BackgroundOverweight and obesity is a prevalent and growing global health concern associated with a significant healthcare burden. With recent advancements in weight management interventions demonstrating cardioprotective benefits, there is a need for risk equations that can accurately predict cardiovascular event risk in health economic models to support healthcare decision making and resource allocation.ObjectiveWe aimed to derive risk equations using SELECT trial data that estimate the risk of acute coronary syndrome and stroke in people with established cardiovascular disease and overweight or obesity but without diabetes mellitus for use in health economic modelling.MethodsRisk equations estimating first in-trial observed acute coronary syndrome and stroke were derived from patient-level data from the SELECT trial, a double-blind randomised placebo-controlled trial comparing semaglutide 2.4 mg with placebo. Risk factors were identified from the literature and by clinical experts. Risk equations were developed using cause-specific Cox proportional hazard models with all-cause mortality as a competing risk. Least absolute shrinkage and selection operator (LASSO) penalisation was applied 100 times in bootstrap samples to refine the risk equations. Final risk equations were validated with clinical experts and using SELECT trial data.ResultsSex, coronary heart disease, a history of acute coronary syndrome and use of angina medications had the strongest associations with acute coronary syndrome (hazard ratio 1.67-1.82). For stroke, a history of atrial fibrillation, cerebrovascular disorder, stroke and transient ischaemic attack had the strongest associations (hazard ratio 1.40-1.70). In terms of discrimination, the risk equations had an area under the receiver operating characteristic curve (AUC) of 0.66-0.68 for acute coronary syndrome and 0.68-0.71 for stroke, and C-indices of 0.67-0.69 for acute coronary syndrome and 0.66-0.69 for stroke. The risk equations showed good cohort-level predictive capabilities over a 4-year time horizon.ConclusionsThese novel, treatment-specific, trial-derived risk equations are the first to predict the risk of secondary cardiovascular events in people with overweight or obesity and established cardiovascular disease but without diabetes. Incorporating these risk equations into health economic models may improve the accuracy of economic evaluations in this population.

AIMS:The fibrosis-4 (FIB-4) score is used to identify risk of advanced liver fibrosis. This post hoc analysis investigated its prognostic value for cardiovascular (CV) outcomes and its relevance to the effects of dapagliflozin. MATERIALS AND METHODS:DECLARE-TIMI 58 was a randomised, placebo-controlled phase 3 trial investigating dapagliflozin in patients with type 2 diabetes (T2D) and either atherosclerotic cardiovascular disease (ASCVD) or high ASCVD risk. Participants were stratified by baseline FIB-4 scores (< 1.30, 1.30 to < 2.67, and ≥ 2.67). Hazard ratios (HRs) and 95% confidence intervals (CIs) for dapagliflozin versus placebo were calculated for the two primary outcomes (major adverse cardiovascular events [MACE] and the composite of CV death and hospitalisation for heart failure [HHF]). RESULTS:Of 17 160 patients enrolled, 16 361 were included (median follow-up of 4.2 years). Distribution across FIB-4 categories was: < 1.30, n = 9084 (55.5%); 1.30 to < 2.67, n = 6556 (40.7%); and ≥ 2.67, n = 621 (3.8%), with similar ASCVD prevalence across groups (40%-43%). In the placebo arm, the ≥ 2.67 FIB-4 group had the highest event rates for MACE, HHF, CV death, and all-cause death. MACE HRs (95% CIs) for dapagliflozin versus placebo were 0.95 (0.83-1.10), 0.92 (0.79-1.08), and 0.61 (0.38-0.97) across ascending FIB-4 groups. For the CV death and HHF composite endpoint, they were 0.81 (0.67-0.98), 0.90 (0.73-1.10), and 0.50 (0.28-0.90). Dapagliflozin reduced aspartate aminotransferase and alanine aminotransferase levels compared with placebo. CONCLUSION:Highest FIB-4 scores were associated with increased CV risk in patients with T2D. Dapagliflozin reduced CV risk across FIB-4 categories without significant interactions.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common chronic liver disease worldwide, but its pathophysiological mechanisms remain elusive. It is a progressive disease, encompassing hepatic steatosis, steatohepatitis with (out) fibrosis, and ultimately cirrhosis and hepatocellular carcinoma. DNA methylation (DNAm) is dysregulated in MASLD and may play a central role in its pathogenesis. Additionally, aging is associated with MASLD and shares common processes of chronic inflammation and oxidative stress. Therefore, this study focuses on DNAm changes in relation to MASLD progression and epigenetic age acceleration (EAA). Liver biopsies from 22 individuals with varying MASLD status were analyzed using Infinium MethylationEPIC BeadChip arrays. Strikingly, progression of MASLD was characterized by gradual DNAm changes, revealing multiple associated KEGG pathways. Additionally, Horvath’s EAA significantly correlated with MASLD stage and individual histological MASLD parameters while LiverClock’s EAA correlated only with MASLD stage. In contrast, both Horvath’s intrinsic EAA and HepClock’s EAA showed no significant correlations. Integrative analyses, leveraging both gradual MASLD and Horvath’s EAA DNAm signatures, gene expression (n = 118), and a MASLD-specific transcriptional regulatory network, identified (regulon-specific) transcription factors implicated in MASLD and EAA progression, representing a transcription factor-network of redox (ferroptosis), immune, and metabolic/endocrine related epigenetic processes. Gradual DNAm changes were found to align with progression of MASLD and EAA, with EAA a potential nonbiased quantitative biomarker for MASLD. Integrative analysis highlighted potential new therapeutic transcription factor targets, with special emphasis on AEBP1 and emerging nuclear receptors including CAR(NR1I3), MR(NR3C2), GR(NR3C1), and ESRRG, underscoring the potential of epigenetic redox-metabolic therapies for MASLD.

