Postexercise Glycemic Control in Type 1 Diabetes Is Associated With Residual β-Cell Function

Insulin Resistance in Type 1 Diabetes: Pathophysiological, Clinical, and Therapeutic Relevance

People with type 1 diabetes (T1D) are usually considered to exclusively exhibit β-cell failure, but they frequently also feature insulin resistance. This review discusses the mechanisms, clinical features, and therapeutic relevance of insulin resistance by focusing mainly on human studies using gold-standard techniques (euglycemic-hyperinsulinemic clamp). In T1D, tissue-specific insulin resistance can develop early and sustain throughout disease progression. The underlying pathophysiology is complex, involving both metabolic- and autoimmune-related factors operating synergistically. Insulin treatment may play an important pathogenic role in predisposing individuals with T1D to insulin resistance. However, the established lifestyle-related risk factors and peripheral insulin administration inducing glucolipotoxicity, hyperinsulinemia, hyperglucagonemia, inflammation, mitochondrial abnormalities, and oxidative stress cannot always fully explain insulin resistance in T1D, suggesting a phenotype distinct from type 2 diabetes. The mutual interaction between insulin resistance and impaired endothelial function further contributes to diabetes-related complications. Insulin resistance should therefore be considered a treatment target in T1D. Aside from lifestyle modifications, continuous subcutaneous insulin infusion can ameliorate insulin resistance and hyperinsulinemia, thereby improving glucose toxicity compared with multiple injection insulin treatment. Among other concepts, metformin, pioglitazone, incretin-based drugs such as GLP-1 receptor agonists, sodium-glucose cotransporter inhibitors, and pramlintide can improve insulin resistance, either directly or indirectly. However, considering the current issues of high cost, side effects, limited efficacy, and their off-label status, these agents in people with T1D are not widely used in routine clinical care at present.

Predicting Hypoglycemia and Hyperglycemia Risk During and After Activity for Adolescents with Type 1 Diabetes

Objective: To predict hypoglycemia and hyperglycemia risk during and after activity for adolescents with type 1 diabetes (T1D) using real-world data from the Type 1 Diabetes Exercise Initiative Pediatric (T1DEXIP) study. Methods: Adolescents with T1D (n = 225; [mean ± SD] age = 14 ± 2 years; HbA1c = 7.1 ± 1.3%; T1D duration = 5 ± 4 years; 56% using hybrid closed loop), wearing continuous glucose monitors (CGMs), logged 3738 total activities over 10 days. Repeated Measures Random Forest (RMRF) and Repeated Measures Logistic Regression (RMLR) models were used to predict a composite risk of hypoglycemia (<70 mg/dL) and hyperglycemia (>250 mg/dL) within 2 h after starting exercise. Results: RMRF achieved high precision predicting composite risk and was more accurate than RMLR Area under the receiver operating characteristic curve (AUROC 0.737 vs. 0.661; P < 0.001). Activities with minimal composite risk had a starting glucose between 132 and 160 mg/dL and a glucose rate of change at activity start between -0.4 and -1.9 mg/dL/min. Time <70 mg/dL and time >250 mg/dL during the prior 24 h, HbA1c level, and insulin on board at activity start were also predictive. Separate models explored factors at the end of activity; activities with glucose between 128 and 133 mg/dL and glucose rate of change between 0.4 and -0.6 mg/dL/min had minimal composite risk. Conclusions: Physically active adolescents with T1D should aim to start exercise with an interstitial glucose between 130 and 160 mg/dL with a flat or slightly decreasing CGM trend to minimize risk for developing dysglycemia. Incorporating factors such as historical glucose and insulin can improve prediction modeling for the acute glucose responses to exercise.

The metabolome as a diagnostic for maximal aerobic capacity during exercise in type 1 diabetes

AIMS/HYPOTHESIS

Our aim was to characterise the in-depth metabolic response to aerobic exercise and the impact of residual pancreatic beta cell function in type 1 diabetes. We also aimed to use the metabolome to distinguish individuals with type 1 diabetes with reduced maximal aerobic capacity in exercise defined byV ˙ O 2peak .

