24-h energy expenditure in people with type 1 diabetes: impact on equations for clinical estimation of energy expenditure.

BACKGROUND/OBJECTIVES: Type 1 diabetes (T1D) is associated with an increase in resting metabolic rate (RMR), but the impact of T1D on other components of 24-h energy expenditure (24-h EE) is not known. Also, there is a lack of equations to estimate 24-h EE in patients with T1D. The aims of this analysis were to compare 24-h EE and its components in young adults with T1D and healthy controls across the spectrum of body mass index (BMI) and derive T1D-specific equations from clinical variables. SUBJECTS/METHODS: Thirty-three young adults with T1D diagnosed ≥1 year prior and 33 healthy controls matched for sex, age and BMI were included in this analysis. We measured 24-h EE inside a whole room indirect calorimeter (WRIC) and body composition with dual x-ray absorptiometry. RESULTS: Participants with T1D had significantly higher 24-h EE than healthy controls (T1D = 2047 ± 23 kcal/day vs control= 1908 ± 23 kcal/day; P < 0.01). We derived equations to estimate 24-h EE with both body composition (fat free mass + fat mass) and anthropometric (weight + height) models, which provided high coefficients of determination (R2 = 0.912 for both). A clinical model that did not incorporate spontaneous physical activity yielded high coefficients of determination as well (R2 = 0.897 and R2 = 0.880 for body composition and anthropometric models, respectively). CONCLUSION: These results confirm that young adults with established T1D have increased 24-h EE relative to controls without T1D. The derived equations from clinically available variables can assist clinicians with energy prescriptions for weight management in patients with T1D.

Associations of Skeletal Muscle Mass, Muscle Fat Infiltration, Mitochondrial Energetics, and Cardiorespiratory Fitness With Liver Fat Among Older Adults.

BACKGROUND: Muscle mass loss may be associated with liver fat accumulation, yet scientific consensus is lacking and evidence in older adults is scant. It is unclear which muscle characteristics might contribute to this association in older adults. METHODS: We associated comprehensive muscle-related phenotypes including muscle mass normalized to body weight (D3-creatine dilution), muscle fat infiltration (magnetic resonance imaging), carbohydrate-supported muscle mitochondrial maximal oxidative phosphorylation (respirometry), and cardiorespiratory fitness (VO2 peak) with liver fat among older adults. Linear regression models adjusted for age, gender, technician (respirometry only), daily minutes of moderate-to-vigorous physical activity, and prediabetes/diabetes status tested main effects and interactions of each independent variable with waist circumference (high: women-≥88 cm, men-≥102 cm) and gender. RESULTS: Among older adults aged 75 (interquartile range: 73, 79 years; 59.8% women), muscle mass and liver fat were not associated overall (N = 362) but were positively associated among participants with a high waist circumference (ß: 25.2; 95% confidence intervals [95% CI]: 11.7, 40.4; p = .0002; N = 160). Muscle fat infiltration and liver fat were positively associated (ß: 15.2; 95% CI: 6.8, 24.3; p = .0003; N = 378). Carbohydrate-supported maximum oxidative phosphorylation (before adjustment) and VO2 peak (after adjustment; ß: -12.9; 95% CI: -20.3, -4.8; p = .003; N = 361) were inversely associated with liver fat; adjustment attenuated the estimate for maximum oxidative phosphorylation although the point estimate remained negative (ß: -4.0; 95% CI: -11.6, 4.2; p = .32; N = 321). CONCLUSIONS: Skeletal muscle-related characteristics are metabolically relevant factors linked to liver fat in older adults. Future research should confirm our results to determine whether trials targeting mechanisms common to liver and muscle fat accumulation are warranted.

Associations of Skeletal Muscle Mass, Muscle Fat Infiltration, Mitochondrial Energetics, and Cardiorespiratory Fitness with Liver Fat Among Older Adults.

