Metabolomics-Based Prospective Studies and Prediction of Type 2 Diabetes Mellitus Risks

Simultaneous determination of free DL-amino acids in human hair with a novel DBD-M-Pro derivatization by UHPLC-HRMS: An application in diabetes patients

Human hair is a non-invasive biological sample that is easy to collect and store and can reflect long-term body health. However, the correlation between DL-amino acids and metabolic diseases in hair samples has not been studied. Therefore, we propose a novel UHPLC-HRMS method for analyzing seven free chiral amino acids (DL-Thr, DL-Glu, DL-Ala, DL-Val, DL-Pro, DL-Leu, and DL-Phe) simultaneously in hair samples by derivatization of chiral probe 4-(N,N-dmethylaminosulfonyl)-2,1,3-benzoxadiazole-trans-2-methyl-L-proline (DBD-M-Pro) labeled with targeted amino functional groups. Gradient elution was carried out using an ACQUITYTM BEH C18 (100×2.1 mm,1.7 μm) column with a mobile phase of 0.15 % formic acid (FA) in 10 mM ammonium acetate (CH3-COONH4) and 0.2 % FA in acetonitrile. The labelled DL-amino acid diastereoisomers could be completely separated, with a resolution (Rs) of 1.59-11.44. These amino acids show a strong linear correlation within the range of 3.1-99.2 pmol (R2 ≥ 0.9990). Intraday and interday precision was 1.87 %-14.87 %. The average recovery was 96.12 %-105.33 %. The limit of detection (LOD) ranged from 0.29 to 2.11 pmol. We then employed the method to determine the concentration of free chiral amino acids in hair samples from 30 healthy volunteers (HVs) and 30 diabetes patients (DPs). Male diabetes patients had significantly higher levels of L-Thr, L-Val, L-Leu (p < 0.05), and D-Ala (p < 0.01) in their hair samples than male healthy volunteers and female diabetes patients had significantly higher levels of D-Ala (p < 0.05) in their hair samples than female healthy volunteers. This is the first study to confirm the feasibility of using free DL-amino acids in human hair as potential biomarkers for diabetes.

Metabolic Disturbances in a Mouse Model of MPTP/Probenecid-Induced Parkinson's Disease: Evaluation Using Liquid Chromatography-Mass Spectrometry

Purpose

Parkinson's disease (PD) is a common neurodegenerative disease that severely affects patients' daily lives and places a significant burden on the global economy. There are currently no specific biomarkers for distinguishing between the different stages of PD.

Methods

We divided 78 mice into six equal groups, including five model PD groups (W1-W5; based on the PD stage induced by length of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine/propofol induction time) and a control group. Then, we used metabolomics technology to detect the serum small-molecule metabolites present in each group. Ultimately, we screened for potential biomarkers using the variable importance in the projection of the orthogonal partial least squares discriminant analysis and the coefficient value of LASSO ordinal logistic regression.

Results

We identified 12 potential biomarkers, including dehydroepiandrosterone sulfate, pipecolic acid, N-acetylleucine, 2-aminoadipic acid, L-tyrosine, uric acid, and 5-hydroxyindoleacetaldehyde. Pathway analysis revealed their involvement in amino acid metabolism, caffeine metabolism, steroid hormone biosynthesis, and purine metabolism. Additionally, the receiver operating characteristic curve indicated that a biomarker panel comprising the 12 biomarkers could differentiate between the different PD stages.

Conclusion

Different PD stages are characterized by different metabolites. The biomarkers identified in this study are helpful to understand the PD process.

Accumulation of branched-chain amino acids deteriorates the neuroinflammatory response of Müller cells in diabetic retinopathy via leucine/Sestrin2-mediated sensing of mTOR signaling

AIMS

This study aimed to investigate branched-chain amino acid (BCAA) catabolism in diabetic retinopathy (DR).

METHODS

Wild-type and db/db mice were fed BCAAs (5 or 10 mg/kg/day) for 12 weeks, and hyperglycemia-exposed Müller cells were treated with BCAAs (2 or 5 mmol/L) for 24 and 48 h. BCAA levels were measured using MS/MS. Western blotting was performed to detect proteins. Flow cytometry, oxygen consumption rate, and Cell Counting Kit-8 assays were used to evaluate Müller cell viability. Each experiment was conducted at least thrice.

