Fasting Glucose Research Articles (Page 1)

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a serious disease and increasingly prevalent in children. MASLD is associated with health consequences such as type 2 diabetes, and cardiovascular disease. While, vitamin E is a potent antioxidant that has been proposed to improve liver function and cardiometabolic health including liver markers, lipid profile, glycemic control, and anthropometric measurements. A comprehensive search was conducted up to March 2025. Data on anthropometric measures, liver enzymes (alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyl transferase (GGT)), glycemic indices (fasting blood sugar (FBS), insulin, homeostatic model assessment for insulin resistance (HOMA-IR)), lipid profiles (total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C)), and serum vitamin E levels were extracted. Statistical analyses were performed using a random-effects model. Eleven RCTs involving 665 participants were included in this study. Vitamin E significantly reduced ALT (weighted mean difference (WMD)= -5.23 U/L;95% confidence interval (CI): -7.72, -2.75; P< 0.001) and AST (WMD= -3.00 U/L;95% CI: -4.59, -1.41; P< 0.001), reflecting improved liver function. It also decreased TC (WMD= -5.77 mg/dL;95% CI: -11.46, -0.09; P= 0.04) and HOMA-IR (WMD= -0.82;95% CI: -1.28, -0.37; P< 0.001), while significantly increasing serum vitamin E levels (WMD= 9.16 mg/L;95%CI: 3.29, 15.03; P=0.002). No significant changes were observed in the BMI, GGT, FBS, insulin, LDL, HDL, or TG levels. Vitamin E supplementation in pediatric MASLD appears to favorably influence key liver enzymes such as ALT, AST and certain metabolic factors including TC, and HOMA-IR levels, supporting its potential role as adjunctive therapy.

The impact of rising temperature variability driven by climate change on metabolic health remains understudied, especially considering the global increase in diabetes prevalence, with long-term effects on glucose metabolism unexplored. This study investigated associations between long-term temperature variability exposure and glucose metabolism in a population-based cohort of 2997 participants (4954 observations) over a 7-year period from KORA F4 and FF4 cohorts in Augsburg, Germany. Long-term exposure to temperature variability was estimated as the standard deviation of the daily mean air temperature over the 365-day period preceding each examination. We applied generalized estimating equations to examine the longitudinal associations between long-term exposure to temperature variability and multiple glucose metabolism biomarkers: fasting glucose, 2h glucose, fasting insulin, homeostasis model assessment of insulin resistance (HOMA-IR), homeostasis model assessment of β-cell function (HOMA-B), quantitative insulin sensitivity check index (QUICKI), and glycated hemoglobin (HbA1c). We found that a 1 °C higher temperature variability was significantly associated with higher fasting insulin, HOMA-IR, and HbA1c with % changes (95% CI) of 2.62 (0.79; 4.49), 2.81 (0.79; 4.87), and 2.38 (1.97; 2.79), respectively, and lower QUICKI (-0.41 [-0.70; -0.11]). These findings suggest that increasing temperature variability exposure may contribute to metabolic dysfunction, potentially accelerating the global diabetes epidemic.

Glucose homeostasis relies on coordinated interactions among multiple organs, and its disruption relates to diabetes development. This study investigated how inter-organ metabolic coordination, assessed by whole-body [¹⁸F]FDG PET/CT, is altered across the glycemic continuum at both the population and individual levels, and whether individualized dysfunction features can improve early diabetes risk stratification. We analyzed whole-body [¹⁸F]FDG PET/CT scans from 1,149 adults across two independent centers, classified into normoglycemic, pre-diabetic, and diabetic groups based on fasting glucose. Standardized uptake values normalized by lean body mass were extracted from 20 major organs. These values were further adjusted for age, sex, and BMI using general linear models to reduce demographic confounding. Group-level metabolic connectivity networks were constructed using bootstrapped correlation matrices with False Discovery Rate correction. To capture individual-level dysregulation, we generated deviation networks by quantifying how each subject's inter-organ coordination diverged from demographically matched normative reference patterns. These personalized network features were used to train and validate a machine learning model for classifying pre-diabetes versus diabetes. At the population-level, network topological analysis revealed a decline in inter-organ metabolic connectivity from normoglycemia to pre-diabetes to diabetes. Pre-diabetes was marked by widespread but modest weakening of connections across multiple organs, while diabetes showed fewer but more concentrated disruptions, indicating a shift toward localized network breakdown. Specific alterations included reduced coordination between the kidneys in pre-diabetes, and disrupted connectivity between the brain and liver in diabetes. Individualized deviation networks captured subject-level differences in metabolic connectivity, with greater heterogenity observed in pre-diabetes. A machine learning model trained on these personalized features successfully distinguished diabetes from pre-diabetes (AUC = 0.75, external validation), with brain-peripheral connections emerging as the most informative predictors. This study reveals distinct patterns of inter-organ matbolic connectivity breakdowns across glycemic states and demonstrates that individualized network features can effectively capture subject-specific dysregulation.

