Oral histidine affects gut microbiota and MAIT cells improving glycemic control in type 2 diabetes patients.

Amino acids, metabolized by host cells as well as commensal gut bacteria, have signaling effects on host metabolism. Oral supplementation of the essential amino acid histidine has been shown to exert metabolic benefits. To investigate whether dietary histidine aids glycemic control, we performed a case-controlled parallel clinical intervention study in participants with type 2 diabetes (T2D) and healthy controls. Participants received oral histidine for seven weeks. After 2 weeks of histidine supplementation, the microbiome was depleted by antibiotics to determine the microbial contribution to histidine metabolism. We assessed glycemic control, immunophenotyping of peripheral blood mononucelar cells (PBMC), DNA methylation of PBMCs and fecal gut microbiota composition. Histidine improves several markers of glycemic control, including postprandial glucose levels with a concordant increase in the proportion of MAIT cells after two weeks of histidine supplementation. The increase in MAIT cells was associated with changes in gut microbial pathways such as riboflavin biosynthesis and epigenetic changes in the amino acid transporter SLC7A5. Associations between the microbiome and MAIT cells were replicated in the MetaCardis cohort. We propose a conceptual framework for how oral histidine may affect MAIT cells via altered gut microbiota composition and SLC7A5 expression in MAIT cells directly and thereby influencing glycemic control. Future studies should focus on the role of flavin biosynthesis intermediates and SLC7A5 modulation in MAIT cells to modulate glycemic control.

Higher fibre and lower carbohydrate intake are associated with favourable CGM metrics in a cross-sectional cohort of 470 individuals with type 1 diabetes.

AIMS/HYPOTHESIS: The aim of this work was to investigate the association between macronutrient intakes and continuous glucose monitoring (CGM) metrics in individuals with type 1 diabetes. METHODS: In 470 individuals with type 1 diabetes of the GUTDM1 cohort (65% female, median age 40 [IQR 28-53] years, median diabetes duration 15 [IQR 6-29] years), we used logistic regression to establish associations between macronutrient intakes and the CGM metrics time in range (TIR, time spent between 3.9-10.0 mmol/l blood glucose, optimally set at ≥70%) and time below range (TBR, <3.9 mmol/l blood glucose, optimally set at <4%). ORs were expressed per 1 SD intake of nutrient and were adjusted for other macronutrient intakes, age, sex, socioeconomic status, BMI, duration of type 1 diabetes, pump use, insulin dose and alcohol intake. RESULTS: The median (IQR) TIR was 67 (51-80)% and TBR was 2 (1-4)%; the mean ± SD energy intake was 6879±2001 kJ, fat intake 75±31 g, carbohydrate intake 162±63 g, fibre intake 20±9 g and protein intake 70±24 g. A higher fibre intake and a lower carbohydrate intake were associated with higher odds of having a TIR≥70% (OR [95% CI] 1.64 [1.22, 2.24] and 0.67 [0.51, 0.87], respectively), whereas solely a higher carbohydrate intake was associated with TBR<4% (OR 1.34 [95% CI 1.02, 1.78]). CONCLUSIONS/INTERPRETATION: A higher fibre intake is independently associated with a higher TIR. A higher carbohydrate intake is associated with less time spent in hypoglycaemia, a lower TIR and a higher time above range. These findings warrant confirmatory (interventional) investigations and may impact current nutritional guidelines for type 1 diabetes.

Risk of perioperative discontinuation of SGLT2 inhibitors.

When sodium-glucose cotransporter-2 (SGLT2) inhibitors were primarily prescribed for treatment of diabetes mellitus, guidelines recommended withholding SGLT2 inhibitors before surgery to mitigate the associated risk of ketoacidosis. However, currently, SGLT2 inhibitors are an established therapy for patients with heart failure, and there is evidence that withholding SGLT2 inhibitors can worsen these patients' cardiovascular risk profile. We present an updated risk-benefit analysis of withholding SGLT2 inhibitors before surgery, focusing on patients with heart failure and addressing the risk of ketoacidosis and its treatment in these patients. Clinicians should consider perioperative continuation of SGLT2 inhibitors when prescribed for treatment of heart failure.

