Metabolomics analysis reveals altered metabolites in lean compared with obese adolescents and additional metabolic shifts associated with hyperinsulinaemia and insulin resistance in obese adolescents: a cross-sectional study

Characterizing human postprandial metabolic response using multiway data analysis

INTRODUCTION

Analysis of time-resolved postprandial metabolomics data can improve our understanding of the human metabolism by revealing similarities and differences in postprandial responses of individuals. Traditional data analysis methods often rely on data summaries or univariate approaches focusing on one metabolite at a time.

OBJECTIVES

Our goal is to provide a comprehensive picture in terms of the changes in the human metabolism in response to a meal challenge test, by revealing static and dynamic markers of phenotypes, i.e., subject stratifications, related clusters of metabolites, and their temporal profiles.

METHODS

We analyze Nuclear Magnetic Resonance (NMR) spectroscopy measurements of plasma samples collected during a meal challenge test from 299 individuals from the COPSAC2000 cohort using a Nightingale NMR panel at the fasting and postprandial states (15, 30, 60, 90, 120, 150, 240 min). We investigate the postprandial dynamics of the metabolism as reflected in the dynamic behaviour of the measured metabolites. The data is arranged as a three-way array: subjects by metabolites by time. We analyze the fasting state data to reveal static patterns of subject group differences using principal component analysis (PCA), and fasting state-corrected postprandial data using the CANDECOMP/PARAFAC (CP) tensor factorization to reveal dynamic markers of group differences.

RESULTS

Our analysis reveals dynamic markers consisting of certain metabolite groups and their temporal profiles showing differences among males according to their body mass index (BMI) in response to the meal challenge. We also show that certain lipoproteins relate to the group difference differently in the fasting vs. dynamic state. Furthermore, while similar dynamic patterns are observed in males and females, the BMI-related group difference is observed only in males in the dynamic state.

CONCLUSION

The CP model is an effective approach to analyze time-resolved postprandial metabolomics data, and provides a compact but a comprehensive summary of the postprandial data revealing replicable and interpretable dynamic markers crucial to advance our understanding of changes in the metabolism in response to a meal challenge.

Polysaccharides from Dendrobium officinale improve obesity-induced insulin resistance through the gut microbiota and the SOCS3-mediated insulin receptor substrate-1 signaling pathway

BACKGROUND

Obesity induces insulin resistance and chronic inflammation, impacting human health. The relationship between obesity, gut microbiota, and regulatory mechanisms has been studied extensively. Dendrobium officinale polysaccharide (DOP), a traditional Chinese herbal medicine, potentially reduces insulin resistance. However, the mechanism through which DOP affects gut microbiota and alleviates obesity-induced insulin resistance in rats requires further investigation.

RESULTS

The current study aimed to assess the impact of DOP on gut microbiota and insulin resistance in rats on a high-fat diet. The results revealed that DOP effectively reduced blood lipids, glucose disorders, oxidative stress, and inflammatory infiltration in the liver of obese Sprague Dawley rats. This was achieved by downregulating SOCS3 expression and upregulating insulin receptor substrate-1 (IRS-1) by regulating the JAK/STAT/SOCS3 signaling pathway. Notably, DOP intervention enhanced the abundance of beneficial gut microbiota and reduced harmful microbiota. Correlation analysis demonstrated significant associations among intestinal microbiota, SOCS3-mediated IRS-1 expression, and inflammatory factors.

CONCLUSION

Dendrobium officinale polysaccharide regulated the gut microbiota, enhanced IRS-1 expression, and mitigated liver injury and insulin resistance due to a high-fat diet. These findings depict the potential anti-insulin resistance properties of DOP and offer further evidence for addressing obesity and its complications. © 2023 Society of Chemical Industry.

Impacts of glutamate, an exercise-responsive metabolite on insulin signaling

AIMS

Disruption of the insulin signaling pathway leads to insulin resistance (IR). IR is characterized by impaired glucose and lipid metabolism. Elevated levels of circulating glutamate are correlated with metabolic indicators and may potentially predict the onset of metabolic diseases. Glutamate receptor antagonists have significantly enhanced insulin sensitivity, and improved glucose and lipid metabolism. Exercise is a well-known strategy to combat IR. The aims of our narrative review are to summarize preclinical and clinical findings to show the correlations between circulating glutamate levels, IR and metabolic diseases, discuss the causal role of excessive glutamate in IR and metabolic disturbance, and present an overview of the exercise-induced alteration in circulating glutamate levels.

