High plasma glutamate and low glutamine-to-glutamate ratio are associated with type 2 diabetes: Case-cohort study within the PREDIMED trial

Hyperglycemia impairs EAAT2 glutamate transporter trafficking and glutamate clearance in islets of Langerhans: implications for type 2 diabetes pathogenesis and treatment

Pancreatic endocrine cells employ a sophisticated system of paracrine and autocrine signals to synchronize their activities, including glutamate, which controls hormone release and β-cell viability by acting on glutamate receptors expressed by endocrine cells. We here investigate whether alteration of the excitatory amino acid transporter 2 (EAAT2), the major glutamate clearance system in the islet, may occur in type 2 diabetes mellitus and contribute to β-cell dysfunction. Increased EAAT2 intracellular localization was evident in islets of Langerhans from T2DM subjects as compared with healthy control subjects, despite similar expression levels. Chronic treatment of islets from healthy donors with high-glucose concentrations led to the transporter internalization in vesicular compartments and reduced [H3]-d-glutamate uptake (65 ± 5% inhibition), phenocopying the findings in T2DM pancreatic sections. The transporter relocalization was associated with decreased Akt phosphorylation protein levels, suggesting an involvement of the phosphoinositide 3-kinase (PI3K)/Akt pathway in the process. In line with this, PI3K inhibition by a 100-µM LY294002 treatment in human and clonal β-cells caused the transporter relocalization in intracellular compartments and significantly reduced the glutamate uptake compared to control conditions, suggesting that hyperglycemia changes the trafficking of the transporter to the plasma membrane. Upregulation of the glutamate transporter upon treatment with the antibiotic ceftriaxone rescued hyperglycemia-induced β-cells dysfunction and death. Our data underscore the significance of EAAT2 in regulating islet physiology and provide a rationale for potential therapeutic targeting of this transporter to preserve β-cell survival and function in diabetes.NEW & NOTEWORTHY The glutamate transporter SLC1A2/excitatory amino acid transporter 2 (EAAT2) is expressed on the plasma membrane of pancreatic β-cells and controls islet glutamate clearance and β-cells survival. We found that the EAAT2 membrane expression is lost in the islets of Langerhans from type 2 diabetes mellitus (T2DM) patients due to hyperglycemia-induced downregulation of the phosphoinositide 3-kinase/Akt pathway and modification of its intracellular trafficking. Pharmacological rescue of EAAT2 expression prevents β-cell dysfunction and death, suggesting EAAT2 as a new potential target of intervention in T2DM.

Association between Childhood Overweight and Altered Concentrations of Circulating Amino Acids

(1) Background: Dysregulated serum amino acids (AA) are known to be associated with obesity and risk of Type 2 Diabetes (T2D) in adults, and recent studies support the same notion in the pubertal age. It is, however, unknown whether childhood overweight may already display alterations of circulating AA. (2) Methods: We used liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS)-targeted metabolomics to determine plasma concentrations of AA and AA-related molecules in 36 children aged 7-12 years with normal weight or overweight. Clinical and anthropometric parameters were measured. (3) Results: Overweight in children is associated with an altered AA profile, with increased branched-chain amino acids (BCAA) and decreased glycine levels, with no clinically manifested metabolic conditions. Moreover, z-BMI was positively and negatively correlated with BCAA and glycine levels, respectively, even after adjustment for age and gender. We also found a correlation between the AA profile and clinical parameters such as lipids profile and glycemia. (4) Conclusions: A pattern of low glycine, and increased BCAA is correlated to z-BMI, total cholesterol, and triglycerides in overweight but otherwise healthy children. Our data suggest that, in childhood overweight, AA disturbances may precede other clinical parameters, thus providing an early indicator for the later development of metabolic disease.

High glutamine increases stroke risk by inducing the endothelial-to-mesenchymal transition in moyamoya disease

At present, there is limited research on the mechanisms underlying moyamoya disease (MMD). Herein, we aimed to determine the role of glutamine in MMD pathogenesis, and 360 adult patients were prospectively enrolled. Human brain microvascular endothelial cells (HBMECs) were subjected to Integrin Subunit Beta 4 (ITGB4) overexpression or knockdown and atorvastatin. We assessed factors associated with various signaling pathways in the context of the endothelial-to-mesenchymal transition (EndMT), and the expression level of related proteins was validated in the superficial temporal arteries of patients. We found glutamine levels were positively associated with a greater risk of stroke (OR = 1.599, p = 0.022). After treatment with glutamine, HBMECs exhibited enhanced proliferation, migration, and EndMT, all reversed by ITGB4 knockdown. In ITGB4-transfected HBMECs, the MAPK-ERK-TGF-β/BMP pathway was activated, with Smad4 knockdown reversing the EndMT. Furthermore, atorvastatin suppressed the EndMT by inhibiting Smad1/5 phosphorylation and promoting Smad4 ubiquitination in ITGB4-transfected HBMECs. We also found the protein level of ITGB4 was upregulated in the superficial temporal arteries of patients with MMD. In conclusion, our study suggests that glutamine may be an independent risk factor for hemorrhage or infarction in patients with MMD and targeting ITGB4 could potentially be therapeutic approaches for MMD.

Excitatory amino acid transporter supports inflammatory macrophage responses

Excitatory amino acid transporters (EAATs) are responsible for excitatory amino acid transportation and are associated with auto-immune diseases in the central nervous system and peripheral tissues. However, the subcellular location and function of EAAT2 in macrophages are still obscure. In this study, we demonstrated that LPS stimulation increases expression of EAAT2 (coded by Slc1a2) via NF-κB signaling. EAAT2 is necessary for inflammatory macrophage polarization through sustaining mTORC1 activation. Mechanistically, lysosomal EAAT2 mediates lysosomal glutamate and aspartate efflux to maintain V-ATPase activation, which sustains macropinocytosis and mTORC1. We also found that mice with myeloid depletion of Slc1a2 show alleviated inflammatory responses in LPS-induced systemic inflammation and high-fat diet induced obesity. Notably, patients with type II diabetes (T2D) have a higher level of expression of lysosomal EAAT2 and activation of mTORC1 in blood macrophages. Taken together, our study links the subcellular location of amino acid transporters with the fate decision of immune cells, which provides potential therapeutic targets for the treatment of inflammatory diseases.

Acute venous thromboembolism plasma and red blood cell metabolomic profiling reveals potential new early diagnostic biomarkers: observational clinical study

BACKGROUND

Venous thromboembolism (VTE) is a leading cause of cardiovascular mortality. The diagnosis of acute VTE is based on complex imaging exams due to the lack of biomarkers. Recent multi-omics based research has contributed to the development of novel biomarkers in cardiovascular diseases. Our aim was to determine whether patients with acute VTE have differences in the metabolomic profile compared to non-acute VTE.

METHODS

This observational trial included 62 patients with clinical suspicion of acute deep vein thrombosis or pulmonary embolism, admitted to the emergency room. There were 50 patients diagnosed with acute VTE and 12 with non-acute VTE conditions and no significant differences were found between the two groups for clinical and demographic characteristics. Metabolomics assays identified and quantified a final number of 91 metabolites in plasma and 55 metabolites in red blood cells (RBCs). Plasma from acute VTE patients expressed tendency to a specific metabolomic signature, with univariate analyses revealing 23 significantly different molecules between acute VTE patients and controls (p < 0.05). The most relevant metabolic pathway with the strongest impact on the acute VTE phenotype was D-glutamine and D-glutamate (p = 0.001, false discovery rate = 0.06). RBCs revealed a specific metabolomic signature in patients with a confirmed diagnosis of DVT or PE that distinguished them from other acutely diseased patients, represented by 20 significantly higher metabolites and four lower metabolites. Three of those metabolites revealed high performant ROC curves, including adenosine 3',5'-diphosphate (AUC 0.983), glutathione (AUC 0.923), and adenine (AUC 0.91). Overall, the metabolic pathway most impacting to the differences observed in the RBCs was the purine metabolism (p = 0.000354, false discovery rate = 0.68).

CONCLUSIONS

Our findings show that metabolite differences exist between acute VTE and nonacute VTE patients admitted to the ER in the early phases. Three potential biomarkers obtained from RBCs showed high performance for acute VTE diagnosis. Further studies should investigate accessible laboratory methods for the future daily practice usefulness of these metabolites for the early diagnosis of acute VTE in the ER.