The 10th Cardiovascular Outcome Trial (CVOT) Summit: Congress on Cardiovascular, Kidney, and Metabolic Outcomes was held virtually on December 5–6, 2024. This year, discussions about cardiovascular (CV) and kidney outcome trials centered on the recent findings from studies involving empagliflozin (EMPACT-MI), semaglutide (STEP-HFpEF-DM and FLOW), tirzepatide (SURMOUNT-OSA and SUMMIT), and finerenone (FINEARTS-HF). These studies represent significant advances in reducing the risk of major adverse cardiovascular events (MACE) and improving metabolic outcomes in heart failure with preserved ejection fraction (HFpEF), chronic kidney disease (CKD), and obstructive sleep apnea (OSA). The congress also comprised sessions on novel and established therapies for managing HFpEF, CKD, and obesity; guidelines for managing CKD and metabolic dysfunction-associated steatotic liver disease (MASLD); organ crosstalk and the development of cardio-kidney-metabolic (CKM) syndrome; precision medicine and person-centered management of diabetes, obesity, cardiovascular disease (CVD) and CKD; early detection of type 1 diabetes (T1D) and strategies to delay its onset; continuous glucose monitoring (CGM) and automated insulin delivery (AID); cardiovascular autonomic neuropathy (CAN) and the diabetic heart; and the role of primary care in the early detection, prevention and management of CKM diseases. The contribution of environmental plastic pollution to CVD risk, the increasing understanding of the efficacy and safety of incretin therapies in the treatment of CKM diseases, and the latest updates on nutrition strategies for CKM management under incretin-based therapies were also topics of interest for a vast audience of endocrinologists, diabetologists, cardiologists, nephrologists and primary care physicians, who actively engaged in online discussions. The 11th CVOT Summit will be held virtually on November 20–21, 2025 ( http://www.cvot.org ).

Background & aims: Weight reduction programs in people with overweight or obesity can be informed by indirect calorimetry (IC) which is the gold standard to measure basal metabolic rate (BMR). Since IC is labor intensive and expensive, predictive equations are often used as an alternative. In this study the accuracy rate was assessed and bias statistics of predictive equations were compared to IC among subjects with overweight or obesity. Secondly, differences in clinical features between individuals with over-, accurate or underestimation of their BMR were evaluated. Methods: This cross sectional study included 731 subjects from the outpatient obesity clinic of the Antwerp University Hospital, Belgium. Fourteen equations were evaluated. Overestimation and underestimation was defined as >10 % and <10 % of measured BMR. Results: In the total population, mean age was 43 +/- 13 years, mean BMI 35.6 +/- 5.8 kg/m(2) and 79.5 % were female. The highest accuracy rates were reached by the Henry (73 %), Ravussin (73 %) and Mifflin St. Jeor (73 %) equations. In the total population, the Mifflin St. Jeor and Henry equation were unbiased. The Akern, Livingston and Ravussin equations were biased to underestimation. All other equations were biased to overestimation. Subjects with an underestimation of BMR had significantly higher waist-hip ratio (1.02 +/- 0.13 vs 0.91 +/- 0.11; P < 0.001), higher visceral adipose tissue (239 +/- 96 vs 162 +/- 93; P < 0.001), lower fat free mass (kg) (67.6 (45.4-95.9) vs 54.0 (39.6-95.5); P < 0.001) and a higher prevalence of the Metabolic Syndrome (24 (77.4) vs 112 (37.5); P < 0.001). Individuals with an overestimation of BMR had significantly higher subcutaneous adipose tissue (545 +/- 149 vs 612 +/- 149; P < 0.05), lower fasting plasma insulin (81 (10-2019) vs 67 (27-253); P < 0.001) and lower 2-h plasma glucose (132 (30-430) vs 116 (43-193); P < 0.001) during OGTT. Conclusions: In this study, the Henry and Mifflin St. Jeor equations have the highest accuracy and lowest bias to estimate the basal metabolic rate in a Caucasian, predominantly female, population living with overweight or obesity. Visceral and subcutaneous adipose tissue and presence of metabolic syndrome were significantly different in individuals with over- or underestimation of BMR.

