Identification of clinically relevant dysglycemia phenotypes based on continuous glucose monitoring data from youth with type 1 diabetes and elevated hemoglobin A1c

Background/Objective: To identify and characterize subgroups of adolescents with type 1 diabetes (T1D) and elevated hemoglobin A1c (HbA1c) who share patterns in their continuous glucose monitoring (CGM) data as “dysglycemia phenotypes.”. Methods: Data were analyzed from the Flexible Lifestyles Empowering Change randomized trial. Adolescents with T1D (13-16 years, duration >1 year) and HbA1c 8% to 13% (64-119 mmol/mol) wore blinded CGM at baseline for 7 days. Participants were clustered based on eight CGM metrics measuring hypoglycemia, hyperglycemia, and glycemic variability. Clusters were characterized by their baseline features and 18 months changes in HbA1c using adjusted mixed effects models. For comparison, participants were stratified by baseline HbA1c (≤/>9.0% [75 mmol/mol]). Results: The study sample included 234 adolescents (49.8% female, baseline age 14.8 ± 1.1 years, baseline T1D duration 6.4 ± 3.7 years, baseline HbA1c 9.6% ± 1.2%, [81 ± 13 mmol/mol]). Three Dysglycemia Clusters were identified with significant differences across all CGM metrics (P <.001). Dysglycemia Cluster 3 (n = 40, 17.1%) showed severe hypoglycemia and glycemic variability with moderate hyperglycemia and had a lower baseline HbA1c than Clusters 1 and 2 (P <.001). This cluster showed increases in HbA1c over 18 months (p-for-interaction = 0.006). No other baseline characteristics were associated with Dysglycemia Clusters. High HbA1c was associated with lower pump use, greater insulin doses, more frequent blood glucose monitoring, lower motivation, and lower adherence to diabetes self-management (all P <.05). Conclusions: There are subgroups of adolescents with T1D for which glycemic control is challenged by different aspects of dysglycemia. Enhanced understanding of demographic, behavioral, and clinical characteristics that contribute to CGM-derived dysglycemia phenotypes may reveal strategies to improve treatment

Associations of Dietary Intake with the Intestinal Microbiota and Short-Chain Fatty Acids Among Young Adults with Type 1 Diabetes and Overweight or Obesity

Background: Diet, a key component of type 1 diabetes (T1D) management, modulates the intestinal microbiota and its metabolically active byproducts—including SCFA—through fermentation of dietary carbohydrates such as fiber. However, the diet–microbiome relationship remains largely unexplored in longstanding T1D. Objectives: We evaluated whether increased carbohydrate intake, including fiber, is associated with increased SCFA-producing gut microbes, SCFA, and intestinal microbial diversity among young adults with longstanding T1D and overweight or obesity. Methods: Young adult men and women with T1D for ≥1 y, aged 19–30 y, and BMI of 27.0–39.9 kg/m2 at baseline provided stool samples at baseline and 3, 6, and 9 mo of a randomized dietary weight loss trial. Diet was assessed by 1–2 24-h recalls. The abundance of SCFA-producing microbes was measured using 16S rRNA gene sequencing. GC-MS measured fecal SCFA (acetate, butyrate, propionate, and total) concentrations. Adjusted and Bonferroni-corrected generalized estimating equations modeled associations of dietary fiber (total, soluble, and pectins) and carbohydrate (available carbohydrate, and fructose) with microbiome-related outcomes. Primary analyses were restricted to data collected before COVID-19 interruptions. Results: Fiber (total and soluble) and carbohydrates (available and fructose) were positively associated with total SCFA and acetate concentrations (n = 40 participants, 52 visits). Each 10 g/d of total and soluble fiber intake was associated with an additional 8.8 μmol/g (95% CI: 4.5, 12.8 μmol/g; P = 0.006) and 24.0 μmol/g (95% CI: 12.9, 35.1 μmol/g; P = 0.003) of fecal acetate, respectively. Available carbohydrate intake was positively associated with SCFA producers Roseburia and Ruminococcus gnavus. All diet variables except pectin were inversely associated with normalized abundance of Bacteroides and Alistipes. Fructose was inversely associated with Akkermansia abundance. Conclusions: In young adults with longstanding T1D, fiber and carbohydrate intake were associated positively with fecal SCFA but had variable associations with SCFA-producing gut microbes. Controlled feeding studies should determine whether gut microbes and SCFA can be directly manipulated in T1D

Dietary intake and risk of non-severe hypoglycemia in adolescents with type 1 diabetes

