Detection of Early Disease Risk Factors Associated with Metabolic Syndrome: A New Era with the NMR Metabolomics Assessment

Pregnancy as a Susceptible Period to Ambient Air Pollution Exposure on the Maternal Postpartum Metabolome

Pregnancy is a potential critical window to air pollution exposure for long-term maternal metabolic effects. However, little is known about potential early metabolic mechanisms linking air pollution to maternal metabolic health. We included 544 pregnant Mexican women with both ambient PM2.5 levels during pregnancy and untargeted serum metabolomics to examine associations between pregnancy PM2.5 exposure (overall and monthly) and postpartum metabolites, implementing FDR-adjusted robust linear regression controlling for covariates. Pathway enrichment analyses (in Reactome and MetaboAnalyst) and effect modification by fetal sex and folic acid supplementation were also evaluated. Higher PM2.5 exposure levels throughout pregnancy were associated with higher bile acids and amino acids, dysregulated glycerophospholipids, or lower fatty acyl levels (FDR < 0.05), among other metabolites. Potential critical windows of susceptibility to monthly PM2.5 on metabolites were observed in early to midpregnancy (FDR < 0.005). Main findings were consistent by strata of fetal sex and folic acid supplementation. Metabolic pathways corresponding to positive PM2.5-metabolite associations indicated enriched bile acid, dietary lipid, and transmembrane transport metabolism, whereas for negative PM2.5-metabolite associations, we identified altered pathways involving adipogenesis, incretin peptide hormone, GLP-1, PPAR-alpha, and fatty acid receptors (FDR < 0.05). PM2.5 exposures during pregnancy, especially in early gestation, altered maternal postpartum lipids as well as amino acid metabolism.

Lipids dysregulation in diseases: core concepts, targets and treatment strategies

Lipid metabolism is a well-regulated process essential for maintaining cellular functions and energy homeostasis. Dysregulation of lipid metabolism is associated with various conditions, including cardiovascular diseases, neurodegenerative disorders, and metabolic syndromes. This review explores the mechanisms underlying lipid metabolism, emphasizing the roles of key lipid species such as triglycerides, phospholipids, sphingolipids, and sterols in cellular physiology and pathophysiology. It also examines the genetic and environmental factors contributing to lipid dysregulation and the challenges of diagnosing and managing lipid-related disorders. Recent advancements in lipid-lowering therapies, including PCSK9 inhibitors, ezetimibe, bempedoic acid, and olpasiran, provide promising treatment options. However, these advancements are accompanied by challenges related to cost, accessibility, and patient adherence. The review highlights the need for personalized medicine approaches to address the interplay between genetics and environmental factors in lipid metabolism. As lipidomics and advanced diagnostic tools continue to progress, a deeper understanding of lipid-related disorders could pave the way for more effective therapeutic strategies.

The relationship between leptin-to-adiponectin ratio and HOMA-IR and metabolic syndrome in five African-origin populations

OBJECTIVE

This cross-sectional study aims to assess the associations between serum leptin, adiponectin, leptin-to-adiponectin ratio (L/A ratio), and metabolic syndrome (MS) and HOMA-IR in five African-origin populations: Ghana, South Africa, Jamaica, Seychelles, and US.

METHODS

Clinical measures included serum glucose, insulin, adipokines, blood pressure and anthropometric measures. MS was determined using the Harmonized criteria. The final sample included 2087 adults.

RESULTS

After adjusting for age, sex, and fat mass, L/A ratio, unlike HOMA-IR, was significantly associated with MS across all sites (p < 0.001). Within sites, L/A ratio was only associated with MS and HOMA-IR in the US (p < 0.001) and South Africa (p < 0.01), respectively. Leptin was associated with MS in South Africa only (p < 0.05) but was significantly associated with HOMA-IR across all five sites and within the US (p < 0.05). Similarly, adiponectin was associated with HOMA-IR in South Africa (p < 0.05) and with MS across all five sites (p < 0.001) and within each site separately, except Ghana.

CONCLUSIONS

Our study suggests that individuals of the African diaspora in different geographical locations may differ in the determinants of MS. Future studies should investigate the determinants for the disparate relationships between MS, IS and adipokines across different African-origin populations.

Clinical Implications of Metabolic Syndrome in Psoriasis Management

Psoriasis is an increasingly common chronic immune-mediated skin disease recognized for its systemic effects that extend beyond the skin and include various cardiovascular diseases, neurological diseases, type 2 diabetes, and metabolic syndrome. This study aimed to explore the complex relationship between psoriasis and metabolic syndrome by analyzing clinical, biochemical, and immunological parameters in patients with psoriasis alone and in patients combining psoriasis and metabolic syndrome. A total of 150 patients were enrolled, 76 with psoriasis only (PSO) and 74 with psoriasis and metabolic syndrome (PSO-MS). Data collected included anthropometric measurements, blood tests, and inflammatory markers. Statistical analysis was performed using the independent t-test, Mann-Whitney U test, Kruskal-Wallis test, and chi-square test to compare the two groups. Patients in the PSO-MS group had a significantly higher body weight, abdominal circumference, BMI, and inflammatory markers compared to patients with PSO. In addition, increased levels of IL-17A, cholesterol, triglycerides, and glucose were observed in the PSO-MS group. This study highlights the increased metabolic risk and exacerbated systemic inflammation associated with the coexistence of psoriasis and metabolic syndrome. These findings demonstrate the need for a comprehensive therapeutic approach and early intervention to manage metabolic complications in patients with psoriasis and metabolic syndrome.

Association of hyperuricemia with metabolic syndrome and its components in an adult population of Faisalabad, Pakistan

BACKGROUND AND AIMS

The rising prevalence of metabolic syndrome (MetS) is a matter of serious concern worldwide. Hyperuricemia has been observed as an independent risk factor in the development of MetS and each of its individual components in different populations. This study aims to determine the association of hyperuricemia with MetS and its individual components in a Pakistani cohort.

METHODS AND RESULTS

A cross-sectional study was performed in a public sector hospital in Faisalabad, Pakistan. Total 204 participants were studied along with their anthropometric measurements and blood sample analysis for clinically important parameters. MetS was defined according to the NCEP-criteria. Independent sample t-test, Binomial logistic regression and Linear regression analyses were used to determine the association between hyperuricemia and metabolic syndrome. The prevalence of MetS and hyperuricemia in our study was 42.6% and 31.9% respectively. As compared to the normo-uricemic group, the hyperuricemic group had a significantly higher systolic blood pressure, BMI and lower HDL-C level (p < 0.05). After adjusting for age, gender, BMI and LDL-C, hyperuricemia was observed to increase the risk of MetS, increased systolic blood pressure and reduce HDL-C respectively by 1.34, 1.23 and 1.20 folds respectively.

