Pathophysiology-based subphenotyping of individuals at elevated risk for type 2 diabetes

Prediabetes remission to reduce the global burden of type 2 diabetes

Prediabetes is a highly prevalent and increasingly common condition affecting a significant proportion of the global population. The heterogeneous nature of prediabetes presents a challenge in identifying individuals who particularly benefit from lifestyle or other therapeutic interventions aiming at preventing type 2 diabetes (T2D) and associated comorbidities. The phenotypic characteristics of individuals at risk for diabetes are associated with both specific risk profiles for progression and a differential potential to facilitate prediabetes remission and reduce the risk of future T2D. This review examines the current definition and global prevalence of prediabetes and evaluates the potential of prediabetes remission to reduce the alarming increase in the global burden of T2D.

In humans increase in intrapancreatic adipose tissue predicts beta-cell dedifferentiation score before diabetes onset: A pilot study

BACKGROUND

The role of intrapancreatic fat (WAT) in the development of T2D remains debated. In T2D, β-cell dedifferentiation is one of the mechanisms responsible for β-cell failure but its role in prediabetes is unknown. We aimed to investigate the relation between WAT and β-cell dedifferentiation prior to diabetes onset.

METHODS

We evaluated pancreatic samples from patients without history of diabetes, who had previously undergone an oral glucose tolerance test and hyperglycemic clamp. Subjects were divided into 3 glucose tolerance groups: normal (NGT), altered (IGT) or newly diagnosed diabetes (nDM). Dedifferentiation and WAT% were morphologically assessed.

RESULTS

WAT was higher in nDM patients compared to NGT and IGT (WAT nDM 43.79 ± 20.83 %, IGT 10.67 ± 8.5 %, NGT 4.43 ± 4.37 %). We observed a progressive increase in dedifferentiation score, in parallel with worsening glucose tolerance (from NGT to IGT to nDM; 4.8 ± 3.8; 32.37 ± 7.4; 40.38 ± 19 respectively). A strong linear regression established that WAT could statistically significantly predict dedifferentiated β-cells (R = 0.86, p = 0.005), and that the predicted increase in dedifferentiated β-cells was 1.25 points for every extra one-point change in WAT. Interestingly, the WAT and dedifferentiation score variable pair were significantly related to 1-hour post-load glycemia.

CONCLUSIONS

The accumulation of WAT might be responsible for dedifferentiation, making it a potential new target to curb diabetes onset.

High energy diet-induced prediabetic neuropathic pain is mediated by reduction of SIRT6 negative control of both spinal and peripheral neuroinflammation

Prediabetic neuropathic pain has been classified as peripheral neuropathic pain associated with polyneuropathy caused by impaired glucose tolerance or impaired fasting glucose, which is a preclinical stage and might develop type 2 diabetes mellitus. Our previous research highlighted that prediabetes is accompanied by dramatic bilateral mechanical hyperalgesia following high energy diet (HED) which results in myelin and axonal degenerations along somatosensory system. However, the pathogenic mechanisms underlying prediabetic neuropathic pain remain unclear. The nuclear sirtuin 6 (SIRT6) is a crucial deacetylase in the regulation of multiple cellular biological processes, such as DNA repair, genome stability, inflammation and metabolic homeostasis. In current study, we show that the expressions of SIRT6 were significantly decreased, while its downstream NF-κB and proinflammatory mediator IL-6 and IL-1β were significantly increased in both dorsal root ganglia (DRG) and spinal dorsal horn of rats with prediabetic neuropathic pain induced by HED. Moreover, siRNA-SIRT6 treatment induced a significant reduction in bilateral paw withdrawal mechanical thresholds, indicating that SIRT6 down-regulation contributed to prediabetic neuropathic pain induced by HED. Furthermore, it was also found that SIRT6 reduction induced the activation of HMGB1 via disinhibition of NF-κB in both DRG and spinal dorsal horn of prediabetic rats. In conclusion, prediabetic neuropathic pain is caused by SIRT6 reduction through upregulating HMGB1-RAGE signaling at both peripheral and spinal levels.

Dissection of type 2 diabetes: a genetic perspective

Diabetes is a leading cause of global mortality and disability, and its economic burden is substantial. This Review focuses on type 2 diabetes, which makes up 90-95% of all diabetes cases. Type 2 diabetes involves a progressive loss of insulin secretion often alongside insulin resistance and metabolic syndrome. Although obesity and a sedentary lifestyle are considerable contributors, research over the last 25 years has shown that type 2 diabetes develops on a predisposing genetic background, with family and twin studies indicating considerable heritability (ie, 31-72%). This Review explores type 2 diabetes from a genetic perspective, highlighting insights into its pathophysiology and the implications for precision medicine. More specifically, the traditional understanding of type 2 diabetes genetics has focused on a dichotomy between monogenic and polygenic forms. However, emerging evidence suggests a continuum that includes monogenic, oligogenic, and polygenic contributions, revealing their complementary roles in type 2 diabetes pathophysiology. Recent genetic studies provide deeper insights into disease mechanisms and pave the way for precision medicine approaches that could transform type 2 diabetes management. Additionally, the effect of environmental factors on type 2 diabetes, particularly from epigenetic modifications, adds another layer of complexity to understanding and addressing this multifaceted disease.

Determinants of increased muscle insulin sensitivity of exercise-trained versus sedentary normal weight and overweight individuals

The athlete's paradox states that intramyocellular triglyceride accumulation associates with insulin resistance in sedentary but not in endurance-trained humans. Underlying mechanisms and the role of muscle lipid distribution and composition on glucose metabolism remain unclear. We compared highly trained athletes (ATHL) with sedentary normal weight (LEAN) and overweight-to-obese (OVWE) male and female individuals. This observational study found that ATHL show higher insulin sensitivity, muscle mitochondrial content, and capacity, but lower activation of novel protein kinase C (nPKC) isoforms, despite higher diacylglycerol concentrations. Notably, sedentary but insulin sensitive OVWE feature lower plasma membrane-to-mitochondria sn-1,2-diacylglycerol ratios. In ATHL, calpain-2, which cleaves nPKC, negatively associates with PKCε activation and positively with insulin sensitivity along with higher GLUT4 and hexokinase II content. These findings contribute to explaining the athletes' paradox by demonstrating lower nPKC activation, increased calpain, and mitochondrial partitioning of bioactive diacylglycerols, the latter further identifying an obesity subtype with increased insulin sensitivity (NCT03314714).

Clustering-based risk stratification of prediabetes populations: Insights from the Taiwan and UK Biobanks

AIMS/INTRODUCTION

This study aimed to identify low- and high-risk diabetes groups within prediabetes populations using data from the Taiwan Biobank (TWB) and UK Biobank (UKB) through a clustering-based Unsupervised Learning (UL) approach, to inform targeted type 2 diabetes (T2D) interventions.

MATERIALS AND METHODS

Data from TWB and UKB, comprising clinical and genetic information, were analyzed. Prediabetes was defined by glucose thresholds, and incident T2D was identified through follow-up data. K-means clustering was performed on prediabetes participants using significant features determined through logistic regression and LASSO. Cluster stability was assessed using mean Jaccard similarity, silhouette score, and the elbow method.

RESULTS

We identified two stable clusters representing high- and low-risk diabetes groups in both biobanks. The high-risk clusters showed higher diabetes incidence, with 15.7% in TWB and 13.0% in UKB, compared to 7.3% and 9.1% in the low-risk clusters, respectively. Notably, males were predominant in the high-risk groups, constituting 76.6% in TWB and 52.7% in UKB. In TWB, the high-risk group also exhibited significantly higher BMI, fasting glucose, and triglycerides, while UKB showed marginal significance in BMI and other metabolic indicators. Current smoking was significantly associated with increased diabetes risk in the TWB high-risk group (P < 0.001). Kaplan-Meier curves indicated significant differences in diabetes complication incidences between clusters.

CONCLUSIONS

UL effectively identified risk-specific groups within prediabetes populations, with high-risk groups strongly associated male gender, higher BMI, smoking, and metabolic markers. Tailored preventive strategies, particularly for young males in Taiwan, are crucial to reducing T2D risk.

Understanding Adipose Tissue Dysfunction

Diseases affecting adipose tissue (AT) function include obesity, lipodystrophy, and lipedema, among others. Both a lack of and excess AT are associated with increased risk for developing diseases including type 2 diabetes mellitus, hypertension, obstructive sleep apnea, and some types of cancer. However, individual risk of developing cardiometabolic and other 'obesity-related' diseases is not entirely determined by fat mass. Rather than excess fat accumulation, AT dysfunction may represent the mechanistic link between obesity and comorbid diseases. There are people who remain metabolically healthy despite obesity, whereas people with normal weight or very low subcutaneous AT mass may develop typically obesity-related diseases. AT dysfunction is characterized by adipocyte hypertrophy, impaired subcutaneous AT expandability (ectopic fat deposition), hypoxia, a variety of stress, inflammatory processes, and the release of proinflammatory, diabetogenic, and atherogenic signals. Genetic and environmental factors might contribute to AT heterogeneity either alone or via interaction with intrinsic biological factors. However, many questions remain regarding the mechanisms of AT dysfunction initiation and whether and how it could be reversed. Do AT signatures define clinically relevant subtypes of obesity? Is the cellular composition of AT associated with variation in obesity phenotypes? What roles do environmental compounds play in the manifestation of AT dysfunction? Answers to these and other questions may explain AT disease mechanisms and help to define strategies for improving AT health. This review focuses on recent advances in our understanding of AT biology.

