Fasting serum lipid and dehydroepiandrosterone sulfate as important metabolites for detecting isolated postchallenge diabetes: serum metabolomics via ultra-high-performance LC-MS

Untargeted lipidomics analysis in women with morbid obesity and type 2 diabetes mellitus: A comprehensive study

There is a phenotype of obese individuals termed metabolically healthy obese that present a reduced cardiometabolic risk. This phenotype offers a valuable model for investigating the mechanisms connecting obesity and metabolic alterations such as Type 2 Diabetes Mellitus (T2DM). Previously, in an untargeted metabolomics analysis in a cohort of morbidly obese women, we observed a different lipid metabolite pattern between metabolically healthy morbid obese individuals and those with associated T2DM. To validate these findings, we have performed a complementary study of lipidomics. In this study, we assessed a liquid chromatography coupled to a mass spectrometer untargeted lipidomic analysis on serum samples from 209 women, 73 normal-weight women (control group) and 136 morbid obese women. From those, 65 metabolically healthy morbid obese and 71 with associated T2DM. In this work, we find elevated levels of ceramides, sphingomyelins, diacyl and triacylglycerols, fatty acids, and phosphoethanolamines in morbid obese vs normal weight. Conversely, decreased levels of acylcarnitines, bile acids, lyso-phosphatidylcholines, phosphatidylcholines (PC), phosphatidylinositols, and phosphoethanolamine PE (O-38:4) were noted. Furthermore, comparing morbid obese women with T2DM vs metabolically healthy MO, a distinct lipid profile emerged, featuring increased levels of metabolites: deoxycholic acid, diacylglycerol DG (36:2), triacylglycerols, phosphatidylcholines, phosphoethanolamines, phosphatidylinositols, and lyso-phosphatidylinositol LPI (16:0). To conclude, analysing both comparatives, we observed decreased levels of deoxycholic acid, PC (34:3), and PE (O-38:4) in morbid obese women vs normal-weight. Conversely, we found elevated levels of these lipids in morbid obese women with T2DM vs metabolically healthy MO. These profiles of metabolites could be explored for the research as potential markers of metabolic risk of T2DM in morbid obese women.

Sex-specific association of serum dehydroepiandrosterone and its sulfate levels with osteoporosis in type 2 diabetes

INTRODUCTION

This study is to investigate the relation between serum dehydroepiandrosterone (DHEA) and its sulfate (DHEAS) levels and the risk of osteoporosis in patients with T2DM.

MATERIALS AND METHODS

This cross-sectional study involved 938 hospitalized patients with T2DM. Linear regression models were used to explore the relationship between DHEA and DHEAS and the BMD at different skeletal sites. Multinominal logistic regression models and the restricted cubic spline (RCS) were used to evaluate the associations of DHEA and DHEAS with the risks of osteopenia and/or osteoporosis.

RESULTS

In postmenopausal women with T2DM, after adjustment for confounders including testosterone and estradiol, DHEA showed a significant positive correlation with lumbar spine BMD (P = 0.013). Moreover, DHEAS exhibited significant positive correlations with BMD at three skeletal sites: including femoral neck, total hip, and lumbar spine (all P < 0.05). Low DHEA and DHEAS levels were associated with increased risk of osteopenia and/or osteoporosis (all P < 0.05) and the risk of osteoporosis gradually decreased with increasing DHEAS levels (P overall = 0.018, P-nonlinear = 0.559). However, DHEA and DHEAS levels in men over the age of 50 with T2DM were not associated with any of above outcomes.

CONCLUSION

In patients with T2DM, independent of testosterone and estradiol, higher DHEA and DHEAS levels are associated with higher BMD and lower risk of osteopenia/osteoporosis in postmenopausal women but not men over the age of 50.

LC/MS-Based Untargeted Metabolomics Analysis in Women with Morbid Obesity and Associated Type 2 Diabetes Mellitus

Obesity is a chronic and complex disease, with an increasing incidence worldwide that is associated with metabolic disorders such as type 2 diabetes mellitus (T2DM). Thus, it is important to determine the differences between metabolically healthy obese individuals and those with metabolic disorders. The aim of this study was to perform an untargeted metabolomics assay in women with morbid obesity (MO) compared to a normal weight group, and to differentiate the metabolome of these women with MO who present with T2DM. We carried out a liquid chromatography-mass spectrometry-based untargeted metabolomics assay using serum samples of 209 Caucasian women: 73 with normal weight and 136 with MO, of which 71 had T2DM. First, we found increased levels of choline and acylglycerols and lower levels of bile acids, steroids, ceramides, glycosphingolipids, lysophosphatidylcholines, and lysophosphatidylethanolamines in MO women than in the control group. Then, in MO women with T2DM, we found increased levels of glutamate, propionyl-carnitine, bile acids, ceramides, lysophosphatidylcholine 14:0, phosphatidylinositols and phosphoethanolamines, and lower levels of Phe-Ile/Leu. Thus, we found metabolites with opposite trends of concentration in the two metabolomic analyses. These metabolites could be considered possible new factors of study in the pathogenesis of MO and associated T2DM in women.

Pathophysiology of type 2 diabetes and the impact of altered metabolic interorgan crosstalk

Diabetes is a complex and multifactorial disease that affects millions of people worldwide, reducing the quality of life significantly, and results in grave consequences for our health care system. In type 2 diabetes (T2D), the lack of β-cell compensatory mechanisms overcoming peripherally developed insulin resistance is a paramount factor leading to disturbed blood glucose levels and lipid metabolism. Impaired β-cell functions and insulin resistance have been studied extensively resulting in a good understanding of these pathways but much less is known about interorgan crosstalk, which we define as signaling between tissues by secreted factors. Besides hormones and organokines, dysregulated blood glucose and long-lasting hyperglycemia in T2D is associated with changes in metabolism with metabolites from different tissues contributing to the development of this disease. Recent data suggest that metabolites, such as lipids including free fatty acids and amino acids, play important roles in the interorgan crosstalk during the development of T2D. In general, metabolic remodeling affects physiological homeostasis and impacts the development of T2D. Hence, we highlight the importance of metabolic interorgan crosstalk in this review to gain enhanced knowledge of the pathophysiology of T2D, which may lead to new therapeutic approaches to treat this disease.

Fatty acids of type 2 diabetic serum decrease the stemness properties of human adipose-derived mesenchymal stem cells

In type 2 diabetes, dyslipidemia and increased serum free fatty acids (FFAs) exacerbate the development of the disease through a negative effect on insulin secretion. Adipose-derived mesenchymal stem cells (AdMSCs) play a key role in regenerative medicine, and these cells can potentially be applied as novel therapeutic resources in the treatment of diabetes. In this study, AdMSCs were treated with diabetic or nondiabetic serum FFAs isolated from women of menopausal age. Serum FFAs were analyzed using gas-liquid chromatography. The expression level of the stemness markers CD49e and CD90 and the Wnt signaling target genes Axin-2 and c-Myc were evaluated using real-time PCR. The proliferation rate and colony formation were also assessed using a BrdU assay and crystal violet staining, respectively. The level of glutathione was assessed using cell fluorescence staining. Compared to nondiabetic serum, diabetic serum contained a higher percentage of oleate (1.5-fold, p < 0.01). In comparison with nondiabetic FFAs, diabetic FFAs demonstrated decreasing effects on the expression of CD90 (-51%, p < 0.001) and c-Myc (-48%, p < 0.05), and proliferation rate (-35%, p < 0.001), colony formation capacity (-50%, p < 0.01), and GSH levels (-62%, p < 0.05). The negative effect of the FFAs of diabetic serum on the stemness characteristics may impair the regenerative capabilities of AdMSCs.

The role for long-term use of dehydroepiandrosterone in adrenal insufficiency

PURPOSE OF REVIEW

Dehydroepiandrosterone (DHEA) is an androgen produced by the zona reticularis of the adrenal gland. Patients with adrenal insufficiency will have a deficiency of DHEA. Unlike glucocorticoid and mineralocorticoid replacement, DHEA supplementation is not considered essential for life and is therefore not routinely replaced in adrenal failure. DHEA deficiency is associated with morbidity, including adverse impacts on metabolic function, quality of life and sexuality in multiple studies. The role for replacement, however, remains unclear.