Associations between diabetes-related genetic risk scores and residual beta cell function in type 1 diabetes: the GUTDM1 study.

AIMS/HYPOTHESIS: Use of genetic risk scores (GRS) may help to distinguish between type 1 diabetes and type 2 diabetes, but less is known about whether GRS are associated with disease severity or progression after diagnosis. Therefore, we tested whether GRS are associated with residual beta cell function and glycaemic control in individuals with type 1 diabetes. METHODS: Immunochip arrays and TOPMed were used to genotype a cross-sectional cohort (n=479, age 41.7 ± 14.9 years, duration of diabetes 16.0 years [IQR 6.0-29.0], HbA1c 55.6 ± 12.2 mmol/mol). Several GRS, which were originally developed to assess genetic risk of type 1 diabetes (GRS-1, GRS-2) and type 2 diabetes (GRS-T2D), were calculated. GRS-C1 and GRS-C2 were based on SNPs that have previously been shown to be associated with residual beta cell function. Regression models were used to investigate the association between GRS and residual beta cell function, assessed using the urinary C-peptide/creatinine ratio, and the association between GRS and continuous glucose monitor metrics. RESULTS: Higher GRS-1 and higher GRS-2 both showed a significant association with undetectable UCPCR (OR 0.78; 95% CI 0.69, 0.89 and OR 0.84: 95% CI 0.75, 0.93, respectively), which were attenuated after correction for sex and age of onset (GRS-2) and disease duration (GRS-1). Higher GRS-C2 was associated with detectable urinary C-peptide/creatinine ratio (≥0.01 nmol/mmol) after correction for sex and age of onset (OR 6.95; 95% CI 1.19, 40.75). A higher GRS-T2D was associated with less time below range (TBR) (OR for TBR<4% 1.41; 95% CI 1.01 to 1.96) and lower glucose coefficient of variance (ß -1.53; 95% CI -2.76, -0.29). CONCLUSIONS/INTERPRETATION: Diabetes-related GRS are associated with residual beta cell function in individuals with type 1 diabetes. These findings suggest some genetic contribution to preservation of beta cell function.

Novel Proteome Targets Marking Insulin Resistance in Metabolic Syndrome.

CONTEXT/OBJECTIVE: In order to better understand which metabolic differences are related to insulin resistance in metabolic syndrome (MetSyn), we used hyperinsulinemic-euglycemic (HE) clamps in individuals with MetSyn and related peripheral insulin resistance to circulating biomarkers. DESIGN/METHODS: In this cross-sectional study, HE-clamps were performed in treatment-naive men (n = 97) with MetSyn. Subjects were defined as insulin-resistant based on the rate of disappearance (Rd). Machine learning models and conventional statistics were used to identify biomarkers of insulin resistance. Findings were replicated in a cohort with n = 282 obese men and women with (n = 156) and without (n = 126) MetSyn. In addition to this, the relation between biomarkers and adipose tissue was assessed by nuclear magnetic resonance imaging. RESULTS: Peripheral insulin resistance is marked by changes in proteins related to inflammatory processes such as IL-1 and TNF-receptor and superfamily members. These proteins can distinguish between insulin-resistant and insulin-sensitive individuals (AUC = 0.72 ± 0.10) with MetSyn. These proteins were also associated with IFG, liver fat (rho 0.36, p = 1.79 × 10-9) and visceral adipose tissue (rho = 0.35, p = 6.80 × 10-9). Interestingly, these proteins had the strongest association in the MetSyn subgroup compared to individuals without MetSyn. CONCLUSIONS: MetSyn associated with insulin resistance is characterized by protein changes related to body fat content, insulin signaling and pro-inflammatory processes. These findings provide novel targets for intervention studies and should be the focus of future in vitro and in vivo studies.