Plasma metabolite predictors of metabolic syndrome incidence and reversion

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Alterations of the glutamatergic system in diabetes mellitus

Diabetes mellitus (DM) is a chronic disease characterized by elevated blood glucose levels caused by a lack of insulin production (type 1 diabetes) or insulin resistance (type 2 diabetes). It is well known that DM is associated with cognitive deficits and metabolic and neurophysiological changes in the brain. Glutamate is the main excitatory neurotransmitter in the central nervous system that plays a key role in synaptic plasticity, learning, and memory processes. An increasing number of studies have suggested that abnormal activity of the glutamatergic system is implicated in the pathophysiology of DM. Dysfunction of glutamatergic neurotransmission in the central nervous system can provide an important neurobiological substrate for many disorders. Magnetic resonance spectroscopy (MRS) is a non-invasive technique that allows a better understanding of the central nervous system factors by measuring in vivo the concentrations of brain metabolites within the area of interest. Here, we briefly review the MRS studies that have examined glutamate levels in the brain of patients with DM. The present article also summarizes the available data on abnormalities in glutamatergic neurotransmission observed in different animal models of DM. In addition, the role of gut microbiota in the development of glutamatergic alterations in DM is addressed. We speculate that therapeutic strategies targeting the glutamatergic system may be beneficial in the treatment of central nervous system-related changes in diabetic patients.

Dietary Glutamine and Glutamate in Relation to Cardiovascular Disease Incidence and Mortality in the United States Men and Women with Diabetes Mellitus

BACKGROUND

Evidence regarding the potential health effects of dietary amino acids glutamine and glutamate among individuals with type 2 diabetes (T2D) is limited.

OBJECTIVES

The aim was to examine dietary glutamine and glutamate in relation to subsequent risk of cardiovascular disease (CVD) and mortality among individuals with T2D.

METHODS

We prospectively followed 15,040 men and women with T2D at baseline or diagnosed during follow-up (Nurses' Health Study: 1980-2014 and Health Professionals Follow-Up Study: 1986-2018). Diet was repeatedly assessed using validated food frequency questionnaires every 2-4 y. Associations of energy-adjusted glutamine and glutamate intake, as well as their ratio, with CVD risk and mortality, were assessed using Cox proportional-hazards models with adjustments for demographics, dietary and lifestyle factors, and medical history.

RESULTS

During 196,955 and 225,371 person-years of follow-up in participants with T2D, there were 2927 incident CVD cases and 4898 deaths, respectively. Higher intake of glutamine was associated with lower risk of CVD incidence, CVD mortality, and total mortality: comparing extreme quintiles, the hazard ratios (HRs) (95% confidence intervals [CIs]) were 0.88 (0.77, 0.99), 0.78 (0.65, 0.92), and 0.84 (0.76, 0.92), respectively (all P-trend < 0.05). In contrast, higher intake of glutamate was associated with a higher risk of CVD incidence, CVD mortality, and total mortality; the HRs were 1.30 (1.15, 1.46), 1.46 (1.24, 1.72), and 1.20 (1.09, 1.32), respectively (all P-trend < 0.05). Furthermore, comparing extreme quintiles, a higher dietary glutamine-to-glutamate ratio was associated with a lower risk of CVD incidence (0.84 [0.75, 0.95]), CVD mortality (0.66 [0.57, 0.77]), and total mortality (0.82 [0.75, 0.90]). In addition, compared with participants with stable or decreased consumption of glutamine-to-glutamate ratio from prediabetes to postdiabetes diagnosis, those who increased the ratio had a 17% (5%, 27%) lower CVD mortality.

CONCLUSIONS

In adults with T2D, dietary glutamine was associated with a lower risk of CVD incidence and mortality, whereas the opposite was observed for glutamate intake.

Impact of individual and environmental factors on dietary or lifestyle interventions to prevent type 2 diabetes development: a systematic review

BACKGROUND

The variability in the effectiveness of type 2 diabetes (T2D) preventive interventions highlights the potential to identify the factors that determine treatment responses and those that would benefit the most from a given intervention. We conducted a systematic review to synthesize the evidence to support whether sociodemographic, clinical, behavioral, and molecular factors modify the efficacy of dietary or lifestyle interventions to prevent T2D.

METHODS

We searched MEDLINE, Embase, and Cochrane databases for studies reporting on the effect of a lifestyle, dietary pattern, or dietary supplement interventions on the incidence of T2D and reporting the results stratified by any effect modifier. We extracted relevant statistical findings and qualitatively synthesized the evidence for each modifier based on the direction of findings reported in available studies. We used the Diabetes Canada Clinical Practice Scale to assess the certainty of the evidence for a given effect modifier.

RESULTS

The 81 publications that met our criteria for inclusion are from 33 unique trials. The evidence is low to very low to attribute variability in intervention effectiveness to individual characteristics such as age, sex, BMI, race/ethnicity, socioeconomic status, baseline behavioral factors, or genetic predisposition.

CONCLUSIONS

We report evidence, albeit low certainty, that those with poorer health status, particularly those with prediabetes at baseline, tend to benefit more from T2D prevention strategies compared to healthier counterparts. Our synthesis highlights the need for purposefully designed clinical trials to inform whether individual factors influence the success of T2D prevention strategies.

Metabolic profile of blood serum in experimental arterial hypertension

The etiology of essential hypertension is intricate, since it employs simultaneously various body systems related to the regulation of blood pressure in one way or another: the sympathetic nervous system, renin-angiotensin-aldosterone and hypothalamic-pituitary-adrenal systems, renal and endothelial mechanisms. The pathogenesis of hypertension is influenced by a variety of both genetic and environmental factors, which determines the heterogeneity of the disease in human population. Hence, there is a need to perform research on experimental models - inbred animal strains, one of them being ISIAH rat strain, which is designed to simulate inherited stress-induced arterial hypertension as close as possible to primary (or essential) hypertension in humans. To determine specific markers of diseases, various omics technologies are applied, including metabolomics, which makes it possible to evaluate the content of low-molecular compounds - amino acids, lipids, carbohydrates, nucleic acids fragments - in biological samples available for clinical analysis (blood and urine). We analyzed the metabolic profile of the blood serum of male ISIAH rats with a genetic stress-dependent form of arterial hypertension in comparison with the normotensive WAG rats. Using the method of nuclear magnetic resonance spectroscopy (NMR spectroscopy), 56 metabolites in blood serum samples were identified, 18 of which were shown to have significant interstrain differences in serum concentrations. Statistical analysis of the data obtained showed that the hypertensive status of ISIAH rats is characterized by increased concentrations of leucine, isoleucine, valine, myo-inositol, isobutyrate, glutamate, glutamine, ornithine and creatine phosphate, and reduced concentrations of 2-hydroxyisobutyrate, betaine, tyrosine and tryptophan. Such a ratio of the metabolite concentrations is associated with changes in the regulation of glucose metabolism (metabolic markers - leucine, isoleucine, valine, myo-inositol), of nitric oxide synthesis (ornithine) and catecholamine pathway (tyrosine), and with inflammatory processes (metabolic markers - betaine, tryptophan), all of these changes being typical for hypertensive status. Thus, metabolic profiling of the stress-dependent form of arterial hypertension seems to be an important result for a personalized approach to the prevention and treatment of hypertensive disease.

The plasma metabolome of long COVID patients two years after infection

One of the major challenges currently faced by global health systems is the prolonged COVID-19 syndrome (also known as "long COVID") which has emerged as a consequence of the SARS-CoV-2 epidemic. It is estimated that at least 30% of patients who have had COVID-19 will develop long COVID. In this study, our goal was to assess the plasma metabolome in a total of 100 samples collected from healthy controls, COVID-19 patients, and long COVID patients recruited in Mexico between 2020 and 2022. A targeted metabolomics approach using a combination of LC-MS/MS and FIA MS/MS was performed to quantify 108 metabolites. IL-17 and leptin were measured in long COVID patients by immunoenzymatic assay. The comparison of paired COVID-19/long COVID-19 samples revealed 53 metabolites that were statistically different. Compared to controls, 27 metabolites remained dysregulated even after two years. Post-COVID-19 patients displayed a heterogeneous metabolic profile. Lactic acid, lactate/pyruvate ratio, ornithine/citrulline ratio, and arginine were identified as the most relevant metabolites for distinguishing patients with more complicated long COVID evolution. Additionally, IL-17 levels were significantly increased in these patients. Mitochondrial dysfunction, redox state imbalance, impaired energy metabolism, and chronic immune dysregulation are likely to be the main hallmarks of long COVID even two years after acute COVID-19 infection.

Pharmacometabolomic Approach to Investigate the Response to Metformin in Patients with Type 2 Diabetes: A Cross-Sectional Study

Metformin constitutes the foundation therapy in type 2 diabetes (T2D). Despite its multiple beneficial effects and widespread use, there is considerable inter-individual variability in response to metformin. Our objective is to identify metabolic signatures associated with poor and good responses to metformin, which may improve our ability to predict outcomes for metformin treatment. In this cross-sectional study, clinical and metabolic data for 119 patients with type 2 diabetes taking metformin were collected from the Qatar Biobank. Patients were empirically dichotomized according to their HbA1C levels into good and poor responders. Differences in the level of metabolites between these two groups were compared using orthogonal partial least square discriminate analysis (OPLS-DA) and linear models. Good responders showed increased levels of sphingomyelins, acylcholines, and glutathione metabolites. On the other hand, poor responders showed increased levels of metabolites resulting from glucose metabolism and gut microbiota metabolites. The results of this study have the potential to increase our knowledge of patient response variability to metformin and carry significant implications for enabling personalized medicine.

