The amino acid response to a mixed meal in patients with type 2 diabetes: effect of sitagliptin treatment

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.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Impact of Nutrient Type and Sequence on Glucose Tolerance: Physiological Insights and Therapeutic Implications

Pharmacological and dietary interventions targeting postprandial glycemia have proved effective in reducing the risk for type 2 diabetes and its cardiovascular complications. Besides meal composition and size, the timing of macronutrient consumption during a meal has been recently recognized as a key regulator of postprandial glycemia. Emerging evidence suggests that premeal consumption of non-carbohydrate macronutrients (i.e., protein and fat "preloads") can markedly reduce postprandial glycemia by delaying gastric emptying, enhancing glucose-stimulated insulin release, and decreasing insulin clearance. The same improvement in glucose tolerance is achievable by optimal timing of carbohydrate ingestion during a meal (i.e., carbohydrate-last meal patterns), which minimizes the risk of body weight gain when compared with nutrient preloads. The magnitude of the glucose-lowering effect of preload-based nutritional strategies is greater in type 2 diabetes than healthy subjects, being comparable and additive to current glucose-lowering drugs, and appears sustained over time. This dietary approach has also shown promising results in pathological conditions characterized by postprandial hyperglycemia in which available pharmacological options are limited or not cost-effective, such as type 1 diabetes, gestational diabetes, and impaired glucose tolerance. Therefore, preload-based nutritional strategies, either alone or in combination with pharmacological treatments, may offer a simple, effective, safe, and inexpensive tool for the prevention and management of postprandial hyperglycemia. Here, we survey these novel physiological insights and their therapeutic implications for patients with diabetes mellitus and altered glucose tolerance.

The insulinotropic effect of a high-protein nutrient preload is mediated by the increase of plasma amino acids in type 2 diabetes

AIMS

Eating protein before carbohydrate reduces postprandial glucose excursions by enhancing insulin and glucagon-like peptide-1 (GLP-1) secretion in type 2 diabetes (T2D). We tested the hypothesis that this insulinotropic effect depends on the elevation of plasma amino acids (AA) after the digestion of food protein.

METHODS

In 16 T2D patients, we measured plasma AA levels through the course of two 75-g oral glucose tolerance tests (OGTT) preceded by either 500-ml water or a high-protein nutrient preload (50-g Parmesan cheese, one boiled egg, and 300-ml water). Changes in beta cell function were evaluated by measuring and modelling plasma glucose, insulin, and C-peptide through the OGTT. Changes in incretin hormone secretion were assessed by measuring plasma GLP-1.

RESULTS

Plasma AA levels were 24% higher after the nutrient preload (p < 0.0001). This increment was directly proportional to both the enhancement of beta cell function (r = 0.58, p = 0.02) and the plasma GLP-1 gradients (r = 0.57, p = 0.02) produced by the nutrient preload. Among single AA, glutamine showed the strongest correlation with changes in beta cell function (r = 0.61, p = 0.01), while leucine showed the strongest correlation with GLP-1 responses (r = 0.74, p = 0.001).

CONCLUSIONS

The elevation of circulating AA that occurs after a high-protein nutrient preload is associated with an enhancement of beta cell function and GLP-1 secretion in T2D. Manipulating the meal sequence of nutrient ingestion may reduce postprandial hyperglycaemia through a direct and GLP-1-mediated stimulation of insulin secretion by plasma AA.

TRIAL REGISTRATION NUMBER

NCT02342834.

Improvement in insulin resistance after gastric bypass surgery is correlated with a decline in plasma 2-hydroxybutyric acid

BACKGROUND

Gastric bypass surgery for weight reduction often corrects dysglycemia in diabetic patients, but a full understanding of the underlying biochemical pathways continues to be investigated.

OBJECTIVES

To explore the effects of weight loss by surgical and dietary interventions on plasma metabolites using both targeted and discovery-oriented metabolomics platforms.

SETTING

An academic medical center in the United States.

METHODS

Improvement in homeostatic model assessment for insulin resistance (HOMA-IR), as an index of insulin resistance, was compared at 6 months in 11 patients that underwent Roux-en-Y gastric bypass against 11 patients that were matched for weight loss in the Weight Loss Maintenance (WLM) program. Metabolites in plasma were evaluated by nontargeted gas chromatography/mass spectrometry for the potential detection of >1100 biochemical markers.

