A new metabolomic signature in type-2 diabetes mellitus and its pathophysiology

Can endogenous ethylene glycol production occur in humans? A detailed investigation of adult monozygotic twin sisters

INTRODUCTION

To the best of our knowledge, clinically significant endogenous ethylene glycol production has never been reported in humans, very seldom reported in other animals or microorganisms, and then only under rare and specific conditions. We describe the detailed investigations we undertook in two adult monozygotic twin sisters to ascertain whether they were producing endogenous ethylene glycol.

METHODS

Two previously healthy monozygotic adult twin sisters presented with recurrent episodes of apparent ethylene glycol poisoning beginning at age 35, requiring chronic hemodialysis to remove ethylene glycol and its metabolites as well as to restore metabolic homeostasis. The sisters denied ingestion or exposure to ethylene glycol. At their request, they were admitted to hospital under strict supervision to exclude surreptitious ingestion of ethylene glycol and to evaluate the need for treatment. Hemodialysis was withheld during this prospective study. Twin A was admitted for 14 days and twin B for 11 days. Serial biochemical analyses were performed in blood and urine. Clinical exome sequencing and mitochondrial deoxyribonucleic acid sequencing were also completed.

RESULTS

In both twins, ethylene glycol was detected in urine, along with intermittent increases in concentrations of lactate, glycolate, and glycine in blood and/or urine. Blood ethylene glycol concentrations, however, remained <62 mg/L (<1 mmol/L) but became positive soon after discharge. The oxalate concentration remained normal in blood and urine. Plasma and urine amino acid profiles showed intermittent small increases in glycine, serine, taurine, proline, and/or alanine concentrations. Exome sequencing and mitochondrial deoxyribonucleic acid sequencing were non-diagnostic. Neither twin has been admitted with metabolic acidosis nor ethylene glycol poisoning since chronic hemodialysis was started. Twin A developed a calcium oxalate dihydrate lithiasis.

DISCUSSION

Mitochondrial disease, methylmalonic/propionic/isovaleric aciduria, primary hyperoxaluria, and analyte error were all excluded in these twins, as were obvious common environmental exposures.

CONCLUSION

Detailed investigations were performed in adult monozygotic twin sisters to ascertain whether they were producing endogenous ethylene glycol. Alternative explanations were excluded to the very best of our efforts and knowledge. Global metabolomics, gut microbiome analyses, and whole genome sequencing are pending.

Pharmacodynamic and targeted amino acid metabolomics researches on the improvement of diabetic retinopathy with Fufang Xueshuantong component compatibility

The Fufang Xueshuantong capsule (FXT) has significant preventive and therapeutic effects on diabetic retinopathy(DR), but the compatibility of its active components remains to be thoroughly explored. In this study, a zebrafish diabetic retinopathy model was established using high-mixed sugars, and the optimal ratios of notoginseng total saponins, total salvianolic acid, astragaloside, and harpagide were selected through orthogonal experiments. Furthermore, we used UPLC-QqQ/MS to detect the changes in amino acid content of DR zebrafish tissues after administration of FXT and its compatible formula to analyze the effects of FXT and its compatible formula on amino acid metabolites. The results showed that the final compatibility ratios of the components were 8: 5: 1: 6.6 by comprehensive evaluation of the indicators. FXT and its compatibility formula had beneficial effects on retinal vasodilatation, lipid accumulation in the liver, total glucose, and VEGF levels in DR zebrafish, and all of them could call back some amino acid levels in DR zebrafish. In this research, we determined the compatible formulation of the active ingredients in the FXT and investigated their efficacy in DR zebrafish for further clinical applications.

Advanced Mass Spectrometry-Based Biomarker Identification for Metabolomics of Diabetes Mellitus and Its Complications

Over the years, there has been notable progress in understanding the pathogenesis and treatment modalities of diabetes and its complications, including the application of metabolomics in the study of diabetes, capturing attention from researchers worldwide. Advanced mass spectrometry, including gas chromatography-tandem mass spectrometry (GC-MS/MS), liquid chromatography-tandem mass spectrometry (LC-MS/MS), and ultra-performance liquid chromatography coupled to electrospray ionization quadrupole time-of-flight mass spectrometry (UPLC-ESI-Q-TOF-MS), etc., has significantly broadened the spectrum of detectable metabolites, even at lower concentrations. Advanced mass spectrometry has emerged as a powerful tool in diabetes research, particularly in the context of metabolomics. By leveraging the precision and sensitivity of advanced mass spectrometry techniques, researchers have unlocked a wealth of information within the metabolome. This technology has enabled the identification and quantification of potential biomarkers associated with diabetes and its complications, providing new ideas and methods for clinical diagnostics and metabolic studies. Moreover, it offers a less invasive, or even non-invasive, means of tracking disease progression, evaluating treatment efficacy, and understanding the underlying metabolic alterations in diabetes. This paper summarizes advanced mass spectrometry for the application of metabolomics in diabetes mellitus, gestational diabetes mellitus, diabetic peripheral neuropathy, diabetic retinopathy, diabetic nephropathy, diabetic encephalopathy, diabetic cardiomyopathy, and diabetic foot ulcers and organizes some of the potential biomarkers of the different complications with the aim of providing ideas and methods for subsequent in-depth metabolic research and searching for new ways of treating the disease.

Identification of blood metabolic biomarkers associated with diabetic distal symmetric sensorimotor polyneuropathy in patients with type 2 diabetes mellitus

BACKGROUND

Distal symmetric sensorimotor polyneuropathy (DSPN) is a common neurologic complication of type 2 diabetes mellitus (T2DM), but the underlying mechanisms and changes in serum metabolites remain largely undefined. This study aimed to characterize the plasma metabolite profiles of participants with T2DM using targeted metabolomics analysis and identify potential biomarkers for DSPN.

METHODS

A combined liquid chromatography MS/MS and direct flow injection were used to quantify plasma metabolite obtained from 63 participants with T2DM, 81 with DSPN, and 33 nondiabetic control participants. A total of 130 metabolites, including amino acids, biogenic amines, sphingomyelins (SM), phosphatidylcholines, carnitines, and hexose, were analyzed.

RESULTS

A total of 16 plasma metabolites and 3 cholesterol-related laboratory parameters were found to have variable importance in the projection score >1.0 and false discovery rate <5.0% between control, T2DM, and DSPN. Among these variables, five serum metabolites, including phenylalanine (AUC = 0.653), alanine (AUC = 0.630), lysine (AUC = 0.622) tryptophan (AUC = 0.620), and SM C16:0 (AUC = 0.630), are potential biomarkers (all p < .05) in distinguishing T2DM with DSPN from those without (AUC = 0.720).

CONCLUSIONS

In this cross-sectional study, derangement of several metabolites in the plasma was observed in T2DM with and without DSPN, and these metabolites may be potential biomarkers for predicting DSPN. Longitudinal studies are warranted.

Cancer-associated fibroblast-secreted glucosamine alters the androgen biosynthesis program in prostate cancer via HSD3B1 upregulation

After androgen deprivation, prostate cancer frequently becomes castration resistant (CRPC), with intratumoral androgen production from extragonadal precursors that activate the androgen receptor pathway. 3β-Hydroxysteroid dehydrogenase-1 (3βHSD1) is the rate-limiting enzyme for extragonadal androgen synthesis, which together lead to CRPC. Here, we show that cancer-associated fibroblasts (CAFs) increased epithelial 3βHSD1 expression, induced androgen synthesis, activated the androgen receptor, and induced CRPC. Unbiased metabolomics revealed that CAF-secreted glucosamine specifically induced 3βHSD1. CAFs induced higher GlcNAcylation in cancer cells and elevated expression of the transcription factor Elk1, which induced higher 3βHSD1 expression and activity. Elk1 genetic ablation in cancer epithelial cells suppressed CAF-induced androgen biosynthesis in vivo. In patient samples, multiplex fluorescent imaging showed that tumor cells expressed more 3βHSD1 and Elk1 in CAF-enriched areas compared with CAF-deficient areas. Our findings suggest that CAF-secreted glucosamine increases GlcNAcylation in prostate cancer cells, promoting Elk1-induced HSD3B1 transcription, which upregulates de novo intratumoral androgen synthesis to overcome castration.

Metabolomics in Corneal Diseases: A Narrative Review from Clinical Aspects

Corneal pathologies may have subtle manifestations in the initial stages, delaying diagnosis and timely treatment. This can lead to irreversible visual loss. Metabolomics is a rapidly developing field that allows the study of metabolites in a system, providing a complementary tool in the early diagnosis and management of corneal diseases. Early identification of biomarkers is key to prevent disease progression. The advancement of nuclear magnetic resonance and mass spectrometry allows the identification of new biomarkers in the analysis of tear, cornea, and aqueous humor. Novel perspectives on disease mechanisms are identified, which provide vital information for potential targeted therapies in the future. Current treatments are analyzed at a molecular level to offer further information regarding their efficacy. In this article, we provide a comprehensive review of the metabolomic studies undertaken in the cornea and various pathologies such as dry eye disease, Sjogren’s syndrome, keratoconus, post-refractive surgery, contact lens wearers, and diabetic corneas. Lastly, we discuss the exciting future that metabolomics plays in cornea research.