Combination therapy for kidney disease in people with diabetes mellitus.

Diabetic kidney disease (DKD), defined as co-existing diabetes and chronic kidney disease in the absence of other clear causes of kidney injury, occurs in approximately 20-40% of patients with diabetes mellitus. As the global prevalence of diabetes has increased, DKD has become highly prevalent and a leading cause of kidney failure, accelerated cardiovascular disease, premature mortality and global health care expenditure. Multiple pathophysiological mechanisms contribute to DKD, and single lifestyle or pharmacological interventions have shown limited efficacy at preserving kidney function. For nearly two decades, renin-angiotensin system inhibitors were the only available kidney-protective drugs. However, several new drug classes, including sodium glucose cotransporter-2 inhibitors, a non-steroidal mineralocorticoid antagonist and a selective endothelin receptor antagonist, have now been demonstrated to improve kidney outcomes in people with type 2 diabetes mellitus. In addition, emerging preclinical and clinical evidence of the kidney-protective effects of glucagon-like-peptide-1 receptor agonists has led to the prospective testing of these agents for DKD. Research and clinical efforts are geared towards using therapies with potentially complementary efficacy in combination to safely halt kidney disease progression. As more kidney-protective drugs become available, the outlook for people living with DKD should improve in the next few decades.

Kidney Energetics and Cyst Burden in Autosomal Dominant Polycystic Kidney Disease: A Pilot Study.

RATIONALE & OBJECTIVE: In this pilot study, we hypothesized that autosomal dominant polycystic kidney disease (ADPKD) is characterized by impaired kidney oxidative metabolism that associates with kidney size and cyst burden. STUDY DESIGN: Cross-sectional study. SETTING & PARTICIPANTS: Twenty adults with ADPKD (age, 31±6 years; 65% women; body mass index [BMI], 26.8 [22.7-30.4] kg/m2; estimated glomerular filtration rate [eGFR, 2021 CKD-EPI creatinine], 103±18mL/min/1.73m2; height-adjusted total kidney volume [HTKV], 731±370mL/m; Mayo classifications 1B [5%], 1C [42%], 1D [21%], and 1E [32%]) and 11 controls in normal weight category (NWC) (age, 25±3 years; 45% women; BMI, 22.5 [21.7-24.2] kg/m2; eGFR, 113±15mL/min/1.73m2; HTKV, 159±31mL/m) at the University of Colorado Anschutz Medical Campus. PREDICTORS: ADPKD status (yes/no) and severity (Mayo classifications). OUTCOME: HTKV and cyst burden by magnetic resonance imaging, kidney oxidative metabolism, and perfusion by 11C-acetate positron emission tomography/computed tomography, insulin sensitivity by hyperinsulinemic-euglycemic clamps (presented as ratio of M-value of steady state insulin concentration [M/I]). ANALYTICAL APPROACH: For categorical variables, χ2/Fisher's exact tests, and for continuous variables t tests/Mann-Whitney U tests. Pearson correlation was used to estimate the relationships between variables. RESULTS: Compared with NWC individuals, the participants with ADPKD exhibited lower mean±SD M/I ratio (0.586±0.205 vs 0.424±0.171 [mg/kg lean/min]/(µIU/mL), P=0.04), lower median cortical perfusion (1.93 [IQR, 1.80-2.09] vs 0.68 [IQR, 0.47-1.04] mL/min/g, P<0.001) and lower median total kidney oxidative metabolism (0.17 [IQR, 0.16-0.19] vs. 0.14 [IQR, 0.12-0.15] min-1, P=0.001) in voxel-wise models excluding cysts. HTKV correlated inversely with cortical perfusion (r: -0.83, P < 0.001), total kidney oxidative metabolism (r: -0.61, P<0.001) and M/I (r: -0.41, P = 0.03). LIMITATIONS: Small sample size and cross-sectional design. CONCLUSIONS: Adults with ADPKD and preserved kidney function exhibited impaired renal perfusion and kidney oxidative metabolism across a wide range of cysts and kidney enlargements. FUNDING: Grants from government (National Institutes of Health, Centers for Disease Control and Prevention) and not-for-profit (JDRF) entities. TRIAL REGISTRATION: Registered at ClinicalTrials.gov with study numbers NCT04407481 and NCT04074668. PLAIN-LANGUAGE SUMMARY: In our study, we explored how a common genetic kidney condition, autosomal dominant polycystic kidney disease (ADPKD), relates to kidney metabolism. ADPKD leads to the growth of numerous cysts in the kidneys, which can impact their ability to work properly. We wanted to understand the kidneys' ability to process oxygen and blood flow in ADPKD. Our approach involved using advanced imaging techniques to observe kidney metabolism and blood flow in people with ADPKD compared with healthy individuals. We discovered that those with ADPKD had significant changes in kidney oxygen metabolism even when their kidney function was still normal. These findings are crucial as they provide deeper insights into ADPKD, potentially guiding future treatments to target these changes.