Time-to-Event Genome-Wide Association Study for Incident Cardiovascular Disease in People with Type 2 Diabetes Mellitus

BACKGROUND

Type 2 diabetes mellitus (T2D) confers a two- to three-fold increased risk of cardiovascular disease (CVD). However, the mechanisms underlying increased CVD risk among people with T2D are only partially understood. We hypothesized that a genetic association study among people with T2D at risk for developing incident cardiovascular complications could provide insights into molecular genetic aspects underlying CVD.

METHODS

From 16 studies of the Cohorts for Heart & Aging Research in Genomic Epidemiology (CHARGE) Consortium, we conducted a multi-ancestry time-to-event genome-wide association study (GWAS) for incident CVD among people with T2D using Cox proportional hazards models. Incident CVD was defined based on a composite of coronary artery disease (CAD), stroke, and cardiovascular death that occurred at least one year after the diagnosis of T2D. Cohort-level estimated effect sizes were combined using inverse variance weighted fixed effects meta-analysis. We also tested 204 known CAD variants for association with incident CVD among patients with T2D.

RESULTS

A total of 49,230 participants with T2D were included in the analyses (31,118 European ancestries and 18,112 non-European ancestries) which consisted of 8,956 incident CVD cases over a range of mean follow-up duration between 3.2 and 33.7 years (event rate 18.2%). We identified three novel, distinct genetic loci for incident CVD among individuals with T2D that reached the threshold for genome-wide significance (P<5.0×10-8): rs147138607 (intergenic variant between CACNA1E and ZNF648) with a hazard ratio (HR) 1.23, 95% confidence interval (CI) 1.15 - 1.32, P=3.6×10-9, rs11444867 (intergenic variant near HS3ST1) with HR 1.89, 95% CI 1.52 - 2.35, P=9.9×10-9, and rs335407 (intergenic variant between TFB1M and NOX3) HR 1.25, 95% CI 1.16 - 1.35, P=1.5×10-8. Among 204 known CAD loci, 32 were associated with incident CVD in people with T2D with P<0.05, and 5 were significant after Bonferroni correction (P<0.00024, 0.05/204). A polygenic score of these 204 variants was significantly associated with incident CVD with HR 1.14 (95% CI 1.12 - 1.16) per 1 standard deviation increase (P=1.0×10-16).

CONCLUSIONS

The data point to novel and known genomic regions associated with incident CVD among individuals with T2D.

Integrative Plasma Metabolic and Lipidomic Modelling of SARS-CoV-2 Infection in Relation to Clinical Severity and Early Mortality Prediction

An integrative multi-modal metabolic phenotyping model was developed to assess the systemic plasma sequelae of SARS-CoV-2 (rRT-PCR positive) induced COVID-19 disease in patients with different respiratory severity levels. Plasma samples from 306 unvaccinated COVID-19 patients were collected in 2020 and classified into four levels of severity ranging from mild symptoms to severe ventilated cases. These samples were investigated using a combination of quantitative Nuclear Magnetic Resonance (NMR) spectroscopy and Mass Spectrometry (MS) platforms to give broad lipoprotein, lipidomic and amino acid, tryptophan-kynurenine pathway, and biogenic amine pathway coverage. All platforms revealed highly significant differences in metabolite patterns between patients and controls (n = 89) that had been collected prior to the COVID-19 pandemic. The total number of significant metabolites increased with severity with 344 out of the 1034 quantitative variables being common to all severity classes. Metabolic signatures showed a continuum of changes across the respiratory severity levels with the most significant and extensive changes being in the most severely affected patients. Even mildly affected respiratory patients showed multiple highly significant abnormal biochemical signatures reflecting serious metabolic deficiencies of the type observed in Post-acute COVID-19 syndrome patients. The most severe respiratory patients had a high mortality (56.1%) and we found that we could predict mortality in this patient sub-group with high accuracy in some cases up to 61 days prior to death, based on a separate metabolic model, which highlighted a different set of metabolites to those defining the basic disease. Specifically, hexosylceramides (HCER 16:0, HCER 20:0, HCER 24:1, HCER 26:0, HCER 26:1) were markedly elevated in the non-surviving patient group (Cliff's delta 0.91-0.95) and two phosphoethanolamines (PE.O 18:0/18:1, Cliff's delta = -0.98 and PE.P 16:0/18:1, Cliff's delta = -0.93) were markedly lower in the non-survivors. These results indicate that patient morbidity to mortality trajectories is determined relatively soon after infection, opening the opportunity to select more intensive therapeutic interventions to these "high risk" patients in the early disease stages.

Influence of glutamatergic and GABAergic neurotransmission on obstructive sleep apnea

Glutamate and γ-aminobutyric acid (GABA) are the two main neurotransmitters in the human brain. The balance between their excitatory and inhibitory functions is crucial for maintaining the brain's physiological functions. Disturbance of glutamatergic or GABAergic neurotransmission leads to serious health problems including neurodegeneration, affective and sleep disorders. Both GABA and glutamate are involved in the control of the sleep-wake cycle. The disturbances in their function may cause sleep and sleep-related disorders. Obstructive sleep apnea (OSA) is the most common sleep respiratory disorder and is characterized by repetitive collapse of the upper airway resulting in intermittent hypoxia and sleep fragmentation. The complex pathophysiology of OSA is the basis of the development of numerous comorbid diseases. There is emerging evidence that GABA and glutamate disturbances may be involved in the pathogenesis of OSA, as well as its comorbidities. Additionally, the GABA/glutamate targeted pharmacotherapy may also influence the course of OSA, which is important in the implementation of wildly used drugs including benzodiazepines, anesthetics, and gabapentinoids. In this review, we summarize current knowledge on the influence of disturbances in glutamatergic and GABAergic neurotransmission on obstructive sleep apnea.

Dose-dependent effects of xylooligosaccharides on glycemic regulation with L. rhamnosus CCFM1060 in diabetic mice

Dietary intervention with the probiotic Lactobacillus rhamnosus CCFM1060 has been proved to be effective on glycemic regulation in diabetic mice. Therefore characterization of the potential symbiotic effect of prebiotic xylooligosaccharides (XOS) with L. rhamnosus CCFM1060 would be desirable. In this study, we evaluated any dose-dependent relationship between XOS and L. rhamnosus CCFM1060, and the potential impact on glycemic regulation. Diabetic mice were randomly assigned to receive 5 × 10⁹ CFU mL^-1L. rhamnosus CCFM1060, 5 × 10⁹ CFU mL^-1L. rhamnosus CCFM1060 with 250 mg kg^-1 XOS (L-LXOS), or 5 × 10⁹ CFU mL^-1L. rhamnosus CCFM1060 with 500 mg kg^-1 XOS (L-HXOS) for 7 weeks. In addition to characterization of the host metabolism, the intestinal microbiota were analyzed using 16S rRNA gene sequencing. The results showed that L. rhamnosus alone and L-LXOS intervention significantly alleviated diabetes symptoms and increased the populations of short-chain fatty acid (SCFA)-producing bacteria. The intake of L-HXOS had an adverse effect on glucose metabolism, causing increased insulin resistance and inflammation. Although a significant increase in the relative abundance of Bifidobacterium was observed in the L-HXOS group, the abundance of SCFA-producing bacteria, such as Romboutsia and Clostrudium sensu stricto 1, decreased. KEGG pathway analysis revealed that the adverse effects of L-HXOS intervention might be attributed to the metabolic pathways involved in amino acid, cofactor, and vitamin metabolism. This study revealed that L. rhamnosus CCFM1060 combined with different doses of XOS exerted dose-dependent effects on glucose metabolism. Therefore, the type and dose of prebiotics should be carefully evaluated when developing individualized symbiotic formula.

Role of sociodemographic, clinical, behavioral, and molecular factors in precision prevention of type 2 diabetes: a systematic review

The variability in the effectiveness of type 2 diabetes (T2D) preventive interventions highlights the potential to identify the factors that determine treatment responses and those that would benefit the most from a given intervention. We conducted a systematic review to synthesize the evidence to support whether sociodemographic, clinical, behavioral, and molecular characteristics modify the efficacy of dietary or lifestyle interventions to prevent T2D. Among the 80 publications that met our criteria for inclusion, the evidence was low to very low to attribute variability in intervention effectiveness to individual characteristics such as age, sex, BMI, race/ethnicity, socioeconomic status, baseline behavioral factors, or genetic predisposition. We found evidence, albeit low certainty, to support conclusions that those with poorer health status, particularly those with prediabetes at baseline, tend to benefit more from T2D prevention strategies compared to healthier counterparts. Our synthesis highlights the need for purposefully designed clinical trials to inform whether individual factors influence the success of T2D prevention strategies.

