapy will be discussed. Together, this chapter will review the current application of metabolomics in CAD management and highlight areas that warrant further investigation.

A Translational In Vivo and In Vitro Metabolomic Study Reveals Altered Metabolic Pathways in Red Blood Cells of Type 2 Diabetes

Clinical parameters used in type 2 diabetes mellitus (T2D) diagnosis and monitoring such as glycosylated haemoglobin (HbA1c) are often unable to capture important information related to diabetic control and chronic complications. In order to search for additional biomarkers, we performed a pilot study comparing T2D patients with healthy controls matched by age, gender, and weight. By using ¹H-nuclear magnetic resonance (NMR) based metabolomics profiling of red blood cells (RBCs), we found that the metabolic signature of RBCs in T2D subjects differed significantly from non-diabetic controls. Affected metabolites included glutathione, 2,3-bisphophoglycerate, inosinic acid, lactate, 6-phosphogluconate, creatine and adenosine triphosphate (ATP) and several amino acids such as leucine, glycine, alanine, lysine, aspartate, phenylalanine and tyrosine. These results were validated by an independent cohort of T2D and control patients. An analysis of the pathways in which these metabolites were involved showed that energetic and redox metabolism in RBCs were altered in T2D, as well as metabolites transported by RBCs. Taken together, our results revealed that the metabolic profile of RBCs can discriminate healthy controls from T2D patients. Further research is needed to determine whether metabolic fingerprint in RBC could be useful to complement the information obtained from HbA1c and glycemic variability as well as its potential role in the diabetes management.

Pathway Analysis of Global Metabolomic Profiles Identified Enrichment of Caffeine, Energy, and Arginine Metabolism in Smokers but Not Moist Snuff Consumers

Existing US epidemiological data demonstrate that consumption of smokeless tobacco, particularly moist snuff, is less harmful than cigarette smoking. However, the molecular and biochemical changes due to moist snuff consumption relative to smoking remain incompletely understood. We previously reported that smokers (SMK) exhibit elevated oxidative stress and inflammation relative to moist snuff consumers (MSC) and non-tobacco consumers (NTC), based on metabolomic profiling data of saliva, plasma, and urine from MSC, SMK, and NTC. In this study, we investigated the effects of tobacco consumption on additional metabolic pathways using pathway-based analysis tools. To this end, metabolic pathway enrichment analysis and topology analysis were performed through pair-wise comparisons of global metabolomic profiles of SMK, MSC, and NTC. The analyses identified >8 significantly perturbed metabolic pathways in SMK compared with NTC and MSC in all 3 matrices. Among these differentially enriched pathways, perturbations of caffeine metabolism, energy metabolism, and arginine metabolism were mostly observed. In comparison, fewer enriched metabolic pathways were identified in MSC compared with NTC (5 in plasma, none in urine and saliva). This is consistent with our transcriptomics profiling results that show no significant differences in peripheral blood mononuclear cell gene expression between MSC and NTC. These findings, taken together with our previous biochemical, metabolomic, and transcriptomic analysis results, provide a better understanding of the relative changes in healthy tobacco consumers, and demonstrate that chronic cigarette smoking, relative to the use of smokeless tobacco, results in more pronounced biological changes, which could culminate in smoking-related diseases.

Metabolomic profiling of blood plasma in patients with primary brain tumours: Basal plasma metabolites correlated with tumour grade and plasma biomarker analysis predicts feasibility of the successful statistical discrimination from healthy subjects - a preliminary study