Prediction of metabolic subphenotypes of type 2 diabetes via continuous glucose monitoring and machine learning

The classification of type 2 diabetes and prediabetes does not consider heterogeneity in the pathophysiology of glucose dysregulation. Here we show that prediabetes is characterized by metabolic heterogeneity, and that metabolic subphenotypes can be predicted by the shape of the glucose curve measured via a continuous glucose monitor (CGM) during standardized oral glucose-tolerance tests (OGTTs) performed in at-home settings. Gold-standard metabolic tests in 32 individuals with early glucose dysregulation revealed dominant or co-dominant subphenotypes (muscle or hepatic insulin-resistance phenotypes in 34% of the individuals, and β-cell-dysfunction or impaired-incretin-action phenotypes in 40% of them). Machine-learning models trained with glucose time series from OGTTs from the 32 individuals predicted the subphenotypes with areas under the curve (AUCs) of 95% for muscle insulin resistance, 89% for β-cell deficiency and 88% for impaired incretin action. With CGM-generated glucose curves obtained during at-home OGTTs, the models predicted the muscle-insulin-resistance and β-cell-deficiency subphenotypes of 29 individuals with AUCs of 88% and 84%, respectively. At-home identification of metabolic subphenotypes via a CGM may aid the risk stratification of individuals with early glucose dysregulation.

Diabetes and obesity: leveraging heterogeneity for precision medicine

The increasing prevalence of diabetes, obesity, and their cardiometabolic sequelae present major global health challenges and highlight shortfalls of current approaches to the prevention and treatment of these conditions. Representing the largest global burden of morbidity and mortality, the pathobiological processes underlying cardiometabolic diseases are in principle preventable and, even when disease is manifest, sometimes reversable. Nevertheless, with current clinical and public health strategies, goals of widespread prevention and remission remain largely aspirational. Application of precision medicine approaches that reduce errors and improve accuracy in medical and health recommendations has potential to accelerate progress towards these goals. Precision medicine must also maintain safety and ideally be cost-effective, as well as being compatible with an individual's preferences, capabilities, and needs. Initial progress in precision medicine was made in the context of rare diseases, with much focus on pharmacogenetic studies, owing to the cause of these diseases often being attributable to highly penetrant single gene mutations. By contrast, most obesity and type 2 diabetes are heterogeneous in aetiology and clinical presentation, underpinned by complex interactions between genetic and non-genetic factors. The heterogeneity of these conditions can be leveraged for development of approaches for precision therapies. Adequate characterization of the heterogeneity in cardiometabolic disease necessitates diversity of and synthesis across data types and research methods, ideally culminating in precision trials and real-world application of precision medicine approaches. This State-of-the-Art Review provides an overview of the current state of the science of precision medicine, as well as outlining a roadmap for study designs that maximise opportunities and address challenges to clinical implementation of precision medicine approaches in obesity and diabetes.

Prediabetes Phenotype Clusters in the Diabetes Prevention Program Study

Objective

The purpose of this study was to apply clustering methods to identify and characterize prediabetes phenotypes and their relationships with treatment arm and type 2 diabetes (T2D) outcomes in the Diabetes Prevention Program (DPP), and to compare the utility of additional clustering measures in phenotype characterization and T2D risk stratification.

Research Design and Methods

This was a secondary analysis of data from a subset of participants (n=994) from the previously completed Diabetes Prevention Program trial. Unsupervised k-means clustering analysis was applied to derive the optimal number of clusters of participants based on common clinical risk factors alone or common risk factors plus more comprehensive measures of glucose tolerance and body composition.

Results

Five clusters were derived from common clinical characteristics and the addition of comprehensive measures of glucose tolerance and body composition. Within each modeling approach, participants show significantly different levels of risk factors. The clinical only model showed higher accuracy for time to T2D, however the more comprehensive models further differentiated a metabolically health overweight phenotype. For both models, the greatest differentiation in determining time to T2D was in the metformin arm of the trial.

Conclusions

Data driven clustering of patients with prediabetes allows for identification of prediabetes phenotypes at greater risk for disease progression and responses to risk reduction interventions. Further investigation into phenotypic differences in treatment response could enable better personalization of prediabetes and T2D prevention and treatment choices.

Identification of proteins associated with type 2 diabetes risk in diverse racial and ethnic populations

AIMS/HYPOTHESIS

Several studies have reported associations between specific proteins and type 2 diabetes risk in European populations. To better understand the role played by proteins in type 2 diabetes aetiology across diverse populations, we conducted a large proteome-wide association study using genetic instruments across four racial and ethnic groups: African; Asian; Hispanic/Latino; and European.

METHODS

Genome and plasma proteome data from the Multi-Ethnic Study of Atherosclerosis (MESA) study involving 182 African, 69 Asian, 284 Hispanic/Latino and 409 European individuals residing in the USA were used to establish protein prediction models by using potentially associated cis- and trans-SNPs. The models were applied to genome-wide association study summary statistics of 250,127 type 2 diabetes cases and 1,222,941 controls from different racial and ethnic populations.

RESULTS

We identified three, 44 and one protein associated with type 2 diabetes risk in Asian, European and Hispanic/Latino populations, respectively. Meta-analysis identified 40 proteins associated with type 2 diabetes risk across the populations, including well-established as well as novel proteins not yet implicated in type 2 diabetes development.

CONCLUSIONS/INTERPRETATION

Our study improves our understanding of the aetiology of type 2 diabetes in diverse populations.

DATA AVAILABILITY

The summary statistics of multi-ethnic type 2 diabetes GWAS of MVP, DIAMANTE, Biobank Japan and other studies are available from The database of Genotypes and Phenotypes (dbGaP) under accession number phs001672.v3.p1. MESA genetic, proteome and covariate data can be accessed through dbGaP under phs000209.v13.p3. All code is available on GitHub ( https://github.com/Arthur1021/MESA-1K-PWAS ).

Photo-transformation of biochar-derived dissolved organic matter and its binding with phenanthrene/9-phenanthrol: The role of functional group and pyrolysis temperature

This study explores the physicochemical attributes of dissolved organic matter from rice straw biochar (BDOM) at varying pyrolysis temperatures and photo-irradiation conditions, focusing on the binding mechanisms of phenanthrene (PHE) and 9-phenanthrol (PTR) using multiple spectroscopic techniques and fluorescence quenching. Following 20 h of photo-irradiation, only 11.3 % of BDOM underwent mineralization, forming new CH3/CH2/CH aliphatics structures. BDOM from biochar produced by pyrolysis at 400°C exhibited a stronger binding affinity with PHE and PTR, achieving 44 % and 52 % maximum binding, respectively. Static and dynamic quenching governed PHE and PTR binding, which was influenced by temperature. Photo-irradiated BDOM showed enhanced binding with PHE, attributed to increased aliphatic content. Hydrogen bond and π-π electron-donor-acceptor (EDA) interactions dominated PTR binding, while π-π interactions and hydrophobic interactions controlled PHE. This study provides valuable insights into BDOM photochemical behaviors and their impact on the environmental fate of polycyclic aromatic hydrocarbons (PAHs) after BDOM photo-irradiation.

Diabetic kidney disease: the kidney disease relevant to individuals with diabetes

In individuals with diabetes, chronic kidney disease (CKD) is a major comorbidity. However, it appears that there is worldwide confusion regarding which term should be used to describe CKD complicated with diabetes: diabetic nephropathy, diabetic kidney disease (DKD), CKD with diabetes, diabetes and CKD, etc. Similar confusion has also been reported in Japan. Therefore, to provide clarification, the Japanese Diabetes Society and the Japanese Society of Nephrology collaborated to update the corresponding Japanese term to describe DKD and clearly define the concept of DKD. In this review, we briefly described the history of kidney complications in individuals with diabetes and the Japanese definition of the DKD concept and provided our rationale for these changes.

Combined impact of prediabetes and hepatic steatosis on cardiometabolic outcomes in young adults

OBJECTIVES

This study aimed to investigate the impact of hepatic steatosis on cardiometabolic outcomes in young adults with prediabetes.