CONCLUSION

In this study, a significant association between hyperuricemia and metabolic syndrome, systolic hypertension, blood glucose and decreased HDL-C was observed.

Associations among NMR-measured inflammatory and metabolic biomarkers and accelerated aging in cardiac catheterization patients

Research into aging has grown substantially with the creation of molecular biomarkers of biological age that can be used to determine age acceleration. Concurrently, nuclear magnetic resonance (NMR) assessment of biomarkers of inflammation and metabolism provides researchers with new ways to examine intermediate risk factors for chronic disease. We used data from a cardiac catheterization cohort to examine associations between biomarkers of cardiometabolic health and accelerated aging assessed using both gene expression (Transcriptomic Age) and DNA methylation (Hannum Age, GrimAge, Horvath Age, and Phenotypic Age). Linear regression models were used to associate accelerated aging with each outcome (cardiometabolic health biomarkers) while adjusting for chronological age, sex, race, and neighborhood socioeconomic status. Our study shows a robust association between GlycA and GrimAge (5.71, 95% CI = 4.36, 7.05, P = 7.94 × 10-16), Hannum Age (1.81, 95% CI = 0.65, 2.98, P = 2.30 × 10-3), and Phenotypic Age (2.88, 95% CI = 1.91, 3.87, P = 1.21 × 10-8). We also saw inverse associations between apolipoprotein A-1 and aging biomarkers. These associations provide insight into the relationship between aging and cardiometabolic health that may be informative for vulnerable populations.

Development of Serum Lactate Level-Based Nomograms for Predicting Diabetic Kidney Disease in Type 2 Diabetes Mellitus Patients

Purpose

To establish nomograms integrating serum lactate levels and traditional risk factors for predicting diabetic kidney disease (DKD) in type 2 diabetes mellitus (T2DM) patients.

Patients and methods

A total of 570 T2DM patients and 100 healthy subjects were enrolled. T2DM patients were categorized into normal and high lactate groups. Univariate and multivariate logistic regression analyses were employed to identify independent predictors for DKD. Then, nomograms for predicting DKD were established, and the model performance was evaluated using the area under the receiver operating characteristic curve (AUC), calibration, and decision curve analysis (DCA).

Results

T2DM patients exhibited higher lactate levels compared to those in healthy subjects. Glucose, platelet, uric acid, creatinine, and hypertension were independent factors for DKD in T2DM patients with normal lactate levels, while diabetes duration, creatinine, total cholesterol, and hypertension were indicators in high lactate levels group (P<0.05). The AUC values were 0.834 (95% CI, 0.776 to 0.891) and 0.741 (95% CI, 0.688 to 0.795) for nomograms in both normal lactate and high lactate groups, respectively. The calibration curve demonstrated excellent agreement of fit. Furthermore, the DCA revealed that the threshold probability and highest Net Yield were 17-99% and 0.36, and 24-99% and 0.24 for the models in normal lactate and high lactate groups, respectively.

Conclusion

The serum lactate level-based nomogram models, combined with traditional risk factors, offer an effective tool for predicting DKD probability in T2DM patients. This approach holds promise for early risk assessment and tailored intervention strategies.

Plasma metabolite predictors of metabolic syndrome incidence and reversion

BACKGROUND

Metabolic Syndrome (MetS) is a progressive pathophysiological state defined by a cluster of cardiometabolic traits. However, little is known about metabolites that may be predictors of MetS incidence or reversion. Our objective was to identify plasma metabolites associated with MetS incidence or MetS reversion.

METHODS

The study included 1468 participants without cardiovascular disease (CVD) but at high CVD risk at enrollment from two case-cohort studies nested within the PREvención con DIeta MEDiterránea (PREDIMED) study with baseline metabolomics data. MetS was defined in accordance with the harmonized International Diabetes Federation and the American Heart Association/National Heart, Lung, and Blood Institute criteria, which include meeting 3 or more thresholds for waist circumference, triglyceride, HDL cholesterol, blood pressure, and fasting blood glucose. MetS incidence was defined by not having MetS at baseline but meeting the MetS criteria at a follow-up visit. MetS reversion was defined by MetS at baseline but not meeting MetS criteria at a follow-up visit. Plasma metabolome was profiled by LC-MS. Multivariable-adjusted Cox regression models and elastic net regularized regressions were used to assess the association of 385 annotated metabolites with MetS incidence and MetS reversion after adjusting for potential risk factors.

RESULTS

Of the 603 participants without baseline MetS, 298 developed MetS over the median 4.8-year follow-up. Of the 865 participants with baseline MetS, 285 experienced MetS reversion. A total of 103 and 88 individual metabolites were associated with MetS incidence and MetS reversion, respectively, after adjusting for confounders and false discovery rate correction. A metabolomic signature comprised of 77 metabolites was robustly associated with MetS incidence (HR: 1.56 (95 % CI: 1.33-1.83)), and a metabolomic signature of 83 metabolites associated with MetS reversion (HR: 1.44 (95 % CI: 1.25-1.67)), both p < 0.001. The MetS incidence and reversion signatures included several lipids (mainly glycerolipids and glycerophospholipids) and branched-chain amino acids.

CONCLUSION

We identified unique metabolomic signatures, primarily comprised of lipids (including glycolipids and glycerophospholipids) and branched-chain amino acids robustly associated with MetS incidence; and several amino acids and glycerophospholipids associated with MetS reversion. These signatures provide novel insights on potential distinct mechanisms underlying the conditions leading to the incidence or reversion of MetS.

Exploring Metabolic and Gut Microbiome Responses to Paraquat Administration in Male Wistar Rats: Implications for Oxidative Stress

In this study, we examined the metabolic and gut microbiome responses to paraquat (PQ) in male Wistar rats, focusing on oxidative stress effects. Rats received a single intraperitoneal injection of PQ at 15 and 30 mg/kg, and various oxidative stress parameters (i.e., MDA, SOD, ROS, 8-isoprostanes) were assessed after three days. To explore the omic profile, GC-qTOF and UHPLC-qTOF were performed to assess the plasma metabolome; 1H-NMR was used to assess the urine metabolome; and shotgun metagenomics sequencing was performed to study the gut microbiome. Our results revealed reductions in body weight and tissue changes, particularly in the liver, were observed, suggesting a systemic effect of PQ. Elevated lipid peroxidation and reactive oxygen species levels in the liver and plasma indicated the induction of oxidative stress. Metabolic profiling revealed changes in the tricarboxylic acid cycle, accumulation of ketone body, and altered levels of key metabolites, such as 3-hydroxybutyric acid and serine, suggesting intricate links between energy metabolism and redox reactions. Plasma metabolomic analysis revealed alterations in mitochondrial metabolism, nicotinamide metabolism, and tryptophan degradation. The gut microbiome showed shifts, with higher PQ doses influencing microbial populations (e.g., Escherichia coli and Akkermansia muciniphila) and metagenomic functions (pyruvate metabolism, fermentation, nucleotide and amino acid biosynthesis). Overall, this study provides comprehensive insights into the complex interplay between PQ exposure, metabolic responses, and gut microbiome dynamics. These findings enhance our understanding of the mechanisms behind oxidative stress-induced metabolic alterations and underscore the connections between xenobiotic exposure, gut microbiota, and host metabolism.