METHODS

Thirty participants with type 1 diabetes (≥3 years duration) and 30 control participants were recruited. Groups did not differ in age or sex. After quantification of peak stimulated C-peptide, participants were categorised into those with undetectable (<3 pmol/l), low (3-200 pmol/l) or high (>200 pmol/l) residual beta cell function. Maximal aerobic capacity was assessed byV ˙ O 2peak test and did not differ between control and type 1 diabetes groups. All participants completed 45 min of incline treadmill walking (60%V ˙ O 2peak ) with venous blood taken prior to exercise, immediately post exercise and after 60 min recovery. Serum was analysed using targeted metabolomics. Metabolomic data were analysed by multivariate statistics to define the metabolic phenotype of exercise in type 1 diabetes. Receiver operating characteristic (ROC) curves were used to identify circulating metabolomic markers of maximal aerobic capacity (V ˙ O 2peak ) during exercise in health and type 1 diabetes.

RESULTS

Maximal aerobic capacity (V ˙ O 2peak ) inversely correlated with HbA1c in the type 1 diabetes group (r2=0.17, p=0.024). Higher resting serum tricarboxylic acid cycle metabolites malic acid (fold change 1.4, p=0.001) and lactate (fold change 1.22, p=1.23×10-5) differentiated people with type 1 diabetes. Higher serum acylcarnitines (AC) (AC C14:1, F value=12.25, p=0.001345; AC C12, F value=11.055, p=0.0018) were unique to the metabolic response to exercise in people with type 1 diabetes. C-peptide status differentially affected metabolic responses in serum ACs during exercise (AC C18:1, leverage 0.066; squared prediction error 3.07). The malic acid/pyruvate ratio in rested serum was diagnostic for maximal aerobic capacity (V ˙ O 2peak ) in people with type 1 diabetes (ROC curve AUC 0.867 [95% CI 0.716, 0.956]).

CONCLUSIONS/INTERPRETATION

The serum metabolome distinguishes high and low maximal aerobic capacity and has diagnostic potential for facilitating personalised medicine approaches to manage aerobic exercise and fitness in type 1 diabetes.

Exploring Factors That Influence Postexercise Glycemia in Youth With Type 1 Diabetes in the Real World: The Type 1 Diabetes Exercise Initiative Pediatric (T1DEXIP) Study

OBJECTIVE

To explore 24-h postexercise glycemia and hypoglycemia risk, data from the Type 1 Diabetes Exercise Initiative Pediatric (T1DEXIP) study were analyzed to examine factors that may influence glycemia.

RESEARCH DESIGN AND METHODS

This was a real-world observational study with participant self-reported physical activity, food intake, and insulin dosing (multiple daily injection users). Heart rate, continuous glucose data, and available pump data were collected.

RESULTS

A total of 251 adolescents (42% females), with a mean ± SD age of 14 ± 2 years, and hemoglobin A1c (HbA1c) of 7.1 ± 1.3% (54 ± 14.2 mmol/mol), recorded 3,319 activities over ∼10 days. Trends for lower mean glucose after exercise were observed in those with shorter disease duration and lower HbA1c; no difference by insulin delivery modality was identified. Larger glucose drops during exercise were associated with lower postexercise mean glucose levels, immediately after activity (P < 0.001) and 12 to <16 h later (P = 0.02). Hypoglycemia occurred on 14% of nights following exercise versus 12% after sedentary days. On nights following exercise, more hypoglycemia occurred when average total activity was ≥60 min/day (17% vs. 8% of nights, P = 0.01) and on days with longer individual exercise sessions. Higher nocturnal hypoglycemia rates were also observed in those with longer disease duration, lower HbA1c, conventional pump use, and if time below range was ≥4% in the previous 24 h.

CONCLUSIONS

In this large real-world pediatric exercise study, nocturnal hypoglycemia was higher on nights when average activity duration was higher. Characterizing both participant- and event-level factors that impact glucose in the postexercise recovery period may support development of new guidelines, decision support tools, and refine insulin delivery algorithms to better support exercise in youth with diabetes.