Aims To determine the association between dietary intake and risk of non-severe hypoglycemia in adolescents with type 1 diabetes. Methods Type 1 adolescents from a randomized trial wore a blinded continuous glucose monitoring (CGM) system at baseline for one week in free-living conditions. Dietary intake was calculated as the average from two 24-h dietary recalls. Non-severe hypoglycemia was defined as having blood glucose < 70 mg/dL for ≥ 10 min but not requiring external assistance, categorized as daytime and nocturnal (11 PM–7AM). Data were analyzed using logistic regression models. Results Among 98 participants with 14,277 h of CGM data, 70 had daytime hypoglycemia, 66 had nocturnal hypoglycemia, 55 had both, and 17 had neither. Soluble fiber and protein intake were positively associated with both daytime and nocturnal hypoglycemia. Glycemic index, monounsaturated fat, and polyunsaturated fat were negatively associated with daytime hypoglycemia only. Adjusting for total daily insulin dose per kilogram eliminated all associations. Conclusions Dietary intake was differentially associated with daytime and nocturnal hypoglycemia. Over 80% of type 1 adolescents had hypoglycemia in a week, which may be attributed to the mismatch between optimal insulin dose needed for each meal and actually delivered insulin dose without considering quality of carbohydrate and nutrients beyond carbohydrate

Associations of disordered eating with the intestinal microbiota and short-chain fatty acids among young adults with type 1 diabetes

Background and aims: Disordered eating (DE) in type 1 diabetes (T1D) includes insulin restriction for weight loss with serious complications. Gut microbiota-derived short chain fatty acids (SCFA) may benefit host metabolism but are reduced in T1D. We evaluated the hypothesis that DE and insulin restriction were associated with reduced SCFA-producing gut microbes, SCFA, and intestinal microbial diversity in adults with T1D. Methods and results: We collected stool samples at four timepoints in a hypothesis-generating gut microbiome pilot study ancillary to a weight management pilot in young adults with T1D. 16S ribosomal RNA gene sequencing measured the normalized abundance of SCFA-producing intestinal microbes. Gas-chromatography mass-spectrometry measured SCFA (total, acetate, butyrate, and propionate). The Diabetes Eating Problem Survey—Revised (DEPS-R) assessed DE and insulin restriction. Covariate-adjusted and Bonferroni-corrected generalized estimating equations modeled the associations. COVID-19 interrupted data collection, so models were repeated restricted to pre-COVID-19 data. Data were available for 45 participants at 109 visits, which included 42 participants at 65 visits pre-COVID-19. Participants reported restricting insulin “At least sometimes” at 53.3% of visits. Pre-COVID-19, each 5-point DEPS-R increase was associated with a −0.34 (95% CI -0.56, −0.13, p = 0.07) lower normalized abundance of genus Anaerostipes; and the normalized abundance of Lachnospira genus was −0.94 (95% CI -1.5, −0.42), p = 0.02 lower when insulin restriction was reported “At least sometimes” compared to “Rarely or Never”. Conclusion: DE and insulin restriction were associated with a reduced abundance of SCFA-producing gut microbes pre-COVID-19. Additional studies are needed to confirm these associations to inform microbiota-based therapies in T1D

Consensus recommendations for the use of automated insulin delivery technologies in clinical practice

The significant and growing global prevalence of diabetes continues to challenge people with diabetes (PwD), healthcare providers, and payers. While maintaining near-normal glucose levels has been shown to prevent or delay the progression of the long-term complications of diabetes, a significant proportion of PwD are not attaining their glycemic goals. During the past 6 years, we have seen tremendous advances in automated insulin delivery (AID) technologies. Numerous randomized controlled trials and real-world studies have shown that the use of AID systems is safe and effective in helping PwD achieve their long-term glycemic goals while reducing hypoglycemia risk. Thus, AID systems have recently become an integral part of diabetes management. However, recommendations for using AID systems in clinical settings have been lacking. Such guided recommendations are critical for AID success and acceptance. All clinicians working with PwD need to become familiar with the available systems in order to eliminate disparities in diabetes quality of care. This report provides much-needed guidance for clinicians who are interested in utilizing AIDs and presents a comprehensive listing of the evidence payers should consider when determining eligibility criteria for AID insurance coverage

A decade of disparities in diabetes technology use and HbA_1c in pediatric type 1 diabetes: A transatlantic comparison.