Developing a model to predict the early risk of hypertriglyceridemia based on inhibiting lipoprotein lipase (LPL): a translational study

Hypertriglyceridemia (HTG) is an independent risk factor for atherosclerotic cardiovascular disease (ASCVD). One of the multiple origins of HTG alteration is impaired lipoprotein lipase (LPL) activity, which is an emerging target for HTG treatment. We hypothesised that early, even mild, alterations in LPL activity might result in an identifiable metabolomic signature. The aim of the present study was to assess whether a metabolic signature of altered LPL activity in a preclinical model can be identified in humans. A preclinical LPL-dependent model of HTG was developed using a single intraperitoneal injection of poloxamer 407 (P407) in male Wistar rats. A rat metabolomics signature was identified, which led to a predictive model developed using machine learning techniques. The predictive model was applied to 140 humans classified according to clinical guidelines as (1) normal, less than 1.7 mmol/L; (2) risk of HTG, above 1.7 mmol/L. Injection of P407 in rats induced HTG by effectively inhibiting plasma LPL activity. Significantly responsive metabolites (i.e. specific triacylglycerols, diacylglycerols, phosphatidylcholines, cholesterol esters and lysophospholipids) were used to generate a predictive model. Healthy human volunteers with the impaired predictive LPL signature had statistically higher levels of TG, TC, LDL and APOB than those without the impaired LPL signature. The application of predictive metabolomic models based on mechanistic preclinical research may be considered as a strategy to stratify subjects with HTG of different origins. This approach may be of interest for precision medicine and nutritional approaches.

Mesenchymal stem cell-derived extracellular vesicles for metabolic syndrome therapy: Assessing efficacy with nuclear magnetic resonance spectroscopy

Metabolic syndrome (MetS) represents a cluster of metabolic abnormalities. The prevalence of MetS has surged, transforming it into a pressing public health concern that could potentially affect around 20%-25% of the global population. As MetS continues its ascent, diverse interventions, pharmacological, nonpharmacological and combined have been deployed. Yet, a comprehensive remedy that fully eradicates MetS symptoms remains elusive, compounded by the risks of polypharmacy's emergence. Acknowledging the imperative to grasp MetS's intricate pathologies, deeper insights for future research and therapy optimisation become paramount. Conventional treatments often target specific syndrome elements. However, a novel approach emerges in mesenchymal stem cell-derived extracellular vesicles (MSC-EVs) therapy, promising a holistic shift. MSC-EVs, tiny membranous vesicles secreted by mesenchymal stem cells, have garnered immense attention for their multifaceted bioactivity and regenerative potential. Their ability to modulate inflammation, enhance tissue repair and regulate metabolic pathways has prompted researchers to explore their therapeutic application in MetS. This review primarily aims to provide an overview of how MSC-EVs therapy can improve metabolic parameters in subjects with MetS disease and also introduce the usefulness of NMR spectroscopy in assessing the efficacy of MSC-EVs therapy for treating MetS.

Prevalence of metabolic syndrome and chronic inflammation in psoriasis before and after biologic therapy: a prospective study

Background

As a chronic inflammatory disease, psoriasis affects not only the skin but also the metabolic profile of the patients. Biologic therapies, including tumor necrosis alpha (TNF-a) inhibitors and interleukin (IL)-12/23 and IL-17 antagonists, have proven effective in the reduction of psoriasis severity; however their impact on the metabolic and chronic inflammatory profiles of the patients remains incompletely elucidated.

Methods

We performed a longitudinal case-control study on 106 psoriasis patients and an equal number of controls without the disease, as well as a prospective study on the patient group with the end point being 6 months of biologic therapy. Patients received either ixekizumab, secukinumab, guselkumab, certolizumab, ustekinumab, risankizumab, or adalimumab. Abdominal circumference, serum fasting glucose, triglycerides (TG), high-density lipoproteins (HDL), erythrocyte sedimentation rate (ESR) and C reactive protein (CRP) were measured for both patients and controls, with an additional measurement for patients after 6 months.

Results

At baseline, the number of psoriasis patients suffering from obesity, metabolic syndrome, and chronic inflammation significantly outnumbered controls (p<0.05), with the calculated odds ratio being 1.88, 6.83, and 81.84 for these conditions in psoriasis, respectively. Biologic therapies increased the abdominal circumference of patients in a slight but significant fashion (p<0.05), as well as significantly improved HDL, CRP, ESR levels at 6 months (p<0.05). Moreover, after 6 months, the number of patients meeting the diagnostic criteria for metabolic syndrome and chronic inflammation was significantly lower than at baseline (p<0.001).

Conclusions

According to our results, biologic therapies improve the overall metabolic and inflammatory profiles of psoriasis patients, the most significant ameliorations being noticed for serum HDL, CRP, and ESR.

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.

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.

Sex-Specific Cut-Offs of Single Point Insulin Sensitivity Estimator (SPISE) in Predicting Metabolic Syndrome in the Arab Adolescents

The Single Point Insulin Sensitivity Estimator (SPISE) is a novel surrogate marker for insulin sensitivity and was found comparable to the gold standard clamp test as well as for predicting the Metabolic Syndrome (MetS) in several populations. The present study aimed to assess for the first time, the validity of SPISE in predicting MetS among Arab adolescents. In this cross-sectional study, 951 Saudi adolescents aged 10−17 years were randomly recruited from different schools across Riyadh, Saudi Arabia. Anthropometrics were measured and fasting blood samples were collected for the assessment of glucose, lipid profile, adipokines, C-reactive protein and 25 hydroxyvitamin (OH) D. MetS was defined using the National Cholesterol Education Program’s (NCEP) criteria with age-specific thresholds for adolescents. The SPISE as well as insulin resistance (HOMA-IR) indices were calculated. The over-all prevalence of MetS was 8.6% (82 out of 951). SPISE index was significantly lower in MetS than non-MetS participants in both sexes (5.5 ± 2.5 vs. 9.4 ± 3.2, p < 0.001 in boys and 4.4 ± 1.4 vs. 8.6 ± 3.2, p < 0.001 in girls). The SPISE index showed a significant inverse correlation with resistin, leptin, and C-reactive protein, and a significant positive correlation with adiponectin and 25(OH) D. Areas under the curve (AUC) revealed fair and good accuracy for predicting MetS 84.1% and 90.3% in boys and girls, respectively. The sex-specific cut-off proposed was SPISE index ≤6.1 (sensitivity 72.2% and specificity 83.9%) for boys and ≤6.46 (sensitivity 96.3% and specificity 73.4%), for girls. This study suggests that the SPISE index is a simple and promising diagnostic marker of insulin sensitivity and MetS in Arab adolescents.

