Metabolites involved in purine degradation, insulin resistance, and fatty acid oxidation are associated with prediction of Gestational diabetes in plasma

Mendelian randomization analysis reveals causal effects of blood lipidome on gestational diabetes mellitus

BACKGROUND

Observational studies have revealed associations between maternal lipid metabolites and gestational diabetes mellitus (GDM). However, whether these associations are causal remain uncertain.

OBJECTIVE

To evaluate the causal relationship between lipid metabolites and GDM.

METHODS

A two-sample Mendelian randomization (MR) analysis was performed based on summary statistics. Sensitivity analyses, validation analyses and reverse MR analyses were conducted to assess the robustness of the MR results. Additionally, a phenome-wide MR (Phe-MR) analysis was performed to evaluate potential side effects of the targeted lipid metabolites.

RESULTS

A total of 295 lipid metabolites were included in this study, 29 of them had three or more instrumental variables (IVs) suitable for sensitivity analyses. The ratio of triglycerides to phosphoglycerides (TG_by_PG) was identified as a potential causal biomarker for GDM (inverse variance weighted (IVW) estimate: odds ratio (OR) = 2.147, 95% confidential interval (95% CI) 1.415-3.257, P = 3.26e-4), which was confirmed by validation and reverse MR results. Two other lipid metabolites, palmitoyl sphingomyelin (d18:1/16:0) (PSM(d18:1/16:0)) (IVW estimate: OR = 0.747, 95% CI 0.583-0.956, P = 0.021) and triglycerides in very small very low-density lipoprotein (XS_VLDL_TG) (IVW estimate: OR = 2.948, 95% CI 1.197-5.215, P = 0.015), were identified as suggestive potential biomarkers for GDM using a conventional cut-off P-value of 0.05. Phe-MR results indicated that lowering TG_by_PG had detrimental effects on two diseases but advantageous effects on the other 13 diseases.

CONCLUSION

Genetically predicted elevated TG_by_PG are causally associated with an increased risk of GDM. Side-effect profiles indicate that TG_by_PG might be a target for GDM prevention, though caution is advised due to potential adverse effects on other conditions.

The effect of high-intensity interval training on type 2 diabetic muscle: A metabolomics-based study

Background

This study aimed to investigate the effect of eight weeks of high-intensity interval training (HIIT) on muscle metabolism in rats with type 2 diabetes (T2D) using metabolomics approaches.

Methods

20 male Wistar rats at the age of 8 weeks-were assigned to four groups of five, each in the group randomly: control (CTL), type 2 diabetes (DB), HIIT (EX), and type 2 diabetes + HIIT (DBX). T2D was induced by two months of a high-fat diet plus a single dose of streptozotocin (35 mg/kg). Rats in the EX and DBX groups performed eight weeks of HIIT (running at 80-100 % of Vmax, 4-10 intervals). NMR spectroscopy was used to determine the changes in the muscle metabolome profile after training.

Results

Changes in metabolite abundance following exercise revealed distinct clustering in multivariate analysis. The essential metabolite changes between the DB and CTL groups were arginine metabolism, purine metabolism, phosphate pathway, amino sugar metabolism, glutathione metabolism, and aminoacyl-tRNA biosynthesis. However, Arginine biosynthesis, pyrimidine metabolism, aminoacyl-tRNA biosynthesis, and alanine, aspartate, and glutamate metabolism were altered between the DBX and DB groups.

Conclusion

These results suggest that eight weeks of HIIT could reverse metabolic changes induced by T2D in rat muscles, contributing to reduced FBG and HOMA-IR levels.

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

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

Early time-restricted eating improves markers of cardiometabolic health but has no impact on intestinal nutrient absorption in healthy adults

Early time-restricted eating (eTRE) improves aspects of cardiometabolic health. Although the circadian system appears to regulate nutrient absorption, little is known about the effects of eTRE on intestinal absorption. In this randomized crossover trial, 16 healthy adults follow a controlled, weight maintenance diet for 9 days, consuming all calories between 0800 and 1400 (eTRE schedule) or 0800 and 2000 (control schedule). We measure the energy content of the diet, stool, and urine with bomb calorimetry and calculate intestinal energy absorption. The eTRE schedule is more effective than the control eating schedule for improving markers of cardiometabolic health, including 24-h mean glucose concentrations and glycemic variability, assessed as the mean amplitude of glycemic excursions. However, eTRE has no effect on intestinal energy and macronutrient absorption, gastrointestinal transit time, colonic hydrogen gas production, or stool microbial composition, suggesting eTRE does not impact gastrointestinal function. This trial is registered (ClinicalTrials.gov: NCT04877262).

