Search Results (9,064)

Background: Metabolic syndrome is a complex disorder characterized by the coexistence of multiple risk factors, including dysglycemia, hypertension, dyslipidemia, and visceral obesity. Both metabolic syndrome and diabetes mellitus are closely associated with the onset of microvascular complications such as retinopathy, polyneuropathy, and nephropathy. Methods: This narrative review analyzed 137 studies published up to 2025, retrieved from PubMed and Crossref databases. The objective was to identify and evaluate potential biomarkers that could facilitate the early detection of microvascular complications in patients with metabolic syndrome. Results: Several biomarkers demonstrated a strong correlation with microvascular complications in individuals with metabolic syndrome. These findings suggest their potential role in early diagnosis and risk assessment. Conclusions: The identification of reliable biomarkers may enhance early detection and targeted interventions for microvascular complications in metabolic syndrome. Further research is essential to validate these markers and establish their clinical applicability in routine medical practice. Full article

Background/Objectives: Our lab has previously reported that Grifola frondosa (maitake mushroom) GF5000 has antidiabetic potential owing to its ability to improve insulin resistance. This study aimed to gain insight into the system-level hypoglycemic mechanisms of GF5000 using transcriptomics, proteomics, and network pharmacology. This study provides new insights into the hypoglycemic mechanisms of GF5000, identifying key molecular targets involved in mitigating insulin resistance in T2DM. Methods: Liver protein and gene expression in normal control (NC), diabetic control (DC), and GF5000-treated (GF5000) rats were analyzed via iTRAQ and RNA-seq. The relationships between differentially expressed genes (DEGs), differentially expressed proteins (DEPs), and type 2 diabetes (T2DM) disease targets were studied using Metascape and the Cytoscape GeneMANIA plug-in. Results: One hundred and fifty-two DEGs and sixty-two DEPs were identified; twenty DEGs/DEPs exhibited the same trend in mRNA and protein expression levels when comparing the GF5000 vs. DC groups. The Metascape analysis revealed that the T2DM disease targets included four DEGs—Gck, Scd, Abcb4, and Cyp3a9—and two DEPs—glucokinase and acetyl-CoA carboxylase 2. A Cytoscape–GeneMANIA analysis of thirteen DEGs/DEPs related to T2DM showed that Apoa1/Apolipoprotein A-I, Gckr/glucokinase regulatory protein, and Gck/glucokinase had the highest connectivity and centrality in the topological network. The qPCR results confirmed that GF5000 increased the mRNA expression of GCK in GCK-knockdown HepG2 cells. Conclusions: These results provide theoretical evidence for the use of GF5000 as a potential active nutritional ingredient for the prevention and treatment of T2DM. Our findings suggest that GF5000 targets multiple pathways implicated in T2DM, offering a multi-faceted approach to disease management and prevention. Full article

Background/Objectives: The pathogenesis of diabetic kidney disease (DKD) is complex and multifactorial. Because of its complications and reduced number of diagnostic biomarkers, it is important to explore new biomarkers with possible roles in the early diagnosis of DKD. Our study aims to investigate the pattern of previously identified metabolites and their association with biomarkers of endothelial dysfunction, proximal tubule (PT) dysfunction, and podocyte injury. Methods: A total of 110 participants, comprising 20 healthy individuals and 90 patients divided in three groups were enrolled in the study: normoalbuminuria, microalbuminuria, and macroalbuminuria. Untargeted and targeted metabolomic methods were employed to assess urinary and serum biomarkers, as well as indicators of endothelial dysfunction, podocyte damage, and PT dysfunction through ELISA techniques. Results: Our research uncovered specific metabolites that exhibit varying levels across different sub-groups. Notably, glycine serves as a distinguishing factor between group C and the normoalbuminuric group. Furthermore, glycine is correlated with endothelial markers, especially VCAM. We observed a gradual decrease in kynurenic acid levels from group C to group P3; this biomarker also demonstrates an inverse relationship with both p-selectin and VCAM. Additionally, tryptophan levels decline progressively from group C to group P3, accompanied by a negative correlation with p-selectin and VCAM. Urinary tiglylglycine also differentiates among the patient groups, with concentrations decreasing as the condition worsens. It shows a strong positive correlation with nephrin, podocalyxin, KIM1, and NAG. Conclusions: In conclusion, glycine, tiglylglycine, kynurenic acid and tryptophan may be considered putative biomarkers for early diagnosis of DKD and T2DM progression. Full article