RECENT FINDINGS

The benefits of DHEA supplementation have been definitively demonstrated in a number of historical studies of patients with primary and secondary adrenal insufficiency. Beneficial impacts on quality of life, body composition, bone health and metabolic markers have been demonstrated. However, published data are inconsistent; controversies persist around the exact role of DHEA replacement and around which patient cohorts are most likely to benefit. There is also a paucity of recent randomized controlled trials in the medical literature to inform on optimal dose and duration of DHEA replacement in adrenal failure.

SUMMARY

Here, we review the evidence for DHEA supplementation in patients with adrenal insufficiency. We highlight knowledge gaps in the medical literature and areas that should be prioritized for future research endeavours.

Evaluation of Untargeted Metabolomic Strategy for the Discovery of Biomarker of Breast Cancer

Discovery of disease biomarker based on untargeted metabolomics is informative for pathological mechanism studies and facilitates disease early diagnosis. Numerous of metabolomic strategies emerge due to different sample properties or experimental purposes, thus, methodological evaluation before sample analysis is essential and necessary. In this study, sample preparation, data processing procedure and metabolite identification strategy were assessed aiming at the discovery of biomarker of breast cancer. First, metabolite extraction by different solvents, as well as the necessity of vacuum-dried and re-dissolution, was investigated. The extraction efficiency was assessed based on the number of eligible components (components with MS/MS data acquired), which was more reasonable for metabolite identification. In addition, a simplified data processing procedure was proposed involving the OPLS-DA, primary screening for eligible components, and secondary screening with constraints including VIP, fold change and p value. Such procedure ensured that only differential candidates were subjected to data interpretation, which greatly reduced the data volume for database search and improved analysis efficiency. Furthermore, metabolite identification and annotation confidence were enhanced by comprehensive consideration of mass and MS/MS errors, isotope similarity, fragmentation match, and biological source confirmation. On this basis, the optimized strategy was applied for the analysis of serum samples of breast cancer, according to which the discovery of differential metabolites highly encouraged the independent biomarkers/indicators used for disease diagnosis and chemotherapy evaluation clinically. Therefore, the optimized strategy simplified the process of differential metabolite exploration, which laid a foundation for biomarker discovery and studies of disease mechanism.

Metabonomic and transcriptomic analyses of Tripterygium glycosides tablet-induced hepatotoxicity in rats

We aimed to explore novel biomarkers involved in alterations of metabolism and gene expression related to the hepatotoxic effects of Tripterygium glycosides tablet (TGT) in rats. Rats were randomly divided into groups based on oral administration of TGTs for 6 weeks: control, low-dose (9.5 mg/kg), and high-dose (18.9 mg/kg). Serum samples and total liver RNA were subjected to metabonomic and transcriptomic analyses. Thirteen metabolites were significantly up-regulated by liver injury induced by Tripterygium glycosides. Five potential biomarkers were more sensitive than Alanine aminotransferase (ALT) for accurate and timely prediction of hepatic damage. The four metabolic pathways most obviously regulated by hepatotoxicity were D-glutamine and D-glutamate metabolism, alanine, aspartate and glutamate metabolism, ether lipid metabolism, and tryptophan metabolism. Transcriptomics revealed significant differences in 1792 mRNAs and 400 long non-coding (lnc) RNAs. Dysregulated lncRNAs in the TGT-induced hepatotoxicity group were associated with genes involved in amino acid metabolism using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis. Up-regulated expression of Ehhadh, Gpt, and Got1, and down-regulated expression of dopa decarboxylase (Ddc), Cyp1a2, Ido2, Aldh1b1, and asparagine synthetase (Asns) was validated by quantitative real-time PCR. This multiomics study has elucidated the relationship between amino metabolism and liver injury, revealing potential biomarkers.

Two untargeted metabolomics reveals yogurt-associated metabolic alterations in women with multiple metabolic disorders from a randomized controlled study

The beneficial role of yogurt on metabolic profile has been widely reported. Yet, few studies have intended to describe the integrated metabolic alterations in response to yogurt. Yogurt and milk (220 g/d) were given to 48 and 44 obese women with metabolic syndrome and nonalcoholic fatty liver disease for 24 weeks in a randomized controlled trial (registered at http://www.chictr.org.cn as ChiCTR-IPR-15006801). Fasting serum samples were collected before and after intervention for global, untargeted metabolomics based on ¹H nuclear magnetic resonance (NMR) and ultra-high-performance liquid chromatography coupled with electrospray ionization time-of-flight mass spectrometry (UPLC-Q-TOF-MS) (in positive and negative ion modes). Multivariable statistical analysis and pathway analysis were conducted. In both ¹H NMR and UPLC-Q-TOF-MS metabolomics, no clustering was observed between the two groups at baseline. While, a clear clustering was shown after intervention, and the yogurt group had significantly different metabolic status from the milk. The metabolites that contributed mostly to class separation were identified, and involved into pathway analysis. Pathways on amino acids metabolism, fatty acid oxidation, cholesterol catabolism and choline metabolism significantly changed after yogurt intervention. The study revealed the integrated metabolic alterations in response to yogurt via two metabolomics approaches, suggesting the potential mechanisms of yogurt against metabolic disorders. TRIAL REGISTRATION: Chinese Clinical Trial Registry, ChiCTR-IPR-15006801. Registered 20 July 2015, http://www.chictr.org.cn/ ChiCTR-IPR-15006801. SIGNIFICANCE: Both review from prospective studies and our randomized clinical trial showed the protective role of yogurt against multiple metabolic disorders. However, they were focus on targeted glucose, lipid, and other metabolic indicators, which were only part of human metabolism, failing to show an integrated metabolic feature on yogurt. Therefore, two global, untargeted metabolomics were applied in our current randomized clinical trial, trying to uncover the significant metabolic alterations characterizing the effects of yogurt on obese women with multiple metabolic disorders, and to explore the potential biological mechanisms of yogurt. The finding will shed light on a more comprehensive picture of how yogurt affects host metabolism, and provide theoretical foundation for dietary prevention of chronic diseases.

UHPLC-MS-Based Serum and Urine Metabolomics Reveals the Anti-Diabetic Mechanism of Ginsenoside Re in Type 2 Diabetic Rats

Panax ginseng was employed in the treatment of “Xiao-Ke” symptom, which nowadays known as diabetes mellitus, in traditional Chinese medicine for more than a thousand years. Ginsenoside Re was the major pharmacologic ingredient found abundantly in ginseng. However, the anti-diabetic of Ginsenoside Re and its underlying mechanism in metabolic level are still unclear. Serum and urine metabolomic method was carried out to investigate the anti-diabetic pharmacological effects and the potential mechanism of Ginsenoside Re on high-fat diet combined streptozotocin-induced type 2 diabetes mellitus (T2DM) rats based on ultra-high-performance liquid chromatography coupled with quadrupole exactive orbitrap mass spectrometry (UHPLC-Q-Exactive Orbitrap/MS). Serum and urine samples were collected from the control group (CON), T2DM group, metformin (MET) treatment group, and ginsenoside Re treatment group after intervention. The biochemical parameters of serum were firstly analyzed. The endogenous metabolites in serum and urine were detected by UHPLC-MS. The potential metabolites were screened by multivariate statistical analysis and identified by accurate mass measurement, MS/MS, and metabolite databases. The anti-diabetic-related metabolites were analyzed by KEGG metabolic pathway, and its potential mechanism was discussed. The treatment of ginsenoside Re significantly reduced the blood glucose and serum lipid level improved the oxidative stress caused by T2DM. Biochemical parameters (urea nitrogen, uric acid) showed that ginsenoside Re could improve renal function in T2DM rats. Respective 2 and 6 differential metabolites were found and identified in serum and urine of ginsenoside Re compared with T2DM group and enriched in KEGG pathway. Metabolic pathways analysis indicated that the differential metabolites related to T2DM were mainly involved in arachidonic acid metabolism, Vitamin B6, steroid hormone biosynthesis, and bile secretion metabolic pathways. This study verified the anti-diabetic and anti-oxidation effects of ginsenoside Re, elaborated that ginsenoside Re has a good regulation of the metabolic disorder in T2DM rats, which could promote insulin secretion, stimulated cannabinoid type 1 receptor (CB₁), and CaMKK β to activate AMPK signaling pathway, inhibited insulin resistance, and improved blood glucose uptake and diabetic nephropathy, so as to play the role of anti-diabetic.

