A metabolomic comparison of urinary changes in type 2 diabetes in mouse, rat, and human

Investigation of pH-dependent 1H NMR urine metabolite profiles for diagnosis of obesity-related disordering

BACKGROUND

Human urine is highly favorable for 1H NMR metabolomics analyses of obesity-related diseases, such as non-alcoholic fatty liver, type 2 diabetes, and hyperlipidemia (HL), due to its non-invasiveness and ease of large-scale collection. However, the wide range of intrinsic urine pH (5.5-8.5) results in inevitably chemical shift and signal intensity modulations in the 1H NMR spectra. For patients where acidic urine pH is closely linked to obesity-related disease phenotypes, the pH-dependent modulations complicate the spectral analysis and deteriorate quantifications of urine metabolites.

METHODS

We characterized human urine metabolites by NMR at intrinsic urine pH, across urine pH 4.5 to 9.5, to account for pH-dependent modulations. A pH-dependent chemical shift database for quantifiable urine metabolites was generated and integrated into a "pH intelligence" program developed for quantifications of pH-dependent modulations at various pH. The 1H NMR spectra of urines collected from patients with Ob-HL and healthy controls were compared to uncover potential metabolic biomarkers of Ob-HL disease.

RESULTS

Three urine metabolites were unveiled by pH-dependent NMR approach, i.e., TMAO, glycine, and pyruvic acid, with VIP score >1.0 and significant q-value < 0.05, that represent as potential biomarkers for discriminating Ob-HL from healthy controls. Further ROC-AUC analyses revealed that TMAO alone achieved the highest diagnostic accuracy (AUC 0.902), surpassed to that obtained by neutralizing pH approach (AUC 0.549) and enabled better recovering potential urine metabolites from the Ob-HL disease phenotypes.

CONCLUSIONS

We concluded that 1H NMR-derived urine metabolite profile represents a snapshot that can reveal the physiological condition of humans in either a healthy or diseased state under intrinsic urine pH. We demonstrated a systematic analysis of pH-dependent modulations on the human urine metabolite signals and further developed software for quantification of urine metabolite profiles with high accuracy, enabling the uncovering of potential metabolite biomarkers in clinical diagnosis applications.

Discovery of Noninvasive Biomarkers for Radiation Exposure via LC-MS-Based Hair Metabolomics

Ionizing radiation exposure from a potential nuclear energy plant leak or detonation of a nuclear weapon can cause massive casualties to both warfighters and civilians. RNA, proteins, and metabolite biomarkers in biological specimens like blood and tissue have shown potential to determine radiation dose levels. However, these biomarkers in blood and urine are short-lived, typically detectable within hours or a few days. To address the need for stable, long-term radiation exposure biomarkers, we developed two mass spectrometry-based methods using noninvasive hair samples to identify radiation-exposure biomarkers. Our results show that hippuric acid and 5-methoxy-3-indoleacetate significantly increase after higher (4 gray) doses of gamma irradiation compared to lower (1 and 2 Gy) doses or nonexposed hair samples. While 2-aminooctadec-4-ene-1,3-diol, oleoyl ethanolamide, palmitoylcarnitine, 25-hydroxy vitamin D3, vernolic acid, and azelaic acid significantly increased over time after exposure. Trimethylamine N-oxide (TMAO) was found in higher concentrations in female specimens across all time points. Further validation using a machine learning model suggested that these biomarkers can predict differences in the exposure dose and time point. Our findings highlight the potential of noninvasive hair sample analysis for assessing radiation exposure, offering a viable alternative to address critical public health concerns of unexpected radiation exposure.

Nicotinamide n-methyltransferase inhibitor synergizes with sodium-glucose cotransporter 2 inhibitor to protect renal tubular epithelium in experimental models of type 2 diabetes mellitus

AIMS

We aim to explore the potential of nicotinamide n-methyltransferase (NNMT) as a sensitive marker of renal tubular injury and the possibility of an NNMT inhibitor to combine with sodium-glucose cotransporter 2 (SGLT2) inhibitor to protect proximal tubular epithelium in vivo and in vitro model of Type 2 diabetes mellitus (T2DM), respectively.

METHODS

In vivo, immunohistochemical staining, Masson's trichrome staining and Sirius red staining were used to observe the changes of NNMT expression, renal tubular injury and interstitial fibrosis in renal tissue from the db/db mice. Bioinformatic analysis was also conducted to broaden the range of data validation. In vitro, Western Blot and quantitative RT-PCR were used to measure the degree of damage of HK-2 cells.

RESULTS

Our in vivo data showed upregulation of NNMT expression paralleled renal tubular damage and interstitial fibrosis. Our in vitro data revealed both NNMT inhibitors and SGLT2 inhibitors can protect against the injury as assessed by extracellular matrix (ECM) synthesis and profibrotic phenotype transition of HK-2 cells, and the combination of these two agents can further reduce these injuries.

CONCLUSIONS

The present study is the first to show that NNMT is a promising marker of renal tubular injury in diabetic nephropathy (DN) and NNMT inhibitors can synergize with SGLT2 inhibitors to protect HK-2 better. Our findings will provide the insight and pave the way of developing novel therapeutic strategies for chronic renal tubular injury associated with T2DM.

Exploring NNMT: from metabolic pathways to therapeutic targets

Cellular metabolism-related epigenetic modulation plays a pivotal role in the maintenance of cellular homeostasis. Nicotinamide N-methyltransferase (NNMT) serves as a crucial link between cellular metabolism and epigenetics by catalyzing nicotinamide methylation using the universal methyl donor S-adenosyl-L-methionine. This direct connection bridges the methylation-mediated one-carbon metabolism with nicotinamide adenine dinucleotide levels. Numerous studies have revealed tissue-specific differences in NNMT expression and activity, indicating that its varied physiological and pathological roles depend on its distribution. In this review, we provide an overview of the NNMT involvement in various pathological conditions, including cancer, liver disease, obesity, diabetes, brain disease, pulmonary disease, cardiovascular disease, and kidney disease. By synthesizing this information, our article aims to enhance our understanding of the cellular mechanisms underlying NNMT biology related to diverse diseases and lay the molecular groundwork for developing therapeutic strategies for pharmacological interventions.

The effects of chicory inulin-type fructans supplementation on weight management outcomes: systematic review, meta-analysis, and meta-regression of randomized controlled trials

BACKGROUND

Excess body weight and adiposity can adversely affect metabolic health. Prebiotics such as inulin-type fructans (ITFs) from chicory root are known to modulate gut microbiota and may improve body weight regulation.

OBJECTIVES

This study aimed to assess evidence for chicory ITF supplementation to support weight management.

METHODS

Eligible articles (initial search to 2021, updated to February 2023) were searched from EMBASE, MEDLINE (PubMed), and Cochrane Library. Data on primary (body weight) and secondary outcomes [body mass index (BMI), total fat mass, body fat percentage, and waist circumference] were extracted by 2 reviewers independently. Random-effects model using inverse-variance method was used. Subgroup analysis (health status and ITF type) and meta-regression (dose and duration) were evaluated.

RESULTS

A total of 32 eligible studies were included. Chicory ITF significantly reduced body weight [mean difference (MD): -0.97 kg; 95% CI: -1.34, -0.59); n = 1184] compared with placebo. ITF favored overall effects reduction in BMI (MD: -0.39 kg/m2; 95% CI: -0.57, -0.20; n = 985), fat mass (MD: -0.37 kg; 95% CI: -0.61, -0.13; n = 397), waist circumference (MD: -1.03 cm; 95% CI: -1.69, -0.37; n = 604), and for intervention duration of >8 wk, body fat percentage (MD: -0.78%; 95% CI: -1.17, -0.39; n = 488). Except for considerable heterogeneity in body weight (I2: 73%) and body fat percentage (I2: 75%), all other outcomes had negligible to moderate heterogeneity. Significant reduction in body weight, BMI, and waist circumference was evident irrespective of participants' health status. There was minimal evidence that dose, duration, or type of ITF influenced the magnitude of reductions in outcomes.

CONCLUSIONS

Chicory ITF supplementation may benefit weight management by reducing body weight, BMI, fat mass, waist circumference, and, to a certain extent, body fat percentage. This systematic review with meta-analysis was registered at PROSPERO as CRD42020184908.

