β-cell function, incretin response, and insulin sensitivity of glucose and fat metabolism in obese youth: Relationship to OGTT-time-to-glucose-peak

Pros and Cons of Current Diagnostic Tools for Risk-Based Screening of Prediabetes and Type 2 Diabetes in Children and Adolescents with Overweight or Obesity

It is still a matter of debate which is the most suitable diagnostic test for risk-based screening of prediabetes and type 2 diabetes (T2D) in children and adolescents with overweight or obesity. This review highlighted benefits and pitfalls of currently recommended screening tools (fasting plasma glucose [FPG], oral glucose tolerance test [OGTT], glycated hemoglobin A1c [HbA1c]). The greatest advantage of OGTT is the ability to detect people with impaired glucose tolerance, a subcategory at high risk of developing both T2D and cardiovascular disease. Important disadvantages are low reproducibility and inconvenience. FPG measurement is more practical, as it needs only one blood draw, although both OGTT and FPG require fasting. The reliability of HbA1c as a screening tool has been questioned, especially in children and adolescents, but its undeniable convenience can lead to increased adherence to screening. In contrast, it can be altered by several nonglycemic factors. Importantly, none of these tests have been validated in the pediatric population. Alternative tests have been recently proposed, including new OGTT-derived biomarkers and additional nonfasting glycemic markers. In conclusion, when choosing the most suitable test in clinical practice, advantages and disadvantages should be considered, as well as the possibility of performing different tests at once.

Data assimilation on mechanistic models of glucose metabolism predicts glycemic states in adolescents following bariatric surgery

Type 2 diabetes mellitus is a complex and under-treated disorder closely intertwined with obesity. Adolescents with severe obesity and type 2 diabetes have a more aggressive disease compared to adults, with a rapid decline in pancreatic β cell function and increased incidence of comorbidities. Given the relative paucity of pharmacotherapies, bariatric surgery has become increasingly used as a therapeutic option. However, subsets of this population have sub-optimal outcomes with either inadequate weight loss or little improvement in disease. Predicting which patients will benefit from surgery is a difficult task and detailed physiological characteristics of patients who do not respond to treatment are generally unknown. Identifying physiological predictors of surgical response therefore has the potential to reveal both novel phenotypes of disease as well as therapeutic targets. We leverage data assimilation paired with mechanistic models of glucose metabolism to estimate pre-operative physiological states of bariatric surgery patients, thereby identifying latent phenotypes of impaired glucose metabolism. Specifically, maximal insulin secretion capacity, σ, and insulin sensitivity, S_I, differentiate aberrations in glucose metabolism underlying an individual's disease. Using multivariable logistic regression, we combine clinical data with data assimilation to predict post-operative glycemic outcomes at 12 months. Models using data assimilation sans insulin had comparable performance to models using oral glucose tolerance test glucose and insulin. Our best performing models used data assimilation and had an area under the receiver operating characteristic curve of 0.77 (95% confidence interval 0.7665, 0.7734) and mean average precision of 0.6258 (0.6206, 0.6311). We show that data assimilation extracts knowledge from mechanistic models of glucose metabolism to infer future glycemic states from limited clinical data. This method can provide a pathway to predict long-term, post-surgical glycemic states by estimating the contributions of insulin resistance and limitations of insulin secretion to pre-operative glucose metabolism.

The characteristics of postprandial glycemic response patterns to white rice and glucose in healthy adults: Identifying subgroups by clustering analysis

OBJECTIVES

Large interpersonal variability in postprandial glycemic response (PGR) to white rice has been reported, and differences in the PGR patterns during the oral glucose tolerance test (OGTT) have been documented. However, there is scant study on the PGR patterns of white rice. We examined the typical PGR patterns of white rice and glucose and the association between them.

MATERIALS AND METHODS

We analyzed the data of 3-h PGRs to white rice (WR) and glucose (G) of 114 normoglycemic female subjects of similar age, weight status, and same ethnic group. Diverse glycemic parameters, based on the discrete blood glucose values, were calculated over 120 and 180 min. K-means clustering based on glycemic parameters calculated over 180 min was applied to identify subgroups and representative PGR patterns. Principal factor analysis based on the parameters used in the cluster analysis was applied to characterize PGR patterns. Simple correspondence analysis was performed on the clustering categories of WR and G.

