Circulating metabolite predictors of glycemia in middle-aged men and women

Circulating Metabolite Biomarkers of Glycemic Control in Youth-Onset Type 2 Diabetes

OBJECTIVE

We aimed to identify metabolites associated with loss of glycemic control in youth-onset type 2 diabetes.

RESEARCH DESIGN AND METHODS

We measured 480 metabolites in fasting plasma samples from the TODAY (Treatment Options for Type 2 Diabetes in Adolescents and Youth) study. Participants (N = 393; age 10-17 years) were randomly assigned to metformin, metformin plus rosiglitazone, or metformin plus lifestyle intervention. Additional metabolomic measurements after 36 months were obtained in 304 participants. Cox models were used to assess baseline metabolites, interaction of metabolites and treatment group, and change in metabolites (0-36 months), with loss of glycemic control adjusted for age, sex, race, treatment group, and BMI. Metabolite prediction models of glycemic failure were generated using elastic net regression and compared with clinical risk factors.

RESULTS

Loss of glycemic control (HbA1c ≥8% or insulin therapy) occurred in 179 of 393 participants (mean 12.4 months). Baseline levels of 33 metabolites were associated with loss of glycemic control (q < 0.05). Associations of hexose and xanthurenic acid with treatment failure differed by treatment randomization; youths with higher baseline levels of these two compounds had a lower risk of treatment failure with metformin alone. For three metabolites, changes from 0 to 36 months were associated with loss of glycemic control (q < 0.05). Changes in d-gluconic acid and 1,5-AG/1-deoxyglucose, but not baseline levels of measured metabolites, predicted treatment failure better than changes in HbA1c or measures of β-cell function.

CONCLUSIONS

Metabolomics provides insight into circulating small molecules associated with loss of glycemic control and may highlight metabolic pathways contributing to treatment failure in youth-onset diabetes.

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.

Metabolomics Characterization of Disease Markers in Diabetes and Its Associated Pathologies

With the change in lifestyle of people, there has been a considerable increase in diabetes, which brings with it certain follow-up pathological conditions, which lead to a substantial medical burden. Identifying biomarkers that aid in screening, diagnosis, and prognosis of diabetes and its associated pathologies would help better patient management and facilitate a personalized treatment approach for prevention and treatment. With the advancement in techniques and technologies, metabolomics has emerged as an omics approach capable of large-scale high throughput data analysis and identifying and quantifying metabolites that provide an insight into the underlying mechanism of the disease and its progression. Diabetes and metabolomics keywords were searched in correspondence with the assigned keywords, including kidney, cardiovascular diseases and critical illness from PubMed and Scopus, from its inception to Dec 2023. The relevant studies from this search were extracted and included in the study. This review is focused on the biomarkers identified in diabetes, diabetic kidney disease, diabetes-related development of CVD, and its role in critical illness.

Metabolic biomarkers using nuclear magnetic resonance metabolomics assay for the prediction of aging-related disease risk and mortality: a prospective, longitudinal, observational, cohort study based on the UK Biobank

The identification of metabolic biomarkers for aging-related diseases and mortality is of significant interest in the field of longevity. In this study, we investigated the associations between nuclear magnetic resonance (NMR) metabolomics biomarkers and aging-related diseases as well as mortality using the UK Biobank dataset. We analyzed NMR samples from approximately 110,000 participants and used multi-head machine learning classification models to predict the incidence of aging-related diseases. Cox regression models were then applied to assess the relevance of NMR biomarkers to the risk of death due to aging-related diseases. Additionally, we conducted survival analyses to evaluate the potential improvements of NMR in predicting survival and identify the biomarkers most strongly associated with negative health outcomes by dividing participants into health, disease, and death groups for all age groups. Our analysis revealed specific metabolomics profiles that were associated with the incidence of age-related diseases, and the most significant biomarker was intermediate density lipoprotein cholesteryl (IDL-CE). In addition, NMR biomarkers could provide additional contributions to relevant mortality risk prediction when combined with conventional risk factors, by improving the C-index from 0.813 to 0.833, with 17 NMR biomarkers significantly contributing to disease-related death, such as monounsaturated fatty acids (MUFA), linoleic acid (LA), glycoprotein acetyls (GlycA), and omega-3. Moreover, the value of free cholesterol in very large HDL particles (XL-HDL-FC) in the healthy control group demonstrated significantly higher values than the disease and death group across all age groups. This study highlights the potential of NMR metabolomics profiling as a valuable tool for identifying metabolic biomarkers associated with aging-related diseases and mortality risk, which could have practical implications for aging-related disease risk and mortality prediction.

Exogenous Melatonin Alleviates Atrazine-Induced Glucose Metabolism Disorders in Mice Liver via Suppressing Endoplasmic Reticulum Stress

Atrazine (ATZ) is a widely used herbicide that has toxic effects on animals. Melatonin (MLT) is a natural hormone with strong antioxidant properties. However, the effect of MLT on the glucose metabolism disorder caused by ATZ is still unclear. Mice were divided into four groups randomly and given 21 days of gavage: blank control group (Con), 5 mg/kg MLT group (MLT), 170 mg/kg ATZ group (ATZ), and 170 mg/kg ATZ and 5 mg/kg MLT group (ATZ + MLT). The results show that ATZ alters mRNA levels of metabolic enzymes related to glycogen synthesis and glycolysis and increased metabolites (glycogen, lactate, and pyruvate). ATZ causes abnormalities in glucose metabolism in mouse liver, interfering with glycemia regulation ability. MLT can regulate the endoplasmic reticulum to respond to disordered glucose metabolism in mice liver. This study suggested that MLT has the power to alleviate the ATZ-induced glycogen overdeposition and glycolytic deficit.

Microbiome and metabolome dysbiosis analysis in impaired glucose tolerance for the prediction of progression to diabetes mellitus

Gut microbiota and circulating metabolite dysbiosis predate important pathological changes in glucose metabolic disorders; however, comprehensive studies on impaired glucose tolerance (IGT), a diabetes mellitus (DM) precursor, are lacking. Here, we perform metagenomic sequencing and metabolomics on 47 pairs of individuals with IGT and newly diagnosed DM and 46 controls with normal glucose tolerance (NGT); patients with IGT are followed up after 4 years for progression to DM. Analysis of baseline data reveals significant differences in gut microbiota and serum metabolites among the IGT, DM, and NGT groups. In addition, 13 types of gut microbiota and 17 types of circulating metabolites showed significant differences at baseline before IGT progressed to DM, including higher levels of Eggerthella unclassified, Coprobacillus unclassified, Clostridium ramosum, L-valine, L-norleucine, and L-isoleucine, and lower levels of Eubacterium eligens, Bacteroides faecis, Lachnospiraceae bacterium 3_1_46FAA, Alistipes senegalensis, Megaspaera elsdenii, Clostridium perfringens, α-linolenic acid, 10E,12Z-octadecadienoic acid, and dodecanoic acid. A random forest model based on differential intestinal microbiota and circulating metabolites can predict the progression from IGT to DM (AUC = 0.87). These results suggest that microbiome and metabolome dysbiosis occur in individuals with IGT and have important predictive values and potential for intervention in preventing IGT from progressing to DM.

Postprandial Metabolite Profiles and Risk of Prediabetes in Young People: A Longitudinal Multicohort Study

OBJECTIVE

Prediabetes in young people is an emerging epidemic that disproportionately impacts Hispanic populations. We aimed to develop a metabolite-based prediction model for prediabetes in young people with overweight/obesity at risk for type 2 diabetes.

RESEARCH DESIGN AND METHODS

In independent, prospective cohorts of Hispanic youth (discovery; n = 143 without baseline prediabetes) and predominately Hispanic young adults (validation; n = 56 without baseline prediabetes), we assessed prediabetes via 2-h oral glucose tolerance tests. Baseline metabolite levels were measured in plasma from a 2-h postglucose challenge. In the discovery cohort, least absolute shrinkage and selection operator regression with a stability selection procedure was used to identify robust predictive metabolites for prediabetes. Predictive performance was evaluated in the discovery and validation cohorts using logistic regression.

RESULTS

Two metabolites (allylphenol sulfate and caprylic acid) were found to predict prediabetes beyond known risk factors, including sex, BMI, age, ethnicity, fasting/2-h glucose, total cholesterol, and triglycerides. In the discovery cohort, the area under the receiver operator characteristic curve (AUC) of the model with metabolites and known risk factors was 0.80 (95% CI 0.72-0.87), which was higher than the risk factor-only model (AUC 0.63 [0.53-0.73]; P = 0.001). When the predictive models developed in the discovery cohort were applied to the replication cohort, the model with metabolites and risk factors predicted prediabetes more accurately (AUC 0.70 [95% CI 40.55-0.86]) than the same model without metabolites (AUC 0.62 [0.46-0.79]).