Protocol for in vivo assessment of glucose metabolism in mouse models.

The purpose of this study was to evaluate the association between glycaemic status and the incidence of third, fourth, and sixth cranial nerve palsy (CNP). This is a retrospective nationwide population-based cohort study using South Korean National Health Insurance Service (NHIS) data since 2009. Health check-up data of 4,067,842 individuals aged from 20 to 90 years in the period from 1 January 2009 to 31 December 2018 were analysed. The subjects were classified according to glycaemic status as follows: non-diabetes, impaired fasting glucose (IFG), newly detected diabetes, diabetes duration <5 years, and diabetes duration ≥5 years. The primary endpoint of this study was the incidence of third, fourth or sixth CNP. Hazard ratio (HR) and 95% confidence interval (CI) of CNP were estimated using Cox proportional hazards regression analysis. In Model 5, we adjusted for age, gender, smoking status, alcohol consumption, physical activity, body mass index, hypertension, dyslipidaemia, and chronic kidney disease. During the follow-up period (mean, 6.3 years), 5835 cases of third, fourth, or sixth CNP were identified with 4,062,007 control cases. In the adjusted model 5, the adjusted HR for third, fourth, and sixth CNP in the IFG group was 1.098 (95% CI 1.030 - 1.171); in the newly detected diabetes group, 1.779 (95% CI 1.587-1.994); in the diabetes duration <5 years group, 1.921 (95% CI 1.731-2.131); and in the diabetes duration ≥5 years group, 2.571 (95% CI 2.343-2.820). Using the Kaplan-Meier curve, the log-rank test demonstrated an increase in the incidence of CNP proportional to the duration of diabetes (p < 0.001). This large-scale, population-based cohort study suggests that the risk of third, fourth, and sixth CNP significantly increased in patients with IFG and diabetes compared to those with normal glycaemic status.

Type 2 diabetes can be prevented by lifestyle intervention. We aimed to identify metabolites that associate with glucose metabolism and respond to lifestyle intervention with evidence-based targets for nutrition and physical activity in individuals at high risk of type 2 diabetes. Standard oral glucose tolerance test (OGTT) was used to categorize 624 participants into those having normal glucose tolerance (NGT), isolated impaired glucose tolerance (IGT), IGT with increased fasting glucose (IGT + IFG), and type 2 diabetes. Plasma LC-MS metabolomics was performed to reveal metabolic signatures. The baseline group differences were analysed with the Kruskal-Wallis test and the effect of intervention with a linear mixed-effects model. Significant differences in the metabolite signature were observed between the baseline groups, particularly in amino acids, acylcarnitines, and phospholipids. Fatty acid amides, phospholipids, amino acids, dimethylguanidinovaleric acid, and 5-aminovaleric acid betaine responded most to the lifestyle intervention. Lysophosphatidylcholines containing odd-chain fatty acids showed associations with improved glucose metabolism. Twenty-five metabolites differed between the baseline groups, responded to the intervention, and were associated with changes in glucose metabolism. The findings suggest a metabolite panel could be used in distinguishing individuals with varying degrees of glucose metabolism and in predicting response to lifestyle interventions.