The brain tumours represent a complex tissue that has its own characteristic metabolic features and is interfaced with the whole organism. We investigated changes in basal blood plasma metabolites in the presence of primary brain tumour, their correlation with tumour grade, as well as the feasibility of statistical discrimination based on plasma metabolites. Together 60 plasma samples from patients with clinically defined glioblastoma, meningioma, oligodendrioglioma, astrocytoma, and non-specific glial tumour and plasma samples from 28 healthy volunteers without any cancer history were measured by NMR spectroscopy. In blood plasma of primary brain tumour patients, we found significantly increased levels of glycolytic metabolites glucose and pyruvate, and significantly decreased level of glutamine and also metabolites participating in tricarboxylic acid (TCA) cycle, citrate and succinate, when compared with controls. Further, plasma metabolites levels: tyrosine, phenylalanine, glucose, creatine and creatinine correlated significantly with tumour grade. In general, observed changes are parallel to the biochemistry expected for tumourous tissue and metabolic changes in plasma seem to follow the similar rules in all primary brain tumours, with very subtle variations among tumour types. Only two plasma metabolites tyrosine and phenylalanine were increased exclusively in blood plasma of patients with glioblastoma. Based on metabolite levels, an excellent discrimination between plasma from patient's tumours and controls was attainable. The metabolites creatine, pyruvate, glucose, formate, creatinine and citrate were of the highest discriminatory power.

NMR metabolome of Borrelia burgdorferi in vitro and in vivo in mice

Lyme borreliosis (LB), caused by bacteria of the Borrelia burgdorferi sensu lato (Borrelia) species, is the most common tick-borne infection in the northern hemisphere. LB diagnostics is based on clinical evaluation of the patient and on laboratory testing, where the main method is the detection of Borrelia specific antibodies in patient samples. There are, however, shortcomings in the current serology based LB diagnostics, especially its inability to differentiate ongoing infection from a previously treated one. Identification of specific biomarkers of diseases is a growing application of metabolomics. One of the main methods of metabolomics is nuclear magnetic resonance (NMR) spectroscopy. In the present study, our aim was to analyze whether Borrelia growth in vitro and infection in vivo in mice causes specific metabolite differences, and whether NMR can be used to detect them. For this purpose, we performed NMR analyses of in vitro culture medium samples, and of serum and urine samples of Borrelia infected and control mice. The results show, that there were significant differences in the concentrations of several amino acids, energy metabolites and aromatic compounds between Borrelia culture and control media, and between infected and control mouse serum and urine samples. For example, the concentration of L-phenylalanine increases in the Borrelia growth medium and in serum of infected mice, whereas the concentrations of allantoin and trigonelline decrease in the urine of infected mice. Therefore, we conclude that Borrelia infection causes measurable metabolome differences in vitro and in Borrelia infected mouse serum and urine samples, and that these can be detected with NMR.

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.

Overview of genomics and post-genomics research on type 2 diabetes mellitus: Future perspectives and a framework for further studies

In this review, we briefly outlined salient features of pathophysiology and results of the genetic association studies hitherto conducted on type 2 diabetes. Primarily focusing on the current status of genomic research, we briefly discussed the limited progress made during the post-genomic era and tried to identify the limitations of the post-genomic research strategies. We suggested reanalysis of the existing genomic data through advanced statistical and computational methods and recommended integrated genomics-metabolomics approaches for future studies to facilitate understanding of the gene-environment interactions in the manifestation of the disease. We also propose a framework for research that may be apt for determining the effects of urbanization and changing lifestyles in the manifestation of complex genetic disorders like type 2 diabetes in the Indian populations and offset the confounding effects of both genetic and environmental factors in the natural way.

Targeted metabolomic analysis of plasma metabolites in patients with coronary heart disease in southern China

Coronary heart disease (CHD), one of the leading causes of death in the world, is a complex metabolic disorder due to genetic and environmental interactions. The potential mechanisms and diagnostic biomarkers for different types of coronary heart disease remain unclear. Metabolomics is increasingly considered to be a promising technology with the potential to identify metabolomic features in an attempt to distinguish the different stages of CHD.We aimed to investigate serum metabolite profiling between CHD patients and normal coronary artery (NCA) subjects and identify metabolic biomarkers associated with CHD progression in an ethnic Hakka population in southern China.Using a novel targeted metabolomics approach, we explored the metabolic characteristics of CHD patients. Blood samples from 302 patients with CHD and 59 NCA subjects were collected that analyses using targeted liquid-chromatography coupled with tandem mass spectrometry (LC-MS).A total of 361 blood samples were determined using targeted LC-MS. Plasma concentrations for trimetlylamine oxide (TMAO), choline, creatinine, and carnitine were significantly higher in patients with CHD compared to the NCA cohort. Further, we observed that the concentration of the 4 metabolites were higher than that of the NCA group in any group of CHD, which including acute myocardial infarction (AMI), unstable angina (UA), and stable angina (SA). In addition, the diagnostic model was constructed based on the metabolites identified and the ROC curve of the NCA subjects and CHD patients were performed. For choline and creatinine, the AUCs ranged from 0.720 to 0.733. For TMAO and carnitine, the AUCs ranged from 0.568 to 0.600.In conclusion, the current study illustrates the distribution of 4 metabolites between CHD patients and NCA subjects. Metabolomics analysis may yield novel predictive biomarkers that will potentially provide value for clinical diagnosis of CHD.