Metabolomic analysis reveals potential biomarkers and serum metabolomic profiling in spontaneous intracerebral hemorrhage patients using UPLC/quadrupole time-of-flight MS

Spontaneous intracerebral hemorrhage (ICH) accounts for 10-20% of all strokes and contributes to higher mortalities and severe disabilities. The aims of this study were, therefore, to characterize novel biomarkers, metabolic disruptions, and mechanisms involving ICH. A total 30 ICH patients and 30 controls were enrolled in the study, and their clinical characteristics were analyzed. Nontargeted metabolomic analysis was conducted using ultra-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry (UPLC/Q-TOF). Multivariate statistical analysis and receiver operating characteristic curve analysis were used for screening and evaluating the predictive ability of biomarkers. ICH patients showed significantly higher systolic blood pressure, diastolic blood pressure, blood glucose levels, white blood cell counts, neutrophil count, percentage of neutrophils and globulin and a lower albumin/globin ratio when compared with controls. In sum, 11 important metabolites were identified, which were associated with disruption of fatty acid oxidation and sphingolipid and phospholipid metabolism, as well as increased inflammation, oxidative stress, and vascular pathologies. Further multiple logistic regression analyses of these metabolites showed that l-carnitine and phosphatidylcholine (20:3/22:6) have potential as biomarkers of ICH, and the area under the curve, sensitivity, specificity were 0.974, 90%, and 93%, respectively. These findings provide insights into the pathogenesis, early prevention, and diagnosis of ICH.

How Perturbated Metabolites in Diabetes Mellitus Affect the Pathogenesis of Hypertension?

The presence of hypertension (HTN) in type 2 diabetes mellitus (DM) is a common phenomenon in more than half of the diabetic patients. Since HTN constitutes a predictor of vascular complications and cardiovascular disease in type 2 DM patients, it is of significance to understand the molecular and cellular mechanisms of type 2 DM binding to HTN. This review attempts to understand the mechanism via the perspective of the metabolites. It reviewed the metabolic perturbations, the biological function of perturbated metabolites in two diseases, and the mechanism underlying metabolic perturbation that contributed to the connection of type 2 DM and HTN. DM-associated metabolic perturbations may be involved in the pathogenesis of HTN potentially in insulin, angiotensin II, sympathetic nervous system, and the energy reprogramming to address how perturbated metabolites in type 2 DM affect the pathogenesis of HTN. The recent integration of the metabolism field with microbiology and immunology may provide a wider perspective. Metabolism affects immune function and supports immune cell differentiation by the switch of energy. The diverse metabolites produced by bacteria modified the biological process in the inflammatory response of chronic metabolic diseases either. The rapidly evolving metabolomics has enabled to have a better understanding of the process of diseases, which is an important tool for providing some insight into the investigation of diseases mechanism. Metabolites served as direct modulators of biological processes were believed to assess the pathological mechanisms involved in diseases.

Metabolomics and metabolites in ischemic stroke

Stroke is a major reason for disability and the second highest cause of death in the world. When a patient is admitted to a hospital, it is necessary to identify the type of stroke, and the likelihood for development of a recurrent stroke, vascular dementia, and depression. These factors could be determined using different biomarkers. Metabolomics is a very promising strategy for identification of biomarkers. The advantage of metabolomics, in contrast to other analytical techniques, resides in providing low molecular weight metabolite profiles, rather than individual molecule profiles. Technically, this approach is based on mass spectrometry and nuclear magnetic resonance. Furthermore, variations in metabolite concentrations during brain ischemia could alter the principal neuronal functions. Different markers associated with ischemic stroke in the brain have been identified including those contributing to risk, acute onset, and severity of this pathology. In the brain, experimental studies using the ischemia/reperfusion model (IRI) have shown an impaired energy and amino acid metabolism and confirmed their principal roles. Literature data provide a good basis for identifying markers of ischemic stroke and hemorrhagic stroke and understanding metabolic mechanisms of these diseases. This opens an avenue for the successful use of identified markers along with metabolomics technologies to develop fast and reliable diagnostic tools for ischemic and hemorrhagic stroke.

Serum Metabolites Responding in a Dose-Dependent Manner to the Intake of a High-Fat Meal in Normal Weight Healthy Men Are Associated with Obesity

Although the composition of the human blood metabolome is influenced both by the health status of the organism and its dietary behavior, the interaction between these two factors has been poorly characterized. This study makes use of a previously published randomized controlled crossover acute intervention to investigate whether the blood metabolome of 15 healthy normal weight (NW) and 17 obese (OB) men having ingested three doses (500, 1000, 1500 kcal) of a high-fat (HF) meal can be used to identify metabolites differentiating these two groups. Among the 1024 features showing a postprandial response, measured between 0 h and 6 h, in the NW group, 135 were dose-dependent. Among these 135 features, 52 had fasting values that were significantly different between NW and OB men, and, strikingly, they were all significantly higher in OB men. A subset of the 52 features was identified as amino acids (e.g., branched-chain amino acids) and amino acid derivatives. As the fasting concentration of most of these metabolites has already been associated with metabolic dysfunction, we propose that challenging normal weight healthy subjects with increasing caloric doses of test meals might allow for the identification of new fasting markers associated with obesity.

Serum untargeted metabolomics delineates the metabolic status in different subtypes of non-alcoholic fatty liver disease

AIMS

The aim of this study was to identify novel serum metabolites associated with non-alcoholic fatty liver disease (NAFLD), and to explore the metabolic discrepancies between Lean-NAFLD and Obese-NAFLD.

METHODS

Serum samples from patients with NAFLD (n = 161) and healthy participants (n = 149) were collected, and metabolites were analyzed with UPLC-Q-TOF MS/MS. Subgroup analyses were performed to explore the metabolic differences among Lean-NAFLD, Obese-NAFLD and healthy controls RESULTS: A total of 24 differentially present metabolites were found between patients with NAFLD and healthy controls. Marked metabolic pathway differences were observed among the NAFLD subtypes, including in fatty acid and amino acid metabolism. Ultimately, five metabolites (prasterone, indoxylsulfuric acid, sebacic acid, arachidonic acid and pregnenolone sulfate) were used to establish a diagnostic model to distinguish patients with NAFLD regardless of Lean- or Obese-NAFLD type.

CONCLUSIONS

This study suggested that significant metabolic differences existed among subtypes of NAFLD, and our model might be useful to distinguish patients with NAFLD. These findings may lay a foundation for the detection and treatment of NAFLD subtypes.

Integration of metabolomics and proteomics to highlight altered neural development related pathways in the adult offspring after maternal folic acid supplement

BACKGROUND & AIMS

Maternal folic acid (FA) supplement (FolS) programs the early development of an offspring. The onset of complex diseases at a later stage of life has been evidently linked with maternal FA ingestion. However, little is known regarding the underlying molecule fingerprints of the offspring. Here, we analyze the influence of maternal FolS on the metabolism of the adult offspring rats using the integrated metabolomics-proteomics.

METHODS

Twenty pregnant female rats were randomly assigned to a FA supplement (FolS group) or control group which were fed AIN93G diet with 2 or 5 mg/kg FA, respectively. The blood samples from the offspring at 0, 3 and 7 weeks after birth were collected. The brain samples were obtained from the offspring at 7 weeks after birth. Serum and brain metabolite profiles were performed by UPLC-MS/MS and the brain proteomics analysis was obtained using iTRAQ-based quantitative proteomics.