CONCLUSIONS

Metabolite profiles may help improve prediabetes prediction compared with traditional risk factors. Findings suggest that medium-chain fatty acids and phytochemicals are early indicators of prediabetes in high-risk youth.

Unlocking the Potential: Amino Acids' Role in Predicting and Exploring Therapeutic Avenues for Type 2 Diabetes Mellitus

Diabetes mellitus, particularly type 2 diabetes mellitus (T2DM), imposes a significant global burden with adverse clinical outcomes and escalating healthcare expenditures. Early identification of biomarkers can facilitate better screening, earlier diagnosis, and the prevention of diabetes. However, current clinical predictors often fail to detect abnormalities during the prediabetic state. Emerging studies have identified specific amino acids as potential biomarkers for predicting the onset and progression of diabetes. Understanding the underlying pathophysiological mechanisms can offer valuable insights into disease prevention and therapeutic interventions. This review provides a comprehensive summary of evidence supporting the use of amino acids and metabolites as clinical biomarkers for insulin resistance and diabetes. We discuss promising combinations of amino acids, including branched-chain amino acids, aromatic amino acids, glycine, asparagine and aspartate, in the prediction of T2DM. Furthermore, we delve into the mechanisms involving various signaling pathways and the metabolism underlying the role of amino acids in disease development. Finally, we highlight the potential of targeting predictive amino acids for preventive and therapeutic interventions, aiming to inspire further clinical investigations and mitigate the progression of T2DM, particularly in the prediabetic stage.

Exploring Metabolomic Patterns in Type 2 Diabetes Mellitus and Response to Glucose-Lowering Medications-Review

The spectrum of information related to precision medicine in diabetes generally includes clinical data, genetics, and omics-based biomarkers that can guide personalized decisions on diabetes care. Given the remarkable progress in patient risk characterization, there is particular interest in using molecular biomarkers to guide diabetes management. Metabolomics is an emerging molecular approach that helps better understand the etiology and promises the identification of novel biomarkers for complex diseases. Both targeted or untargeted metabolites extracted from cells, biofluids, or tissues can be investigated by established high-throughput platforms, like nuclear magnetic resonance (NMR) and mass spectrometry (MS) techniques. Metabolomics is proposed as a valuable tool in precision diabetes medicine to discover biomarkers for diagnosis, prognosis, and management of the progress of diabetes through personalized phenotyping and individualized drug-response monitoring. This review offers an overview of metabolomics knowledge as potential biomarkers in type 2 diabetes mellitus (T2D) diagnosis and the response to glucose-lowering medications.

Metabolomic profiling of glucose homeostasis in African Americans: the Insulin Resistance Atherosclerosis Family Study (IRAS-FS)

INTRODUCTION

African Americans are at increased risk for type 2 diabetes.

OBJECTIVES

This work aimed to examine metabolomic signature of glucose homeostasis in African Americans.

METHODS

We used an untargeted liquid chromatography-mass spectrometry metabolomic approach to comprehensively profile 727 plasma metabolites among 571 African Americans from the Insulin Resistance Atherosclerosis Family Study (IRAS-FS) and investigate the associations between these metabolites and both the dynamic (S_I, insulin sensitivity; AIR, acute insulin response; DI, disposition index; and S_G, glucose effectiveness) and basal (HOMA-IR and HOMA-B) measures of glucose homeostasis using univariate and regularized regression models. We also compared the results with our previous findings in the IRAS-FS Mexican Americans.

RESULTS

We confirmed increased plasma metabolite levels of branched-chain amino acids and their metabolic derivatives, 2-aminoadipate, 2-hydroxybutyrate, glutamate, arginine and its metabolic derivatives, carbohydrate metabolites, and medium- and long-chain fatty acids were associated with insulin resistance, while increased plasma metabolite levels in the glycine, serine and threonine metabolic pathway were associated with insulin sensitivity. We also observed a differential ancestral effect of glutamate on glucose homeostasis with significantly stronger effects observed in African Americans than those previously observed in Mexican Americans.

CONCLUSION

We extended the observations that metabolites are useful biomarkers in the identification of prediabetes in individuals at risk of type 2 diabetes in African Americans. We revealed, for the first time, differential ancestral effect of certain metabolites (i.e., glutamate) on glucose homeostasis traits. Our study highlights the need for additional comprehensive metabolomic studies in well-characterized multiethnic cohorts.

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.

New Advances in Metabolic Syndrome, from Prevention to Treatment: The Role of Diet and Food

The definition of metabolic syndrome (MetS) has undergone several changes over the years due to the difficulty in establishing universal criteria for it. Underlying the disorders related to MetS is almost invariably a pro-inflammatory state related to altered glucose metabolism, which could lead to elevated cardiovascular risk. Indeed, the complications closely related to MetS are cardiovascular diseases (CVDs) and type 2 diabetes (T2D). It has been observed that the predisposition to metabolic syndrome is modulated by complex interactions between human microbiota, genetic factors, and diet. This review provides a summary of the last decade of literature related to three principal aspects of MetS: (i) the syndrome's definition and classification, pathophysiology, and treatment approaches; (ii) prediction and diagnosis underlying the biomarkers identified by means of advanced methodologies (NMR, LC/GC-MS, and LC, LC-MS); and (iii) the role of foods and food components in prevention and/or treatment of MetS, demonstrating a possible role of specific foods intake in the development of MetS.

Systematic assessment of streptozotocin-induced diabetic metabolic alterations in rats using metabolomics

PURPOSE

Type 1 diabetes is characterized by elevated blood glucose levels, which negatively impacts multiple organs and tissues throughout the body, and its prevalence is on the rise. Prior reports primarily investigated the serum and urine specimen from diabetic patients. However, only a few studies examined the overall metabolic profile of diabetic animals or patients. The current systemic investigation will benefit the knowledge of STZ-based type 1 diabetes pathogenesis.

METHODS

Male SD rats were arbitrarily separated into control and streptozotocin (STZ)-treated diabetic rats (n = 7). The experimental rats received 50mg/kg STZ intraperitoneal injection daily for 2 consecutive days. Following 6 weeks, metabolites were assessed via gas chromatography-mass spectrometry (GC-MS), and multivariate analysis was employed to screen for differentially expressed (DE) metabolites between the induced diabetic and normal rats.

RESULTS

We identified 18, 30, 6, 24, 34, 27, 27 and 12 DE metabolites in the serum, heart, liver, kidney, cortex, renal lipid, hippocampus, and brown fat tissues of STZ-treated diabetic rats, compared to control rats. Based on our analysis, the largest differences were observed in the amino acids (AAs), B-group vitamin, and purine profiles. Using the metabolic pathway analysis, we screened 13 metabolic pathways related to the STZ-exposed diabetes pathogenesis. These pathways were primarily AA metabolism, followed by organic acids, sugars, and lipid metabolism.

CONCLUSION

Based on our GC-MS analysis, we identified potential metabolic alterations within the STZ-exposed diabetic rats, which may aid in the understanding of diabetes pathogenesis.

The association between dietary amino acids and the risk of nonalcoholic fatty liver disease among Tehranian adults: a case-control study

BACKGROUND

Amino acids (AAs) are important bioactive components in the diet that can be involved in various underlying biological processes that contribute to the development of nonalcoholic fatty liver disease (NAFLD). The present study investigates the association between dietary intake of amino acids and NAFLD in Iranian adults.

METHODS

This study was conducted among 225 newly diagnosed cases of NAFLD and 450 controls. A valid and reliable 168-item semiquantitative food frequency questionnaire (FFQ) was used to collect participants' dietary intakes. Multivariable logistic regression models were used to assess the association between tertiles of branched-chain amino acids (BCAAs), aromatic amino acids (AAAs), and sulfuric amino acids (SAAs) intake with the odds of NAFLD among the study participants.

RESULTS

The mean ± standard deviation of age and BMI of participants (53% male) were 38.1 ± 8.8 years and 26.8 ± 4.3 kg/m2, respectively. In the final models, the OR and 95% CI of NAFLD among participants in the highest tertiles of BCAAs, AAAs, and SAAs intake compared with those in the lowest tertiles were (OR = 2.82; 95% CI: 1.50-5.30), (OR = 2.82; 95% CI: 1.50-5.30), (OR = 2.86; 95% CI: 1.49-5.48), respectively.