High-Throughput Metabolomics by 1D NMR

Metabolomics deals with the whole ensemble of metabolites (the metabolome). As one of the -omic sciences, it relates to biology, physiology, pathology and medicine; but metabolites are chemical entities, small organic molecules or inorganic ions. Therefore, their proper identification and quantitation in complex biological matrices requires a solid chemical ground. With respect to for example, DNA, metabolites are much more prone to oxidation or enzymatic degradation: we can reconstruct large parts of a mammoth's genome from a small specimen, but we are unable to do the same with its metabolome, which was probably largely degraded a few hours after the animal's death. Thus, we need standard operating procedures, good chemical skills in sample preparation for storage and subsequent analysis, accurate analytical procedures, a broad knowledge of chemometrics and advanced statistical tools, and a good knowledge of at least one of the two metabolomic techniques, MS or NMR. All these skills are traditionally cultivated by chemists. Here we focus on metabolomics from the chemical standpoint and restrict ourselves to NMR. From the analytical point of view, NMR has pros and cons but does provide a peculiar holistic perspective that may speak for its future adoption as a population-wide health screening technique.

NMR-based metabolomics identifies patients at high risk of death within two years after acute myocardial infarction in the AMI-Florence II cohort

BACKGROUND

Risk stratification and management of acute myocardial infarction patients continue to be challenging despite considerable efforts made in the last decades by many clinicians and researchers. The aim of this study was to investigate the metabolomic fingerprint of acute myocardial infarction using nuclear magnetic resonance spectroscopy on patient serum samples and to evaluate the possible role of metabolomics in the prognostic stratification of acute myocardial infarction patients.

METHODS

In total, 978 acute myocardial infarction patients were enrolled in this study; of these, 146 died and 832 survived during 2 years of follow-up after the acute myocardial infarction. Serum samples were analyzed via high-resolution ¹H-nuclear magnetic resonance spectroscopy and the spectra were used to characterize the metabolic fingerprint of patients. Multivariate statistics were used to create a prognostic model for the prediction of death within 2 years after the cardiovascular event.

RESULTS

In the training set, metabolomics showed significant differential clustering of the two outcomes cohorts. A prognostic risk model predicted death with 76.9% sensitivity, 79.5% specificity, and 78.2% accuracy, and an area under the receiver operating characteristics curve of 0.859. These results were reproduced in the validation set, obtaining 72.6% sensitivity, 72.6% specificity, and 72.6% accuracy. Cox models were used to compare the known prognostic factors (for example, Global Registry of Acute Coronary Events score, age, sex, Killip class) with the metabolomic random forest risk score. In the univariate analysis, many prognostic factors were statistically associated with the outcomes; among them, the random forest score calculated from the nuclear magnetic resonance data showed a statistically relevant hazard ratio of 6.45 (p = 2.16×10^-16). Moreover, in the multivariate regression only age, dyslipidemia, previous cerebrovascular disease, Killip class, and random forest score remained statistically significant, demonstrating their independence from the other variables.

CONCLUSIONS

For the first time, metabolomic profiling technologies were used to discriminate between patients with different outcomes after an acute myocardial infarction. These technologies seem to be a valid and accurate addition to standard stratification based on clinical and biohumoral parameters.