RESULTS

The metabolic change of the offspring for the maternal FA supplement is characterized by the phospholipids, fatty acid and amino acids, which are involved in linoleic acid, docosahexaenoic acid, glycerophosphocholine, lysophosphatidylcholine, tryptophan, glycine, arachidonic acid, γ-aminobutyric acid, and so on. Using iTRAQ-based quantitative proteomics analysis, 51 differential proteins in the brain are identified, which provides valuable insight into the underlying mechanisms of the offspring after the maternal FolS. These results demonstrate neural development related metabolites and proteins, such as docosahexaenoic acid, glycine, tryptophan, γ-aminobutyric acid, dopaminergic synapse related proteins including G protein, PPP1R1B and CAMK2G, are significantly altered, which suggests that the active neural conduction occurs in the offspring after maternal FA supplement. The behavioral testing demonstrates that the high level of memory is observed in rats with FA supplement.

CONCLUSIONS

We conceive that the alterations of metabolites and protein in the offspring are associated with the maternal FA supplement and these alterations are involved in the neural development, although such animal data are limited in their ability to mimic metabolic outcomes in humans.

Comparison of the Metabolic Profiles in the Plasma and Urine Samples Between Autistic and Typically Developing Boys: A Preliminary Study

Background: Autism spectrum disorder (ASD) is defined as a pervasive developmental disorder which is caused by genetic and environmental risk factors. Besides the core behavioral symptoms, accumulated results indicate children with ASD also share some metabolic abnormalities. Objectives: To analyze the comprehensive metabolic profiles in both of the first-morning urine and plasma samples collected from the same cohort of autistic boys. Methods: In this study, 30 autistic boys and 30 tightly matched healthy control (HC) boys (age range: 2.4~6.7 years) were recruited. First-morning urine and plasma samples were collected and the liquid chromatography-mass spectrometry (LC-MS) was applied to obtain the untargeted metabolic profiles. The acquired data were processed by multivariate analysis and the screened metabolites were grouped by metabolic pathway. Results: Different discriminating metabolites were found in plasma and urine samples. Notably, taurine and catechol levels were decreased in urine but increased in plasma in the same cohort of ASD children. Enriched pathway analysis revealed that perturbations in taurine and hypotaurine metabolism, phenylalanine metabolism, and arginine and proline metabolism could be found in both of the plasma and urine samples. Conclusion: These preliminary results suggest that a series of common metabolic perturbations exist in children with ASD, and confirmed the importance to have a comprehensive analysis of the metabolites in different biological samples to reveal the full picture of the complex metabolic patterns associated with ASD. Further targeted analyses are needed to validate these results in a larger cohort.

Serum biomarkers of the calcium-deficient rats identified by metabolomics based on UPLC/Q-TOF MS/MS

BACKGROUND

We previously identified the urinary biomarkers to diagnose calcium deficiency and nutritional rickets by ultra-performance liquid chromatography/quadrupole time-of-flight tandem mass spectrometry (UPLC/Q-TOF MS/MS). To find biomarkers of calcium deficiency and further confirm these biomarkers in serum, we performed serum metabolomics analysis of calcium-deficient rats.

METHODS

A calcium-deficient rat model was established with a low-calcium diet for 12 weeks. Serum metabolomics based UPLC/Q-TOF MS/MS and multivariate statistical analysis was performed to identify the alterations in metabolites associated with calcium deficiency in rats.

RESULTS

Bone mineral density, serum parathyroid hormone and alkaline phosphatase were significantly decreased in the low-calcium diet group (LCG) compared to the normal calcium diet group (NCG). Serum metabolic-profiling analysis could definitively distinguish between the LCG and NCG and identified 24 calcium-deficient biomarkers. Three metabolites (indoxyl sulfate, phosphate, and taurine) of the 24 biomarkers were found in our previous urinary metabolomics study of rats with a calcium deficiency and nutritional rickets. The areas under the curve (AUCs) of these three biomarkers were greater than 0.8, and the combination of any two biomarkers was higher than 0.95.

CONCLUSION

Dietary calcium deficiency induced the alterations of metabolites in the serum of rats, and the three identified biomarkers had relatively high diagnostic values for calcium deficiency in rats.

Derivatization-based quadruplex LC/ESI-MS/MS method for high throughput quantification of serum dehydroepiandrosterone sulfate

The quantification of the circulating dehydroepiandrosterone sulfate (DHEAS) might be of diagnostic help for several diseases. For the DHEAS quantification, LC/ESI-MS/MS has the advantage of a high specificity compared with immunoassay, whereas LC/ESI-MS/MS has room to improve the analysis throughput. One of the promising solutions to enhance the analysis throughput is sample-multiplexing in the same injection, which can reduce the total LC/ESI-MS/MS run time. In this study, a quadruplex LC/ESI-MS/MS method was developed to quantify DHEAS in four different serum samples in a single run. After the four samples were separately deproteinized and derivatized with one of four Girard reagents (Girard reagent T, P and their isotopologs), the resulting samples were mixed, then injected into the LC/ESI-MS/MS. The applicability and advantage of the developed method were evaluated based on the analysis of nine batches of serum samples from healthy subjects (total 36 samples). The limit of quantitation was 0.050 μg/ml, which was sensitive enough for clinical laboratory use. The method was precise (intra- and inter-assay RSDs ≤ 3.6%), accurate (94.4-108.1%) and robust for the matrix effects. The analysis time was also shortened by about 60% for 36 samples by the introduced method compared with the conventional method.

Metabolomics and correlation network analyses of core biomarkers in type 2 diabetes

The identification of metabolic pathways and the core metabolites provide novel molecular targets for the prevention and treatment of diseases. Diabetes is often accompanied with multiple metabolic disorders including hyperglycemia and dyslipidemia. Analysis of the variances of plasma metabolites is critical for identifying potential therapeutic targets for diabetes. In the current study, non-diabetic subjects with normal glucose tolerance and diabetics (age 40-60 years; n = 42 per group) were selected and plasma samples were analyzed by GC-MS for various metabolites profiling followed by network analysis. Our study identified 24 differential metabolites that were mainly enriched in protein synthesis, lipid and amino acid metabolism. Furthermore, we applied the correlation network analysis on these differential metabolites in fatty acid and amino acid metabolism and identified glycerol, alanine and serine as the hub metabolites in diabetic group. In addition, we measured the activities of enzymes in gluconeogenesis and amino acid metabolism and found significant higher activities of fructose 1,6-bisphosphatase, pyruvate carboxylase, lactate dehydrogenase, aspartate aminotransferase and alanine aminotransferase in diabetic patients. In contrast, the enzyme activities of glycolysis pathway (e.g., hexokinase, phosphofructokinase and pyruvate kinase) and TCA cycle (e.g., isocitrate dehydrogenase, succinate dehydrogenase, fumarate hydratase and malate dehydrogenase) were reduced in diabetes. Together, our studies showed that the linoleic acid and amino acid metabolism were the most affected metabolic pathways and glycerol, alanine and serine could play critical role in diabetes. The integration of network analysis and metabolic data could provide novel molecular targets or biomarkers for diabetes.

Altered Metabolome of Lipids and Amino Acids Species: A Source of Early Signature Biomarkers of T2DM

Diabetes mellitus, a disease of modern civilization, is considered the major mainstay of mortalities around the globe. A great number of biochemical changes have been proposed to occur at metabolic levels between perturbed glucose, amino acid, and lipid metabolism to finally diagnoe diabetes mellitus. This window period, which varies from person to person, provides us with a unique opportunity for early detection, delaying, deferral and even prevention of diabetes. The early detection of hyperglycemia and dyslipidemia is based upon the detection and identification of biomarkers originating from perturbed glucose, amino acid, and lipid metabolism. The emerging “OMICS” technologies, such as metabolomics coupled with statistical and bioinformatics tools, proved to be quite useful to study changes in physiological and biochemical processes at the metabolic level prior to an eventual diagnosis of DM. Approximately 300–400 such metabolites have been reported in the literature and are considered as predicting or risk factor-reporting metabolic biomarkers for this metabolic disorder. Most of these metabolites belong to major classes of lipids, amino acids and glucose. Therefore, this review represents a snapshot of these perturbed plasma/serum/urinary metabolic biomarkers showing a significant correlation with the future onset of diabetes and providing a foundation for novel early diagnosis and monitoring the progress of metabolic syndrome at early symptomatic stages. As most metabolites also find their origin from gut microflora, metabolism and composition of gut microflora also vary between healthy and diabetic persons, so we also summarize the early changes in the gut microbiome which can be used for the early diagnosis of diabetes.