Integration strategies involving 16S rDNA sequencing combined with untargeted metabolomics revealed the mechanism of Selaginella tamariscina (Beauv.) Spring in db/db diabetic mice

Selaginella tamariscina extracts (STS), total flavonoids of Selaginella tamariscina (TFST) and the main active component amentoflavone (AMT) have hypoglycaemic-mitigating effects, but their efficacy and mechanism of action in db/db mice are unknown. This study aimed to evaluate the hypoglycaemic effects of Selaginella tamariscina and its extracts in db/db diabetic mice and explore their mechanisms through gut microbiota modulation and metabolomics. Sixty male db/db mice were divided into model (db/db), STS (1.1 g/kg), TFST (140 mg/kg), AMT (60 mg/kg), mulberry twig alkaloid tablets (MTA, 24 mg/kg), and metformin (Met, 160 mg/kg) groups. Another 10 db/m mice served as controls. Treatments lasted 4 weeks. Blood glucose, body weight, diabetes symptoms, lipid levels, pathological changes, oxidative stress markers and liver damage levels were assessed. The gut microbiota composition was analyzed via 16S rDNA sequencing, and urinary metabolomics was conducted to understand metabolic changes. Selaginella tamariscina and its extracts significantly improved hyperglycaemia, insulin sensitivity, lipid metabolism, oxidative stress and liver injury in db/db mice, among which TFST was the most effective, with an effect comparable to that of Met and superior to that of MTA. TFST regulates gut microbiota disorders and metabolic profiles in db/db diabetic mice and modulates Alloprevotella levels, affecting butyric acid content and, thus, exerting a hypoglycaemic effect. These findings suggest that TFST modulates Alloprevotella, influencing butyric acid levels, which improves glycaemic control, enhances insulin sensitivity, and prevents oxidative stress and tissue damage. In conclusion, TFST has potential as a natural therapeutic agent for the control of T2DM.

Nicotinamide N-methyltransferase (NNMT): a novel therapeutic target for metabolic syndrome

Metabolic syndrome (MetS) represents a constellation of metabolic abnormalities, typified by obesity, hypertension, hyperglycemia, and hyperlipidemia. It stems from intricate dysregulations in metabolic pathways governing energy and substrate metabolism. While comprehending the precise etiological mechanisms of MetS remains challenging, evidence underscores the pivotal roles of aberrations in lipid metabolism and insulin resistance (IR) in its pathogenesis. Notably, nicotinamide N-methyltransferase (NNMT) has recently surfaced as a promising therapeutic target for addressing MetS. Single nucleotide variants in the NNMT gene are significantly correlated with disturbances in energy metabolism, obesity, type 2 diabetes (T2D), hyperlipidemia, and hypertension. Elevated NNMT gene expression is notably observed in the liver and white adipose tissue (WAT) of individuals with diabetic mice, obesity, and rats afflicted with MetS. Knockdown of NNMT elicits heightened energy expenditure in adipose and hepatic tissues, mitigates lipid accumulation, and enhances insulin sensitivity. NNMT catalyzes the methylation of nicotinamide (NAM) using S-adenosyl-methionine (SAM) as the donor methyl group, resulting in the formation of S-adenosyl-l-homocysteine (SAH) and methylnicotinamide (MNAM). This enzymatic process results in the depletion of NAM, a precursor of nicotinamide adenine dinucleotide (NAD+), and the generation of SAH, a precursor of homocysteine (Hcy). Consequently, this cascade leads to reduced NAD+ levels and elevated Hcy levels, implicating NNMT in the pathogenesis of MetS. Moreover, experimental studies employing RNA interference (RNAi) strategies and small molecule inhibitors targeting NNMT have underscored its potential as a therapeutic target for preventing or treating MetS-related diseases. Nonetheless, the precise mechanistic underpinnings remain elusive, and as of yet, clinical trials focusing on NNMT have not been documented. Therefore, further investigations are warranted to elucidate the intricate roles of NNMT in MetS and to develop targeted therapeutic interventions.

Potential impact of underlying diseases influencing ADME in nonclinical safety assessment

Nonclinical studies involve in vitro, in silico, and in vivo experiments to assess the toxicokinetics, toxicology, and safety pharmacology of drugs according to regulatory requirements by a national or international authority. In this review, we summarize the potential effects of various underlying diseases governing the absorption, distribution, metabolism, and excretion (ADME) of drugs to consider the use of animal models of diseases in nonclinical trials. Obesity models showed alterations in hepatic metabolizing enzymes, transporters, and renal pathophysiology, which increase the risk of drug-induced toxicity. Diabetes models displayed changes in hepatic metabolizing enzymes, transporters, and glomerular filtration rates (GFR), leading to variability in drug responses and susceptibility to toxicity. Animal models of advanced age exhibited impairment of drug metabolism and kidney function, thereby reducing the drug-metabolizing capacity and clearance. Along with changes in hepatic metabolic enzymes, animal models of metabolic syndrome-related hypertension showed renal dysfunction, resulting in a reduced GFR and urinary excretion of drugs. Taken together, underlying diseases can induce dysfunction of organs involved in the ADME of drugs, ultimately affecting toxicity. Therefore, the use of animal models of representative underlying diseases in nonclinical toxicity studies can be considered to improve the predictability of drug side effects before clinical trials.

Pilot-Study to Explore Metabolic Signature of Type 2 Diabetes: A Pipeline of Tree-Based Machine Learning and Bioinformatics Techniques for Biomarkers Discovery

BACKGROUND

This study aims to identify unique metabolomics biomarkers associated with Type 2 Diabetes (T2D) and develop an accurate diagnostics model using tree-based machine learning (ML) algorithms integrated with bioinformatics techniques.

METHODS

Univariate and multivariate analyses such as fold change, a receiver operating characteristic curve (ROC), and Partial Least-Squares Discriminant Analysis (PLS-DA) were used to identify biomarker metabolites that showed significant concentration in T2D patients. Three tree-based algorithms [eXtreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), and Adaptive Boosting (AdaBoost)] that demonstrated robustness in high-dimensional data analysis were used to create a diagnostic model for T2D.

RESULTS

As a result of the biomarker discovery process validated with three different approaches, Pyruvate, D-Rhamnose, AMP, pipecolate, Tetradecenoic acid, Tetradecanoic acid, Dodecanediothioic acid, Prostaglandin E3/D3 (isobars), ADP and Hexadecenoic acid were determined as potential biomarkers for T2D. Our results showed that the XGBoost model [accuracy = 0.831, F1-score = 0.845, sensitivity = 0.882, specificity = 0.774, positive predictive value (PPV) = 0.811, negative-PV (NPV) = 0.857 and Area under the ROC curve (AUC) = 0.887] had the slight highest performance measures.

CONCLUSIONS

ML integrated with bioinformatics techniques offers accurate and positive T2D candidate biomarker discovery. The XGBoost model can successfully distinguish T2D based on metabolites.

Global status and trends of metabolomics in diabetes: A literature visualization knowledge graph study

BACKGROUND

Diabetes is a metabolic disease characterized by hyperglycemia, which has increased the global medical burden and is also the main cause of death in most countries.

AIM

To understand the knowledge structure of global development status, research focus, and future trend of the relationship between diabetes and metabolomics in the past 20 years.

METHODS

The articles about the relationship between diabetes and metabolomics in the Web of Science Core Collection were retrieved from 2002 to October 23, 2023, and the relevant information was analyzed using CiteSpace6.2.2R (CiteSpace), VOSviewer6.1.18 (VOSviewer), and Bibliometrix software under R language.

RESULTS

A total of 3123 publications were included from 2002 to 2022. In the past two decades, the number of publications and citations in this field has continued to increase. The United States, China, Germany, the United Kingdom, and other relevant funds, institutions, and authors have significantly contributed to this field. Scientific Reports and PLoS One are the journals with the most publications and the most citations. Through keyword co-occurrence and cluster analysis, the closely related keywords are "insulin resistance", "risk", "obesity", "oxidative stress", "metabolomics", "metabolites" and "biomarkers". Keyword clustering included cardiovascular disease, gut microbiota, metabonomics, diabetic nephropathy, molecular docking, gestational diabetes mellitus, oxidative stress, and insulin resistance. Burst detection analysis of keyword depicted that "Gene", "microbiota", "validation", "kidney disease", "antioxidant activity", "untargeted metabolomics", "management", and "accumulation" are knowledge frontiers in recent years.

CONCLUSION

The relationship between metabolomics and diabetes is receiving extensive attention. Diabetic nephropathy, diabetic cardiovascular disease, and kidney disease are key diseases for future research in this field. Gut microbiota, molecular docking, and untargeted metabolomics are key research directions in the future. Antioxidant activity, gene, validation, mass spectrometry, management, and accumulation are at the forefront of knowledge frontiers in this field.