ASSESSMENT OF CARDIOVASCULAR DISEASE RISK FACTORS IN PATIENTS WITH CORONARY HEART DISEASE COMBINED WITH NONALCOHOLIC FATTY LIVER DISEASE

OBJECTIVE

The aim: To study the risk factors of cardiovascular diseases in patients with coronary heart disease with stable angina pectoris II functional class in combi¬nation with NAFLD.

PATIENTS AND METHODS

Materials and methods: The study included 245 patients with a diagnosis of CHD, stable angina pectoris II functional class (FC), who were being treated at the Communal Nonprofit Enterprise «Central City Clinical Hospital» of Uzhhorod City Council. We singled out 2 groups of patients: group 1 (n=145) - patients with CHD with stable angina pectoris II FC in combination with NAFLD and group 2 (n=100) - patients with CHD with stable angina pectoris II FC.

RESULTS

Results: Analysis of the frequency of occurrence of CVD risk factors in patients with CHD showed that among patients of group 1 there are 50% more people with abdominal obesity, excess body and dyslipidemia. The reliability between the groups in the occurrence of hypertension and type 2 diabetes was not revealed. The obtained results confirm the data that the prevalence of NAFLD increases with increasing body weight and a high degree of obesity increases the risk of its development.

CONCLUSION

Conclusions: The most frequent risk factors for CVD in patients with coronary artery disease in combination with NAFLD are hypertension, obesity, and dyslipidemia.

The association between acylcarnitine and amino acids profile and metabolic syndrome and its components in Iranian adults: Data from STEPs 2016

BACKGROUND

Evidence, albeit with conflicting results, has suggested that cardiometabolic risk factors, including obesity, type 2 diabetes (T2D), dyslipidemia, and hypertension, are highly associated with changes in metabolic signature, especially plasma amino acids and acylcarnitines levels. Here, we aimed to evaluate the association of circulating levels of amino acids and acylcarnitines with metabolic syndrome (MetS) and its components in Iranian adults.

METHODS

This cross-sectional study was performed on 1192 participants from the large-scale cross-sectional study of Surveillance of Risk Factors of non-communicable diseases (NCDs) in Iran (STEP 2016). The circulating levels of amino acids and acylcarnitines were measured using liquid chromatography-tandem mass spectrometry (LC-MS/MS) in individuals with MetS (n=529) and without MetS (n=663).

RESULTS

The higher plasma levels of branched-chain amino acids (Val, Leu), aromatic amino acids (Phe, Tyr), Pro, Ala, Glu, and the ratio of Asp to Asn were significantly associated with MetS, whereas lower circulating levels of Gly, Ser, His, Asn, and citrulline were significantly associated with MetS. As for plasma levels of free carnitine and acylcarnitines, higher levels of short-chain acylcarnitines (C2, C3, C4DC), free carnitine (C0), and long-chain acylcarnitines (C16, C18OH) were significantly associated with MetS. Principal component analysis (PCA) showed that factor 3 (Tyr, Leu, Val, Met, Trp, Phe, Thr) [OR:1.165, 95% CI: 1.121-1.210, P<0.001], factor 7 (C0, C3, C4) [OR:1.257, 95% CI: 1.150-1.374, P<0.001], factor 8 (Gly, Ser) [OR:0.718, 95% CI: 0.651-0.793, P< 0.001], factor 9 (Ala, Pro, C4DC) [OR:1.883, 95% CI: 1.669-2.124, P<0.001], factor 10 (Glu, Asp, C18:2OH) [OR:1.132, 95% CI: 1.032-1.242, P= 0.009], factor 11 (citrulline, ornithine) [OR:0.862, 95% CI: 0.778-0.955, P= 0.004] and 13 (C18OH, C18:1 OH) [OR: 1.242, 95% CI: 1.042-1.480, P= 0.016] were independently correlated with metabolic syndrome.

CONCLUSION

Change in amino acid, and acylcarnitines profiles were seen in patients with MetS. Moreover, the alteration in the circulating levels of amino acids and acylcarnitines is along with an increase in MetS component number. It also seems that amino acid and acylcarnitines profiles can provide valuable information on evaluating and monitoring MetS risk. However, further studies are needed to establish this concept.

Multi-Tissue Time-Domain NMR Metabolomics Investigation of Time-Restricted Feeding in Male and Female Nile Grass Rats

Metabolic disease resulting from overnutrition is prevalent and rapidly increasing in incidence in modern society. Time restricted feeding (TRF) dietary regimens have recently shown promise in attenuating some of the negative metabolic effects associated with chronic nutrient stress. The purpose of this study is to utilize a multi-tissue metabolomics approach using nuclear magnetic resonance (NMR) spectroscopy to investigate TRF and sex-specific effects of high-fat diet in a diurnal Nile grass rat model. Animals followed a six-week dietary protocol on one of four diets: chow ad libitum, high-fat ad libitum (HF-AD), high-fat early TRF (HF-AM), or high-fat late TRF (HF-PM), and their liver, heart, and white adipose tissues were harvested at the end of the study and were analyzed by NMR. Time-domain complete reduction to amplitude–frequency table (CRAFT) was used to semi-automate and systematically quantify metabolites in liver, heart, and adipose tissues while minimizing operator bias. Metabolite profiling and statistical analysis revealed lipid remodeling in all three tissues and ectopic accumulation of cardiac and hepatic lipids for HF-AD feeding compared to a standard chow diet. Animals on TRF high-fat diet had lower lipid levels in the heart and liver compared to the ad libitum group; however, no significant differences were noted for adipose tissue. Regardless of diet, females exhibited greater amounts of hepatic lipids compared to males, while no consistent differences were shown in adipose and heart. In conclusion, this study demonstrates the feasibility of performing systematic and time-efficient multi-tissue NMR metabolomics to elucidate metabolites involved in the crosstalk between different metabolic tissues and provides a more holistic approach to better understand the etiology of metabolic disease and the effects of TRF on metabolic profiles.