CONCLUSION

Our study indicated a direct association between the intake of AAs groups, including BCAAs, AAAs, SAAs, and the odds of NAFLD. We suggest that other researchers examine the association between AAs groups and NAFLD in large cohort studies.

Metabolomic profiles predict individual multidisease outcomes

Risk stratification is critical for the early identification of high-risk individuals and disease prevention. Here we explored the potential of nuclear magnetic resonance (NMR) spectroscopy-derived metabolomic profiles to inform on multidisease risk beyond conventional clinical predictors for the onset of 24 common conditions, including metabolic, vascular, respiratory, musculoskeletal and neurological diseases and cancers. Specifically, we trained a neural network to learn disease-specific metabolomic states from 168 circulating metabolic markers measured in 117,981 participants with ~1.4 million person-years of follow-up from the UK Biobank and validated the model in four independent cohorts. We found metabolomic states to be associated with incident event rates in all the investigated conditions, except breast cancer. For 10-year outcome prediction for 15 endpoints, with and without established metabolic contribution, a combination of age and sex and the metabolomic state equaled or outperformed established predictors. Moreover, metabolomic state added predictive information over comprehensive clinical variables for eight common diseases, including type 2 diabetes, dementia and heart failure. Decision curve analyses showed that predictive improvements translated into clinical utility for a wide range of potential decision thresholds. Taken together, our study demonstrates both the potential and limitations of NMR-derived metabolomic profiles as a multidisease assay to inform on the risk of many common diseases simultaneously.

Nrf2 deficiency deteriorates diabetic kidney disease in Akita model mice

Oxidative stress is an essential component in the progression of diabetic kidney disease (DKD), and the transcription factor NF-E2-related factor-2 (Nrf2) plays critical roles in protecting the body against oxidative stress. To clarify the roles of Nrf2 in protecting against DKD, in this study we prepared compound mutant mice with diabetes and loss of antioxidative defense. Specifically, we prepared compound Ins2^Akita/+ (Akita) and Nrf2 knockout (Akita::Nrf2^-/-) or Akita and Nrf2 induction (Akita::Keap1^FA/FA) mutant mice. Eighteen-week-old Akita::Nrf2^-/- mice showed more severe diabetic symptoms than Akita mice. In the Akita::Nrf2^-/- mouse kidneys, the glomeruli showed distended capillary loops, suggesting enhanced mesangiolysis. Distal tubules showed dilation and an increase in 8-hydroxydeoxyguanosine-positive staining. In the Akita::Nrf2^-/- mouse kidneys, the expression of glutathione (GSH) synthesis-related genes was decreased, and the actual GSH level was decreased in matrix-assisted laser desorption/ionization mass spectrometry imaging analysis. Akita::Nrf2^-/- mice exhibited severe inflammation and enhancement of infiltrated macrophages in the kidney. To further examine the progression of DKD, we compared forty-week-old Akita mouse kidney compounds with Nrf2-knockout or Nrf2 mildly induced (Akita::Keap1^FA/FA) mice. Nrf2-knockout Akita (Akita::Nrf2^-/-) mice displayed severe medullary cast formation, but the formation was ameliorated in Akita::Keap1^FA/FA mice. Moreover, in Akita::Keap1^FA/FA mice, tubule injury and inflammation-related gene expression were significantly suppressed, which was evident in Akita::Nrf2^-/- mouse kidneys. These results demonstrate that Nrf2 contributes to the protection of the kidneys against DKD by suppressing oxidative stress and inflammation.

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.

Chronically elevated branched chain amino acid levels are pro-arrhythmic

AIMS

Cardiac arrhythmias comprise a major health and economic burden and are associated with significant morbidity and mortality, including cardiac failure, stroke, and sudden cardiac death (SCD). Development of efficient preventive and therapeutic strategies is hampered by incomplete knowledge of disease mechanisms and pathways. Our aim is to identify novel mechanisms underlying cardiac arrhythmia and SCD using an unbiased approach.

METHODS AND RESULTS

We employed a phenotype-driven N-ethyl-N-nitrosourea mutagenesis screen and identified a mouse line with a high incidence of sudden death at young age (6-9 weeks) in the absence of prior symptoms. Affected mice were found to be homozygous for the nonsense mutation Bcat2p.Q300*/p.Q300* in the Bcat2 gene encoding branched chain amino acid transaminase 2. At the age of 4-5 weeks, Bcat2p.Q300*/p.Q300* mice displayed drastic increase of plasma levels of branch chain amino acids (BCAAs-leucine, isoleucine, valine) due to the incomplete catabolism of BCAAs, in addition to inducible arrhythmias ex vivo as well as cardiac conduction and repolarization disturbances. In line with these findings, plasma BCAA levels were positively correlated to electrocardiogram indices of conduction and repolarization in the German community-based KORA F4 Study. Isolated cardiomyocytes from Bcat2p.Q300*/p.Q300* mice revealed action potential (AP) prolongation, pro-arrhythmic events (early and late afterdepolarizations, triggered APs), and dysregulated calcium homeostasis. Incubation of human pluripotent stem cell-derived cardiomyocytes with elevated concentration of BCAAs induced similar calcium dysregulation and pro-arrhythmic events which were prevented by rapamycin, demonstrating the crucial involvement of mTOR pathway activation.

CONCLUSIONS

Our findings identify for the first time a causative link between elevated BCAAs and arrhythmia, which has implications for arrhythmogenesis in conditions associated with BCAA metabolism dysregulation such as diabetes, metabolic syndrome, and heart failure.

Metabolic changes induced by dapagliflozin, an SGLT2 inhibitor, in Japanese patients with type 2 diabetes treated by oral anti-diabetic agents: A randomized, clinical trial

AIM

We aimed to determine whether SGLT2 inhibitor dapagliflozin treatment affects body composition and amino acid (AA) metabolism.

METHODS

Fifty-two overweight patients treated by oral antidiabetic agents were randomly assigned to dapagliflozin (Dapa) or a standard treatment (Con) and followed for 24 weeks. The primary outcome was the change in body mass (BM) between baseline and week 24. Body composition, intrahepatic triglyceride (IHTG) content, and plasma AA concentrations were examined as secondary outcomes.

RESULTS

The change in BM was significantly larger in the Dapa than in the Con group, with a difference in the mean change of -1.72 kg (95 %CI: -2.85, -0.59; P = 0.004) between the groups. Total fat mass was reduced by dapagliflozin treatment, but fat-free mass was maintained. IHTG content was significantly reduced in the Dapa than in the Con (P = 0.033). Changes in AAs showed small differences between the groups, but only serine concentrations were significantly reduced in the Dapa. Intra-group analysis showed that positive associations were observed between changes in branched chain AA concentrations and body composition only in the Dapa.

CONCLUSIONS

Dapagliflozin treatment causes a reduction in BM mainly by reducing fat mass. AA metabolism shows subtle changes with dapagliflozin treatment.

Positive association of branched-chain amino acids with triglyceride and glycated haemoglobin in Indian patients with type 2 diabetes mellitus

BACKGROUND AND AIMS

Over the past few years, branched-chain amino acids (BCAAs) are increasingly being linked to insulin resistance and type 2 diabetes mellitus (T2DM), but their relevance for metabolic dyslipidaemia in T2DM is unclear. This study aims to determine the plasma and urinary BCAAs and their association with insulin resistance, lipid profile and glycated haemoglobin in patients with T2DM among Indian adults.

METHODS

In this analytical cross-sectional study, a total of eighty subjects were recruited, 40 T2DM cases and 40 healthy controls. Blood samples collected were subjected to fasting blood sugar (FBS), lipid profile, HbA1c, insulin and BCAAs analysis and urine samples were assessed for BCAAs. All associations were assessed using Spearman Rank Correlation.

RESULTS

The plasma levels of BCAAs were significantly higher (p < 0.05) in subjects with T2DM than in control subjects. Spearman Rank Correlation analyses revealed a non-significant (p = 0.21) but positive association between BCAAs and homeostasis model assessment of insulin resistance (HOMA-IR) in patients with T2DM (Rho: 0.27). Among lipid profile parameters, only triglycerides had a significant positive correlation to plasma BCAAs in cases (Rho: 0.5971) but not in control subjects. Findings also revealed a significant positive (p < 0.05) association between plasma BCAAs and HbA1c in patients with T2DM (Rho: 0.5325). Urinary BCAAs levels had a non-significant increase in T2DM subjects and did not show any significant correlation with other parameters assessed.