Genetic Upregulation of Activated Protein C Mitigates Delayed Effects of Acute Radiation Exposure in the Mouse Plasma

Exposure to ionizing radiation, accidental or intentional, may lead to delayed effects of acute radiation exposure (DEARE) that manifest as injury to organ systems, including the kidney, heart, and brain. This study examines the role of activated protein C (APC), a known mitigator of radiation-induced early toxicity, in long-term plasma metabolite and lipid panels that may be associated with DEARE in APCHi mice. The APCHi mouse model used in the study was developed in a C57BL/6N background, expressing the D168F/N173K mouse analog of the hyper-activatable human D167F/D172K protein C variant. This modification enables increased circulating APC levels throughout the mouse's lifetime. Male and female cohorts of C57BL/6N wild-type and APCHi transgenic mice were exposed to 9.5 Gy γ-rays with their hind legs shielded to allow long-term survival that is necessary to monitor DEARE, and plasma was collected at 6 months for LC-MS-based metabolomics and lipidomics. We observed significant dyslipidemia, indicative of inflammatory phenotype, upon radiation exposure. Additionally, observance of several other metabolic dysregulations was suggestive of gut damage, perturbations in TriCarboxylic Acid (TCA) and urea cycles, and arginine metabolism. We also observed gender- and genotype-modulated metabolic perturbations post radiation exposure. The APCHi mice showed near-normal abundance for several lipids. Moreover, restoration of plasma levels of some metabolites, including amino acids, citric acid, and hypoxanthine, in APCHi mice is indicative of APC-mediated protection from radiation injuries. With the help of these findings, the role of APC in plasma molecular events after acute γ-radiation exposure in a gender-specific manner can be established for the first time.

Mapping multi-omics characteristics related to short-term PM2.5 trajectory and their impact on type 2 diabetes in middle-aged and elderly adults in Southern China

The relationship between PM2.5 and metabolic diseases, including type 2 diabetes (T2D), has become increasingly prominent, but the molecular mechanism needs to be further clarified. To help understand the mechanistic association between PM2.5 exposure and human health, we investigated short-term PM2.5 exposure trajectory-related multi-omics characteristics from stool metagenome and metabolome and serum proteome and metabolome in a cohort of 3267 participants (age: 64.4 ± 5.8 years) living in Southern China. And then integrate these features to examine their relationship with T2D. We observed significant differences in overall structure in each omics and 193 individual biomarkers between the high- and low-PM2.5 groups. PM2.5-related features included the disturbance of microbes (carbohydrate metabolism-associated Bacteroides thetaiotaomicron), gut metabolites of amino acids and carbohydrates, serum biomarkers related to lipid metabolism and reducing n-3 fatty acids. The patterns of overall network relationships among the biomarkers differed between T2D and normal participants. The subnetwork membership centered on the hub nodes (fecal rhamnose and glycylproline, serum hippuric acid, and protein TB182) related to high-PM2.5, which well predicted higher T2D prevalence and incidence and a higher level of fasting blood glucose, HbA1C, insulin, and HOMA-IR. Our findings underline crucial PM2.5-related multi-omics biomarkers linking PM2.5 exposure and T2D in humans.

Temporal and region-specific tau hyperphosphorylation in the medulla and forebrain coincides with development of functional changes in male obese Zucker rats

Metabolic syndrome (MetS) is associated with development of tauopathies that contribute to cognitive decline. Without functional leptin receptors, male obese Zucker rats (OZRs) develop MetS, and they have increased phosphorylated tau (ptau) with impaired cognitive function. In addition to regulating energy balance, leptin enhances activation of the hippocampus, which is essential for spatial learning and memory. Whether spatial learning and memory are always impaired in OZRs or develop with MetS is unknown. We hypothesized that male OZRs develop MetS traits that promote regional increases in ptau and functional deficits associated with those brain regions. In the medulla and cortex, tau-pSer199,202 and tau-pSer396 were comparable in juvenile (7-8 wk old) lean Zucker rats (LZRs) and OZRs but increased in 18- to 19-wk-old OZRs. Elevated tau-pSer396 was concentrated in the dorsal vagal complex of the medulla, and by this age OZRs had hypertension with increased arterial pressure variability. In the hippocampus, tau-pSer199,202 and tau-pSer396 were still comparable in 18- to 19-wk-old OZRs and LZRs but elevated in 28- to 29-wk-old OZRs, with emergence of deficits in Morris water maze performance. Comparable escape latencies observed during acquisition in 18- to 19-wk-old OZRs and LZRs were increased in 28- to 29-wk-old OZRs, with greater use of nonspatial search strategies. Increased ptau developed with changes in the insulin/phosphatidylinositol 3-kinase (PI3K)/Akt signaling pathway in the hippocampus and cortex but not medulla, suggesting different underlying mechanisms. These data demonstrate that leptin is not required for spatial learning and memory in male OZRs. Furthermore, early development of MetS-associated autonomic dysfunction by the medulla may be predictive of later hippocampal dysfunction and cognitive impairment.NEW & NOTEWORTHY Male obese Zucker rats (OZRs) lack functional leptin receptors and develop metabolic syndrome (MetS). At 16-19 wk, OZRs are insulin resistant, with increased ptau in dorsal medulla and impaired autonomic regulation of AP. At 28-29 wk OZRs develop increased ptau in hippocampus with deficits in spatial learning and memory. Juvenile OZRs lack elevated ptau and these deficits, demonstrating that leptin is not essential for normal function. Elevated ptau and deficits emerge before the onset of diabetes in insulin-resistant OZRs.

LAVASET: Latent Variable Stochastic Ensemble of Trees. An ensemble method for correlated datasets with spatial, spectral, and temporal dependencies

MOTIVATION

Random forests (RFs) can deal with a large number of variables, achieve reasonable prediction scores, and yield highly interpretable feature importance values. As such, RFs are appropriate models for feature selection and further dimension reduction. However, RFs are often not appropriate for correlated datasets due to their mode of selecting individual features for splitting. Addressing correlation relationships in high-dimensional datasets is imperative for reducing the number of variables that are assigned high importance, hence making the dimension reduction most efficient. Here, we propose the LAtent VAriable Stochastic Ensemble of Trees (LAVASET) method that derives latent variables based on the distance characteristics of each feature and aims to incorporate the correlation factor in the splitting step.

RESULTS

Without compromising on performance in the majority of examples, LAVASET outperforms RF by accurately determining feature importance across all correlated variables and ensuring proper distribution of importance values. LAVASET yields mostly non-inferior prediction accuracies to traditional RFs when tested in simulated and real 1D datasets, as well as more complex and high-dimensional 3D datatypes. Unlike traditional RFs, LAVASET is unaffected by single 'important' noisy features (false positives), as it considers the local neighbourhood. LAVASET, therefore, highlights neighbourhoods of features, reflecting real signals that collectively impact the model's predictive ability.

AVAILABILITY AND IMPLEMENTATION

LAVASET is freely available as a standalone package from https://github.com/melkasapi/LAVASET.

Using metabolomics and proteomics to identify the potential urine biomarkers for prediction and diagnosis of gestational diabetes

Gestational diabetes mellitus (GDM) is one of the most common metabolic complications during pregnancy, threatening both maternal and fetal health. Prediction and diagnosis of GDM is not unified. Finding effective biomarkers for GDM is particularly important for achieving early prediction, accurate diagnosis and timely intervention. Urine, due to its accessibility in large quantities, noninvasive collection and easy preparation, has become a good sample for biomarker identification. In recent years, a number of studies using metabolomics and proteomics approaches have identified differential expressed urine metabolites and proteins in GDM patients. In this review, we summarized these potential urine biomarkers for GDM prediction and diagnosis and elucidated their role in development of GDM.

Antidiabetic effect of Ardisia elliptica extract and its mechanisms of action in STZ-NA-induced diabetic rat model via 1H-NMR-based metabolomics

ETHNOPHARMACOLOGICAL RELEVANCE

Ardisia elliptica Thunb. (AE) (Primulaceae) is a medicinal plant found in the Malay Peninsula and has been traditionally used to treat diabetes. However, limited studies to date in providing scientific evidence to support the antidiabetic efficacy of this plant by in-vitro and in-vivo models.

AIM OF THE STUDY

To investigate the anti-hyperglycemic potential of AE through in-vitro enzymatic activities and streptozotocin-nicotinamide (STZ-NA) induced diabetic rat models using proton-nuclear magnetic resonance (1H-NMR)-based metabolomics approach.

MATERIALS AND METHODS

Anti-α-amylase and anti-α-glucosidase activities of the hydroethanolic extracts of AE were evaluated. The absolute quantification of bioactive constituents, using ultra-high performance liquid chromatography (UHPLC) was performed for the most active extract. Three different dosage levels of the AE extract were orally administered for 4 weeks consecutively in STZ-NA induced diabetic rats. Physical assessments, biochemical analysis, and an untargeted 1H-NMR-based metabolomics analysis of the urine and serum were carried out on the animal model.