METHODS

A nationwide cohort study was conducted with 896,585 young adults under 40 years old without diabetes or previous history of cardiovascular disease. Hepatic steatosis was identified using a fatty liver index of ≥ 60. The outcomes of this study were incident diabetes (DM) and composite major adverse cardiovascular events (MACE), including myocardial infarction, stroke, or cardiovascular death.

RESULTS

During a median follow-up of 11.8 years, 27,437 (3.1%) incident DM cases and 6,584 (0.7%) MACE cases were recorded. Young adults with prediabetes had a significantly higher risk of incident DM (hazard ratio [HR]: 2.81; 95% confidence interval [CI]: 2.74-2.88; P-value: <0.001) and composite MACE risk (HR: 1.10; 95% CI: 1.03-1.17; P-value: 0.003) compared to individuals with normoglycemia, after adjusting for relevant covariates. Stratification based on hepatic steatosis showed that the combination of prediabetes and hepatic steatosis posed the highest risk for these outcomes, after adjusting for relevant covariates. For incident DM, the HRs (95% CI; P-value) were: 3.15 (3.05-3.26; <0.001) for prediabetes without hepatic steatosis, 2.89 (2.78-3.01; <0.001) for normoglycemia with hepatic steatosis, and 6.60 (6.33-6.87; <0.001) for prediabetes with hepatic steatosis. For composite MACE, the HRs (95% CI; P-value) were 1.05 (0.97-1.13; 0.235) for prediabetes without hepatic steatosis, 1.39 (1.27-1.51; <0.001) for normoglycemia with hepatic steatosis, and 1.60 (1.44-1.78; <0.001) for prediabetes with hepatic steatosis.

CONCLUSIONS

Prediabetes and hepatic steatosis additively increased the risk of cardiometabolic outcomes in young adults. These findings hold significance for physicians as they provide insights into assessing high-risk individuals among young adults with prediabetes.

Identifying subtypes of type 2 diabetes mellitus based on real-world electronic medical record data in China

AIMS

To replicate the European subtypes of type 2 diabetes mellitus (T2DM) in the Chinese diabetes population and investigate the risk of complications in different subtypes.

METHODS

A diabetes cohort using real-world patient data was constructed, and clustering was employed to subgroup the T2DM patients. Kaplan-Meier analysis and the Cox models were used to analyze the association between diabetes subtypes and the risk of complications.

RESULTS

A total of 2,652 T2DM patients with complete clustering data were extracted. Among them, 466 (17.57 %) were classified as severe insulin-deficient diabetes (SIDD), 502 (18.93 %) as severe insulin-resistant diabetes (SIRD), 672 (25.34 %) as mild obesity-related diabetes (MOD), and 1,012 (38.16 %) as mild age-related diabetes (MARD). The risk of chronic kidney disease (CKD) and diabetic retinopathy (DR) were different in the four subtypes. Compared with MARD, SIRD had a higher risk of CKD (HR 2.40 [1.16, 4.96]), and SIDD had a higher risk of DR (HR 2.16 [1.11, 4.20]). The risk of stroke and coronary events had no difference.

CONCLUSIONS

The European T2DM subtypes can be replicated in the Chinese diabetes population. The risk of CKD and DR varied among different subtypes, indicating that proper interventions can be taken to prevent specific complications in different subtypes.

'DKD' as the kidney disease relevant to individuals with diabetes

Even though chronic kidney disease (CKD) is a significant comorbidity in individuals with diabetes, there appears to be worldwide confusion regarding the terminology used to describe it, including diabetic nephropathy, diabetic kidney disease (DKD), CKD with diabetes, diabetes and CKD, etc. In Japan, we have encountered similar confusion regarding the terminology used to describe kidney disease in individuals with diabetes, especially when written in Japanese due to terminological similarities in Chinese characters. The primary issue in Japan was deciphering the significance of "Diabetic," specifically whether it is an essential attribute of the condition itself. The confusions may arise from the deficiencies in establishing a clear criterion for the disease concept, whether it is diabetic nephropathy or DKD. Furthermore, among specialists in the field, each may have their own concept of the disease. In this regard, the Japanese Diabetes Society and the Japanese Society of Nephrology updated the corresponding Japanese term for DKD and defined the concept of DKD with rationale. The goal of these efforts should be the future improvement of the prognosis of DKD patients, the stakeholders.

Predicting Type 2 Diabetes Metabolic Phenotypes Using Continuous Glucose Monitoring and a Machine Learning Framework

Type 2 diabetes (T2D) and prediabetes are classically defined by the level of fasting glucose or surrogates such as hemoglobin HbA1c. This classification does not take into account the heterogeneity in the pathophysiology of glucose dysregulation, the identification of which could inform targeted approaches to diabetes treatment and prevention and/or predict clinical outcomes. We performed gold-standard metabolic tests in a cohort of individuals with early glucose dysregulation and quantified four distinct metabolic subphenotypes known to contribute to glucose dysregulation and T2D: muscle insulin resistance, β-cell dysfunction, impaired incretin action, and hepatic insulin resistance. We revealed substantial inter-individual heterogeneity, with 34% of individuals exhibiting dominance or co-dominance in muscle and/or liver IR, and 40% exhibiting dominance or co-dominance in β-cell and/or incretin deficiency. Further, with a frequently-sampled oral glucose tolerance test (OGTT), we developed a novel machine learning framework to predict metabolic subphenotypes using features from the dynamic patterns of the glucose time-series ("shape of the glucose curve"). The glucose time-series features identified insulin resistance, β-cell deficiency, and incretin defect with auROCs of 95%, 89%, and 88%, respectively. These figures are superior to currently-used estimates. The prediction of muscle insulin resistance and β-cell deficiency were validated using an independent cohort. We then tested the ability of glucose curves generated by a continuous glucose monitor (CGM) worn during at-home OGTTs to predict insulin resistance and β-cell deficiency, yielding auROC of 88% and 84%, respectively. We thus demonstrate that the prediabetic state is characterized by metabolic heterogeneity, which can be defined by the shape of the glucose curve during standardized OGTT, performed in a clinical research unit or at-home setting using CGM. The use of at-home CGM to identify muscle insulin resistance and β-cell deficiency constitutes a practical and scalable method by which to risk stratify individuals with early glucose dysregulation and inform targeted treatment to prevent T2D.

A novel simple disposition index (SPINA-DI) from fasting insulin and glucose concentration as a robust measure of carbohydrate homeostasis

AIMS

The widely used dynamic disposition index, derived from oral glucose tolerance testing, is an integrative measure of the homeostatic performance of the insulin-glucose feedback control. Its collection is, however, time consuming and expensive. We, therefore, pursued the question if such a measure can be calculated at baseline/fasting conditions using plasma concentrations of insulin and glucose.

METHODS

A new fasting-based disposition index (structure parameter inference approach-disposition index [SPINA-DI]) was calculated as the product of the reconstructed insulin receptor gain (SPINA-GR) times the secretory capacity of pancreatic beta cells (SPINA-GBeta). The novel index was evaluated in computer simulations and in three independent, multiethnic cohorts. The objectives were distribution in various populations, diagnostic performance, reliability and correlation to established physiological biomarkers of carbohydrate metabolism.

RESULTS

Mathematical and in-silico analysis demonstrated SPINA-DI to mirror the hyperbolic relationship between insulin sensitivity and beta-cell function and to represent an optimum of the homeostatic control. It significantly correlates to the oral glucose tolerance test based disposition index and other important physiological parameters. Furthermore, it revealed higher discriminatory power for the diagnosis of (pre)diabetes and superior retest reliability than other static and dynamic function tests of glucose homeostasis.

CONCLUSIONS

SPINA-DI is a novel simple reliable and inexpensive marker of insulin-glucose homeostasis suitable for screening purposes and a wider clinical application.

EASL-EASD-EASO Clinical Practice Guidelines on the management of metabolic dysfunction-associated steatotic liver disease (MASLD)

Metabolic dysfunction-associated steatotic liver disease (MASLD), previously termed non-alcoholic fatty liver disease (NAFLD), is defined as steatotic liver disease (SLD) in the presence of one or more cardiometabolic risk factor(s) and the absence of harmful alcohol intake. The spectrum of MASLD includes steatosis, metabolic dysfunction-associated steatohepatitis (MASH, previously NASH), fibrosis, cirrhosis and MASH-related hepatocellular carcinoma (HCC). This joint EASL-EASD-EASO guideline provides an update on definitions, prevention, screening, diagnosis and treatment for MASLD. Case-finding strategies for MASLD with liver fibrosis, using non-invasive tests, should be applied in individuals with cardiometabolic risk factors, abnormal liver enzymes, and/or radiological signs of hepatic steatosis, particularly in the presence of type 2 diabetes (T2D) or obesity with additional metabolic risk factor(s). A stepwise approach using blood-based scores (such as FIB-4) and, sequentially, imaging techniques (such as transient elastography) is suitable to rule-out/in advanced fibrosis, which is predictive of liver-related outcomes. In adults with MASLD, lifestyle modification - including weight loss, dietary changes, physical exercise and discouraging alcohol consumption - as well as optimal management of comorbidities - including use of incretin-based therapies (e.g. semaglutide, tirzepatide) for T2D or obesity, if indicated - is advised. Bariatric surgery is also an option in individuals with MASLD and obesity. If locally approved and dependent on the label, adults with non-cirrhotic MASH and significant liver fibrosis (stage ≥2) should be considered for a MASH-targeted treatment with resmetirom, which demonstrated histological effectiveness on steatohepatitis and fibrosis with an acceptable safety and tolerability profile. No MASH-targeted pharmacotherapy can currently be recommended for the cirrhotic stage. Management of MASH-related cirrhosis includes adaptations of metabolic drugs, nutritional counselling, surveillance for portal hypertension and HCC, as well as liver transplantation in decompensated cirrhosis.

