Identification of Metabolic Phenotypes in Young Adults with Obesity by 1H NMR Metabolomics of Blood Serum

Obesity and cardiovascular disease: Risk assessment, physical activity, and management of complications

The patient with obesity is at risk of developing cardiovascular disease and risk factors. Obesity negatively impacts prognosis and increases cardiovascular morbidity and mortality. Therefore, a comprehensive risk assessment is needed to define the cardiovascular risk of the patient and, thus, a tailored management and treatment. Chronic and successful management of these patients involves the evaluation of the various therapeutic strategies available (comprehensive lifestyle intervention, weight-loss medications, and bariatric surgery) and the diagnosis and treatment of cardiovascular complications (coronary artery disease, heart failure, and atrial fibrillation). Cardiac rehabilitation in patients with obesity is showing beneficial effect and a positive impact on weight loss, cardiovascular risk factors, mental health, functional capacity, and adherence to lifestyle interventions and pharmacological treatment. Long-term weight loss and maintenance represent a key objective during the management of the patient with obesity to reduce the risk of future adverse events. Multidisciplinary management and interventions are necessary to prevent and reduce overall cardiovascular risk and mortality. The aim of our review is to propose a comprehensive, critical and updated overview regarding risk assessment, physical activity, and the management of cardiovascular complications in patient with obesity.

Sarcosine, Trigonelline and Phenylalanine as Urinary Metabolites Related to Visceral Fat in Overweight and Obesity

The objective of the present study is to analyze the urinary metabolome profile of patients with obesity and overweight and relate it to different obesity profiles. This is a prospective, cross-sectional study in which patients with a body mass index (BMI) ≥25 kg/m were selected. Anthropometric data were assessed by physical examination and body composition was obtained by bioimpedance (basal metabolic rate, body fat percentile, skeletal muscle mass, gross fat mass and visceral fat). Urine was collected for metabolomic analysis. Patients were classified according to abdominal circumference measurements between 81 and 93, 94 and 104, and >104 cm; visceral fat up to 16 kilos and less than; and fat percentiles of <36%, 36-46% and >46%. Spectral alignment of urinary metabolite signals and bioinformatic analysis were carried out to select the metabolites that stood out. NMR spectrometry was used to detect and quantify the main urinary metabolites and to compare the groups. Seventy-five patients were included, with a mean age of 38.3 years, and 72% females. The urinary metabolomic profile showed no differences in BMI, abdominal circumference and percentage of body fat. Higher concentrations of trigonelline (p = 0.0488), sarcosine (p = 0.0350) and phenylalanine (p = 0.0488) were associated with patients with visceral fat over 16 kg. The cutoff points obtained by the ROC curves were able to accurately differentiate between patients according to the amount of visceral fat: sarcosine 0.043 mg/mL; trigonelline 0.068 mg/mL and phenylalanine 0.204 mg/mL. In conclusion, higher visceral fat was associated with urinary levels of metabolites such as sarcosine, related to insulin resistance; trigonelline, related to muscle mass and strength; and phenylalanine, related to glucose metabolism and abdominal fat. Trigonelline, sarcosine and phenylalanine play significant roles in regulating energy balance and metabolic pathways essential for controlling obesity. Our findings could represent an interesting option for the non-invasive estimation of visceral fat through biomarkers related to alterations in metabolic pathways involved in the pathophysiology of obesity.

Untargeted metabolomics reveal signatures of a healthy lifestyle

This cross-sectional study investigated differences in the plasma metabolome in two groups of adults that were of similar age but varied markedly in body composition and dietary and physical activity patterns. Study participants included 52 adults in the lifestyle group (LIFE) (28 males, 24 females) and 52 in the control group (CON) (27 males, 25 females). The results using an extensive untargeted ultra high-performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS) metabolomics analysis with 10,535 metabolite peaks identified 486 important metabolites (variable influence on projections scores of VIP ≥ 1) and 16 significantly enriched metabolic pathways that differentiated LIFE and CON groups. A novel metabolite signature of positive lifestyle habits emerged from this analysis highlighted by lower plasma levels of numerous bile acids, an amino acid profile characterized by higher histidine and lower glutamic acid, glutamine, β-alanine, phenylalanine, tyrosine, and proline, an elevated vitamin D status, higher levels of beneficial fatty acids and gut microbiome catabolism metabolites from plant substrates, and reduced levels of N-glycan degradation metabolites and environmental contaminants. This study established that the plasma metabolome is strongly associated with body composition and lifestyle habits. The robust lifestyle metabolite signature identified in this study is consistent with an improved life expectancy and a reduced risk for chronic disease.