CONCLUSION

Elevated levels of plasma BCAAs are positively associated with triglyceride and HbA1c. They could serve as an effective marker for the assessment of metabolic dyslipidaemia in subjects with T2DM. Further, large scale studies are needed for confirmation of the same.

Binary and Ternary Complexes of Cucurbit[8]uril with Tryptophan, Phenylalanine, and Tyrosine: A Computational Study

Selective binding of amino acids, peptides, and proteins by synthetic molecules and elucidation of the geometry and dynamics of the resulting complexes and their strengths are active areas of contemporary research. In recent work, we analyzed via molecular dynamics (MD) simulations the complexes formed between cucurbit[7]uril (CB7) and three aromatic amino acids: tryptophan (W), phenylalanine (F), and tyrosine (Y). Herein, we continue this line of research by performing MD simulations lasting 100 ns to investigate the formation, stabilities, binding modes, dynamics, and specific host-guest noncovalent interactions contributing to the formation of the binary (1:1) and ternary (2:1) complexes in aqueous solution between W, F, and Y amino acids and cucurbit[8]uril (CB8). All complexes were found to be stable, with the binding in each complex dominated by one mode (except for the F-CB8 complex, which had two) characterized by encapsulation of the aromatic side chains of the amino acids within the cavity of CB8 and the exclusion of their ammonium and carboxylate groups. Using the molecular mechanics/Poisson-Boltzmann surface area method to estimate the individual contributions to the overall free energies of binding, results revealed that the key role is played by the amino acid side chains in stabilizing the complexes through their favorable van der Waals interactions with the CB8 cavity and the importance of favorable electrostatic interactions between the carbonyl portal of CB8 and the ammonium group of the amino acid. Visual analysis of structures of the ternary complexes indicated the presence of π-π stacking between the aromatic side chains of the included amino acids. The insights provided by this work may be of value for further efforts aiming to employ the recognition properties of CB8 toward amino acids in applications requiring more elaborate recognition of short peptides and proteins.

Identification of the Metabolomics Signature of Human Follicular Fluid from PCOS Women with Insulin Resistance

Context. Polycystic ovary syndrome (PCOS) is a gynecological endocrine disease, and approximately 60% of patients with PCOS have different degrees of insulin resistance (IR). The regulatory role of metabolic networks in human follicular fluid (FF) related to IR in PCOS remains unclear. Aims. To explore the effect of IR on the metabolism of PCOS by analyzing the changes in FF metabolites in PCOS patients who are undergoing assisted reproductive technology based on the metabonomic platform of ultraperformance gas chromatography coupled to mass spectrometry (GC/MS). Method. Eight PCOS patients with IR (PCOS-IR) and 8 PCOS patients without IR (PCOS-NIR) were enrolled. All patients received controlled ovarian stimulation by using the gonadotropin-releasing hormone (GnRH) antagonist protocol, and the FF of a single dominant follicle was collected on the day of oocyte retrieval. The metabolite profiles of the FF were determined by GC/MS. Key Results. A total of 20 differentially expressed metabolites in FF were identified. Compared with levels in the PCOS-NIR group, stearic acid, palmitic acid, pentadecanoic acid, stigmasterol, citric acid, isocitric acid, thymine, and pyruvic acid in FF were significantly increased in the PCOS-IR group. Lithocholic acid and sinapinic acid in FF decreased significantly. The affected metabolic pathways with potential regulatory roles were identified by KEGG annotation. Conclusion. Compared with the PCOS-NIR group, the PCOS-IR group showed more significant metabolic abnormalities. Implications. These results will help us to understand the pathogenesis of PCOS combined with IR and will provide new clues for studying metabolic disorders associated with PCOS, e.g., IR.

Urinary Metabolomic Changes Accompanying Albuminuria Remission following Gastric Bypass Surgery for Type 2 Diabetic Kidney Disease

In the Microvascular Outcomes after Metabolic Surgery randomised clinical trial (MOMS RCT, NCT01821508), combined metabolic surgery (gastric bypass) plus medical therapy (CSM) was superior to medical therapy alone (MTA) as a means of achieving albuminuria remission at 2-year follow-up in patients with obesity and early diabetic kidney disease (DKD). In the present study, we assessed the urinary ¹H-NMR metabolome in a subgroup of patients from both arms of the MOMS RCT at baseline and 6-month follow-up. Whilst CSM and MTA both reduced the urinary excretion of sugars, CSM generated a distinctive urinary metabolomic profile characterised by increases in host–microbial co-metabolites (N-phenylacetylglycine, trimethylamine N-oxide, and 4-aminobutyrate (GABA)) and amino acids (arginine and glutamine). Furthermore, reductions in aromatic amino acids (phenylalanine and tyrosine), as well as branched-chain amino acids (BCAAs) and related catabolites (valine, leucine, 3-hydroxyisobutyrate, 3-hydroxyisovalerate, and 3-methyl-2-oxovalerate), were observed following CSM but not MTA. Improvements in BMI did not correlate with improvements in metabolic and renal indices following CSM. Conversely, urinary metabolites changed by CSM at 6 months were moderately to strongly correlated with improvements in blood pressure, glycaemia, triglycerides, and albuminuria up to 24 months following treatment initiation, highlighting the potential involvement of these shifts in the urinary metabolomic profile in the metabolic and renoprotective effects of CSM.

Metabolomics of Type 1 and Type 2 Diabetes: Insights into Risk Prediction and Mechanisms

PURPOSE OF REVIEW

Metabolomics enables rapid interrogation of widespread metabolic processes making it well suited for studying diabetes. Here, we review the current status of metabolomic investigation in diabetes, highlighting its applications for improving risk prediction and mechanistic understanding.

RECENT FINDINGS

Findings of metabolite associations with type 2 diabetes risk have confirmed experimental observations (e.g., branched-chain amino acids) and also pinpointed novel pathways of diabetes risk (e.g., dimethylguanidino valeric acid). In type 1 diabetes, abnormal metabolite patterns are observed prior to the development of autoantibodies and hyperglycemia. Diabetes complications display specific metabolite signatures that are distinct from the metabolic derangements of diabetes and differ across vascular beds. Lastly, metabolites respond acutely to pharmacologic treatment, providing opportunities to understand inter-individual treatment responses. Metabolomic studies have elucidated biological mechanisms underlying diabetes development, complications, and therapeutic response. While not yet ready for clinical translation, metabolomics is a powerful and promising precision medicine tool.

Serum Orosomucoid Is Associated with Serum Adiponectin, Adipose Tissue Insulin Resistance Index, and a Family History of Type 2 Diabetes in Young Normal Weight Japanese Women

INTRODUCTION

Adipose tissue (AT) expandability may be facilitated by adiponectin and suppressed by orosomucoid, and reduced AT expandability may be associated with first-degree relatives of type 2 diabetes. We tested the hypothesis that orosomucoid may be associated not only with adiponectin and adipose tissue insulin resistance but also with a family history of type 2 diabetes (FHD). Research Design and Methods. Anthropometric and metabolic variables, adipokines, and measures of inflammatory and insulin resistance were cross-sectionally investigated in 153 young normal weight Japanese women. Stepwise multivariate linear regression analyses were used to identify the most important determinants of orosomucoid.

RESULTS

Orosomucoid was higher in women with positive (n = 57) compared to women with negative FHD and was associated positively with FHD (both p = 0.01). Orosomucoid also showed positive associations with fasting glucose (p < 0.001), free fatty acids (p = 0.001), and HbA1c (p = 0.007), whereas there was no association with fasting insulin and serum lipids. In addition, orosomucoid was associated inversely with adiponectin (p = 0.02) and positively with adipose tissue-insulin resistance index (AT-IR, the product of fasting insulin and free fatty acids; p = 0.001) but not with homeostasis model assessment-insulin resistance, leptin, and high-sensitivity C-reactive protein. In multivariate analyses, AT-IR (standardized β, 0.22; p = 0.003), serum adiponectin (standardized β, -0.163; p = 0.032), FHD+ (standardized β, 0.178; p = 0.029), and HbA1c (standardized β, 0.213; p = 0.005) emerged as independent determinants of orosomucoid and explained 15.2% of its variability.

CONCLUSIONS

These results are the first to demonstrate that orosomucoid is associated not only with adipose tissue-insulin resistance and adiponectin but also with FHD.