Elevated metabolites of acetaminophen in cord blood of children with obesity

BACKGROUND

High-throughput metabolomics has been used cross-sectionally to evaluate differential metabolic profiles associated with human obesity.

OBJECTIVES

This study longitudinally assessed the cord blood metabolome to explore if metabolic signatures of obesity at age 3-5 are apparent at birth.

METHODS

In a nested case-control design, metabolomics analysis was performed on umbilical cord blood of 25 children who developed obesity by age 3-5 years, compared with 25 sex-matched non-obese children enrolled as part of an ongoing birth cohort. Logistic regression models were used to identify significant metabolites, adjusting for maternal pre-pregnancy obesity.

RESULTS

Children who had obesity by age 3-5 years had elevated levels of medium and long chain fatty acids including stearate, oleate and palmitate at birth. Children with obesity were also more likely to have elevated levels of acetaminophen metabolites at birth, specifically: 3-(N-acetyl-L-cystein-S-yl) acetaminophen, 2-hydroxyacetaminophen sulfate, 2-methoxyacetaminophen glucuronide and p-acetamidophenyl glucuronide.

CONCLUSION

Although the observed increases in lipids are consistent with previous metabolomic studies of obesity, this study is the first to report associations between acetaminophen metabolites and obesity in children; however, we lack mechanistic insights for this link. Larger human studies with longer follow-up and laboratory-controlled animal experiments are needed to clarify associations.

Fasting serum α‑hydroxybutyrate and pyroglutamic acid as important metabolites for detecting isolated post-challenge diabetes based on organic acid profiles

The aim of this study was to develop a method to detect serum organic acid profiles in patients with isolated post-challenge diabetes (IPD) and to compare the metabolites between IPD patients, type 2 diabetes mellitus (T2DM) and healthy controls. We developed a gas chromatography-mass spectrometry method to detect serum organic acids and validated it using serum from 40 patients with IPD, 47 with newly diagnosed T2DM, and 48 healthy controls. We then analyzed the organic acid profiles by multivariate analysis to identify potential metabolites. This method allowed the fast and accurate measurement of 27 organic acids in serum. Serum organic acid profiles differed significantly among IPD patients, T2DM patients, and healthy controls. IPD samples had significantly higher concentrations of α‑hydroxybutyrate and β‑hydroxybutyrate (P < 0.05) and lower pyroglutamic acid concentration (P < 0.05) compared with the healthy controls, and the area under the curve for the combination of α‑hydroxybutyrate and pyroglutamic acid was 0.863 for the IPD group. These results provide useful information regarding the changes in organic acid metabolism associated with IPD. Measurement of these metabolites in fasting serum from IPD patients may provide useful diagnostic and/or prognostic biomarkers, as well as helpful markers for the therapeutic monitoring of IPD patients.

Sex and age discrepancy of HbA1c and fetal hemoglobin determined by HPLC in a large Chinese Han population

BACKGROUND

It is accepted that HbA1c is an effective indicator to evaluate glycemic control. Fetal hemoglobin (HbF) is seldom measured because traditional detection is inconvenient. In this regard, there may be an advantage in using HPLC autoanalysis of HbA1c as a surrogate method for HbF detection. The aim of the present study was to explore the distribution of HbA1c and HbF in a large Chinese Han population.

METHODS

In all, 70 553 blood samples were collected between January 2012 and June 2016. Study subjects were inpatients undergoing routine medical care and were divided into four groups based on age: Group A, 20-39 years; Group B, 40-59 years; Group C, 60-79 years; and Group D, ≥80 years. Blood HbA1c and HbF concentrations were measured by HPLC using a Tosho Bioscience (Tokyo, Japan) G8 analyzer.

RESULTS

There was a positive association between HbA1c and age, and a negative association between HbF and age. The concentration range of HbF was narrow and HbF concentrations were significantly higher in females than males, regardless of age (median 0.7% vs 0.6%, respectively; P < 0.0001). There was a low degree of correlation between HbF and HbA1c (r = 0.181, P < 0.0001). Although median HbA1c levels were higher in male than female subjects aged 20-59 years (5.5% vs 5.4%, respectively, in Group A; 5.9% vs 5.8%, respectively in Group B), in the 60-79 years group, HbA1c levels were lower in males than females (6.1% vs 6.2%, respectively; P < 0.0001).

CONCLUSIONS

The data suggest that sex and age should be considered in clinical interpretation of HbA1c.

A window into extreme longevity; the circulating metabolomic signature of the naked mole-rat, a mammal that shows negligible senescence

Mouse-sized naked mole-rats (Heterocephalus glaber), unlike other mammals, do not conform to Gompertzian laws of age-related mortality; adults show no age-related change in mortality risk. Moreover, we observe negligible hallmarks of aging with well-maintained physiological and molecular functions, commonly altered with age in other species. We questioned whether naked mole-rats, living an order of magnitude longer than laboratory mice, exhibit different plasma metabolite profiles, which could then highlight novel mechanisms or targets involved in disease and longevity. Using a comprehensive, unbiased metabolomics screen, we observe striking inter-species differences in amino acid, peptide, and lipid metabolites. Low circulating levels of specific amino acids, particularly those linked to the methionine pathway, resemble those observed during the fasting period at late torpor in hibernating ground squirrels and those seen in longer-lived methionine-restricted rats. These data also concur with metabolome reports on long-lived mutant mice, including the Ames dwarf mice and calorically restricted mice, as well as fruit flies, and even show similarities to circulating metabolite differences observed in young human adults when compared to older humans. During evolution, some of these beneficial nutrient/stress response pathways may have been positively selected in the naked mole-rat. These observations suggest that interventions that modify the aging metabolomic profile to a more youthful one may enable people to lead healthier and longer lives.

Serum Lipids in Association With Type 2 Diabetes Risk and Prevalence in a Chinese Population

CONTEXT

We previously reported an association between lysophosphatidylinositol (LPI) (16:1) and risk for type 2 diabetes in a Chinese population using an untargeted analysis.

OBJECTIVE

To examine the overall associations of LPIs and their related metabolites, such as nonesterified fatty acids (NEFAs) and acylcarnitines, with incident and prevalent type 2 diabetes using a targeted approach.

DESIGN AND SETTING

A case-control study was nested within the Singapore Chinese Health Study. Cases and controls were individually matched by age, sex, and date of blood collection. We used both liquid and gas chromatography tandem mass spectrometry to measure serum metabolite levels at baseline, including 8 LPIs, 19 NEFAs, and 34 acylcarnitines. Conditional logistic regression models were used to estimate the associations between metabolites and diabetes risk.

PARTICIPANTS

Participants included 160 incident and 144 prevalent cases with type 2 diabetes and 304 controls.

MAIN OUTCOME MEASURE

Incident and prevalent type 2 diabetes.

RESULTS

On the basis of a false discovery rate <0.1, we identified 37 metabolites associated with prevalent type 2 diabetes, including 7 LPIs, 18 NEFAs, and 12 acylcarnitines, and 11 metabolites associated with incident type 2 diabetes, including 2 LPIs and 9 NEFAs. Two metabolites, LPI (16:1) and dihomo-γ-linolenic acid, showed independent associations with incident type 2 diabetes and significantly enhanced the risk prediction.

CONCLUSIONS

We found several LPIs and NEFAs that were associated with risk for type 2 diabetes and may improve our understanding of the pathogenesis. The findings suggest that lipid profiles could aid in diabetes risk assessment in Chinese populations.

Potential serum biomarkers and metabonomic profiling of serum in ischemic stroke patients using UPLC/Q-TOF MS/MS

Background

Stroke still has a high incidence with a tremendous public health burden and it is a leading cause of mortality and disability. However, biomarkers for early diagnosis are absent and the metabolic alterations associated with ischemic stroke are not clearly understood. The objectives of this case-control study are to identify serum biomarkers and explore the metabolic alterations of ischemic stroke.