Advances in Mass Spectrometry-Based Blood Metabolomics Profiling for Non-Cancer Diseases: A Comprehensive Review

Blood metabolomics profiling using mass spectrometry has emerged as a powerful approach for investigating non-cancer diseases and understanding their underlying metabolic alterations. Blood, as a readily accessible physiological fluid, contains a diverse repertoire of metabolites derived from various physiological systems. Mass spectrometry offers a universal and precise analytical platform for the comprehensive analysis of blood metabolites, encompassing proteins, lipids, peptides, glycans, and immunoglobulins. In this comprehensive review, we present an overview of the research landscape in mass spectrometry-based blood metabolomics profiling. While the field of metabolomics research is primarily focused on cancer, this review specifically highlights studies related to non-cancer diseases, aiming to bring attention to valuable research that often remains overshadowed. Employing natural language processing methods, we processed 507 articles to provide insights into the application of metabolomic studies for specific diseases and physiological systems. The review encompasses a wide range of non-cancer diseases, with emphasis on cardiovascular disease, reproductive disease, diabetes, inflammation, and immunodeficiency states. By analyzing blood samples, researchers gain valuable insights into the metabolic perturbations associated with these diseases, potentially leading to the identification of novel biomarkers and the development of personalized therapeutic approaches. Furthermore, we provide a comprehensive overview of various mass spectrometry approaches utilized in blood metabolomics research, including GC-MS, LC-MS, and others discussing their advantages and limitations. To enhance the scope, we propose including recent review articles supporting the applicability of GC×GC-MS for metabolomics-based studies. This addition will contribute to a more exhaustive understanding of the available analytical techniques. The Integration of mass spectrometry-based blood profiling into clinical practice holds promise for improving disease diagnosis, treatment monitoring, and patient outcomes. By unraveling the complex metabolic alterations associated with non-cancer diseases, researchers and healthcare professionals can pave the way for precision medicine and personalized therapeutic interventions. Continuous advancements in mass spectrometry technology and data analysis methods will further enhance the potential of blood metabolomics profiling in non-cancer diseases, facilitating its translation from the laboratory to routine clinical application.

The role of lipid dysregulation in gestational diabetes mellitus: Early prediction and postpartum prognosis

Gestational diabetes mellitus (GDM) is a pathological condition during pregnancy characterized by impaired glucose tolerance, and the failure of pancreatic beta-cells to respond appropriately to an increased insulin demand. However, while the majority of women with GDM will return to normoglycemia after delivery, they have up to a seven times higher risk of developing type 2 diabetes during midlife, compared with those with no history of GDM. Gestational diabetes mellitus also increases the risk of multiple metabolic disorders, including non-alcoholic fatty liver disease, obesity, and cardiovascular diseases. Lipid metabolism undergoes significant changes throughout the gestational period, and lipid dysregulation is strongly associated with GDM and the progression to future type 2 diabetes. In addition to common lipid variables, discovery-based omics techniques, such as metabolomics and lipidomics, have identified lipid biomarkers that correlate with GDM. These lipid species also show considerable potential in predicting the onset of GDM and subsequent type 2 diabetes post-delivery. This review aims to update the current knowledge of the role that lipids play in the onset of GDM, with a focus on potential lipid biomarkers or metabolic pathways. These biomarkers may be useful in establishing predictive models to accurately predict the future onset of GDM and type 2 diabetes, and early intervention may help to reduce the complications associated with GDM.

Gestational Diabetes Is Characterized by Decreased Medium-Chain Acylcarnitines and Elevated Purine Degradation Metabolites across Pregnancy: A Case-Control Time-Course Analysis

Gestational Diabetes Mellitus (GDM) results in complications affecting both mothers and their offspring. Metabolomic analysis across pregnancy provides an opportunity to better understand GDM pathophysiology. The objective was to conduct a metabolomics analysis of first and third trimester plasma samples to identify metabolic differences associated with GDM development. Forty pregnant women with overweight/obesity from a multisite clinical trial of a lifestyle intervention were included. Participants who developed GDM (n = 20; GDM group) were matched with those who did not develop GDM (n = 20; Non-GDM group). Plasma samples collected at the first (10-16 weeks) and third (28-35 weeks) trimesters were analyzed with ultra-performance liquid chromatography-mass spectrometry (UPLC-MS). Cardiometabolic risk markers, dietary recalls, and physical activity metrics were also assessed. Four medium-chain acylcarnitines, lauroyl-, octanoyl-, decanoyl-, and decenoylcarnitine, significantly differed over the course of pregnancy in the GDM vs Non-GDM group in a group-by-time interaction (p < 0.05). Hypoxanthine and inosine monophosphate were elevated in the GDM group (p < 0.04). In both groups over time, bile acids and sorbitol increased while numerous acylcarnitines and α-hydroxybutyrate decreased (p < 0.05). Metabolites involved in fatty acid oxidation and purine degradation were altered across the first and third trimesters of GDM-affected pregnancies, providing insight into metabolites and metabolic pathways altered with GDM development.