Blood coagulation in Prediabetes clusters-impact on all-cause mortality in individuals undergoing coronary angiography

BACKGROUND

Metabolic clusters can stratify subgroups of individuals at risk for type 2 diabetes mellitus and related complications. Since obesity and insulin resistance are closely linked to alterations in hemostasis, we investigated the association between plasmatic coagulation and metabolic clusters including the impact on survival.

METHODS

Utilizing data from the Ludwigshafen Risk and Cardiovascular Health (LURIC) study, we assigned 917 participants without diabetes to prediabetes clusters, using oGTT-derived glucose and insulin, high-density lipoprotein cholesterol, triglycerides, and anthropometric data. We performed a comprehensive analysis of plasmatic coagulation parameters and analyzed their associations with mortality using proportional hazards models. Mediation analysis was performed to assess the effect of coagulation factors on all-cause mortality in prediabetes clusters.

RESULTS

Prediabetes clusters were assigned using published tools, and grouped into low-risk (clusters 1,2,4; n = 643) and high-risk (clusters 3,5,6; n = 274) clusters. Individuals in the high-risk clusters had a significantly increased risk of death (HR = 1.30; CI: 1.01 to 1.67) and showed significantly elevated levels of procoagulant factors (fibrinogen, FVII/VIII/IX), D-dimers, von-Willebrand factor, and PAI-1, compared to individuals in the low-risk clusters. In proportional hazards models adjusted for relevant confounders, elevated levels of fibrinogen, D-dimers, FVIII, and vWF were found to be associated with an increased risk of death. Multiple mediation analysis indicated that vWF significantly mediates the cluster-specific risk of death.

CONCLUSIONS

High-risk prediabetes clusters are associated with prothrombotic changes in the coagulation system that likely contribute to the increased mortality in those individuals at cardiometabolic risk. The hypercoagulable state observed in the high-risk clusters indicates an increased risk for cardiovascular and thrombotic diseases that should be considered in future risk stratification and therapeutic strategies.

Diabetes Management Based on the Phenotype and Stage of the Disease: An Expert Proposal from the AGORA Diabetes Collaborative Group

Diabetes is a complex and rapidly growing disease with heterogeneous clinical presentations. Recent advances in molecular and genetic technologies have led to the identification of various subtypes of diabetes. These advancements offer the potential for a more precise, individualized approach to treatment, known as precision medicine. Recognizing high-risk phenotypes and intervening early and intensively is crucial. A staging system for type 1 diabetes has been proposed and accepted globally. In this article, we will explore the different methods for categorizing and classifying type 2 diabetes (T2D) based on clinical characteristics, progression patterns, risk of complications, and the use of molecular techniques for patient grouping. We, as a team of experts, will also present an easy-to-follow treatment plan and guidance for non-specialists, particularly primary care physicians, that integrates the classification and staging of diabetes. This will help ensure that the most suitable therapy is applied to the different types of T2D at each stage of the disease's progression.

The central role of the gut microbiota in the pathophysiology and management of type 2 diabetes

The inhabitants of our intestines, collectively called the gut microbiome, comprise fungi, viruses, and bacterial strains. These microorganisms are involved in the fermentation of dietary compounds and the regulation of our adaptive and innate immune systems. Less known is the reciprocal interaction between the gut microbiota and type 2 diabetes mellitus (T2DM), as well as their role in modifying therapies to reduce associated morbidity and mortality. In this review, we aim to discuss the existing literature on gut microbial strains and their diet-derived metabolites involved in T2DM. We also explore the potential diagnostics and therapeutic avenues the gut microbiota presents for targeted T2DM management. Personalized treatment plans, driven by diet and medication based on the patient's microbiome and clinical markers, could optimize therapy.

Fasting and postprandial plasma metabolite responses to a 12-wk dietary intervention in tissue-specific insulin resistance: a secondary analysis of the PERSonalized glucose Optimization through Nutritional intervention (PERSON) randomized trial

BACKGROUND

We previously showed that dietary intervention effects on cardiometabolic health were driven by tissue-specific insulin resistance (IR) phenotype: individuals with predominant muscle IR (MIR) benefited more from a low-fat, high-protein, and high-fiber (LFHP) diet, whereas individuals with predominant liver insulin resistance (LIR) benefited more from a high-monounsaturated fatty acid (HMUFA) diet.

OBJECTIVES

To further characterize the effects of LFHP and HMUFA diets and their interaction with tissue-specific IR, we investigated dietary intervention effects on fasting and postprandial plasma metabolite profile.

METHODS

Adults with MIR or LIR (40-75 y, BMI 25-40 kg/m2) were randomly assigned to a 12-wk HMUFA or LFHP diet (n = 242). After the exclusion of statin use, 214 participants were included in this prespecified secondary analysis. Plasma samples were collected before (T = 0) and after (T = 30, 60, 120, and 240 min) a high-fat mixed meal for quantification of 247 metabolite measures using nuclear magnetic resonance spectroscopy.

RESULTS

A larger reduction in fasting VLDL-triacylglycerol (TAG) and VLDL particle size was observed in individuals with MIR following the LFHP diet and those with LIR following the HMUFA diet, although no longer statistically significant after false discovery rate (FDR) adjustment. No IR phenotype-by-diet interactions were found for postprandial plasma metabolites assessed as total area under the curve (tAUC). Irrespective of IR phenotype, the LFHP diet induced greater reductions in postprandial plasma tAUC of the larger VLDL particles and small HDL particles, and TAG content in most VLDL subclasses and the smaller LDL and HDL subclasses (for example, VLDL-TAG tAUC standardized mean change [95% CI] LFHP = -0.29 [-0.43, -0.16] compared with HMUFA = -0.04 [-0.16, 0.09]; FDR-adjusted P for diet × time = 0.041).

CONCLUSIONS

Diet effects on plasma metabolite profiles were more pronounced than phenotype-by-diet interactions. An LFHP diet may be more effective than an HMUFA diet for reducing cardiometabolic risk in individuals with tissue-specific IR, irrespective of IR phenotype. Am J Clin Nutr 20xx;x:xx. This trial was registered at the clinicaltrials.gov registration (https://clinicaltrials.gov/study/NCT03708419?term=NCT03708419&rank=1) as NCT03708419 and CCMO registration (https://www.toetsingonline.nl/to/ccmo_search.nsf/fABRpop?readform&unids=3969AABCD9BA27FEC12587F1001BCC65) as NL63768.068.17.

Surrogate measures of first-phase insulin secretion versus reference methods intravenous glucose tolerance test and hyperglycemic clamp: a systematic review and meta-analyses

INTRODUCTION

In this systematic review, we investigated the diagnostic accuracy of surrogate measures of insulin secretion based on fasting samples and the oral glucose tolerance test (OGTT). The first phase of insulin secretion was calculated using two gold standard methods; the hyperglycemic clamp (HGC) test and intravenous glucose tolerance test (IVGTT).

RESEARCH DESIGN AND METHODS

We conducted searches in the PubMed, Cochrane Central, and Web of Science databases, the last of which was conducted at the end of June 2021. Studies were included that measured first-phase insulin secretion in adults using both a gold-standard reference method (either HGC or IVGTT) and one or more surrogate measures from either fasting samples, OGTT or a meal-tolerance test. QUADAS-2, a revised tool for the quality assessment of diagnostic accuracy studies, was used for quality assessment. Random-effects meta-analyses were performed to examine the correlation between first-phase measured with gold standard and surrogate methods.

RESULTS

A total of 33 articles, encompassing 5362 individuals with normal glucose tolerance, pre-diabetes or type 2 diabetes, were included in our systematic review. Homeostatic model assessment (HOMA)-beta and Insulinogenic Index 30 (IGI(30)) were the surrogate measures validated in the largest number of studies (17 and 13, respectively). HOMA-beta's pooled correlation to the reference methods was 0.48 (95% CI 0.40 to 0.56) The pooled correlation of IGI to the reference methods was 0.61 (95% CI 0.54 to 0.68). The surrogate measures with the highest correlation to the reference methods were Kadowaki (0.67 (95% CI 0.61 to 0.73)) and Stumvoll's first-phase secretion (0.65 (95% CI 0.58 to 0.71)), both calculated from an OGTT.