Introduction Schizophrenia (SCH) is a chronic psychiatric disorder characterized by disturbances in thought, emotion, perception, and behavior. Although gut microbiota interventions (e.g., probiotics, prebiotics, synbiotics, dietary modifications and fecal microbiota transplantation) have been widely applied in the treatment of SCH, the most effective intervention strategy remains uncertain. Methods By searching four databases, only randomized controlled trials (RCTs) were included to examine the impacts of gut microbiota interventions on SCH. The Cochrane risk-of-bias tool for randomized trials (RoB 2.0) was employed to assess the methodological quality of the included studies, RevMan5.4 was used for the meta-analysis, Stata 18 was used for sensitivity analysis, Engauge Digitizer was used to convert pictures to numbers and GRADEPro3.6 was used to grade the evidence quality. Results This study incorporated RCTs published from the earliest records up to December 2024. A total of 10 RCTs, encompassing 585 participants, were analyzed. The meta-analysis demonstrated that interventions primarily utilizing probiotics to modulate gut microbiota significantly lowered the total Positive and Negative Syndrome Scale (PANSS) scores among patients ( p = 0.001). Furthermore, substantial improvements were observed across multiple metabolic parameters: fasting blood sugar, triglycerides, total cholesterol, homeostasis model assessment of insulin resistance, and quantitative insulin sensitivity check index (all p &amp;lt; 0.05). While no significant effects were observed on high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, body weight, body mass index, and insulin. Conclusion This meta-analysis suggests that auxiliary probiotic interventions hold promise as an adjunctive therapy for schizophrenia, potentially yielding benefits in psychopathological, metabolic, and physiological domains. However, the current evidence remains inconclusive due to the limited number of studies, small sample sizes, and methodological variations. Firm therapeutic recommendations cannot be made at this time. The findings underscore the need for more robust, large-scale, and rigorously designed randomized controlled trials to definitively establish the efficacy and optimal protocols of auxiliary probiotic supplementation for SCH. Systematic review registration https://www.crd.york.ac.uk/PROSPERO , CRD 420250652507.

Elevated prolactin levels are considered a potential parameter associated with increased cardiovascular risk. The aim of our study is to investigate the possible role of Endocan levels in the cardiovascular risk associated with hyperprolactinemia by comparing patients with hyperprolactinemia to a healthy control group. The study included 39 patients with hyperprolactinemia of various etiologies and 39 healthy controls. In both groups, cardiovascular risk-related parameters-including height, body weight, BMI, waist circumference, CRP, and lipid levels-were evaluated and recorded. Endocan levels were measured using the ELISA method. The groups were comparable in age, sex, height, body weight, BMI, and waist circumference. No significant differences were found between the patient and control groups in terms of height, body weight, BMI, waist circumference, WBC count, fasting glucose, insulin levels, HOMA-IR, HbA1c, lipid profile, CRP, and 25(OH) vitamin D levels. However, serum Endocan levels were significantly higher in the hyperprolactinemic group (p = 0.028). In this group, Endocan levels showed a significant positive correlation with waist circumference, body weight, and BMI, and a negative correlation with WBC count. One of the key findings of our study is the elevated Endocan levels in patients with mildly increased prolactin levels (45.90 ± 2.72 ng/mL), indicating a higher cardiovascular risk. This may reflect the association between elevated prolactin and endothelial dysfunction. Further prospective studies with larger sample sizes and longer follow-up are needed to better evaluate Endocan levels in patients with hyperprolactinemia. No applicable.

Objective This study analyzed metabolic indicators and height gain in short-statured children within the first year of recombinant human growth hormone (rhGH) therapy, identifying predictive factors for treatment efficacy. Methods A retrospective analysis of 72 children with short stature (growth hormone deficiency or idiopathic short stature) receiving rhGH therapy (January 2022 to January 2024) was performed. Data included height, weight, age, skeletal age (SA), and laboratory results (IGF1, fasting glucose, insulin, C-peptide, thyroid function, lipids). Analyses focused on height standard deviation score (HSDS), HSDS for SA, and factors associated with 12-month changes in HSDS for SA (△HSDS for SA). Results The mean initial rhGH dose was 0.053 ± 0.010mg/kg/day, with a mean starting age of 8.36 ± 2.24 years. Significant increases in HSDS and HSDS for SA were observed after 12 months. △HSDS for SA negatively correlated with baseline homeostasis model assessment of insulin resistance (HOMA-IR) and fasting insulin, and positively correlated with baseline free triiodothyronine (FT3). Children with △HSDS for SA&amp;gt;0.5 had lower baseline insulin and HOMA-IR, and higher FT3, high-density lipoprotein cholesterol (HDL), and hemoglobin. Conclusions Insulin resistance, hyperinsulinemia, FT3, and HDL determine rhGH efficacy in short-statured children. Metabolic profiling optimizes rhGH therapy, and targeting insulin resistance may improve growth outcomes.