Prevalence and predictive features of metabolic dysfunction-associated steatotic liver disease in type 1 diabetes.

AIMS/HYPOTHESIS: The prevalence and severity of metabolic dysfunction-associated steatotic liver disease (MASLD) in type 1 diabetes remain unclear. Therefore, we investigated the prevalence and severity of MASLD in type 1 diabetes and assessed which clinical features are most important in predicting MASLD severity. METHODS: A total of 453 individuals with type 1 diabetes (41.6 ± 15.0 years, 64% female, body mass index [BMI] 25.4 ± 4.2 kg/m2, and HbA1c 55.6 ± 12 mmol/mol) underwent vibration-controlled transient elastography (VCTE), with a controlled attenuation parameter (CAP) score for steatosis (≥280.0 dB/m) and a liver stiffness measurement (LMS) for fibrosis (≥8.0 kPa). A machine learning Extra-Trees classification model was performed to assess the predictive power of the clinical features associated with type 1 diabetes with respect to steatosis and fibrosis. RESULTS: The prevalence of hepatic steatosis and fibrosis was 9.5% (95% CI, 6.8-12.2) and 3.5% (95% CI, 1.8-5.2). Higher LMS was associated with a longer duration of type 1 diabetes (median 30.5 [IQR 18.0-39.3] years vs 15.0 [IQR 6.0-27.0] years), and individuals were older, had a higher BMI (mean 27.8 ± 5.2 vs 25.3 ± 4.1 kg/m2), and a higher CAP score (mean 211.4 ± 51.7 dB/m vs 241.4 ± 75.6 dB/m). The most important predictive features of fibrosis were duration of type 1 diabetes, age, and systolic blood pressure, with a mean ± SD area under the curve of 0.73 ± 0.03. CONCLUSION: Individuals with type 1 diabetes and high blood pressure, older age, higher BMI, and longer duration of disease could be considered at high-risk for developing MASLD.

Glycoprotein Acetyls Associate With Intraglomerular Hemodynamic Dysfunction, Albuminuria, Central Adiposity, and Insulin Resistance in Youth With Type 1 Diabetes.