OBJECTIVE: As diabetes technology use in youth increases worldwide, inequalities in access may exacerbate disparities in hemoglobin A1c (HbA1c). We hypothesized that an increasing gap in diabetes technology use by socioeconomic status (SES) would be associated with increased HbA1c disparities. RESEARCH DESIGN AND METHODS: Participants aged &lt;18 years with diabetes duration ≥1 year in the Type 1 Diabetes Exchange (T1DX, U.S., n = 16,457) and Diabetes Prospective Follow-up (DPV, Germany, n = 39,836) registries were categorized into lowest (Q1) to highest (Q5) SES quintiles. Multiple regression analyses compared the relationship of SES quintiles with diabetes technology use and HbA1c from 2010-2012 to 2016-2018. RESULTS: HbA1c was higher in participants with lower SES (in 2010-2012 and 2016-2018, respectively: 8.0% and 7.8% in Q1 and 7.6% and 7.5% in Q5 for DPV; 9.0% and 9.3% in Q1 and 7.8% and 8.0% in Q5 for T1DX). For DPV, the association between SES and HbA1c did not change between the two time periods, whereas for T1DX, disparities in HbA1c by SES increased significantly (P &lt; 0.001). After adjusting for technology use, results for DPV did not change, whereas the increase in T1DX was no longer significant. CONCLUSIONS: Although causal conclusions cannot be drawn, diabetes technology use is lowest and HbA1c is highest in those of the lowest SES quintile in the T1DX, and this difference for HbA1c broadened in the past decade. Associations of SES with technology use and HbA1c were weaker in the DPV registry

The Importance of Office Blood Pressure Measurement Frequency and Methodology in Evaluating the Prevalence of Hypertension in Children and Adolescents With Type 1 Diabetes: The SWEET International Database

OBJECTIVE: The prevalence of hypertension is higher in children and adolescents with type 1 diabetes (T1D) compared with those without. This retrospective analysis of a large cohort of children and adolescents with T1D from the SWEET (Better control in Pediatric and Adolescent diabeteS: Working to crEate CEnTers of Reference) international consortium of pediatric diabetes centers aimed to 1) estimate the prevalence of elevated office blood pressure (BP) and hypertension and 2) investigate the influence of BP measurement methodology on the prevalence of hypertension. RESEARCH DESIGN AND METHODS: A total of 27,120 individuals with T1D, aged 5-18 years, were analyzed. Participants were grouped into those with BP measurements at three or more visits (n = 10,440) and fewer than 3 visits (n = 16,680) per year and stratified by age and sex. A subgroup analysis was performed on 15,742 individuals from centers providing a score indicating BP measurement accuracy. RESULTS: Among participants with BP measurement at three or more visits, the prevalence of hypertension was lower compared with those with fewer than three visits (10.8% vs. 17.5% P &lt; 0.001), whereas elevated BP and normotension were higher (17.5% and 71.7% vs. 15.3% and 67.1%, respectively; both P &lt; 0.001). The prevalence of hypertension and elevated BP was higher in individuals aged ≥13 years than in younger ones (P &lt; 0.001) and in male than female participants (P &lt; 0.001). In linear regression models, systolic and diastolic BP was independently determined by the BP measurement methodology. CONCLUSIONS: The estimated prevalence of elevated BP and hypertension in children and adolescents with T1D is ∼30% and depends on the BP measurement methodology. Less frequent BP evaluation may overestimate the prevalence of hypertension. © 2022 by the American Diabetes Association

Urinary proteomic diagnosis of coronary artery disease: identification and clinical validation in 623 individuals

Objectives We studied the urinary proteome in a total of 623 individuals with and without coronary artery disease (CAD) in order to characterize multiple biomarkers that enable prediction of the presence of CAD. Methods Urine samples were analyzed by capillary electrophoresis coupled online to micro time-of-flight mass spectrometry. Results We defined a pattern of 238 CAD-specific polypeptides from comparison of 586 spot urine samples from 408 individuals. This pattern identified patients with CAD in a blinded cohort of 138 urine samples (71 patients with CAD and 67 healthy individuals) with high sensitivity and specificity (area under the receiver operator characteristic curve 87%, 95% confidence interval 81-92) and was superior to previously developed 15-marker (area under the receiver operator characteristic curve 68%, P &lt; 0.0001) and 17-marker panels (area under the receiver operator characteristic curve 77%, P &lt; 0.0001). The sequences of the discriminatory polypeptides include fragments of alpha-1-antitrypsin, collagen types 1 and 3, granin-like neuroendocrine peptide precursor, membrane-associated progesterone receptor component 1, sodium/potassium-transporting ATPase gamma chain and fibrinogen-alpha chain. Several biomarkers changed significantly toward the healthy signature following 2-year treatment with irbesartan, whereas short-term treatment with irbesartan did not significantly affect the polypeptide pattern. Conclusion Urinary proteomics identifies CAD with high confidence and might also be useful for monitoring the effects of therapeutic interventions