STUDY AIMS: A history of gestational diabetes mellitus is a known risk factor for developing type 2 diabetes in the future. Therefore, screening for persistent dysglycaemia in the postpartum period is of utmost importance. However, follow-up rates tend to be low. The aim of this study was to investigate postpartum screening adherence at a tertiary care centre and to identify factors contributing to persistent dysglycaemia. METHODS: A cohort of women with gestational diabetes mellitus diagnosed between 2015 and 2018 at the department of Obstetrics and Gynaecology, University Hospital Bern, Switzerland, was retrospectively studied. Ethnicity, parity, pre-pregnancy BMI, family history of diabetes mellitus, first trimester glycosylated haemoglobin (HbA1c), 75 g oral glucose tolerance test during pregnancy and in the postpartum period were analysed. Postpartum dysglycaemia was defined as overt diabetes (fasting plasma glucose ≥7.0 mmol/l and/or 2 hours plasma glucose ≥11.1 mmol/l for the 75 g oral glucose tolerance test), impaired glucose tolerance (2 hours plasma glucose 7.8–11.0 mmol/l) or impaired fasting glucose (plasma glucose 5.6–6.9 mmol/l). Parametric and non-parametric tests as well as multivariate regression were used. ROC analyses were performed to assess the prognostic accuracy of HbA1c and oral glucose tolerance test results at predicting postpartum dysglycaemia. RESULTS: We included 489 women with gestational diabetes mellitus in our study. Of these, 217 (44.4%) returned for postpartum testing and 59/217 (27.2%) had an abnormal oral glucose tolerance test. Ethnicity was found to be a factor in adherence to follow-up. Specifically, women of African origin showed a significantly higher compliance than Asian or Caucasian women (61.8% vs 47.8% vs 34.5%, respectively; p = 0.04). The multivariate analysis revealed that obesity (OR: 3.64, 95% CI: 1.41–9.37) and first trimester HbA1c &gt;5.7% (OR: 3.67, 95% CI: 1.28–10.52) are significantly associated with an increased risk of postpartum dysglycaemia. CONCLUSION: Our study indicates that adherence to postpartum screening after gestational diabetes mellitus is low but in line with the existing experience. This is of particular concern as 1 of 4 women undergoing postpartum screening show some sort of disturbed glucose metabolism. In particular, women with higher first trimester HbA1c and/or obesity may warrant closer observation and motivation for testing as the risk for persistent metabolic disorders is increased.

Background and aim Sustained lifestyle changes are crucial for the remission of type 2 diabetes (T2D) but remain challenging. Citizen initiatives using peer coaching and self-management may offer a promising alternative to professional medical care. This study evaluated Your Lifestyle As Medicine (YLAM), a Dutch citizen initiative for people with T2D. We aimed to assess its impact on metabolic parameters and to examine participants’ engagement. Methods This observational study analysed self-reported data on weight, waist circumference, fasting glucose and glycated haemoglobin (HbA 1 c) from participants in YLAM’s online community. Participants could report their self-measured data on a weekly basis. Linear mixed-model analyses, stratified by sex, were used to assess changes in metabolic parameters over time. Additionally, we evaluated participants’ engagement through reporting duration and weekly reporting rates. Results We assessed all 232 people with T2D who reported multiple measurements for at least 3 months. The median reporting duration was 11.2 months (IQR 4.6–26.5). Weekly reporting rates were 59% for weight, 55% for waist circumference and 52% for fasting glucose, and 12-weekly reporting rates were 49% for HbA 1 c. Overall, mean weight, waist circumference, fasting glucose and HbA 1 c improved in the first year in both women and men. More specifically, weight decreased by 7.2 kg in women (95% CI –7.6 to –6.8) and by 7.4 kg in men (95% CI –8.0 to –6.8). This represented a mean relative weight loss of 9.0% (SD 7.7) and 8.6% (SD 6.5), respectively. Waist circumference decreased by 8.9 cm in women (95% CI –9.4 to –8.5) and by 8.5 cm in men (95% CI –9.1 to –7.8). Fasting glucose decreased by 1.15 mmol/L in women (95% CI –1.32 to –0.98) and by 0.49 mmol/L in men (95% CI –0.75 to –0.23). HbA 1 c decreased by 14.5 mmol/mol in women (95% CI –17.4 to –11.6) and by 9.1 mmol/mol in men (95% CI –13.2 to –5.0). Of all participants, 44% reported data for longer than a year and demonstrated sustained improvements in weight and waist circumference in the long term. Conclusion This study provides evidence for substantial and sustained improvements in self-reported metabolic parameters in people with T2D engaged in a citizen initiative without medical supervision. Initiatives like YLAM offer a promising, accessible and scalable strategy to address the growing burden of lifestyle-related diseases.