Mixed meal tolerance testing highlights in diabetes altered branched-chain ketoacid metabolism and pathways associated with all-cause mortality

BACKGROUND

Elevated BCAA levels are strongly associated with diabetes, but how diabetes affects BCAA, branched-chain ketoacids (BCKAs), and the broader metabolome after a meal is not well known.

OBJECTIVE

To compare quantitative BCAA and BCKA levels in a multiracial cohort with and without diabetes after a mixed meal tolerance test (MMTT) as well as to explore the kinetics of additional metabolites and their associations with mortality in self-identified African Americans.

METHODS

We administered an MMTT to 11 participants without obesity or diabetes and 13 participants with diabetes (treated with metformin only) and measured the levels of BCKAs, BCAAs, and 194 other metabolites at 8 time points across 5 h. We used mixed models for repeated measurements to compare between group metabolite differences at each timepoint with adjustment for baseline. We then evaluated the association of top metabolites with different kinetics with all-cause mortality in the Jackson Heart Study (JHS) (N = 2441).

RESULTS

BCAA levels, after adjustment for baseline, were similar at all timepoints between groups, but adjusted BCKA kinetics were different between groups for α-ketoisocaproate (P = 0.022) and α-ketoisovalerate (P = 0.021), most notably diverging at 120 min post-MMTT. An additional 20 metabolites had significantly different kinetics across timepoints between groups, and 9 of these metabolites-including several acylcarnitines-were significantly associated with mortality in JHS, irrespective of diabetes status. The highest quartile of a composite metabolite risk score was associated with higher mortality (HR:1.57; 1.20, 2.05, P = 0.00094) than the lowest quartile.

CONCLUSIONS

BCKA levels remained elevated after an MMTT among participants with diabetes, suggesting that BCKA catabolism may be a key dysregulated process in the interaction of BCAA and diabetes. Metabolites with different kinetics after an MMTT may be markers of dysmetabolism and associated with increased mortality in self-identified African Americans.

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.

Pathophysiology of type 2 diabetes and the impact of altered metabolic interorgan crosstalk

Diabetes is a complex and multifactorial disease that affects millions of people worldwide, reducing the quality of life significantly, and results in grave consequences for our health care system. In type 2 diabetes (T2D), the lack of β-cell compensatory mechanisms overcoming peripherally developed insulin resistance is a paramount factor leading to disturbed blood glucose levels and lipid metabolism. Impaired β-cell functions and insulin resistance have been studied extensively resulting in a good understanding of these pathways but much less is known about interorgan crosstalk, which we define as signaling between tissues by secreted factors. Besides hormones and organokines, dysregulated blood glucose and long-lasting hyperglycemia in T2D is associated with changes in metabolism with metabolites from different tissues contributing to the development of this disease. Recent data suggest that metabolites, such as lipids including free fatty acids and amino acids, play important roles in the interorgan crosstalk during the development of T2D. In general, metabolic remodeling affects physiological homeostasis and impacts the development of T2D. Hence, we highlight the importance of metabolic interorgan crosstalk in this review to gain enhanced knowledge of the pathophysiology of T2D, which may lead to new therapeutic approaches to treat this disease.

Targeted and untargeted metabolomic approach for GDM diagnosis

Gestational diabetes mellitus (GDM) is a disorder which manifests itself for the first time during pregnancy and is mainly connected with glucose metabolism. It is also known that fatty acid profile changes in erythrocyte membranes and plasma could be associated with obesity and insulin resistance. These factors can lead to the development of diabetes. In the reported study, we applied the untargeted analysis of plasma in GDM against standard glucose-tolerant (NGT) women to identify the differences in metabolomic profiles between those groups. We found higher levels of 2-hydroxybutyric and 3-hydroxybutyric acids. Both secondary metabolites are associated with impaired glucose metabolism. However, they are products of different metabolic pathways. Additionally, we applied lipidomic profiling using gas chromatography to examine the fatty acid composition of cholesteryl esters in the plasma of GDM patients. Among the 14 measured fatty acids characterizing the representative plasma lipidomic cluster, myristic, oleic, arachidonic, and α-linoleic acids revealed statistically significant changes. Concentrations of both myristic acid, one of the saturated fatty acids (SFAs), and oleic acid, which belong to monounsaturated fatty acids (MUFAs), tend to decrease in GDM patients. In the case of polyunsaturated fatty acids (PUFAs), some of them tend to increase (e.g., arachidonic), and some of them tend to decrease (e.g., α-linolenic). Based on our results, we postulate the importance of hydroxybutyric acid derivatives, cholesteryl ester composition, and the oleic acid diminution in the pathophysiology of GDM. There are some evidence suggests that the oleic acid can have the protective role in diabetes onset. However, metabolic alterations that lead to the onset of GDM are complex; therefore, further studies are needed to confirm our observations.

Nontargeted and Targeted Metabolomic Profiling Reveals Novel Metabolite Biomarkers of Incident Diabetes in African Americans

Nontargeted metabolomics methods have increased potential to identify new disease biomarkers, but assessments of the additive information provided in large human cohorts by these less biased techniques are limited. To diversify our knowledge of diabetes-associated metabolites, we leveraged a method that measures 305 targeted or "known" and 2,342 nontargeted or "unknown" compounds in fasting plasma samples from 2,750 participants (315 incident cases) in the Jackson Heart Study (JHS)-a community cohort of self-identified African Americans-who are underrepresented in omics studies. We found 307 unique compounds (82 known) associated with diabetes after adjusting for age and sex at a false discovery rate of <0.05 and 124 compounds (35 known, including 11 not previously associated) after further adjustments for BMI and fasting plasma glucose. Of these, 144 and 68 associations, respectively, replicated in a multiethnic cohort. Among these is an apparently novel isomer of the 1-deoxyceramide Cer(m18:1/24:0) with functional geonomics and high-resolution mass spectrometry. Overall, known and unknown metabolites provided complementary information (median correlation ρ = 0.29), and their inclusion with clinical risk factors improved diabetes prediction modeling. Our findings highlight the importance of including nontargeted metabolomics methods to provide new insights into diabetes development in ethnically diverse cohorts.

Untargeted approach to investigating the metabolomics profile of type 2 diabetes emiratis

Type 2 Diabetes (T2D) is expected to be the seventh most significant cause of death worldwide by 2030. Although research into its mechanism has received the attention it deserves, our understanding of T2D is still limited. This case-control study employs untargeted metabolomics to explore novel T2D plasma biomarkers in the Emirati population. Ninety-two UAE nationals were included in the cohort, with fifty T2D and forty-two non-T2D profiles. Participants were then stratified into three groups based on metabolic profiles, clinically verified diabetic status, and current HbA1c values: namely controlled diabetics, uncontrolled diabetics and prediabetics, and non-diabetics. The study identified fifteen significant differentially abundant metabolites between the uncontrolled diabetics group and the prediabetics or controlled diabetics group. Interestingly, some metabolites essential for the corticosteroid and thyroid signaling pathways were found to be significantly elevated in poorly controlled T2D, including cortisol, glycocholic acid, bile acids, thyroxine, and the tryptophan metabolite, 5-hydroxyindoleacetic acid. These findings align with those from prior western cohorts and suggest an intriguing linkage between T2D glycemic control and thyroid and adrenal signaling that may provide new diagnostic and prognostic indicators. RESEARCH SIGNIFICANCE: This study investigates the underlooked metabolomic role and correlation with T2D in the UAE population. The report indicates fifteen significant differentially abundant metabolites between on diabetics, uncontrolled diabetics and or controlled diabetics or prediabetics. This panel of metabolites such as thyroxine and corticosteroids should be considered further as potential diagnostic or prognostic biomarkers for T2D in the region.