The number of metabolic syndrome risk factors predicts alterations in gut microbiota in Chinese children from the Huantai study

BACKGROUND

Evidence on the effect of gut microbiota on the number of metabolic syndrome (MetS) risk factors among children is scarce. We aimed to examine the alterations of gut microbiota with different numbers of MetS risk factors among children.

METHODS

Data were collected from a nested case-control study at the baseline of the Huantai Childhood Cardiovascular Health Cohort Study in Zibo, China. We compared the differences in gut microbiota based on 16S rRNA gene sequencing among 72 children with different numbers of MetS risk factors matched by age and sex (i.e., none, one, and two-or-more MetS risk factors; 24 children for each group).

RESULTS

The community richness (i.e., the total number of species in the community) and diversity (i.e., the richness and evenness of species in the community) of gut microbiota decreased with an increased number of MetS risk factors in children (P for trend < 0.05). Among genera with a relative abundance greater than 0.01%, the relative abundance of Lachnoclostridium (P_FDR = 0.009) increased in the MetS risk groups, whereas Alistipes (P_FDR < 0.001) and Lachnospiraceae_NK4A136_group (P_FDR = 0.043) decreased in the MetS risk groups compared to the non-risk group. The genus Christensenellaceae_R-7_group excelled at distinguishing one and two-or-more risk groups from the non-risk group (area under the ROC curve [AUC]: 0.84 - 0.92), while the genera Family_XIII_AD3011_group (AUC: 0.73 - 0.91) and Lachnoclostridium (AUC: 0.77 - 0.80) performed moderate abilities in identifying none, one, and two-or-more MetS risk factors in children.

CONCLUSIONS

Based on the nested case-control study and the 16S rRNA gene sequencing technology, we found that dysbiosis of gut microbiota, particularly for the genera Christensenellaceae_R-7_group, Family_XIII_AD3011_group, and Lachnoclostridium may contribute to the early detection and the accumulation of MetS risk factors in childhood.

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.

Plasma Amino Acids in Early Pregnancy and Midpregnancy and Their Interplay With Phospholipid Fatty Acids in Association With the Risk of Gestational Diabetes Mellitus: Results From a Longitudinal Prospective Cohort

OBJECTIVE

We prospectively evaluated plasma amino acids (AAs) in early pregnancy and midpregnancy and their interplay with phospholipid fatty acids (FAs) in association with gestational diabetes mellitus (GDM) risk.

RESEARCH DESIGN AND METHODS

From a longitudinal pregnancy cohort of 2,802 individuals, concentrations of 24 plasma AAs at 10-14 and 15-26 gestational weeks (GW) were assessed among 107 GDM case subjects and 214 non-GDM control subjects. We estimated adjusted odds ratios (OR) and 95% CI for the associations of plasma AAs and the joint associations of plasma AAs and phospholipid FAs with GDM risk, adjusting for risk factors including age, prepregnancy BMI, and family history of diabetes.

RESULTS

Glycine at 10-14 GW was inversely associated with GDM (adjusted OR [95% CI] per SD increment: 0.55 [0.39-0.79]). Alanine, aspartic acid, and glutamic acid at 10-14 GW were positively associated with GDM (1.43 [1.08-1.88], 1.41 [1.11-1.80], and 1.39 [0.98-1.98]). At 15-26 GW, findings for glycine, alanine, aspartic acid, and the glutamine-to-glutamic acid ratio were consistent with the directions observed at 10-14 GW. Isoleucine, phenylalanine, and tyrosine were positively associated with GDM (1.64 [1.19-2.27], 1.15 [0.87-1.53], and 1.56 [1.16-2.09]). All P values for linear trend were <0.05. Several AAs and phospholipid FAs were significantly and jointly associated with GDM. For instance, the lowest risk was observed among women with higher glycine and lower even-chain saturated FAs at 10-14 GW (adjusted OR [95% CI] 0.15 [0.06, 0.37]).

CONCLUSIONS

Plasma AAs may be implicated in GDM development starting in early pregnancy. Associations of AAs with GDM may be enhanced in the copresence of phospholipid FA profile.

Circulating amino acid levels and colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition and UK Biobank cohorts

BACKGROUND

Amino acid metabolism is dysregulated in colorectal cancer patients; however, it is not clear whether pre-diagnostic levels of amino acids are associated with subsequent risk of colorectal cancer. We investigated circulating levels of amino acids in relation to colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition (EPIC) and UK Biobank cohorts.

METHODS

Concentrations of 13-21 amino acids were determined in baseline fasting plasma or serum samples in 654 incident colorectal cancer cases and 654 matched controls in EPIC. Amino acids associated with colorectal cancer risk following adjustment for the false discovery rate (FDR) were then tested for associations in the UK Biobank, for which measurements of 9 amino acids were available in 111,323 participants, of which 1221 were incident colorectal cancer cases.

RESULTS

Histidine levels were inversely associated with colorectal cancer risk in EPIC (odds ratio [OR] 0.80 per standard deviation [SD], 95% confidence interval [CI] 0.69-0.92, FDR P-value=0.03) and in UK Biobank (HR 0.93 per SD, 95% CI 0.87-0.99, P-value=0.03). Glutamine levels were borderline inversely associated with colorectal cancer risk in EPIC (OR 0.85 per SD, 95% CI 0.75-0.97, FDR P-value=0.08) and similarly in UK Biobank (HR 0.95, 95% CI 0.89-1.01, P=0.09) In both cohorts, associations changed only minimally when cases diagnosed within 2 or 5 years of follow-up were excluded.

CONCLUSIONS

Higher circulating levels of histidine were associated with a lower risk of colorectal cancer in two large prospective cohorts. Further research to ascertain the role of histidine metabolism and potentially that of glutamine in colorectal cancer development is warranted.

Dietary metabolic signatures and cardiometabolic risk

AIMS

Observational studies of diet in cardiometabolic-cardiovascular disease (CM-CVD) focus on self-reported consumption of food or dietary pattern, with limited information on individual metabolic responses to dietary intake linked to CM-CVD. Here, machine learning approaches were used to identify individual metabolic patterns related to diet and relation to long-term CM-CVD in early adulthood.

METHODS AND RESULTS

In 2259 White and Black adults (age 32.1 ± 3.6 years, 45% women, 44% Black) in the Coronary Artery Risk Development in Young Adults (CARDIA) study, multivariate models were employed to identify metabolite signatures of food group and composite dietary intake across 17 food groups, 2 nutrient groups, and healthy eating index-2015 (HEI2015) diet quality score. A broad array of metabolites associated with diet were uncovered, reflecting food-related components/catabolites (e.g. fish and long-chain unsaturated triacylglycerols), interactions with host features (microbiome), or pathways broadly implicated in CM-CVD (e.g. ceramide/sphingomyelin lipid metabolism). To integrate diet with metabolism, penalized machine learning models were used to define a metabolite signature linked to a putative CM-CVD-adverse diet (e.g. high in red/processed meat, refined grains), which was subsequently associated with long-term diabetes and CVD risk numerically more strongly than HEI2015 in CARDIA [e.g. diabetes: standardized hazard ratio (HR): 1.62, 95% confidence interval (CI): 1.32-1.97, P < 0.0001; CVD: HR: 1.55, 95% CI: 1.12-2.14, P = 0.008], with associations replicated for diabetes (P < 0.0001) in the Framingham Heart Study.

CONCLUSION

Metabolic signatures of diet are associated with long-term CM-CVD independent of lifestyle and traditional risk factors. Metabolomics improves precision to identify adverse consequences and pathways of diet-related CM-CVD.

Identification of Biomarkers Related to Metabolically Unhealthy Obesity in Korean Obese Adolescents: A Cross-Sectional Study

BACKGROUND

The current study aimed to screen for relationships and different potential metabolic biomarkers involved between metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO) in adolescents.

METHODS

The study included 148 obese adolescents aged between 14 and 16. The study participants were divided into MUO and MHO groups based on the age-specific adolescent metabolic syndrome (MetS) criteria of the International Diabetes Federation. The current study was conducted to investigate the clinical and metabolic differences between the MHO and MUO groups. Multivariate analyses were conducted to investigate the metabolites as independent predictors for the odds ratio and the presence of the MetS.

RESULTS

There were significant differences in the three acylcarnitines, five amino acids, glutamine/glutamate ratio, three biogenic amines, two glycerophospholipids, and the triglyceride-glucose index between the MUO group and those in the MHO group. Moreover, several metabolites were associated with the prevalence of MUO. Additionally, several metabolites were inversely correlated with MHO in the MUO group.

CONCLUSIONS

In this study, the biomarkers found in this study have the potential to reflect the clinical outcomes of the MUO group. These biomarkers will lead to a better understanding of MetS in obese adolescents.