RESULTS

BCAAs and branched-chain α-keto acids (BCKAs) were increased in the retina and systemic tissues of diabetic mice, and these changes were further enhanced to approximately 2-fold by extra BCAAs compared to wild-type group. In vitro, BCAAs and BCKAs were induced in hyperglycemic Müller cells, and augmented by BCAA supplementation. The aberrant BCAA catabolism was accompanied by mTORC1 activation and subsequently induced TNF-ɑ, VEGFA, GS, and GFAP in retinas and Müller cells under diabetic conditions. The cell apoptosis rate increased by approximately 50%, and mitochondrial respiration was inhibited by hyperglycemia and BCAA in Müller cells. Additionally, mTORC1 signaling was activated by leucine in Müller cells. Knockdown of Sestrin2 or LeuRS significantly abolished the leucine-induced mTORC1 phosphorylation and protected Müller cell viability under diabetic conditions.

CONCLUSIONS

We found that BCAA catabolism is hindered in DR through mTORC1 activation. Leucine plays a key role in inducing mTORC1 by sensing Sestrin2 in Müller cells. Targeting Sestrin2 may ameliorate the toxic effects of BCAA accumulation on Müller cells in DR.

Unveiling novel metabolic alterations in postmenopausal osteoporosis and type 2 diabetes mellitus through NMR-based metabolomics: A pioneering approach for identifying early diagnostic markers

BACKGROUND AND AIMS

Postmenopausal osteoporosis (PMO) and type 2 diabetes mellitus (T2DM) frequently coexist in postmenopausal women. The study aimed to explore metabolic variations linked to these circumstances and their simultaneous presence through proton nuclear magnetic resonance metabolomics (1H NMR).

MATERIALS AND METHODS

Serum samples from 80 postmenopausal women, including 20 PMO individuals, 20 T2DM, 20 T2DM + PMO, and 20 healthy postmenopausal women, were analyzed using 1H NMR spectroscopy.

RESULTS

Our study revealed significant metabolic profile differences among the four groups. Notably, the T2DM + PMO group showed elevated levels of alanine, pyruvate, glutamate, lactate, and aspartate, indicating their involvement in lipid metabolism, energy, and amino acids. Importantly, our multivariate statistical analysis identified a metabolite set that accurately distinguished the groups, suggesting its potential as an early diagnostic marker.

CONCLUSION

The 1H NMR metabolomics approach uncovered metabolic biomarkers intricately linked to postmenopausal osteoporosis (PMO), type 2 diabetes mellitus (T2DM), and their concurrent presence. Among these biomarkers, alanine emerged as a pivotal player, showing its significant role in the metabolic landscape associated with PMO and T2DM. These findings shed light on the pathophysiological mechanisms underlying these conditions and underscore alanine's potential as a diagnostic biomarker.

Aged garlic extract preserves beta-cell functioning via modulation of nuclear factor kappa-B (NF-κB)/Toll-like receptor (TLR)-4 and sarco endoplasmic reticulum calcium ATPase (SERCA)/Ca2+ in diabetes mellitus

BACKGROUND

Peripheral insulin resistance and compromised insulin secretion from pancreatic β-cells are significant factors and pathogenic hallmarks of diabetes mellitus (DM). NF-κβ/TLR-4 and SERCA/Ca2+ pathways have been identified as potential pathways regulating insulin synthesis by preserving pancreatic β-cell functioning. The current study aimed to evaluate the therapeutic effect of aged garlic extract (AGE) against DM in a streptozotocin (STZ)-induced rat model with particular emphasis on pancreatic β-cell functioning.

METHODS

AGE was characterized by gas chromatography-mass spectrometry (GC-MS), Fourier-transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM) to evaluate its physio-chemical characteristics followed by in-vitro anti-diabetic and antioxidant potential. This was followed by the induction of DM in laboratory animals for investigating the therapeutic action of AGE by evaluating the role of NF-κβ/TLR-4 and the SERCA/Ca2+ pathway. The parameters assessed in the present experimental setup encompassed antioxidant parameters, metabolic indicators, insulin concentration, intracellular calcium levels, apoptotic markers (CCK-8 and Caspase Glo-8), and protein expression (P-62 and APACHE-II).