A double-blinded, randomized, parallel intervention to evaluate biomarker-based nutrition plans for weight loss: The PREVENTOMICS study

BACKGROUND & AIMS

Growing evidence suggests that biomarker-guided dietary interventions can optimize response to treatment. In this study, we evaluated the efficacy of the PREVENTOMCIS platform-which uses metabolomic and genetic information to classify individuals into different 'metabolic clusters' and create personalized dietary plans-for improving health outcomes in subjects with overweight or obesity.

METHODS

A 10-week parallel, double-blinded, randomized intervention was conducted in 100 adults (82 completers) aged 18-65 years, with body mass index ≥27 but <40 kg/m², who were allocated into either a personalized diet group (n = 49) or a control diet group (n = 51). About 60% of all food was provided free-of-charge. No specific instruction to restrict energy intake was given. The primary outcome was change in fat mass from baseline, evaluated by dual energy X-ray absorptiometry. Other endpoints included body weight, waist circumference, lipid profile, glucose homeostasis markers, inflammatory markers, blood pressure, physical activity, stress and eating behavior.

RESULTS

There were significant main effects of time (P < 0.01), but no group main effects, or time-by-group interactions, for the change in fat mass (personalized: -2.1 [95% CI -2.9, -1.4] kg; control: -2.0 [95% CI -2.7, -1.3] kg) and body weight (personalized: -3.1 [95% CI -4.1, -2.1] kg; control: -3.3 [95% CI -4.2, -2.4] kg). The difference between groups in fat mass change was -0.1 kg (95% CI -1.2, 0.9 kg, P = 0.77). Both diets resulted in significant improvements in insulin resistance and lipid profile, but there were no significant differences between groups.

CONCLUSION

Personalized dietary plans did not result in greater benefits over a generic, but generally healthy diet, in this 10-week clinical trial. Further studies are required to establish the soundness of different precision nutrition approaches, and translate this science into clinically relevant dietary advice to reduce the burden of obesity and its comorbidities.

CLINICAL TRIAL REGISTRY

ClinicalTrials.gov registry (NCT04590989).

Uncontrolled Thyroid during Pregnancy Alters the Circulative and Exerted Metabolome

Normal levels of thyroid hormones (THs) are essential for a normal pregnancy outcome, fetal growth and the normal function of the central nervous system. Hypothyroidism, a common endocrine disorder during pregnancy, is a significant metabolic factor leading to cognitive impairments. It is essential to investigate whether patients with thyroid dysfunction may present an altered circulative and excreted metabolic profile, even after receiving treatment with thyroxine supplements. NMR metabolomics was employed to analyze 90 serum and corresponding colostrum samples. Parallel analyses of the two biological specimens provided a snapshot of the maternal metabolism through the excretive and circulating characteristics of mothers. The metabolomics data were analyzed by performing multivariate statistical, biomarker and pathway analyses. Our results highlight the impact of hypothyroidism on metabolites’ composition during pregnancy and lactation. Thyroid disorder causing metabolite fluctuations may lead to impaired lipid and glucose metabolic pathways as well as aberrant prenatal neurodevelopment, thus posing a background for the occurrence of metabolic syndrome or neurogenerative diseases later in life. This risk applies to not only untreated but also hypothyroid women under replacement therapy since our findings in both biofluids framed a different metabolic phenotype for the latter group, thus emphasizing the need to monitor women adequately after treatment initiation.

Empowering consumers to PREVENT diet-related diseases through OMICS sciences (PREVENTOMICS): protocol for a parallel double-blinded randomised intervention trial to investigate biomarker-based nutrition plans for weight loss

INTRODUCTION

Personalised nutrition holds immense potential over conventional one-size-fits-all approaches for preventing and treating diet-related diseases, such as obesity. The current study aims to examine whether a personalised nutritional plan produces more favourable health outcomes than a standard approach based on general dietary recommendations in subjects with overweight or obesity and elevated waist circumference.

METHODS AND ANALYSIS

This project is a 10-week parallel, double-blinded randomised intervention trial. We plan to include 100 adults aged 18-65 years interested in losing weight, with body mass index ≥27 but<40 kg/m² and elevated waist circumference (males >94 cm; females >80 cm). Participants will be categorised into one of five predefined 'clusters' based on their individual metabolic biomarker profile and genetic background, and will be randomised in a 1:1 ratio to one of two groups: (1) personalised plan group that will receive cluster-specific meals every day for 6 days a week, in conjunction with a personalised behavioural change programme via electronic push notifications; or (2) control group that will receive meals following the general dietary recommendations in conjunction with generic health behaviour prompts. The primary outcome is the difference between groups (personalised vs control) in the change in fat mass from baseline. Secondary outcomes include changes in weight and body composition, fasting blood glucose and insulin, lipid profile, adipokines, inflammatory biomarkers, and blood pressure. Other outcomes involve measures of physical activity and sleep patterns, health-related quality of life, dietary intake, eating behaviour, and biomarkers of food intake. The effect of the intervention on the primary outcome will be analysed by means of linear mixed models.

ETHICS AND DISSEMINATION

The protocol has been approved by the Ethics Committee of the Capital Region, Copenhagen, Denmark. Study findings will be disseminated through peer-reviewed publications, conference presentations and media outlets.

TRIAL REGISTRATION NUMBER

NCT04590989.

Imbalances in TCA, Short Fatty Acids and One-Carbon Metabolisms as Important Features of Homeostatic Disruption Evidenced by a Multi-Omics Integrative Approach of LPS-Induced Chronic Inflammation in Male Wistar Rats

Chronic inflammation is an important risk factor in a broad variety of physical and mental disorders leading to highly prevalent non-communicable diseases (NCDs). However, there is a need for a deeper understanding of this condition and its progression to the disease state. For this reason, it is important to define metabolic pathways and complementary biomarkers associated with homeostatic disruption in chronic inflammation. To achieve that, male Wistar rats were subjected to intraperitoneal and intermittent injections with saline solution or increasing lipopolysaccharide (LPS) concentrations (0.5, 5 and 7.5 mg/kg) thrice a week for 31 days. Biochemical and inflammatory parameters were measured at the end of the study. To assess the omics profile, GC-qTOF and UHPLC-qTOF were performed to evaluate plasma metabolome; 1H-NMR was used to evaluate urine metabolome; additionally, shotgun metagenomics sequencing was carried out to characterize the cecum microbiome. The chronicity of inflammation in the study was evaluated by the monitoring of monocyte chemoattractant protein-1 (MCP-1) during the different weeks of the experimental process. At the end of the study, together with the increased levels of MCP-1, levels of interleukin-6 (IL-6), tumour necrosis factor alpha (TNF-α) and prostaglandin E2 (PGE2) along with 8-isoprostanes (an indicative of oxidative stress) were significantly increased (p-value < 0.05). The leading features implicated in the current model were tricarboxylic acid (TCA) cycle intermediates (i.e., alpha-ketoglutarate, aconitic acid, malic acid, fumaric acid and succinic acid); lipids such as specific cholesterol esters (ChoEs), lysophospholipids (LPCs) and phosphatidylcholines (PCs); and glycine, as well as N, N-dimethylglycine, which are related to one-carbon (1C) metabolism. These metabolites point towards mitochondrial metabolism through TCA cycle, β-oxidation of fatty acids and 1C metabolism as interconnected pathways that could reveal the metabolic effects of chronic inflammation induced by LPS administration. These results provide deeper knowledge concerning the impact of chronic inflammation on the disruption of metabolic homeostasis.