Background: Muscle mass loss may be associated with liver fat accumulation, yet scientific consensus is lacking and evidence in older adults is scant. It is unclear which muscle characteristics might contribute to this association in older adults. Methods: We associated comprehensive muscle-related phenotypes including muscle mass normalized to body weight (D 3 -creatine dilution), muscle fat infiltration (MRI), carbohydrate-supported muscle mitochondrial maximal oxidative phosphorylation (respirometry), and cardiorespiratory fitness (VO 2 peak) with liver fat among older adults. Linear regression models adjusted for age, gender, technician (respirometry only), daily minutes of moderate to vigorous physical activity, and prediabetes/diabetes status tested main effects and interactions of each independent variable with waist circumference (high: women-≥88 cm, men-≥102 cm) and gender. Results: Among older adults aged 75 (IQR 73, 79 years; 59.8% women), muscle mass and liver fat were not associated overall but were positively associated among participants with a high waist circumference (ß: 25.2; 95%CI 11.7, 40.4; p =.0002; N=362). Muscle fat infiltration and liver fat were positively associated (ß: 15.2; 95%CI 6.8, 24.3; p =.0003; N=378). Carbohydrate-supported maximum oxidative phosphorylation and VO 2 peak (adjusted ß: -12.9; 95%CI -20.3, -4.8; p =0.003; N=361) were inversely associated with liver fat; adjustment attenuated the estimate for maximum oxidative phosphorylation although the point estimate remained negative (ß: -4.0; 95%CI -11.6, 4.2; p =0.32; N=321). Conclusions: Skeletal muscle-related characteristics are metabolically relevant factors linked to liver fat in older adults. Future research should confirm our results to determine whether trials targeting mechanisms common to liver and muscle fat accumulation are warranted.

The proteome and phosphoproteome of circulating extracellular vesicle-enriched preparations are associated with characteristic clinical features in type 1 diabetes.

Introduction: There are no validated clinical or laboratory biomarkers to identify and differentiate endotypes of type 1 diabetes (T1D) or the risk of progression to chronic complications. Extracellular vesicles (EVs) have been studied as biomarkers in several different disease states but have not been well studied in T1D. Methods: As the initial step towards circulating biomarker identification in T1D, this pilot study aimed to provide an initial characterization of the proteomic and phosphoproteomic landscape of circulating EV-enriched preparations in participants with established T1D (N=10) and healthy normal volunteers (Controls) (N=7) (NCT03379792) carefully matched by age, race/ethnicity, sex, and BMI. EV-enriched preparations were obtained using EVtrap® technology. Proteins were identified and quantified by LC-MS analysis. Differential abundance and coexpression network (WGCNA), and pathway enrichment analyses were implemented. Results: The detected proteins and phosphoproteins were enriched (75%) in exosomal proteins cataloged in the ExoCarta database. A total of 181 proteins and 8 phosphoproteins were differentially abundant in participants with T1D compared to controls, including some well-known EVproteins (i.e., CD63, RAB14, BSG, LAMP2, and EZR). Enrichment analyses of differentially abundant proteins and phosphoproteins of EV-enriched preparations identified associations with neutrophil, platelet, and immune response functions, as well as prion protein aggregation. Downregulated proteins were involved in MHC class II signaling and the regulation of monocyte differentiation. Potential key roles in T1D for C1q, plasminogen, IL6ST, CD40, HLA-DQB1, HLA-DRB1, CD74, NUCB1, and SAP, are highlighted. Remarkably, WGCNA uncovered two protein modules significantly associated with pancreas size, which may be implicated in the pathogenesis of T1D. Similarly, these modules showed significant enrichment for membrane compartments, processes associated with inflammation and the immune response, and regulation of viral processes, among others. Discussion: This study demonstrates the potential of proteomic and phosphoproteomic signatures of EV-enriched preparations to provide insight into the pathobiology of T1D. The WGCNA analysis could be a powerful tool to discriminate signatures associated with different pathobiological components of the disease.

An Overview of Diet and Physical Activity for Healthy Weight in Adolescents and Young Adults with Type 1 Diabetes: Lessons Learned from the ACT1ON Consortium.