RESULTS

More distinct differences were found in glycemic parameters calculated over 180 min compared with that calculated over 120 min, especially in the negative area under the curve and Nadir. We identified four distinct PGR patterns to WR (WR1, WR2, WR3, and WR4) and G (G1, G2, G3, and G4), respectively. There were significant differences among the patterns regard to postprandial hyperglycemia, hypoglycemic, and glycemic variability. The WR1 clusters had significantly lower glycemic index (59 ± 19), while no difference was found among the glycemic index based on the other three clusters. Each given G subgroup presented multiple patterns of PGR to WR, especially in the largest G subgroup (G1), and in subgroup with the greatest glycemic variability (G3).

CONCLUSION

Multiple subgroups could be classified based on the PGR patterns to white rice and glucose even in seemingly homogeneous subjects. Extending the monitoring time to 180 min was conducive to more effective discrimination of PGR patterns. It may not be reliable to extrapolate the patterns of PGR to rice from that to glucose, suggesting a need of combining OGTT and meal tolerance test for individualized glycemic management.

Metabolic inflexibility in youth with obesity: Is it a feature of obesity or distinctive of youth who are metabolically unhealthy?

Individuals with obesity have metabolic inflexibility with diminished fasting fat oxidation and blunted increase in respiratory quotient (RQ) in insulin-stimulated states. However, it is unclear if metabolic inflexibility is a characteristic of obesity per se or is unique to youth who have metabolically unhealthy obesity (MUO) compared with metabolically healthy obesity (MHO). We investigated metabolic flexibility in youth with MUO, MHO and normal weight (NW) and compared their metabolic characteristics. Youth (n = 188) were divided, based on cut-off points for in vivo insulin sensitivity (IS) of adolescents with NW, into 137 with MUO and 51 with MHO. Fasting hepatic IS (HIS) from hepatic glucose production by [6,6-² H₂ ]glucose, adipose tissue IS (ATIS) from whole-body lipolysis by [² H₅ ]glycerol, RQ (indirect calorimetry) during fasting and a hyperinsulinemic (80 mU/m² /min)-euglycemic clamp were measured. Youth with MUO versus MHO had blunted ΔRQ (p = .035) and lower HIS and ATIS (both p < .0001), while ΔRQ, HIS and ATIS were not different between youth with MHO and NW. In a pair-matched sub-analyses of 30 MUO and 30 MHO the results were similar to the total cohort. Metabolic inflexibility, does not appear to be a feature of obesity per se rather distinctive of youth with MUO, who also have worse HIS and ATIS compared with youth with MHO.

Changes in OGTT-derived biomarkers in response to lifestyle intervention among Latino adolescents with obesity

BACKGROUND

Glucose concentrations during an oral glucose tolerance test (OGTT) have been used as biomarkers to differentiate type 2 diabetes risk phenotypes. No studies have examined changes in OGTT-glucose phenotypes following lifestyle intervention among high-risk youth.

OBJECTIVE

To examine changes in OGTT-glucose phenotypes following lifestyle intervention and to explore differences in insulin sensitivity and β-cell function among post-intervention phenotypes.

METHODS

Latino adolescents with obesity (n = 48, age 15.4 ± 1.0, BMI% 98.2 ± 1.4, female 56.3%) completed a 12-week lifestyle intervention that included weekly nutrition education and physical activity. At baseline and 12 weeks, youth completed a 2-h OGTT with glucose and insulin concentrations assessed at 0', 30', 60', 90' and 120'. Glucose concentrations during the OGTT were used to identify biomarkers, 1-h glucose, glucose response curve and time to glucose peak. Using these respective biomarkers, high-risk (1-h glucose ≥ 155 mg/dl, Monophasic, Late Peak) and lower-risk phenotypes (1-h glucose < 155 mg/dl, Biphasic, Early Peak) were categorized. Insulin sensitivity was estimated by whole-body insulin sensitivity index (WBISI) and β-cell function by oral disposition index (oDI).