Electrospun Fibrous Nanocomposite Sensing Materials for Monitoring Biomarkers in Exhaled Breath

Human-exhaled breath mainly contains water, oxygen, carbon dioxide, and endogenous gases closely related to human metabolism. The linear relationship between breath acetone and blood glucose concentration has been revealed when monitoring diabetes patients. Considerable attention has been directed toward developing a highly sensitive volatile organic compounds (VOCs) sensing material that can detect breath acetone. In this study, we propose a tungsten oxide/tin oxide/silver/poly (methyl methacrylate) (WO₃/SnO₂/Ag/PMMA) sensing material fabricated using the electrospinning technique. By monitoring the evolution of sensing materials' extinction spectra, low concentrations of acetone vapor can be detected. Moreover, the interfaces between SnO₂ and WO₃ nanocrystals construct n-n junctions, which generate more electron-hole pairs than those without such structure when the light strikes. This helps to improve the sensitivity of sensing materials when they are subjected to acetone surroundings. The established sensing materials (WO₃/SnO₂/Ag/PMMA) exhibit a sensing limit of 20 ppm for acetone vapor and show specificity for acetone even in ambient humidity.

Identification of potential biomarkers and metabolic insights for gestational diabetes prevention: A review of evidence contrasting gestational diabetes versus weight loss studies that may direct future nutritional metabolomics studies

Gestational diabetes mellitus (GDM) significantly increases maternal health risks and adverse effects for the offspring. Observational studies suggest that weight loss before pregnancy may be a promising GDM prevention method. Still, biochemical pathways linking preconception weight changes with subsequent development of GDM among women who are overweight or obese remain unclear. Metabolomic assessment is a powerful approach for understanding the global biochemical pathways linking preconception weight changes and subsequent GDM. We hypothesize that many of the alterations of metabolite levels associated with GDM will change in one direction in GDM studies but will change in the opposite direction in studies focusing on lifestyle interventions for weight loss. The present review summarizes available evidence from 21 studies comparing women with GDM with healthy participants and 12 intervention studies that investigated metabolite changes that occurred during weight loss using caloric restriction and behavioral interventions. We discuss 15 metabolites, including amino acids, lipids, amines, carbohydrates, and carbohydrate derivatives. Of particular note are the altered levels of branched-chain amino acids, alanine, palmitoleic acid, lysophosphatidylcholine 18:1, and hypoxanthine because of their mechanistic links to insulin resistance and weight change. Mechanisms that may explain how these metabolite modifications contribute to GDM development in those who are overweight or obese are proposed, including insulin resistance pathways. Future nutritional metabolomics preconception intervention studies in overweight or obese are necessary to investigate whether weight loss through lifestyle intervention can reduce GDM occurrence in association with these metabolite alterations and to test the value of these metabolites as potential diagnostic biomarkers of GDM development.

Lipidomics in gestational diabetes mellitus

PURPOSE OF REVIEW

Epidemiological and mechanistic studies have reported relationships between blood lipids, mostly measured by traditional method in clinical settings, and gestational diabetes mellitus (GDM). Recent advances of high-throughput lipidomics techniques have made available more comprehensive lipid profiling in biological samples. This review aims to summarize evidence from prospective studies in assessing relations between blood lipids and GDM, and discuss potential underlying mechanisms.

RECENT FINDINGS

Mass spectrometry and nuclear magnetic resonance spectroscopy-based analytical platforms are extensively used in lipidomics research. Epidemiological studies have identified multiple novel lipidomic biomarkers that are associated with risk of GDM, such as certain types of fatty acids, glycerolipids, glycerophospholipids, sphingolipids, cholesterol, and lipoproteins. However, the findings are inconclusive mainly due to the heterogeneities in study populations, sample sizes, and analytical platforms. Mechanistic evidence indicates that abnormal lipid metabolism may be involved in the pathogenesis of GDM by impairing pancreatic β-cells and inducing insulin resistance through several etiologic pathways, such as inflammation and oxidative stress.

SUMMARY

Lipidomics is a powerful tool to study pathogenesis and biomarkers for GDM. Lipidomic biomarkers and pathways could help to identify women at high risk for GDM and could be potential targets for early prevention and intervention of GDM.