RESULTS

Among multiple metabolites detected, 2-hydroxybutyric acid (2-HBA) declined most significantly after 6 months in comparing patients that underwent Roux-en-Y gastric bypass with those in WLM (P < .001), corresponding with declines in HOMA-IR (P = .025). Baseline levels of 2-HBA for all patients were correlated with preintervention levels of HOMA-IR (R² = .565, P < .001). Moreover, the changes in 2-HBA after 6 months were correlated with changes in HOMA-IR (R² = .399, P = .0016).

CONCLUSIONS

Correlation between insulin resistance and 2-HBA suggests the utility of the latter as an excellent biomarker for tracking glycemic improvement, and offers further insight into the pathways that control diabetes. This is the first report of a decline in 2-HBA in response to bariatric surgery.

Serum metabolic profiling of type 2 diabetes mellitus in Chinese adults using an untargeted GC/TOFMS

BACKGROUND

Type 2 diabetes mellitus (T2DM) is a huge burden in China. The Chinese patients with T2DM have several special clinical characteristics. Metabolomics studies predominantly have identified several distinguishing metabolites associated with T2DM in Western ancestry population. However, few previous metabolomics studies were conducted in Chinese populations.

METHODS

We performed untargeted serum metabolic profiling between 30 T2DM patients and 30 healthy controls based on GC/TOFMS. Multivariate data analyses were applied to identify the distinguishing metabolites.

RESULTS

Excellent separation was obtained between the two cases. And overall 54 distinguishing metabolites were identified with VIP>1 and P<0.05, which were involved in metabolic pathways of amino acid, carbohydrate, lipids, membrane transport and nucleotides. To further analyze the correlation between the identified metabolites and T2DM, 17 metabolites were selected with FC>2.0, including gentisic acid, citraconic acid, succinic acid, 2-hydroxybutanoic acid and 3-hydroxy-l-proline, the corresponding FC were respectively 5.44, 2.21, 2.10, 2.21 and -2.04.

CONCLUSION

Our results demonstrated that untargeted GC/TOFMS-based metabolic approach processed well performance to identify serum distinguishing metabolites of T2DM in Chinese adults, which may be as potential biomarkers in diagnose and treatment of diabetes. And the results also provided new insight into understand the underlying molecular mechanism.

Pharmacometabolomic Assessment of Metformin in Non-diabetic, African Americans

Millions of individuals are diagnosed with type 2 diabetes mellitus (T2D), which increases the risk for a plethora of adverse outcomes including cardiovascular events and kidney disease. Metformin is the most widely prescribed medication for the treatment of T2D; however, its mechanism is not fully understood and individuals vary in their response to this therapy. Here, we use a non-targeted, pharmacometabolomics approach to measure 384 metabolites in 33 non-diabetic, African American subjects dosed with metformin. Three plasma samples were obtained from each subject, one before and two after metformin administration. Validation studies were performed in wildtype mice given metformin. Fifty-four metabolites (including 21 unknowns) were significantly altered upon metformin administration, and 12 metabolites (including six unknowns) were significantly associated with metformin-induced change in glucose (q < 0.2). Of note, indole-3-acetate, a metabolite produced by gut microbes, and 4-hydroxyproline were modulated following metformin exposure in both humans and mice. 2-Hydroxybutanoic acid, a metabolite previously associated with insulin resistance and an early biomarker of T2D, was positively correlated with fasting glucose levels as well as glucose levels following oral glucose tolerance tests after metformin administration. Pathway analysis revealed that metformin administration was associated with changes in a number of metabolites in the urea cycle and in purine metabolic pathways (q < 0.01). Further research is needed to validate the biomarkers of metformin exposure and response identified in this study, and to understand the role of metformin in ammonia detoxification, protein degradation and purine metabolic pathways.

Mechanisms through which a small protein and lipid preload improves glucose tolerance

AIMS/HYPOTHESIS

Small protein or lipid preloads are able to improve glucose tolerance to a different extent and through different and poorly defined mechanisms. We aimed at quantifying the effect of a mixed protein and lipid preload and at evaluating the underlying mechanisms.