Effect of the gut microbiome, plasma metabolome, peripheral cells, and inflammatory cytokines on obesity: a bidirectional two-sample Mendelian randomization study and mediation analysis

Background

Obesity is a metabolic and chronic inflammatory disease involving genetic and environmental factors. This study aimed to investigate the causal relationship among gut microbiota abundance, plasma metabolomics, peripheral cell (blood and immune cell) counts, inflammatory cytokines, and obesity.

Methods

Summary statistics of 191 gut microbiota traits (N = 18,340), 1,400 plasma metabolite traits (N = 8,299), 128 peripheral cell counts (blood cells, N = 408,112; immune cells, N = 3,757), 41 inflammatory cytokine traits (N = 8,293), and 6 obesity traits were obtained from publicly available genome-wide association studies. Two-sample Mendelian randomization (MR) analysis was applied to infer the causal links using inverse variance-weighted, maximum likelihood, MR-Egger, weighted median, weighted mode, and Wald ratio methods. Several sensitivity analyses were also utilized to ensure reliable MR results. Finally, we used mediation analysis to identify the pathway from gut microbiota to obesity mediated by plasma metabolites, peripheral cells, and inflammatory cytokines.

Results

MR revealed a causal effect of 44 gut microbiota taxa, 281 plasma metabolites, 27 peripheral cells, and 8 inflammatory cytokines on obesity. Among them, five shared causal gut microbiota taxa belonged to the phylum Actinobacteria, order Bifidobacteriales, family Bifidobacteriaceae, genus Lachnospiraceae UCG008, and species Eubacterium nodatum group. Furthermore, we screened 42 shared causal metabolites, 7 shared causal peripheral cells, and 1 shared causal inflammatory cytokine. Based on known causal metabolites, we observed that the metabolic pathways of D-arginine, D-ornithine, linoleic acid, and glycerophospholipid metabolism were closely related to obesity. Finally, mediation analysis revealed 20 mediation relationships, including the causal pathway from gut microbiota to obesity, mediated by 17 metabolites, 2 peripheral cells, and 1 inflammatory cytokine. Sensitivity analysis represented no heterogeneity or pleiotropy in this study.

Conclusion

Our findings support a causal relationship among gut microbiota, plasma metabolites, peripheral cells, inflammatory cytokines, and obesity. These biomarkers provide new insights into the mechanisms underlying obesity and contribute to its prevention, diagnosis, and treatment.

Highlights of three metabolites HDL and reduction in blood pressure values after dietary fiber supplementation in overweight and obese normotensive women: a metabolomic study

INTRODUCTION

The prevalence of hypertension and obesity are a worldwide concern.

OBJETIVES

Assess the metabolites profile after intervention with mixed dietary fiber in overweight and obese normotensive women.

METHODS

This is a randomized double blind placebo-controlled study. Through a simple randomization process, two groups were allocated, with eleven women (group 1) receiving 12 g of mixed dietary fiber and thirteen women (group 2) receiving 12 g of placebo (corn starch) for eight weeks. Anthropometric and biochemical tests and lifestyle were analyzed. As for evaluation metabolomics, used a 1H NMR. The data matrix generated 96 samples and 225 variables, which was exported in the ASCII format for the "The Unscrumbler" statistics software (version 9.7, CAMO Process).