RESULTS

Type 2 diabetes mellitus (T2DM) rat model was successfully developed based on the clear separation observed between the STZ-NA induced diabetic and normal non-diabetic groups. Discriminating biomarkers included glucose, citrate, succinate, allantoin, hippurate, 2-oxoglutarate, and 3-hydroxybutyrate, as determined through an orthogonal partial least squares-discriminant analysis (OPLS-DA) model. A treatment dosage of 250 mg/kg body weight (BW) of standardized 70% ethanolic AE extract mitigated increase in serum glucose, creatinine, and urea levels, providing treatment levels comparable to that obtained using metformin, with flavonoids primarily contribute to the anti-hyperglycemic activities. Urinary metabolomics disclosed that the following disturbed metabolism pathways: the citrate cycle (TCA cycle), butanoate metabolism, glycolysis and gluconeogenesis, pyruvate metabolism, and synthesis and degradation of ketone bodies, were ameliorated after treatment with the standardized AE extract.

CONCLUSIONS

This study demonstrated the first attempt at revealing the therapeutic effect of oral treatment with 250 mg/kg BW of standardized AE extract on chemically induced T2DM rats. The present study provides scientific evidence supporting the ethnomedicinal use of Ardisia elliptica and further advances the understanding of the fundamental molecular mechanisms affected by this herbal antidote.

IBS randomized study: FODMAPs alter bile acids, phenolic- and tryptophan metabolites, while gluten modifies lipids

Diet is considered a culprit for symptoms in irritable bowel syndrome (IBS), although the mechanistic understanding of underlying causes is lacking. Metabolomics, i.e., the analysis of metabolites in biological samples may offer a diet-responsive fingerprint for IBS. Our aim was to explore alterations in the plasma metabolome after interventions with fermentable oligosaccharides, disaccharides, monosaccharides, and polyols (FODMAPs) or gluten versus control in IBS, and to relate such alterations to symptoms. People with IBS (n = 110) were included in a double-blind, randomized, crossover study with 1-wk provocations of FODMAPs, gluten, or placebo. Symptoms were evaluated with the IBS severity scoring system (IBS-SSS). Untargeted metabolomics was performed on plasma samples using LC-qTOF-MS. Discovery of metabolite alterations by treatment was performed using random forest followed by linear mixed modeling. Associations were studied using Spearman correlation. The metabolome was affected by FODMAP [classification rate (CR) 0.88, P < 0.0001], but less by gluten intake CR 0.72, P = 0.01). FODMAP lowered bile acids, whereas phenolic-derived metabolites and 3-indolepropionic acid (IPA) were higher compared with placebo. IPA and some unidentified metabolites correlated weakly to abdominal pain and quality of life. Gluten affected lipid metabolism weakly, but with no interpretable relationship to IBS. FODMAP affected gut microbial-derived metabolites relating to positive health outcomes. IPA and unknown metabolites correlated weakly to IBS severity. Minor symptom worsening by FODMAP intake must be weighed against general positive health aspects of FODMAP. The gluten intervention affected lipid metabolism weakly with no interpretable association to IBS severity. Registration: www.clinicaltrials.gov as NCT03653689.NEW & NOTEWORTHY In irritable bowel syndrome (IBS), fermentable oligo-, di-, monosaccharides, and polyols (FODMAPs) affected microbial-derived metabolites relating to positive health outcomes such as reduced risk of colon cancer, inflammation, and type 2 diabetes, as shown in previous studies. The minor IBS symptom induction by FODMAP intake must be weighed against the positive health aspects of FODMAP consumption. Gluten affected lipids weakly with no association to IBS severity.

Feeding High-Fat Diet Accelerates Development of Peripheral and Central Insulin Resistance and Inflammation and Worsens AD-like Pathology in APP/PS1 Mice

Alzheimer's disease (AD) is a progressive brain disorder characterized by extracellular amyloid-β (Aβ) plaques, intracellular neurofibrillary tangles formed by hyperphosphorylated Tau protein and neuroinflammation. Previous research has shown that obesity and type 2 diabetes mellitus, underlined by insulin resistance (IR), are risk factors for neurodegenerative disorders. In this study, obesity-induced peripheral and central IR and inflammation were studied in relation to AD-like pathology in the brains and periphery of APP/PS1 mice, a model of Aβ pathology, fed a high-fat diet (HFD). APP/PS1 mice and their wild-type controls fed either a standard diet or HFD were characterized at the ages of 3, 6 and 10 months by metabolic parameters related to obesity via mass spectroscopy, nuclear magnetic resonance, immunoblotting and immunohistochemistry to quantify how obesity affected AD pathology. The HFD induced substantial peripheral IR leading to central IR. APP/PS1-fed HFD mice had more pronounced IR, glucose intolerance and liver steatosis than their WT controls. The HFD worsened Aβ pathology in the hippocampi of APP/PS1 mice and significantly supported both peripheral and central inflammation. This study reveals a deleterious effect of obesity-related mild peripheral inflammation and prediabetes on the development of Aβ and Tau pathology and neuroinflammation in APP/PS1 mice.

Atlas of gut microbe-derived products from aromatic amino acids and risk of cardiovascular morbidity and mortality

AIMS

Precision microbiome modulation as a novel treatment strategy is a rapidly evolving and sought goal. The aim of this study is to determine relationships among systemic gut microbial metabolite levels and incident cardiovascular disease risks to identify gut microbial pathways as possible targets for personalized therapeutic interventions.

METHODS AND RESULTS

Stable isotope dilution mass spectrometry methods to quantitatively measure aromatic amino acids and their metabolites were used to examine sequential subjects undergoing elective diagnostic cardiac evaluation in two independent cohorts with longitudinal outcome data [US (n = 4000) and EU (n = 833) cohorts]. It was also used in plasma from humans and mice before vs. after a cocktail of poorly absorbed antibiotics to suppress gut microbiota. Multiple aromatic amino acid-derived metabolites that originate, at least in part, from gut bacteria are associated with incident (3-year) major adverse cardiovascular event (MACE) risks (myocardial infarction, stroke, or death) and all-cause mortality independent of traditional risk factors. Key gut microbiota-derived metabolites associated with incident MACE and poorer survival risks include: (i) phenylacetyl glutamine and phenylacetyl glycine (from phenylalanine); (ii) p-cresol (from tyrosine) yielding p-cresol sulfate and p-cresol glucuronide; (iii) 4-OH-phenyllactic acid (from tyrosine) yielding 4-OH-benzoic acid and 4-OH-hippuric acid; (iv) indole (from tryptophan) yielding indole glucuronide and indoxyl sulfate; (v) indole-3-pyruvic acid (from tryptophan) yielding indole-3-lactic acid and indole-3-acetyl-glutamine, and (vi) 5-OH-indole-3-acetic acid (from tryptophan).

CONCLUSION

Key gut microbiota-generated metabolites derived from aromatic amino acids independently associated with incident adverse cardiovascular outcomes are identified, and thus will help focus future studies on gut-microbial metabolic outputs relevant to host cardiovascular health.

Metabolic Alterations in Streptozotocin-nicotinamide-induced Diabetic Rats Treated with Muntingia calabura Extract via 1H-NMR-based Metabolomics

Diabetes mellitus (DM) is a metabolic endocrine disorder caused by decreased insulin concentration or poor insulin response. Muntingia calabura (MC) has been used traditionally to reduce blood glucose levels. This study aims to support the traditional claim of MC as a functional food and blood-glucose-lowering regimen. The antidiabetic potential of MC is tested on a streptozotocin-nicotinamide (STZ-NA)-induced diabetic rat model by using the ¹H-NMR-based metabolomic approach. Serum biochemical analyses reveal that treatment with 250 mg/kg body weight (bw) standardized freeze-dried (FD) 50% ethanolic MC extract (MCE 250) shows favorable serum creatinine (37.77 ± 3.53 µM), urea (5.98 ± 0.84 mM) and glucose (7.36 ± 0.57 mM) lowering capacity, which was comparable to the standard drug, metformin. The clear separation between diabetic control (DC) and normal group in principal component analysis indicates the successful induction of diabetes in the STZ-NA-induced type 2 diabetic rat model. A total of nine biomarkers, including allantoin, glucose, methylnicotinamide, lactate, hippurate, creatine, dimethylamine, citrate and pyruvate are identified in rats' urinary profile, discriminating DC and normal groups through orthogonal partial least squares-discriminant analysis. Induction of diabetes by STZ-NA is due to alteration in the tricarboxylic acid (TCA) cycle, gluconeogenesis pathway, pyruvate metabolism and nicotinate and nicotinamide metabolism. Oral treatment with MCE 250 in STZ-NA-induced diabetic rats shows improvement in the altered carbohydrate metabolism, cofactor and vitamin metabolic pathway, as well as purine and homocysteine metabolism.