Mechanism of YLTZ on glycolipid metabolism based on UPLC/TOF/MS metabolomics

Type 2 diabetes mellitus (T2DM) is a metabolic disease characterized by dysfunction of glycolipid metabolism. YLTZ is used to treat hyperlipidemia, yet its hypolipidemic and hypoglycemic mechanism on T2DM are unknown. Thus, UPLC/TOF/MS was applied in this study to identify the potential bio-markers, and deduce the possible metabolic pathways. According to bio-indexes, the increased blood lipid levels, including TC, TG, LDL and FA, and the decreased HDL, the elevated glucose, reduced insulin level and impaired OGTT were observed in diabetic rat model. While YLTZ can decrease the lipid levels and glucose content, as well as increased insulin standards and improve OGTT. After data from UPLC/TOF/MS processed, 17 metabolites were obtained, including phospholipids (LPCs, PCs and PGP (18:1)), beta-oxidation production (HAA, VAG and CNE) and precursors (THA), bile acid (CA, CDCA and IDCA), hydrolysate of TG (MG (22:4)), glycometabolism (G6P), cholesterol-driven synthetics (ADO) and production of arachidonate acid (THETA). As a result, YLTZ was able to reduce LPCs, PCs, PGP (18:1), HAA, VAG, CNE, CA, ADO and THETA, as well as enhance MG (22:4) and G6P. After analyzing results, several metabolic pathways were deduced, which containing, cholesterol synthesis and elimination, FA beta-oxidation, TG hydrolysis, phospholipids synthesis, glycolysis, gluconeogenesis and inflammation. Consequently, YLTZ performed to prohibit the FA beta-oxidation, synthesis of cholesterol and phospholipids, gluconeogenesis and inflammation level, as well as promote TG hydrolysis, glycolysis and blood circulation. Hence, applying metabonomics in TCM research can uncover its pharmacological edges, elucidating comprehensively that YLTZ has capacity of hypolipidemic, hypoglycemic and promoting blood circulation, matching the effect of removing blood stasis, eliminating phlegm and dampness.

Metabolomics-A Promising Approach to Pituitary Adenomas

Background: Metabolomics-the novel science that evaluates the multitude of low-molecular-weight metabolites in a biological system, provides new data on pathogenic mechanisms of diseases, including endocrine tumors. Although development of metabolomic profiling in pituitary disorders is at an early stage, it seems to be a promising approach in the near future in identifying specific disease biomarkers and understanding cellular signaling networks. Objectives: To review the metabolomic profile and the contributions of metabolomics in pituitary adenomas (PA). Methods: A systematic review was conducted via PubMed, Web of Science Core Collection and Scopus databases, summarizing studies that have described metabolomic aspects of PA. Results: Liquid chromatography tandem mass spectrometry (LC-MS/MS) and nuclear magnetic resonance (NMR) spectrometry, which are traditional techniques employed in metabolomics, suggest amino acids metabolism appears to be primarily altered in PA. N-acetyl aspartate, choline-containing compounds and creatine appear as highly effective in differentiating PA from healthy tissue. Deoxycholic and 4-pyridoxic acids, 3-methyladipate, short chain fatty acids and glucose-6-phosphate unveil metabolite biomarkers in patients with Cushing's disease. Phosphoethanolamine, N-acetyl aspartate and myo-inositol are down regulated in prolactinoma, whereas aspartate, glutamate and glutamine are up regulated. Phosphoethanolamine, taurine, alanine, choline-containing compounds, homocysteine, and methionine were up regulated in unclassified PA across studies. Intraoperative use of ultra high mass resolution matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), which allows localization and delineation between functional PA and healthy pituitary tissue, may contribute to achievement of complete tumor resection in addition to preservation of pituitary cell lines and vasopressin secretory cells, thus avoiding postoperative diabetes insipidus. Conclusion: Implementation of ultra high performance metabolomics analysis techniques in the study of PA will significantly improve diagnosis and, potentially, the therapeutic approach, by identifying highly specific disease biomarkers in addition to novel molecular pathogenic mechanisms. Ultra high mass resolution MALDI-MSI emerges as a helpful clinical tool in the neurosurgical treatment of pituitary tumors. Therefore, metabolomics appears to be a science with a promising prospect in the sphere of PA, and a starting point in pituitary care.