RESULTS

After the intervention with mixed dietary fiber, significant differences were observed between the main types of metabolites, referring to the increase in the relative peak areas of in three HDL metabolites 4.94 ppm (0.0086*), HDL 1.28 ppm (0 .0337*), HDL 0.88 ppm (0.0224*) and an α-glucose metabolite 4.90 ppm (0.0106) and the reduction in systolic blood pressure (SBP) (0.0292*) of 7 mmHg in the reference range and in the placebo group there was a reduction in SBP (0.0118*) of 4 mmHg and of a choline metabolite 3.65 ppm (0.0266*), which does not call into question the validity of these results in the literature.

CONCLUSION

The synergism of the functions of these statistically highlighted metabolites contributed to prevention the increase in SBP after fiber intervention in overweight and obese normotensive women.

Anti-obesity effects of olivetol in adult zebrafish model induced by short-term high-fat diet

Obesity is a complex disease caused by various factors, and synthetic drugs used to treat it can have side effects. Natural compounds, such as olivetol, could be a promising alternative. Olivetol is a substance found in certain lichen species and has anti-inflammatory and anti-cancer properties. In this study, researchers conducted in-silico molecular docking studies and found that olivetol had significant binding affinity with receptors involved in obesity. They also investigated the effects of olivetol on a diet-induced obese zebrafish model and found that high doses of olivetol reduced excessive fat accumulation and triglyceride and lipid accumulation. The low dose of olivetol showed a significant reduction in liver enzymes' levels. However, the high dose of olivetol resulted in a significant increase in HMG-CoA levels. These results suggest that olivetol may be a promising anti-obesity agent for the treatment of hyperlipidemia-related disorders, but further research is necessary to understand its full effects on the body.

Benchtop NMR-Based Metabolomics: First Steps for Biomedical Application

Nuclear magnetic resonance (NMR)-based metabolomics is a valuable tool for identifying biomarkers and understanding the underlying metabolic changes associated with various diseases. However, the translation of metabolomics analysis to clinical practice has been limited by the high cost and large size of traditional high-resolution NMR spectrometers. Benchtop NMR, a compact and low-cost alternative, offers the potential to overcome these limitations and facilitate the wider use of NMR-based metabolomics in clinical settings. This review summarizes the current state of benchtop NMR for clinical applications where benchtop NMR has demonstrated the ability to reproducibly detect changes in metabolite levels associated with diseases such as type 2 diabetes and tuberculosis. Benchtop NMR has been used to identify metabolic biomarkers in a range of biofluids, including urine, blood plasma and saliva. However, further research is needed to optimize the use of benchtop NMR for clinical applications and to identify additional biomarkers that can be used to monitor and manage a range of diseases. Overall, benchtop NMR has the potential to revolutionize the way metabolomics is used in clinical practice, providing a more accessible and cost-effective way to study metabolism and identify biomarkers for disease diagnosis, prognosis, and treatment.

Omics biomarkers and an approach for their practical implementation to delineate health status for personalized nutrition strategies

Personalized nutrition (PN) has gained much attention as a tool for empowerment of consumers to promote changes in dietary behavior, optimizing health status and preventing diet related diseases. Generalized implementation of PN faces different obstacles, one of the most relevant being metabolic characterization of the individual. Although omics technologies allow for assessment the dynamics of metabolism with unprecedented detail, its translatability as affordable and simple PN protocols is still difficult due to the complexity of metabolic regulation and to different technical and economical constrains. In this work, we propose a conceptual framework that considers the dysregulation of a few overarching processes, namely Carbohydrate metabolism, lipid metabolism, inflammation, oxidative stress and microbiota-derived metabolites, as the basis of the onset of several non-communicable diseases. These processes can be assessed and characterized by specific sets of proteomic, metabolomic and genetic markers that minimize operational constrains and maximize the information obtained at the individual level. Current machine learning and data analysis methodologies allow the development of algorithms to integrate omics and genetic markers. Reduction of dimensionality of variables facilitates the implementation of omics and genetic information in digital tools. This framework is exemplified by presenting the EU-Funded project PREVENTOMICS as a use case.

Quantitative profiling of comprehensive composition in compound herbal injections: An NMR approach applied on Shenmai injection

INTRODUCTION

Compound herbal injections (CHIs) can be regarded as a significant innovation in the modernisation of herbal medicine. Therefore, improving the quality control level of CHIs has always been an active research topic in traditional herbal medicine.