Methods

Metabonomic analysis was performed using ultra-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry and multivariate statistical analysis was employed to study 60 patients with or without ischemic stroke (30 cases and 30 controls).

Results

Serum metabolic profiling identified a series of 12 metabolites with significant alterations, and the related metabolic pathways involved glycerophospholipid, sphingolipid, phospholipid, fat acid, acylcarnitine, heme, and purine metabolism. Subsequently, multiple logistic regression analyses of these metabolites showed uric acid, sphinganine and adrenoyl ethanolamide were potential biomarkers of ischemic stroke with an area under the receiver operating characteristic curve of 0.941.

Conclusions

These findings provide insights into the early diagnosis and potential pathophysiology of ischemic stroke.

LC-MS-based metabolomics revealed SLC25A22 as an essential regulator of aspartate-derived amino acids and polyamines in KRAS-mutant colorectal cancer

SLC25A22, which encodes the mitochondrial glutamate transporter, is overexpressed in colorectal cancer (CRC) and is essential for the proliferation of CRC cells harboring KRAS mutations. However, the role of SLC25A22 on metabolic regulation in KRAS-mutant CRC cells has not been comprehensively characterized. We performed non-targeted metabolomics, targeted metabolomics and isotope kinetic analysis of KRAS-mutant DLD1 cells with or without SLC25A22 knockdown using ultra-high-performance liquid chromatography (UHPLC) coupled to Orbitrap mass spectrometry (MS) or tandem MS (MS/MS). Global metabolomics analysis identified 35 altered metabolites, which were attributed to alanine, aspartate and glutamate metabolism, urea cycle and polyamine metabolism. Targeted metabolomics including 24 metabolites revealed that most tricarboxylic acid (TCA) cycle intermediates, aspartate-derived asparagine, alanine and ornithine-derived polyamines were strongly down-regulated in SLC25A22 knockdown cells. Moreover, targeted kinetic isotope analysis showed that most of the ¹³C-labeled ornithine-derived polyamines were significantly decreased in SLC25A22 knockdown cells and culture medium. Exogenous addition of polyamines could significantly promote cell proliferation in DLD1 cells, highlighting their potential role as oncogenic metabolites that function downstream of SLC25A22-mediated glutamine metabolism. Collectively, SLC25A22 acts as an essential metabolic regulator during CRC progression as it promotes the synthesis of aspartate-derived amino acids and polyamines in KRAS mutant CRC cells.

A 1H-NMR based metabolomics study of the intervention effect of mangiferin on hyperlipidemia hamsters induced by a high-fat diet

It has been demonstrated that mangiferin can ameliorate hypertriglyceridemia by modulating the expression levels of genes involved in lipid metabolism in animal experiments, but its effects on the serum metabolic fingerprinting of hyperlipidemia animal models have not been reported. Thus, a NMR-based metabolomics approach was conducted to explore the effects of mangiferin on hyperlipidemia hamsters and to gain a better understanding of the involved metabolic pathways. Hamsters fed with a high-fat diet were orally administered with mangiferin 150 mg per kg BW once a day for 8 weeks. Serum samples were analysed by 1H NMR, and multivariate statistical analysis was applied to the data to identify potential biomarkers. In total, 20 discriminating metabolites were identified. It turned out that mangiferin administration can partly reverse the metabolism disorders induced by a high-fat diet and exerted a good anti-hypertriglyceridemia effect. Mangiferin ameliorated hyperlipidemia by intervening in some major metabolic pathways, involving glycolysis, the TCA cycle, synthesis of ketone bodies, and BCAAs as well as choline and lipid metabolism. These findings provided new essential information on the effects of mangiferin and demonstrated the great potential of this nutrimetabolomics approach.

Effects of Histidine Supplementation on Global Serum and Urine 1H NMR-based Metabolomics and Serum Amino Acid Profiles in Obese Women from a Randomized Controlled Study

The aim of current study was to investigate the metabolic changes associated with histidine supplementation in serum and urine metabolic signatures and serum amino acid (AA) profiles. Serum and urine 1H NMR-based metabolomics and serum AA profiles were employed in 32 and 37 obese women with metabolic syndrome (MetS) intervened with placebo or histidine for 12 weeks. Multivariable statistical analysis were conducted to define characteristic metabolites. In serum 1H NMR metabolic profiles, increases in histidine, glutamine, aspartate, glycine, choline, and trimethylamine-N-oxide (TMAO) were observed; meanwhile, decreases in cholesterol, triglycerides, fatty acids and unsaturated lipids, acetone, and α/β-glucose were exhibited after histidine supplement. In urine 1H NMR metabolic profiles, citrate, creatinine/creatine, methylguanidine, and betaine + TMAO were higher, while hippurate was lower in histidine supplement group. In serum AA profiles, 10 AAs changed after histidine supplementation, including increased histidine, glycine, alanine, lysine, asparagine, and tyrosine and decreased leucine, isoleucine, ornithine, and citrulline. The study showed a systemic metabolic response in serum and urine metabolomics and AA profiles to histidine supplementation, showing significantly changed metabolism in AAs, lipid, and glucose in obese women with MetS.

Metabolic signatures and risk of type 2 diabetes in a Chinese population: an untargeted metabolomics study using both LC-MS and GC-MS

AIMS/HYPOTHESIS

Metabolomics has provided new insight into diabetes risk assessment. In this study we characterised the human serum metabolic profiles of participants in the Singapore Chinese Health Study cohort to identify metabolic signatures associated with an increased risk of type 2 diabetes.

METHODS

In this nested case-control study, baseline serum metabolite profiles were measured using LC-MS and GC-MS during a 6-year follow-up of 197 individuals with type 2 diabetes but without a history of cardiovascular disease or cancer before diabetes diagnosis, and 197 healthy controls matched by age, sex and date of blood collection.

RESULTS

A total of 51 differential metabolites were identified between cases and controls. Of these, 35 were significantly associated with diabetes risk in the multivariate analysis after false discovery rate adjustment, such as increased branched-chain amino acids (leucine, isoleucine and valine), non-esterified fatty acids (palmitic acid, stearic acid, oleic acid and linoleic acid) and lysophosphatidylinositol (LPI) species (16:1, 18:1, 18:2, 20:3, 20:4 and 22:6). A combination of six metabolites including proline, glycerol, aminomalonic acid, LPI (16:1), 3-carboxy-4-methyl-5-propyl-2-furanpropionic acid and urea showed the potential to predict type 2 diabetes in at-risk individuals with high baseline HbA1c levels (≥6.5% [47.5 mmol/mol]) with an AUC of 0.935. Combined lysophosphatidylglycerol (LPG) (12:0) and LPI (16:1) also showed the potential to predict type 2 diabetes in individuals with normal baseline HbA1c levels (<6.5% [47.5 mmol/mol]; AUC = 0.781).

CONCLUSIONS/INTERPRETATION

Our findings show that branched-chain amino acids and NEFA are potent predictors of diabetes development in Chinese adults. Our results also indicate the potential of lysophospholipids for predicting diabetes.

Random Survival Forest in practice: a method for modelling complex metabolomics data in time to event analysis

BACKGROUND

The application of metabolomics in prospective cohort studies is statistically challenging. Given the importance of appropriate statistical methods for selection of disease-associated metabolites in highly correlated complex data, we combined random survival forest (RSF) with an automated backward elimination procedure that addresses such issues.

METHODS

Our RSF approach was illustrated with data from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam study, with concentrations of 127 serum metabolites as exposure variables and time to development of type 2 diabetes mellitus (T2D) as outcome variable. Out of this data set, Cox regression with a stepwise selection method was recently published. Replication of methodical comparison (RSF and Cox regression) was conducted in two independent cohorts. Finally, the R-code for implementing the metabolite selection procedure into the RSF-syntax is provided.