Environmental risk factors of type 2 diabetes-an exposome approach

Type 2 diabetes is one of the major chronic diseases accounting for a substantial proportion of disease burden in Western countries. The majority of the burden of type 2 diabetes is attributed to environmental risks and modifiable risk factors such as lifestyle. The environment we live in, and changes to it, can thus contribute substantially to the prevention of type 2 diabetes at a population level. The 'exposome' represents the (measurable) totality of environmental, i.e. nongenetic, drivers of health and disease. The external exposome comprises aspects of the built environment, the social environment, the physico-chemical environment and the lifestyle/food environment. The internal exposome comprises measurements at the epigenetic, transcript, proteome, microbiome or metabolome level to study either the exposures directly, the imprints these exposures leave in the biological system, the potential of the body to combat environmental insults and/or the biology itself. In this review, we describe the evidence for environmental risk factors of type 2 diabetes, focusing on both the general external exposome and imprints of this on the internal exposome. Studies provided established associations of air pollution, residential noise and area-level socioeconomic deprivation with an increased risk of type 2 diabetes, while neighbourhood walkability and green space are consistently associated with a reduced risk of type 2 diabetes. There is little or inconsistent evidence on the contribution of the food environment, other aspects of the social environment and outdoor temperature. These environmental factors are thought to affect type 2 diabetes risk mainly through mechanisms incorporating lifestyle factors such as physical activity or diet, the microbiome, inflammation or chronic stress. To further assess causality of these associations, future studies should focus on investigating the longitudinal effects of our environment (and changes to it) in relation to type 2 diabetes risk and whether these associations are explained by these proposed mechanisms.

Curcumin Reverts the Protein Differential Expression in the Liver of the Diabetic Obese db/db Mice

Background:

In type 2 diabetic mouse liver, hyperglycemia, and insulin modify gene expression. Curcumin is a powerful antioxidant and antidiabetic agent that regulates the gene expression of different signaling pathways through various transcription factors. Therefore, we hypothesized that curcumin modifies the protein expression profile in the liver of diabetic db/db mice.

Objective:

To determine the effects of curcumin on the liver protein profile of diabetic db/db mice.

Methods:

db/db and wild type (WT) male mice were allocated in four groups, and they were fed for eight weeks. Three WT and three diabetic db/db mice received a standard diet (SD; WT and db/db groups, respectively); three WT and three diabetic db/db mice received a SD supplemented with 0.75 % (w/w) curcumin (WT+C and db/db+C groups, respectively). Liver proteins were separated by 2D electrophoresis. Differential protein expression analysis was performed on ImageMaster 2D Platinum software, and selected proteins were identified by MALDI-TOF-MS and subjected to enrichment analysis using STRING and DAVID databases.

Results:

Thirty-six proteins with differential expression due to the diabetic background and curcumin treatment were found; these proteins participate in the metabolism of amino acids, carbohydrates, and lipids. Interestingly, the altered expression of seven proteins was prevented in the liver of the diabetic mice that received curcumin.

Conclusions:

Among all differentially expressed proteins, curcumin reverted the altered expression of seven proteins. Thus, although it was observed that curcumin did not affect the biochemical parameters, it does modify the expression of some liver proteins in diabetic mice.

Determination of up to twenty carboxylic acid containing compounds in clinically relevant matrices by o-benzylhydroxylamine derivatization and liquid chromatography-tandem mass spectrometry

Carboxylic acid containing compounds (R-COOH) are involved in a large number of biological processes and they are relevant for several pathological processes such as neurodegeneration or cancer. Comprehensive methodologies for the quantitative determination of R-COOH in biological samples are required. In this study we have developed a LC-MS/MS method for the quantification of 20 endogenous R-COOH belonging to different pathways such as kynurenine metabolism, serotoninergic pathway, glycolysis, tricarboxylic acid cycle, dopaminergic pathway, short chain fatty acids and glycine metabolism. The approach included derivatization with o-benzylhydroxylamine (reaction time 1 h), liquid-liquid extraction with ethyl acetate and LC-MS/MS detection (run time 10 min). The method was optimized and validated in 5 different matrices (urine, plasma, saliva, brain and liver) following two different approaches: (i) using surrogate matrices and (ii) using actual human samples by standard additions. A suitable linearity was obtained in the endogenous range of the analytes. Adequate intra and inter-assay accuracies (80-120%) and intra- and inter-assay precisions (<20%) were achieved for almost all analytes in all studied matrices. The method was applied in several scenarios to confirm (i) human urinary changes produced in glycolysis after exercise, (ii) metabolic changes produced in rat brain and plasma by methamphetamine administration and (iii) metabolic alterations in human plasma caused by vitamin B6 deficiency. Additionally, the application of the method allowed for establishing previously unreported alterations in R-COOH metabolites under these conditions. Due to the comprehensive analyte and matrix coverage and the wide applicability of the developed methodology, it can be considered as a suitable tool for the study of R-COOH status in health and disease by targeted metabolomics.

Emerging Applications of Metabolomics to Assess the Efficacy of Traditional Chinese Medicines for Treating Type 2 Diabetes Mellitus

Diabetes is a common and complex disease that can exacerbate the complications related to cardiovascular disease, and this is especially true for type 2 diabetes mellitus (T2DM). In addition to the standard pharmacological therapies, T2DM has also been treated with nonconventional regimens such as traditional Chinese medicine (TCM), e.g., herbal medicines and TCM prescriptions, although the mechanisms underlying the therapeutic benefits remain unclear. In this regard, many studies have used metabolomics technology to elucidate the basis for the efficacy of TCM for T2DM. Metabolomics has recently attracted much attention with regard to drug discovery and pharmacologically relevant natural products. In this review, we summarize the application of metabolomics to the assessment of TCM efficacy for treating T2DM. Increasing evidence suggests that the metabolic profile of an individual patient may reflect a specific type of T2DM syndrome, which may provide a new perspective for disease diagnosis. In addition, TCM has proved effective for countering the metabolic disorders related to T2DM, and this may constitute the basis for TCM efficacy. Therefore, further determining how TCM contributes to the reversal of metabolic disorders, such as using network pharmacology or by assessing the contribution of host–gut microbiota interactions, will also provide researchers with new potential targets for pharmacologic-based therapies.

Comparison of the blood, bone marrow, and cerebrospinal fluid metabolomes in children with b-cell acute lymphoblastic leukemia

Metabolomics may shed light on treatment response in childhood acute lymphoblastic leukemia (ALL), however, most assessments have analyzed bone marrow or cerebrospinal fluid (CSF), which are not collected during all phases of therapy. Blood is collected frequently and with fewer risks, but it is unclear whether findings from marrow or CSF biomarker studies may translate. We profiled end-induction plasma, marrow, and CSF from N = 10 children with B-ALL using liquid chromatography-mass spectrometry. We estimated correlations between plasma and marrow/CSF metabolite abundances detected in ≥ 3 patients using Spearman rank correlation coefficients (r_s). Most marrow metabolites were detected in plasma (N = 661; 81%), and we observed moderate-to-strong correlations (median r_s 0.62, interquartile range [IQR] 0.29–0.83). We detected 328 CSF metabolites in plasma (90%); plasma-CSF correlations were weaker (median r_s 0.37, IQR 0.07–0.70). We observed plasma-marrow correlations for metabolites in pathways associated with end-induction residual disease (pyruvate, asparagine) and plasma-CSF correlations for a biomarker of fatigue (gamma-glutamylglutamine). There is considerable overlap between the plasma, marrow, and CSF metabolomes, and we observed strong correlations for biomarkers of clinically relevant phenotypes. Plasma may be suitable for biomarker studies in B-ALL.

Diabetes and Heart Failure: Multi-Omics Approaches

Diabetes and heart failure, as important global issues, cause substantial expenses to countries and medical systems because of the morbidity and mortality rates. Most people with diabetes suffer from type 2 diabetes, which has an amplifying effect on the prevalence and severity of many health problems such as stroke, neuropathy, retinopathy, kidney injuries, and cardiovascular disease. Type 2 diabetes is one of the cornerstones of heart failure, another health epidemic, with 44% prevalence. Therefore, finding and targeting specific molecular and cellular pathways involved in the pathophysiology of each disease, either in diagnosis or treatment, will be beneficial. For diabetic cardiomyopathy, there are several mechanisms through which clinical heart failure is developed; oxidative stress with mediation of reactive oxygen species (ROS), reduced myocardial perfusion due to endothelial dysfunction, autonomic dysfunction, and metabolic changes, such as impaired glucose levels caused by insulin resistance, are the four main mechanisms. In the field of oxidative stress, advanced glycation end products (AGEs), protein kinase C (PKC), and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) are the key mediators that new omics-driven methods can target. Besides, diabetes can affect myocardial function by impairing calcium (Ca) homeostasis, the mechanism in which reduced protein phosphatase 1 (PP1), sarcoplasmic/endoplasmic reticulum Ca2+ ATPase 2a (SERCA2a), and phosphorylated SERCA2a expressions are the main effectors. This article reviewed the recent omics-driven discoveries in the diagnosis and treatment of type 2 diabetes and heart failure with focus on the common molecular mechanisms.

Effect of Vitamin B2-Deficient Diet on Hydroxyproline- or Obesity-Induced Hyperoxaluria in Mice

SCOPE

Hyperoxaluria is a major cause of kidney stone disease. Around half of the oxalate in mammals is supplied from the diet and the other half is endogenously synthesized from glyoxylate. Reduction of hepatic glycolate oxidase (GO) activity is one approach to reduce endogenous production of oxalate. However, there are currently few effective dietary approaches to reduce hepatic GO activity.