Metabolic perspective of astrocyte dysfunction in Alzheimer's disease and type 2 diabetes brains

The term type III diabetes (T3DM) has been proposed for Alzheimer's disease (AD) due to the shared molecular and cellular features between type 2 diabetes (T2DM) and insulin resistance-associated memory deficits and cognitive decline in elderly individuals. Astrocytes elicit neuroprotective or deleterious effects in AD progression and severity. Patients with T2DM are at a high risk of cognitive impairment, and targeting astrocytes might be promising in alleviating neurodegeneration in the diabetic brain. Recent studies focusing on cell-specific activities in the brain have revealed the important role of astrocytes in brain metabolism (e.g., glucose metabolism, lipid metabolism), neurovascular coupling, synapses, and synaptic plasticity. In this review, we discuss how astrocytes and their dysfunction result in multiple pathological and clinical features of AD and T2DM from a metabolic perspective and the potential comorbid mechanism in these two diseases from the perspective of astrocytes.

Development and validation of a metabolite index for obstructive sleep apnea across race/ethnicities

Obstructive sleep apnea (OSA) is a common disorder characterized by recurrent episodes of upper airway obstruction during sleep resulting in oxygen desaturation and sleep fragmentation, and associated with increased risk of adverse health outcomes. Metabolites are being increasingly used for biomarker discovery and evaluation of disease processes and progression. Studying metabolomic associations with OSA in a diverse community-based cohort may provide insights into the pathophysiology of OSA. We aimed to develop and replicate a metabolite index for OSA and identify individual metabolites associated with OSA. We studied 219 metabolites and their associations with the apnea hypopnea index (AHI) and with moderate-severe OSA (AHI ≥ 15) in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) (n = 3507) using two methods: (1) association analysis of individual metabolites, and (2) least absolute shrinkage and selection operator (LASSO) regression to identify a subset of metabolites jointly associated with OSA, which was used to develop a metabolite index for OSA. Results were validated in the Multi-Ethnic Study of Atherosclerosis (MESA) (n = 475). When assessing the associations with individual metabolites, we identified seven metabolites significantly positively associated with OSA in HCHS/SOL (FDR p < 0.05), of which four associations-glutamate, oleoyl-linoleoyl-glycerol (18:1/18:2), linoleoyl-linoleoyl-glycerol (18:2/18:2) and phenylalanine, were replicated in MESA (one sided-p < 0.05). The OSA metabolite index, composed of 14 metabolites, was associated with a 50% increased risk for moderate-severe OSA (OR = 1.50 [95% CI 1.21-1.85] per 1 SD of OSA metabolite index, p < 0.001) in HCHS/SOL and 55% increased risk (OR = 1.55 [95% CI 1.10-2.20] per 1 SD of OSA metabolite index, p = 0.013) in MESA, both adjusted for demographics, lifestyle, and comorbidities. Similar albeit less significant associations were observed for AHI. Replication of the metabolite index in an independent multi-ethnic dataset demonstrates the robustness of metabolomic-based OSA index to population heterogeneity. Replicated metabolite associations may provide insights into OSA-related molecular and metabolic mechanisms.

Response of circulating metabolites to an oral glucose challenge and risk of cardiovascular disease and mortality in the community

Background

New biomarkers to identify cardiovascular disease (CVD) risk earlier in its course are needed to enable targeted approaches for primordial prevention. We evaluated whether intraindividual changes in blood metabolites in response to an oral glucose tolerance test (OGTT) may provide incremental information regarding the risk of future CVD and mortality in the community.

Methods

An OGTT (75 g glucose) was administered to a subsample of Framingham Heart Study participants free from diabetes (n = 361). Profiling of 211 plasma metabolites was performed from blood samples drawn before and 2 h after OGTT. The log2(post/pre) metabolite levels (Δmetabolites) were related to incident CVD and mortality in Cox regression models adjusted for age, sex, baseline metabolite level, systolic blood pressure, hypertension treatment, body mass index, smoking, and total/high-density lipoprotein cholesterol. Select metabolites were related to subclinical cardiometabolic phenotypes using Spearman correlations adjusted for age, sex, and fasting metabolite level.

Results

Our sample included 42% women, with a mean age of 56 ± 9 years and a body mass index of 30.2 ± 5.3 kg/m². The pre- to post-OGTT changes (Δmetabolite) were non-zero for 168 metabolites (at FDR ≤ 5%). A total of 132 CVD events and 144 deaths occurred during median follow-up of 24.9 years. In Cox models adjusted for clinical risk factors, four Δmetabolites were associated with incident CVD (higher glutamate and deoxycholate, lower inosine and lysophosphatidylcholine 18:2) and six Δmetabolites (higher hydroxyphenylacetate, triacylglycerol 56:5, alpha-ketogluturate, and lower phosphatidylcholine 32:0, glucuronate, N-monomethyl-arginine) were associated with death (P < 0.05). Notably, baseline metabolite levels were not associated with either outcome in models excluding Δmetabolites. The Δmetabolites exhibited varying cross-sectional correlation with subclinical risk factors such as visceral adiposity, insulin resistance, and vascular stiffness, but overall relations were modest. Significant Δmetabolites included those with established roles in cardiometabolic disease (e.g., glutamate, alpha-ketoglutarate) and metabolites with less defined roles (e.g., glucuronate, lipid species).

Conclusions

Dynamic changes in metabolite levels with an OGTT are associated with incident CVD and mortality and have potential relevance for identifying CVD risk earlier in its development and for discovering new potential therapeutic targets.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-022-01647-w.

Association of COVID-19 with hepatic metabolic dysfunction

The coronavirus disease 2019 (COVID-19) pandemic continues to be a global problem with over 438 million cases reported so far. Although it mostly affects the respiratory system, the involvement of extrapulmonary organs, including the liver, is not uncommon. Since the beginning of the pandemic, metabolic com-orbidities, such as obesity, diabetes, hypertension, and dyslipidemia, have been identified as poor prognostic indicators. Subsequent metabolic and lipidomic studies have identified several metabolic dysfunctions in patients with COVID-19. The metabolic alterations appear to be linked to the course of the disease and inflammatory reaction in the body. The liver is an important organ with high metabolic activity, and a significant proportion of COVID-19 patients have metabolic comorbidities; thus, this factor could play a key role in orchestrating systemic metabolic changes during infection. Evidence suggests that metabolic dysregulation in COVID-19 has both short- and long-term metabolic implications. Furthermore, COVID-19 has adverse associations with metabolic-associated fatty liver disease. Due to the ensuing effects on the renin-angiotensin-aldosterone system and ammonia metabolism, COVID-19 can have significant implications in patients with advanced chronic liver disease. A thorough understanding of COVID-19-associated metabolic dysfunction could lead to the identification of important plasma biomarkers and novel treatment targets. In this review, we discuss the current understanding of metabolic dysfunction in COVID-19, focusing on the liver and exploring the underlying mechanistic pathogenesis and clinical implications.

Longitudinal Changes in Circulating Metabolites and Lipoproteins After Breast Cancer Treatment

The multimodal treatment of breast cancer may induce long term effects on the metabolic profile and increase the risk of future cardiovascular disease. In this study, we characterized longitudinal changes in serum lipoprotein subfractions and metabolites after breast cancer treatment, aiming to determine the long-term effect of different treatment modalities. Further, we investigated the prognostic value of treatment-induced changes in breast cancer-specific and overall 10-year survival. In this study, serum samples from breast cancer patients (n = 250) were collected repeatedly before and after radiotherapy, and serum metabolites and lipoprotein subfractions were quantified by NMR spectroscopy. Longitudinal changes were assessed by univariate and multivariate data analysis methods applicable for repeated measures. Distinct changes were detectable in levels of lipoprotein subfractions and circulating metabolites during the first year, with similar changes despite large differences in treatment regimens. We detect increased free cholesterol and decreased esterified cholesterol levels of HDL subfractions, a switch towards larger LDL particles and higher total LDL-cholesterol, in addition to a switch in the glutamine-glutamate ratio. Non-survivors had different lipid profiles from survivors already at baseline. To conclude, our results show development towards an atherogenic lipid profile in breast cancer patients with different treatment regimens.

Metabolomics and Type 2 Diabetes Risk: An Updated Systematic Review and Meta-analysis of Prospective Cohort Studies

BACKGROUND

Due to the rapidly increasing availability of metabolomics data in prospective studies, an update of the meta evidence on metabolomics and type 2 diabetes risk is warranted.

PURPOSE

To conduct an updated systematic review and meta-analysis of plasma, serum, and urine metabolite markers and incident type 2 diabetes.

DATA SOURCES

We searched PubMed and Embase until 6 March 2021.

STUDY SELECTION

We selected prospective observational studies where investigators used high-throughput techniques to investigate the relationship between plasma, serum, or urine metabolites and incident type 2 diabetes.

DATA EXTRACTION

Baseline metabolites per-SD risk estimates and 95% CIs for incident type 2 diabetes were extracted from all eligible studies.