OBJECTIVES: Glycoprotein acetyls (GlycA's) are biomarkers of systemic inflammation and cardiovascular disease, yet little is known about their role in type 1 diabetes (T1D). In this study we examined the associations among GlycA's, central adiposity, insulin resistance, and early kidney injury in youth with T1D. METHODS: Glomerular filtration rate and renal plasma flow by iohexol and p-aminohippurate clearance, urine albumin-to-creatinine ratio (UACR), central adiposity by dual-energy x-ray absorptiometry, and estimated insulin sensitivity were assessed in 50 youth with T1D (16±3.0 years of age, 50% female, glycated hemoglobin 8.7%±1.3%, T1D duration 5.7±2.6 years). Concentrations of GlycA were quantified by targeted nuclear magnetic resonance spectroscopy. Correlation and multivariable linear regression analyses were performed. RESULTS: GlycA's were higher in girls vs boys (1.05±0.26 vs 0.84±0.15 mmol/L, p=0.001) and in participants living with overweight/obesity vs normal weight (1.12±0.23 vs 0.87±0.20 mmol/L, p=0.0004). GlycA's correlated positively with estimated intraglomerular pressure (r=0.52, p=0.001), UACR (r=0.53, p<0.0001), and trunk mass (r=0.45, p=0.001), and inversely with estimated insulin sensitivity (r=-0.36, p=0.01). All relationships remained significant after adjustment for age, sex, and glycated hemoglobin. CONCLUSIONS: As biomarkers of inflammation, GlycA's were higher in girls and those with overweight or obese body habitus in T1D. GlycA's associated with parameters of early kidney dysfunction, central adiposity, and insulin resistance.

Networks of gut bacteria relate to cardiovascular disease in a multi-ethnic population: the HELIUS study.

AIMS: Gut microbiota have been linked to blood lipid levels and cardiovascular diseases (CVDs). The composition and abundance of gut microbiota trophic networks differ between ethnicities. We aim to evaluate the relationship between gut microbiotal trophic networks and CVD phenotypes. METHODS AND RESULTS: We included cross-sectional data from 3860 individuals without CVD history from 6 ethnicities living in the Amsterdam region participating in the prospective Healthy Life in Urban Setting (HELIUS) study. Genetic variants were genotyped, faecal gut microbiota were profiled, and blood and anthropometric parameters were measured. A machine learning approach was used to assess the relationship between CVD risk (Framingham score) and gut microbiota stratified by ethnicity. Potential causal relationships between gut microbiota composition and CVD were inferred by performing two-sample Mendelian randomization with hard CVD events from the Pan-UK Biobank and microbiome genome-wide association studies summary data from a subset of the HELIUS cohort (n = 4117). Microbial taxa identified to be associated with CVD by machine learning and Mendelian randomization were often ethnic-specific, but some concordance across ethnicities was found. The microbes Akkermansia muciniphila and Ruminococcaceae UCG-002 were protective against ischaemic heart disease in African-Surinamese and Moroccans, respectively. We identified a strong inverse association between blood lipids, CVD risk, and the combined abundance of the correlated microbes Christensenellaceae-Methanobrevibacter-Ruminococcaceae (CMR). The CMR cluster was also identified in two independent cohorts and the association with triglycerides was replicated. CONCLUSION: Certain gut microbes can have a potentially causal relationship with CVD events, with possible ethnic-specific effects. We identified a trophic network centred around Christensenellaceae, Methanobrevibacter, and various Ruminococcaceae, frequently lacking in South-Asian Surinamese, to be protective against CVD risk and associated with low triglyceride levels.

Insulin Secretion, Sensitivity, and Kidney Function in Young Individuals With Type 2 Diabetes.