METHODS AND RESULTS

In the present study, it is investigated whether restriction of dietary vitamin B2 (VB2) can reduce hepatic GO activity and oxalate excretion in mice with hyperoxaluria induce by hydroxyproline (Hyp) or obesity. It is found that VB2 restriction significantly reduces hepatic GO activity in both the Hyp- and obesity-induced model of hyperoxaluria in mice. However, VB2 restriction reduces urinary oxalate excretion only in the Hyp-treated mice and not the obese mice. This difference could be due to the contribution of endogenous oxalate production that manifests as increased hepatic GO activity in Hyp-treated mice but not obese mice.

CONCLUSION

Together these results suggest that VB2 restriction could be a new dietary approach to improve hyperoxaluria when endogenous production of oxalate is increased.

Associations of network-derived metabolite clusters with prevalent type 2 diabetes among adults of Puerto Rican descent

INTRODUCTION

We investigated whether network analysis revealed clusters of coregulated metabolites associated with prevalent type 2 diabetes (T2D) among Puerto Rican adults.

RESEARCH DESIGN AND METHODS

We used liquid chromatography-mass spectrometry to measure fasting plasma metabolites (>600) among participants aged 40-75 years in the Boston Puerto Rican Health Study (BPRHS; discovery) and San Juan Overweight Adult Longitudinal Study (SOALS; replication), with (n=357; n=77) and without (n=322; n=934) T2D, respectively. Among BPRHS participants, we used unsupervised partial correlation network-based methods to identify and calculate metabolite cluster scores. Logistic regression was used to assess cross-sectional associations between metabolite clusters and prevalent T2D at the baseline blood draw in the BPRHS, and significant associations were replicated in SOALS. Inverse-variance weighted random-effect meta-analysis was used to combine cohort-specific estimates.

RESULTS

Six metabolite clusters were significantly associated with prevalent T2D in the BPRHS and replicated in SOALS (false discovery rate (FDR) <0.05). In a meta-analysis of the two cohorts, the OR and 95% CI (per 1 SD increase in cluster score) for prevalent T2D were as follows for clusters characterized primarily by glucose transport (0.21 (0.16 to 0.30); FDR <0.0001), sphingolipids (0.40 (0.29 to 0.53); FDR <0.0001), acyl cholines (0.35 (0.22 to 0.56); FDR <0.0001), sugar metabolism (2.28 (1.68 to 3.09); FDR <0.0001), branched-chain and aromatic amino acids (2.22 (1.60 to 3.08); FDR <0.0001), and fatty acid biosynthesis (1.54 (1.29 to 1.85); FDR <0.0001). Three additional clusters characterized by amino acid metabolism, cell membrane components, and aromatic amino acid metabolism displayed significant associations with prevalent T2D in the BPRHS, but these associations were not replicated in SOALS.

CONCLUSIONS

Among Puerto Rican adults, we identified several known and novel metabolite clusters that associated with prevalent T2D.

Environmental pollution and diabetes mellitus

Diabetes mellitus (DM) is a chromic metabolic disease that affects a large segment of the population worldwide. Physical inactivity, poor nutrition, and genetic predisposition are main risk factors for disease development. In the last decade, it was clear to the scientific community that DM development is linked to a novel disease inducer that was later defined as diabetogenic factors of pollution and endocrine disrupting agents. Environmental pollution is exponentially increasing in uncontrolled manner in several countries. Environmental pollutants are of diverse nature and toxicities, including polyaromatic hydrocarbons (PAHs), pesticides, and heavy metals. In the current review, we shed light on the impact of each class of these pollutants and the underlined molecular mechanism of diabetes induction and biological toxicities. Finally, a brief overview about the connection between coronavirus disease 2019 and diabetes pandemics is presented.

Integration of Metabolomics and Transcriptomicsto Comprehensively Evaluate the Metabolic Effects of Gelsemium elegans on Pigs

Some naturalphytogenic feed additives, which contain several active compounds, have been shown to be effective alternatives to traditional antibiotics. Gelsemium elegans (G. elegans) is a whole grass in the family Loganiaceae. It is a known toxic plant widely distributed in China and has been used as a traditional Chinese herbal medicine for many years to treat neuropathic pain, rheumatoid pain, inflammation, skin ulcers, and cancer. However, G. elegans not only is nontoxic to animals such as pigs and sheep but also has an obvious growth-promoting effect. To our knowledge, the internal mechanism of the influence of G. elegans on the animal body is still unclear. The goal of this work is to evaluate the metabolic consequences of feeding piglets G. elegans for 45 days based on the combination of transcriptomics and metabolomics. According to growth measurement and evaluation, compared with piglets fed a complete diet, adding 20 g/kg G. elegans powder to the basal diet of piglets significantly reduced the feed conversion ratio. Results of the liver transcriptome suggest that glycine and cysteine-related regulatory pathways, including the MAPK signaling pathway and the mTOR signaling pathway, were extensively altered in G. elegans-induced piglets. Plasma metabolomics identified 21 and 18 differential metabolites (p < 0.05) in the plasma of piglets in the positive and negative ion modes, respectively, between G. elegans exposure and complete diet groups. The concentrations of glycine and its derivatives and N-acetylcysteine were higher in the G. elegans exposure group than in the complete diet group.This study demonstrated that G. elegans could be an alternative to antibiotics that improves the immune function of piglets, and the latent mechanism of G. elegans may be related to various signaling pathways, including the MAPK signaling pathway and the PPAR signaling pathway.

Triangulating evidence from longitudinal and Mendelian randomization studies of metabolomic biomarkers for type 2 diabetes

The number of people affected by Type 2 diabetes mellitus (T2DM) is close to half a billion and is on a sharp rise, representing a major and growing public health burden. Given its mild initial symptoms, T2DM is often diagnosed several years after its onset, leaving half of diabetic individuals undiagnosed. While several classical clinical and genetic biomarkers have been identified, improving early diagnosis by exploring other kinds of omics data remains crucial. In this study, we have combined longitudinal data from two population-based cohorts CoLaus and DESIR (comprising in total 493 incident cases vs. 1360 controls) to identify new or confirm previously implicated metabolomic biomarkers predicting T2DM incidence more than 5 years ahead of clinical diagnosis. Our longitudinal data have shown robust evidence for valine, leucine, carnitine and glutamic acid being predictive of future conversion to T2DM. We confirmed the causality of such association for leucine by 2-sample Mendelian randomisation (MR) based on independent data. Our MR approach further identified new metabolites potentially playing a causal role on T2D, including betaine, lysine and mannose. Interestingly, for valine and leucine a strong reverse causal effect was detected, indicating that the genetic predisposition to T2DM may trigger early changes of these metabolites, which appear well-before any clinical symptoms. In addition, our study revealed a reverse causal effect of metabolites such as glutamic acid and alanine. Collectively, these findings indicate that molecular traits linked to the genetic basis of T2DM may be particularly promising early biomarkers.

CMap analysis identifies Atractyloside as a potential drug candidate for type 2 diabetes based on integration of metabolomics and transcriptomics

Background

This research aimed at exploring the mechanisms of alterations of metabolites and pathways in T2D from the perspective of metabolomics and transcriptomics, as well as uncovering novel drug candidate for T2D treatment.

Methods

Metabolites in human plasma from 42 T2D patients and 45 non‐diabetic volunteers were detected by liquid chromatography‐mass spectrometer (LC‐MS). Microarray dataset of the transcriptome was obtained from Gene Expression Omnibus (GEO) database. Kyoto Encyclopedia of Genes and Genomes (KEGG) database was used to conduct pathway enrichment analysis. Connectivity Map (CMap) was employed to select potential drugs for T2D therapy. In vivo assay was performed to verify above findings. The protein expression levels of ME1, ME2 and MDH1 were detected by Western blot to determine the status of NAD/NADH cofactor system.

Results

In our study, differentially expressed metabolites were selected out between healthy samples and T2D samples with selection criteria P value < .05, |Fold Change| > 2, including N‐acetylglutamate and Malate. Genes set enrichment analysis (GSEA) revealed that 34 pathways were significantly enriched in T2D. Based on CMap analysis and animal experiments, Atractyloside was identified as a potential novel drug for T2D treatment via targeting ME1, ME2 and MDH1 and regulating the NAD/NADH cofactor system.

Conclusion

The present research revealed differentially expressed metabolites and genes, as well as significantly altered pathways in T2D via an integration of metabolomics, transcriptomics and CMap analysis. It was also demonstrated that comprehensive analysis based on metabolomics and transcriptomics was an effective approach for identification and verification of metabolic biomarkers and alternated pathways.