Rationale: Indirect calorimetry (IC) is considered the gold standard to measure basal metabolic rate (BMR). Since IC is labor intensive, predictive equations are used as an alternative. Precise evaluation of their usefulness is needed. This study assessed the accuracy rate and bias statistics of predictive equations compared to IC among people living with overweight and obesity (PwO). Methods: This cross sectional observational study included 731 subjects from the outpatient obesity clinic. Fourteen equations were evaluated. A one sample t-test was performed to report bias based on a 95% confidence interval (CI) between measured and estimated values. Precision was expressed as the percentage of participants with predicted energy expenditure within 10% of measured values of IC. The level of agreement was assessed by Bland–Altman plots with a cut off of 95%. Results: In the total population, 79,5% was female with a mean age of 43±13 years and a mean Body Mass Index of 35,6±5,8 kg/m2. The Henry (73,3%), Ravussin (73.2%), Mifflin- St.Jeor (72.8%), and Livingston (71.0%) equations had the highest accuracy rates. With increasing BMI, the accuracy decreased slightly. In the BMI >40kg/m2 group, the Mifflin-St.Jeor (70,3%) and Henry (70,3%) equations had the highest accuracy rates. The Mifflin-St.Jeor and Henry equation were unbiased. The Livingston and Ravussin equations were biased to underestimation. All other equations were biased to overestimation. There was an agreement between IC and the Henry, Livingston and Mifflin-St.Jeor equation and a lack of agreement between IC and Ravussin equation. Conclusion: The Henry and Mifflin-St.Jeor equations had the highest accuracy and lowest bias to estimate the basal metabolic rate in caucasian, predominantly female PwO. However, accuracy decreased as BMI increased. Disclosure of Interest: None declared

In the primary care setting providers have more tools available than ever before to impact positively obesity, diabetes, and their complications, such as renal and cardiac diseases. It is important to recognise what is available for treatment taking into account diabetes heterogeneity. For those who develop type 2 diabetes (T2DM), effective treatments are available that for the first time have shown a benefit in reducing mortality and macrovascular complications, in addition to the well-established benefits of glucose control in reducing microvascular complications. Some of the newer medications for treating hyperglycaemia have also a positive impact in reducing heart failure (HF). Technological advances have also contributed to improving the quality of care in patients with diabetes. The use of technology, such as continuous glucose monitoring systems (CGM), has improved significantly glucose and glycated haemoglobin A1c (HbA1c) values, while limiting the frequency of hypoglycaemia. Other technological support derives from the use of predictive algorithms that need to be refined to help predict those subjects who are at great risk of developing the disease and/or its complications, or who may require care by other specialists. In this review we also provide recommendations for the optimal use of the new medications; sodium-glucose co-transporter-2 inhibitors (SGLT2i) and Glucagon-like peptide-receptor agonists 1 (GLP1RA) in the primary care setting considering the relevance of these drugs for the management of T2DM also in its early stage.

BACKGROUND AND AIMS:Peroxisome Proliferator-Activated Receptor α (PPARα) is a key regulator of hepatic lipid metabolism and therefore a promising therapeutic target against Metabolic-dysfunction Associated Steatotic Liver Diseases (MASLD). However, its expression and activity decrease during disease progression and several of its agonists did not achieve sufficient efficiency in clinical trials with, surprisingly, a lack of steatosis improvement. Here, we identified the Human leukocyte antigen-F Adjacent Transcript 10 (FAT10) as an inhibitor of PPARα lipid metabolic activity during MASLD progression. APPROACH AND RESULTS:In vivo, the expression of FAT10 is upregulated in human and murine MASLD livers upon disease progression and correlates negatively with PPARα expression. The increase of FAT10 occurs in hepatocytes in which both proteins interact. FAT10 silencing in vitro in hepatocytes increases PPARα target gene expression, promotes fatty acid oxidation and decreases intra-cellular lipid droplet content. In line, FAT10 overexpression in hepatocytes in vivo inhibits the lipid regulatory activity of PPARα in response to fasting and agonist treatment in conditions of physiological and pathological hepatic lipid overload. CONCLUSIONS:FAT10 is induced during MASLD development and interacts with PPARα resulting in a decreased lipid metabolic response of PPARα to fasting or agonist treatment. Inhibition of the FAT10-PPARα interaction may provide a means to design potential therapeutic strategies against MASLD.