CONCLUSIONS

Surrogate measures from the first 30 min of an OGTT capture the first phase of insulin secretion and are a good choice for epidemiological studies. HOMA-beta has a moderate correlation to the reference methods but is not a measure of the first phase specifically.

PROSPERO REGISTRATION NUMBER

The meta-analysis was registered at PROSPERO (Id: CRD42020169064) before inclusion started.

The insulin resistant brain: impact on whole-body metabolism and body fat distribution

Insulin exerts its actions not only on peripheral organs but is also transported into the brain where it performs distinct functions in various brain regions. This review highlights recent advancements in our understanding of insulin's actions within the brain, with a specific emphasis on investigations in humans. It summarises current knowledge on the transport of insulin into the brain. Subsequently, it showcases robust evidence demonstrating the existence and physiological consequences of brain insulin action, while also introducing the presence of brain insulin resistance in humans. This pathophysiological condition goes along with an impaired acute modulation of peripheral metabolism in response to brain insulin action, particularly in the postprandial state. Furthermore, brain insulin resistance has been associated with long-term adiposity and an unfavourable adipose tissue distribution, thus implicating it in the pathogenesis of subgroups of obesity and (pre)diabetes that are characterised by distinct patterns of body fat distribution. Encouragingly, emerging evidence suggests that brain insulin resistance could represent a treatable entity, thereby opening up novel therapeutic avenues to improve systemic metabolism and enhance brain functions, including cognition. The review closes with an outlook towards prospective research directions aimed at further elucidating the clinical implications of brain insulin resistance. It emphasises the critical need to establish feasible diagnostic measures and effective therapeutic interventions.

Evaluating Sex-specific Differences in Abdominal Fat Volume and Proton Density Fat Fraction at MRI Using Automated nnU-Net-based Segmentation

Sex-specific abdominal organ volume and proton density fat fraction (PDFF) in people with obesity during a weight loss intervention was assessed with automated multiorgan segmentation of quantitative water-fat MRI. An nnU-Net architecture was employed for automatic segmentation of abdominal organs, including visceral and subcutaneous adipose tissue, liver, and psoas and erector spinae muscle, based on quantitative chemical shift-encoded MRI and using ground truth labels generated from participants of the Lifestyle Intervention (LION) study. Each organ's volume and fat content were examined in 127 participants (73 female and 54 male participants; body mass index, 30-39.9 kg/m2) and in 81 (54 female and 32 male participants) of these participants after an 8-week formula-based low-calorie diet. Dice scores ranging from 0.91 to 0.97 were achieved for the automatic segmentation. PDFF was found to be lower in visceral adipose tissue compared with subcutaneous adipose tissue in both male and female participants. Before intervention, female participants exhibited higher PDFF in subcutaneous adipose tissue (90.6% vs 89.7%; P < .001) and lower PDFF in liver (8.6% vs 13.3%; P < .001) and visceral adipose tissue (76.4% vs 81.3%; P < .001) compared with male participants. This relation persisted after intervention. As a response to caloric restriction, male participants lost significantly more visceral adipose tissue volume (1.76 L vs 0.91 L; P < .001) and showed a higher decrease in subcutaneous adipose tissue PDFF (2.7% vs 1.5%; P < .001) than female participants. Automated body composition analysis on quantitative water-fat MRI data provides new insights for understanding sex-specific metabolic response to caloric restriction and weight loss in people with obesity. Keywords: Obesity, Chemical Shift-encoded MRI, Abdominal Fat Volume, Proton Density Fat Fraction, nnU-Net ClinicalTrials.gov registration no. NCT04023942 Supplemental material is available for this article. Published under a CC BY 4.0 license.

Genetic Subtypes of Prediabetes, Healthy Lifestyle, and Risk of Type 2 Diabetes

Prediabetes is a heterogenous metabolic state with various risks for development of type 2 diabetes (T2D). In this study, we used genetic data on 7,227 US Hispanic/Latino participants without diabetes from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) and 400,149 non-Hispanic White participants without diabetes from the UK Biobank (UKBB) to calculate five partitioned polygenetic risk scores (pPRSs) representing various pathways related to T2D. Consensus clustering was performed in participants with prediabetes in HCHS/SOL (n = 3,677) and UKBB (n = 16,284) separately based on these pPRSs. Six clusters of individuals with prediabetes with distinctive patterns of pPRSs and corresponding metabolic traits were identified in the HCHS/SOL, five of which were confirmed in the UKBB. Although baseline glycemic traits were similar across clusters, individuals in cluster 5 and cluster 6 showed an elevated risk of T2D during follow-up compared with cluster 1 (risk ratios [RRs] 1.29 [95% CI 1.08, 1.53] and 1.34 [1.13, 1.60], respectively). Inverse associations between a healthy lifestyle score and risk of T2D were observed across different clusters, with a suggestively stronger association observed in cluster 5 compared with cluster 1. Among individuals with a healthy lifestyle, those in cluster 5 had a similar risk of T2D compared with those in cluster 1 (RR 1.03 [0.91, 1.18]). This study identified genetic subtypes of prediabetes that differed in risk of progression to T2D and in benefits from a healthy lifestyle.

ARTICLE HIGHLIGHTS

EASL-EASD-EASO Clinical Practice Guidelines on the Management of Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD)

Metabolic dysfunction-associated steatotic liver disease (MASLD), previously termed non-alcoholic fatty liver disease (NAFLD), is defined as steatotic liver disease (SLD) in the presence of one or more cardiometabolic risk factor(s) and the absence of harmful alcohol intake. The spectrum of MASLD includes steatosis, metabolic dysfunction-associated steatohepatitis (MASH, previously NASH), fibrosis, cirrhosis and MASH-related hepatocellular carcinoma (HCC). This joint EASL-EASD-EASO guideline provides an update on definitions, prevention, screening, diagnosis and treatment for MASLD. Case-finding strategies for MASLD with liver fibrosis, using non-invasive tests, should be applied in individuals with cardiometabolic risk factors, abnormal liver enzymes, and/or radiological signs of hepatic steatosis, particularly in the presence of type 2 diabetes (T2D) or obesity with additional metabolic risk factor(s). A stepwise approach using blood-based scores (such as FIB-4) and, sequentially, imaging techniques (such as transient elastography) is suitable to rule-out/in advanced fibrosis, which is predictive of liver-related outcomes. In adults with MASLD, lifestyle modification - including weight loss, dietary changes, physical exercise and discouraging alcohol consumption - as well as optimal management of comorbidities - including use of incretin-based therapies (e.g. semaglutide, tirzepatide) for T2D or obesity, if indicated - is advised. Bariatric surgery is also an option in individuals with MASLD and obesity. If locally approved and dependent on the label, adults with non-cirrhotic MASH and significant liver fibrosis (stage ≥2) should be considered for a MASH-targeted treatment with resmetirom, which demonstrated histological effectiveness on steatohepatitis and fibrosis with an acceptable safety and tolerability profile. No MASH-targeted pharmacotherapy can currently be recommended for the cirrhotic stage. Management of MASH-related cirrhosis includes adaptations of metabolic drugs, nutritional counselling, surveillance for portal hypertension and HCC, as well as liver transplantation in decompensated cirrhosis.

Reframing prediabetes: A call for better risk stratification and intervention

Prediabetes is an intermediate state of glucose homeostasis whereby plasma glucose concentrations are above normal but below the threshold of diagnosis for diabetes. Over the last several decades, criteria for prediabetes have changed as the cut points for normal glucose concentration and diagnosis of diabetes have shifted. Global consensus does not exist for prediabetes criteria; as a result, the clinical course and risk for type 2 diabetes vary. At present, we can identify individuals with prediabetes based on three glycemic tests (hemoglobin A1c, fasting plasma glucose, and 2-h plasma glucose during an oral glucose tolerance test). The majority of individuals diagnosed with prediabetes meet only one of these criteria. Meeting one, two, or all glycemic criteria changes risk for type 2 diabetes, but this information is not widely known and does not currently guide intervention strategies for individuals with prediabetes. This review summarizes current epidemiology, prognosis, and intervention strategies for individuals diagnosed with prediabetes and suggests a call for more precise risk stratification of individuals with prediabetes as elevated (one prediabetes criterion), high risk (two prediabetes criteria), and very high risk (three prediabetes criteria). In addition, the roles of oral glucose tolerance testing and continuous glucose monitoring in the diagnostic criteria for prediabetes need reassessment. Finally, we must reframe our goals for prediabetes and prioritize intensive interventions for those at high and very high risk for type 2 diabetes.