Integrating Physical Activity Strategies to Lower Hyperglycaemia in Structured Education Programmes for Children and Young People with Type 1 Diabetes Improves Glycaemic Control without Augmenting the Risk of Hypoglycaemia

Objectives

Investigate the effect of using short bursts of moderate-intensity activity between meals to lower hyperglycaemia on glucose metrics. Design and Methods. Children and young people with type 1 diabetes (CYPD) attending continuous glucose monitoring education were taught to use moderate-intensity activity to lower high glucose levels (to <10.0 mmol/L using 10-15 minlowers ∼2.0 mmol/L) between meals. Retrospective cross-sectional data analysis of CYPD at a single tertiary centre between 2019 and 2022. Data were collected on demographics and glucose metrics (HbA1c, time in range (TIR, 3.9-10.0 mmol/L), time above range (TAR, >10.0 mmol/L), time below range (TBR, <3.9 mmol/L)). Minutes of activity usually performed to lower a glucose level of 14.0 mmol/L trending steady at 6 months grouped the CYPD into low (<5 min), mild (5-10 min), or moderate (11-20 min) activity groups.

Results

125 (n = 53, 40% male) CYPD with a mean (standard deviations) age of 12.3 (±3.7) years and diabetes duration of 7.0 ± 3.7 years were included. HbA1c improved from 58.5 (±8.6) mmol/mol at baseline to 54.9 (±7.2) mmol/mol at 6 months (p < 0.001). Low, mild, and moderate activity was reported by 30% (n = 37), 34% (n = 43), and 36% (n = 45), respectively. At 6 months, HbA1c (52.0 vs. 54.3 vs. 59.4 mmol/mol, p < 0.001), TIR (68.0% vs. 59.71 vs. 51.1%, p < 0.001) and TAR (29.9% vs. 38.3% vs. 45.3%, p < 0.001) were significantly different across the moderate, mild, and low activity groups, respectively. No association was found for TBR (2.16% vs. 2.32% vs. 2.58%, p = 0.408) across groups.

Conclusion

Increasing the use of moderate-intensity activity to lower hyperglycaemia between meals is associated with improved glucose control without increasing hypoglycaemia for CYPD.

Exercise in adults with type 1 diabetes mellitus

Regular physical activity improves cardiometabolic and musculoskeletal health, helps with weight management, improves cognitive and psychosocial functioning, and is associated with reduced mortality related to cancer and diabetes mellitus. However, turnover rates of glucose in the blood increase dramatically during exercise, which often results in either hypoglycaemia or hyperglycaemia as well as increased glycaemic variability in individuals with type 1 diabetes mellitus (T1DM). A complex neuroendocrine response to an acute exercise session helps to maintain circulating levels of glucose in a fairly tight range in healthy individuals, while several abnormal physiological processes and limitations of insulin therapy limit the capacity of people with T1DM to exercise in a normoglycaemic state. Knowledge of the acute and chronic effects of exercise and regular physical activity is critical for the formulation of clinical strategies for the management of insulin and nutrition for active patients with T1DM. Emerging diabetes-related technologies, such as continuous glucose monitors, automated insulin delivery systems and the administration of solubilized glucagon, are demonstrating efficacy for preserving glucose homeostasis during and after exercise in this population of patients. This Review highlights the beneficial effects of regular exercise and details the complex endocrine and metabolic responses to different types of exercise for adults with T1DM. An overview of basic clinical strategies for the preservation of glucose homeostasis using emerging technologies is also provided.

Time to first optimal glycemic control and its predictors among type 1 diabetic children in Bahir Dar city public referral hospitals, North West Ethiopia: a retrospective follow up study

Background

Recognizing the level of glycemic control of a client is an important measure/tool to prevent acquiring complications and risk of death from diabetes. However, the other most important variable, which is the time that the patient stayed in that poor glycemic level before reaching optimal glycemic control, has not been studied so far. Therefore, this study aim to estimate time to first optimal glycemic control and identify predictors among type 1 diabetic children in Bahir Dar city public referral hospitals, Northwest, Ethiopia, 2021.