Background/Objectives: The current standard of care for assessing chronic kidney disease complicating diabetes (DKD) includes measurement of estimated glomerular filtration rate (eGFR) and urinary albumin:creatinine ratio (uACR) but both tests have limitations. The present study compared the biomarker-based Promarker^®D test with conventional biochemical measures for predicting future kidney function decline in adults with type 2 diabetes (T2D). Methods: Baseline concentrations of apolipoprotein A-IV, CD5 antigen-like protein and insulin-like growth factor binding protein 3 were combined with age, serum HDL cholesterol and eGFR to generate PromarkerD risk scores for incident DKD/eGFR decline ≥ 30% (the primary endpoint) in 857 adults with T2D (mean age 65.4 years, 54% males). Logistic regression modelling was used to compare the association of (i) PromarkerD, (ii) eGFR, (iii) uACR, and (iv) eGFR plus uACR with this outcome during 4 years of follow-up. Results: Study participants were classified by PromarkerD as low (63%), moderate (13%), or high risk (24%) for kidney function decline at baseline. Over a mean 4.2 years, 12.5% developed the primary endpoint. PromarkerD scores showed significantly higher predictive performance (area under the receiver operating characteristic curve (AUC) 0.88 (95% confidence interval (CI) 0.85–0.91)) compared to conventional biochemical measures (AUC = 0.63–0.82). There was a progressive increase in risk with moderate and high risk by PromarkerD exhibiting greater odds of the primary endpoint compared to those at low risk (odds ratios (OR) (95% CI) 8.11 (3.99–16.94) and 21.34 (12.03–40.54), respectively, both p < 0.001). Conclusions: PromarkerD more accurately identifies adults with T2D at risk of kidney function decline than current usual care biochemical tests. Full article

Background: Diabetes mellitus (DM) is a global healthcare concern with a rising prevalence. Patients with DM have a severely diminished quality of life due to the extensive range of connected complications. One of the most impactful diabetes-associated pathologies is diabetic macular edema (DME), as it is a major cause of blindness globally. Patients with DME present many concomitant diseases that influence their prognosis. The present research seeks to describe the most frequent DME-related comorbidities. Method: This study enrolled 105 participants previously diagnosed with type 1 DM (T1DM) or type 2 DM (T2DM) (77 presenting with DME), who were evaluated regarding other associated comorbidities. Results: Patients in the DME group presented a median age of 65, with a mean disease duration of 15 years and inadequate glycemic control, reflected by a mean HbA1c of 7.5%. All patients presented at least one comorbidity, with hypertension (100%) and dyslipidemia (62.3%) being the most prevalent. Spearman analysis revealed a statistically significant correlation between DME and diabetes duration (p = 0.01), proliferative diabetic retinopathy (p = 0.004), and chronic kidney disease (p = 0.034). Conclusions: Patients with DME often present multiple comorbidities that must be screened for and addressed through a multidisciplinary approach. Full article

Pancreatic β-cells rely on a delicate balance between the endoplasmic reticulum (ER) and mitochondria to maintain sufficient insulin stores for the regulation of whole animal glucose homeostasis. The ER supports proinsulin maturation through oxidative protein folding, while mitochondria supply the energy and redox buffering that maintain ER proteostasis. In the development of Type 2 diabetes (T2D), the progressive decline of β-cell function is closely linked to disruptions in ER-mitochondrial communication. Mitochondrial dysfunction is a well-established driver of β-cell failure, whereas the downstream consequences for ER redox homeostasis have only recently emerged. This interdependence of ER-mitochondrial functions suggests that an imbalance is both a cause and consequence of metabolic dysfunction. In this review, we discuss the regulatory mechanisms of ER redox control and requirements for mitochondrial function. In addition, we describe how ER redox imbalances may trigger mitochondrial dysfunction in a vicious feed forward cycle that accelerates β-cell dysfunction and T2D onset. Full article