RESULTS

Following intervention, the prevalence of Monophasic phenotypes decreased from 81% to 67% (p = 0.048) and 1-h glucose ≥ 155 mg/dl from 38% to 10% (p = 0.054). Although Late Peak phenotypes did not significantly change (from 58% to 29%, p = 0.200), Early Peak phenotypes at post-intervention demonstrated significantly higher WBISI compared to Late Peak (2.3 ± 0.1 vs 1.7 ± 0.2, p = 0.023).

CONCLUSIONS

OGTT-glucose phenotypes improve following lifestyle intervention among high-risk youth. These findings further support their potential utility as clinical biomarkers to identify diabetes risk and risk reduction in youth.

Fat-free/lean body mass in children with insulin resistance or metabolic syndrome: a systematic review and meta-analysis

BACKGROUND

Lean / Fat Free Body Mass (LBM) is metabolically involved in active processes such as resting energy expenditure, glucose uptake, and myokine secretion. Nonetheless, its association with insulin sensitivity / resistance / glucose tolerance and metabolic syndrome remains unclear in childhood.

METHODS

The current investigation aimed to examine the differences in fat-free mass /lean body mass according to the presence of insulin sensitivity/insulin resistance/glucose tolerance/metabolic syndrome in children. A systematic search was carried out in Medline/PubMed, Embase, Scopus, Web of Science, and SciELO, covering the period from each database's respective start to 21 June 2021. Two researchers evaluated 7111 studies according to the inclusion criteria: original human studies, written in English or Spanish, evaluating fat-free mass/lean body mass in children and adolescents including both with and without insulin sensitivity/insulin resistance /glucose tolerance and metabolic syndrome and reported the differences between them in terms of fat free mass/lean body mass. The results of the studies were combined with insulin sensitivity, insulin, resistance, glucose tolerance and metabolic syndrome. The standardized mean difference (SMD) in each study was calculated and combined using the random-effects model. Heterogeneity between studies was tested using the index of heterogeneity (I2), leave-one-out sensitivity analyses were performed, and publication bias was assessed using the Egger and Begg tests.

RESULTS

Finally, 15 studies which compared groups defined according to different glucose homeostasis criteria or metabolic syndrome out of 103 eligible studies were included in this systematic review and 12 studies in the meta-analysis. Meta-analysis showed lower fat-free mass/lean body mass percentage in participants with insulin resistance/glucose tolerance/metabolic syndrome (SMD -0.47; 95% CI, - 0.62 to - 0.32) while in mass units (kg), higher values were found in the same group (SMD, 1.01; 95% CI, 0.43 to 1.60).

CONCLUSIONS

Our results identified lower values of fat-free mass/lean body mass (%) in children and adolescents with insulin resistance/glucose tolerance/metabolic syndrome and higher values of fat-free mass/lean body mass when these are expressed in kg. The evidence of the impact of lean mass on children's glucose homeostasis or metabolic syndrome is limited, so future studies research should focus on explaining the effect of fat-free mass/lean body mass on different metabolic outcomes. Moreover, it may be interesting to evaluate the quality (muscle density) or functional (muscle strength) outcomes in addition to both absolute (kg) and relative (%) values in future studies. The systematic review was prospectively registered at PROSPERO (registration number CRD42019124734; available at: http://www.crd.york.ac.uk/prospero [accessed: 05 April 2019]).

Is There a Link between Balance and Body Mass Composition in Children and Adolescents?