RESULTS

AGE characterization by SEM, GC-MS, and X-ray diffraction (XRD) revealed the presence of phenylalanine, alliin, S-allylmercaptocysteine (SAMC), tryptophan, 1-methyl-1,2,3,4-tetrahydro-β-carboline-3-carboxylic acid as major bioactive constituents of AGE. Metabolic studies, including intraperitoneal glucose tolerance test (IPGTT), revealed significantly lower blood glucose levels in the AGE group compared to the disease control group. In contrast, the intraperitoneal insulin tolerance test (ITT) exhibited no significant difference in insulin sensitivity between the AGE supplementation group and the DM control group. Interestingly, AGE was found to have no significant effect on fasting glucose and serum insulin levels. In contrast, AGE supplementation was found to cause significant hypoglycaemia in postprandial blood glucose and insulin levels. Importantly, AGE causes restoration of intracellular Ca2+ levels by modulation of SERCA/Ca2 functioning and inhibition NF-κB/TLR-4 pathway. AGE was found to interact with and inhibit the DR-5/ caspase-8/3 apoptotic complex. Furthermore, microscopic studies revealed degeneration and apoptotic changes in pancreatic β-cells of the DM control group, while supplementation of AGE resulted in inhibition of apoptotic pathway and regeneration of pancreatic β-cells.

CONCLUSION

The current study suggests that AGE enhance glucose homeostasis by exerting their effects on pancreatic β-cells, without ameliorating peripheral sensitivity. Moreover, AGEs promote an increase in β-cell mass by mitigating the apoptosis of pancreatic β-cells. These findings suggest that AGE could aid in developing a viable alternative therapy for diabetes mellitus (DM).

Identification of potential serum biomarkers associated with HbA1c levels in Indian type 2 diabetic subjects using NMR-based metabolomics

BACKGROUND

The prevalence of type 2 diabetes mellitus (T2DM), a progressive metabolic disorder characterized by chronic hyperglycemia and the development of insulin resistance, has increased globally, with worrying statistics coming from children, adolescents, and young adults from developing countries like India. Here, we investigated unique circulating metabolic signatures associated with prediabetes and T2DM in an Indian cohort using NMR-based metabolomics.

MATERIALS AND METHODS

The study subjects included healthy volunteers (N = 101), prediabetic subjects (N = 75), and T2DM patients (N = 108). Serum metabolic profiling was performed using 1H NMR spectroscopy and major perturbed metabolites were identified by multivariate analysis and receiver operating characteristic (ROC) modules.

RESULTS

Of the 36 aqueous abundant metabolites, 24 showed a statistically significant difference between healthy volunteers, prediabetics, and established T2DM subjects. On performing multivariate ROC curve analysis with 5 commonly dysregulated metabolites (namely, glucose, pyroglutamate, o-phosphocholine, serine, and methionine) in prediabetes and T2DM, AUC values obtained were 0.96 (95 % confidence interval (CI) = 0.93, 0.98) for T2DM; and 0.88 (95 % CI = 0.81, 0.93) for prediabetic subjects, respectively.

CONCLUSION

We propose that the identified metabolite panel can be used in the future as a biomarker for clinical diagnosis, patient surveillance, and for predicting individuals at risk for developing diabetes.

Alanine to glycine ratio is a novel predictive biomarker for type 2 diabetes mellitus

AIM

We aimed to evaluate the metabolite ratios that could predict the clinical incidence or remission of type 2 diabetes mellitus (T2D).

METHODS

The Cox proportional hazards regression model was used to assess 1813 individuals without T2D to test the predictive value of metabolite ratios for T2D incidence and 451 newly diagnosed T2D for remission. The receiver operating characteristic curve analysis was performed to determine the best cut-off values for the metabolite ratios. Survival analyses were performed to compare the four subgroups defined by baseline metabolite ratios and clinical status of obesity.