Background: Diet plays an important role in preventing and managing the progression from prediabetes to type 2 diabetes mellitus (T2DM). This study aims to develop prediction models incorporating specific dietary indicators and explore the performance in T2DM patients and non-T2DM patients. Methods: This retrospective study was conducted on 2215 patients from the Henan Rural Cohort. The key variables were selected using univariate analysis and the least absolute shrinkage and selection operator (LASSO). Multiple predictive models were constructed separately based on dietary and clinical factors. The performance of different models was compared and the impact of integrating dietary factors on prediction accuracy was evaluated. Receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were used to evaluate the predictive performance. Meanwhile, group and spatial validation sets were used to further assess the models. SHapley Additive exPlanations (SHAP) analysis was applied to identify key factors influencing the progression of T2DM. Results: Nine dietary indicators were quantitatively collected through standardized questionnaires to construct dietary models. The extreme gradient boosting (XGBoost) model outperformed the other three models in T2DM prediction. The area under the curve (AUC) and F1 score of the dietary model in the validation cohort were 0.929 [95% confidence interval (CI) 0.916–0.942] and 0.865 (95%CI 0.845–0.884), respectively. Both were higher than the traditional model (AUC and F1 score were 0.854 and 0.779, respectively, p < 0.001). SHAP analysis showed that fasting plasma glucose, eggs, whole grains, income level, red meat, nuts, high-density lipoprotein cholesterol, and age were key predictors of the progression. Additionally, the calibration curves displayed a favorable agreement between the dietary model and actual observations. DCA revealed that employing the XGBoost model to predict the risk of T2DM occurrence would be advantageous if the threshold were beyond 9%. Conclusions: The XGBoost model constructed by dietary indicators has shown good performance in predicting T2DM. Emphasizing the role of diet is crucial in personalized patient care and management. Full article

Background: The mechanisms of diabetes remission following bariatric surgery independent of calorie restriction and weight loss remain unclear. Objectives: To undertake a systematic review and meta-analysis to investigate mechanisms underpinning diabetes remission. Methods: We included individuals with type 2 diabetes who have undergone RYGB, SG, and a very low-calorie diet (VLCD). In total, 234 studies were identified (N = 52 for qualitative; N = 40 for quantitative synthesis). Review Manager v5.4 and IBM SPSS for Windows (v28.0.1.1) were used for analysis. Results: Crude annualised diabetes relapse rates for RYGB and SG are as follows: −6.98 ± 16.19 (p = 0.046) and −2.75 ± 4.94 (p = 0.08); crude remission rates for RYGB and SG, respectively, are as follows: 39.59 ± 45.93 (p = 0.000) and 33.36 ± 33.87 SG (p = 0.006). Differences in other metabolic outcomes (standardised mean difference and 95% confidence intervals (CIs)) are BMI: ([RYGB: −2.73, 95%CI: −3.14 to −2.32, p < 0.000001) (SG: −2.82, 95%CI: −5.04 to −0.60, p = 0.01)]; HbA1c: [(RYGB: −1.58, 95%CI: −2.16 to −1.00, p < 0.00001) (SG: −1.42, 95%CI: −1.69 to −1.15, p < 0.00001)]; insulin: [(RYGB: 0.16, 95%CI: −0.19 to −0.50, p = 0.37) (SG: −3.00, 95%CI: −3.17 to −2.82, p = 0.75)]; and fat mass [(RYGB: −2.56, 95%CI: −4.49 to −0.64, p = 0.009) (SG: −1.69, 95%CI: −4.58 to 1.21, p = 0.25)]. RYGB and SG produced a significant improvement in HOMA-B measurements. Adiponectin and the Matsuda index were significantly increased with RYGB. No difference was observed for other metabolic markers (RYGB: GLP-1, GIP, leptin, ghrelin, PYY) (SG: GLP-1 and FGF19) (VLCD: leptin, GLP-1, GIP, and ghrelin). Conclusions: Diabetes remission following RYGB and SG was primarily driven by improvement in beta-cell function, with improvement in insulin resistance markers also observed for RYGB, driven by reductions in fat mass. No other metabolic mechanism explaining diabetes remission was observed based on clinical studies. Full article