DATA SYNTHESIS

A total of 61 reports with 71,196 participants and 11,771 type 2 diabetes cases/events were included in the updated review. Meta-analysis was performed for 412 metabolites, of which 123 were statistically significantly associated (false discovery rate-corrected P < 0.05) with type 2 diabetes risk. Higher plasma and serum levels of certain amino acids (branched-chain, aromatic, alanine, glutamate, lysine, and methionine), carbohydrates and energy-related metabolites (mannose, trehalose, and pyruvate), acylcarnitines (C4-DC, C4-OH, C5, C5-OH, and C8:1), the majority of glycerolipids (di- and triacylglycerols), (lyso)phosphatidylethanolamines, and ceramides included in meta-analysis were associated with higher risk of type 2 diabetes (hazard ratio 1.07-2.58). Higher levels of glycine, glutamine, betaine, indolepropionate, and (lyso)phosphatidylcholines were associated with lower type 2 diabetes risk (hazard ratio 0.69-0.90).

LIMITATIONS

Substantial heterogeneity (I2 > 50%, τ2 > 0.1) was observed for some of the metabolites.

CONCLUSIONS

Several plasma and serum metabolites, including amino acids, lipids, and carbohydrates, are associated with type 2 diabetes risk.

Circulating metabolite profile in young adulthood identifies long-term diabetes susceptibility: the Coronary Artery Risk Development in Young Adults (CARDIA) study

AIMS/HYPOTHESIS

The aim of this work was to define metabolic correlates and pathways of diabetes pathogenesis in young adults during a subclinical latent phase of diabetes development.

METHODS

We studied 2083 young adults of Black and White ethnicity in the prospective observational cohort Coronary Artery Risk Development in Young Adults (CARDIA) study (mean ± SD age 32.1 ± 3.6 years; 43.9% women; 42.7% Black; mean ± SD BMI 25.6 ± 4.9 kg/m2) and 1797 Framingham Heart Study (FHS) participants (mean ± SD age 54.7 ± 9.7 years; 52.1% women; mean ± SD BMI 27.4 ± 4.8 kg/m2), examining the association of comprehensive metabolite profiles with endophenotypes of diabetes susceptibility (adipose and muscle tissue phenotypes and systemic inflammation). Statistical learning techniques and Cox regression were used to identify metabolite signatures of incident diabetes over a median of nearly two decades of follow-up across both cohorts.

RESULTS

We identified known and novel metabolites associated with endophenotypes that delineate the complex pathophysiological architecture of diabetes, spanning mechanisms of muscle insulin resistance, inflammatory lipid signalling and beta cell metabolism (e.g. bioactive lipids, amino acids and microbe- and diet-derived metabolites). Integrating endophenotypes of diabetes susceptibility with the metabolome generated two multi-parametric metabolite scores, one of which (a proinflammatory adiposity score) was associated with incident diabetes across the life course in participants from both the CARDIA study (young adults; HR in a fully adjusted model 2.10 [95% CI 1.72, 2.55], p<0.0001) and FHS (middle-aged and older adults; HR 1.33 [95% CI 1.14, 1.56], p=0.0004). A metabolite score based on the outcome of diabetes was strongly related to diabetes in CARDIA study participants (fully adjusted HR 3.41 [95% CI 2.85, 4.07], p<0.0001) but not in the older FHS population (HR 1.15 [95% CI 0.99, 1.33], p=0.07).

CONCLUSIONS/INTERPRETATION

Selected metabolic abnormalities in young adulthood identify individuals with heightened diabetes risk independent of race, sex and traditional diabetes risk factors. These signatures replicate across the life course.

AMPK-mediated glutaminolysis maintains coelomocytes redox homeostasis in Vibrio splendidus-challenged Apostichopus japonicus

Glutaminolysis has been proved to play an irreplaceable role in vertebrate immunity, including effects on cytokine production, bacterial killing, and redox homeostasis maintenance. Our previous metabolomics analysis indicated that glutaminolysis metabolic substrates glutamine (Gln) and metabolites glutamate (Glu) were significantly lower in Skin ulceration syndrome (SUS)-diseased Apostichopus japonicus. To further delineate the role of glutaminolysis, we assayed the levels of Gln and Glu. We found that their contents in coelomocytes were decreased, accompanied by an increase in glutathione (GSH) in pathogen-challenged Apostichopus japonicus. Consistently, the mRNA transcripts of three key genes in glutaminolysis (AjASCT2, AjGOT, and AjGCS) were significantly induced. Moreover, the increased MDA and NADPH/NADP ⁺ levels in response to pathogen infection indicated that oxidative stress occurs during the immune response. The metabolic regulator AMPKβ could regulate glutaminolysis in vertebrates by inducing cells to take up extracellular Gln. To explore the underlying regulatory mechanism behind glutaminolysis that occurred in coelomocytes, the full-length cDNA of AMPKβ was identified from A. japonicus (designated as AjAMPKβ). AjAMPKβ expression was significantly induced in the coelomocytes after pathogen challenge, which was consistent with the expression of key genes of glutaminolysis. A functional assay indicated that AjAMPKβ silencing by siRNA transfection could increase the levels of Gln and Glu and depress the production of GSH. Moreover, the expression of glutaminolysis-related genes was significantly inhibited, and the reduction of redox homeostasis indexes (MDA and NADPH/NADP⁺) was also observed. Contrastingly, AjAMPKβ overexpression promoted redox homeostasis balance. Intracellular ROS is mostly responsible for breaking redox homeostasis and leading to oxidative stress, contributing to cell fate changes in immune cells. Exogenous Gln and GSH treatments could significantly reduce ROS level while the AjAMPKβ silencing induced the level of ROS and accelerated the necrosis rate. All these results collectively revealed that AjAMPKβ could modulate cellular redox homeostasis by affecting the glutaminolysis in A. japonicus.

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 glutamate and glutamine-to-glutamate ratio are associated with coronary angiography defined coronary artery disease

BACKGROUND AND AIMS

Serum concentrations of glutamate (Glu), Glutamine (Gln) and Gln/Glu ratio have consistently been reported to be associated with metabolic disorders and diabetes. The aim of this study was to examine the relationship between these metabolites with the presence of coronary artery disease (CAD) and CAD severity in Chinese patients.

METHODS AND RESULTS

2970 Chinese patients undergoing coronary angiography (CAG) in Beijing Hospital were enrolled. Baseline demographics and medical history data was recorded by questionnaires. Serum Glu and Gln concentrations were analyzed by isotope dilution liquid chromatography-tandem mass spectrometry (LC-MS/MS). Statistical analysis showed that CAD patients had significantly higher levels of Glu and lower Gln/Glu ratios compared with non-CAD control group. Glu was significantly positively associated with body mass index (BMI), fasting blood glucose (FBG), triglycerides (TG), creatinine (Crea), and uric acid (UA), and negatively associated with high-density lipoprotein cholesterol (HDL-C), while inverse associations between Gln/Glu ratio and these risk factors were observed. Glu levels increased and Gln/Glu decreased with the increase of CAD severity as represented by either the number of stenosed vessels or the Gensini scores. Logistic regression analysis demonstrated that, after adjusting for smoking status, obesity or overweight, hypertension, dyslipidemia, diabetes, stroke and family history of premature CAD, high Glu level and low Gln/Glu ratio were positively associated with CAG defined CAD as well as CAD severity expressed by Gensini score.

CONCLUSIONS

We identified Glu and Gln/Glu ratio independently associated with CAG defined CAD as well as CAD severity in Chinese patients undergoing CAG.

The Effect of Mild Renal Dysfunction on the Assessment of Plasma Amino Acid Concentration and Insulin Resistance in Patients with Type 2 Diabetes Mellitus

BACKGROUND

An increase in the levels of branched-chain amino acids (BCAAs) and certain aromatic amino acids, such as alanine, in plasma is correlated with insulin resistance (IR) in type 2 diabetes mellitus (T2DM). T2DM is a leading risk factor for chronic kidney disease. Meanwhile, renal dysfunction causes changes in plasma amino acid levels. To date, no study has examined how mild renal dysfunction and IR interact with plasma amino acid levels. This study examines the effects of IR and renal dysfunction on plasma amino acid concentrations in T2DM.

METHODS

Data were collected from healthy male participants (controls) and male patients with T2DM between May 2018 and February 2022. Blood samples were collected after overnight fasting. IR and renal function were evaluated using the homeostasis model assessment of IR (HOMA-IR) and serum cystatin C (CysC), respectively.

RESULTS

A total of 49 and 93 participants were included in the control and T2DM groups, respectively. In the T2DM group, eight amino acids (alanine, glutamic acid, glutamine, glycine, isoleucine, leucine, tyrosine, and valine) and total BCAA showed a significant correlation with HOMA-IR (p < 0.01), whereas six amino acids (γ-aminobutyric acid, citrulline, cysteine, glycine, methionine, and valine) and total BCAA showed a significant correlation with 1/CysC (p < 0.02). However, only alanine, glutamic acid, and each BCAA showed significant differences between the control group and the IR T2DM subgroup. Increases in the BCAA levels with T2DM were canceled by renal dysfunction (CysC ≥ 0.93) in patients with intermediate IR.