MATERIALS AND METHODS

A literature search was conducted to identify studies on glutamate, insulin signaling, and exercise in the PubMed database. The search covered articles published from December 1955 to January 2024, using the search terms of "glutamate", "glutamic acid", "insulin signaling", "insulin resistance", "insulin sensitivity", "exercise", and "physical activity".

KEY FINDINGS

Elevated levels of circulating glutamate are correlated with IR. Excessive glutamate can potentially hinder the insulin signaling pathway through various mechanisms, including the activation of ectopic lipid accumulation, inflammation, and endoplasmic reticulum stress. Glutamate can also modify mitochondrial function through Ca2+ and induce purine degradation mediated by AMP deaminase 2. Exercise has the potential to decrease circulating levels of glutamate, which can be attributed to accelerated glutamate catabolism and enhanced glutamate uptake.

SIGNIFICANCE

Glutamate may act as a mediator in the exercise-induced improvement of insulin sensitivity.

Analyzing postprandial metabolomics data using multiway models: a simulation study

BACKGROUND

Analysis of time-resolved postprandial metabolomics data can improve the understanding of metabolic mechanisms, potentially revealing biomarkers for early diagnosis of metabolic diseases and advancing precision nutrition and medicine. Postprandial metabolomics measurements at several time points from multiple subjects can be arranged as a subjects by metabolites by time points array. Traditional analysis methods are limited in terms of revealing subject groups, related metabolites, and temporal patterns simultaneously from such three-way data.

RESULTS

We introduce an unsupervised multiway analysis approach based on the CANDECOMP/PARAFAC (CP) model for improved analysis of postprandial metabolomics data guided by a simulation study. Because of the lack of ground truth in real data, we generate simulated data using a comprehensive human metabolic model. This allows us to assess the performance of CP models in terms of revealing subject groups and underlying metabolic processes. We study three analysis approaches: analysis of fasting-state data using principal component analysis, T0-corrected data (i.e., data corrected by subtracting fasting-state data) using a CP model and full-dynamic (i.e., full postprandial) data using CP. Through extensive simulations, we demonstrate that CP models capture meaningful and stable patterns from simulated meal challenge data, revealing underlying mechanisms and differences between diseased versus healthy groups.

CONCLUSIONS

Our experiments show that it is crucial to analyze both fasting-state and T0-corrected data for understanding metabolic differences among subject groups. Depending on the nature of the subject group structure, the best group separation may be achieved by CP models of T0-corrected or full-dynamic data. This study introduces an improved analysis approach for postprandial metabolomics data while also shedding light on the debate about correcting baseline values in longitudinal data analysis.

Metabolomics profiling of maternal and umbilical cord blood in normoglycemia macrosomia

Background: Macrosomia is a common disorder that occurs during pregnancy. We investigated the comprehensive metabolite profiles of pregnant maternal and fetal sera in normoglycemic macrosomia in a Chinese population. Methods: Forty pregnant women and their fetuses were included in the study (twenty macrosomia patients and twenty normal-weight controls). Maternal and umbilical cord serum metabolites were identified using ultra-performance liquid chromatography coupled with tandem mass spectrometry. Results: In total, 203 metabolites were identified. Lipids and lipid-like molecules were the predominant metabolites. Fifty-three metabolites with significant differences were obtained in the maternal samples. In the macrosomia group, the levels of docosahexaenoic acid, eicosapentaenoic acid, and arachidonic acid were significantly higher than those in the control group. Umbilical cord serum samples were obtained for 24 different metabolites. The maternal-fetal gradient of polyunsaturated fatty acids was decreased in the macrosomia group. Aconitic acid, citric acid, isocitric acid, 2-methylhexanoic acid, and 12-hydroxystearic acid were the common differential metabolites in the maternal and umbilical cord serum samples. Conclusion: There were obvious metabolic abnormalities in the sera of pregnant women and fetuses with macrosomia. Lipids and lipid-like molecules were the predominant differential metabolites but had different classifications in the maternal and umbilical cord serum. These results may provide new insights into the long-term metabolic disorders associated with macrosomia.