Insulin-like growth factor 2 mRNA-binding protein 2 (IMP2) is an RNA-binding protein that positively regulates m6A-modified RNAs involved in critical cellular processes such as metabolism, oncogenesis, and immune function. Here, we elucidate facets of IMP2 biology, including several mechanisms of action on RNA, factors that regulate IMP2 expression, its relevant biological target RNAs, its role in normal development and disease, and its potential as a therapeutic target. IMP2 is a multi-level regulator of metabolism, influencing pathways linked to diabetes, obesity, and adipose function. Through genomic amplification and transcriptional overexpression in cancer cells, IMP2 can drive the initiation and progression of multiple cancer types, and high expression is associated with decreased overall survival of patients with cancer. IMP2 influences normal immune function, inflammation, macrophage polarization, and tumor immune evasion. IMP2 has emerged as a promising therapeutic target, particularly for cancers and metabolic diseases. Full article

Chronic obstructive pulmonary disease (COPD) and type 2 diabetes mellitus (T2DM) are highly prevalent chronic conditions, frequently coexisting due to their shared pathophysiological mechanisms and risk factors. Epidemiological studies estimate that up to 30% of COPD patients have comorbid T2DM, contributing to worsened disease progression, more hospitalizations, and higher mortality rates. Systemic inflammation in COPD contributes to insulin resistance by increasing pro-inflammatory cytokines (TNF-α, IL-6, and CRP), which impair glucose metabolism and beta-cell function. Conversely, hyperglycemia in T2DM exacerbates oxidative stress, leading to endothelial dysfunction, reduced lung function, and impaired pulmonary repair mechanisms. A comprehensive narrative review was conducted to evaluate the interplay between COPD and T2DM, examining shared pathophysiological mechanisms, clinical consequences, and management strategies. The co-occurrence of COPD and T2DM accelerates disease development, elevates hospitalization rates, and deteriorates overall prognosis. Pharmacological interactions complicate illness treatment, requiring a multidisciplinary therapy strategy. Recent data underscore the need to integrate palliative care, facilitate shared decision-making, and provide psychological support to enhance patient outcomes. Efficient therapy of COPD-T2DM comorbidity necessitates a customized, interdisciplinary strategy that targets both respiratory and metabolic health. Preliminary prognostic dialogues, palliative care, and holistic lifestyle modifications can improve patient quality of life and clinical results. Full article

This review aims to present the latest advancements in prediction models for diabetes mellitus, with a particular focus on children and adolescents. It highlights models for predicting both type 1 and type 2 diabetes in this population, emphasizing the inclusion of risk factors that facilitate the identification of potential occurrence and early detection of diabetes in young individuals. Newly identified factors for differentiating between types of diabetes are discussed, alongside an overview of various machine learning and deep learning algorithms specifically adapted for diabetes prediction in children and adolescents. The advantages and limitations of these methods are critically examined. The review underscores the necessity of addressing challenges posed by incomplete datasets and emphasizes the importance of creating a comprehensive data repository. Such developments are essential for enabling artificial intelligence tools to generate models suitable for broad clinical application and advancing early diagnostic and preventive strategies for diabetes in children and adolescents. Full article