Sudden cardiac death in diabetes and obesity: mechanisms and therapeutic strategies

Ventricular arrhythmias and sudden cardiac death (SCD) occur most frequently in the setting of coronary artery disease, cardiomyopathy and heart failure, but are also increasingly observed in individuals suffering from diabetes mellitus and obesity. The incidence of these metabolic disorders is rising in Western countries, but adequate prevention and treatment of arrhythmias and SCD in affected patients is limited due to our incomplete knowledge of the underlying disease mechanisms. Here, an overview is presented of the prevalence of electrophysiological disturbances, ventricular arrhythmias and SCD in the clinical setting of diabetes and obesity. Experimental studies are reviewed, which have identified disease pathways and associated modulatory factors, in addition to pro-arrhythmic mechanisms. Key processes are discussed, including mitochondrial dysfunction, oxidative stress, cardiac structural derangements, abnormal cardiac conduction, ion channel dysfunction, prolonged repolarization and dysregulation of intracellular sodium and calcium homeostasis. In addition, the recently identified pro-arrhythmic effects of dysregulated branched chain amino acid metabolism, a common feature in patients with metabolic disorders, are addressed. Finally, current management options are discussed, in addition to the potential development of novel preventive and therapeutic strategies based on recent insight gained from translational studies.

Gut microbiota: A new target for T2DM prevention and treatment

Type 2 diabetes mellitus (T2DM), one of the fastest growing metabolic diseases, has been characterized by metabolic disorders including hyperglycemia, hyperlipidemia and insulin resistance (IR). In recent years, T2DM has become the fastest growing metabolic disease in the world. Studies have indicated that patients with T2DM are often associated with intestinal flora disorders and dysfunction involving multiple organs. Metabolites of the intestinal flora, such as bile acids (BAs), short-chain fatty acids (SCFAs) and amino acids (AAs)may influence to some extent the decreased insulin sensitivity associated with T2DM dysfunction and regulate metabolic as well as immune homeostasis. In this paper, we review the changes in the gut flora in T2DM and the mechanisms by which the gut microbiota modulates metabolites affecting T2DM, which may provide a basis for the early identification of T2DM-susceptible individuals and guide targeted interventions. Finally, we also highlight gut microecological therapeutic strategies focused on shaping the gut flora to inform the improvement of T2DM progression.

Glycoprotein Profile Measured by a 1H-Nuclear Magnetic Resonance Based on Approach in Patients with Diabetes: A New Robust Method to Assess Inflammation

Patients with type 2 diabetes mellitus (T2DM) and atherogenic dyslipidemia (AD) are at higher risk of developing cardiovascular diseases (CVDs), so an interest in discovering inflammation biomarkers as indicators of processes related to CVD progression is increasing. This study aims (a) to characterize the plasma glycoprotein profile of a cohort of 504 participants, including patients with and without T2DM and/or AD and controls, and (b) to study the associations between the glycoprotein profile and other lipid and clinical variables in these populations. We characterized the plasma glycoprotein profiles by using ¹H-NMR. We quantified the two peaks associated with the concentration of plasma glycoproteins (GlycA and GlycB) and their height/width ratios (H/W GlycA and H/W GlycB), as higher and narrower signals have been related to inflammation. We also quantified GlycF, the signal of which is proportional to the concentration of the acetyl groups of free N-acetylglucosamine, N-acetylgalactosamine, and N-acetylneuraminic in the samples. The lipoprotein profile was also determined (Liposcale^®). Standard clinical and anthropometric measurements were taken. Multivariate classification models were developed to study the differences between the study groups. Reduced HDL-C levels, increased small dense LDL and HDL particles, and elevated TG levels were significantly associated with glycoprotein variables. Glycoprotein values in the diagnostic groups were significantly different from those in the CT groups. AD and DM conditions together contribute to a positive and significant synergetic effect on the GlycA area (<0.05) and the H/W ratios of GlycA (<0.01) and GlycB (<0.05). By adding the new glycoprotein variables to the traditionally used marker of inflammation C-reactive protein (CRP), the AUC increased sharply for classification models between the CT group and the rest (0.68 to 0.84), patients with and without dyslipidemia (0.54 to 0.86), and between patients with and without diabetes (0.55 to 0.75). ¹H-NMR-derived glycoproteins can be used as possible markers of the degree of inflammation associated with T2DM and AD.

Spousal associations of serum metabolomic profiles by nuclear magnetic resonance spectroscopy

Phenotype-based assortative mating is well established in humans, with the potential for further convergence through a shared environment. To assess the correlation within infertile couples of physical, social, and behavioural characteristics and 155 circulating metabolic measures. Cross sectional study at a tertiary medical center of 326 couples undertaking IVF. Serum lipids, lipoprotein subclasses, and low-molecular weight metabolites as quantified by NMR spectroscopy (155 metabolic measures). Multivariable and quantile regression correlations within couples of metabolite profiles. Couples exhibited statistical correlations of varying strength for most physical, social, and behavioural characteristics including age, height, alcohol consumption, education, smoking status, physical activity, family history and ethnicity, with correlation coefficients ranging from 0.22 to 0.73. There was no evidence of within couple associations for BMI and weight, where the correlation coefficients were - 0.03 (95% CI - 0.14, 0.08) and 0.01 (95% CI - 0.10, 0.12), respectively. Within spousal associations of the metabolite measurements were all positive but with weak to modest magnitudes, with the median correlation coefficient across all 155 measures being 0.12 (range 0.01-0.37 and interquartile range 0.10-0.18). With just four having associations stronger than 0.3: docosahexaenoic acid (0.37, 95% CI 0.22, 0.52), omega-3 fatty acids (0.32, 95% CI 0.20, 0.43) histidine (0.32, 95% CI 0.23, 0.41) and pyruvate (0.32, 95% CI 0.22, 0.43). Infertile couples exhibit spousal similarities for a range of demographic and serum metabolite measures, supporting initial assortative mating, with diet-derived metabolites suggesting possible subsequent convergence of their individual metabolic profile.

Plasma triacylglycerols are biomarkers of β-cell function in mice and humans

Objectives

To find plasma biomarkers prognostic of type 2 diabetes, which could also inform on pancreatic β-cell deregulations or defects in the function of insulin target tissues.

Methods

We conducted a systems biology approach to characterize the plasma lipidomes of C57Bl/6J, DBA/2J, and BALB/cJ mice under different nutritional conditions, as well as their pancreatic islet and liver transcriptomes. We searched for correlations between plasma lipids and tissue gene expression modules.

Results

We identified strong correlation between plasma triacylglycerols (TAGs) and islet gene modules that comprise key regulators of glucose- and lipid-regulated insulin secretion and of the insulin signaling pathway, the two top hits were Gck and Abhd6 for negative and positive correlations, respectively. Correlations were also found between sphingomyelins and islet gene modules that overlapped in part with the gene modules correlated with TAGs. In the liver, the gene module most strongly correlated with plasma TAGs was enriched in mRNAs encoding fatty acid and carnitine transporters as well as multiple enzymes of the β-oxidation pathway. In humans, plasma TAGs also correlated with the expression of several of the same key regulators of insulin secretion and the insulin signaling pathway identified in mice. This cross-species comparative analysis further led to the identification of PITPNC1 as a candidate regulator of glucose-stimulated insulin secretion.

Conclusion

TAGs emerge as biomarkers of a liver-to-β-cell axis that links hepatic β-oxidation to β-cell functional mass and insulin secretion.

•

Plasma triacylglycerols correlated with genes controlling β-cell mass and function.

•

Plasma triacylglycerols correlated with genes controlling liver β-oxidation.

•

In humans, triacylglycerols also correlated with key regulators of insulin secretion.

•

Mouse and human data identified PITPNC1 as a candidate regulator of insulin secretion.

•

Triacylglycerols are biomarkers of the liver-to-β-cell axis and β-cell function.

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.

Current progress in metabolomics of gestational diabetes mellitus

Gestational diabetes mellitus (GDM) is one of the most common metabolic disorders of pregnancy and can cause short- and long-term adverse effects in both pregnant women and their offspring. However, the etiology and pathogenesis of GDM are still unclear. As a metabolic disease, GDM is well suited to metabolomics study, which can monitor the changes in small molecular metabolites induced by maternal stimuli or perturbations in real time. The application of metabolomics in GDM can be used to discover diagnostic biomarkers, evaluate the prognosis of the disease, guide the application of diet or drugs, evaluate the curative effect, and explore the mechanism. This review provides comprehensive documentation of metabolomics research methods and techniques as well as the current progress in GDM research. We anticipate that the review will contribute to identifying gaps in the current knowledge or metabolomics technology, provide evidence-based information, and inform future research directions in GDM.