The prevalence of overweight and obesity in young people with type 1 diabetes (T1D) now parallels that of the general population. Excess adiposity increases the risk of cardiovascular disease, which is already elevated up to 10-fold in T1D, underscoring a compelling need to address weight management as part of routine T1D care. Sustainable weight management requires both diet and physical activity (PA). Diet and PA approaches must be optimized towards the underlying metabolic and behavioral challenges unique to T1D to support glycemic control throughout the day. Diet strategies for people with T1D need to take into consideration glycemic management, metabolic status, clinical goals, personal preferences, and sociocultural considerations. A major barrier to weight management in this high-risk population is the challenge of integrating regular PA with day-to-day management of T1D. Specifically, exercise poses a substantial challenge due to the increased risk of hypoglycemia and/or hyperglycemia. Indeed, about two-thirds of individuals with T1D do not engage in the recommended amount of PA. Hypoglycemia presents a serious health risk, yet prevention and treatment often necessitates the consumption of additional calories, which may prohibit weight loss over time. Exercising safely is a concern and challenge with weight management and maintaining cardiometabolic health for individuals living with T1D and many healthcare professionals. Thus, a tremendous opportunity exists to improve exercise participation and cardiometabolic outcomes in this population. This article will review dietary strategies, the role of combined PA and diet for weight management, current resources for PA and glucose management, barriers to PA adherence in adults with T1D, as well as findings and lessons learned from the Advancing Care for Type 1 Diabetes and Obesity Network (ACT1ON).

Host-diet-gut microbiome interactions influence human energy balance: a randomized clinical trial.

The gut microbiome is emerging as a key modulator of human energy balance. Prior studies in humans lacked the environmental and dietary controls and precision required to quantitatively evaluate the contributions of the gut microbiome. Using a Microbiome Enhancer Diet (MBD) designed to deliver more dietary substrates to the colon and therefore modulate the gut microbiome, we quantified microbial and host contributions to human energy balance in a controlled feeding study with a randomized crossover design in young, healthy, weight stable males and females (NCT02939703). In a metabolic ward where the environment was strictly controlled, we measured energy intake, energy expenditure, and energy output (fecal and urinary). The primary endpoint was the within-participant difference in host metabolizable energy between experimental conditions [Control, Western Diet (WD) vs. MBD]. The secondary endpoints were enteroendocrine hormones, hunger/satiety, and food intake. Here we show that, compared to the WD, the MBD leads to an additional 116 ± 56 kcals (P < 0.0001) lost in feces daily and thus, lower metabolizable energy for the host (89.5 ± 0.73%; range 84.2-96.1% on the MBD vs. 95.4 ± 0.21%; range 94.1-97.0% on the WD; P < 0.0001) without changes in energy expenditure, hunger/satiety or food intake (P > 0.05). Microbial 16S rRNA gene copy number (a surrogate of biomass) increases (P < 0.0001), beta-diversity changes (whole genome shotgun sequencing; P = 0.02), and fermentation products increase (P < 0.01) on an MBD as compared to a WD along with significant changes in the host enteroendocrine system (P < 0.0001). The substantial interindividual variability in metabolizable energy on the MBD is explained in part by fecal SCFAs and biomass. Our results reveal the complex host-diet-microbiome interplay that modulates energy balance.

Indices of hepatic steatosis and fibrosis in prediabetes and association with diabetes development in the vitamin D and type 2 diabetes study.