CONCLUSION

To use plasma BCAA concentration as a marker of IR, renal function must be considered, even in mild renal dysfunction. Increased alanine and glutamic acid levels indicate IR, regardless of mild renal dysfunction.

Potential Therapeutic Targeting Neurotransmitter Receptors in Diabetes

Neurotransmitters are signaling molecules secreted by neurons to coordinate communication and proper function among different sections in the central neural system (CNS) by binding with different receptors. Some neurotransmitters as well as their receptors are found in pancreatic islets and are involved in the regulation of glucose homeostasis. Neurotransmitters can act with their receptors in pancreatic islets to stimulate or inhibit the secretion of insulin (β cell), glucagon (α cell) or somatostatin (δ cell). Neurotransmitter receptors are either G-protein coupled receptors or ligand-gated channels, their effects on blood glucose are mainly decided by the number and location of them in islets. Dysfunction of neurotransmitters receptors in islets is involved in the development of β cell dysfunction and type 2 diabetes (T2D).Therapies targeting different transmitter systems have great potential in the prevention and treatment of T2D and other metabolic diseases.

Multi-omics approach to COVID-19: a domain-based literature review

Background

Omics data, driven by rapid advances in laboratory techniques, have been generated very quickly during the COVID-19 pandemic. Our aim is to use omics data to highlight the involvement of specific pathways, as well as that of cell types and organs, in the pathophysiology of COVID-19, and to highlight their links with clinical phenotypes of SARS-CoV-2 infection.

Methods

The analysis was based on the domain model, where for domain it is intended a conceptual repository, useful to summarize multiple biological pathways involved at different levels. The relevant domains considered in the analysis were: virus, pathways and phenotypes. An interdisciplinary expert working group was defined for each domain, to carry out an independent literature scoping review.

Results

The analysis revealed that dysregulated pathways of innate immune responses, (i.e., complement activation, inflammatory responses, neutrophil activation and degranulation, platelet degranulation) can affect COVID-19 progression and outcomes. These results are consistent with several clinical studies.

Conclusions

Multi-omics approach may help to further investigate unknown aspects of the disease. However, the disease mechanisms are too complex to be explained by a single molecular signature and it is necessary to consider an integrated approach to identify hallmarks of severity.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-03168-8.

Low Branched Chain Amino Acids and Tyrosine in Thai Patients with Type 2 Diabetes Mellitus Treated with Metformin and Metformin-Sulfonylurea Combination Therapies

Type 2 diabetes mellitus (T2DM) is a growing public health challenge for Thailand (current prevalence ~10.0%). Amino acids offer novel biomarkers to predict risk of T2DM and indicate sub-optimal disease management, which could facilitate earlier treatment. We studied amino acid profiles in a Thai cohort comprising of individuals with T2DM (n = 65 single-drug-treated; n = 38 multi-drug-treated) compared to healthy controls (n = 104) using liquid chromatography-mass spectrometry. Age and BMI were significantly lower in the healthy controls compared to the single or multi-treated T2DM groups. The BCAA (leucine and valine) were significantly lower in the single and multi-treated T2DM groups compared to healthy controls (p < 0.001 and p < 0.001) and isoleucine was significantly lower in the single-treated compared to the healthy controls (p = 0.014). These findings beg the question whether BCAAs supplementation be beneficial in T2DM patients treated with single or multi-drug therapy? Tyrosine was significantly lower in the single and multi-treated T2DM groups compared to healthy controls (p < 0.001 and p = 0.002), whereas phenylalanine was significantly higher in the multi-treated T2DM group compared to the single treated T2DM group (p = 0.045). We provide novel insights into the effects of diabetes treatments on these amino acids in insulin resistant states such as T2DM in a unique but understudied Thai population.

HSP70 as a biomarker of the thin threshold between benefit and injury due to physical exercise when exposed to air pollution

Physical exercise has acute and chronic effects on inflammatory balance, metabolic regulation, and redox status. Exercise-induced adaptations are mediated by enhanced 70-kDa heat shock protein (HSP70) levels and an improved heat shock response (HSR). Therefore, exercise could be useful against disease conditions [obesity, diabetes mellitus (DM), and exposure to atmospheric pollutants] marked by an impaired HSR. However, exercise performed by obese or diabetic subjects under pollution conditions might also be dangerous at certain intensities. Intensity correlates with an increase in HSP70 levels during physical exercise until a critical point at which the effort becomes harmful and impairs the HSR. Establishing a unique biomarker able to indicate the exercise intensity on metabolism and cellular fatigue is essential to ensure adequate and safe exercise recommendations for individuals with obesity or DM who require exercise to improve their metabolic status and live in polluted regions. In this review, we examined the available evidence supporting our hypothesis that HSP70 could serve as a biomarker for determining the optimal exercise intensity for subjects with obesity or diabetes when exposed to air pollution and establishing the fine threshold between anti-inflammatory and pro-inflammatory exercise effects.

Plasma Metabolomic Markers of Insulin Resistance and Diabetes and Rate of Incident Parkinson's Disease

BACKGROUND

Although there is evidence of shared dysregulated pathways between diabetes and Parkinson's disease, epidemiologic research on an association between the two diseases has produced inconsistent results.

OBJECTIVE

We aimed to assess whether known metabolomic markers of insulin resistance and diabetes are also associated with Parkinson's disease development.

METHODS

We conducted a nested case-control study among Nurses' Health Study and Health Professionals Follow-up Study participants who had provided blood samples up to twenty years prior to Parkinson's diagnosis. Cases were matched to risk-set sampled controls by age, sex, fasting status, and time of blood collection. Participants provided covariate information via regularly collected cohort questionnaires. We used conditional logistic regression models to assess whether plasma levels of branched chain amino acids, acylcarnitines, glutamate, or glutamine were associated with incident development of Parkinson's disease.

RESULTS

A total of 349 case-control pairs were included in this analysis. In the primary analyses, none of the metabolites of interest were associated with Parkinson's disease development. In investigations of the association between each metabolite and Parkinson's disease at different time intervals prior to diagnosis, some metabolites showed marginally significant association but, after correction for multiple testing, only C18 : 2 acylcarnitine was significantly associated with Parkinson's disease among subjects for whom blood was collected less than 60 months prior to case diagnosis.

CONCLUSIONS

Plasma levels of diabetes-related metabolites did not contribute to predict risk of Parkinson's disease. Further investigation of the relationship between pre-diagnostic levels of diabetes-related metabolites and Parkinson's disease in other populations is needed to confirm these findings.

Decreased fasting serum glucogenic amino acids with a higher compared to normal protein diet during energy restriction in women: a randomized controlled trial

Dietary protein alters circulating amino acid (AAs) levels and higher protein intake (HP) is one means of losing weight. We examined 34 overweight and obese women (57 ± 4 years) during 6 months of energy restriction (7.3 ± 3.8% weight loss) divided into groups consuming either normal protein (NP; 18.6 energy% protein) or HP (24.3 energy% protein). There was a reduction in fasting serum glucogenic AAs (p = 0.015) that also associated with greater weight loss (p < 0.05) in the HP group, but not in the NP group. These findings have implications for nutrient prioritization during energy restriction.

Glutamine metabolism: from proliferating cells to cardiomyocytes

Glutamine is a major energy source for rapidly dividing cells, such as hematopoietic stem cells and cancer cells. Reliance on glutamine is therefore regarded as a metabolic hallmark of proliferating cells. Moreover, reprogramming glutamine metabolism by various factors, including tissue type, microenvironment, pro-oncogenes, and tumor suppressor genes, can facilitate stem cell fate decisions, tumor recurrence, and drug resistance. However, the significance of glutamine metabolism in cardiomyocytes, an end-differentiated cell type, is not fully understood. Existing evidence suggests important roles of glutamine metabolism in the development of cardiovascular diseases. In this review, we have focused on glutaminolysis and its regulatory network in proliferating cells. We have summarized current findings about the role of glutamine utilization in cardiomyocytes and have discussed possibilities of targeting glutamine metabolism for the treatment of cardiovascular diseases.

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.

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.

Assessment of the amino acid profile in Thai patients with type 2 diabetes mellitus using liquid chromatography-mass spectrometry

Background

Type 2 diabetes mellitus (T2DM) is a global health problem. Early identification of those at risk is necessary to prevent its onset through lifestyle and pharmacologic interventions. T2DM is characterized by metabolic abnormalities, including protein metabolism. Evaluation of the amino acid profile might be beneficial for early assessment.