Metabolomics and Proteomics in Type 2 Diabetes

The persistent increase in the worldwide burden of type 2 diabetes mellitus (T2D) and the accompanying rise of its complications, including cardiovascular disease, necessitates our understanding of the metabolic disturbances that cause diabetes mellitus. Metabolomics and proteomics, facilitated by recent advances in high-throughput technologies, have given us unprecedented insight into circulating biomarkers of T2D even over a decade before overt disease. These markers may be effective tools for diabetes mellitus screening, diagnosis, and prognosis. As participants of metabolic pathways, metabolite and protein markers may also highlight pathways involved in T2D development. The integration of metabolomics and proteomics with genomics in multiomics strategies provides an analytical method that can begin to decipher causal associations. These methods are not without their limitations; however, with careful study design and sample handling, these methods represent powerful scientific tools that can be leveraged for the study of T2D. In this article, we aim to give a timely overview of circulating metabolomics and proteomics findings with T2D observed in large human population studies to provide the reader with a snapshot into these emerging fields of research.

Sedentariness and Urinary Metabolite Profile in Type 2 Diabetic Patients, a Cross-Sectional Study

Recent findings indicate a significant association between sedentary (SED)-time and type 2 diabetes mellitus (T2DM). The aim of this study was to investigate whether different levels of SED-time could impact on biochemical and physiological processes occurring in sedentary and physically inactive T2DM patients. In particular, patients from the “Italian Diabetes and Exercise Study (IDES)_2 trial belonging to the first and fourth quartile of SED-time were compared. Urine samples were analyzed by comprehensive two-dimensional gas chromatography (GC × GC) with parallel detection by mass spectrometry and flame ionization detection (GC × 2GC-MS/FID). This platform enables accurate profiling and fingerprinting of urinary metabolites while maximizing the overall information capacity, quantitation reliability, and response linearity. Moreover, using advanced pattern recognition, the fingerprinting process was extended to untargeted and targeted features, revealing diagnostic urinary fingerprints between groups. Quantitative metabolomics was then applied to analytes of relevance for robust comparisons. Increased levels of glycine, L-valine, L-threonine, L-phenylalanine, L-leucine, L-alanine, succinic acid, 2-ketoglutaric acid, xylitol, and ribitol were revealed in samples from less sedentary women. In conclusion, SED-time is associated with changes in urine metabolome signatures. These preliminary results suggest that reducing SED-time could be a strategy to improve the health status of a large proportion of diabetic patients.

Amino acid and lipid metabolism in post-gestational diabetes and progression to type 2 diabetes: A metabolic profiling study

BACKGROUND

Women with a history of gestational diabetes mellitus (GDM) have a 7-fold higher risk of developing type 2 diabetes (T2D) during midlife and an elevated risk of developing hypertension and cardiovascular disease. Glucose tolerance reclassification after delivery is recommended, but fewer than 40% of women with GDM are tested. Thus, improved risk stratification methods are needed, as is a deeper understanding of the pathology underlying the transition from GDM to T2D. We hypothesize that metabolites during the early postpartum period accurately distinguish risk of progression from GDM to T2D and that metabolite changes signify underlying pathophysiology for future disease development.

METHODS AND FINDINGS

The study utilized fasting plasma samples collected from a well-characterized prospective research study of 1,035 women diagnosed with GDM. The cohort included racially/ethnically diverse pregnant women (aged 20-45 years-33% primiparous, 37% biparous, 30% multiparous) who delivered at Kaiser Permanente Northern California hospitals from 2008 to 2011. Participants attended in-person research visits including 2-hour 75-g oral glucose tolerance tests (OGTTs) at study baseline (6-9 weeks postpartum) and annually thereafter for 2 years, and we retrieved diabetes diagnoses from electronic medical records for 8 years. In a nested case-control study design, we collected fasting plasma samples among women without diabetes at baseline (n = 1,010) to measure metabolites among those who later progressed to incident T2D or did not develop T2D (non-T2D). We studied 173 incident T2D cases and 485 controls (pair-matched on BMI, age, and race/ethnicity) to discover metabolites associated with new onset of T2D. Up to 2 years post-baseline, we analyzed samples from 98 T2D cases with 239 controls to reveal T2D-associated metabolic changes. The longitudinal analysis tracked metabolic changes within individuals from baseline to 2 years of follow-up as the trajectory of T2D progression. By building prediction models, we discovered a distinct metabolic signature in the early postpartum period that predicted future T2D with a median discriminating power area under the receiver operating characteristic curve of 0.883 (95% CI 0.820-0.945, p < 0.001). At baseline, the most striking finding was an overall increase in amino acids (AAs) as well as diacyl-glycerophospholipids and a decrease in sphingolipids and acyl-alkyl-glycerophospholipids among women with incident T2D. Pathway analysis revealed up-regulated AA metabolism, arginine/proline metabolism, and branched-chain AA (BCAA) metabolism at baseline. At follow-up after the onset of T2D, up-regulation of AAs and down-regulation of sphingolipids and acyl-alkyl-glycerophospholipids were sustained or strengthened. Notably, longitudinal analyses revealed only 10 metabolites associated with progression to T2D, implicating AA and phospholipid metabolism. A study limitation is that all of the analyses were performed with the same cohort. It would be ideal to validate our findings in an independent longitudinal cohort of women with GDM who had glucose tolerance tested during the early postpartum period.

CONCLUSIONS

In this study, we discovered a metabolic signature predicting the transition from GDM to T2D in the early postpartum period that was superior to clinical parameters (fasting plasma glucose, 2-hour plasma glucose). The findings suggest that metabolic dysregulation, particularly AA dysmetabolism, is present years prior to diabetes onset, and is revealed during the early postpartum period, preceding progression to T2D, among women with GDM.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT01967030.

Urinary oxalate as a potential mediator of kidney disease in diabetes mellitus and obesity

PURPOSE OF REVIEW

Hyperoxaluria can cause kidney disease through multiple mechanisms, including tubular obstruction from calcium oxalate crystals, sterile inflammation, and tubular epithelial cell injury. Hyperoxaluria is also observed in individuals with diabetes mellitus and obesity, which are in turn risk factors for chronic kidney disease (CKD). Whether hyperoxaluria is a potential mediator of increased risk of CKD in diabetes mellitus and obesity is unknown.

RECENT FINDINGS

Individuals with diabetes have increased levels of plasma glyoxal (a protein glycation product) and glyoxylate, both of which are precursors for oxalate. Increased gut absorption of oxalate in obesity may be because of obesity-associated inflammation. A recent study in individuals with CKD found that higher 24 h urinary oxalate excretion was independently associated with increased risk of kidney disease progression, especially in individuals with diabetes and obesity.

SUMMARY

Both diabetes mellitus and obesity are associated with higher urinary oxalate excretion through distinct mechanisms. Hyperoxaluria could be a mechanism by which kidney disease develops in individuals with diabetes mellitus or obesity and could also contribute to progressive loss of renal function. Future research on pharmacologic or dietary measures to limit oxalate absorption or generation are required to test whether lowering urinary oxalate excretion is beneficial in preventing kidney disease development and progression in diabetes mellitus and obesity.

Glycolysis/gluconeogenesis- and tricarboxylic acid cycle-related metabolites, Mediterranean diet, and type 2 diabetes

BACKGROUND

Glycolysis/gluconeogenesis and tricarboxylic acid (TCA) cycle metabolites have been associated with type 2 diabetes (T2D). However, the associations of these metabolites with T2D incidence and the potential effect of dietary interventions remain unclear.

OBJECTIVES

We aimed to evaluate the association of baseline and 1-y changes in glycolysis/gluconeogenesis and TCA cycle metabolites with insulin resistance and T2D incidence, and the potential modifying effect of Mediterranean diet (MedDiet) interventions.

METHODS

We included 251 incident T2D cases and 638 noncases in a nested case-cohort study within the PREDIMED Study during median follow-up of 3.8 y. Participants were allocated to MedDiet + extra-virgin olive oil, MedDiet + nuts, or control diet. Plasma metabolites were measured using a targeted approach by LC-tandem MS. We tested the associations of baseline and 1-y changes in glycolysis/gluconeogenesis and TCA cycle metabolites with subsequent T2D risk using weighted Cox regression models and adjusting for potential confounders. We designed a weighted score combining all these metabolites and applying the leave-one-out cross-validation approach.

RESULTS

Baseline circulating concentrations of hexose monophosphate, pyruvate, lactate, alanine, glycerol-3 phosphate, and isocitrate were significantly associated with higher T2D risk (17-44% higher risk for each 1-SD increment). The weighted score including all metabolites was associated with a 30% (95% CI: 1.12, 1.51) higher relative risk of T2D for each 1-SD increment. Baseline lactate and alanine were associated with baseline and 1-y changes of homeostasis model assessment of insulin resistance. One-year increases in most metabolites and in the weighted score were associated with higher relative risk of T2D after 1 y of follow-up. Lower risks were observed in the MedDiet groups than in the control group although no significant interactions were found after adjusting for multiple comparisons.