Molecular Aspects of Lifestyle and Environmental Effects in Patients With Diabetes: JACC Focus Seminar

Diabetes is characterized as an integrated condition of dysregulated metabolism across multiple tissues, with well-established consequences on the cardiovascular system. Recent advances in precision phenotyping in biofluids and tissues in large human observational and interventional studies have afforded a unique opportunity to translate seminal findings in models and cellular systems to patients at risk for diabetes and its complications. Specifically, techniques to assay metabolites, proteins, and transcripts, alongside more recent assessment of the gut microbiome, underscore the complexity of diabetes in patients, suggesting avenues for precision phenotyping of risk, response to intervention, and potentially novel therapies. In addition, the influence of external factors and inputs (eg, activity, diet, medical therapies) on each domain of molecular characterization has gained prominence toward better understanding their role in prevention. Here, the authors provide a broad overview of the role of several of these molecular domains in human translational investigation in diabetes.

Metabolomics in Bariatric Surgery: Towards Identification of Mechanisms and Biomarkers of Metabolic Outcomes

Bariatric surgery has been widely performed for the treatment of obesity and type 2 diabetes. Efforts have been made to investigate the mechanisms underlying the metabolic effects achieved by bariatric surgery and to identify candidates who will benefit from this surgery. Metabolomics, which includes comprehensive profiling of metabolites in biological samples, has been utilized for various disease entities to discover pathophysiological metabolic pathways and biomarkers predicting disease progression or prognosis. Over the last decade, metabolomic studies on patients undergoing bariatric surgery have identified significant biomarkers related to metabolic effects. This review describes the significance, progress, and challenges for the future of metabolomics in the area of bariatric surgery.

Associations between serum amino acids and incident type 2 diabetes in Chinese rural adults

BACKGROUND AND AIMS

Some amino acids (AAs) may be associated with type 2 diabetes (T2DM). This study aimed to determine the associations of individual AAs with the development of T2DM in rural Chinese adults.

METHODS AND RESULTS

A cohort study of 1199 individuals aged 18 years or older was conducted from 2006 to 2008 in a rural community of Deqing, China, a repeated survey was done in 2015 and data linkage with the electronic health records system was performed each year for identifying new T2DM cases. A high-performance liquid chromatography approach was used to measure the baseline serum concentrations of 15 AAs. Cox proportional hazards models were used to examine the associations between AAs and the risk of incident T2DM. A total of 98 new T2DM cases were identified during the follow-up of 12 years on average. Among 15 AAs, proline was associated with an increased risk of incident T2DM after adjusted for age, sex, body mass index, fasting plasma glucose, family history of T2DM, smoking status, alcohol use, and history of hypertension, the adjusted hazard ratio for 1-standard deviation increment was 1.20 (95% confidence interval: 1.00, 1.43). The association tended to be more marked in subjects younger than 60 years and overweight/obese subjects. Among participants without hypertension, proline and phenylalanine were associated with an increased risk of incident T2DM, while aspartic acid was associated with a decreased risk.

CONCLUSION

Serum proline was associated with the risk of incident T2DM in rural Chinese adults and might be a potential predictor.

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.

Effect on gut microbiota of a 1-y lifestyle intervention with Mediterranean diet compared with energy-reduced Mediterranean diet and physical activity promotion: PREDIMED-Plus Study

BACKGROUND

The Mediterranean diet is a well-recognized healthy diet that has shown to induce positive changes in gut microbiota. Lifestyle changes such as diet along with physical activity could aid in weight loss and improve cardiovascular risk factors.

OBJECTIVES

To investigate the effect of an intensive lifestyle weight loss intervention on gut microbiota.

METHODS

This is a substudy of the PREDIMED-Plus (Prevención con Dieta Mediterránea-Plus), a randomized controlled trial conducted in overweight/obese men and women (aged 55-75 y) with metabolic syndrome. The intervention group (IG) underwent an intensive weight loss lifestyle intervention based on an energy-restricted Mediterranean diet (MedDiet) and physical activity promotion, and the control group (CG) underwent a non-energy-restricted MedDiet for 1 y. Anthropometric, biochemical, and gut microbial 16S rRNA sequencing data were analyzed at baseline (n = 362) and 1-y follow-up (n = 343).

RESULTS

IG participants had a weight loss of 4.2 (IQR, -6.8, -2.5) kg compared with 0.2 (IQR, -2.1, 1.4) kg in the CG (P < 0.001). Reductions in BMI, fasting glucose, glycated hemoglobin, and triglycerides and an increase in HDL cholesterol were greater in IG than in CG participants (P < 0.05). We observed a decrease in Butyricicoccus, Haemophilus, Ruminiclostridium 5, and Eubacterium hallii in the IG compared with the CG. Many genera shifted in the same direction within both intervention groups, indicating an overall effect of the MedDiet. Decreases in Haemophilus, Coprococcus 3, and few other genera were associated with a decrease in adiposity parameters in both intervention groups. Changes in Lachnospiraceae NK4A136 were positively associated with changes in MedDiet adherence.

CONCLUSIONS

Weight loss induced by an energy-restricted MedDiet and physical activity induce changes in gut microbiota. The role of MedDiet-induced changes on the host might be via short-chain fatty acid producing bacteria, whereas with energy restriction, these changes might be modulated with other mechanisms, which need to be explored in future studies. This trial was registered at http://www.isrctn.com/ISRCTN89898870 as ISRCT 89898870.

Metabolic and biological changes in children with obesity and diabetes

The World Health Organization has stated that obesity in childhood is one of the most serious public health challenges of the 21^st century. Overweightness and obesity in early childhood lead to a higher risk of overweightness and obesity in adulthood, thus conferring an increased risk of chronic inflammatory conditions, including type 2 diabetes mellitus, cardiovascular diseases, non-alcoholic fatty liver disease, and some cancers. Therefore, metabolome analysis, targeted at screening and intervening in childhood obesity, is very important. Recent studies have indicated that amino acid and lipid metabolism could influence metabolic pathways in children with obesity. For this review, we searched clinical data addressing metabolomic profiles and insulin resistance (IR) in children with obesity from inception to February 2021 in Medline, Web of Science, and Scopus. According to our search, branched-chain amino acids (BCAAs), aromatic amino acids, and acylcarnitines have reportedly been associated with IR as biomarkers for diabetes in children. BCAAs, tyrosine, and phenylalanine could be predictors of the future development of diabetes in nondiabetic subjects. In addition, it is well known that insulin regulates BCAA metabolism, and BCAA is a biomarker for IR. To interpret the mechanism behind metabolic changes in obesity, it is very important to understand the pathways and combinations related with amino acid, lipid and glucose metabolism. In this review, we summarize studies on metabolic changes to understand metabolomics in children with obesity.

Changes in Plasma Metabolome Profiles Following Oral Glucose Challenge among Adult Chinese

Little is known about changes in plasma metabolome profiles during the oral glucose tolerance test (OGTT) in Chinese. We aimed to characterize plasma metabolomic profiles at 0 and 2 h of OGTT and their changes in individuals of different glycemic statuses. A total of 544 metabolites were detected at 0 and 2 h of OGTT by a nontarget strategy in subjects with normal glucose (n = 234), prediabetes (n = 281), and newly diagnosed type 2 diabetes (T2D) (n = 66). Regression model, mixed model, and partial least squares discrimination analysis were applied. Compared with subjects of normal glucose, T2D cases had significantly higher levels of glycerone at 0 h and 22 metabolites at 2 h of OGTT (false discovery rate (FDR) < 0.05, variable importance in projection (VIP) > 1). Seven of the twenty-two metabolites were also significantly higher in T2D than in prediabetes subjects at 2 h of OGTT (FDR < 0.05, VIP > 1). Two hours after glucose challenge, concentrations of 35 metabolites (normal: 18; prediabetes: 23; T2D: 13) significantly increased (FDR < 0.05, VIP > 1, fold change (FC) > 1.2), whereas those of 45 metabolites (normal: 36; prediabetes: 29; T2D: 18) significantly decreased (FDR < 0.05, VIP > 1, FC < 0.8). Distinct responses between cases and noncases were detected in metabolites including 4-imidazolone-5-acetate and 4-methylene-L-glutamine. More varieties of distinct metabolites across glycemic statuses were observed at 2 h of OGTT compared with fasting state. Whether the different patterns and responsiveness of certain metabolites in T2D reflect a poor resilience of specific metabolic pathways in regaining glucose homeostasis merits further study.