The rising global incidence of Type 2 Diabetes Mellitus (T2DM) is a major contributor to increased morbidity and mortality. Research consistently links type 2 diabetes mellitus (T2DM) with various hematological and lipid abnormalities. However, studies in Libya that examine the relationship between these factors in T2DM patients and correlate them with geographical distribution are scarce. This study aims to evaluate the variations in hematological and lipid profiles among Libyan individuals with type 2 diabetes mellitus (T2DM) and to investigate potential correlations between these parameters. Additionally, it seeks to conduct T2DM surveillance in densely populated regions. A cross-sectional study was conducted at laboratories located in three different districts of Tripoli: Ghout Al Shaal Specialized Hospital, Abu Salim Hospital, and Al Sarai Laboratory in Hay Al Andalus. A total of 261 Libyan participants were divided into 170 patients with type 2 diabetes and 91 non-diabetic (controls), aged 50-85 years. Anthropometric data (weight, height, and body mass index (BMI)) were measured using standard protocols. Complete blood count (CBC) and lipid profile analysis were measured using the Sysmex XP-300 automated hematology analyzer and the Roche Cobas Integra 400 Plus system, respectively. Data were analyzed statistically using GraphPad Prism and SPSS version 27. A p-value of &lt;0.05 was considered statistically significant. -value of &lt;0.05 was considered statistically significant. T2DM subjects exhibited a higher body mass index (BMI) across study groups, genders, and districts (p&lt;0.001) and demonstrated a statistically significant increase in red blood cell (RBC) counts (p=0.018) when compared to controls. Gender analysis indicated that diabetic women had a slightly higher RBC count (p=0.02), while men showed elevated neutrophil percentages (p=0.046). District-specific analyses revealed distinct trends. In Abu Salim, both hemoglobin (Hb) concentrations and RBC counts were high (p=0.036 and p=0.012, respectively). In Hay Al Andalus, mean cell volume (MCV) was significantly lower, and white blood cell (WBC) counts were higher (p=0.031 and p=0.022, respectively). In Ghout Al Shaal, significantly higher neutrophil percentages (p&lt;0.001) and lower lymphocyte percentages (p=0.005) were found among diabetics. Additionally, the diabetic group exhibited substantially high levels of HbA1c, fasting blood sugar (FBS), and triglycerides (TG) (p&lt;0.001). While diabetic women aligned with these trends, the male subgroup displayed similar glycaemic levels but exhibited less pronounced lipid differences. Notably, lipid variances were only observed in Hay Al Andalus; diabetic participants had lower high-density lipoprotein cholesterol (HDL-C) and higher TG (p=0.02 and p=0.001, respectively). T2DM Libyan patients suffer from increased adiposity and poor glycemic control. Distinct lipid abnormalities were also observed among patients, but these are commonly seen in women. Patients in the Hay Al Andalus region had the most devastating dyslipidaemia compared to other districts. Moreover, the observed variations in blood indices may be attributed to chronic inflammation, disease severity, and potential hypoxia, influenced by gender and geographic factors. Our findings may offer valuable guidance for prevention and clinical management strategies for T2DM patients in Tripoli.