Food Polyphenols and Type II Diabetes Mellitus: Pharmacology and Mechanisms

Type II diabetes mellitus and its related complications are growing public health problems. Many natural products present in our diet, including polyphenols, can be used in treating and managing type II diabetes mellitus and different diseases, owing to their numerous biological properties. Anthocyanins, flavonols, stilbenes, curcuminoids, hesperidin, hesperetin, naringenin, and phenolic acids are common polyphenols found in blueberries, chokeberries, sea-buckthorn, mulberries, turmeric, citrus fruits, and cereals. These compounds exhibit antidiabetic effects through different pathways. Accordingly, this review presents an overview of the most recent developments in using food polyphenols for managing and treating type II diabetes mellitus, along with various mechanisms. In addition, the present work summarizes the literature about the anti-diabetic effect of food polyphenols and evaluates their potential as complementary or alternative medicines to treat type II diabetes mellitus. Results obtained from this survey show that anthocyanins, flavonols, stilbenes, curcuminoids, and phenolic acids can manage diabetes mellitus by protecting pancreatic β-cells against glucose toxicity, promoting β-cell proliferation, reducing β-cell apoptosis, and inhibiting α-glucosidases or α-amylase. In addition, these phenolic compounds exhibit antioxidant anti-inflammatory activities, modulate carbohydrate and lipid metabolism, optimize oxidative stress, reduce insulin resistance, and stimulate the pancreas to secrete insulin. They also activate insulin signaling and inhibit digestive enzymes, regulate intestinal microbiota, improve adipose tissue metabolism, inhibit glucose absorption, and inhibit the formation of advanced glycation end products. However, insufficient data are available on the effective mechanisms necessary to manage diabetes.

Identification of Novel Biomarkers in Late Preterm Neonates with Respiratory Distress Syndrome (RDS) Using Urinary Metabolomic Analysis

Urine metabolomics is gaining traction as a means of identifying metabolic signatures associated with health and disease states. Thirty-one (31) late preterm (LP) neonates admitted to the neonatal intensive care unit (NICU) and 23 age-matched healthy LPs admitted to the maternity ward of a tertiary hospital were included in the study. Proton nuclear magnetic resonance (¹H NMR) spectroscopy was employed for urine metabolomic analysis on the 1st and 3rd days of life of the neonates. The data were analyzed using univariate and multivariate statistical analysis. A unique metabolic pattern of enhanced metabolites was identified in the NICU-admitted LPs from the 1st day of life. Metabolic profiles were distinct in LPs presenting with respiratory distress syndrome (RDS). The discrepancies likely reflect differences in the gut microbiota, either due to variations in nutrient intake or as a result of medical interventions, such as the administration of antibiotics and other medications. Altered metabolites could potentially serve as biomarkers for identifying critically ill LP neonates or those at high risk for adverse outcomes later in life, including metabolic risks. The discovery of novel biomarkers may uncover potential targets for drug discovery and optimal periods for effective intervention, offering a personalized approach.

Urinary 1H NMR Metabolomic Analysis of Prenatal Maternal Stress Due to a Natural Disaster Reveals Metabolic Risk Factors for Non-Communicable Diseases: The QF2011 Queensland Flood Study

Prenatal stress alters fetal programming, potentially predisposing the ensuing offspring to long-term adverse health outcomes. To gain insight into environmental influences on fetal development, this QF2011 study evaluated the urinary metabolomes of 4-year-old children (n = 89) who were exposed to the 2011 Queensland flood in utero. Proton nuclear magnetic resonance spectroscopy was used to analyze urinary metabolic fingerprints based on maternal levels of objective hardship and subjective distress resulting from the natural disaster. In both males and females, differences were observed between high and low levels of maternal objective hardship and maternal subjective distress groups. Greater prenatal stress exposure was associated with alterations in metabolites associated with protein synthesis, energy metabolism, and carbohydrate metabolism. These alterations suggest profound changes in oxidative and antioxidative pathways that may indicate a higher risk for chronic non-communicable diseases such obesity, insulin resistance, and diabetes, as well as mental illnesses, including depression and schizophrenia. Thus, prenatal stress-associated metabolic biomarkers may provide early predictors of lifetime health trajectories, and potentially serve as prognostic markers for therapeutic strategies in mitigating adverse health outcomes.

Metabolomic Study of Aging in fa/fa Rats: Multiplatform Urine and Serum Analysis

Zucker fatty (fa/fa) rats represent a well-established and widely used model of genetic obesity. Because previous metabolomic studies have only been published for young fa/fa rats up to 20 weeks of age, which can be considered early maturity in male fa/fa rats, the aim of our work was to extend the metabolomic characterization to significantly older animals. Therefore, the urinary profiles of obese fa/fa rats and their lean controls were monitored using untargeted NMR metabolomics between 12 and 40 weeks of age. At the end of the experiment, the rats were also characterized by NMR and LC-MS serum analysis, which was supplemented by a targeted LC-MS analysis of serum bile acids and neurotransmitters. The urine analysis showed that most of the characteristic differences detected in young obese fa/fa rats persisted throughout the experiment, primarily through a decrease in microbial co-metabolite levels, the upregulation of the citrate cycle, and changes in nicotinamide metabolism compared with the age-related controls. The serum of 40-week-old obese rats showed a reduction in several bile acid conjugates and an increase in serotonin. Our study demonstrated that the fa/fa model of genetic obesity is stable up to 40 weeks of age and is therefore suitable for long-term experiments.

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

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

Identification of novel human nicotinamide N-methyltransferase inhibitors: a structure-based pharmacophore modeling and molecular dynamics approach

Human nicotinamide N-methyltransferase (hNNMT) is a cytosolic enzyme associated in the phase-II metabolism, belonging to the S-adenosyl-L-methionine (SAM)-dependent methyltransferases family. Overexpression of hNNMT was observed in diseases such as metabolic disorders and different types of cancers, which suggest NNMT as a prospective therapeutic target. In this study we propose a structure-based pharmacophore model to understand the structural features responsible for the pharmacological activity. The generated model was validated using the ROC curve (AUC), goodness of hit score (GH), specificity, sensitivity and enrichment factor (EF). The pharmacophore was employed to retrieve active molecules from the ZINC database, followed by virtual-screening and molecular docking. Six molecules with the best pharmfit score, binding energy and ADMET properties were identified in this study. A 150 ns molecular dynamics simulation was performed on the selected molecules complexed with hNNMT protein to validate the results. The molecules ZINC35464499, ZINC13311192, ZINC31159282, ZINC14650833, ZINC14819515 and ZINC00303881 were identified, which could be act as the potential hNNMT inhibitors and can also be used as direct hits for developing novel hNNMT antagonists.Communicated by Ramaswamy H. Sarma.

Comparison of Local Metabolic Changes in Diabetic Rodent Kidneys Using Mass Spectrometry Imaging

Understanding the renal region-specific metabolic alteration in different animal models of diabetic nephropathy (DN) is critical for uncovering the underlying mechanisms and for developing effective treatments. In the present study, spatially resolved metabolomics based on air flow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI) was used to compare the local metabolic changes in the kidneys of HFD/STZ-induced diabetic rats and db/db mice. As a result, a total of 67 and 59 discriminating metabolites were identified and visualized in the kidneys of the HFD/STZ-induced diabetic rats and db/db mice, respectively. The result showed that there were significant region-specific changes in the glycolysis, TCA cycle, lipid metabolism, carnitine metabolism, choline metabolism, and purine metabolism in both DN models. However, the regional levels of the ten metabolites, including glucose, AMP, eicosenoic acid, eicosapentaenoic acid, Phosphatidylserine (36:1), Phosphatidylserine (36:4), Phosphatidylethanolamine (34:1), Phosphatidylethanolamine (36:4), Phosphatidylcholine (34:2), Phosphatidylinositol (38:5) were changed in reversed directions, indicating significant differences in the local metabolic phenotypes of these two commonly used DN animal models. This study provides comprehensive and in-depth analysis of the differences in the tissue and molecular pathological features in diabetic kidney injury in HFD/STZ-induced diabetic rats and db/db mice.

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.

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

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

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

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

A time differentiated dietary intervention effect on the biomarkers of exposure to pyrethroids and neonicotinoids pesticides

Tailoring medical models to the right person or risk subgroups delivered at the right time is important in personalized medicine/prevention initiatives. The CIRCA-CHEM randomized 2x2 crossover pilot trial investigated whether the consumption of fruits/vegetables within a time-restricted daily window would affect urinary biomarkers of exposure to neonicotinoids (6-chloronicotinic acid, 6-CN) and pyrethroids (3-phenoxybenzoic acid, 3-PBA) pesticides, a biomarker of oxidative damage (4-hydroxynonenal, 4-HNE) and the associated urinary NMR metabolome. A statistically significant difference (p < 0.001) in both creatinine-adjusted 6-CN and 3-PBA levels was observed between the two-time dietary intervention windows (morning vs. evening). In the evening intervention period, pesticides biomarker levels were higher compared to the baseline, whereas in the morning period, pesticide levels remained unchanged. Positive associations were observed between pesticides and 4-HNE suggesting a diurnal chrono-window of pesticide toxicity. The discovery of a chronotoxicity window associated with chrono-disrupted metabolism of food contaminants may find use in personalized medicine initiatives.