Methods

A Retrospective cohort study was conducted at Bahir Dar city public referral hospitals among a randomly selected sample of 385 patients with type 1 diabetes who were on follow up from January 1, 2016 to February30, 2021.Data were collected by using a data abstraction tool and then entered into Epi-data version 4.6 and exported into STATA 14.0 statistical software. Descriptive statistics, Kaplan Meier plots and median survival times, Log-rank test and Cox-proportional hazard regression were used for reporting the findings of this study. After performing Cox-proportional hazard regression, model goodness-of-fit and assumptions were checked. Finally, the association between independent variables and time to first optimal glycemic control in months was assessed using the multivariable Cox Proportional Hazard model and variables with a p-value < 0.05 were considered as statistically significant.

Results

Median survival time to first optimal glycemic control among type 1 diabetic clients was 8 months (95%CI: 6.9–8.9). The first optimal glycemic achievement rate was 8.2 (95%CI: 7.2–9.2) per 100 person/month observation. Factors that affect time to first optimal glycemic control were age > 10–14 years (AHR = 0.32;95%CI = 0.19–0.55), increased weight (AHR = 0.96;95%CI = 0.94–0.99), having primary care giver (AHR = 2.09;95%CI = 1.39–3.13), insulin dose (AHR = 1.05;95%CI = 1.03–1.08), duration of diabetes ≥4 years (AHR = 0.64;95%CI = 0.44–0.94), adherence to diabetic care (AHR = 9.72;95%CI = 6.09–15.51), carbohydrate counting (AHR = 2.43;95%CI = 1.12–5.26), and comorbidity (AHR = 0.72;95%CI = 0.53–0.98).

Conclusion

The median survival time to first optimal glycemic control in this study was long. Age, weight, primary care giver, insulin dose, duration of diabetes, adherence, and carbohydrate counting, including history of comorbidity were determinant factors. Giving attention for overweight and comorbid illness prevention, increasing either the dose or frequency of insulin during initial treatment; counseling parent (for both the mother and father) about adherence to diabetic care focusing on insulin drugs and how to audit their children’s diet as prescription helps to reduce the length of glycemic control.

Capturing the real-world benefit of residual β-cell function during clinically important time-periods in established Type 1 diabetes

AIMS

Many individuals with type 1 diabetes retain residual β-cell function, with increased endogenous insulin secretion associated with reduced hyperglycaemia, hypoglycaemia and glycaemic variability. However, it is unknown when these improvements occur during the day. Dysglycaemia is common in overnight and postprandial periods and associated with diabetes complications. Therefore, this study aimed to determine the influence of residual β-cell function upon nocturnal and postprandial glycaemic control in established type 1 diabetes.

METHODS

Under free-living conditions, 66 participants wore a blinded continuous glucose monitor (CGM), kept a food diary, and completed a stimulated urine C-peptide creatinine (UCPCR) test. Nocturnal, and postprandial CGM outcomes (participant means and discrete event analysis) were compared between UCPCR groups: undetectable (Cpep_und ), low (Cpep_low : 0.001-0.19 nmol/mmol) and high (Cpep_high : ≥0.2 nmol/mmol).

RESULTS

Greater β-cell function was associated with incremental improvements in glycaemia. Cpep_high spent significantly greater time in normoglycaemia than Cpep_und overnight (76 ± 20% vs. 58 ± 20%, p = 0.005) and 0-300 mins postprandially (68 ± 22% vs. 51 ± 22%, p = 0.045), while also having reducing nocturnal variability (SD 1.12 ± 0.41 vs. 1.52 ± 0.43 mmol/L, p = 0.010). Analysis of individual events, controlling for diabetes duration, BMI, basal insulin, use of a continuous or flash glucose monitor and (for postprandial) meal type, carbohydrate and bolus insulin intake, replicated the group findings, additionally demonstrating Cpep_und had increased hyperglycaemia versus Cpep_low overnight and increased postprandial hypoglycaemic events compared with Cpep_high . For all participants, breakfast had a significantly higher incremental area under the curve than lunch and dinner.

CONCLUSIONS

Residual β-cell function is associated with improved nocturnal and postprandial glycaemic control. These data may be of clinical importance for identifying specific periods and individuals where further glycaemic management strategies would be beneficial.