RESULTS

The application of the RSF approach in EPIC-Potsdam resulted in the identification of 16 incident T2D-associated metabolites which slightly improved prediction of T2D when used in addition to traditional T2D risk factors and also when used together with classical biomarkers. The identified metabolites partly agreed with previous findings using Cox regression, though RSF selected a higher number of highly correlated metabolites.

CONCLUSIONS

The RSF method appeared to be a promising approach for identification of disease-associated variables in complex data with time to event as outcome. The demonstrated RSF approach provides comparable findings as the generally used Cox regression, but also addresses the problem of multicollinearity and is suitable for high-dimensional data.

Combined effects of sex hormone-binding globulin and sex hormones on risk of incident type 2 diabetes

BACKGROUND

The aim of the present study was to investigate the combined effects of sex hormone-binding globulin (SHBG) and sex hormones on the risk of type 2 diabetes (T2D).

METHODS

A nested case-control study of Chinese participants in the Environment, Inflammation and Metabolic Diseases Study (2008-13) was performed. Of the 3510 subjects free of diabetes, 145 men and 87 women developed diabetes over the 5-year follow-up. One age- and sex-matched control subject was selected for each case. Baseline concentrations of SHBG, estradiol, testosterone, and dehydroepiandrosterone sulfate (DHEA-S) were divided into tertiles and subjects were classified as having low, intermediate and high levels accordingly.

RESULTS

After multivariate adjustment, men with low SHBG levels had a fourfold greater risk of T2D than men with high SHBG levels. Conversely, men with high estradiol levels had a fourfold greater risk of T2D than men with low estradiol levels. Men with low SHBG + high estradiol had a 20-fold greater risk of T2D than men with high SHBG + low estradiol (odds ratio [OR] 20.23; 95% confidence interval [CI] 4.62-51.33). These risk associations in men were not observed for testosterone or DHEA-S, alone or in combination with SHBG. Compared with low SHBG, the risk of T2D decreased with increasing SHBG tertile (OR 0.92 [95% CI 0.21-4.53], 0.14 [95% CI 0.10-0.74]; Ptrend  = 0.043) after multivariate adjustment in women. Estradiol, testosterone, and DHEA-S levels showed no association with T2D in women.

CONCLUSION

Low SHBG in conjunction with high estradiol has an additive detrimental effect on the risk of T2D in men.

A Metabolomic Approach to Understanding the Metabolic Link between Obesity and Diabetes

Obesity and diabetes arise from an intricate interplay between both genetic and environmental factors. It is well recognized that obesity plays an important role in the development of insulin resistance and diabetes. Yet, the exact mechanism of the connection between obesity and diabetes is still not completely understood. Metabolomics is an analytical approach that aims to detect and quantify small metabolites. Recently, there has been an increased interest in the application of metabolomics to the identification of disease biomarkers, with a number of well-known biomarkers identified. Metabolomics is a potent approach to unravel the intricate relationships between metabolism, obesity and progression to diabetes and, at the same time, has potential as a clinical tool for risk evaluation and monitoring of disease. Moreover, metabolomics applications have revealed alterations in the levels of metabolites related to obesity-associated diabetes. This review focuses on the part that metabolomics has played in elucidating the roles of metabolites in the regulation of systemic metabolism relevant to obesity and diabetes. It also explains the possible metabolic relation and association between the two diseases. The metabolites with altered profiles in individual disorders and those that are specifically and similarly altered in both disorders are classified, categorized and summarized.

The Harbin Cohort Study on Diet, Nutrition and Chronic Non-communicable Diseases: study design and baseline characteristics

Diet and nutrition have been reported to be associated with many common chronic diseases and blood-based assessment would be vital to investigate the association and mechanism, however, blood-based prospective studies are limited. The Harbin Cohort Study on Diet, Nutrition and Chronic Non-communicable Diseases was set up in 2010. From 2010 to 2012, 9,734 participants completed the baseline survey, including demographic characteristics, dietary intake, lifestyles and physical condition, and anthropometrics. A re-survey on 490 randomly selected participants was done by using the same methods which were employed in the baseline survey. For all participants, the mean age was 50 years and 36% of them were men. Approximately 99.4 % of cohort members donated blood samples. The mean total energy intake was 2671.7 kcal/day in men and 2245.9 kcal/day in women, the mean body mass index was 25.7 kg/m² in men and 24.6 kg/m² in women, with 18.4% being obese (≥28 kg/m²), 12.7% being diabetic, and 29.5% being hypertensive. A good agreement was obtained for the physical measurements between the baseline survey and re-survey. The resources from the cohort and its fasting and postprandial blood samples collected both at baseline and in each follow-up will be valuable and powerful in investigating relationship between diet, nutrition and chronic diseases and discovering novel blood biomarkers and the metabolism of these biomarkers related to chronic diseases.

In vivo and in vitro evidences of dehydroepiandrosterone protective role on the cardiovascular system

CONTEXT

Dehydroepiandrosterone (DHEA) and its sulfate ester, Dehydroepiandrosterone Sulfate (DHEA-S) have been considered as putative anti-aging hormones for many years. Indeed, while DHEAS is the most abundant circulating hormone, its concentration is markedly decreased upon aging and early epidemiologic trials have revealed a strong inverse correlation between the hormone concentrations and the occurrence of several dysfunctions frequently encountered in the elderly. Naturally, hormonal supplementation has been rapidly suggested to prevent DHEA (S) deficiency and therefore, age-related development of these pathologies, using the same strategy as estrogen replacement therapy proposed in postmenopausal women.

EVIDENCE ACQUISITION

All references were searched using PubMed and the following strategy: our initial selection included all articles in English and we sorted them with the following keywords: "DHEA or DHEA-S" and "heart or vascular or endothelium or cardiovascular disease". The search was limited to neither the publication date nor specific journals. The final selection was made according to the relevance of the article content with the aims of the review. According to these criteria, fewer than 10% of the articles retrieved at the first step were discarded.

RESULTS

In this short review, we have focused on the cardiovascular action of DHEA. We started by analyzing evidences in favor of a strong inverse association between DHEA (S) levels and the cardiovascular risk as demonstrated in multiple observational epidemiologic studies for several decades. Then we discussed the different trials aimed at supplementing DHEA (S), both in animals and human, for preventing cardiovascular diseases and we analyzed the possible reasons for the discrepancy observed among the results of some studies. Finally, we presented putative molecular mechanisms of action for DHEA (S), demonstrated in vitro in different models of vascular and cardiac cells, highlighting the complexity of the involved signaling pathways.

CONCLUSIONS

The identification of the beneficial cardiovascular effects of DHEA (S) and a better understanding of the involved mechanisms should be helpful to develop new strategies or pharmacologic approaches for many lethal diseases in Western countries.

Rapid identification of erythrocyte phospholipids in Sprague-Dawley rats by ultra high performance liquid chromatography with electrospray ionization quadrupole time-of-flight tandem mass spectrometry

A rapid, sensitive, and reliable approach for analyzing five kinds of erythrocyte phospholipids in Sprague-Dawley rats was provided by ultra high performance liquid chromatography coupled with electrospray ionization quadrupole time-of-flight tandem mass spectrometry with MassLynx(TM) MassFragment. Improving conventional high performance liquid chromatography techniques, ultra high performance liquid chromatography integrated with quadrupole time-of-flight tandem mass spectrometry offers high sensitivity and increased analytical speed by using columns packed with sub-2 μm particles (1.7 μm), which allows a faster separation to be achieved. Through this method, 83 phospholipids were tentatively characterized based on their mass spectra and tandem mass spectra, as well as by matching the in-house formula database within a mass error of 5 ppm, including 40 phosphatidylcholines, 24 phosphatidyl ethanolamines, three phosphatidylinositols, six phosphatidylserines, and ten sphingomyelins. Our present results proved that the established method could be used to qualitatively analyze complex erythrocyte phospholipids in Sprague-Dawley rats and provide a useful data base for pharmacology and phospholipidomics to seek potential biomarkers of disease prediction.