AIMS: Non-alcoholic fatty liver disease (NAFLD) is a common comorbidity that leads to poor outcomes in people at high risk for development of type 2 diabetes (T2D). Vitamin D is a possible mediator. In the vitamin D and type 2 diabetes study (D2d), we investigated the relationship of baseline indices of NAFLD with incident T2D and whether the effect of vitamin D on diabetes was modified by NAFLD. METHODS: Cross-sectional associations of indices of NAFLD with glycemia and vitamin D status were assessed in 3972 individuals screened for the D2d study. In those with prediabetes randomized to vitamin D or placebo (n = 2423), we examined longitudinal associations of NAFLD indices with incident T2D. We used validated non-invasive scores to assess steatosis [(hepatic steatosis index (HSI); NAFLD-liver fat score (NAFLD-LFS)] and advanced fibrosis [fibrosis-4 (FIB-4) index; AST to Platelet Ratio Index (APRI)]. RESULTS: Eighty-five percent of screened participants had likely steatosis by HSI and 71 % by NAFLD-LFS; 3 % were likely to have advanced fibrosis by FIB-4 and 1.2 % by APRI. FIB-4 indicated that 20.4 % of individuals require further follow up to assess liver health. Steatosis and fibrosis scores were higher among participants with worse glycemia. The NAFLD-LFS and APRI predicted development of diabetes (hazard ratios [95%CI] 1.35 [1.07, 1.70]; P = 0.012) and 2.36 (1.23, 4.54; P = 0.010), respectively). The effect of vitamin D on diabetes risk was not modified by baseline NAFLD indices. Individuals with likely steatosis had a smaller increase in serum 25-hydroxyvitamin D level in response to vitamin D than those without steatosis. CONCLUSIONS: The predicted high prevalence of steatosis, the need for further fibrosis workup, and the relationship between liver health and incident T2D suggest that routine screening with clinically accessible scores may be an important strategy to reduce disease burden.

Reprogramming the Human Gut Microbiome Reduces Dietary Energy Harvest.

The gut microbiome is emerging as a key modulator of host energy balance1. We conducted a quantitative bioenergetics study aimed at understanding microbial and host factors contributing to energy balance. We used a Microbiome Enhancer Diet (MBD) to reprogram the gut microbiome by delivering more dietary substrates to the colon and randomized healthy participants into a within-subject crossover study with a Western Diet (WD) as a comparator. In a metabolic ward where the environment was strictly controlled, we measured energy intake, energy expenditure, and energy output (fecal, urinary, and methane)2. The primary endpoint was the within-participant difference in host metabolizable energy between experimental conditions. The MBD led to an additional 116 ± 56 kcals lost in feces daily and thus, lower metabolizable energy for the host by channeling more energy to the colon and microbes. The MBD drove significant shifts in microbial biomass, community structure, and fermentation, with parallel alterations to the host enteroendocrine system and without altering appetite or energy expenditure. Host metabolizable energy on the MBD had quantitatively significant interindividual variability, which was associated with differences in the composition of the gut microbiota experimentally and colonic transit time and short-chain fatty acid absorption in silico. Our results provide key insights into how a diet designed to optimize the gut microbiome lowers host metabolizable energy in healthy humans.

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.

Glucagon-like peptide-1/glucagon receptor agonism associates with reduced metabolic adaptation and higher fat oxidation: A randomized trial.

OBJECTIVE: This study tested the hypothesis that treatment with the glucagon-like peptide-1/glucagon receptor agonist SAR425899 would lead to a smaller decrease in sleeping metabolic rate (SMR; kilocalories/day) than expected from the loss of lean and fat mass (metabolic adaptation). METHODS: This Phase 1b, double-blind, randomized, placebo-controlled study was conducted at two centers in inpatient metabolic wards. Thirty-five healthy males and females with overweight and obesity (age = 36.5 ± 7.1 years) were randomized to a calorie-reduced diet (-1000 kcal/d) and escalating doses (0.06-0.2 mg/d) of SAR425899 (n = 17) or placebo (n = 18) for 19 days. SMR was measured by whole-room calorimetry. RESULTS: Both groups lost weight (-3.68 ± 1.37 kg placebo; -4.83 ± 1.44 kg SAR425899). Those treated with SAR425899 lost more weight, fat mass, and fat free mass (p < 0.05) owing to a greater achieved energy deficit than planned. The SAR425899 group had a smaller reduction in body composition-adjusted SMR (p = 0.002) as compared with placebo, but not 24-hour energy expenditure. Fat oxidation and ketogenesis increased in both groups, with significantly greater increases with SAR425899 (p < 0.05). CONCLUSIONS: SAR425899 led to reduced selective metabolic adaptation and increased lipid oxidation, which are believed to be beneficial for weight loss and weight-loss maintenance.

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.

Weight management in young adults with type 1 diabetes: The advancing care for type 1 diabetes and obesity network sequential multiple assignment randomized trial pilot results.