Extent reflecting overall dietary amino acids composition adherence to the human requirement amino acids pattern is associated with the development of type 2 diabetes

This study aimed to elucidate whether dietary amino acids (AAs) composition is associated with type 2 diabetes mellitus (T2DM) and to investigate how serum AAs profiles mediated this association. Two prospective cohorts of 1750 and 4024 adults were enrolled. Dietary AAs compositions index (AACI) was developed to reflect the overall quality of dietary AAs composition. Multivariate linear regression and logistic regression models were used to examine associations of AACI and T2DM. The AACI was associated with the incidence of T2DM with the relative risk and 95%CI from the bottom to the top tertiles being 1.00, 1.49 (0.88-2.51) and 2.27 (1.20-4.28), and 1.00, 1.58 (1.13-2.19) and 2.33 (1.56-3.47) in the two cohorts, respectively. The AACI was positively associated with serum valine, isoleucine, glutamic acid and phenylalanine, and it was negatively associated with serum glycine and histidine in both cohorts (P<0.01). Valine, glutamic acid and histidine consistently and partially mediated the association between the AACI and T2DM in the two cohorts, with total mediation effects of 33.4% and 54.6%, respectively. Dietary AAs composition was associated with the incidence of T2DM, meanwhile, the relationship was mediated by some degree of serum AAs. Future dietary strategies should focus on the improvement of the overall quality of dietary AAs compositions.

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.

Multiomics Approach to Explore the Amelioration Mechanisms of Glucomannans on the Metabolic Disorder of Type 2 Diabetic Rats

Type 2 diabetes (T2D) is a worldwide epidemic associated with metabolic disorders and intestinal microbiota alterations. Polysaccharides have been considered to be beneficial to the prevention and alleviation of T2D. In the present study, ultra-performance liquid chromatography-triple-time-of-flight-based metabolomics and proteomics and 16S rRNA sequencing methods were employed to evaluate the effects of glucomannans from Dendrobium officinale stem, konjac, and Aloe vera leaves on host metabolism and intestinal microbiota regulation in type 2 diabetic rats and potential mechanisms. The metabolism of amino acids was significantly disturbed in the type 2 diabetic rats, especially the upregulated branched-chain amino acid (BCAA) metabolism. Host-derived BCAA metabolism was significantly decreased in type 2 diabetic rats. However, the levels of BCAAs in host circulation and gene abundance of BCAA biosynthesis in gut microbiota were significantly increased in diabetic rats, which suggested that the disturbed intestinal microbiota might be responsible for the increased circulation of BCAAs in T2D. Glucomannan treatment decreased the abundance of microbial BCAA biosynthesis-related genes and ameliorated the host BCAA metabolism. Also, glucomannan with a higher molecular weight and a lower ratio of mannose/glucose possessed better antidiabetic effects. In summary, the antidiabetic effects of glucomannans might be associated with the amelioration of BCAA metabolism by modulating intestinal microbiota.

Identification of metabolic markers predictive of prediabetes in a Korean population

Prediabetes (PD) is a high-risk state of developing type 2 diabetes, and cardiovascular and metabolic diseases. Metabolomics-based biomarker studies can provide advanced opportunities for prediction of PD over the conventional methods. Here, we aimed to identify metabolic markers and verify their abilities to predict PD, as compared to the performance of the traditional clinical risk factor (CRF) and previously reported metabolites in other population-based studies. Targeted metabolites quantification was performed in 1723 participants in the Korea Association REsource (KARE) cohort, from which 500 normal individuals were followed up for 6 years. We selected 12 significant metabolic markers, including five amino acids, four glycerophospholipids, two sphingolipids, and one acylcarnitine, at baseline, resulting in a predicted incidence of PD with an area under the curve (AUC) of 0.71 during follow-up. The performance of these metabolic markers compared to that of fasting glucose was significantly higher in obese patients (body mass index: BMI ≥ 25 kg/m², 0.79 vs. 0.58, P < 0.001). The combination with metabolic markers, CRF, and fasting glucose yielded the best prediction performance (AUC = 0.86). Our results revealed that metabolic markers were not only associated with the risk of PD, but also improved the prediction performance in combination with conventional approaches.

Branched-Chain Amino Acid Oxidation Is Elevated in Adults with Morbid Obesity and Decreases Significantly after Sleeve Gastrectomy

BACKGROUND

Plasma concentrations of branched-chain amino acids (BCAAs) are elevated in obese individuals with insulin resistance (IR) and decrease after bariatric surgery. However, the metabolic mechanisms are unclear.

OBJECTIVES

Our objectives are to compare leucine kinetics between morbidly obese and healthy-weight individuals cross-sectionally, and to prospectively evaluate changes in the morbidly obese after sleeve gastrectomy. We hypothesized that leucine oxidation is slower in obese individuals and increases after surgery.

METHODS

Ten morbidly obese [BMI (in kg/m2) ≥32.5, age 21-50 y] and 10 healthy-weight participants (BMI <25), matched for age (median ∼30 y) but not gender, were infused with [U-13C6] leucine and [2H5] glycerol to quantify leucine and glycerol kinetics. Morbidly obese participants were studied again 6 mo postsurgery. Primary outcomes were kinetic parameters related to BCAA metabolism. Data were analyzed by nonparametric methods and presented as median (IQR).

RESULTS

Participants with obesity had IR with an HOMA-IR (4.89; 4.36-8.76) greater than that of healthy-weight participants (1.32; 0.99-1.49; P < 0.001) and had significantly faster leucine flux [218; 196-259 compared with 145; 138-149 μmol · kg fat-free mass (FFM)-1 · h-1], oxidation (24.0; 17.9-29.8 compared with 16.1; 14.3-18.5 μmol · kg FFM-1 · h-1), and nonoxidative disposal (204; 190-247 compared with 138; 129-140 μmol · kg FFM-1 · h-1) (P < 0.017 for all). After surgery, the morbidly obese had a marked improvement in IR (3.54; 3.06-6.08; P = 0.008) and significant reductions in BCAA concentrations (113; 95-157 μmol/L) and leucine oxidation (9.37; 6.85-15.2 μmol · kg FFM-1 · h-1) (P = 0.017 for both). Further, leucine flux in this group correlated significantly with IR (r = 0.78, P < 0.001).

CONCLUSIONS

BCAA oxidation is not impaired but elevated in individuals with morbid obesity. Plasma BCAA concentrations are lowered after surgery owing to slower breakdown of body proteins as insulin's ability to suppress proteolysis is restored. These findings suggest that IR is the underlying cause and not the consequence of elevated BCAAs in obesity.

Establishing reference intervals for triglyceride-containing lipoprotein subfraction metabolites measured using nuclear magnetic resonance spectroscopy in a UK population

BACKGROUND

Nuclear magnetic resonance (NMR) spectroscopy allows triglycerides to be subclassified into 14 different classes based on particle size and lipid content. We recently showed that these subfractions have differential associations with cardiovascular disease events. Here we report the distributions and define reference interval ranges for 14 triglyceride-containing lipoprotein subfraction metabolites.

METHODS

Lipoprotein subfractions using the Nightingale NMR platform were measured in 9073 participants from four cohort studies contributing to the UCL-Edinburgh-Bristol consortium. The distribution of each metabolite was assessed, and reference interval ranges were calculated for a disease-free population, by sex and age group (<55, 55-65, >65 years), and in a subgroup population of participants with cardiovascular disease or type 2 diabetes. We also determined the distribution across body mass index and smoking status.

RESULTS

The largest reference interval range was observed in the medium very-low density lipoprotein subclass (2.5th 97.5th percentile; 0.08 to 0.68 mmol/L). The reference intervals were comparable among male and female participants, with the exception of triglyceride in high-density lipoprotein. Triglyceride subfraction concentrations in very-low density lipoprotein, intermediate-density lipoprotein, low-density lipoprotein and high-density lipoprotein subclasses increased with increasing age and increasing body mass index. Triglyceride subfraction concentrations were significantly higher in ever smokers compared to never smokers, among those with clinical chemistry measured total triglyceride greater than 1.7 mmol/L, and in those with cardiovascular disease, and type 2 diabetes as compared to disease-free subjects.

CONCLUSION

This is the first study to establish reference interval ranges for 14 triglyceride-containing lipoprotein subfractions in samples from the general population measured using the nuclear magnetic resonance platform. The utility of nuclear magnetic resonance lipid measures may lead to greater insights for the role of triglyceride in cardiovascular disease, emphasizing the importance of appropriate reference interval ranges for future clinical decision making.