Serum metabolomics profiling by proton nuclear magnetic resonance spectrometry of the response to single oral macronutrient challenges in women with polycystic ovary syndrome (PCOS) compared with male and female controls

BACKGROUND

The polycystic ovary syndrome (PCOS) is associated with insulin resistance, obesity and cardiometabolic comorbidities. We here challenged the hypothesis, using state-of-the-art proton nuclear magnetic resonance spectrometry (1H-NMRS) metabolomics profiling, that androgen excess in women induces a certain masculinization of postprandial metabolism that is modulated by obesity.

MATERIALS AND METHODS

Participants were 53 Caucasian young adults, including 17 women with classic PCOS consisting of hyperandrogenism and ovulatory dysfunction, 17 non-hyperandrogenic women presenting with regular menses, and 19 healthy men, selected to be similar in terms of age and body mass index (BMI). Half of the subjects had obesity. Patients were submitted to isocaloric separate glucose, lipid and protein oral challenges in alternate days and fasting and postprandial serum samples were submitted to 1H-NMRS metabolomics profiling for quantification of 36 low-molecular-weight polar metabolites.

RESULTS

The largest postprandial changes were observed after glucose and protein intake, with lipid ingestion inducing smaller differences. Changes after glucose intake consisted of a marked increase in carbohydrates and byproducts of glycolysis, and an overall decrease in byproducts of proteolysis, lipolysis and ketogenesis. After the protein load, most amino acids and derivatives increased markedly, in parallel to an increase in pyruvate and a decrease in 3-hydroxybutyric acid and glycerol. Obesity increased β- and D-glucose and pyruvate levels, with this effect being observed mostly after glucose ingestion in women with PCOS. Regardless of the type of macronutrient, men presented increased lysine and decreased 3-hydroxybutyric acid. In addition, non-obese men showed increased postprandial β-glucose and decreased pyroglutamic acid, compared with non-obese control women. We observed a common pattern of postprandial changes in branched-chain and aromatic amino acids, where men showed greater amino acids increases after protein intake than control women and patients with PCOS but only within the non-obese participants. Conversely, this increase was blunted in obese men but not in obese women, who even presented a larger increase in some amino acids compared with their non-obese counterparts. Interestingly, regardless of the type of macronutrient, only obese women with PCOS showed increased leucine, lysine, phenylalanine and tryptophan levels compared with non-obese patients.

CONCLUSIONS

Serum 1H-NMRS metabolomics profiling indicated sexual dimorphism in the responses to oral macronutrient challenges, which were apparently driven by the central role of postprandial insulin effects with obesity, and to a lesser extent PCOS, exerting modifying roles derived from insulin resistance. Hence, obesity impaired metabolic flexibility in young adults, yet sex and sex hormones also influenced the regulation of postprandial metabolism.

Metabolomics in archaeological science: A review of their advances and present requirements

Metabolomics, the study of metabolites (small molecules of <1500 daltons), has been posited as a potential tool to explore the past in a comparable manner to other omics, e.g., genomics or proteomics. Archaeologists have used metabolomic approaches for a decade or so, mainly applied to organic residues adhering to archaeological materials. Because of advances in sensitivity, resolution, and the increased availability of different analytical platforms, combined with the low mass/volume required for analysis, metabolomics is now becoming a more feasible choice in the archaeological sector. Additional approaches, as presented by our group, show the versatility of metabolomics as a source of knowledge about the human past when using human osteoarchaeological remains. There is tremendous potential for metabolomics within archaeology, but further efforts are required to position it as a routine technique.

Salivary Metabolomic Signatures and Body Mass Index in Italian Adolescents: A Pilot Study

Context

Obesity surveillance is scarce in adolescents, and little is known on whether salivary metabolomics data, emerging minimally invasive biomarkers, can characterize metabolic patterns associated with overweight or obesity in adolescents.

Objective

This pilot study aims to identify the salivary molecular signatures associated with body mass index (BMI) in Italian adolescents.