AIMS: Co-management of weight and glycaemia is critical yet challenging in type 1 diabetes (T1D). We evaluated the effect of a hypocaloric low carbohydrate, hypocaloric moderate low fat, and Mediterranean diet without calorie restriction on weight and glycaemia in young adults with T1D and overweight or obesity. MATERIALS AND METHODS: We implemented a 9-month Sequential, Multiple Assignment, Randomized Trial pilot among adults aged 19-30 years with T1D for ≥1 year and body mass index 27-39.9 kg/m2 . Re-randomization occurred at 3 and 6 months if the assigned diet was not acceptable or not effective. We report results from the initial 3-month diet period and re-randomization statistics before shutdowns due to COVID-19 for primary [weight, haemoglobin A1c (HbA1c), percentage of time below range <70 mg/dl] and secondary outcomes [body fat percentage, percentage of time in range (70-180 mg/dl), and percentage of time below range <54 mg/dl]. Models adjusted for design, demographic and clinical covariates tested changes in outcomes and diet differences. RESULTS: Adjusted weight and HbA1c (n = 38) changed by -2.7 kg (95% CI -3.8, -1.5, P < .0001) and -0.91 percentage points (95% CI -1.5, -0.30, P = .005), respectively, while adjusted body fat percentage remained stable, on average (P = .21). Hypoglycaemia indices remained unchanged following adjustment (n = 28, P > .05). Variability in all outcomes, including weight change, was considerable (57.9% were re-randomized primarily due to loss of <2% body weight). No outcomes varied by diet. CONCLUSIONS: Three months of a diet, irrespective of macronutrient distribution or caloric restriction, resulted in weight loss while improving or maintaining HbA1c levels without increasing hypoglycaemia in adults with T1D.

Cardiorenal outcomes by indices of liver steatosis and fibrosis in individuals with type 2 diabetes and atherosclerotic cardiovascular disease: Analyses from VERTIS CV, a randomized trial of the sodium-glucose cotransporter-2 inhibitor ertugliflozin.

AIM: To conduct a post hoc analysis to explore indices of hepatic steatosis/fibrosis and cardiorenal outcomes in the VERTIS CV study. MATERIALS AND METHODS: Patients with type 2 diabetes and atherosclerotic cardiovascular (CV) disease were randomized to ertugliflozin or placebo. Liver steatosis and fibrosis were assessed post hoc using the hepatic steatosis index (HSI) and fibrosis-4 (FIB-4) index to explore associations with cardiorenal outcomes (ertugliflozin and placebo data pooled, intention-to-treat analysis set). Cardiorenal outcomes (major adverse CV events [MACE]; hospitalization for heart failure [HHF]/CV death; CV death; HHF; and a composite kidney outcome) were stratified by baseline HSI and FIB-4 quartiles (Q1-Q4). Change in liver indices and enzymes over time were assessed (for ertugliflozin vs. placebo). RESULTS: Amongst 8246 participants, the mean age was 64.4 years, body mass index 32.0 kg/m2 , HSI 44.0 and FIB-4 score 1.34. The hazard ratios (HRs) for MACE, HHF/CV death, CV death, and HHF by FIB-4 score quartile (Q4 vs. Q1) were 1.48 (95% confidence interval [CI] 1.25, 1.76), 2.0 (95% CI 1.63, 2.51), 1.85 (95% CI 1.45, 2.36), and 2.94 (95% CI 1.98, 4.37), respectively (P < 0.0001 for all). With HSI, the incidence of HHF was higher in Q4 versus Q1 (HR 1.52 [95% CI 1.07, 2.17]; P < 0.05). The kidney composite outcome did not differ across FIB-4 or HSI quartiles. Liver enzymes and HSI decreased over time with ertugliflozin. CONCLUSION: In VERTIS CV, higher FIB-4 score was associated with CV events. HSI correlated with HHF. Neither measure was associated with the composite kidney outcome. Ertugliflozin was associated with a reduction in liver enzymes and HSI.

More hypoglycemia not associated with increasing estimated adiposity in youth with type 1 diabetes.