Effect of Acylated and Nonacylated Anthocyanins on Urine Metabolic Profile during the Development of Type 2 Diabetes in Zucker Diabetic Fatty Rats

The effect of nonacylated and acylated anthocyanins on urinary metabolites in diabetic rats was investigated. Nonacylated anthocyanins extract from bilberries (NAAB) or acylated anthocyanins extract from purple potatoes (AAPP) was given to Zucker diabetic fatty (ZDF) rats for 8 weeks at daily doses of 25 and 50 mg/kg body weight. ¹H NMR metabolomics was applied to study alterations in urinary metabolites from three time points (weeks 1, 4, and 8). Both types of anthocyanins modulated the metabolites associated with the tricarboxylic acid cycle, gut microbiota metabolism, and renal function at weeks 1 and 4, such as 2-oxoglutarate, fumarate, alanine, trigonelline, and hippurate. In addition, only a high dose of AAPP decreased monosaccharides, formate, lactate, and glucose levels at week 4, suggesting improvement in energy production in mitochondria, glucose homeostasis, and oxidative stress. This study suggested different impacts of AAPP and NAAB on the metabolic profile of urine in diabetes.

Problems, principles and progress in computational annotation of NMR metabolomics data

BACKGROUND

Compound identification remains a critical bottleneck in the process of exploiting Nuclear Magnetic Resonance (NMR) metabolomics data, especially for ¹H 1-dimensional (¹H 1D) data. As databases of reference compound spectra have grown, workflows have evolved to rely heavily on their search functions to facilitate this process by generating lists of potential metabolites found in complex mixture data, facilitating annotation and identification. However, approaches for validating and communicating annotations are most often guided by expert knowledge, and therefore are highly variable despite repeated efforts to align practices and define community standards.

AIM OF REVIEW

This review is aimed at broadening the application of automated annotation tools by discussing the key ideas of spectral matching and beginning to describe a set of terms to classify this information, thus advancing standards for communicating annotation confidence. Additionally, we hope that this review will facilitate the growing collaboration between chemical data scientists, software developers and the NMR metabolomics community aiding development of long-term software solutions.

KEY SCIENTIFIC CONCEPTS OF REVIEW

We begin with a brief discussion of the typical untargeted NMR identification workflow. We differentiate between annotation (hypothesis generation, filtering), and identification (hypothesis testing, verification), and note the utility of different NMR data features for annotation. We then touch on three parts of annotation: (1) generation of queries, (2) matching queries to reference data, and (3) scoring and confidence estimation of potential matches for verification. In doing so, we highlight existing approaches to automated and semi-automated annotation from the perspective of the structural information they utilize, as well as how this information can be represented computationally.

Dietary restriction and medical therapy drives PPARα-regulated improvements in early diabetic kidney disease in male rats

The attenuation of diabetic kidney disease (DKD) by metabolic surgery is enhanced by pharmacotherapy promoting renal fatty acid oxidation (FAO). Using the Zucker Diabetic Fatty and Zucker Diabetic Sprague Dawley rat models of DKD, we conducted studies to determine if these effects could be replicated with a non-invasive bariatric mimetic intervention. Metabolic control and renal injury were compared in rats undergoing a dietary restriction plus medical therapy protocol (DMT; fenofibrate, liraglutide, metformin, ramipril, and rosuvastatin) and ad libitum-fed controls. The global renal cortical transcriptome and urinary 1H-NMR metabolomic profiles were also compared. Kidney cell type-specific and medication-specific transcriptomic responses were explored through in silico deconvolution. Transcriptomic and metabolomic correlates of improvements in kidney structure were defined using a molecular morphometric approach. The DMT protocol led to ∼20% weight loss, normalized metabolic parameters and was associated with reductions in indices of glomerular and proximal tubular injury. The transcriptomic response to DMT was dominated by changes in fenofibrate- and peroxisome proliferator-activated receptor-α (PPARα)-governed peroxisomal and mitochondrial FAO transcripts localizing to the proximal tubule. DMT induced urinary excretion of PPARα-regulated metabolites involved in nicotinamide metabolism and reversed DKD-associated changes in the urinary excretion of tricarboxylic acid (TCA) cycle intermediates. FAO transcripts and urinary nicotinamide and TCA cycle metabolites were moderately to strongly correlated with improvements in glomerular and proximal tubular injury. Weight loss plus pharmacological PPARα agonism is a promising means of attenuating DKD.

NMR-based metabolic profiling of children with premature adrenarche

INTRODUCTION

Premature adrenarche (PA) for long time was considered a benign condition but later has been connected to various diseases in childhood and adulthood which remains controversial.

OBJECTIVE

To investigate the effect of premature adrenarche on the metabolic phenotype, and correlate the clinical and biochemical data with the metabolic profile of children with PA.

METHODS

Nuclear magnetic resonance (NMR)-based untargeted and targeted metabolomic approach in combination with multivariate and univariate statistical analysis applied to study the metabolic profiles of children with PA. Plasma, serum, and urine samples were collected from fifty-two children with Idiopathic PA and forty-eight age-matched controls from the division of Pediatric Endocrinology of the University Hospital of Patras were enrolled.

RESULTS

Metabolomic results showed that plasma and serum glucose, myo-inositol, amino acids, a population of unsaturated lipids, and esterified cholesterol were higher and significantly different in PA children. In the metabolic profiles of children with PA and age-matched control group a gradual increase of glucose and myo-inositol levels was observed in serum and plasma, which was positively correlated their body mass index standard deviation score (BMI SDS) values respectively. Urine ¹H NMR metabolic fingerprint of PA children showed positive correlation and a clustering-dependent relationship with their BMI and bone age (BA) respectively.

CONCLUSION

This study provides evidence that PA driven metabolic changes begin during the childhood and PA may has an inductive role in a BMI-driven increase of specific metabolites. Finally, urine may be considered as the best biofluid for identification of the PA metabolism as it reflects more clearly the PA metabolic fingerprint.

Urinary Metabolomics Study on the Protective Role of Cocoa in Zucker Diabetic Rats via 1H-NMR-Based Approach

Cocoa constitutes one of the richest sources of dietary flavonoids with demonstrated anti-diabetic potential. However, the metabolic impact of cocoa intake in a diabetic context remains unexplored. In this study, metabolomics tools have been used to investigate the potential metabolic changes induced by cocoa in type 2 diabetes (T2D). To this end, male Zucker diabetic fatty rats were fed on standard (ZDF) or 10% cocoa-rich diet (ZDF-C) from week 10 to 20 of life. Cocoa supplementation clearly decreased serum glucose levels, improved glucose metabolism and produced significant changes in the urine metabolome of ZDF animals. Fourteen differential urinary metabolites were identified, with eight of them significantly modified by cocoa. An analysis of pathways revealed that butanoate metabolism and the synthesis and degradation of branched-chain amino acids and ketone bodies are involved in the beneficial impact of cocoa on diabetes. Moreover, correlation analysis indicated major associations between some of these urine metabolites (mainly valine, leucine, and isoleucine) and body weight, glycemia, insulin sensitivity, and glycated hemoglobin levels. Overall, this untargeted metabolomics approach provides a clear metabolic fingerprint associated to chronic cocoa intake that can be used as a marker for the improvement of glucose homeostasis in a diabetic context.

Maternal Exercise and Paternal Exercise Induce Distinct Metabolite Signatures in Offspring Tissues

That maternal and paternal exercise improve the metabolic health of adult offspring is well established. Tissue and serum metabolites play a fundamental role in the health of an organism, but how parental exercise affects offspring tissue and serum metabolites has not yet been investigated. Here, male and female breeders were fed a high-fat diet and housed with or without running wheels before breeding (males) and before and during gestation (females). Offspring were sedentary and chow fed, with parents as follows: sedentary (Sed), maternal exercise (MatEx), paternal exercise (PatEx), or maternal+paternal exercise (Mat+PatEx). Adult offspring from all parental exercise groups had similar improvement in glucose tolerance and hepatic glucose production. Targeted metabolomics was performed in offspring serum, liver, and triceps muscle. Offspring from MatEx, PatEx, and Mat+PatEx each had a unique tissue metabolite signature, but Mat+PatEx offspring had an additive phenotype relative to MatEx or PatEx alone in a subset of liver and muscle metabolites. Tissue metabolites consistently indicated that the metabolites altered with parental exercise contribute to enhanced fatty acid oxidation. These data identify distinct tissue-specific adaptations and mechanisms for parental exercise-induced improvement in offspring metabolic health. Further mining of this data set could aid the development of novel therapeutic targets to combat metabolic diseases.