Background & Aims: Roux-en-Y gastric bypass (RYGB), the most effective surgical procedure for weight loss, decreases obesity and ameliorates comorbidities, such as non-alcoholic fatty liver (NAFLD) and cardiovascular (CVD) diseases. Cholesterol is a major CVD risk factor and modulator of NAFLD development, and the liver tightly controls its metabolism. How RYGB surgery modulates systemic and hepatic cholesterol metabolism is still unclear.Methods: We studied the hepatic transcriptome of 26 patients with obesity but not diabetes before and 1 year after undergoing RYGB. In parallel, we measured quantitative changes in plasma cholesterol metabolites and bile acids (BAs).Results: RYGB surgery improved systemic cholesterol metabolism and increased plasma total and primary BA levels. Tran-scriptomic analysis revealed specific alterations in the liver after RYGB, with the downregulation of a module of genes implicated in inflammation and the upregulation of three modules, one associated with BA metabolism. A dedicated analysis of hepatic genes related to cholesterol homeostasis pointed towards increased biliary cholesterol elimination after RYGB, associated with enhancement of the alternate, but not the classical, BA synthesis pathway. In parallel, alterations in the expression of genes involved in cholesterol uptake and intracellular trafficking indicate improved hepatic free cholesterol handling. Finally, RYGB decreased plasma markers of cholesterol synthesis, which correlated with an improvement in liver disease status after surgery.Conclusions: Our results identify specific regulatory effects of RYGB on inflammation and cholesterol metabolism. RYGB alters the hepatic transcriptome signature, likely improving liver cholesterol homeostasis. These gene regulatory effects are reflected by systemic post-surgery changes of cholesterol-related metabolites, corroborating the beneficial effects of RYGB on both hepatic and systemic cholesterol homeostasis.

Background & Aims:The epidemiology of non-alcoholic fatty liver disease (NAFLD) in people with type 1 diabetes (T1D) is not yet elucidated. This study aimed to assess the diagnostic accuracy of non-invasive tests for NAFLD, to investigate the prevalence and severity of NAFLD, and to search for factors contributing to NAFLD in people with T1D. Methods:In this prospective cohort study, we consecutively screened 530 adults with T1D from a tertiary care hospital, using ultrasound (US), vibration-controlled transient elastography equipped with liver stiffness measurement (LSM) and controlled attenuation parameter, and the fatty liver index. Magnetic resonance spectroscopy (MRS) was performed in a representative subgroup of 132 individuals to validate the diagnostic accuracy of the non-invasive tests. Results:Based on MRS as reference standard, US identified individuals with NAFLD with an AUROC of 0.98 (95% CI 0.95-1.00, sensitivity: 1.00, specificity: 0.96). The controlled attenuation parameter was also accurate with an AUROC of 0.85 (95% CI 0.77-0.93). Youden cut-off was ≥270 dB/m (sensitivity: 0.90, specificity: 0.74). The fatty liver index yielded a similar AUROC of 0.83 (95% CI 0.74-0.91), but the conventional cut-off used to rule in (≥60) had low sensitivity and specificity (0.62, 0.78). The prevalence of NAFLD in the overall cohort was 16.2% based on US. Metabolic syndrome was associated with NAFLD (OR: 2.35 [1.08-5.12], p = 0.031). The overall prevalence of LSM ≥8.0 kPa indicating significant fibrosis was 3.8%, but reached 13.2% in people with NAFLD. Conclusions:NAFLD prevalence in individuals with T1D is 16.2%, with approximately one in 10 featuring elevated LSM. US-based screening could be considered in people with T1D and metabolic syndrome. Impact and Implications:We aimed to report on the prevalence, disease severity, and risk factors of NAFLD in type 1 diabetes (T1D), while also tackling which non-invasive test for NAFLD is the most accurate. We found that ultrasound is the best test to diagnose NAFLD. NAFLD prevalence is 16.2%, and is associated with metabolic syndrome and BMI. Elevated liver stiffness indicating fibrosis is overall not prevalent in people with T1D (3.8%), but it reaches 13.2% in those with T1D and NAFLD.

To explore changes in body weight and cardiometabolic risk factors after treatment withdrawal in the STEP 1 trial extension.

Obesity represents a major risk factor for the development of impaired glucose tolerance and type 2 diabetes. In this chapter, the authors focus on the causes and consequences of visceral and ectopic fat accumulation and its relevance to the development of type 2 diabetes. Attention is given to biomarkers that allow a more exact identification of those patients at risk for metabolic disease. The clinical features that lead to a better understanding of those factors influencing the risk for diabetes and cardiovascular disease can be studied by means of the two ends of a clinical spectrum of people with obesity and metabolic health. An individual's ability to expand adipose tissue and factors involved in body fat distribution seems to be modified both by genetic/epigenetic factors, hormonal effects, and environmental factors. Finally, some therapeutic options are reviewed.