CONCLUSIONS

We identified a panel of glycolysis/gluconeogenesis-related metabolites that was significantly associated with T2D risk in a Mediterranean population at high cardiovascular disease risk. A MedDiet could counteract the detrimental effects of these metabolites.This trial was registered at controlled-trials.com as ISRCTN35739639.

The Impact of New Biomarkers and Drug Targets on Age-Related Disorders

The increase in the human lifespan has not been paralleled by an increase in healthy life. With the increase in the proportion of the aged population, there has been a natural increase in the prevalence of age-related disorders, such as Alzheimer's disease, type 2 diabetes mellitus, frailty, and various other disorders. A continuous rise in these conditions could lead to a widespread medical and social burden. There are now considerable efforts underway to address these deficits in preclinical and clinical studies, which include the use of better study cohorts, longitudinal designs, improved translation of data from preclinical models, multi-omics profiling, identification of new biomarker candidates and refinement of computational tools and databases containing relevant information. Such efforts will support future interdisciplinary studies and help to identify potential new targets that are amenable to therapeutic approaches such as pharmacological interventions to increase the human healthspan in parallel with the lifespan.

Integration of lipidomics and metabolomics for in-depth understanding of cellular mechanism and disease progression

Mass spectrometry (MS)-based omics technologies are now widely used to profile small molecules in multiple matrices to confer comprehensive snapshots of cellular metabolic phenotypes. The metabolomes of cells, tissues, and organisms comprise a variety of molecules including lipids, amino acids, sugars, organic acids, and so on. Metabolomics mainly focus on the hydrophilic classes, while lipidomics has emerged as an independent omics owing to the complexities of the organismal lipidomes. The potential roles of lipids and small metabolites in disease pathogenesis have been widely investigated in various human diseases, but system-level understanding is largely lacking, which could be partly attributed to the insufficiency in terms of metabolite coverage and quantitation accuracy in current analytical technologies. While scientists are continuously striving to develop high-coverage omics approaches, integration of metabolomics and lipidomics is becoming an emerging approach to mechanistic investigation. Integration of metabolome and lipidome offers a complete atlas of the metabolic landscape, enabling comprehensive network analysis to identify critical metabolic drivers in disease pathology, facilitating the study of interconnection between lipids and other metabolites in disease progression. In this review, we summarize omics-based findings on the roles of lipids and metabolites in the pathogenesis of selected major diseases threatening public health. We also discuss the advantages of integrating lipidomics and metabolomics for in-depth understanding of molecular mechanism in disease pathogenesis.

Metabolomics-Based Prospective Studies and Prediction of Type 2 Diabetes Mellitus Risks

The preceding decade has witnessed an intense upsurge in the diabetic population across the world making type 2 diabetes mellitus (T2DM) more of an epidemic than a lifestyle disease. Metabolic disorders are often latent for a while before becoming clinically evident, thus reinforcing the pursuit of early biomarkers of metabolic alterations. A prospective study along with metabolic profiling is the most appropriate way to detect the early pathophysiological changes in metabolic diseases such as T2DM. The aim of this review was to summarize the different potential biomarkers of T2DM identified in prospective studies, which used tools of metabolomics. The review also demonstrates on how metabolomic profiling-based prospective studies can be used to address a concern like population-specific disease mechanism. We performed a literature search on metabolomics-based prospective studies on T2DM using the key words "metabolomics," "Type 2 diabetes," "diabetes mellitus", "metabolite profiling," "prospective study," "metabolism," and "biomarker." Additional articles that were obtained from the reference lists of the articles obtained using the above key words were also examined. Articles on dietary intake, type 1 diabetes mellitus, and gestational diabetes were excluded. The review revealed that many studies showed a direct association of branched-chain amino acids and an inverse association of glycine with T2DM. Majority of the prospective studies conducted were targeted metabolomics-based, with Caucasians as their study cohort. The whole disease risk in populations, including Asians, could therefore not be identified. This review proposes the utility of prospective studies in conjunction with metabolomics platform to unravel the altered metabolic pathways that contribute to the risk of T2DM.

Metabolomics of Type 1 and Type 2 Diabetes

Type 1 and type 2 diabetes mellitus (DM) are chronic diseases that affect nearly 425 million people worldwide, leading to poor health outcomes and high health care costs. High-throughput metabolomics screening can provide vital insight into the pathophysiological pathways of DM and help in managing its effects. The primary aim of this study was to contribute to the understanding and management of DM by providing reliable evidence of the relationships between metabolites and type 1 diabetes (T1D) and metabolites and type 2 diabetes (T2D). Information for the study was obtained from the PubMed, MEDLINE, and EMBASE databases, and leads to additional articles that were obtained from the reference lists of the studies examined. The results from the selected studies were used to assess the relationships between diabetes (T1D and/or T2D) and metabolite markers—such as glutamine, glycine, and aromatic amino acids—in patients. Seventy studies were selected from the three databases and from the reference lists in the records retrieved. All studies explored associations between various metabolites and T1D or T2D. This review identified several plasma metabolites associated with T2D prediabetes and/or T1D and/or T2D in humans. The evidence shows that metabolites such as glucose, fructose, amino acids, and lipids are typically altered in individuals with T1D and T2D. These metabolites exhibit significant predictive associations with T2D prediabetes, T1D, and/or T2D. The current review suggests that changes in plasma metabolites can be identified by metabolomic techniques and used to identify and analyze T1D and T2D biomarkers. The results of the metabolomic studies can be used to help create effective interventions for managing these diseases.

Perfluoroalkyl substances, metabolomic profiling, and alterations in glucose homeostasis among overweight and obese Hispanic children: A proof-of-concept analysis

OBJECTIVE

To examine the prospective associations between exposure to perfluoroalkyl substances (PFASs) and longitudinal measurements of glucose metabolism in high-risk overweight and obese Hispanic children.

METHODS

Forty overweight and obese Hispanic children (8-14 years) from urban Los Angeles underwent clinical measures and 2-hour oral glucose tolerance tests (OGTT) at baseline and a follow-up visit (range: 1-3 years after enrollment). Baseline plasma perfluorooctanoic acid (PFOA), perfluorooctane sulfonate (PFOS), perfluorohexane sulfonic acid (PFHxS), and the plasma metabolome were measured by liquid-chromatography with high-resolution mass spectrometry. Multiple linear regression models were used to assess the association between baseline PFASs and changes in glucose homeostasis over follow-up. A metabolome-wide association study coupled with pathway enrichment analysis was performed to evaluate metabolic dysregulation associated with plasma PFASs concentrations. We performed a structural integrated analysis aiming to characterize the joint impact of all factors and to identify latent clusters of children with alterations in glucose homeostasis, based on their exposure and metabolomics profile.

RESULTS

Each ln (ng/ml) increase in PFOA and PFHxS concentrations was associated with a 30.6 mg/dL (95% CI: 8.8-52.4) and 10.2 mg/dL (95% CI: 2.7-17.7) increase in 2-hour glucose levels, respectively. A ln (ng/ml) increase in PFHxS concentrations was also associated with 17.8 mg/dL increase in the glucose area under the curve (95% CI: 1.5-34.1). Pathway enrichment analysis showed significant alterations of lipids (e.g., glycosphingolipids, linoleic acid, and de novo lipogenesis), and amino acids (e.g., aspartate and asparagine, tyrosine, arginine and proline) in association to PFASs exposure. The integrated analysis identified a cluster of children with increased 2-h glucose levels over follow up, characterized by increased PFAS levels and altered metabolite patterns.

CONCLUSIONS

This proof-of-concept analysis shows that higher PFAS exposure was associated with dysregulation of several lipid and amino acid pathways and longitudinal alterations in glucose homeostasis in Hispanic youth. Larger studies are needed to confirm these findings and fully elucidate the underlying biological mechanisms.

Exposure to disinfection byproducts and risk of type 2 diabetes: a nested case-control study in the HUNT and Lifelines cohorts

INTRODUCTION

Environmental chemicals acting as metabolic disruptors have been implicated with diabetogenesis, but evidence is weak among short-lived chemicals, such as disinfection byproducts (trihalomethanes, THM composed of chloroform, TCM and brominated trihalomethanes, BrTHM).

OBJECTIVES

We assessed whether THM were associated with type 2 diabetes (T2D) and we explored alterations in metabolic profiles due to THM exposures or T2D status.