Metabolomics in gestational diabetes mellitus: A review

Gestational diabetes mellitus (GDM), a common complication of pregnancy, is a type of diabetes that is first detected and diagnosed during pregnancy. The incidence of GDM is increasing annually and is associated with many adverse pregnancy outcomes. Early prediction of the risk of GDM and intervention are thus important to reduce adverse pregnancy outcomes. Studies have revealed a correlation between the levels of amino acids, fatty acids, triglycerides, and other metabolites in early pregnancy and the occurrence of GDM. The development of high-throughput technologies used in metabolomics has enabled the detection of changes in the levels of small-molecule metabolites during early pregnancy, which can help reflect the overall physiological and pathological status of the body and explore the underlying mechanisms of the development of GDM. This review sought to summarize current research in this field and provide data for the development of strategies to manage GDM.

The Role of the Kynurenine Pathway in the (Patho) physiology of Maternal Pregnancy and Fetal Outcomes: A Systematic Review

INTRODUCTION

Tryptophan is the precursor of kynurenine pathway (KP) metabolites which regulate immune tolerance, energy metabolism, and vascular tone. Since these processes are important during pregnancy, changes in KP metabolite concentrations may play a role in the pathophysiology of pregnancy complications. We hypothesize that KP metabolites can serve as novel biomarkers and preventive therapeutic targets. This review aimed to provide more insight into associations between KP metabolite concentrations in maternal and fetal blood, and in the placenta, and adverse maternal pregnancy and fetal outcomes.

METHODS

A systematic search was performed on 18 February 2022 comprising all KP metabolites, and keywords related to maternal pregnancy and fetal outcomes. English-written human studies measuring KP metabolite(s) in maternal or fetal blood or in the placenta in relation to pregnancy complications, were included. Methodological quality was assessed using the ErasmusAGE quality score (QS) (range: 0-10). A meta-analysis of the mean maternal tryptophan and kynurenine concentrations in uncomplicated pregnancies was conducted.

RESULTS

Of the 6262 unique records, 37 were included (median QS = 5). Tryptophan was investigated in most studies, followed by kynurenine, predominantly in maternal blood (n = 28/37), and in the second and third trimester of pregnancy (n = 29/37). Compared to uncomplicated pregnancies, decreased tryptophan in maternal blood was associated with an increased prevalence of depression, gestational diabetes mellitus, fetal growth restriction, spontaneous abortion, and preterm birth. Elevated tryptophan was only observed in women with pregnancy-induced hypertension compared to normotensive pregnant women. In women with preeclampsia, only kynurenic acid was altered; elevated in the first trimester of pregnancy, and positively associated with proteinuria in the third trimester of pregnancy.

CONCLUSIONS

KP metabolite concentrations were altered in a variety of maternal pregnancy and fetal complications. This review implies that physiological pregnancy requires a tight balance of KP metabolites, and that disturbances in either direction are associated with adverse maternal pregnancy and fetal outcomes.

Investigation of Metabolome Underlying the Biological Mechanisms of Acute Heat Stressed Granulosa Cells

Heat stress affects granulosa cells and the ovarian follicular microenvironment, ultimately resulting in poor oocyte developmental competence. This study aims to investigate the metabo-lomics response of bovine granulosa cells (bGCs) to in vitro acute heat stress of 43 °C. Heat stress triggers oxidative stress-mediated apoptosis in cultured bGCs. Heat-stressed bGCs exhibited a time-dependent recovery of proliferation potential by 48 h. A total of 119 metabolites were identified through LC-MS/MS-based metabolomics of the spent culture media, out of which, 37 metabolites were determined as differentially involved in metabolic pathways related to bioenergetics support mechanisms and the physical adaptations of bGCs. Multiple analyses of metabolome data identified choline, citric acid, 3-hydroxy-3-methylglutaric acid, glutamine, and glycocyamine as being upregulated, while galactosamine, AICAR, ciliatine, 16-hydroxyhexadecanoic acid, lysine, succinic acid, uridine, xanthine, and uraconic acid were the important downregulated metabolites in acute heat stress. These differential metabolites were implicated in various important metabolic pathways directed towards bioenergetics support mechanisms including glycerophospholipid metabolism, the citrate cycle (TCA cycle), glyoxylate and dicarboxylate metabolism, and serine, threonine, and tyrosine metabolism. Our study presents important metabolites and metabolic pathways involved in the adaptation of bGCs to acute heat stress in vitro.

Application of Metabolomics in Various Types of Diabetes

Metabolomics is the analysis of numerous small molecules known as metabolites. Over the past few years, with the continuous development in metabolomics, it has been widely used in the detection, diagnosis, and treatment of diabetes and has demonstrated great benefits. At the same time, studies on diabetes and its complications have discovered the metabolic markers that are characteristic of diabetes. However, the pathogenesis of diabetes has yet to be clarified, as well as no complete cure. The mechanism of diabetes has not been completely elucidated, and its eradication treatment is not available. Thus, prevention of the onset of the disease and its treatment have become very important. In this review, we focused on the recent progress in the use of metabolites in diabetes and their complications, as well as understanding the impact of diabetes metabolites.