Longitudinal HbA1c patterns before the first treatment of diabetes in routine clinical practice: A latent class trajectory analysis

AIMS

To examine the longitudinal heterogeneity of HbA1c preceding the initiation of diabetes treatment in clinical practice.

METHODS

In this population-based study, we used HbA1c from routine laboratory and healthcare databases. Latent class trajectory analysis was used to classify individuals according to their longitudinal HbA1c patterns before first glucose-lowering drug prescription irrespective of type of diabetes.

RESULTS

Among 21,556 individuals initiating diabetes treatment during 2017-2018, 20,733 (96 %) had HbA1c measured (median 4 measurements [IQR 2-7]) in the 5 years preceding treatment initiation. Four classes with distinct HbA1c trajectories were identified, with varying steepness of increase in HbA1c. The largest class (74 % of the individuals) had mean HbA1c above the 48 mmol/mol threshold 9 months before treatment initiation. Mean HbA1c was 52 mmol/mol (95 % CI 52-52) at treatment initiation. In the remaining three classes, mean HbA1c exceeded 48 mmol/mol almost 1.5 years before treatment initiation and reached 79 mmol/mol (95 % CI 78-80), 105 mmol/mol (95 % CI 104-106), and 137 mmol/mol (95 % CI 135-140) before treatment initiation.

CONCLUSION

We identified four distinct longitudinal HbA1c patterns before initiation of diabetes treatment in clinical practice. All had mean HbA1c levels exceeding the diagnostic threshold many months before treatment initiation, indicating therapeutic inertia.

Divergent age-associated and metabolism-associated gut microbiome signatures modulate cardiovascular disease risk

Insight into associations between the gut microbiome with metabolism and aging is crucial for tailoring interventions to promote healthy longevity. In a discovery cohort of 10,207 individuals aged 40-93 years, we used 21 metabolic parameters to classify individuals into five clusters, termed metabolic multimorbidity clusters (MCs), that represent different metabolic subphenotypes. Compared to the cluster classified as metabolically healthy (MC1), clusters classified as 'obesity-related mixed' (MC4) and 'hyperglycemia' (MC5) exhibited an increased 11.1-year cardiovascular disease (CVD) risk by 75% (multivariable-adjusted hazard ratio (HR): 1.75, 95% confidence interval (CI): 1.43-2.14) and by 117% (2.17, 1.72-2.74), respectively. These associations were replicated in a second cohort of 9,061 individuals with a 10.0-year follow-up. Based on analysis of 4,491 shotgun fecal metagenomes from the discovery cohort, we found that gut microbial composition was associated with both MCs and age. Next, using 55 age-specific microbial species to capture biological age, we developed a gut microbial age (MA) metric, which was validated in four external cohorts comprising 4,425 metagenomic samples. Among individuals aged 60 years or older, the increased CVD risk associated with MC4 or MC5, as compared to MC1, MC2 or MC3, was exacerbated in individuals with high MA but diminished in individuals with low MA, independent of age, sex and other lifestyle and dietary factors. This pattern, in which younger MA appears to counteract the CVD risk attributable to metabolic dysfunction, implies a modulating role of MA in cardiovascular health for metabolically unhealthy older people.

Prediabetes as a risk factor for all-cause and cause-specific mortality: a prospective analysis of 115,919 adults without diabetes in Mexico City

BACKGROUND

Prediabetes has been associated with increased all-cause and cardiovascular mortality. However, no large-scale studies have been conducted in Mexico or Latin America examining these associations.

METHODS

We analyzed data from 115,919 adults without diabetes (diagnosed or undiagnosed) aged 35-84 years who participated in the Mexico City Prospective Study between 1998 and 2004. Participants were followed until January 1st, 2021 for cause-specific mortality. We defined prediabetes according to the American Diabetes Association (ADA, HbA1c 5.7% to 6.4%) and the International Expert Committee (IEC, HbA1c 6.0-6.4%) definitions. Cox regression adjusted for confounders was used to estimate all-cause and cause-specific mortality rate ratios (RR) at ages 35-74 years associated with prediabetes.

FINDINGS

During 2,085,392 person-years of follow-up (median in survivors 19 years), there were 6,810 deaths at ages 35-74, including 1,742 from cardiovascular disease, 892 from renal disease and 108 from acute diabetic crises. Of 110,405 participants aged 35-74 years at recruitment, 28,852 (26%) had ADA-defined prediabetes and 7,203 (7%) had IEC-defined prediabetes. Compared with those without prediabetes, individuals with prediabetes had higher risk of all-cause mortality at ages 35-74 years (RR 1.13, 95% CI 1.07-1.19 for ADA-defined prediabetes and RR 1.28, 1.18-1.39 for IEC-defined prediabetes), as well as increased risk of cardiovascular mortality (RR 1.22 [1.10-1.35] and 1.42 [1.22-1.65], respectively), renal mortality (RR 1.35 [1.08-1.68] and 1.69 [1.24-2.31], respectively), and death from an acute diabetic crisis (RR 2.63 [1.76-3.94] and 3.43 [2.09-5.62], respectively). RRs were larger at younger than at older ages, and similar for men compared to women. The absolute excess risk associated with ADA and IEC-defined prediabetes at ages 35-74 accounted for6% and 3% of cardiovascular deaths respectively, 10% and 5% of renal deaths respectively, and 31% and 14% of acute diabetic deaths respectively.

INTERPRETATION

Prediabetes is a significant risk factor for all-cause, cardiovascular, renal, and acute diabetic deaths in Mexican adults. Identification and timely management of individuals with prediabetes for targeted risk reduction could contribute to reducing premature mortality from cardiometabolic causes in this population.

FUNDING

Wellcome Trust, the Mexican Health Ministry, the National Council of Science and Technology for Mexico, Cancer Research UK, British Heart Foundation, UK Medical Research Council. Instituto Nacional de Geriatría (Mexico City).

Delving the vitamin D receptor variation and expression profiles in the context of type 2 diabetes among families

BACKGROUND

Vitamin D is essential for insulin secretion and sensitivity. Consequently, its inadequacy is linked to higher insulin resistance and Type 2 Diabetes (T2D). The Vitamin D receptor (VDR) gene is one potential candidate for T2D, and multiple polymorphisms in VDR have been examined in various populations, but no conclusive answers have been provided.

OBJECTIVES

This study was designed to evaluate the susceptibility of VDR gene polymorphism and its expression in diabetic families in Pakistan.

METHODOLOGY

In this family-based study, twenty diabetic families with a positive family history of T2D and at least three T2D patients were recruited from outpatient clinics and public hospitals. The current study comprised 143 individuals with 55 affected and 88 unaffected individuals. Blood samples of the selected families were collected. DNA was extracted from the collected samples and the PCR-RFLP method was followed to identify the genotyping and RT-qPCR for expression. Phenotypic and genotypic pedigrees of the families were developed by the progeny online tool. The association values of SNPs were determined by TDT and DFAM analysis implemented on Plink software.

RESULTS

The results explained a significant familial aggregation among phenotypic characters including Age, Gender, BMI (body mass index), age of disease diagnosis, disease duration, and blood pressure in the probands, affected FDRs (First Degree Relatives) and affected SDRs (Second Degree Relatives). A significant association of rs731236 C/T (OR = 1.522), rs2228570 C/T (OR = 1.327) with p < 0.05. Whereas, for rs1544410 G/A (OR = 0.9706) and rs7975232 T/G (OR = 0.7368) no considerable association evidence was seen (p > 0.05) in families. The mRNA expression of VDR increased threefold (p = 0.0204) in patients compared to controls. Variation-based expression analysis exhibited that the rs2228570 genotype influences the expression.

CONCLUSION

A linkage was found among the FDRs with probands. Variation in the gene VDR at loci rs731236 and rs2228570 was associated with familial T2D. However further research is required to explore more genetic factors that could influence T2D risks in families.

Heterogeneity in elevated glucose and A1C as predictors of the prediabetes to diabetes transition: Framingham Heart Study, Multi-Ethnic Study on Atherosclerosis, Jackson Heart Study, and Atherosclerosis Risk In Communities

Introduction

There are a number of glycemic definitions for prediabetes; however, the heterogeneity in diabetes transition rates from prediabetes across different glycemic definitions in major US cohorts has been unexplored. We estimate the variability in risk and relative risk of adiposity based on diagnostic criteria like fasting glucose and hemoglobin A1C% (HA1C%).

Research Design and Methods

We estimated transition rate from prediabetes, as defined by fasting glucose between 100-125 and/or 110-125 mg/dL, and HA1C% between 5.7-6.5% in participant data from the Framingham Heart Study, Multi-Ethnic Study on Atherosclerosis, Atherosclerosis Risk in Communities, and the Jackson Heart Study. We estimated the heterogeneity and prediction interval across cohorts, stratifying by age, sex, and body mass index. For individuals who were prediabetic, we estimated the relative risk for obesity, blood pressure, education, age, and sex for diabetes.