Impact of flash glucose monitoring on glycemic control varies with the age and residual β-cell function of patients with type 1 diabetes mellitus

AIMS/INTRODUCTION

We aimed to explore the clinical factors associated with glycemic variability (GV) assessed with flash glucose monitoring (FGM), and investigate the impact of FGM on glycemic control among Chinese type 1 diabetes mellitus patients in a real-life clinical setting.

MATERIALS AND METHODS

A total of 171 patients were included. GV was assessed from FGM data. A total of 110 patients wore FGM continuously for 6 months (longitudinal cohort). Hemoglobin A1c (HbA1c), fasting and 2-h postprandial C-peptide, and glucose profiles were collected. Changes in HbA1c and glycemic parameters were assessed during a 6-month FGM period.

RESULTS

Individuals with high residual C-peptide (HRCP; 2-h postprandial C-peptide >200 pmol/L) had less GV than patients with low residual C-peptide ( 2-h postprandial C-peptide ≤200 pmol/L; P < 0.001). In the longitudinal cohort (n = 110), HbA1c and mean glucose decreased, time in range (TIR) increased during the follow-up period (P < 0.05). The 110 patients were further divided into age and residual C-peptide subgroups: (i) HbA1c and mean glucose were reduced significantly only in the subgroup aged ≤14 years during the follow-up period, whereas time below range also increased in this subgroup at 3 months (P = 0.047); and (ii) HbA1c improved in the HRCP subgroup at 3 and 6 months (P < 0.05). The mean glucose decreased and TIR improved significantly in the low residual C-peptide subgroup; however, TIR was still lower and time below range was higher than those of the HRCP subgroup at all time points (P < 0.05).

CONCLUSIONS

HRCP was associated with less GV. FGM wearing significantly reduced HbA1c, especially in pediatric patients and those with HRCP. Additionally, the mean glucose and TIR were also found to improve.

Type 1 Diabetes Patients With Different Residual Beta-Cell Function but Similar Age, HBA1c, and Cardiorespiratory Fitness Have Differing Exercise-Induced Angiogenic Cell Mobilisation

BACKGROUND

Many individuals with type 1 diabetes retain residual beta-cell function. Sustained endogenous insulin and C-peptide secretion is associated with reduced diabetes related complications, but underlying mechanisms remain unclear. Lower circulating numbers of endothelial and hematopoietic progenitor cells (EPCs and HPCs), and the inability to increase the count of these cells in response to exercise, are also associated with increased diabetes complications and cardiovascular disease. It is unknown whether residual beta-cell function influences HPCs and EPCs. Thus, this study examined the influence of residual beta-cell function in type 1 diabetes upon exercise-induced changes in haematopoietic (HPCs) and endothelial progenitor cells (EPCs).

METHODS

Participants with undetectable stimulated C-peptide (n=11; Cpep_und), 10 high C-peptide (Cpep_high; >200 pmol/L), and 11 non-diabetes controls took part in this observational exercise study, completing 45 minutes of intensive walking at 60% V˙O2peak . Clinically significant HPCs (CD34⁺) and EPCs (CD34⁺VEGFR2⁺) phenotypes for predicting future adverse cardiovascular outcomes, and subsequent cell surface expression of chemokine receptor 4 (CXCR4) and 7 (CXCR7), were enumerated at rest and immediately post-exercise by flow cytometry.

RESULTS

Exercise increased HPCs and EPCs phenotypes similarly in the Cpep_high and control groups (+34-121% across phenotypes, p<0.04); but Cpep_und group did not significantly increase from rest, even after controlling for diabetes duration. Strikingly, the post-exercise Cpep_und counts were still lower than Cpep_high at rest.

CONCLUSIONS

Residual beta-cell function is associated with an intact exercise-induced HPCs and EPCs mobilisation. As key characteristics (age, fitness, HbA1c) were similar between groups, the mechanisms underpinning the absent mobilisation within those with negative C-peptide, and the vascular implications, require further investigation.