OBJECTIVE: ß-Cell dysfunction and insulin resistance magnify the risk of kidney injury in type 2 diabetes. The relationship between these factors and intraglomerular hemodynamics and kidney oxygen availability in youth with type 2 diabetes remains incompletely explored. RESEARCH DESIGN AND METHODS: Fifty youth with type 2 diabetes (mean age ± SD 16 ± 2 years; diabetes duration 2.3 ± 1.8 years; 60% female; median HbA1c 6.4% [25th, 75th percentiles 5.9, 7.6%]; BMI 36.4 ± 7.4 kg/m2; urine albumin-to-creatinine ratio [UACR] 10.3 [5.9, 58.0] mg/g) 21 control participants with obesity (OCs; age 16 ± 2 years; 29% female; BMI 37.6 ± 7.4 kg/m2), and 20 control participants in the normal weight category (NWCs; age 17 ± 3 years; 70% female; BMI 22.5 ± 3.6 kg/m2) underwent iohexol and p-aminohippurate clearance to assess glomerular filtration rate (GFR) and renal plasma flow, kidney MRI for oxygenation, hyperglycemic clamp for insulin secretion (acute C-peptide response to glucose [ACPRg]) and disposition index (DI; ×103 mg/kg lean/min), and DXA for body composition. RESULTS: Youth with type 2 diabetes exhibited lower DI (0.6 [0.0, 1.6] vs. 3.8 [2.4, 4.5] × 103 mg/kg lean/min; P < 0.0001) and ACPRg (0.6 [0.3, 1.4] vs. 5.3 [4.3, 6.9] nmol/L; P < 0.001) and higher UACR (10.3 [5.9, 58.0] vs. 5.3 [3.4, 14.3] mg/g; P = 0.003) and intraglomerular pressure (77.8 ± 11.5 vs. 64.8 ± 5.0 mmHg; P < 0.001) compared with OCs. Youth with type 2 diabetes and OCs had higher GFR and kidney oxygen availability (relative hyperoxia) than NWCs. DI was associated inversely with intraglomerular pressure and kidney hyperoxia. CONCLUSIONS: Youth with type 2 diabetes demonstrated severe ß-cell dysfunction that was associated with intraglomerular hypertension and kidney hyperoxia. Similar but attenuated findings were found in OCs.

Kidney and liver fat accumulation: from imaging to clinical consequences.

BACKGROUND: Recent studies indicate that accumulation of adipose tissue in various organs such as liver and kidney may contribute to the pathophysiology of metabolic syndrome. We aim to investigate the association between kidney and liver adipose tissue accumulation, assessed by the magnetic resonance imaging (MRI) proton density fat fraction technique, along with its relation to clinical and biochemical parameters. METHODS: We included 51 volunteers with phenotypical features of metabolic syndrome (mean age = 34 years, mean body-mass index = 26.4 kg/m2) in our study in which liver and kidney adipose tissue accumulation was assessed via MRI-proton density fat fraction along with multiple other clinical and biochemical parameters such as estimated glomerular filtration rate (eGFR), urine albumin-to-creatinine ratio, serum lipid profile, liver function tests and body-mass index (BMI). RESULTS: Our results from the univariate linear regression analysis indicate that both the kidney and liver scores were positively correlated with markers such as BMI, urine albumin-to-creatinine ratio, triglycerides (p < 0.001) and negatively correlated with eGFR (p < 0.05). In multivariate analysis, urine albumin-to-creatinine ratio (p < 0.05), triglycerides (p < 0.01), eGFR (p < 0.05) and BMI (p < 0.001) were found to be independently associated with kidney and liver fat accumulation, respectively (R2 = 0.64; R2 = 0.89). There was also a positive correlation between kidney and liver fat accumulation. CONCLUSION: We have found a significant association between adipose tissue accumulation in liver and kidney and the parameters of metabolic syndrome. Moreover, the presence of a strong association between kidney and liver fat accumulation and kidney function parameters such as urine albumin-to-creatinine ratio and eGFR may be an indicator of the clinical significance of parenchymal fat accumulation.

Cystatin C-Based eGFR Changes during Gender-Affirming Hormone Therapy in Transgender Individuals.