Results

There is substantial heterogeneity in diabetes transition rates across cohorts and prediabetes definitions with large prediction intervals. We observed the highest range of rates in individuals with fasting glucose of 110-125 mg/dL ranging from 2-18 per 100 person-years. Across different cohorts, the association obesity or hypertension in the progression to diabetes was consistent, yet it varied in magnitude. We provide a database of transition rates across subgroups and cohorts for comparison in future studies.

Conclusion

The absolute transition rate from prediabetes to diabetes significantly depends on cohort and prediabetes definitions.

Effectiveness of a cognitive behavioral therapy-integrated, hospital-based program for prediabetes: a matched cohort study

Intensive lifestyle interventions are effective in preventing T2DM, but evidence is lacking for high cardiometabolic individuals in hospital settings. We evaluated a hospital-based, diabetes prevention program integrating cognitive behavioral therapy (CBT) for individuals with prediabetes. This matched cohort assessed individuals with prediabetes receiving the prevention program, which were matched 1:1 with those receiving standard care. The year-long program included five in-person sessions and several online sessions covering prediabetes self-management, dietary and behavioral interventions. Kaplan-Meier and Cox regression models estimated the 60-month T2DM incidence rate. Of 192 patients, 190 joined the prevention program, while 190 out of 10,260 individuals were in the standard-care group. Both groups had similar baseline characteristics (mean age 58.9 ± 10.2 years, FPG 102.3 ± 8.2 mg/dL, HbA1c 5.9 ± 0.3%, BMI 26.2 kg/m2, metabolic syndrome 75%, and ASCVD 6.3%). After 12 months, the intervention group only showed significant decreases in FPG, HbA1c, and triglyceride levels and weight. At 60 months, the T2DM incidence rate was 1.7 (95% CI 0.9-2.8) in the intervention group and 3.5 (2.4-4.9) in the standard-care group. After adjusting for variables, the intervention group had a 0.46 times lower risk of developing diabetes. Therefore, healthcare providers should actively promote CBT-integrated, hospital-based diabetes prevention programs to halve diabetes progression.

Transforming the cardiometabolic disease landscape: Multimodal AI-powered approaches in prevention and management

The rise of artificial intelligence (AI) has revolutionized various scientific fields, particularly in medicine, where it has enabled the modeling of complex relationships from massive datasets. Initially, AI algorithms focused on improved interpretation of diagnostic studies such as chest X-rays and electrocardiograms in addition to predicting patient outcomes and future disease onset. However, AI has evolved with the introduction of transformer models, allowing analysis of the diverse, multimodal data sources existing in medicine today. Multimodal AI holds great promise in more accurate disease risk assessment and stratification as well as optimizing the key driving factors in cardiometabolic disease: blood pressure, sleep, stress, glucose control, weight, nutrition, and physical activity. In this article we outline the current state of medical AI in cardiometabolic disease, highlighting the potential of multimodal AI to augment personalized prevention and treatment strategies in cardiometabolic disease.

Precise glucose measurement in sodium fluoride-citrate plasma affects estimates of prevalence in diabetes and prediabetes

OBJECTIVES

Estimates of glucose concentrations vary among types of blood samples, which impact on the assessment of diabetes prevalence. Guidelines recommend a conversion factor to calculate plasma glucose from measurements of glucose in whole blood. The American Diabetes Association recommends the use of blood drawing tubes containing sodium fluoride (NaF) and citrate, which have not yet been evaluated regarding possible differences in glucose concentration and conversion factors. Thus, we compared glucose measurements in NaF-citrate plasma and venous whole blood and estimated the impact of differences on diabetes and prediabetes prevalence.

METHODS

Glucose differences were calculated by Bland-Altman analysis with pairwise comparison of glucose measurements from whole blood and NaF-citrate plasma (n=578) in clinical studies of the German Diabetes Center. Subsequently, we computed the impact of the glucose difference on diabetes and prediabetes prevalence in the population-based National Health and Nutrition Examination Survey (NHANES).

RESULTS

Even upon conversion of whole blood to plasma glucose concentrations using the recommended conversion factor, mean glucose concentration difference remained 4.72 % higher in NaF-citrate plasma. Applying the higher glucose estimates, increases the population-based diabetes and prediabetes prevalence by 13.67 and 33.97 % or more than 7.2 and 13 million people in NHANES, respectively. Additional economic burden could be about 20 $ billion per year due to undiagnosed diabetes.

CONCLUSIONS

The recommended conversion factor is not valid for NaF-citrate plasma. Systematic bias of glucose measurements due to sampling type leads to clinically relevant higher estimates of diabetes and prediabetes prevalence.

Metabolic Profiles of Type 2 Diabetes and Their Association With Renal Complications

CONTEXT

The components of metabolic syndrome (MetS) are interrelated and associated with renal complications in patients with type 2 diabetes (T2D).

OBJECTIVE

We aimed to reveal prevalent metabolic profiles in patients with T2D and identify which metabolic profiles were risk markers for renal progression.

METHODS

A total of 3556 participants with T2D from a hospital (derivation cohort) and 931 participants with T2D from a community survey (external validation cohort) were included. The primary outcome was the onset of diabetic kidney disease (DKD), and secondary outcomes included estimated glomerular filtration rate (eGFR) decline, macroalbuminuria, and end-stage renal disease (ESRD). In the derivation cohort, clusters were identified using the 5 components of MetS, and their relationships with the outcomes were assessed. To validate the findings, participants in the validation cohort were assigned to clusters. Multivariate odds ratios (ORs) of the primary outcome were evaluated in both cohorts, adjusted for multiple covariates at baseline.

RESULTS

In the derivation cohort, 6 clusters were identified as metabolic profiles. Compared with cluster 1, cluster 3 (severe hyperglycemia) had increased risks of DKD (hazard ratio [HR] [95% CI]: 1.72 [1.39-2.12]), macroalbuminuria (2.74 [1.84-4.08]), ESRD (4.31 [1.16-15.99]), and eGFR decline [P < .001]; cluster 4 (moderate dyslipidemia) had increased risks of DKD (1.97 [1.53-2.54]) and macroalbuminuria (2.62 [1.61-4.25]). In the validation cohort, clusters 3 and 4 were replicated to have significantly increased risks of DKD (adjusted ORs: 1.24 [1.07-1.44] and 1.39 [1.03-1.87]).

CONCLUSION

We identified 6 prevalent metabolic profiles in patients with T2D. Severe hyperglycemia and moderate dyslipidemia were validated as significant risk markers for DKD.

The clinical relevance of a polygenic risk score for type 2 diabetes mellitus in the Korean population

The clinical utility of a type 2 diabetes mellitus (T2DM) polygenic risk score (PRS) in the East Asian population remains underexplored. We aimed to examine the potential prognostic value of a T2DM PRS and assess its viability as a clinical instrument. We first established a T2DM PRS for 5490 Korean individuals using East Asian Biobank data (269,487 samples). Subsequently, we assessed the predictive capability of this T2DM PRS in a prospective longitudinal study with baseline data and data from seven additional follow-ups. Our analysis showed that the T2DM PRS could predict the transition of glucose tolerance stages from normal glucose tolerance to prediabetes and from prediabetes to T2DM. Moreover, T2DM patients in the top-decile PRS group were more likely to be treated with insulin (hazard ratio = 1.69, p value = 2.31E-02) than were those in the remaining PRS groups. T2DM PRS values were significantly high in the severe diabetes subgroup, characterized by insulin resistance and β -cell dysfunction (p value = 0.0012). The prediction models with the T2DM PRS had significantly greater Harrel's C-indices than did corresponding models without it. By utilizing prospective longitudinal study data and extensive clinical risk factor information, our analysis provides valuable insights into the multifaceted clinical utility of the T2DM PRS.

Prediabetes and Cardiometabolic Risk: The Need for Improved Diagnostic Strategies and Treatment to Prevent Diabetes and Cardiovascular Disease

The progression from prediabetes to type-2 diabetes depends on multiple pathophysiological, clinical, and epidemiological factors that generally overlap. Both insulin resistance and decreased insulin secretion are considered to be the main causes. The diagnosis and approach to the prediabetic patient are heterogeneous. There is no agreement on the diagnostic criteria to identify prediabetic subjects or the approach to those with insufficient responses to treatment, with respect to regression to normal glycemic values or the prevention of complications. The stratification of prediabetic patients, considering the indicators of impaired fasting glucose, impaired glucose tolerance, or HbA1c, can help to identify the sub-phenotypes of subjects at risk for T2DM. However, considering other associated risk factors, such as impaired lipid profiles, or risk scores, such as the Finnish Diabetes Risk Score, may improve classification. Nevertheless, we still do not have enough information regarding cardiovascular risk reduction. The sub-phenotyping of subjects with prediabetes may provide an opportunity to improve the screening and management of cardiometabolic risk in subjects with prediabetes.