Diabetes mellitus is a major global health burden, and early identification of insulin dependency is important for timely intervention. This study developed an artificial intelligence-based diagnostic system using a real-world clinical dataset of 100 anonymized patient records, collected with ethical approval and informed consent. The dataset included demographic, lifestyle, and biochemical variables such as glycated hemoglobin (HbA1c), fasting blood sugar (FBS), and postprandial blood sugar (PPBS). After preprocessing to handle missing values, normalize continuous variables, and encode categorical features, four machine learning models were implemented: Logistic Regression, Random Forest, XGBoost, and LightGBM, along with ensemble based, combined approaches. Model evaluation was performed using 5-fold cross-validation with accuracy, precision, recall, and F1-score as metrics. XGBoost achieved the highest performance (accuracy 0.88, precision 0.86, recall 0.90, F1-score 0.88), followed by LightGBM (accuracy 0.85, F1-score 0.84), Random Forest (accuracy 0.82, F1-score 0.81), and Logistic Regression (accuracy 0.76, F1-score 0.74). The most predictive features were PPBS and HbA1c, consistent with clinical understanding. While results are promising, they reflect a single-center dataset of 100 records, and should be interpreted as preliminary, further study will include external validation on larger, multi-site cohorts prior to clinical adoption.

To evaluate the lipid-lowering efficacy, safety, and adherence of switching from moderate- or low-intensity statin monotherapy to ezetimibe 10 mg/rosuvastatin 2.5 mg in Korean patients with type 2 diabetes mellitus (T2DM) and dyslipidaemia. This multicentre, open-label, single-arm, prospective study enrolled adults with T2DM and LDL-C ≥70 mg/dL despite ≥12 weeks of moderate or low-intensity statin therapy. Participants received ezetimibe 10 mg/rosuvastatin 2.5 mg once daily for 12 weeks. The primary endpoint was the proportion achieving LDL-C <70 mg/dL at Week 12. Secondary endpoints included changes in lipid and glycaemic parameters, subgroup analyses, and safety outcomes. Of 639 screened patients, 586 were included in the full analysis set (FAS). At Week 12, 62.3% (95% CI 58.4-66.2) achieved LDL-C <70 mg/dL. Mean LDL-C decreased by 26.0% from 90.9 ± 17.2 to 67.3 ± 19.3 mg/dL (p < 0.001). Total cholesterol, non-HDL-C, and apoB decreased significantly (all p < 0.001); HDL-C and triglycerides were unchanged (p = 0.914 and p = 0.393, respectively). HbA1c increased by 0.15 ± 0.53% and fasting glucose by 3.6 ± 24.7 mg/dL (both p < 0.001). HOMA-IR decreased by -0.22 ± 3.09, not significant (p = 0.085). Subgroup analyses showed greater LDL-C reductions in patients with BMI <23 kg/m2, prior low-intensity statin use, or pravastatin therapy, and smaller reductions in those receiving GLP-1 receptor agonists or thiazolidinediones. Adherence averaged 97.5% (97.4%, ≥80%). Among 591 participants, 9.8% had at least one adverse event, mostly mild and not clinically significant. Switching to ezetimibe 10 mg/rosuvastatin 2.5 mg achieved substantial LDL-C reductions, high goal attainment, excellent adherence, and good tolerability in Korean T2DM patients with dyslipidaemia.

Statin use is associated with increased risk of type 2 diabetes and mild hyperglycemia. The underlying mechanisms are not well studied and the effect of statin treatment on GLP-1 secretion or production are unknown. To assess the effects of rosuvastatin on GLP-1 secretion and production. We performed association studies in the Malmö Diet and Cancer study cardiovascular cohort (MDCS-CC) re-examination cohort, in vitro investigations using GLUTag cells and acute and chronic studies in female, normoglycemic C57Bl/6j mice. Studies in the MDCS-CC reexamination cohort(n=3734) revealed that in individuals without type 2 diabetes, statin usage was associated with higher fasting GIP, insulin, glucose, glucagon and HOMA-IR, but not GLP-1. However, in patients with type 2 diabetes, statin usage was associated with higher fasting GLP-1 levels.Rosuvastatin treatment or Hmgcr knockdown reduced GLP-1 secretion and increased Gcg mRNA in GLUTag cells. Rosuvastatin acutely reduced postprandial GLP-1 secretion, whereas chronic rosuvastatin treatment in mice caused hyperglycemia and increased postprandial GLP-1 levels. The acute effect of Hmgcr KD on GLP-1 secretion could be mimicked by targeting intracellular cholesterol using a PCSK9 inhibitor. Finally, transcriptomic alterations induced by rosuvastatin were limited to genes involved in cholesterol biosynthesis. We have established HMGCR as a regulator of GLP-1 secretion and provide a plausible explanation for the clinically observed mild hyperglycemia associated with statin use. Given the negative acute effect on GLP-1 secretion, monitoring of blood glucose levels is recommended after prescribing rosuvastatin."