BACKGROUND: Men with CKD tend to experience a faster eGFR decline than women, potentially because of sex hormones. Limited research exists regarding the effect of gender-affirming hormone therapy (GAHT) on kidney function. Furthermore, monitoring kidney function during GAHT is challenging because serum creatinine is confounded by body composition. To investigate the relationship between sex hormones and kidney function, we studied the changes of serum creatinine and serum cystatin C, a filtration marker less affected by sex, during 1 year of GAHT. METHODS: As part of the European Network for the Investigation of Gender Incongruence study, we measured serum creatinine and serum cystatin C in 260 transgender women and 285 transgender men before and 12 months after initiating GAHT. Transgender women received estradiol plus cyproterone acetate, while transgender men received testosterone. Cystatin C-based eGFR was calculated using the full-age-spectrum equation. RESULTS: In transgender women, cystatin C decreased by 0.069 mg/L (95% confidence interval [CI], 0.049 to 0.089), corresponding with a 7 ml/min per 1.73 m 2 increase in eGFR. In transgender men, cystatin C increased by 0.052 mg/L (95% CI, 0.031 to 0.072), corresponding with a 6 ml/min per 1.73 m 2 decrease in eGFR. Creatinine concentrations decreased (-0.065 mg/dl; 95% CI, -0.076 to -0.054) in transgender women and increased (+0.131 mg/dl; 95% CI, 0.119 to 0.142) in transgender men. Changes in creatinine-based eGFR varied substantially depending on the sex used in the equation. CONCLUSIONS: In this cohort of transgender individuals, cystatin C-based eGFR increased with estradiol and antiandrogen therapy and decreased with testosterone therapy.

Effect of tirzepatide on blood pressure and lipids: A meta-analysis of randomized controlled trials.

AIM: To perform a meta-analysis to quantify the effect of tirzepatide on blood pressure and lipids. METHODS: PubMed, Ovid/Medline, Web of Science, Scopus, Cochrane Library and CINAHL databases were screened and the randomized controlled trials evaluating the effects of tirzepatide on either blood pressure or lipid profiles were included. RESULTS: Seven randomized controlled trials have investigated the effects of tirzepatide on blood pressure and lipid profiles. Regardless of the dose administered, tirzepatide resulted in significant decreases in systolic blood pressure of median -4.20 (95% confidence interval [CI] -5.17 to -3.23) mmHg for 5 mg, -5.34 (-6.31 to -4.37) mmHg for 10 mg, and -5.77 (-6.73 to -4.81) mmHg for 15 mg. At all three once-weekly doses, tirzepatide treatment resulted in significant decreases in total cholesterol levels: median -3.76% (95% CI -5.20% to -2.31%) for 5 mg; -4.63% (-6.07% to -3.19%) for 10 mg; and -5.93% (-7.36% to -4.49%) for 15 mg. Additionally, tirzepatide treatment led to increased high-density lipoprotein (HDL) cholesterol levels and decreased low-density lipoprotein (LDL) cholesterol and triglyceride levels. CONCLUSIONS: Tirzepatide induced clinically meaningful reductions in the levels of systolic and diastolic blood pressure, total cholesterol, LDL cholesterol and triglycerides, along with increases in the level of HDL cholesterol.

Glucose variability and mood in people with type 1 diabetes using ecological momentary assessment.

OBJECTIVE: Mood fluctuations related to blood glucose excursions are a commonly reported source of diabetes-distress, but research is scarce. We aimed to assess the relationship between real-time glucose variability and mood in adults with type 1 diabetes (T1D) using ecological momentary assessments. METHODS: In this prospective observational study, participants wore a masked continuous glucose monitor and received prompts on their smartphone 6 times a day to answer questions about their current mood (Profile Of Mood States (POMS)-SF (dimensions: Anxiety, Depressive symptoms, Anger, Fatigue, Vigor)) for 14 days. Mixed model analyses examined associations over time between daily Coefficient of Variation (CV) of blood glucose and mean and variability (CV) of POMS scores. Further, within-person differences in sleep and nocturnal hypoglycemia were explored. RESULTS: 18 people with T1D (10 female, mean age 44.3 years) participated. A total of 264 out of 367 days (70.2%) could be included in the analyses. No overall significant associations were found between CV of blood glucose and mean and CV of POMS scores, however, nocturnal hypoglycemia moderated the associations between CV of blood glucose and POMS scales (mean Fatigue Estimate 1.998, p < .006, mean Vigor Estimate -3.308, p < .001; CV Anger Estimate 0.731p = 0.02, CV Vigor Estimate -0.525, p = .006). CONCLUSION: We found no overall relationship between real-time glycemic variability and mood per day. Further research into within-person differences such as sleep and nocturnal hypoglycemia is warranted.