RESULTS

The alanine/glycine was the most significant marker for T2D incidence (hazard ratio per SD: 1.24; p < .001). On the other hand, metabolite hydroxy sphingomyelin C22:2 was most specific for T2D remission (hazard ratio per SD: 1.32; p = .029). Survival analysis of T2D incidence among the subgroups defined by the combination of alanine/glycine and obesity showed the group with a high alanine/glycine and obesity had the highest risk of T2D incidence (p < .001). The alanine/glycine as a T2D risk marker was also validated in the independent external data.

CONCLUSIONS

The combination of obesity and the alanine/glycine ratio can be used to evaluate the diabetes risk.

Integrated biomarker profiling of the metabolome associated with type 2 diabetes mellitus among Tibetan in China

INTRODUCTION

Metabolomic signatures of type 2 diabetes mellitus (T2DM) in Tibetan Chinese population, a group with high diabetes burden, remain largely unclear. Identifying the serum metabolite profile of Tibetan T2DM (T-T2DM) individuals may provide novel insights into early T2DM diagnosis and intervention.

METHODS

Hence, we conducted untargeted metabolomics analysis of plasma samples from a retrospective cohort study with 100 healthy controls and 100 T-T2DM patients by using liquid chromatography-mass spectrometry.

RESULTS

The T-T2DM group had significant metabolic alterations that are distinct from known diabetes risk indicators, such as body mass index, fasting plasma glucose, and glycosylated hemoglobin levels. The optimal metabolite panels for predicting T-T2DM were selected using a tenfold cross-validation random forest classification model. Compared with the clinical features, the metabolite prediction model provided a better predictive value. We also analyzed the correlation of metabolites with clinical indices and found 10 metabolites that were independently predictive of T-T2DM.

CONCLUSION

By using the metabolites identified in this study, we may provide stable and accurate biomarkers for early T-T2DM warning and diagnosis. Our study also provides a rich and open-access data resource for optimizing T-T2DM management.

A holistic view of muscle metabolic reprogramming through personalized metabolic modeling in newly diagnosed diabetic patients

Type 2 diabetes mellitus (T2DM) is a challenging and progressive metabolic disease caused by insulin resistance. Skeletal muscle is the major insulin-sensitive tissue that plays a pivotal role in blood sugar homeostasis. Dysfunction of muscle metabolism is implicated in the disturbance of glucose homeostasis, the development of insulin resistance, and T2DM. Understanding metabolism reprogramming in newly diagnosed patients provides opportunities for early diagnosis and treatment of T2DM as a challenging disease to manage. Here, we applied a system biology approach to investigate metabolic dysregulations associated with the early stage of T2DM. We first reconstructed a human muscle-specific metabolic model. The model was applied for personalized metabolic modeling and analyses in newly diagnosed patients. We found that several pathways and metabolites, mainly implicating in amino acids and lipids metabolisms, were dysregulated. Our results indicated the significance of perturbation of pathways implicated in building membrane and extracellular matrix (ECM). Dysfunctional metabolism in these pathways possibly interrupts the signaling process and develops insulin resistance. We also applied a machine learning method to predict potential metabolite markers of insulin resistance in skeletal muscle. 13 exchange metabolites were predicted as the potential markers. The efficiency of these markers in discriminating insulin-resistant muscle was successfully validated.

NMR-based metabolomic profiling identifies inflammation and muscle-related metabolites as predictors of incident type 2 diabetes mellitus beyond glucose: the Di@bet.es study

AIMS

The aim of this study was to combine nuclear magnetic resonance-based metabolomics and machine learning to find a glucose-independent molecular signature associated with future type 2 diabetes mellitus development in a subgroup of individuals from the Di@bet.es study.

METHODS

The study group included 145 individuals developing type 2 diabetes mellitus during the 8-year follow-up, 145 individuals matched by age, sex and BMI who did not develop diabetes during the follow-up but had equal glucose concentrations to those who did and 145 controls matched by age and sex. A metabolomic analysis of serum was performed to obtain the lipoprotein and glycoprotein profiles and 15 low molecular weight metabolites. Several machine learning-based models were trained.