Background The TNF‐α -promoter polymorphisms rs1800629 (−308G&amp;gt;A) and rs361525 (−238G&amp;gt;A) have been variably associated with type 2 diabetes mellitus (T2DM) risk in different populations. This study evaluated these two polymorphisms in a cohort of Punjabi individuals from Pakistan. Methods A case–control study was conducted including 100 clinically diagnosed T2DM patients and 100 healthy controls. Genotyping of TNF‐α rs1800629 and rs361525 was performed using allele‐specific ARMS-PCR and validated by sequencing. Allele and genotype frequencies were compared between groups, odds ratios (ORs) and 95% confidence intervals (CIs) were calculated, and Hardy–Weinberg equilibrium was assessed. Results The A alleles of rs1800629 and rs361525 were significantly more frequent in T2DM cases compared to controls (3.68% vs. 0.54%, OR = 6.779, p = 0.037 for rs1800629; 5.26% vs. 0.53%, OR = 9.684, p = 0.006 for rs361525). Fasting blood sugar level (FBS) of 150 ± 45 mg/dL was recorded in diabetic subjects. Multivariate and forest plot analyses supported the association of both variants with increased T2DM risk. Control group genotypes conformed to Hardy-Weinberg equilibrium, validating population stability. Conclusion In this Punjabi cohort from Pakistan, the A alleles of TNF-α promoter polymorphisms rs1800629 and rs361525 were significantly more frequent in T2DM cases, indicating that these variants increase susceptibility to T2DM in this population.

Adenylyl cyclase 5 knockout (AC5 KO) is a healthful longevity model; not only do the AC5 KO mice live a third longer than wild-type (WT) mice, but they are also protected against obesity, diabetes, heart failure, and exercise intolerance, mediated by anti-apoptosis, cell survival, myocardial biogenesis, and anti-oxidative stress mechanisms. To translate these salutary effects to the clinics, we developed a drug, C90, which recapitulates the AC5 KO model of healthful longevity. We then examined its effects on glucose tolerance and exercise capacity. C90 (30 mg/kg/day) or vehicle was chronically administered to age-matched C57BL/6 mice via an osmotic pump. The WT mice receiving C90 exhibited improved glucose tolerance, following glucose i.v. injection, when compared to the vehicle. Furthermore, the C90-treated mice had a lower fasting glucose level when compared to the vehicle-treated mice (113 ± 6.5 mg/dL vs. 129 ± 4.2 mg/dL, p &lt; 0.05). Additionally, the WT group that received C90 exhibited greater exercise capacity, reflected by longer running distance (384 ± 27 m vs. 253 ± 16 m, p &lt; 0.05) and greater work to exhaustion (18.1 ± 1.5 J vs. 12.4 ± 0.7 J, p &lt; 0.05) than mice receiving vehicle. In view of these findings, C90 is an excellent candidate for clinical development as an effective pharmacological treatment for glucose intolerance and enhancing exercise performance.

Insulin resistance (IR) drives early cardiometabolic risk in low-resource settings, yet gold-standard measures are impractical. We assessed routine lipids, triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and the TG/HDL-C ratio, as predictors of IR in 781 adults aged 20–29 years from the Ellisras Longitudinal Study (Lephalale, Limpopo). IR was defined as HOMA-IR ≥2.5. Participants were 51.8% female and 39.1% diabetic. Diabetic participants showed higher fasting glucose, insulin, and HOMA-IR, and more adverse lipid profiles than non-diabetics (all p < 0.001). Receiver-operating-characteristic analysis showed the TG/HDL-C ratio discriminated IR best (AUC 0.88, 95% CI 0.85–0.91), outperforming TG (0.78, 0.74–0.82) and HDL-C (0.75, 0.71–0.79). A practical cut-off of ≥2.0 yielded 82.1% sensitivity and 85.0% specificity. In multivariable models adjusted for age and sex, TG ≥1.7 mmol/L (aOR 2.92, 95% CI 2.04–4.18), low HDL-C (AOR 2.47, 1.75–3.48), and TG/HDL-C ≥ 2.0 (aOR 4.85, 3.32–7.08) were independently associated with IR; each year of age increased odds (AOR 1.06), and sex was not significant. Performance was consistent across diabetes status (AUC 0.84 non-diabetic; 0.81 diabetic) and sex (0.86 males; 0.83 females). The TG/HDL-C ratio is a simple, low-cost screening tool for IR in semi-rural South Africa and merits integration into primary care.