Residual ß-Cell Function Is Associated With Longer Time in Range in Individuals With Type 1 Diabetes.

OBJECTIVE: Little is known about the influence of residual islet function on glycemic control in type 1 diabetes (T1D). We investigated the associations between residual ß-cell function and metrics of continuous glucose monitoring (CGM) in individuals with T1D. RESEARCH DESIGN AND METHODS: In this cross-sectional cohort comprising 489 individuals (64% female, age 41.0 ± 14.0 years), T1D duration was 15.0 (interquartile range [IQR] 6.0-29.0) years. Individuals had a time in range (TIR) of 66% (IQR 52-80%) and a urinary C-peptide-to-creatinine ratio (UCPCR) of 0.01 (IQR 0.00-0.41) nmol/mmol. To assess ß-cell function, we measured UCPCR (detectable >0.01 nmol/mmol), and to assess α-cell function, fasting plasma glucagon/glucose ratios were measured. CGM was used to record TIR (3.9-10 mmol/L), time below range (TBR) (<3.9 mmol/L), time above range (TAR) (>10 mmol/L), and glucose coefficient of variance (CV). For CGM, 74.7% used FreeStyle Libre 2, 13.8% Medtronic Guardian, and 11.5% Dexcom G6 as their device. RESULTS: The percentage of patients with T1D who had a detectable UCPCR was 49.4%. A higher UCPCR correlated with higher TIR (r = 0.330, P < 0.05), lower TBR (r = -0.237, P < 0.05), lower TAR (r = -0.302, P < 0.05), and lower glucose CV (r = -0.356, P < 0.05). A higher UCPCR correlated negatively with HbA1c levels (r = -0.183, P < 0.05) and total daily insulin dose (r = -0.183, P < 0.05). Glucagon/glucose ratios correlated with longer TIR (r = 0.234, P < 0.05). CONCLUSIONS: Significantly longer TIR, shorter TBR and TAR, and lower CV were observed in individuals with greater UCPCR-assessed ß-cell function. Therefore, better CGM-derived metrics in individuals with preserved ß-cell function may be a contributor to a lower risk of developing long-term complications.

Sex differences in associations of plasma metabolites with blood pressure and heart rate variability: The HELIUS study.

BACKGROUND AND AIMS: Since plasma metabolites can modulate blood pressure (BP) and vary between men and women, we examined sex differences in plasma metabolite profiles associated with BP and sympathicovagal balance. Our secondary aim was to investigate associations between gut microbiota composition and plasma metabolites predictive of BP and heart rate variability (HRV). METHODS: From the HELIUS cohort, we included 196 women and 173 men. Office systolic BP and diastolic BP were recorded, and heart rate variability (HRV) and baroreceptor sensitivity (BRS) were calculated using finger photoplethysmography. Plasma metabolomics was measured using untargeted LC-MS/MS. Gut microbiota composition was determined using 16S sequencing. We used machine learning models to predict BP and HRV from metabolite profiles, and to predict metabolite levels from gut microbiota composition. RESULTS: In women, best predicting metabolites for systolic BP included dihomo-lineoylcarnitine, 4-hydroxyphenylacetateglutamine and vanillactate. In men, top predictors included sphingomyelins, N-formylmethionine and conjugated bile acids. Best predictors for HRV in men included phenylacetate and gentisate, which were associated with lower HRV in men but not in women. Several of these metabolites were associated with gut microbiota composition, including phenylacetate, multiple sphingomyelins and gentisate. CONCLUSIONS: Plasma metabolite profiles are associated with BP in a sex-specific manner. Catecholamine derivatives were more important predictors for BP in women, while sphingomyelins were more important in men. Several metabolites were associated with gut microbiota composition, providing potential targets for intervention.