School-age children are particularly prone to disturbances in body composition, because this is a period of intensive growth and a period in which correct habits are shaped, especially in relation to diet. This is why it is so important to diagnose emerging disorders early so as to implement therapeutic or educational activities. The aim of this study was to assess the relationship between the factors of body mass composition and body mass index (BMI), as well as the balance parameters in children and adolescents. The study group consisted of 1137 children aged 7 to 15. There were 559 girls and 578 boys among the subjects. The study used the Tanita 780 body mass composition analyser and the Zebris stabilometric platform. It was found that girls were characterized by a significantly higher content of adipose tissue (24.37% vs. 20.45%), while boys were characterized by a higher content of lean tissue (32.99% vs. 30.43%), muscle tissue (31.23% vs. 28.86%) and water (24.15% vs. 22.28%). Interestingly, the girls had better balance than their peers in all analyzed parameters (COF TTL.-616.72 vs. 661.50; CEArea-73.63 vs. 112.24; COF HD-3.44 vs. 4.23; COF VD-4.52 vs. 5.12). It turned out that among children in adolescence, a higher adipose tissue content and a higher BMI correlated with a smaller surface area (p < 0.05) defined by the center of gravity and smaller deviations of the center of gravity in the horizontal plane (p < 0.05). Sex and adolescence play an important role in differentiating both body composition and body balance. The results of this study allow us to conclude that children with higher BMI values have better balance. Due to the fact that these conclusions are inconsistent with those of other researchers, it will be worth continuing the research (e.g., on a different population group) in order to confirm the results and to draw far-reaching conclusions.

Effects of Combined High-Protein Diet and Exercise Intervention on Cardiometabolic Health in Middle-Aged Obese Adults: A Randomized Controlled Trial

Background: Obesity is the main risk factor of cardiovascular diseases (CVD) and metabolic diseases. The middle-aged population is the age group with the highest prevalence of obesity. Thus, improving cardiometabolic health is important to prevent CVD and metabolic diseases in middle-aged obese adults. The aim of this study was to examine the effects of exercise alone or in combination with a high-protein diet on markers of cardiometabolic health in middle-aged adults with obesity.

Methods: Sixty-nine middle-aged adults with obesity were assigned randomly to the control group (C; n = 23), exercise group (E; n = 23), or exercise combined with high-protein diet group (EP; n = 23). Individuals in the E and EP groups received supervised exercise training and individuals in the EP group received high-protein diet intervention. Body composition (assessed by dual-energy X-ray absorptiometry), oral glucose tolerance test (OGTT), lipid profiles, and inflammatory markers were determined before and after 12 weeks of intervention. Insulin sensitivity index (ISI_0,120) was calculated from values of fasting and 2-h insulin and glucose concentration of OGTT. Insulin-peak-time during the OGTT was recorded to reflect β-cell function. Analysis of covariance with baseline values as covariates was used to examine the effects of the intervention. The significant level was set at 0.05.

Results: After 12 weeks of intervention, the E group had a greater percentage of individuals with early insulin-peak-time during the OGTT than that in the C and EP groups (p = 0.031). EP group had lower total cholesterol and triglycerides than that in the C group (p = 0.046 and 0.014, respectively). Within-group comparisons showed that the 2-h glucose of OGTT and C-reactive protein decreased in the EP group (p = 0.013 and 0.008, respectively) but not in the E and C groups; insulin sensitivity improved in the EP group (p = 0.016) and had a trend to improve in the E group (p = 0.052); and abdominal fat mass and total body fat mass decreased in both intervention groups (p < 0.05).

Conclusion: Combined high-protein diet and exercise intervention significantly decreased fat mass and improved lipid profiles, insulin sensitivity, glucose tolerance, and inflammation in middle-aged adults with obesity.

Clinical Trial Registration: Thai Clinical Trials Registry, TCTR20180913003, 13-09-2018.

The incessant increase curve during oral glucose tolerance tests in Chinese adults with type 2 diabetes and its association with gut hormone levels