BACKGROUND: Despite the widespread clinical perception that hypoglycemia may drive weight gain in youth with type 1 diabetes (T1D), there is an absence of published evidence supporting this hypothesis. METHODS: We estimated the body fat percentage (eBFP) of 211 youth (HbA1c 8.0-13.0%, age 13-16) at baseline, 6, and 18 months of the Flexible Lifestyles Empowering Change trial using validated equations. Group-based trajectory modeling assigned adolescents to sex-specific eBFP groups. Using baseline 7-day blinded continuous glucose monitoring data, "more" vs. "less" percent time spent in hypoglycemia was defined by cut-points using sample median split and clinical guidelines. Adjusted logistic regression estimated the odds of membership in an increasing eBFP group comparing youth with more vs. less baseline hypoglycemia. RESULTS: More time spent in clinical hypoglycemia (defined by median split) was associated with 0.29 the odds of increasing eBFP in females (95% CI: 0.12, 0.69; p = 0.005), and 0.33 the odds of stable/increasing eBFP in males (95% CI: 0.14, 0.78; p = 0.01). CONCLUSIONS: Hypoglycemia may not be a major driver of weight gain in US youth with T1D and HbA1c ≥8.0. Further studies in different sub-groups are needed to clarify for whom hypoglycemia may drive weight gain and focus future etiological studies and interventions. IMPACT: We contribute epidemiological evidence that hypoglycemia may not be a major driver of weight gain in US youth with type 1 diabetes and HbA1c ≥8.0% and highlight the need for studies to prospectively test this hypothesis rooted in clinical perception. Future research should examine the relationship between hypoglycemia and adiposity together with psychosocial, behavioral, and other clinical factors among sub-groups of youth with type 1 diabetes (i.e., who meet glycemic targets or experience a frequency/severity of hypoglycemia above a threshold) to further clarify for whom hypoglycemia may drive weight gain and progress etiological understanding of and interventions for healthy weight maintenance.

The Intestinal Microbiota and Short-Chain Fatty Acids in Association with Advanced Metrics of Glycemia and Adiposity Among Young Adults with Type 1 Diabetes and Overweight or Obesity.

Background: Comanagement of glycemia and adiposity is the cornerstone of cardiometabolic risk reduction in type 1 diabetes (T1D), but targets are often not met. The intestinal microbiota and microbiota-derived short-chain fatty acids (SCFAs) influence glycemia and adiposity but have not been sufficiently investigated in longstanding T1D. Objectives: We evaluated the hypothesis that an increased abundance of SCFA-producing gut microbes, fecal SCFAs, and intestinal microbial diversity were associated with improved glycemia but increased adiposity in young adults with longstanding T1D. Methods: Participants provided stool samples at ≤4 time points (NCT03651622: https://clinicaltrials.gov/ct2/show/NCT03651622). Sequencing of the 16S ribosomal RNA gene measured abundances of SCFA-producing intestinal microbes. GC-MS measured total and specific SCFAs (acetate, butyrate, propionate). DXA (body fat percentage and percentage lean mass) and anthropometrics (BMI) measured adiposity. Continuous glucose monitoring [percentage of time in range (70-180 mg/dL), above range (>180 mg/dL), and below range (54-69 mg/dL)] and glycated hemoglobin (i.e., HbA1c) assessed glycemia. Adjusted and Bonferroni-corrected generalized estimating equations modeled the associations of SCFA-producing gut microbes, fecal SCFAs, and intestinal microbial diversity with glycemia and adiposity. COVID-19 interrupted data collection, so models were repeated restricted to pre-COVID-19 visits. Results: Data were available for ≤45 participants at 101 visits (including 40 participants at 54 visits pre-COVID-19). Abundance of Eubacterium hallii was associated inversely with BMI (all data). Pre-COVID-19, increased fecal propionate was associated with increased percentage of time above range and reduced percentage of time in target and below range; and abundances of 3 SCFA-producing taxa (Ruminococcus gnavus, Eubacterium ventriosum, and Lachnospira) were associated inversely with body fat percentage, of which two microbes were positively associated with percentage lean mass. Abundance of Anaerostipes was associated with reduced percentage of time in range (all data) and with increased body fat percentage and reduced percentage lean mass (pre-COVID-19). Conclusions: Unexpectedly, fecal propionate was associated with detriment to glycemia, whereas most SCFA-producing intestinal microbes were associated with benefit to adiposity. Future studies should confirm these associations and determine their potential causal linkages in T1D.This study is registered at clinical.trials.gov (NCT03651622; https://clinicaltrials.gov/ct2/show/NCT03651622).