Serum metabolic profiling of type 2 diabetes mellitus in Chinese adults using an untargeted GC/TOFMS

BACKGROUND

Type 2 diabetes mellitus (T2DM) is a huge burden in China. The Chinese patients with T2DM have several special clinical characteristics. Metabolomics studies predominantly have identified several distinguishing metabolites associated with T2DM in Western ancestry population. However, few previous metabolomics studies were conducted in Chinese populations.

METHODS

We performed untargeted serum metabolic profiling between 30 T2DM patients and 30 healthy controls based on GC/TOFMS. Multivariate data analyses were applied to identify the distinguishing metabolites.

RESULTS

Excellent separation was obtained between the two cases. And overall 54 distinguishing metabolites were identified with VIP>1 and P<0.05, which were involved in metabolic pathways of amino acid, carbohydrate, lipids, membrane transport and nucleotides. To further analyze the correlation between the identified metabolites and T2DM, 17 metabolites were selected with FC>2.0, including gentisic acid, citraconic acid, succinic acid, 2-hydroxybutanoic acid and 3-hydroxy-l-proline, the corresponding FC were respectively 5.44, 2.21, 2.10, 2.21 and -2.04.

CONCLUSION

Our results demonstrated that untargeted GC/TOFMS-based metabolic approach processed well performance to identify serum distinguishing metabolites of T2DM in Chinese adults, which may be as potential biomarkers in diagnose and treatment of diabetes. And the results also provided new insight into understand the underlying molecular mechanism.

Potential Application of 1H NMR for Routine Serum Lipidome Analysis -Evaluation of Effects of Bariatric Surgery

Routine laboratory lipid assays include simple measurements of total cholesterol, triacylglycerols and HDL. However, lipids are a large group of compounds involved in many metabolic pathways, and their alterations may have serious health consequences. In this study, we used 1H NMR to analyze lipids extracted from sera of 16 obese patients prior to and after bariatric surgeries. We observed a post-surgery decrease in serum concentrations of lipids from various groups. The hereby presented findings imply that 1H NMR is suitable for rapid, simple and non-invasive detection of lipids from 30 structural groups, among them triacylglycerols, phosphatidylcholine, phosphatidylethanolamine, sphingomyelin, total phospholipids, total, free and esterified cholesterol, total and unsaturated fatty acids. NMR-based analysis of serum lipids may contribute to a substantial increase in the number of routinely determined markers from this group; therefore, it may find application in clinical assessment of obese subjects prior to and after bariatric surgeries, as well as in the examination of patients with other metabolic diseases.

Comprehensive metabolomics identified lipid peroxidation as a prominent feature in human plasma of patients with coronary heart diseases

Coronary heart disease (CHD) is a complex human disease associated with inflammation and oxidative stress. The underlying mechanisms and diagnostic biomarkers for the different types of CHD remain poorly defined. Metabolomics has been increasingly recognized as an enabling technique with the potential to identify key metabolomic features in an attempt to understand the pathophysiology and differentiate different stages of CHD. We performed comprehensive metabolomic analysis in human plasma from 28 human subjects with stable angina (SA), myocardial infarction (MI), and healthy control (HC). Subsequent analysis demonstrated a uniquely altered metabolic profile in these CHD: a total of 18, 37 and 36 differential metabolites were identified to distinguish SA from HC, MI from SA, and MI from HC groups respectively. Among these metabolites, glycerophospholipid (GPL) metabolism emerged as the most significantly disturbed pathway. Next, we used a targeted metabolomic approach to systematically analyze GPL, oxidized phospholipid (oxPL), and downstream metabolites derived from polyunsaturated fatty acids (PUFAs), such as arachidonic acid and linoleic acid. Surprisingly, lipids associated with lipid peroxidation (LPO) pathways including oxidized PL and isoprostanes, isomers of prostaglandins, were significantly elevated in plasma of MI patients comparing to HC and SA, consistent with the notion that oxidative stress-induced LPO is a prominent feature in CHD. Our studies using the state-of-the-art metabolomics help to understand the underlying biological mechanisms involved in the pathogenesis of CHD; LPO metabolites may serve as potential biomarkers to differentiation MI from SA and HC.