Vancomycin-Induced Modulation of Gram-Positive Gut Bacteria and Metabolites Remediates Insulin Resistance in iNOS Knockout Mice

The role of oxidative and nitrosative stress has been implied in both physiology and pathophysiology of metabolic disorders. Inducible nitric oxide synthase (iNOS) has emerged as a crucial regulator of host metabolism and gut microbiota activity. The present study examines the role of the gut microbiome in determining host metabolic functions in the absence of iNOS. Insulin-resistant and dyslipidemic iNOS-/- mice displayed reduced microbial diversity, with a higher relative abundance of Allobaculum and Bifidobacterium, gram-positive bacteria, and altered serum metabolites along with metabolic dysregulation. Vancomycin, which largely depletes gram-positive bacteria, reversed the insulin resistance (IR), dyslipidemia, and related metabolic anomalies in iNOS-/- mice. Such improvements in metabolic markers were accompanied by alterations in the expression of genes involved in fatty acid synthesis in the liver and adipose tissue, lipid uptake in adipose tissue, and lipid efflux in the liver and intestine tissue. The rescue of IR in vancomycin-treated iNOS-/- mice was accompanied with the changes in select serum metabolites such as 10-hydroxydecanoate, indole-3-ethanol, allantoin, hippurate, sebacic acid, aminoadipate, and ophthalmate, along with improvement in phosphatidylethanolamine to phosphatidylcholine (PE/PC) ratio. In the present study, we demonstrate that vancomycin-mediated depletion of gram-positive bacteria in iNOS-/- mice reversed the metabolic perturbations, dyslipidemia, and insulin resistance.

Alterations in Metabolome and Microbiome Associated with an Early Stress Stage in Male Wistar Rats: A Multi-Omics Approach

Stress disorders have dramatically increased in recent decades becoming the most prevalent psychiatric disorder in the United States and Europe. However, the diagnosis of stress disorders is currently based on symptom checklist and psychological questionnaires, thus making the identification of candidate biomarkers necessary to gain better insights into this pathology and its related metabolic alterations. Regarding the identification of potential biomarkers, omic profiling and metabolic footprint arise as promising approaches to recognize early biochemical changes in such disease and provide opportunities for the development of integrative candidate biomarkers. Here, we studied plasma and urine metabolites together with metagenomics in a 3 days Chronic Unpredictable Mild Stress (3d CUMS) animal approach that aims to focus on the early stress period of a well-established depression model. The multi-omics integration showed a profile composed by a signature of eight plasma metabolites, six urine metabolites and five microbes. Specifically, threonic acid, malic acid, alpha-ketoglutarate, succinic acid and cholesterol were proposed as key metabolites that could serve as key potential biomarkers in plasma metabolome of early stages of stress. Such findings targeted the threonic acid metabolism and the tricarboxylic acid (TCA) cycle as important pathways in early stress. Additionally, an increase in opportunistic microbes as virus of the Herpesvirales was observed in the microbiota as an effect of the primary stress stages. Our results provide an experimental biochemical characterization of the early stage of CUMS accompanied by a subsequent omic profiling and a metabolic footprinting that provide potential candidate biomarkers.

Metabolite profiles and the risk of metabolic syndrome in early childhood: a case-control study

BACKGROUND

Defining the metabolic syndrome (MetS) in children remains challenging. Furthermore, a dichotomous MetS diagnosis can limit the power to study associations. We sought to characterize the serum metabolite signature of the MetS in early childhood using high-throughput metabolomic technologies that allow comprehensive profiling of metabolic status from a biospecimen.

METHODS

In the Family Atherosclerosis Monitoring In earLY life (FAMILY) prospective birth cohort study, we selected 228 cases of MetS and 228 matched controls among children age 5 years. In addition, a continuous MetS risk score was calculated for all 456 participants. Comprehensive metabolite profiling was performed on fasting serum samples using multisegment injection-capillary electrophoresis-mass spectrometry. Multivariable regression models were applied to test metabolite associations with MetS adjusting for covariates of screen time, diet quality, physical activity, night sleep, socioeconomic status, age, and sex.

RESULTS

Compared to controls, thirteen serum metabolites were identified in MetS cases when using multivariable regression models, and using the quantitative MetS score, an additional eight metabolites were identified. These included metabolites associated with gluconeogenesis (glucose (odds ratio (OR) 1.55 [95% CI 1.25-1.93]) and glutamine/glutamate ratio (OR 0.82 [95% CI 0.67-1.00])) and the alanine-glucose cycle (alanine (OR 1.41 [95% CI 1.16-1.73])), amino acids metabolism (tyrosine (OR 1.33 [95% CI 1.10-1.63]), threonine (OR 1.24 [95% CI 1.02-1.51]), monomethylarginine (OR 1.33 [95% CI 1.09-1.64]) and lysine (OR 1.23 [95% CI 1.01-1.50])), tryptophan metabolism (tryptophan (OR 0.78 [95% CI 0.64-0.95])), and fatty acids metabolism (carnitine (OR 1.24 [95% CI 1.02-1.51])). The quantitative MetS risk score was more powerful than the dichotomous outcome in consistently detecting this metabolite signature.

CONCLUSIONS

A distinct metabolite signature of pediatric MetS is detectable in children as young as 5 years old and may improve risk assessment at early stages of development.

Multi-stage metabolomics and genetic analyses identified metabolite biomarkers of metabolic syndrome and their genetic determinants

Background

Metabolic syndrome (MetS) is a cluster of multiple cardiometabolic risk factors that increase the risk of type 2 diabetes and cardiovascular diseases. Identifying novel biomarkers of MetS and their genetic associations could provide insights into the mechanisms of cardiometabolic diseases.

Methods

Potential MetS-associated metabolites were screened and internally validated by untargeted metabolomics analyses among 693 patients with MetS and 705 controls. External validation was conducted using two well-established targeted metabolomic methods among 149 patients with MetS and 253 controls. The genetic associations of metabolites were determined by linear regression using our previous genome-wide SNP data. Causal relationships were assessed using a one-sample Mendelian Randomization (MR) approach.