Untargeted metabolic profiling identifies altered serum metabolites of type 2 diabetes mellitus in a prospective, nested case control study

BACKGROUND

Application of metabolite profiling could expand the etiological knowledge of type 2 diabetes mellitus (T2D). However, few prospective studies apply broad untargeted metabolite profiling to reveal the comprehensive metabolic alterations preceding the onset of T2D.

METHODS

We applied untargeted metabolite profiling in serum samples obtained from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort comprising 300 individuals who developed T2D after a median follow-up time of 6 years and 300 matched controls. For that purpose, we used ultraperformance LC-MS with a protocol specifically designed for large-scale metabolomics studies with regard to robustness and repeatability. After multivariate classification to select metabolites with the strongest contribution to disease classification, we applied multivariable-adjusted conditional logistic regression to assess the association of these metabolites with T2D.

RESULTS

Among several alterations in lipid metabolism, there was an inverse association with T2D for metabolites chemically annotated as lysophosphatidylcholine(dm16:0) and phosphatidylcholine(O-20:0/O-20:0). Hexose sugars were positively associated with T2D, whereas higher concentrations of a sugar alcohol and a deoxyhexose sugar reduced the odds of diabetes by approximately 60% and 70%, respectively. Furthermore, there was suggestive evidence for a positive association of the circulating purine nucleotide isopentenyladenosine-5'-monophosphate with incident T2D.

CONCLUSIONS

This study constitutes one of the largest metabolite profiling approaches of T2D biomarkers in a prospective study population. The findings might help generate new hypotheses about diabetes etiology and develop further targeted studies of a smaller number of potentially important metabolites.

Current state-of-the-art of nontargeted metabolomics based on liquid chromatography-mass spectrometry with special emphasis in clinical applications

Metabolomics, as a part of systems biology, has been widely applied in different fields of life science by studying the endogenous metabolites. The development and applications of liquid chromatography (LC) coupled with high resolution mass spectrometry (MS) greatly improve the achievable data quality in non-targeted metabolic profiling. However, there are still some emerging challenges to be covered in LC-MS based metabolomics. Here, recent approaches about sample collection and preparation, instrumental analysis, and data handling of LC-MS based metabolomics are summarized, especially in the analysis of clinical samples. Emphasis is put on the improvement of analytical techniques including the combination of different LC columns, isotope coded derivatization methods, pseudo-targeted LC-MS method, new data analysis algorithms and structural identification of important metabolites.

Biomarkers identified by urinary metabonomics for noninvasive diagnosis of nutritional rickets

Nutritional rickets is a worldwide public health problem; however, the current diagnostic methods retain shortcomings for accurate diagnosis of nutritional rickets. To identify urinary biomarkers associated with nutritional rickets and establish a noninvasive diagnosis method, urinary metabonomics analysis by ultra-performance liquid chromatography/quadrupole time-of-flight tandem mass spectrometry and multivariate statistical analysis were employed to investigate the metabolic alterations associated with nutritional rickets in 200 children with or without nutritional rickets. The pathophysiological changes and pathogenesis of nutritional rickets were illustrated by the identified biomarkers. By urinary metabolic profiling, 31 biomarkers of nutritional rickets were identified and five candidate biomarkers for clinical diagnosis were screened and identified by quantitative analysis and receiver operating curve analysis. Urinary levels of five candidate biomarkers were measured using mass spectrometry or commercial kits. In the validation step, the combination of phosphate and sebacic acid was able to give a noninvasive and accurate diagnostic with high sensitivity (94.0%) and specificity (71.2%). Furthermore, on the basis of the pathway analysis of biomarkers, our urinary metabonomics analysis gives new insight into the pathogenesis and pathophysiology of nutritional rickets.

UPLC-MS-based serum metabonomics for identifying acute liver injury biomarkers in Chinese miniature pigs

Metabonomics has emerged as an important technology for exploring the underlying mechanisms of diseases and screening for biomarkers. In this investigation, to comprehensively assess metabolite changes in D-galactosamine (GalN)-induced liver injury in Chinese miniature pigs and to increase our understanding of physiological changes in normal and pathological states, we used ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) to analyze metabolites and identify biomarkers in serum. Blood samples were collected both from 18 h after GalN treatment group and control group pigs. We performed multivariate analyses on the metabolite profiles to identify potential biomarkers of acute liver injury, which were then confirmed by tandem MS. Based on "variable of importance in the project" (VIP) values and S-plots, four groups of biomarkers were identified--namely conjugated bile acids, lysophosphatidylcholines (LPCs), phosphatidylcholines (PCs) and fatty acid amides (FAAs)--that were present at significantly different levels in the control and GalN-induced groups. LPCs, PCs, and FAAs showed marked decreases in the GalN-treated group, whereas conjugated bile acids in the treated group showed considerable increases. Taken together, our results suggested that obvious metabolic disturbances occur during acute liver injury, which provided novel insights into the molecular mechanism(s) of D-galactosamine (GalN)-induced liver injury, and will facilitate future research and management of liver injury.

Apolipoprotein Gene Polymorphisms (APOB, APOC111, APOE) in the Development of Coronary Heart Disease in Ethnic Groups of Kazakhstan

BACKGROUND

Previous Analysis of polymorphism of genes associated with the development of coronary heart disease (CHD) reveals that the frequency distribution of genotypes and alleles depends on the ethnic characteristics of the populations under study. Further impetus is derived from the well -established links between alcoholism (high prevalence in Kazakhstan region) and cardiovascular disorders.

OBJECTIVES

The purpose of this study was to examine a number of apolipoprotein gene polymorphisms and correlate these alleles with changes of lipid profile in CHD patients of Kazakh and Uyghur nationalities.

METHODS

Four-Hundred Forty Eight (448) males of Kazakh and Uyghur nationalities residing in Kazakhstan were evaluated and genotyped. The age range of these subjects was 30-55 years which included both afflicted and controls. Specifically, 161- Kazakhs suffered from myocardial infarction compared to 112 health controls; 80- Uyghurs suffered from CHD compared to 95 health controls. Blood lipid profiles were examined in the total cohort. Genotyping was performed by polymerase chain reaction (PCR) using oligonucleotide primers identifying; ApoB; ApoC111; and APOE gene polymorphisms.

RESULTS

Initial screening revealed a significant inter-ethnic difference on the frequency of alleles associated with both the ApoB and APOE genes. We found that the X1 ApoB gene polymorphism is overrepresented in healthy Kazakhs relative to Uyghurs [86.4% in Kazakhs vs. 69.4% in Uyghurs]. Moreover, we found that the E4APOE allele was also overrepresented in healthy Kazakhs relative to Uyghurs [16.8% in Kazakhs vs. 9.5% in Uyghurs]. There was a significant relationship of polymorphisms of APOE such as ApoB and ApoC 111 with the value of lipid indices in Kazakhs. Additionally, we found that the E4 allele of the APOE gene also correlated with the value of lipid indices in Kazakhs. Further evaluation showed that the X2 allele of the ApoB and the S2 allele of the ApoCIII gene significantly associated with the lipid indices of Uyghurs.

CONCLUSION

This systematic investigation confirms the association of various alleles of Apolipoprotein gene polymorphisms and contribution to aberrant lipid metabolism. Putatively at least in our population we are proposing that certain gene polymorphisms of Apolipoprotein genes such as ApoB; ApoC111; APOE ; X2 of ApoB; and S2 of ApoCIII differentially represented in either Kazakhs or Uyghurs are genetic markers of hypertriglyceridemia.

Metabolomic profiling of tumor-bearing mice

Metabolomics is one of the newcomers among the "omics" techniques, perhaps also constituting the most relevant for the study of pathophysiological conditions. Metabolomics may indeed yield not only disease-specific biomarkers but also profound insights into the etiology and progression of a variety of human disorders. Various metabolomic approaches are currently available to study oncogenesis and tumor progression in vivo, in murine tumor models. Many of these models rely on the xenograft of human cancer cells into immunocompromised mice. Understanding how the metabolism of these cells evolves in vivo is critical to evaluate the actual pertinence of xenograft models to human pathology. Here, we discuss various tumor xenograft models and methods for their metabolomic profiling to provide a short guide to investigators interested in this field of research.