METHODS

Volunteers with normal (NGT, n = 12) or impaired (IGT, n = 13) glucose tolerance and patients with type 2 diabetes (n = 10) underwent two OGTTs coupled to the double glucose tracer protocol, preceded by either 50 g of parmesan cheese, a boiled egg and 300 ml of water, or 500 ml of water. We measured plasma glucose, insulin, C-peptide, glucagon-like peptide-1 (GLP-1), glucose-dependent insulinotropic polypeptide (GIP), pancreatic polypeptide (PP), NEFA and glucose tracers, and calculated glucose fluxes, beta cell function variables, insulin sensitivity and clearance.

RESULTS

After the nutrient preload, the OGTT-induced rise of plasma glucose was lower than after water alone in each study group. This reduction—more pronounced across classes of glucose tolerance (NGT -32%, IGT -37%, type 2 diabetes -49%; p < 0.002)—was the result of different combinations of slower exogenous glucose rate of appearance, improved beta cell function and reduced insulin clearance, in this order of relevance, which were associated with an only mild stimulation of GIP and GLP-1.

CONCLUSIONS/INTERPRETATION

After a non-glucidic nutrient preload, glucose tolerance improved in proportion to the degree of its baseline deterioration through mechanisms that appear particularly effective in type 2 diabetes. Exploiting the physiological responses to nutrient ingestion might reveal, at least in the first stages of the diabetic disease, a potent tool to improve daily life glycaemic control.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02342834 FUNDING: This work was supported by grants from the University of Pisa (Fondi di Ateneo) and by FCT grant (PIC/IC/82956/2007).

Type 2 diabetes is associated with postprandial amino acid measures

Most studies examining the association between type 2 diabetes (T2D) and amino acids have focused on fasting concentrations. We hypothesized that, besides fasting concentrations, amino acid responses to a standardized meal challenge are also associated with T2D. In a cross-sectional study of 525 participants (165 newly-diagnosed T2D, 186 newly-diagnosed impaired fasting glycaemia, and 174 normal fasting glucose), we examined postprandial amino acid concentrations and the responses (defined as the concentrations and responses 150 min after a standardized meal) of fourteen amino acids in relation to T2D. T2D was associated with lower postprandial concentration of seven amino acids compared to the normal fasting glucose group (lowest effect estimate for serine: -0.54 standard deviations (SD) (95% CI: -0.77, -0.32)), and higher concentrations of phenylalanine, tryptophan, tyrosine and (iso-)leucine (highest effect estimate for (iso-)leucine: 0.44 SD (95% CI: 0.20, 0.67)). Regarding the meal responses, T2D was associated with lower responses of seven amino acids (ranging from -0.55 SD ((95% CI): -0.78, -0.33) for serine to -0.25 SD ((95% CI: -0.45, -0.02) for ornithine). We conclude that T2D is associated with postprandial concentrations of amino acids and a reduced amino acid meal response, indicating that these measures may also be potential markers of T2D.

Effect of insulin sensitizer therapy on amino acids and their metabolites

AIMS

Prior studies have reported that elevated concentrations of several plasma amino acids (AA), particularly branched chain (BCAA) and aromatic AA predict the onset of type 2 diabetes. We sought to test the hypothesis that circulating BCAA, aromatic AA and related AA metabolites decline in response to the use of insulin sensitizing agents in overweight/obese adults with impaired fasting glucose or untreated diabetes.

METHODS

We performed a secondary analysis of a randomized, double-blind, placebo, controlled study conducted in twenty five overweight/obese (BMI ~30kg/m(2)) adults with impaired fasting glucose or untreated diabetes. Participants were randomized to three months of pioglitazone (45mg per day) plus metformin (1000mg twice per day, N=12 participants) or placebo (N=13). We measured insulin sensitivity by the euglycemic-hyperinsulinemic clamp and fasting concentrations of AA and AA metabolites using ultra-pressure liquid chromatography tandem mass spectrometry before and after the three-month intervention.

RESULTS

Insulin sensitizer therapy that significantly enhanced insulin sensitivity reduced 9 out of 33 AA and AA metabolites measured compared to placebo treatment. Moreover, insulin sensitizer therapy significantly reduced three functionally clustered AA and metabolite pairs: i) phenylalanine/tyrosine, ii) citrulline/arginine, and iii) lysine/α-aminoadipic acid.

CONCLUSIONS

Reductions in plasma concentrations of several AA and AA metabolites in response to three months of insulin sensitizer therapy support the concept that reduced insulin sensitivity alters AA and AA metabolites.