Design of the Advancing Care for Type 1 Diabetes and Obesity Network energy metabolism and sequential multiple assignment randomized trial nutrition pilot studies: An integrated approach to develop weight management solutions for individuals with type 1 diabetes.

Young adults with type 1 diabetes (T1D) often have difficulty co-managing weight and glycemia. The prevalence of overweight and obesity among individuals with T1D now parallels that of the general population and contributes to dyslipidemia, insulin resistance, and risk for cardiovascular disease. There is a compelling need to develop a program of research designed to optimize two key outcomes-weight management and glycemia-and to address the underlying metabolic processes and behavioral challenges unique to people with T1D. For an intervention addressing these dual outcomes to be effective, it must be appropriate to the unique metabolic phenotype of T1D, and to biological and behavioral responses to glycemia (including hypoglycemia) that relate to weight management. The intervention must also be safe, feasible, and accepted by young adults with T1D. In 2015, we established a consortium called ACT1ON: Advancing Care for Type 1 Diabetes and Obesity Network, a transdisciplinary team of scientists at multiple institutions. The ACT1ON consortium designed a multi-phase study which, in parallel, evaluated the mechanistic aspects of the unique metabolism and energy requirements of individuals with T1D, alongside a rigorous adaptive behavioral intervention to simultaneously facilitate weight management while optimizing glycemia. This manuscript describes the design of our integrative study-comprised of an inpatient mechanistic phase and an outpatient behavioral phase-to generate metabolic, behavioral, feasibility, and acceptability data to support a future, fully powered sequential, multiple assignment, randomized trial to evaluate the best approaches to prevent and treat obesity while co-managing glycemia in people with T1D. Clinicaltrials.gov identifiers: NCT03651622 and NCT03379792. The present study references can be found here: https://clinicaltrials.gov/ct2/show/NCT03651622 https://clinicaltrials.gov/ct2/show/NCT03379792?term=NCT03379792&draw=2&rank=1 Submission Category: "Study Design, Statistical Design, Study Protocols".

Weight Loss and Weight Regain in Usual Clinical Practice: Results From the TARGET-NASH Observational Cohort.

First-line treatment for nonalcoholic fatty liver disease (NAFLD) focuses on weight loss through lifestyle modifications.1,2 Weight loss ≥5% results in reduction of steatosis and weight loss ≥10% has been associated with improvement in hepatic inflammation and fibrosis.3 The incidence and sustainability of weight loss among patients with NAFLD were estimated and associating factors identified.

Twenty-four hour assessments of substrate oxidation reveal differences in metabolic flexibility in type 2 diabetes that are improved with aerobic training.