Findings

Nine metabolites were ultimately found to be associated with MetS or its components. Five metabolites, including LysoPC(14:0), LysoPC(15:0), propionyl carnitine, phenylalanine, and docosapentaenoic acid (DPA) were selected to construct a metabolite risk score (MRS), which was found to have a dose-response relationship with MetS and metabolic abnormalities. Moreover, MRS displayed a good ability to differentiate MetS and metabolic abnormalities. Three SNPs (rs11635491, rs7067822, and rs1952458) were associated with LysoPC(15:0). Two SNPs, rs1952458 and rs11635491 were found to be marginally correlated with several MetS components. MR analyses showed that a higher LysoPC(15:0) level was causally associated with the risk of overweight/obesity, dyslipidaemia, high uric acid, high insulin and high HOMA-IR.

Interpretation

We identified five metabolite biomarkers of MetS and three SNPs associated with LysoPC(15:0). MR analyses revealed that abnormal LysoPC metabolism may be causally linked the metabolic risk.

Funding

This work was supported by grants from the National Key Research and Development Program of China (2017YFC0907004).

Metabolomic connections between schizophrenia, antipsychotic drugs and metabolic syndrome: A variety of players

BACKGROUND

Diagnosis of schizophrenia lacks of reliable medical diagnostic tests and robust biomarkers applied to clinical practice. Schizophrenic patients undergoing treatment with antipsychotics suffer a reduced life expectancy due to metabolic disarrangements that co-exist with their mental illness and predispose them to develop metabolic syndrome, also exacerbated by medication. Metabolomics is an emerging and potent technology able to accelerate this biomedical research. <P> Aim: This review focus on a detailed vision of the molecular mechanisms involved both in schizophrenia and antipsychotic-induced metabolic syndrome, based on innovative metabolites that consistently change in nascent metabolic syndrome, drug-naïve, first episode psychosis and/or schizophrenic patients compared to healthy subjects. <P> Main lines: Supported by metabolomic approaches, although not exclusively, noteworthy variations are reported mainly through serum samples of patients and controls in several scenes: 1) alterations in fatty acids, inflammatory response indicators, amino acids and biogenic amines, biometals and gut microbiota metabolites (schizophrenia); 2) alterations in metabolites involved in carbohydrate and gut microbiota metabolism, inflammation and oxidative stress (metabolic syndrome), some of them shared with the schizophrenia scene; 3) alterations of cytokines secreted by adipose tissue, phosphatidylcholines, acylcarnitines, Sirtuin 1, orexin-A and changes in microbiota composition (antipsychotic-induced metabolic syndrome). <P> Conclusion: Novel insights into the pathogenesis of schizophrenia and metabolic side-effects associated to its antipsychotic treatment, represent an urgent request for scientifics and clinicians. Leptin, carnitines, adiponectin, insulin or interleukin-6 represent some examples of candidate biomarkers. Cutting-edge technologies like metabolomics have the power of strengthen research for achieving preventive, diagnostic and therapeutical solutions for schizophrenia.

CX3CR1 regulates gut microbiota and metabolism. A risk factor of type 2 diabetes

OBJECTIVE

The intestinal microbiota to immune system crosstalk is a major regulator of metabolism and hence metabolic diseases. An impairment of the chemokine receptor CX3CR1, as a key regulator shaping intestinal microbiota under normal chow feeding, could be one of the early events of dysglycemia.

METHODS

We studied the gut microbiota ecology by sequencing the gut and tissue microbiota. We studied its role in energy metabolism in CX3CR1-deficent and control mice using various bioassays notably the glycemic regulation during fasting and the respiratory quotient as two highly sensitive physiological features. We used antibiotics and prebiotics treatments, and germ free mouse colonization.

RESULTS

We identify that CX3CR1 disruption impairs gut microbiota ecology and identified a specific signature associated to the genotype. The glycemic control during fasting and the respiratory quotient throughout the day are deeply impaired. A selected four-week prebiotic treatment modifies the dysbiotic microbiota and improves the fasting state glycemic control of the CX3CR1-deficent mice and following a glucose tolerance test. A 4 week antibiotic treatment also improves the glycemic control as well. Eventually, germ free mice colonized with the microbiota from CX3CR1-deficent mice developed glucose intolerance.

CONCLUSIONS

CX3CR1 is a molecular mechanism in the control of the gut microbiota ecology ensuring the maintenance of a steady glycemia and energy metabolism. Its impairment could be an early mechanism leading to gut microbiota dysbiosis and the onset of metabolic disease.

A molecular signature for the metabolic syndrome by urine metabolomics

Background

Metabolic syndrome (MetS) is a multimorbid long-term condition without consensual medical definition and a diagnostic based on compatible symptomatology. Here we have investigated the molecular signature of MetS in urine.

Methods

We used NMR-based metabolomics to investigate a European cohort including urine samples from 11,754 individuals (18–75 years old, 41% females), designed to populate all the intermediate conditions in MetS, from subjects without any risk factor up to individuals with developed MetS (4–5%, depending on the definition). A set of quantified metabolites were integrated from the urine spectra to obtain metabolic models (one for each definition), to discriminate between individuals with MetS.

Results

MetS progression produces a continuous and monotonic variation of the urine metabolome, characterized by up- or down-regulation of the pertinent metabolites (17 in total, including glucose, lipids, aromatic amino acids, salicyluric acid, maltitol, trimethylamine N-oxide, and p-cresol sulfate) with some of the metabolites associated to MetS for the first time. This metabolic signature, based solely on information extracted from the urine spectrum, adds a molecular dimension to MetS definition and it was used to generate models that can identify subjects with MetS (AUROC values between 0.83 and 0.87). This signature is particularly suitable to add meaning to the conditions that are in the interface between healthy subjects and MetS patients. Aging and non-alcoholic fatty liver disease are also risk factors that may enhance MetS probability, but they do not directly interfere with the metabolic discrimination of the syndrome.

Conclusions

Urine metabolomics, studied by NMR spectroscopy, unravelled a set of metabolites that concomitantly evolve with MetS progression, that were used to derive and validate a molecular definition of MetS and to discriminate the conditions that are in the interface between healthy individuals and the metabolic syndrome.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-021-01349-9.

The association of adiponectin gene polymorphisms with susceptibility and progression of NAFLD in a cohort of Egyptian patients

Background

Several genetic polymorphisms have been proven to play a key role in the progression of non-alcoholic fatty liver disease (NAFLD) from simple steatosis to NASH with fibrosis. Our aim was to study the effect of single nucleotide polymorphisms (SNPs) in the adiponectin gene, namely rs266729 and rs3774261, on susceptibility to NAFLD and disease progression.