The Semmelweis Study: a longitudinal occupational cohort study within the framework of the Semmelweis Caring University Model Program for supporting healthy aging

The Semmelweis Study is a prospective occupational cohort study that seeks to enroll all employees of Semmelweis University (Budapest, Hungary) aged 25 years and older, with a population of 8866 people, 70.5% of whom are women. The study builds on the successful experiences of the Whitehall II study and aims to investigate the complex relationships between lifestyle, environmental, and occupational risk factors, and the development and progression of chronic age-associated diseases. An important goal of the Semmelweis Study is to identify groups of people who are aging unsuccessfully and therefore have an increased risk of developing age-associated diseases. To achieve this, the study takes a multidisciplinary approach, collecting economic, social, psychological, cognitive, health, and biological data. The Semmelweis Study comprises a baseline data collection with open healthcare data linkage, followed by repeated data collection waves every 5 years. Data are collected through computer-assisted self-completed questionnaires, followed by a physical health examination, physiological measurements, and the assessment of biomarkers. This article provides a comprehensive overview of the Semmelweis Study, including its origin, context, objectives, design, relevance, and expected contributions.

Analysis of type 2 diabetes heterogeneity with a tree-like representation: insights from the prospective German Diabetes Study and the LURIC cohort

BACKGROUND

Heterogeneity in type 2 diabetes can be represented by a tree-like graph structure by use of reversed graph-embedded dimensionality reduction. We aimed to examine whether this approach can be used to stratify key pathophysiological components and diabetes-related complications during longitudinal follow-up of individuals with recent-onset type 2 diabetes.

METHODS

For this cohort analysis, 927 participants aged 18-69 years from the German Diabetes Study (GDS) with recent-onset type 2 diabetes were mapped onto a previously developed two-dimensional tree based on nine simple clinical and laboratory variables, residualised for age and sex. Insulin sensitivity was assessed by a hyperinsulinaemic-euglycaemic clamp, insulin secretion was assessed by intravenous glucose tolerance test, hepatic lipid content was assessed by 1 H magnetic resonance spectroscopy, serum interleukin (IL)-6 and IL-18 were assessed by ELISA, and peripheral and autonomic neuropathy were assessed by functional and clinical measures. Participants were followed up for up to 16 years. We also investigated heart failure and all-cause mortality in 794 individuals with type 2 diabetes undergoing invasive coronary diagnostics from the Ludwigshafen Risk and Cardiovascular Health (LURIC) cohort.

FINDINGS

There were gradients of clamp-measured insulin sensitivity (both dimensions: p<0·0001) and insulin secretion (pdim1<0·0001, pdim2=0·00097) across the tree. Individuals in the region with the lowest insulin sensitivity had the highest hepatic lipid content (n=205, pdim1<0·0001, pdim2=0·037), pro-inflammatory biomarkers (IL-6: n=348, pdim1<0·0001, pdim2=0·013; IL-18: n=350, pdim1<0·0001, pdim2=0·38), and elevated cardiovascular risk (nevents=143, pdim1=0·14, pdim2<0·00081), whereas individuals positioned in the branch with the lowest insulin secretion were more prone to require insulin therapy (nevents=85, pdim1=0·032, pdim2=0·12) and had the highest risk of diabetic sensorimotor polyneuropathy (nevents=184, pdim1=0·012, pdim2=0·044) and cardiac autonomic neuropathy (nevents=118, pdim1=0·0094, pdim2=0·06). In the LURIC cohort, all-cause mortality was highest in the tree branch showing insulin resistance (nevents=488, pdim1=0·12, pdim2=0·0032). Significant gradients differentiated individuals having heart failure with preserved ejection fraction from those who had heart failure with reduced ejection fraction.

INTERPRETATION

These data define the pathophysiological underpinnings of the tree structure, which has the potential to stratify diabetes-related complications on the basis of routinely available variables and thereby expand the toolbox of precision diabetes diagnosis.

FUNDING

German Diabetes Center, German Federal Ministry of Health, Ministry of Culture and Science of the state of North Rhine-Westphalia, German Federal Ministry of Education and Research, German Diabetes Association, German Center for Diabetes Research, European Community, German Research Foundation, and Schmutzler Stiftung.

Inter-organ crosstalk during development and progression of type 2 diabetes mellitus

Type 2 diabetes mellitus (T2DM) is characterized by tissue-specific insulin resistance and pancreatic β-cell dysfunction, which result from the interplay of local abnormalities within different tissues and systemic dysregulation of tissue crosstalk. The main local mechanisms comprise metabolic (lipid) signalling, altered mitochondrial metabolism with oxidative stress, endoplasmic reticulum stress and local inflammation. While the role of endocrine dysregulation in T2DM pathogenesis is well established, other forms of inter-organ crosstalk deserve closer investigation to better understand the multifactorial transition from normoglycaemia to hyperglycaemia. This narrative Review addresses the impact of certain tissue-specific messenger systems, such as metabolites, peptides and proteins and microRNAs, their secretion patterns and possible alternative transport mechanisms, such as extracellular vesicles (exosomes). The focus is on the effects of these messengers on distant organs during the development of T2DM and progression to its complications. Starting from the adipose tissue as a major organ relevant to T2DM pathophysiology, the discussion is expanded to other key tissues, such as skeletal muscle, liver, the endocrine pancreas and the intestine. Subsequently, this Review also sheds light on the potential of multimarker panels derived from these biomarkers and related multi-omics for the prediction of risk and progression of T2DM, novel diabetes mellitus subtypes and/or endotypes and T2DM-related complications.

Disentangling Dual Threats: Premature Coronary Artery Disease and Early-Onset Type 2 Diabetes Mellitus in South Asians

South Asian individuals (SAs) face heightened risks of premature coronary artery disease (CAD) and early-onset type 2 diabetes mellitus (T2DM), with grave health, societal, and economic implications due to the region's dense population. Both conditions, influenced by cardiometabolic risk factors such as insulin resistance, hypertension, and central adiposity, manifest earlier and with unique thresholds in SAs. Epidemiological, demographic, nutritional, environmental, sociocultural, and economic transitions in SA have exacerbated the twin epidemic. The coupling of premature CAD and T2DM arises from increased obesity due to limited adipose storage, early-life undernutrition, distinct fat thresholds, reduced muscle mass, and a predisposition for hepatic fat accumulation from certain dietary choices cumulatively precipitating a decline in insulin sensitivity. As T2DM ensues, the β-cell adaptive responses are suboptimal, precipitating a transition from compensatory hyperinsulinemia to β-cell decompensation, underscoring a reduced functional β-cell reserve in SAs. This review delves into the interplay of these mechanisms and highlights a prediabetes endotype tied to elevated vascular risk. Deciphering these mechanistic interconnections promises to refine stratification paradigms, surpassing extant risk-prediction strategies.

Distinct patterns of personalised dietary advice delivered by a metabotype framework similarly improve dietary quality and metabolic health parameters: secondary analysis of a randomised controlled trial

Background

In a 12-week randomised controlled trial, personalised nutrition delivered using a metabotype framework improved dietary intake, metabolic health parameters and the metabolomic profile compared to population-level dietary advice. The objective of the present work was to investigate the patterns of dietary advice delivered during the intervention and the alterations in dietary intake and metabolic and metabolomic profiles to obtain further insights into the effectiveness of the metabotype framework.

Methods

Forty-nine individuals were randomised into the intervention group and subsequently classified into metabotypes using four biomarkers (triacylglycerol, HDL-C, total cholesterol, glucose). These individuals received personalised dietary advice from decision tree algorithms containing metabotypes and individual characteristics. In a secondary analysis of the data, patterns of dietary advice were identified by clustering individuals according to the dietary messages received and clusters were compared for changes in dietary intake and metabolic health parameters. Correlations between changes in blood clinical chemistry and changes in metabolite levels were investigated.

Results

Two clusters of individuals with distinct patterns of dietary advice were identified. Cluster 1 had the highest percentage of messages delivered to increase the intake of beans and pulses and milk and dairy products. Cluster 2 had the highest percentage of messages delivered to limit the intake of foods high in added sugar, high-fat foods and alcohol. Following the intervention, both patterns improved dietary quality assessed by the Alternate Mediterranean Diet Score and the Alternative Healthy Eating Index, nutrient intakes, blood pressure, triacylglycerol and LDL-C (p ≤ 0.05). Several correlations were identified between changes in total cholesterol, LDL-C, triacylglycerol, insulin and HOMA-IR and changes in metabolites levels, including mostly lipids (sphingomyelins, lysophosphatidylcholines, glycerophosphocholines and fatty acid carnitines).

Conclusion

The findings indicate that the metabotype framework effectively personalises and delivers dietary advice to improve dietary quality and metabolic health.

Clinical trial registration

isrctn.com, identifier ISRCTN15305840.