METHODS

A prospective 1:1 matched case-control study (n = 430) and a cross-sectional 1:1 matched case-control study (n = 362) nested within the HUNT cohort (Norway) and the Lifelines cohort (Netherlands), respectively, were set up. Urinary biomarkers of THM exposure and mass spectrometry-based serum metabolomics were measured. Associations between THM, clinical markers, metabolites and disease status were evaluated using logistic regressions with Least Absolute Shrinkage and Selection Operator procedure.

RESULTS

Low median THM exposures (ng/g, IQR) were measured in both cohorts (cases and controls of HUNT and Lifelines, respectively, 193 (76, 470), 208 (77, 502) and 292 (162, 595), 342 (180, 602). Neither BrTHM (OR = 0.87; 95% CI: 0.67, 1.11 | OR = 1.09; 95% CI: 0.73, 1.61), nor TCM (OR = 1.03; 95% CI: 0.88, 1.2 | OR = 1.03; 95% CI: 0.79, 1.35) were associated with incident or prevalent T2D, respectively. Metabolomics showed 48 metabolites associated with incident T2D after adjusting for sex, age and BMI, whereas a total of 244 metabolites were associated with prevalent T2D. A total of 34 metabolites were associated with the progression of T2D. In data driven logistic regression, novel biomarkers, such as cinnamoylglycine or 1-methylurate, being protective of T2D were identified. The incident T2D risk prediction model (HUNT) predicted well incident Lifelines cases (AUC = 0.845; 95% CI: 0.72, 0.97).

CONCLUSION

Such exposome-based approaches in cohort-nested studies are warranted to better understand the environmental origins of diabetogenesis.

Assessing the causal association of glycine with risk of cardio-metabolic diseases

Circulating levels of glycine have previously been associated with lower incidence of coronary heart disease (CHD) and type 2 diabetes (T2D) but it remains uncertain if glycine plays an aetiological role. We present a meta-analysis of genome-wide association studies for glycine in 80,003 participants and investigate the causality and potential mechanisms of the association between glycine and cardio-metabolic diseases using genetic approaches. We identify 27 genetic loci, of which 22 have not previously been reported for glycine. We show that glycine is genetically associated with lower CHD risk and find that this may be partly driven by blood pressure. Evidence for a genetic association of glycine with T2D is weaker, but we find a strong inverse genetic effect of hyperinsulinaemia on glycine. Our findings strengthen evidence for a protective effect of glycine on CHD and show that the glycine-T2D association may be driven by a glycine-lowering effect of insulin resistance.

The pattern of plasma BCAA concentration and liver Bckdha gene expression in GK rats during T2D progression

BACKGROUND

This study was conducted to measure the concentration of branched chain amino acid (BCAA) in different species and detect the expression pattern of the liver Bckdha gene in Goto-Kakizaki (GK) rats during type 2 diabetes (T2D) progression.

METHODS

We measured the concentration of BCAA in GK rats, induced T2D cynomolgus monkeys and T2D humans by liquid chromatography tandem mass spectrometry, and used real-time quantitative PCR to analyze the gene expression of Bckdha and Bckdk, which encode the rate-limiting enzymes in catabolism of, respectively, branched chain amino acids and branched chain α-keto acid dehydrogenase kinase.

RESULTS

In this study, we showed that GK rat BCAA concentrations were significantly reduced at 4 and 8 weeks (P < 0.05 and P < 0.01, respectively), while the expression of Bckdha in GK rat liver was increased at 4 and 8 weeks (1.62-fold and 1.93-fold, respectively). The BCAA concentrations were significantly reduced in diet-induced T2D cynomolgus monkeys (P < 0.01), but significantly increased in T2D humans (P < 0.001).

CONCLUSIONS

Our results showed that BCAA concentrations changed at different times and by different amounts in different species and during different periods of T2D progress, and the significant changes of BCAA concentration in the three species indicated that BCAA might participate in the progress of T2D. The results suggested that the increased expression of Bckdha in GK rat liver might partially explain the reduced plasma BCAA concentration at 4 and 8 weeks. Further studies are required to investigate the exact mechanism of BCAA changes in non-obese T2D.

Fasting serum α‑hydroxybutyrate and pyroglutamic acid as important metabolites for detecting isolated post-challenge diabetes based on organic acid profiles

The aim of this study was to develop a method to detect serum organic acid profiles in patients with isolated post-challenge diabetes (IPD) and to compare the metabolites between IPD patients, type 2 diabetes mellitus (T2DM) and healthy controls. We developed a gas chromatography-mass spectrometry method to detect serum organic acids and validated it using serum from 40 patients with IPD, 47 with newly diagnosed T2DM, and 48 healthy controls. We then analyzed the organic acid profiles by multivariate analysis to identify potential metabolites. This method allowed the fast and accurate measurement of 27 organic acids in serum. Serum organic acid profiles differed significantly among IPD patients, T2DM patients, and healthy controls. IPD samples had significantly higher concentrations of α‑hydroxybutyrate and β‑hydroxybutyrate (P < 0.05) and lower pyroglutamic acid concentration (P < 0.05) compared with the healthy controls, and the area under the curve for the combination of α‑hydroxybutyrate and pyroglutamic acid was 0.863 for the IPD group. These results provide useful information regarding the changes in organic acid metabolism associated with IPD. Measurement of these metabolites in fasting serum from IPD patients may provide useful diagnostic and/or prognostic biomarkers, as well as helpful markers for the therapeutic monitoring of IPD patients.

Metabolomics applied to the discovery of tuberculosis and diabetes mellitus biomarkers

Tuberculosis (TB) and diabetes mellitus Type 2 (DM2) are two diseases as ancient as they are harmful to human health. The outcome for both diseases in part depends on immune and metabolic individual responses. DM2 is increasing yearly, mainly due to environmental, genetic and lifestyle habits. There are multiple evidence that DM2 is one of the most important risk factor of becoming infected with TB or reactivating latent TB. Mass spectrometry-based metabolomics is an important tool for elucidating the metabolites and metabolic pathways that influence the immune responses to M. tuberculosis infection during diabetes. We provide an up-to-date review highlighting the importance and benefit of metabolomics for identifying biomarkers as candidate molecules for diagnosis, disease activity or prognosis.

Time course metabolome of Roux-en-Y gastric bypass confirms correlation between leptin, body weight and the microbiome

Roux-en-Y gastric bypass (RYGB) is an effective way to lose weight and reverse type 2 diabetes. We profiled the metabolome of 18 obese patients (nine euglycemic and nine diabetics) that underwent RYGB surgery and seven lean subjects. Plasma samples from the obese patients were collected before the surgery and one week and three months after the surgery. We analyzed the metabolome in association to five hormones (Adiponectin, Insulin, Ghrelin, Leptin, and Resistin), four peptide hormones (GIP, Glucagon, GLP1, and PYY), and two cytokines (IL-6 and TNF). PCA showed samples cluster by surgery time and many microbially driven metabolites (indoles in particular) correlated with the three months after the surgery. Network analysis of metabolites revealed a connection between carbohydrate (mannosamine and glucosamine) and glyoxylate and confirms glyoxylate association to diabetes. Only leptin and IL-6 had a significant association with the measured metabolites. Leptin decreased immediately after RYGB (before significant weight loss), whereas IL-6 showed no consistent response to RYGB. Moreover, leptin associated with tryptophan in support of the possible role of leptin in the regulation of serotonin synthesis pathways in the gut. These results suggest a potential link between gastric leptin and microbial-derived metabolites in the context of obesity and diabetes.

The efficacy and safety of Ginkgo biloba extract as an adjuvant in type 2 diabetes mellitus patients ineffectively managed with metformin: a double-blind, randomized, placebo-controlled trial

Background and aim

Type 2 diabetes mellitus (T2DM) is one of the major diseases confronting the health care systems. In diabetes mellitus (DM), combined use of oral hypoglycemic medications has been shown to be more effective than metformin (Met) alone in glycemic control. This study determined the effects of Ginkgo biloba (GKB) extract as an adjuvant to Met in patients with uncontrolled T2DM.

Subjects and methods

Sixty T2DM patients were recruited in a randomized, placebo-controlled, double-blinded, and multicenter trial. The patients, currently using Met, were randomly grouped into those treated with either GKB extract (120 mg/day) or placebo (starch, 120 mg/day) for 90 days. Blood glycated hemoglobin (HbA1c), fasting serum glucose, serum insulin, body mass index (BMI), waist circumference (WC), insulin resistance, and visceral adiposity index (VAI) were determined before (baseline) and after 90 days of GKB extract treatment.