Methods

Saliva samples and BMI were collected in a subset of n = 74 young adolescents enrolled in the Public Health Impact of Metal Exposure study (2007-2014). A total of 217 untargeted metabolites were identified using liquid chromatography-high resolution mass spectrometry. Robust linear regression was used to cross-sectionally determine associations between metabolomic signatures and sex-specific BMI-for-age z-scores (z-BMI).

Results

Nearly 35% of the adolescents (median age: 12 years; 51% females) were either obese or overweight. A higher z-BMI was observed in males compared to females (P = .02). One nucleoside (deoxyadenosine) and 2 lipids (18:0-18:2 phosphatidylcholine and dipalmitoyl-phosphoethanolamine) were negatively related to z-BMI (P < .05), whereas 2 benzenoids (3-hydroxyanthranilic acid and a phthalate metabolite) were positively associated with z-BMI (P < .05). In males, several metabolites including deoxyadenosine, as well as deoxycarnitine, hyodeoxycholic acid, N-methylglutamic acid, bisphenol P, and trigonelline were downregulated, while 3 metabolites (3-hydroxyanthranilic acid, theobromine/theophylline/paraxanthine, and alanine) were upregulated in relation to z-BMI (P < .05). In females, deoxyadenosine and dipalmitoyl-phosphoethanolamine were negatively associated with z-BMI while deoxycarnitine and a phthalate metabolite were positively associated (P < .05). A single energy-related pathway was enriched in the identified associations in females (carnitine synthesis, P = .04).

Conclusion

Salivary metabolites involved in nucleotide, lipid, and energy metabolism were primarily altered in relation to BMI in adolescents.

Sulfur X-ray Absorption and Emission Spectroscopy of Organic Sulfones

The sulfones are a widespread group of organo-sulfur compounds, which contain the sulfonyl SO₂ group attached to two carbons and have a formal sulfur oxidation state of +2. We have examined the sulfur K near-edge X-ray absorption spectroscopy (XAS) of a range of different sulfones and find substantial spectroscopic variability depending upon the nature of the coordination to the sulfonyl group. We have also examined the sulfur Kβ X-ray emission spectroscopy (XES) of selected representative sulfones. Density functional theory simulations show satisfactory reproduction of both absorption and emission spectra while enabling assignment of the various transitions comprising the spectra. The correspondence between observed and simulated spectra shows promise for ab initio prediction of sulfur X-ray absorption and emission spectra of sulfones of any substituent. The absorption spectra and, to a lesser extent, the emission spectra are sensitive to the nature of the organic groups bound to the sulfonyl (SO₂) moiety, clearly showing the potential of X-ray spectroscopy as an in situ probe of sulfone chemistry.

Genetic variants in ALDH1L1 and GLDC influence the serine-to-glycine ratio in Hispanic children

BACKGROUND

Glycine is a proteogenic amino acid that is required for numerous metabolic pathways, including purine, creatine, heme, and glutathione biosynthesis. Glycine formation from serine, catalyzed by serine hydroxy methyltransferase, is the major source of this amino acid in humans. Our previous studies in a mouse model have shown a crucial role for the 10-formyltetrahydrofolate dehydrogenase enzyme in serine-to-glycine conversion.

OBJECTIVES

We sought to determine the genomic influence on the serine-glycine ratio in 803 Hispanic children from 319 families of the Viva La Familia cohort.

METHODS

We performed a genome-wide association analysis for plasma serine, glycine, and the serine-glycine ratio in Sequential Oligogenic Linkage Analysis Routines while accounting for relationships among family members.