OBJECTIVES

In this study, Shenmai injection was used as a representative sample for investigating the ability of proton nuclear magnetic resonance (¹ H NMR) in the quality evaluation of CHIs.

METHODS

A quantitative ¹ H NMR method was developed to simultaneously determine the contents of total ginsenosides, polysorbate 80, and 20 primary metabolites in Shenmai injection. Multivariate statistical analysis was combined to compare differences between samples from different manufacturers.

RESULTS

It was found that the combined measurement uncertainty of each component is less than 1.61%, which demonstrates the reliability of the method. Furthermore, the components determined by this method account for up to 92.64% of the total solids, which is an unprecedented success in the analysis of Shenmai injection. In the end, the method was applied to the quality comparison of Shenmai injection from six manufacturers. The results showed that the differences among the samples from the six manufacturers were reflected in multiple types of components.

CONCLUSION

This study fully demonstrates the superiority of the quantitative ¹ H NMR method in comprehensive composition profiling of CHIs, which is conducive to improving the quality control level of Shenmai injection. Further, the present study can be used as a reference study for the research on the quality and safety of CHIs.

Compound green tea (CGT) regulates lipid metabolism in high-fat diet induced mice

This work aims to study the effect of compound green tea (CGT) on liver lipid metabolism in mice based on metabolomics of liquid chromatography-mass spectrometry (LC-MS), and preliminarily identify potential biomarkers and pathways of action by using a metabonomic network database to explore the lipid-lowering effect of CGT. In this study, forty mice were randomly divided into four groups: compound tea treatment group (DH), high-fat model control group (NK), normal control group (CK) and positive drug group (YK). After a month of different interventions, the mice were weighed and the blood lipid indexes were detected. In addition, differential liver metabolites were monitored by using LC-MS. The results showed that CGT and positive drug treatment were able to decrease body weight, liver coefficient, TC, TG and LDL levels of obese mice, while increasing HDL levels. Among the 110 compounds obtained, 54 metabolites were significantly altered in the four comparisons. More importantly, 15 remarkably downregulated metabolites involved in Lysopc 16:1, Lysopc 18:1, and Lysopc 18:2 were found in the DH group when the mice were treated with CGT; meanwhile, the positive drug Xuezhikang was able to significantly downregulate 14 compounds, including (±)18-HEPE, and 6 keto-PGF1α, compared with the NK group. Besides, KEGG enrichment analysis also revealed the important metabolic pathways, such as linoleic acid metabolism, Biosynthesis of unsaturated fatty acids, and α-linolenic acid metabolism, were related to fatty acid metabolism. These results suggested that CGT could regulate the lipid metabolism in the liver of hyperlipidemia mice, and may regulate 54 potential biomarkers in mice through a related metabolic pathway to make them return to a normal state and improve the disorder of lipid metabolism.

Noninvasive NMR/MRS Metabolic Parameters to Evaluate Metabolic Syndrome in Rats

(1) Background: Ectopic fat deposition and its effects, metabolic syndrome, have been significantly correlated to lifestyle and caloric consumption. There is no specific noninvasive evaluation tool being used in order to establish clinical markers for tracing the metabolic pathway implicated in obesity-related abnormalities that occur in the body as a result of a high-fat diet (HFD). The purpose of this work is to investigate in vivo ectopic fat distribution and in vitro metabolite profiles given by HFDs, as well as how they are inter-related, in order to find surrogate metabolic biomarkers in the development of metabolic syndrome utilizing noninvasive approaches. (2) Methods: Male Wistar rats were divided into a standard normal chow diet, ND group, and HFD group. After 16 weeks of different diet administration, blood samples were collected for proton nuclear magnetic resonance (1H NMR) and biochemical analysis. Magnetic resonance imaging/proton magnetic resonance spectroscopy (MRI/1H MRS) was performed on the abdomen, liver, and psoas muscle of the rats. (3) Results: Visceral fat showed the strongest relationship with blood cholesterol. Although liver fat content (LFC) was not associated with any biophysical profiles, it had the highest correlation with metabolites such as (-CH2)n very-low-density lipoprotein/low-density lipoprotein (VLDL/LDL), lactate, and N-acetyl glycoprotein of serum 1H NMR. HFD showed no obvious influence on muscle fat accumulation. Acetoacetate, N-acetyl glycoprotein, lactate, (-CH2)n VLDL/LDL, and valine were the five possible metabolic biomarkers used to differentiate HFD from ND in the present study. (4) Conclusions: Our study has validated the influence of long-term HFD-induced ectopic fat on body metabolism as well as the metabolic profile deterioration both in vivo and in vitro.