Results

GKB extract significantly decreased blood HbA1c (7.7%±1.2% vs baseline 8.6%±1.6%, P<0.001), fasting serum glucose (154.7±36.1 mg/dL vs baseline 194.4±66.1 mg/dL, P<0.001) and insulin (13.4±7.8 μU/mL vs baseline 18.5±8.9 μU/mL, P=0.006) levels, BMI (31.6±5.1 kg/m² vs baseline 34.0±6.0 kg/m², P<0.001), waist WC (102.6±10.5 cm vs baseline 106.0±10.9 cm, P<0.001), and VAI (158.9±67.2 vs baseline 192.0±86.2, P=0.007). GKB extract did not negatively impact the liver, kidney, or hematopoietic functions.

Conclusion

GKB extract as an adjuvant was effective in improving Met treatment outcomes in T2DM patients. Thus, it is suggested that GKB extract is an effective dietary supplement for the control of DM in humans.

MALDI-MS Imaging Reveals Asymmetric Spatial Distribution of Lipid Metabolites from Bisphenol S-Induced Nephrotoxicity

With the continuous exposure of environmental pollutants in organisms, determination of abundance variation and spatial distribution of lipids might expand our understanding of toxicological mechanisms occurring in the kidney. Herein, an integrated method involving mass spectrometry (MS)-based lipidomics and matrix-assisted laser desorption/ionization-MS imaging (MALDI-MSI) was developed for the study of nephrotoxicity in mice exposed to 10 and 100 μg bisphenol S (BPS)/kg body weight/day. The BPS exposure remarkable perturbed abundances of 91 potential markers that mainly involved in five metabolic pathways. We elucidated the lipids spatial heterogeneity by using morphological analysis, probabilistic latent semantic analysis, and coregistered multimodal three-dimensional (3D)-MSI. In morphological analysis, both 10 and 100 μg BPS induced significant nephrotoxicity to mice, including glomerular necrosis in renal cortex, cloudy swelling in renal medulla, and interstitial collapsing in renal pelvis. Significant differential signaling lipids such as sphingomyelin (SM) (d22:0/20:4), ceramide (Cer) (d18:2/24:1), and sphingosine (d18:0) related to inflammation were found to be up-regulated and colocalized in the renal cortex, medulla, and pelvis, respectively. Also, seven significant differential lipids, which are considered to be involved in membrane homeostasis and cellular function, were found to be colocalized in the renal cortex. The observed significant variations of morphology, lipid accumulation, and metabolism in the renal cortex implicated that lipids in the renal cortex were more sensitive to BPS exposure than those in the renal medulla and pelvis. Moreover, we reconstructed a 3D-MSI model of kidney and identified two heterogeneous-related substructures in the renal cortex and pelvis upon 100 μg BPS exposure. It might be used in novel specificity evaluation and early diagnosis for environmental pollutant-induced kidney diseases.

Metabolomics as a Tool to Understand Pathophysiological Processes

Multiple diseases have a strong metabolic component, and metabolomics as a powerful phenotyping technology, in combination with orthogonal biological and clinical approaches, will undoubtedly play a determinant role in accelerating the understanding of mechanisms that underlie these complex diseases determined by a set of genetic, lifestyle, and environmental exposure factors. Here, we provide several examples of valuable findings from metabolomics-led studies in diabetes and obesity metabolism, neurodegenerative disorders, and cancer metabolism and offer a longer term vision toward personalized approach to medicine, from population-based studies to pharmacometabolomics.

Proteomics and metabolomics in ageing research: from biomarkers to systems biology

Age is the single greatest risk factor for a wide range of diseases, and as the mean age of human populations grows steadily older, the impact of this risk factor grows as well. Laboratory studies on the basic biology of ageing have shed light on numerous genetic pathways that have strong effects on lifespan. However, we still do not know the degree to which the pathways that affect ageing in the lab also influence variation in rates of ageing and age-related disease in human populations. Similarly, despite considerable effort, we have yet to identify reliable and reproducible 'biomarkers', which are predictors of one's biological as opposed to chronological age. One challenge lies in the enormous mechanistic distance between genotype and downstream ageing phenotypes. Here, we consider the power of studying 'endophenotypes' in the context of ageing. Endophenotypes are the various molecular domains that exist at intermediate levels of organization between the genotype and phenotype. We focus our attention specifically on proteins and metabolites. Proteomic and metabolomic profiling has the potential to help identify the underlying causal mechanisms that link genotype to phenotype. We present a brief review of proteomics and metabolomics in ageing research with a focus on the potential of a systems biology and network-centric perspective in geroscience. While network analyses to study ageing utilizing proteomics and metabolomics are in their infancy, they may be the powerful model needed to discover underlying biological processes that influence natural variation in ageing, age-related disease, and longevity.

Metabolic profiles in heart failure due to non-ischemic cardiomyopathy at rest and under exercise

AIMS

Identification of metabolic signatures in heart failure (HF) patients and evaluation of their diagnostic potential to discriminate HF patients from healthy controls during baseline and exercise conditions.

METHODS

Plasma samples were collected from 22 male HF patients with non-ischemic idiopathic cardiomyopathy and left ventricular systolic dysfunction and 19 healthy controls before (t0), at peak (t1) and 1 h after (t2) symptom-limited cardiopulmonary exercise testing. Two hundred fifty-two metabolites were quantified by gas chromatography-mass spectrometry (GC-MS) and liquid chromatography (LC)-MS/MS-based metabolite profiling.

RESULTS

Plasma metabolite profiles clearly differed between HF patients and controls at t0 (P < 0.05). The metabolic signature of HF was characterized by decreased levels of complex lipids and fatty acids, notably phosphatidylcholines, cholesterol, and sphingolipids. Moreover, reduced glutamine and increased glutamate plasma levels, significantly increased purine degradation products, as well as signs of impaired glucose metabolism were observed. The metabolic differences increased strongly according to New York Heart Association functional class and the addition of three metabolites further improved prediction of exercise capacity (Q² = 0.24 to 0.35). Despite a high number of metabolites changing significantly with exercise (30.2% at t1/t0), the number of significant alterations between HF and controls was almost unchanged at t₁ and t₂ (30.7 and 29.0% vs. 31.3% at t₀) with a similar predictive group separation (Q² = 0.50 for t0, 0.52 for t1, and 0.56 for t2, respectively).

CONCLUSIONS

Our study identified a metabolic signature of non-ischemic HF with prominent changes in complex lipids including phosphatidylcholines, cholesterol, and sphingolipids. The metabolic changes were already evident at rest and largely preserved under exercise.

Multiplex Biomarker Approaches in Type 2 Diabetes Mellitus Research

Type 2 diabetes mellitus is a multifactorial condition resulting in high fasting blood glucose levels. Although its diagnosis is straightforward, there is not one set of biomarkers or drug targets that can be used for classification or personalized treatment of individuals who suffer from this condition. Instead, the application of multiplex methods incorporating a systems biology approach is essential in order to increase our understanding of this disease. This chapter reviews the state of the art in biomarker studies of human type 2 diabetes from a proteomic and metabolomic perspective. Our main focus was on biomarkers for disease prediction as these could lead to early intervention strategies for the best possible patient outcomes.

Validation of a metabolite panel for early diagnosis of type 2 diabetes

BACKGROUND

Accurate, early diagnosis of type 2 diabetes (T2D) would enable more effective clinical management and a reduction in T2D complications. Therefore, we sought to identify plasma metabolite and protein biomarkers that, in combination with glucose, can better predict future T2D compared with glucose alone.

METHODS

In this case-control study, we used plasma samples from the Bavarian Red Cross Blood Transfusion Center study (61 T2D cases and 78 non-diabetic controls) for discovering T2D-associated metabolites, and plasma samples from the Personalized Medicine Research Project in Wisconsin (56 T2D cases and 445 non-diabetic controls) for validation. All samples were obtained before or at T2D diagnosis. We tested whether the T2D-associated metabolites could distinguish incident T2D cases from controls, as measured by the area under the receiver operating characteristic curve (AUC). Additionally, we tested six metabolic/pro-inflammatory proteins for their potential to augment the ability of the metabolites to distinguish cases from controls.

RESULTS

A panel of 10 metabolites discriminated better between T2D cases and controls than glucose alone (AUCs: 0.90 vs 0.87; p=2.08×10(-5)) in Bavarian samples, and associations between these metabolites and T2D were confirmed in Wisconsin samples. With use of either a Bayesian network classifier or ridge logistic regression, the metabolites, with or without the proteins, discriminated incident T2D cases from controls marginally better than glucose in the Wisconsin samples, although the difference in AUCs was not statistically significant. However, when the metabolites and proteins were added to two previously reported T2D prediction models, the AUCs were higher than those of each prediction model alone (AUCs: 0.92 vs 0.87; p=3.96×10(-2) and AUCs: 0.91 vs 0.71; p=1.03×10(-5), for each model, respectively).

CONCLUSIONS

Compared with glucose alone or with previously described T2D prediction models, a panel of plasma biomarkers showed promise for improved discrimination of incident T2D, but more investigation is needed to develop an early diagnostic marker.