Higher circulating orosomucoid, an acute-phase protein, and reduced glucose-induced insulin secretion in middle-aged Japanese people with prediabetes

INTRODUCTION

Circulating orosomucoid, an acute-phase protein, predicted type 2 diabetes mellitus risk in several Western countries. Here, we assessed serum orosomucoid (ORM) in relation to prediabetes in the Japanese.

RESEARCH DESIGN AND METHODS

Participants consisted of 83 middle-aged Japanese subjects with normal glucose tolerance (NGT), 37 with prediabetes and 4 with newly identified diabetes, whose homeostasis model assessment-insulin resistance (HOMA-IR) averaged 1.1±0.7, 1.4±0.9 and 1.7±0.8, respectively. Body composition, serum inflammatory markers, adiponectin, β-cell function and insulin resistance inferred from serum insulin kinetics during an oral glucose tolerance test were compared cross-sectionally between those with prediabetes and NGT.

RESULTS

Serum orosomucoid, but not high-sensitivity C reactive protein, was elevated in prediabetes (190±29 vs 141±31 mg/dL) with further elevation in diabetes (295±52 mg/dL) (all p<0.001). Prediabetes was associated with lower Oral Disposition Index (the product of the Insulinogenic Index and Matsuda Index) with further depression in diabetes. No association was found with skeletal muscle mass, HOMA-IR, serum triglyceride, high-density lipoprotein (HDL) cholesterol and adiponectin.

CONCLUSIONS

Higher circulating ORM and reduced glucose induced insulin secretion were found in middle-aged Japanese people with prediabetes in the absence of insulin resistance.

Molecular Signature of Multisystem Cardiometabolic Stress and Its Association With Prognosis

Importance

Cardiometabolic disease is responsible for decreased longevity and poorer cardiovascular outcomes in the modern era. Metabolite profiling provides a specific measure of global metabolic function to examine specific metabolic mechanisms and pathways of cardiometabolic disease beyond its clinical definitions.

Objectives

To define a molecular basis for cardiometabolic stress and assess its association with cardiovascular prognosis.

Design, Setting, and Participants

A prospective observational cohort study was conducted in a population-based setting across 2 geographically distinct centers (Boston Puerto Rican Health Study [BPRHS], an ongoing study of individuals enrolled between June 1, 2004, and October 31, 2009; and Atherosclerosis Risk in Communities [ARIC] study, whose participants were originally sampled between November 24, 1986, and February 10, 1990, and followed up through December 31, 2017). Participants in the BPRHS were 668 Puerto Rican individuals with metabolite profiling living in Massachusetts, and participants in the ARIC study were 2152 individuals with metabolite profiling and long-term follow-up for mortality and cardiovascular outcomes. Statistical analysis was performed from October 1, 2018, to March 13, 2020.

Exposure

The primary exposure was metabolite profiles across both cohorts.

Main Outcomes and Measures

Outcomes included associations with multisystem cardiometabolic stress and all-cause mortality and incident coronary heart disease (in the ARIC study).

Results

Participants in the BPRHS (N = 668; 491 women; mean [SD] age, 57.0 [7.4] years; mean [SD] body mass index [calculated as weight in kilograms divided by height in meters squared], 32.0 [6.5]) had higher prevalent cardiometabolic risk relative to those in the ARIC study (N = 2152; 599 African American individuals; 1213 women; mean [SD] age, 54.3 [5.7] years; mean [SD] body mass index, 28.0 [5.5]). Multisystem cardiometabolic stress was defined for 668 Puerto Rican individuals in the BPRHS as a multidimensional composite of hypothalamic-adrenal axis activity, sympathetic activation, blood pressure, proatherogenic dyslipidemia, insulin resistance, visceral adiposity, and inflammation. A total of 260 metabolites associated with cardiometabolic stress were identified in the BPRHS, involving known and novel pathways of cardiometabolic disease (eg, amino acid metabolism, oxidative stress, and inflammation). A parsimonious metabolite-based score associated with cardiometabolic stress in the BPRHS was subsequently created; this score was applied to shared metabolites in the ARIC study, demonstrating significant associations with coronary heart disease and all-cause mortality after multivariable adjustment at a 30-year horizon (per SD increase in metabolomic score: hazard ratio, 1.14; 95% CI, 1.00-1.31; P = .045 for coronary heart disease; and hazard ratio, 1.15; 95% CI, 1.07-1.24; P < .001 for all-cause mortality).

Conclusions and Relevance

Metabolites associated with cardiometabolic stress identified known and novel pathways of cardiometabolic disease in high-risk, community-based cohorts and were associated with coronary heart disease and survival at a 30-year time horizon. These results underscore the shared molecular pathophysiology of metabolic dysfunction, cardiovascular disease, and longevity and suggest pathways for modification to improve prognosis across all linked conditions.

Association of the functional ovarian reserve with serum metabolomic profiling by nuclear magnetic resonance spectroscopy: a cross-sectional study of ~ 400 women

BACKGROUND

Women with diminished ovarian reserve are known to have increased cardiovascular risk, whether there is a continuous association between the ovarian reserve biomarkers; anti-Müllerian hormone (AMH), antral follicle count (AFC) and cardio-metabolic risk factors are unknown.

METHODS

A cross-sectional study of 398 women intending to undergo IVF with pre-treatment early follicular AMH and AFC measurements. Serum lipids, lipoprotein subclasses and low-molecular-weight metabolites were quantified by NMR spectroscopy (155 metabolic measures). Associations were analysed using multivariable regression.

RESULTS

Participants were mean 35.5 (SD 4.43) years old and had a median AMH of 16 pmol/l (IQR 8.8, 28.0 pmol/l) and a median AFC of 12 (IQR 7.16). AMH showed positive associations with HDL, omega-6 and polyunsaturated fatty acids and the amino acids isoleucine, leucine and tyrosine, with effects ranging from 0.11 (95%CI 0.004 to 0.21) for total lipids in small HDL to 0.16 (0.06 to 0.26) for isoleucine, for a mean difference of one SD of metabolite per one SD increment in AMH, and negatively with acetate: - 0.31(- 0.22, - 0.004) SD per 1 SD AMH. AFC was positively associated with alanine, glutamine and glycine. Results were consistent, though less precisely estimated, when restricted to those women who were preparing for treatment because of their partner's infertility.

CONCLUSIONS

In women intending to have IVF, AMH and AFC were not associated with traditional lipid measured but were associated with a number of novel cardiovascular risk factors. Prospective studies will be required for replication, determination of causality and confirmation that ovarian reserve is impacting on metabolism rather than variation in metabolism is influencing ovarian reserve.

Early Metabolic Features of Genetic Liability to Type 2 Diabetes: Cohort Study With Repeated Metabolomics Across Early Life

OBJECTIVE

Type 2 diabetes develops for many years before diagnosis. We aimed to reveal early metabolic features characterizing liability to adult disease by examining genetic liability to adult type 2 diabetes in relation to metabolomic traits across early life.

RESEARCH DESIGN AND METHODS

Up to 4,761 offspring from the Avon Longitudinal Study of Parents and Children were studied. Linear models were used to examine effects of a genetic risk score (162 variants) for adult type 2 diabetes on 229 metabolomic traits (lipoprotein subclass-specific cholesterol and triglycerides, amino acids, glycoprotein acetyls, and others) measured at age 8 years, 16 years, 18 years, and 25 years. Two-sample Mendelian randomization (MR) was also conducted using genome-wide association study data on metabolomic traits in an independent sample of 24,925 adults.

RESULTS

At age 8 years, associations were most evident for type 2 diabetes liability (per SD higher) with lower lipids in HDL subtypes (e.g., -0.03 SD [95% CI -0.06, -0.003] for total lipids in very large HDL). At 16 years, associations were stronger with preglycemic traits, including citrate and with glycoprotein acetyls (0.05 SD; 95% CI 0.01, 0.08), and at 18 years, associations were stronger with branched-chain amino acids. At 25 years, associations had strengthened with VLDL lipids and remained consistent with previously altered traits, including HDL lipids. Two-sample MR estimates among adults indicated persistent patterns of effect of disease liability.

CONCLUSIONS

Our results support perturbed HDL lipid metabolism as one of the earliest features of type 2 diabetes liability, alongside higher branched-chain amino acid and inflammatory levels. Several features are apparent in childhood as early as age 8 years, decades before the clinical onset of disease.