Metabolomics Analysis Reveals the Effects of Compound Fuzhuan Brick Tea (CFBT) on Regulating Dyslipidemia and Metabolic Disorders in Mice Induced by High-Fat Diet

Background: It is well known that obesity induced by high-fat diet (HFD) poses a serious threat to people’s health. Fuzhuan brick tea, one of the most popular beverages, is reported to possess a significant effect on regulating lipid metabolism, attributed to its many bioactive ingredients. However, the efficacy and mechanism of compound Fuzhuan brick tea (CFBT) made from Fuzhuan brick tea and other six Chinese herbal medicines are still not well defined. Methods: Sixty mice were divided into six groups: normal control group (CK), high-fat model group (NK), positive control group with anti-hyperlipidemic drug (YK), CFBT at low-(FL), medium-(FM) and high-(FH) dosage. Intervening for 30 days, conventional indexes analysis combined with metabolomics were performed to evaluate the changes in biochemical indexes and liver metabolic profiles in mice submitted to HFD. Results: CFBT treatment was able to ameliorate obesity, serum biochemical parameters, antioxidant activity and hepatic steatosis. In addition, significant alterations in the liver tissue metabolic profiles were observed, with most of these associated with inflammation, glucose and lipid metabolism. Conclusions: This study provides evidence that consumption of CFBT is capable of preventing dyslipidemia, reducing weight gain, restoring liver injury, as well as improving metabolic disorders.

Advanced Molecular Imaging (MRI/MRS/1H NMR) for Metabolic Information in Young Adults with Health Risk Obesity

BACKGROUND

Obesity or being overweight is a medical condition of abnormal body fat accumulation which is associated with a higher risk of developing metabolic syndrome. The distinct body fat depots on specific parts of the anatomy have unique metabolic properties and different types of regional excessive fat distribution can be a disease hazard. The aim of this study was to identify the metabolome and molecular imaging phenotypes among a young adult population.

METHODS

The amount and distribution of fat and lipid metabolites profile in the abdomen, liver, and calf muscles of 46 normal weight, 17 overweight, and 13 obese participants were acquired using MRI and MR spectroscopy (MRS), respectively. The serum metabolic profile was obtained using proton NMR spectroscopy. NMR spectra were integrated into seven integration regions, which reflect relative metabolites.

RESULTS

A significant metabolic disorder symptom appeared in the overweight and obese group, and increased lipid deposition occurred in the abdomen, hepatocytes, and muscles that were statistically significant. Overall, the visceral fat depots had a marked influence on dyslipidemia biomarkers, blood triglyceride (r = 0.592, p < 0.001), and high-density lipoprotein cholesterol (r = -0.484, p < 0.001). Intrahepatocellular lipid was associated with diabetes predictors for hemoglobin (HbA1c%; r = 0.379, p < 0.001) and for fasting blood sugar (r = 0.333, p < 0.05). The lipid signals in serum triglyceride and glucose signals gave similar correspondence to biochemical lipid profiles.

CONCLUSIONS

This study proves the association between alteration in metabolome in young adults, which is the key population for early prevention of obesity and metabolic syndrome. This study suggests that dyslipidemia prevalence is influenced mainly by the visceral fat depot, and liver fat depot is a key determinant for glucose metabolism and hyperglycemia. Moreover, noninvasive advanced molecular imaging completely elucidated the impact of fat distribution on the anthropometric and laboratory parameters, especially indices of the metabolic syndrome biomarkers in young adults.