Washed microbiota transplantation improves patients with high blood glucose in South China

Background and Aims

Although fecal microbiota transplantation (FMT) from healthy donors has been shown to have hypoglycemic effects in animal models of diabetes, its clinical impact in patients with abnormal blood glucose metabolism is unclear, especially in southern Chinese populations. The aim of this study was to investigate the feasibility and efficacy of washed microbiota transplantation (WMT) in the treatment of abnormal blood glucose metabolism in a population in southern China.

Methods

The clinical data of patients with different indications who received 1-3 treatments of WMT were retrospectively collected. The changes of blood glucose, blood lipids, blood pressure, liver function and blood routine before and after WMT were compared, such as fasting blood glucose (FBG), glycosylated hemoglobin (HbA1c), total cholesterol (TC), triglyceride (TG), systolic blood pressure (SBP), white blood cells (WBC), lymphocytes (LY) and platelets (PLT), etc.

Results

A total of 195 patients were included in the First Affiliated Hospital of Guangdong Pharmaceutical University, including 20 patients with high blood glucose and 175 patients with normal blood glucose. WMT has a significant effect in reducing short term blood glucose level (FBG) in patients with high blood glucose (p < 0.05). The fasting blood glucose (FBG) of 72.22% of patients with high blood glucose decreased to normal in a short term (about 1 month) (p < 0.001); In the medium term (about 2 months), there was a significant hypolipidemic (TG) (p = 0.043) effect, long term (about 6 months) significant blood pressure lowering (SBP, p = 0.048) effect. Overall, WMT significantly reduced the risk of high risk classes of Atherosclerotic Cardiovascular Disease (ASCVD) in the short term (p = 0.029) and medium term (p = 0.050).

Conclusion

WMT can significantly improve blood glucose in patients with high blood glucose, and there is no long-term elevated risk of blood glucose and ASCVD. FBG levels were significantly reduced in both the short and medium term in patients with high blood glucose treated with WMT. Therefore, the regulation of gut microbiota by WMT may provide a new clinical approach for the treatment of abnormal blood glucose metabolism.

Age-related metabolic and neurodegenerative changes in SAMP8 mice

The most important risk factor for the development of sporadic Alzheimer's disease (AD) is ageing. Senescence accelerated mouse prone 8 (SAMP8) is a model of sporadic AD, with senescence accelerated resistant mouse (SAMR1) as a control. In this study, we aimed to determine the onset of senescence-induced neurodegeneration and the related potential therapeutic window using behavioral experiments, immunohistochemistry and western blotting in SAMP8 and SAMR1 mice at 3, 6 and 9 months of age. The Y-maze revealed significantly impaired working spatial memory of SAMP8 mice from the 6th month. With ageing, increasing plasma concentrations of proinflammatory cytokines in SAMP8 mice were detected as well as significantly increased astrocytosis in the cortex and microgliosis in the brainstem. Moreover, from the 3rd month, SAMP8 mice displayed a decreased number of neurons and neurogenesis in the hippocampus. From the 6th month, increased pathological phosphorylation of tau protein at Thr231 and Ser214 was observed in the hippocampi of SAMP8 mice. In conclusion, changes specific for neurodegenerative processes were observed between the 3rd and 6th month of age in SAMP8 mice; thus, potential neuroprotective interventions could be applied between these ages.

Novel tricyclic small molecule inhibitors of Nicotinamide N-methyltransferase for the treatment of metabolic disorders

Nicotinamide N-methyltransferase (NNMT) is a metabolic regulator that catalyzes the methylation of nicotinamide (Nam) using the co-factor S-adenosyl-L-methionine to form 1-methyl-nicotinamide (MNA). Overexpression of NNMT and the presence of the active metabolite MNA is associated with a number of diseases including metabolic disorders. We conducted a high-throughput screening campaign that led to the identification of a tricyclic core as a potential NNMT small molecule inhibitor series. Elaborate medicinal chemistry efforts were undertaken and hundreds of analogs were synthesized to understand the structure activity relationship and structure property relationship of this tricyclic series. A lead molecule, JBSNF-000028, was identified that inhibits human and mouse NNMT activity, reduces MNA levels in mouse plasma, liver and adipose tissue, and drives insulin sensitization, glucose modulation and body weight reduction in a diet-induced obese mouse model of diabetes. The co-crystal structure showed that JBSNF-000028 binds below a hairpin structural motif at the nicotinamide pocket and stacks between Tyr-204 (from Hairpin) and Leu-164 (from central domain). JBSNF-000028 was inactive against a broad panel of targets related to metabolism and safety. Interestingly, the improvement in glucose tolerance upon treatment with JBSNF-000028 was also observed in NNMT knockout mice with diet-induced obesity, pointing towards the glucose-normalizing effect that may go beyond NNMT inhibition. JBSNF-000028 can be a potential therapeutic option for metabolic disorders and developmental studies are warranted.

Evaluation of Hypoglycemic Activity and Sub-Acute Toxicity of the Novel Biochanin A–Chromium(III) Complex

The novel biochanin A–chromium(III) complex was synthesized by chelating chromium with biochanin A (BCA). The structure of the complex was determined and the complex ([CrBCA3]) was composed of chromium(III) and three ligands, and the chromium content was 55 μg/mg. The hypoglycemic activity of the complex was studied in db/db mice and C57 mice. The sub-acute toxicity test of the complex was carried out by the maximum limit method in KM mice. The hypoglycemic activity showed that the complex could reduce the weight of db/db mice and lower the fasting blood glucose and random blood glucose levels. The complex also improved the organ index, oral glucose tolerance test (OGTT) and insulin tolerance test (ITT) results of db/db mice, and some of the indicators were similar to those of the positive control group after treatment with the complex. The histopathology study showed significant improvements in the liver, kidney, pancreas and skeletal muscle compared with the diabetes model group. The complex also showed a significant improvement in serum biochemical indices and antioxidant enzyme activities, as well as glycogen levels. The sub-acute toxicity study showed that the complex did not cause death or any dangerous symptoms during the study. In addition, the sub-acute toxicity study showed that the complex had no significant effect on the serum biochemical indices, antioxidant capacity and organs of normal mice. This study showed that [CrBCA3] had good hypoglycemic activity in vivo and had no sub-acute toxicity. This work provides an important reference for the development of functional hypoglycemic foods or drugs.

Quantification of Gut Microbiota Dysbiosis-Related Organic Acids in Human Urine Using LC-MS/MS

Urine organic acid contains water-soluble metabolites and/or metabolites—derived from sugars, amino acids, lipids, vitamins, and drugs—which can reveal a human’s physiological condition. These urine organic acids—hippuric acid, benzoic acid, phenylacetic acid, phenylpropionic acid, 4-hydroxybenzoic acid, 4-hydroxyphenyl acetic acid, 3-hydroxyphenylpropionic acid, 3,4-dihydroxyphenyl propionic acid, and 3-indoleacetic acid—were the eligible candidates for the dysbiosis of gut microbiota. The aim of this proposal was to develop and to validate a liquid chromatography−tandem mass spectrometry (LC-MS/MS) bioanalysis method for the nine organic acids in human urine. Stable-labeled isotope standard (creatinine-d3) and acetonitrile were added to the urine sample. The supernatant was diluted with deionized water and injected into LC-MS/MS. This method was validated with high selectivity for the urine sample, a low limit of quantification (10−40 ng/mL), good linearity (r > 0.995), high accuracy (85.8−109.7%), and high precision (1.4−13.3%). This method simultaneously analyzed creatinine in urine, which calibrates metabolic rate between different individuals. Validation has been completed for this method; as such, it could possibly be applied to the study of gut microbiota clinically.