RESULTS

Logistic regression performed the best classification between individuals developing type 2 diabetes during the follow-up and glucose-matched individuals. The area under the curve was 0.628, and its 95% confidence interval was 0.510-0.746. Glycoprotein-related variables, creatinine, creatine, small HDL particles and the Johnson-Neyman intervals of the interaction of Glyc A and Glyc B were statistically significant.

CONCLUSIONS

The model highlighted a relevant contribution of inflammation (glycosylation pattern and HDL) and muscle (creatinine and creatine) in the development of type 2 diabetes as independent factors of hyperglycemia.

Regulation of PKC/TLR-4/NF-kB signaling by sulbutiamine improves diabetic nephropathy in rats

One of the serious complications of diabetes mellitus is diabetic nephropathy (DN) which may finally lead to renal failure. The current study aimed to explore the effect of sulbutiamine, a synthetic derivative of vitamin B1, in streptozotocin (STZ)-induced DN and related pathways. Experimental DN was successfully induced 8 weeks after a single low dose of STZ (45 mg/kg, I.P.). Four groups of rats were used in this study and divided randomly into: control group, diabetic group, sulbutiamine control (control + sulbutiamine) group, and sulbutiamine-treated (60 mg/kg) (diabetic + sulbutiamine) group. The fasting blood glucose level (BGL) and the levels of kidney injury molecule-1 (Kim-1), urea, creatinine in serum, and the renal content of malondialdehyde (MDA), protein kinase C (PKC), toll-like receptor-4 (TLR-4) and nuclear factor kappa B (NF-κB) were determined. Additionally, tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β) and transforming growth factor-β1 (TGF-β1) contents were evaluated immunohistochemically. Sulbutiamine treatment decreased fasting BGL and improved the kidney function tests compared to diabetic rats. Moreover, TLR-4, NF-κB, MDA and PKC contents were substantially reduced following sulbutiamine treatment compared to the diabetic group. Sulbutiamine managed to obstruct the production of the pro-inflammatory TNF-α and IL-1β and suppressed TGF-β1 level, in addition to attenuating the histopathological changes associated with DN. This study revealed, for the first time, the ability of sulbutiamine to ameliorate STZ-induced diabetic nephropathy in rats. This nephroprotective outcome of sulbutiamine against DN may be attributed to glycemic control in addition to its anti-oxidative, anti-inflammatory and anti-fibrotic effects.

Maternal and Fetal Metabolites in Gestational Diabetes Mellitus: A Narrative Review

Gestational diabetes mellitus (GDM) is a major public health issue of our century due to its increasing prevalence, affecting 5% to 20% of all pregnancies. The pathogenesis of GDM has not been completely elucidated to date. Increasing evidence suggests the association of environmental factors with genetic and epigenetic factors in the development of GDM. So far, several metabolomics studies have investigated metabolic disruptions associated with GDM. The aim of this review is to highlight the usefulness of maternal metabolites as diagnosis markers of GDM as well as the importance of both maternal and fetal metabolites as prognosis biomarkers for GDM and GDM’s transition to type 2 diabetes mellitus T2DM.

Liquid Chromatography-Mass Spectrometry for Clinical Metabolomics: An Overview

Metabolomics is a discipline that offers a comprehensive analysis of metabolites in biological samples. In the last decades, the notable evolution in liquid chromatography and mass spectrometry technologies has driven an exponential progress in LC-MS-based metabolomics. Targeted and untargeted metabolomics strategies are important tools in health and medical science, especially in the study of disease-related biomarkers, drug discovery and development, toxicology, diet, physical exercise, and precision medicine. Clinical and biological problems can now be understood in terms of metabolic phenotyping. This overview highlights the current approaches to LC-MS-based metabolomics analysis and its applications in the clinical research.