Restoring normal islet mass and function in type 1 diabetes through regenerative medicine and tissue engineering

Type 1 diabetes is characterised by autoimmune-mediated destruction of pancreatic β-cell mass. With the advent of insulin therapy a century ago, type 1 diabetes changed from a progressive, fatal disease to one that requires lifelong complex self-management. Replacing the lost β-cell mass through transplantation has proven successful, but limited donor supply and need for lifelong immunosuppression restricts widespread use. In this Review, we highlight incremental advances over the past 20 years and remaining challenges in regenerative medicine approaches to restoring β-cell mass and function in type 1 diabetes. We begin by summarising the role of endocrine islets in glucose homoeostasis and how this is altered in disease. We then discuss the potential regenerative capacity of the remaining islet cells and the utility of stem cell-derived β-like cells to restore β-cell function. We conclude with tissue engineering approaches that might improve the engraftment, function, and survival of β-cell replacement therapies.

Pancreatic islet reserve in type 1 diabetes

Type 1 diabetes (T1D) is a chronic autoimmune disease characterized by pancreatic islet β cell loss and dysfunction resulting in insulin deficiency and hyperglycemia. During a presymptomatic phase of established β cell autoimmunity, β cell loss may first be evident through assessment of β cell secretory capacity, a measure of functional β cell mass. Reduction in pancreatic islet β cell reserve eventually manifests as impaired first-phase insulin response to glucose and abnormal glucose tolerance, which progresses until the functional capacity for β cell secretion can no longer meet the demand for insulin to control glycemia. A functional β cell mass of ∼25% of normal may be required to avoid symptomatic T1D but is already associated with dysregulated glucagon secretion. With symptomatic T1D, stimulated C-peptide levels >0.60 ng/mL (0.200 pmol/mL) indicate the presence of clinically meaningful residual β cell function for contributing to glycemic control, although even higher residual C-peptide appears necessary for evidencing glucose-dependent islet β and α cell function that may contribute to maintaining (near)normal glycemia. β cell replacement by islet transplantation can restore a physiologic reserve capacity for insulin secretion, confirming thresholds for functional β cell mass required for independence from insulin therapy.

Bone turnover and metabolite responses to exercise in people with and without long-duration type 1 diabetes: a case-control study

INTRODUCTION

Exercise acutely alters markers of bone resorption and formation. As risk of fracture is increased in patients with type 1 diabetes, understanding if exercise-induced bone turnover is affected within this population is prudent. We assessed bone turnover responses to acute exercise in individuals with long-duration type 1 diabetes and matched controls.

RESEARCH DESIGN AND METHODS

Participants with type 1 diabetes (n=15; age: 38.7±13.3; glycosylated hemoglobin: 60.5±6.7 mmol/mol; diabetes duration: 19.3±11.4 years) and age-matched, fitness-matched, and body mass index-matched controls (n=15) completed 45 min of incline walking (60% peak oxygen uptake). Blood samples were collected at baseline and immediately, 30 min, and 60 min postexercise. Markers of bone resorption (β-C-terminal cross-linked telopeptide of type 1 collagen, β-CTx) and formation (procollagen type-1 amino-terminal propeptide, P1NP), parathyroid hormone (PTH), phosphate, and calcium (albumin-adjusted and ionized) were measured. Data (mean±SD) were analyzed by a mixed-model analysis of variance.

RESULTS

Baseline concentrations of P1NP and β-CTx were comparable between participants with type 1 diabetes and controls. P1NP did not change with exercise (p=0.20) but β-CTx decreased (p<0.001) in both groups, but less so in participants with type 1 diabetes compared with controls (-9.2±3.7%; p=0.02). PTH and phosphate increased immediately postexercise in both groups; only PTH was raised at 30 min postexercise (p<0.001), with no between-group differences (p>0.39). Participants with type 1 diabetes had reduced albumin and ionized calcium at all sample points (p<0.01).

CONCLUSIONS

Following exercise, participants with type 1 diabetes displayed similar time-course changes in markers of bone formation and associated metabolites, but an attenuated suppression in bone resorption. The reduced albumin and ionized calcium may have implications for future bone health. Further investigation of the interactions between type 1 diabetes, differing modalities and intensities of exercise, and bone health is warranted.