RESULTS

All 3 parameters were significantly heritable (h2 = 0.22-0.78; P < 0.004). The strongest associations for the serine-glycine ratio were with single nucleotide polymorphisms (SNPs) in aldehyde dehydrogenase 1 family member L1 (ALDH1L1) and glycine decarboxylase (GLDC) and for glycine with GLDC (P < 3.5 × 10-8; effect sizes, 0.03-0.07). No significant associations were found for serine. We also conducted a targeted genetic analysis with ALDH1L1 exonic SNPs and found significant associations between the serine-glycine ratio and rs2886059 (β = 0.68; SE, 0.25; P = 0.006) and rs3796191 (β = 0.25; SE, 0.08; P = 0.003) and between glycine and rs3796191 (β = -0.08; SE, 0.02; P = 0.0004). These exonic SNPs were further associated with metabolic disease risk factors, mainly adiposity measures (P < 0.006). Significant genetic and phenotypic correlations were found for glycine and the serine-glycine ratio with metabolic disease risk factors, including adiposity, insulin sensitivity, and inflammation-related phenotypes [estimate of genetic correlation = -0.37 to 0.35 (P < 0.03); estimate of phenotypic correlation = -0.19 to 0.13 (P < 0.006)]. The significant genetic correlations indicate shared genetic effects among glycine, the serine-glycine ratio, and adiposity and insulin sensitivity phenotypes.

CONCLUSIONS

Our study suggests that ALDH1L1 and GLDC SNPs influence the serine-to-glycine ratio and metabolic disease risk.

Investigating the Postprandial Metabolome after Challenge Tests to Assess Metabolic Flexibility and Dysregulations Associated with Cardiometabolic Diseases

This review focuses on the added value provided by a research strategy applying metabolomics analyses to assess phenotypic flexibility in response to different nutritional challenge tests in the framework of metabolic clinical studies. We discuss findings related to the Oral Glucose Tolerance Test (OGTT) and to mixed meals with varying fat contents and food matrix complexities. Overall, the use of challenge tests combined with metabolomics revealed subtle metabolic dysregulations exacerbated during the postprandial period when comparing healthy and at cardiometabolic risk subjects. In healthy subjects, consistent postprandial metabolic shifts driven by insulin action were reported (e.g., a switch from lipid to glucose oxidation for energy fueling) with similarities between OGTT and mixed meals, especially during the first hours following meal ingestion while differences appeared in a wider timeframe. In populations with expected reduced phenotypic flexibility, often associated with increased cardiometabolic risk, a blunted response on most key postprandial pathways was reported. We also discuss the most suitable statistical tools to analyze the dynamic alterations of the postprandial metabolome while accounting for complexity in study designs and data structure. Overall, the in-depth characterization of the postprandial metabolism and associated phenotypic flexibility appears highly promising for a better understanding of the onset of cardiometabolic diseases.

Omics era in type 2 diabetes: From childhood to adulthood

Parallel to the dramatic rise of pediatric obesity, estimates reported an increased prevalence of type 2 diabetes (T2D) already in childhood. The close relationship between obesity and T2D in children is mainly sustained by insulin resistance (IR). In addition, the cardiometabolic burden of T2D including nonalcoholic fatty liver disease, cardiovascular disease and metabolic syndrome is also strictly related to IR. Although T2D pathophysiology has been largely studied in an attempt to improve therapeutic options, molecular mechanisms are still not fully elucidated. In this perspective, omics approaches (including lipidomics, metabolomics, proteomics and metagenomics) are providing the most attractive therapeutic options for T2D. In particular, distinct both lipids and metabolites are emerging as potential therapeutic tools. Of note, among lipid classes, the pathogenic role of ceramides in T2D context has been supported by several data. Thus, selective changes of ceramides expression might represent innovative therapeutic strategies for T2D treatment. More, distinct metabolomics pathways have been also found to be associated with higher T2D risk, by providing novel potential T2D biomarkers. Taken together, omics data are responsible for the expanding knowledge of T2D pathophysiology, by providing novel insights to improve therapeutic strategies for this tangled disease. We aimed to summarize the most recent evidence in the intriguing field of the omics approaches in T2D both in adults and children.

Imaging with [99mTc]HMPAO - a novel perspective: investigation of [99mTc]HMPAO leg muscle uptake in metabolic diseases

BACKGROUND

Sensitive imaging modalities in the diagnosis of microcircular complications of the lower extremities induced by metabolic diseases are becoming a focus of interest.

PURPOSE

To investigate the [^99mTc]HMPAO uptake of the legs in type 2 diabetes mellitus (T2DM) and obesity, and to search for associations with clinical parameters and nerve conducting studies.