Glucose curve shapes during oral glucose tolerance tests (OGTTs) are mainly classified as incessant increase, monophasic and biphasic. Youth with an incessant increase curve have worse β-cell function. The aim of this paper was to investigate the incessant increase curve in Chinese adults with type 2 diabetes (T2DM), and its association with β-cell function and gut hormone levels. Eighty-nine Chinese patients (59 males and 30 females) were included in this study with a mean age of 50.56 ± 16.00 years. They were all recently diagnosed with T2DM and underwent 180-min OGTTs. Data on demographics, β-cell function, and insulin sensitivity were also collected. Gut hormones, including glucagon-like peptide-1 (GLP-1), glucose-dependent insulinotropic polypeptide (GIP), and ghrelin, were also detected during the OGTT. A total of 39.3 % of subjects had an incessant increase in the glucose response curve, while 59.6 % had a monophasic curve. Because only one curve was classified as biphasic, patients with a biphasic curve were omitted from further research. Lower plasma C-peptide, HOMA2-β, area under the curve (AUC) of C-peptide, and ratio of AUC of insulin to AUC of glucose were found in patients with incessant increase curves compared to those with monophasic curves (P < 0.05). Higher glycated hemoglobin (HbA_1c) was found in subjects with an incessant increase curve (P < 0.05). Importantly, fasting plasma ghrelin was lower and incremental ghrelin at 120 min was higher in the incessant increase group (P < 0.05), irrespective of age, sex, body mass index (BMI), fasting glucose, and fasting insulin. Time to peak is also a parameter of the OGTT curve shape. In the late-peak group, GLP-1 at 120 min and the AUC of GLP-1 were elevated compared with those in the early-peak group (P < 0.05). In Chinese adults with T2DM, the incessant increase in OGTT shape indicated impaired insulin secretion. Lower fasting ghrelin and absence of ghrelin drops after glucose load may be associated with the incessant increase OGTT shape. In addition, compensatory elevated GLP-1 dose not prevent peak delay in the OGTT curve. Gut hormones may have an effect on OGTT shapes in T2DM adults.

Time to the Peak, Shape of the Curve and Combination of These Glucose Response Characteristics During Oral Glucose Tolerance Test as Indicators of Early Beta-cell Dysfunction in Obese Adolescents

OBJECTIVE

Characteristics of the glucose response during oral glucose tolerance test (OGTT) may reflect differences in insulin secretion and action. The aim was to examine whether timing of the glucose peak, shape of the glucose curve and their combination could be indicators of beta-cell dysfunction in obese/severely obese adolescents with normal glucose tolerance (NGT).

METHODS

Data from 246 obese/severely obese adolescents who completed OGTT were reviewed. Out of 184 adolescents with NGT, 174 could be further classified into groups based on timing of the glucose peak (early/30 minutes vs late/≥60 minutes) and shape of the glucose curve (monophasic vs biphasic). Groups were compared with respect to insulin sensitivity (whole body insulin sensitivity index - WBISI), early-phase insulin secretion (insulinogenic index - IGI) and beta-cell function relative to insulin sensitivity (oral disposition index - oDI).

RESULTS

Late glucose peak (p=0.004) and monophasic glucose curve (p=0.001) were both associated with lower oDI after adjustment for age, sex, puberty stage and body mass index z-score. Among obese/severely obese adolescents with NGT, those with coexistent late glucose peak and monophasic glucose curve had lower oDI than those with early glucose peak and biphasic glucose curve (p=0.002). Moreover, a combination of late glucose peak and monophasic glucose curve was the most powerful predictor of the lowest oDI quartile [odds ratio (OR): 11.68, 95% confidence interval: 3.048-44.755, p<0.001].

CONCLUSION

Late timing of the glucose peak, monophasic shape of the glucose curve and, in particular, a combination of those characteristics during OGTT may indicate early beta-cell dysfunction in obese/severely obese adolescents with NGT.

Metabolomics analysis reveals altered metabolites in lean compared with obese adolescents and additional metabolic shifts associated with hyperinsulinaemia and insulin resistance in obese adolescents: a cross-sectional study

INTRODUCTION

Hyperinsulinaemia and insulin resistance (IR) are strongly associated with obesity and are forerunners of type 2 diabetes. Little is known about metabolic alterations separately associated with obesity, hyperinsulinaemia/IR and impaired glucose tolerance (IGT) in adolescents.

OBJECTIVES

To identify metabolic alterations associated with obesity, hyperinsulinaemia/IR and hyperinsulinaemia/IR combined with IGT in obese adolescents.