Risk of cardiometabolic disease increases in women transitioning to postmenopause, during which estradiol declines universally. Most of these women experience fragmentation of sleep due to nocturnal hot flashes, without a reduction in total sleep time. We examined the independent impact of estradiol suppression, sleep, and their combination on cardiometabolic outcomes categorized as satiety and hunger, lipid profile, cardiac vital signs, and glucoregulation. Participants completed 5-night inpatient studies under eucaloric conditions, once during mid-follicular phase/estrogenized and again under estrogen suppressed conditions, using the same experimental protocol both times. For all participants, sleep was unfragmented the first two nights and then experimentally fragmented without reducing total sleep time the next three nights. Inpatient Intensive Physiological Monitoring research facility. 38 healthy premenopausal women. Clinical experimental induced menopause model including gonadotropin-releasing hormone agonist-induced hypoestrogenism and sleep fragmentation. Leptin and satiety. Estradiol suppression significantly decreased leptin and increased lipid profiles (FDR-adjusted p≤0.05). Sleep fragmentation significantly increased heart rate (FDR-adjusted p=0.002) and trended to increase fasting glucose (FDR-adjusted p=0.08). Estradiol suppression and sleep fragmentation worsened individual cardiometabolic outcomes by (median, IQR) 4.0% (1.5%, 6.3%) from normalized baseline values. Sleep fragmentation worsened a composite cardiometabolic index derived from individual clinical cardiometabolic measures by an additional 103% over estradiol suppression alone. Independent of aging, there are significant adverse changes in cardiometabolic health induced by core components of the transition to postmenopause, including novel effects of sleep fragmentation, a modifiable target.

Introduction Basal insulin with glucagon-like peptide-1 receptor agonist could be preferred over premixed insulin for intensification in type 2 diabetes due to better glycemic control, lower hypoglycemia risk, and favorable effects on body weight. Comparative data on premixed insulin and the combination of degludec and liraglutide (iDegLira) are limited. Methods We conducted a 24-week single-arm prospective study to evaluate the impact of iDegLira compared to premixed insulin on the regulation of diabetes and glucovariability using continuous glucose monitoring (CGM), HbA1c, and anthropometric measurements. A total of 37 participants with type 2 diabetes (20 male and 17 female, aged 70.2 ± 10.0 years with BMI 31.0 (28.0-34.0) kg/m 2 and duration of diabetes for 15.2 ± 7.7 years) were switched from premixed insulin treatment to iDegLira. The primary outcome was the change in HbA1c. Secondary outcomes included change in time in range (TIR) from baseline to 6 months, change in time below range (TBR), change in nocturnal hypoglycemia, glucovariability, insulin dose and body weight. Results We observed improved glycemic control on iDegLira with improvement of average fasting glucose (6.92 ± 1.64 vs . 8.25 ± 2.2 mmol/l; p&amp;lt;0.031), HbA1c (7.10 ± 0.7% vs . 7.39 ± 0.7% p=0.045) and TIR (71.2 ± 17.2% vs . 64.3 ± 18.0; p=0.027). These results were accompanied by a nearly halved total daily insulin dose (-21 units/day, p&amp;lt;0.001) and a modest reduction of body weight. Discussion iDegLira improved glycemic control, resulting in a lower HbA1c and higher TIR, alongside beneficial effects on body weight and total daily insulin doses. While numerical reductions in hypoglycemia did not reach statistical significance, treatment was not associated with an increased risk of hypoglycemia. iDegLira can be an efficient and safe treatment option, providing simplified treatment with improved glycemic control.