MATERIAL AND METHODS

A total of 57 patients with controlled T2DM and 46 obese participants without DM were enrolled in the study. [^99mTc]HMPAO SPECT/CT examinations were performed to evaluate the radiopharmaceutical accumulation of the legs. For the quantitative assessment of tracer uptake, standardized uptake value (SUV_peak) was measured in fixed spheric volumes of interest placed on both sural muscles on the attenuation-corrected images. Measurement of current perception threshold applying Neurometer (NM-01/CPT) was used to evaluate peripheral nerve dysfunction. Laboratory parameters assessing the glucose homeostasis of the study participants were also measured.

RESULTS

In the diabetic group, significantly lower leg SUV values were detected compared to the non-DM obese group (median: 0.517 vs. 0.607; P < 0.001). Body mass index (BMI) (P < 0.0001), age (P = 0.0283), HbA1c (P = 0.0068), and glucose level (P = 0.0044) proved to be significant predictors of muscle tracer uptake. Neurometer studies showed positive correlation with HbA1c levels in the T2DM group (P = 0.0002).

CONCLUSION

We assume that [^99mTc]HMPAO uptake of leg muscles is associated with microcirculation, so quantitative [^99mTc]HMPAO SPECT/CT might be a sensitive method for evaluating lower limb microvascular alterations. BMI, age, HbA1c, and glucose level may be significant predictors of peripheral vascular abnormalities triggered by metabolic disturbances.

Comparing the Fasting and Random-Fed Metabolome Response to an Oral Glucose Tolerance Test in Children and Adolescents: Implications of Sex, Obesity, and Insulin Resistance

As the incidence of obesity and type 2 diabetes (T2D) is occurring at a younger age, studying adolescent nutrient metabolism can provide insights on the development of T2D. Metabolic challenges, including an oral glucose tolerance test (OGTT) can assess the effects of perturbations in nutrient metabolism. Here, we present alterations in the global metabolome in response to an OGTT, classifying the influence of obesity and insulin resistance (IR) in adolescents that arrived at the clinic fasted and in a random-fed state. Participants were recruited as lean (n = 55, aged 8–17 years, BMI percentile 5–85%) and overweight and obese (OVOB, n = 228, aged 8–17 years, BMI percentile ≥ 85%). Untargeted metabolomics profiled 246 annotated metabolites in plasma at t0 and t60 min during the OGTT. Our results suggest that obesity and IR influence the switch from fatty acid (FA) to glucose oxidation in response to the OGTT. Obesity was associated with a blunted decline of acylcarnitines and fatty acid oxidation intermediates. In females, metabolites from the Fasted and Random-Fed OGTT were associated with HOMA-IR, including diacylglycerols, leucine/isoleucine, acylcarnitines, and phosphocholines. Our results indicate that at an early age, obesity and IR may influence the metabolome dynamics in response to a glucose challenge.

Correlation of Plasma Amino Acid and Anthropometric Profiles with Brown Adipose Tissue Density in Humans

This study examined the relationship between plasma amino acid (AA) concentrations, including branched-chain AAs, and brown adipose tissue density (BAT-d). One hundred and seventy-three subjects (69 men, 104 women) aged 22-68 years were recruited during the winter season. AAs were comprehensively quantified using liquid chromatography-time-of-flight-mass spectrometry. The total hemoglobin concentration in the supraclavicular region ([total-Hb]sup), an indicator of BAT-d, was assessed using near-infrared time-resolved spectroscopy. Anthropometric parameters, including age, percentage of body fat, and visceral fat, were evaluated. Factors associated with higher (≥74 µM) or lower (<74 µM) [total-Hb]sup were investigated by multiple logistic regression models that included AA concentrations alone (model 1) or AA concentrations and anthropometric parameters (model 2) as independent variables. When adjusted for the false discovery rate, [total-Hb]sup was positively correlated with glycine and asparagine levels in men and with the serine level in both men and women and was negatively correlated with the branched-chain AA concentration in men. Models 1 and 2 correlated with higher or lower BAT-d for men (r = 0.73, p = 0.015) and women (r = 0.58, p = 0.079) and for men (r = 0.82, p = 0.0070) and women (r = 0.70, p = 0.020), respectively. A combination of anthropometric parameters and plasma AA concentrations could be a reliable biomarker for higher and lower BAT-d.