METHODS

81 adolescents were stratified into four groups based on body mass index (lean vs. obese), insulin responses (normal insulin (NI) vs. high insulin (HI)) and glucose responses (normal glucose tolerance (NGT) vs. IGT) after an oral glucose tolerance test (OGTT). The groups comprised: (1) healthy lean with NI and NGT, (2) obese with NI and NGT, (3) obese with HI and NGT, and (4) obese with HI and IGT. Targeted nuclear magnetic resonance-based metabolomics analysis was performed on fasting and seven post-OGTT plasma samples, followed by univariate and multivariate statistical analyses.

RESULTS

Two groups of metabolites were identified: (1) Metabolites associated with insulin response level: adolescents with HI (groups 3-4) had higher concentrations of branched-chain amino acids and tyrosine, and lower concentrations of serine, glycine, myo-inositol and dimethylsulfone, than adolescents with NI (groups 1-2). (2) Metabolites associated with obesity status: obese adolescents (groups 2-4) had higher concentrations of acetylcarnitine, alanine, pyruvate and glutamate, and lower concentrations of acetate, than lean adolescents (group 1).

CONCLUSIONS

Obesity is associated with shifts in fat and energy metabolism. Hyperinsulinaemia/IR in obese adolescents is also associated with increased branched-chain and aromatic amino acids.

Role of exercise on insulin sensitivity and beta-cell function: is exercise sufficient for the prevention of youth-onset type 2 diabetes?

Parallel with the current pediatric obesity epidemic, the escalating rates of youthonset type 2 diabetes mellitus (T2DM) have become a major public health burden. Although lifestyle modification can be the first-line prevention for T2DM in youths, there is a lack of evidence to establish optimal specific exercise strategies for obese youths at high risk for T2DM. The purpose of this narrative review is to summarize the potential impact of exercise on 2 key pathophysiological risk factors for T2DM, insulin sensitivity and β-cell function, among obese youths. The studies cited are grouped by use of metabolic tests, i.e., direct and indirect measures of insulin sensitivity and β-cell function. In general, there are an increasing number of studies that demonstrate positive effects of aerobic exercise, resistance exercise, and the 2 combined on insulin sensitivity. However, a lack of evidence exists for the effect of any exercise modality on β-cell functional improvement. We also suggest a future direction for research into exercise medical prevention of youth-onset T2DM. These suggestions focus on the effects of exercise modalities on emerging biomarkers of T2DM risk.

Relative Hypoxia and Early Diabetic Kidney Disease in Type 1 Diabetes

The objective of this study was to compare the ratio of renal oxygen availability (RO₂) to glomerular filtration rate (GFR), a measure of relative renal hypoxia, in adolescents with and without type 1 diabetes (T1D) and relate the ratio to albuminuria, renal plasma flow (RPF), fat mass, and insulin sensitivity (M/I). RO₂ was estimated by blood oxygen level-dependent MRI; fat mass was estimated by DXA; GFR and RPF were estimated by iohexol and p-aminohippurate clearance; albuminuria was estimated by urine albumin-to-creatinine ratio (UACR); and M/I was estimated from steady-state glucose infusion rate/insulin (mg/kg/min) by hyperglycemic clamp in 50 adolescents with T1D (age 16.1 ± 3.0 years, HbA_1c 8.6 ± 1.2%) and 20 control patients of similar BMI (age 16.1 ± 2.9 years, HbA_1c 5.2 ± 0.2%). The RO₂:GFR (ms/mL/min) was calculated as RO₂ (T2*, ms) divided by GFR (mL/min). Whole-kidney RO₂:GFR was 25% lower in adolescents with T1D versus control patients (P < 0.0001). In adolescents with T1D, lower whole-kidney RO₂:GFR was associated with higher UACR (r = -0.31, P = 0.03), RPF (r = -0.52, P = 0.0009), and fat mass (r = -0.33, P = 0.02). Lower medullary RO₂:GFR was associated with lower M/I (r = 0.31, P = 0.03). In conclusion, adolescents with T1D exhibited relative renal hypoxia that was associated with albuminuria and with increased RPF, fat mass, and insulin resistance. These data suggest a potential role of renal hypoxia in the development of diabetic kidney disease.