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

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

A Contemporary Insight of Metabolomics Approach for Type 1 Diabetes: Potential for Novel Diagnostic Targets

High-throughput omics has been widely applied in metabolic disease, type 1 diabetes (T1D) was one of the most typical diseases. Effective prevention and early diagnosis are very important because of infancy and persistent characteristics of T1D. The occurrence and development of T1D is a chronic and continuous process, in which the production of autoantibodies (ie serum transformation) occupies the central position. Metabolomics can evaluate the metabolic characteristics of serum before seroconversion, the changes with age and T1D complications. And the addition of natural drug metabolomics is more conducive to the systematic and comprehensive diagnosis and treatment of T1D. This paper reviewed the metabolic changes and main pathogenesis from pre-diagnosis to treatment in T1D. The metabolic spectrum of significant abnormal energy and glucose-related metabolic pathway, down-regulation of lipid metabolism and up-regulation of some antioxidant pathways has appeared before seroconversion, indicating that the body has been in the dual state of disease progression and disease resistance before T1D onset. Some metabolites (such as methionine) are closely related to age, and the types of autoantibodies produced are age-specific. Some metabolites may jointly predict DN with eGFR, and metabolomics can further contribute to the pathogenesis based on the correlation between DN and DR. Many natural drug components have been proved to act on abnormal metabolic pathways of T1D and have a positive impact on some metabolic levels, which is very important for further finding therapeutic targets and developing new drugs with small side effects. Metabolomics can provide auxiliary value for the diagnosis of T1D and provide a new direction to reveal the pathogenesis of T1D and find new therapeutic targets. The development of T1D metabolomics shows that high-throughput research methods are expected to be introduced into clinical practice.

Unraveling the Rewired Metabolism in Lung Cancer Using Quantitative NMR Metabolomics

Lung cancer cells are well documented to rewire their metabolism and energy production networks to enable proliferation and survival in a nutrient-poor and hypoxic environment. Although metabolite profiling of blood plasma and tissue is still emerging in omics approaches, several techniques have shown potential in cancer diagnosis. In this paper, the authors describe the alterations in the metabolic phenotype of lung cancer patients. In addition, we focus on the metabolic cooperation between tumor cells and healthy tissue. Furthermore, the authors discuss how metabolomics could improve the management of lung cancer patients.

Guide to Metabolomics Analysis: A Bioinformatics Workflow

Metabolomics is an emerging field that quantifies numerous metabolites systematically. The key purpose of metabolomics is to identify the metabolites corresponding to each biological phenotype, and then provide an analysis of the mechanisms involved. Although metabolomics is important to understand the involved biological phenomena, the approach's ability to obtain an exhaustive description of the processes is limited. Thus, an analysis-integrated metabolomics, transcriptomics, proteomics, and other omics approach is recommended. Such integration of different omics data requires specialized statistical and bioinformatics software. This review focuses on the steps involved in metabolomics research and summarizes several main tools for metabolomics analyses. We also outline the most abnormal metabolic pathways in several cancers and diseases, and discuss the importance of multi-omics integration algorithms. Overall, our goal is to summarize the current metabolomics analysis workflow and its main analysis software to provide useful insights for researchers to establish a preferable pipeline of metabolomics or multi-omics analysis.

Diet dependent impact of benzoate on diabetes and obesity in mice

The gut microbiota contributes to mammalian host biology by supplying metabolites from nutrients and pro-inflammatory molecules. We have recently shown that urinary hippurate is associated with reduced risk of obesity, increased gut microbiome diversity and gene richness, and functional modules for microbial production of its precursor benzoate. Obese mice infused with hippurate exhibit profound alterations of glucose homeostasis. Here, we tested the biological effects of chronic administration of benzoate on cardiometabolic phenotypes in lean and obese mice. Benzoate induced glucose intolerance, enhanced insulin secretion, increased adiposity and stimulated liver inflammation in lean mice fed control diet. In contrast, in condition of obesity and diabetes induced by high fat diet feeding, benzoate infusion resulted in reduction of glucose intolerance, stimulation of both glucose-induced insulin secretion and β-cell proliferation, and reduction of liver triglyceride and collagen accumulation. These results combined with those previously obtained in mice treated with hippurate underline the importance of the benzoate-hippurate pathway in cardiometabolic diseases and pave the way to diagnostic and therapeutic solutions.

Mass Spectrometry-Based Metabolomic and Lipidomic Analysis of the Effect of High Fat/High Sugar Diet and GreenshellTM Mussel Feeding on Plasma of Ovariectomized Rats

This study aimed to examine the changes in lipid and metabolite profiles of ovariectomized (OVX) rats with diet-induced metabolic syndrome-associated osteoarthritis (MetOA) after supplementation with greenshell mussel (GSM) using an untargeted liquid chromatography-mass spectrometry (LC-MS) metabolomics approach. Ninety-six rats were fed with one of four diets: control, control supplemented with GSM + GSM, high fat/high sugar (HFHS), or high fat/high sugar enriched with GSM (HFHS + GSM). After 8 weeks on experimental diets, half of the rats in each group underwent OVX and the other half were sham operated. After being fed for an additional 28 weeks, blood samples were collected for the metabolomics analysis. Lipid and polar metabolites were extracted from plasma and analysed by LC-MS. We identified 29 lipid species from four lipid subclasses (phosphatidylcholine, lysophosphatidylcholine, diacylglycerol, and triacylglycerol) and a set of eight metabolites involved in amino acid metabolism (serine, threonine, lysine, valine, histidine, pipecolic acid, 3-methylcytidine, and cholic acid) as potential biomarkers for the effect of HFHS diet and GSM supplementation. GSM incorporation more specifically in the control diet generated significant alterations in the levels of several lipids and metabolites. Further studies are required to validate these findings that identify potential biomarkers to follow OA progression and to monitor the impact of GSM supplementation.

Serum and Amniotic Fluid Metabolic Profile Changes in Response to Gestational Diabetes Mellitus and the Association with Maternal-Fetal Outcomes

This study was designed to identify serum and amniotic fluid (AF) metabolic profile changes in response to gestational diabetes mellitus (GDM) and explore the association with maternal-fetal outcomes. We established the GDM rat models by combining a high-fat diet (HFD) with an injection of low-dose streptozotocin (STZ), detected the fasting plasma glucose (FPG) of pregnant rats in the second and third trimester, and collected AF and fetal rats by cesarean section on gestational day 19 (GD19), as well as measuring the weight and crown-rump length (CRL) of fetal rats. We applied liquid chromatography-tandem mass spectrometry (LC-MS/MS) for the untargeted metabolomics analyses of serum and AF samples and then explored their correlation with maternal-fetal outcomes via the co-occurrence network. The results showed that 91 and 68 metabolites were upregulated and 125 and 78 metabolites were downregulated in serum and AF samples exposed to GDM, respectively. In maternal serum, the obvious alterations emerged in lipids and lipid-like molecules, while there were great changes in carbohydrate and carbohydrate conjugates, followed by amino acids, peptides, and analogs in amniotic fluid. The altered pathways both in serum and AF samples were amino acid, lipid, nucleotide, and vitamin metabolism pathways. In response to GDM, changes in the steroid hormone metabolic pathway occurred in serum, and an altered carbohydrate metabolism pathway was found in AF samples. Among differential metabolites in two kinds of samples, there were 34 common biochemicals shared by serum and AF samples, and a mutual significant association existed. These shared differential metabolites were implicated in several metabolism pathways, including choline, tryptophan, histidine, and nicotinate and nicotinamide metabolism, and among them, N1-methyl-4-pyridone-3-carboxamide, 5'-methylthioadenosine, and kynurenic acid were significantly associated with both maternal FPG and fetal growth. In conclusion, serum and AF metabolic profiles were remarkably altered in response to GDM. N1-Methyl-4-pyridone-3-carboxamide, 5'-methylthioadenosine, and kynurenic acid have the potential to be taken as biomarkers for maternal-fetal health status of GDM. The common and inter-related differential metabolites both in the serum and AF implied the feasibility of predicting fetal health outcomes via detecting the metabolites in maternal serum exposed to GDM.

Combined Untargeted and Targeted Metabolomics Approaches Reveal Urinary Changes of Amino Acids and Energy Metabolism in Canine Babesiosis With Different Levels of Kidney Function

Canine babesiosis is a tick-borne disease with a worldwide distribution, caused by the haemoprotozoan parasites of the genus Babesia. One of the most prevalent complication is acute kidney injury, and an early diagnosis of altered kidney function remains a challenge for veterinary practice. The aim of this study was to assess the urine metabolic profile from dogs with babesiosis and different degree of kidney function using untargeted and targeted MS-based metabolomics approaches. In this study, 22 dogs naturally infected with Babesia canis and 12 healthy dogs were included. Untargeted metabolomics approach identified 601 features with a differential abundance between the healthy group and groups of dogs with babesiosis and different level of kidney function, with 27 of them identified as a match to known standards; while targeted approach identified 17 metabolites with significantly different concentrations between the groups. A pattern of significantly altered metabolites referring to the inflammatory host response, oxidative stress, and energy metabolism modulation in babesiosis was presented. Our findings have demonstrated that kidney dysfunction accompanying canine babesiosis was associated with changes in amino acid metabolism, energy metabolism, fatty acid metabolism, and biochemical pathways such as urea cycle and ammonia detoxication. These findings will enable the inclusion of urinary markers for the detection and monitoring of renal damage in babesiosis, as well as in other similar diseases.