Results

There was a definitive association between polymorphisms of the studied SNPs and NAFLD. Among rs266729, CG was significantly higher among patients than controls showing increased risk for NAFLD (P<0.05). AA genotype of the rs3774261 variant was significantly lower in patients than in controls (P value< 0.001) while AG and GG genotypes were significantly higher in patients than in controls (P value<0.05); A allele was significantly higher among controls (P=0.019) which might have a protective effect. None of the variants correlated significantly with the degree of steatosis. Using multivariate regression analysis, there was no significant correlation with any of the independent risk factors to the degree of steatosis.

Conclusions

There was an association between polymorphisms of the studied SNPs of rs266729 and rs3774261 of the adiponectin gene and NAFLD.

A Pilot Study for Metabolic Profiling of Obesity-Associated Microbial Gut Dysbiosis in Male Wistar Rats

Obesity is one of the most incident and concerning disease worldwide. Definite strategies to prevent obesity and related complications remain elusive. Among the risk factors of the onset of obesity, gut microbiota might play an important role in the pathogenesis of the disease, and it has received extensive attention because it affects the host metabolism. In this study, we aimed to define a metabolic profile of the segregated obesity-associated gut dysbiosis risk factor. The study of the metabolome, in an obesity-associated gut dysbiosis model, provides a relevant way for the discrimination on the different biomarkers in the obesity onset. Thus, we developed a model of this obesity risk factors through the transference of gut microbiota from obese to non-obese male Wistar rats and performed a subsequent metabolic analysis in the receptor rats. Our results showed alterations in the lipid metabolism in plasma and in the phenylalanine metabolism in urine. In consequence, we have identified metabolic changes characterized by: (1) an increase in DG:34:2 in plasma, a decrease in hippurate, (2) an increase in 3-HPPA, and (3) an increase in o-coumaric acid. Hereby, we propose these metabolites as a metabolic profile associated to a segregated dysbiosis state related to obesity disease.

Short Sleep Duration and Its Association with Obesity and Other Metabolic Risk Factors in Kuwaiti Urban Adults

BACKGROUND

Efficient sleep duration and its quality are increasingly recognized as important contributors for maintaining normal body weight. However, lifestyle and social structure within the Arab-gulf region differ compared to those in the western world. This study was specifically conducted in Kuwait's population to investigate the link between sleep quality (SQ) and obesity in the absence of sleep apnea (SA) onset.

METHODS

SQ was measured by the Pittsburgh Sleep Quality Index (PQSI) in 984 participants, then verified in 60 individuals including 20 lean (Body mass index/BMI: 18.5-24.9 kg/m²), 20 overweight (BMI: 25-29.9 kg/m²) and 20 obese (BMI: ≥30 kg/m²) through actigraph worn over the right-hip for 7 consecutive days to characterize their sleep-wake cycle, rest-activity, and physical activity. Blood samples were collected for metabolic markers.

RESULTS

59.6% of participants reported a PSQI score higher than 5, with 57.6% of the participants reporting less than 6 hours of sleep per day. The data show that both SQ and sleep duration are considered inadequate in comparison to the international SQ standards. We found a significant association between SQ and obesity independent of age and sex. Actigraph data further supported the independent association of sleep duration on BMI within the population (p < 0.001). Additionally, total sleep time (TST) was found to significantly correlate with several other metabolic factors including diastolic blood pressure, elevated resting heart rate (RHR), triglycerides, total cholesterol, homeostatic model assessment for insulin resistance (HOMA-IR), C-peptide, and C-Reactive Protein (CRP) secretion. Further multiple-regression analysis showed a significant independent association between blood pressure (p < 0.03), HOMA-IR (p < 0.04), and C-peptide (p < 0.3) and sleep duration.

CONCLUSION

These findings suggest that sleep deprivation and disturbance could be indirect factors involved in the development of not only obesity in Kuwait but also other metabolic syndromes such as type 2 diabetes.

Effect of Defatted Dabai Pulp Extract in Urine Metabolomics of Hypercholesterolemic Rats

A source of functional food can be utilized from a source that might otherwise be considered waste. This study investigates the hypocholesterolemic effect of defatted dabai pulp (DDP) from supercritical carbon dioxide extraction and the metabolic alterations associated with the therapeutic effects of DDP using ¹H NMR urinary metabolomic analysis. Male-specific pathogen-free Sprague-Dawley rats were fed with a high cholesterol diet for 30 days to induce hypercholesterolemia. Later, the rats were administered with a 2% DDP treatment diet for another 30 days. Supplementation with the 2% DDP treatment diet significantly reduced the level of total cholesterol (TC), triglyceride, low-density lipoprotein (LDL), and inflammatory markers (C-reactive protein (CRP), interleukin 6 (IL6) and tumour necrosis factor-α (α-TNF)) and significantly increased the level of antioxidant profile (total antioxidant status (TAS), superoxide dismutase (SOD), glutathione peroxide (GPX), and catalase (CAT)) compared with the positive control group (PG) group (p < 0.05). The presence of high dietary fibre (28.73 ± 1.82 g/100 g) and phenolic compounds (syringic acid, 4-hydroxybenzoic acid and gallic acid) are potential factors contributing to the beneficial effect. Assessment of ¹H NMR urinary metabolomics revealed that supplementation of 2% of DDP can partially recover the dysfunction in the metabolism induced by hypercholesterolemia via choline metabolism. ¹H-NMR-based metabolomic analysis of urine from hypercholesterolemic rats in this study uncovered the therapeutic effect of DDP to combat hypercholesterolemia.

NMR microsystem for label-free characterization of 3D nanoliter microtissues

Performing chemical analysis at the nanoliter (nL) scale is of paramount importance for medicine, drug development, toxicology, and research. Despite the numerous methodologies available, a tool for obtaining chemical information non-invasively is still missing at this scale. Observer effects, sample destruction and complex preparatory procedures remain a necessary compromise. Among non-invasive spectroscopic techniques, one able to provide holistic and highly resolved chemical information in-vivo is nuclear magnetic resonance (NMR). For its renowned informative power and ability to foster discoveries and life-saving applications, efficient NMR at microscopic scales is highly sought after, but so far technical limitations could not match the stringent necessities of microbiology, such as biocompatible handling, ease of use, and high throughput. Here we introduce a novel microsystem, which combines CMOS technology with 3D microfabrication, enabling nL NMR as a platform tool for non-invasive spectroscopy of organoids, 3D cell cultures, and early stage embryos. In this study we show its application to microlivers models simulating non-alcoholic fatty liver disease, demonstrating detection of lipid metabolism dynamics in a time frame of 14 days based on 117 measurements of single 3D human liver microtissues.