Phytosterols: Nutritional Health Players in the Management of Obesity and Its Related Disorders

Obesity and its related disorders, such as diabetes and cardiovascular risk, represent an emerging global health issue. Even though genetic factors seem to be the primary actors in the development and progression of these diseases, dietary choices also appear to be of crucial importance. A healthy diet combined with physical activity have been shown to ameliorate glycaemic levels and insulin sensitivity, reduce body weight and the risk of chronic diseases, and contribute to an overall improvement in quality of life. Among nutrients, phytosterols have become the focus of growing attention as novel functional foods in the management of metabolic disorders. Phytosterols are natural plant compounds belonging to the triterpene family and are structurally similar to cholesterol. They are known for their cholesterol-lowering effects, anti-inflammatory and antioxidant properties, and the benefits they offer to the immune system. The present review aims to provide an overview of these bioactive compounds and their therapeutic potential in the fields of obesity and metabolic disorders, with special attention given to oxidative stress, inflammatory status, and gut dysbiosis, all common features of the aforementioned diseases.

Metabolomics in Radiation Biodosimetry: Current Approaches and Advances

Triage and medical intervention strategies for unanticipated exposure during a radiation incident benefit from the early, rapid and accurate assessment of dose level. Radiation exposure results in complex and persistent molecular and cellular responses that ultimately alter the levels of many biological markers, including the metabolomic phenotype. Metabolomics is an emerging field that promises the determination of radiation exposure by the qualitative and quantitative measurements of small molecules in a biological sample. This review highlights the current role of metabolomics in assessing radiation injury, as well as considerations for the diverse range of bioanalytical and sampling technologies that are being used to detect these changes. The authors also address the influence of the physiological status of an individual, the animal models studied, the technology and analysis employed in interrogating response to the radiation insult, and variables that factor into discovery and development of robust biomarker signatures. Furthermore, available databases for these studies have been reviewed, and existing regulatory guidance for metabolomics are discussed, with the ultimate goal of providing both context for this area of radiation research and the consideration of pathways for continued development.

Sinapic Acid Ameliorates the Progression of Streptozotocin (STZ)-Induced Diabetic Nephropathy in Rats via NRF2/HO-1 Mediated Pathways

Diabetic neuropathy (DN) is a complicated inauspicious outcome of diabetes, like other abnormalities of diabetes the cause of DN is still vague and it may be the result of various pathological conditions leading up to end-stage renal failure. The present study examines the efficacy of sinapic acid (SA) in streptozotocin (STZ)-induced DN nephropathy and the linked pathway. Twenty-four rats were equally divided randomly into four categories: Normal control (NC), STZ, STZ + SA 20 mg/kg bw, and STZ + SA 40 mg/kg bw. After 8 weeks they were evaluated for ratio of renal index, the fasting blood glucose (FBG), blood urea nitrogen (BUN), 24 h urea protein, serum creatinine (SCr), reduced glutathione peroxidase (GPx), superoxide dismutase (SOD), lipid peroxidation (MDA), tumor necrosis factor α (TNFα), interleukin (IL)-6, as well as lipid profile total cholesterol (TC), total triglycerides (TG), very low density lipoprotein (VLDL), low density lipoprotein (LDL), and high density lipoprotein (HDL) levels. Additionally, histomorphology and ultrastructure of the kidneys were also assessed. Protein expression levels of transforming growth factor-β1 (TGF-β1), nuclear factor erythroid 2-related factor 2 (Nrf2), heme oxygenase-1 (HO-1), IκBα protein (IkBα), anti-apoptotic protein BCl2, nuclear factor kappa B (NF-kB), and Bax were examined. We observed that SA 20 mg/kg bw and 40 mg/kg bw pretreatment significantly and dose-dependently upregulated the protein expression of HO-1, Nrf2, IKBα, and Bcl-2 but downregulated the protein expression of NF-κB, proposing that the nephroprotective mechanism of SA is due to its antioxidant and anti-inflammatory activity; SA prevents the release of cytokines and inflammatory markers (TNFα and IL-6), upregulates antioxidant defense enzymes, and reduces lipid peroxidation, as well as nitric oxide, and anti-apoptotic activity, which may be influenced by the regulation of TNF-α, IL-6, Bcl-2, NF-kB, and BaX via the Nrf2/HO-1 pathway in STZ induced DN. Thus, our results suggest that SA ameliorates the development of STZ-induced DN in rats via NRF2/HO-1 mediated pathways. Further comprehensive studies are required for complete elucidation of the fundamental mechanisms.