AIMS/HYPOTHESIS: The aim of this study was to assess metabolic flexibility (MetFlex) in participants with type 2 diabetes within the physiologically relevant conditions of sleeping, the post-absorptive (fasting) state and during meals using 24 h whole-room indirect calorimetry (WRIC) and to determine the impact of aerobic training on these novel features of MetFlex. METHODS: Normal-weight, active healthy individuals (active; n = 9), obese individuals without type 2 diabetes (ND; n = 9) and obese individuals with type 2 diabetes (n = 23) completed baseline metabolic assessments. The type 2 diabetes group underwent a 10 week supervised aerobic training intervention and repeated the metabolic assessments. MetFlex was assessed by indirect calorimetry in response to insulin infusion and during a 24 h period in a whole-room indirect calorimeter. Indices of MetFlex evaluated by WRIC included mean RQ and RQ kinetic responses after ingesting a standard high-carbohydrate breakfast (RQBF) and sleep RQ (RQsleep). Muscle mitochondrial energetics were assessed in the vastus lateralis muscle in vivo and ex vivo using 31P-magnetic resonance spectroscopy and high-resolution respirometry, respectively. RESULTS: The three groups had significantly different RQsleep values (active 0.823 ± 0.04, ND 0.860 ± 0.01, type 2 diabetes 0.842 ± 0.03; p < 0.05). The active group had significantly faster RQBF and more stable RQsleep responses than the ND and type 2 diabetes groups, as demonstrated by steeper and flatter slopes, respectively. Following the training intervention, the type 2 diabetes group displayed significantly increased RQBF slope. Several indices of RQ kinetics had significant associations with in vivo and ex vivo muscle mitochondrial capacities. CONCLUSIONS/INTERPRETATION: Twenty-four hour WRIC revealed that physiological RQ responses exemplify differences in MetFlex across a spectrum of metabolic health and correlated with skeletal muscle mitochondrial energetics. Defects in certain features of MetFlex were improved with aerobic training, emphasising the need to assess multiple aspects of MetFlex and disentangle insulin resistance from MetFlex in type 2 diabetes. TRIAL REGISTRATION: ClinicalTrials.gov NCT01911104. FUNDING: This study was funded by the ADA (grant no. 7-13-JF-53).

Reliability of measurements of energy expenditure and substrate oxidation using whole-room indirect calorimetry.

OBJECTIVE: This analysis aimed to measure the intraparticipant reliability-the intraclass correlation coefficient-of all the components of daily energy expenditure (EE) (24-hour EE, sleep EE, resting EE, basal EE, and thermic effect of food) over a period of 3 consecutive days in 35 study participants. METHODS: The components of daily EE and substrate use (respiratory exchange ratio) were measured over 3 consecutive days before and after a 3-week 1,000-kcal/d caloric restriction/weight-loss intervention. RESULTS: There was a high degree of reliability for sleep EE (96.8%), 24-hour EE (97.8%), basal EE (90.6%), and resting EE (93.2%) during the run-in period. The intraclass correlation coefficient for the follow-up period after weight loss (3.67 ± 1.10 kg) remained high for sleep EE (95.6%), 24-hour EE (100%), basal EE (96.1%), and resting EE (92.5%). The minimal detectable differences in EE were reduced by 30% for both 24-hour EE and sleep EE when comparing 2 days versus 1 day spent in the whole-room indirect calorimeter. CONCLUSIONS: The reliability of the daily components of EE is very high both prior to and after a weight-loss intervention. We here provide instrumental data for investigators to adequately power studies investigating energy metabolism using whole-room indirect calorimetry.

Energy intake as a short-term biomarker for weight loss in adults with obesity receiving liraglutide: A randomized trial.

BACKGROUND AND OBJECTIVE: Obesity is a chronic disease associated with many serious comorbidities. Pharmacologic therapies are approved for the treatment of obesity; however, short-term biomarkers to predict weight loss are not well understood. This study aimed to determine the ability of single-meal energy intake (EI) to predict weight loss in participants with obesity treated with liraglutide. METHODS: In this randomized, double-blind, placebo-controlled study, participants received subcutaneous liraglutide (titrated to 3.0 mg/day) or placebo once daily, with inpatient assessments at baseline and weeks 3 and 6. The primary endpoint was change from baseline (CFB) in EI during consecutive ad libitum lunch meals at weeks 3 and 6. Secondary endpoints included CFB in 24- and 48-h EI, weight, appetite scores, and gastric emptying measures. RESULTS: Sixty-one participants were randomized (n = 32, liraglutide; n = 29, placebo). The least squares mean (LSM) difference (95% CI; p-value) in CFB in EI during ad libitum lunch meals between the liraglutide and placebo groups was -236 (-322, -149; p < 0.0001) kcal at week 3 and -244 (-339, -148, p < 0.0001) kcal at week 6. The liraglutide group experienced significant weight loss at weeks 3 and 6, compared with placebo. Weight loss was significantly correlated with EI, but not with appetite score or gastric emptying. CONCLUSIONS: EI during a single meal is a robust clinical predictor of weight changes in participants with obesity. Future clinical trials can utilize EI at a single meal as a predictor of weight loss.