Methods

Liquid chromatography-mass spectrometry was performed to separate and quantify plasma amino acids from two groups of Thai individuals, patients with T2DM (n=103) and healthy individuals (n=104). Multivariate analysis was applied to compare free amino acid levels between groups. Subgroup analyses of patients with T2DM were performed to assess the association between amino acid profiles and important T2DM clinical characteristics.

Results

The multivariate analysis showed that glutamic acid was significantly associated with T2DM (OR 1.113, 95% CI 1.006 to 1.231) and results from the subgroup analyses showed that this correlation was significant in all subgroups of patients (p<0.05).

Conclusions

This finding needs to be confirmed in larger groups of patients with T2DM to explore glutamic acid as a biomarker for early prevention in particular at-risk groups. An in-depth understanding of the involvement of glutamic acid in T2DM could enhance our understanding of the disease and potentially provide novel interventions.

New ratio as a useful marker for early diagnosis of proximal urea cycle disorders

BACKGROUND AND AIMS

Proximal urea cycle disorders (PUCDs) are not included in most newborn screening programs due to the lack of adequate markers to monitor. Failure to alter citrulline and glutamine levels, the prognostic markers commonly used, can results in high false negative. Therefore, new biomarkers, prognostic of PUCDs, are strongly desirable.

MATERIALS AND METHODS

We used tandem mass spectrometry to analyze blood spot from PUCDs patients during their follow up in our referral center focusing on glutamine to glutamate (Gln/Glu) ratio. We reanalyzed the same specimens of three patients after two months and the specimen of a new patient with suspicious of PUCD disorder.

RESULTS

Specimens of our patients shown a significant elevation of the ratio Gln/Glu compared to that of a healthy population (p < 0.05) as well as the specimens analyzed after two months, while the glutamine concentration dropped. New patient, showing high value of the ratio, was molecularly confirmed as PUCD patient. We further analyzed the blood spots from a neonatal population in order to fix a cut-off value and include it in a newborn screening panel.

CONCLUSION

Our preliminary results suggest that the Gln/Glu ratio could be a very useful diagnostic marker, more stable over time than glutamine, which could improve the performance in early PUCDs identification.

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.

Comprehensive Metabolic Phenotyping Refines Cardiovascular Risk in Young Adults

BACKGROUND

Whereas cardiovascular disease (CVD) metrics define risk in individuals >40 years of age, the earliest lesions of CVD appear well before this age. Despite the role of metabolism in CVD antecedents, studies in younger, biracial populations to define precise metabolic risk phenotypes are lacking.

METHODS

We studied 2330 White and Black young adults (mean age, 32 years; 45% Black) in the CARDIA study (Coronary Artery Risk Development in Young Adults) to identify metabolite profiles associated with an adverse CVD phenome (myocardial structure/function, fitness, vascular calcification), mechanisms, and outcomes over 2 decades. Statistical learning methods (elastic nets/principal components analysis) and Cox regression generated parsimonious, metabolite-based risk scores validated in >1800 individuals in the Framingham Heart Study.

RESULTS

In the CARDIA study, metabolite profiles quantified in early adulthood were associated with subclinical CVD development over 20 years, specifying known and novel pathways of CVD (eg, transcriptional regulation, brain-derived neurotrophic factor, nitric oxide, renin-angiotensin). We found 2 multiparametric, metabolite-based scores linked independently to vascular and myocardial health, with metabolites included in each score specifying microbial metabolism, hepatic steatosis, oxidative stress, nitric oxide modulation, and collagen metabolism. The metabolite-based vascular scores were lower in men, and myocardial scores were lower in Black participants. Over a nearly 25-year median follow-up in CARDIA, the metabolite-based vascular score (hazard ratio, 0.68 per SD [95% CI, 0.50-0.92]; P=0.01) and myocardial score (hazard ratio, 0.60 per SD [95% CI, 0.45-0.80]; P=0.0005) in the third and fourth decades of life were associated with clinical CVD with a synergistic association with outcome (Pinteraction=0.009). We replicated these findings in 1898 individuals in the Framingham Heart Study over 2 decades, with a similar association with outcome (including interaction), reclassification, and discrimination. In the Framingham Heart Study, the metabolite scores exhibited an age interaction (P=0.0004 for a combined myocardial-vascular score with incident CVD), such that young adults with poorer metabolite-based health scores had highest hazard of future CVD.

CONCLUSIONS

Metabolic signatures of myocardial and vascular health in young adulthood specify known/novel pathways of metabolic dysfunction relevant to CVD, associated with outcome in 2 independent cohorts. Efforts to include precision measures of metabolic health in risk stratification to interrupt CVD at its earliest stage are warranted.

Metabolic Architecture of Acute Exercise Response in Middle-Aged Adults in the Community

BACKGROUND

Whereas regular exercise is associated with lower risk of cardiovascular disease and mortality, mechanisms of exercise-mediated health benefits remain less clear. We used metabolite profiling before and after acute exercise to delineate the metabolic architecture of exercise response patterns in humans.

METHODS

Cardiopulmonary exercise testing and metabolite profiling was performed on Framingham Heart Study participants (age 53±8 years, 63% women) with blood drawn at rest (n=471) and at peak exercise (n=411).

RESULTS

We observed changes in circulating levels for 502 of 588 measured metabolites from rest to peak exercise (exercise duration 11.9±2.1 minutes) at a 5% false discovery rate. Changes included reductions in metabolites implicated in insulin resistance (glutamate, -29%; P=1.5×10-55; dimethylguanidino valeric acid [DMGV], -18%; P=5.8×10-18) and increases in metabolites associated with lipolysis (1-methylnicotinamide, +33%; P=6.1×10-67), nitric oxide bioavailability (arginine/ornithine + citrulline, +29%; P=2.8×10-169), and adipose browning (12,13-dihydroxy-9Z-octadecenoic acid +26%; P=7.4×10-38), among other pathways relevant to cardiometabolic risk. We assayed 177 metabolites in a separate Framingham Heart Study replication sample (n=783, age 54±8 years, 51% women) and observed concordant changes in 164 metabolites (92.6%) at 5% false discovery rate. Exercise-induced metabolite changes were variably related to the amount of exercise performed (peak workload), sex, and body mass index. There was attenuation of favorable excursions in some metabolites in individuals with higher body mass index and greater excursions in select cardioprotective metabolites in women despite less exercise performed. Distinct preexercise metabolite levels were associated with different physiologic dimensions of fitness (eg, ventilatory efficiency, exercise blood pressure, peak Vo2). We identified 4 metabolite signatures of exercise response patterns that were then analyzed in a separate cohort (Framingham Offspring Study; n=2045, age 55±10 years, 51% women), 2 of which were associated with overall mortality over median follow-up of 23.1 years (P≤0.003 for both).

CONCLUSIONS

In a large sample of community-dwelling individuals, acute exercise elicits widespread changes in the circulating metabolome. Metabolic changes identify pathways central to cardiometabolic health, cardiovascular disease, and long-term outcome. These findings provide a detailed map of the metabolic response to acute exercise in humans and identify potential mechanisms responsible for the beneficial cardiometabolic effects of exercise for future study.

Integrative Modeling of Quantitative Plasma Lipoprotein, Metabolic, and Amino Acid Data Reveals a Multiorgan Pathological Signature of SARS-CoV-2 Infection

The metabolic effects of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection on human blood plasma were characterized using multiplatform metabolic phenotyping with nuclear magnetic resonance (NMR) spectroscopy and liquid chromatography-mass spectrometry (LC-MS). Quantitative measurements of lipoprotein subfractions, α-1-acid glycoprotein, glucose, and biogenic amines were made on samples from symptomatic coronavirus disease 19 (COVID-19) patients who had tested positive for the SARS-CoV-2 virus (n = 17) and from age- and gender-matched controls (n = 25). Data were analyzed using an orthogonal-projections to latent structures (OPLS) method and used to construct an exceptionally strong (AUROC = 1) hybrid NMR-MS model that enabled detailed metabolic discrimination between the groups and their biochemical relationships. Key discriminant metabolites included markers of inflammation including elevated α-1-acid glycoprotein and an increased kynurenine/tryptophan ratio. There was also an abnormal lipoprotein, glucose, and amino acid signature consistent with diabetes and coronary artery disease (low total and HDL Apolipoprotein A1, low HDL triglycerides, high LDL and VLDL triglycerides), plus multiple highly significant amino acid markers of liver dysfunction (including the elevated glutamine/glutamate and Fischer's ratios) that present themselves as part of a distinct SARS-CoV-2 infection pattern. A multivariate training-test set model was validated using independent samples from additional SARS-CoV-2 positive patients and controls. The predictive model showed a sensitivity of 100% for SARS-CoV-2 positivity. The breadth of the disturbed pathways indicates a systemic signature of SARS-CoV-2 positivity that includes elements of liver dysfunction, dyslipidemia, diabetes, and coronary heart disease risk that are consistent with recent reports that COVID-19 is a systemic disease affecting multiple organs and systems. Metabolights study reference: MTBLS2014.