Metabolic dysfunction-associated steatotic liver disease (MASLD), a hepatic form of metabolic syndrome, often co-occurs with type 2 diabetes (T2D) and now affects approximately 30% of the global population. MASLD encompasses conditions from simple steatosis to metabolic dysfunction-associated steatohepatitis, with oxidative stress (OS) driving progression through inflammation. This study analyzes the expression levels of circulating miRNAs and redox status markers in MASLD patients with and without T2D, exploring their potential as disease biomarkers. The expressions of miR-21, miR-34a, and miR-122 were analyzed in the platelet-poor plasma of 147 participants, divided into three groups: MASLD + T2D (48), MASLD (50), and a control group (49). Total oxidant status (TOS), total antioxidant status (TAS), ischemia-modified albumin (IMA), and superoxide anion radical (O₂^•−) were measured in serum and plasma. Logistic regression showed that miR-21, miR-34a, TOS, TAS, O₂^•−, and IMA were positive predictors of MASLD, while miR-21 and TAS were negative predictors of T2D in MASLD. Although miR-122 did not show a significant association with either condition, in combination with miR-34a and other markers such as lipid status and liver enzymes, a new significant predictor of MASLD was identified. Circulating miRNAs in combination with redox status markers, lipid status and liver enzymes show potential as MASLD biomarkers. Full article

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a multifactorial disorder characterized by excessive lipid accumulation in the liver which dysregulates the organ’s function. The key contributor to MASLD development is insulin resistance (IR) which affects many organs (including adipose tissue, skeletal muscles, and the liver), whereas the molecular background is associated with oxidative, nitrosative, and carbonyl stress. Among molecules responsible for carbonyl stress effects, methylglyoxal (MGO) seems to play a major pathological function. MGO—a by-product of glycolysis, fructolysis, and lipolysis (from glycerol and fatty acids-derived ketone bodies)—is implicated in hyperglycemia, hyperlipidemia, obesity, type 2 diabetes, hypertension, and cardiovascular diseases. Its causative effect in the stimulation of prooxidative and proinflammatory pathways has been well documented. Since metabolic dysregulation leading to these pathologies promotes MASLD, the role of MGO in MASLD is addressed in this review. Potential MGO participation in the mechanism of MASLD development is discussed in regard to its role in different signaling routes leading to pathological events accelerating the disorder. Moreover, treatment strategies including approved and potential therapies in MASLD are overviewed and discussed in this review. Among them, medications aimed at attenuating MGO-induced pathological processes are addressed. Full article

Background/Objectives: During the last decade, there has been an increased interest in phenolic compound-rich natural products as natural therapies for regulating the molecular pathways behind central obesity and associated metabolic disorders. The present scoping review presents the outcomes of clinical and preclinical studies examining the anti-obesity effects of high phenolic extra virgin olive oil (HP-EVOO) and its possible underlying molecular mechanisms. Methods: Studies published between 2014 and 2024 were searched via MEDLINE, Scopus, Cochrane, the Web of Science, Semantic Scholar, Google Scholar, Science.gov, and Clinicaltrials.gov databases. A combination of keywords and Boolean logic was used to search throughout the last decade in all databases, including “hyperglycemia” or “hypertension” or “metabolic syndrome” or “dyslipidemia” or “hyperlipidemia” or “hypoglycemia” or “obesity” or “macrovascular diabetic complications” or “microvascular diabetic complications” or “cardiovascular disease” or “overweight” or “insulin sensitivity” or “insulin resistance” and “extra virgin olive oil” or “high phenolic olive oil” and “human” or “animal model”. Results: The 10-year literature survey identified 21 studies in both animal models and humans, indicating that HP-EVOO improves inflammation, glycemic control, oxidative stress and endothelial function, potentially protecting against metabolic syndrome, hypertension and type 2 diabetes, even compared to EVOO. Moreover, HP-EVOO’s antiplatelet effect and improvement in HDL functionality reduce cardiovascular risk. Conclusions: The evidence presented in this study demonstrates that HP-EVOO represents an effective preventive and therapeutic dietary approach to cardiometabolic diseases. Full article

Aim: Mobile health (mHealth) applications have been reported to be effective in improving glycaemic control and cardiometabolic health, but mainly as part of shorter-term intervention studies. The aim of this study is to examine the effect of the ongoing Defeat Diabetes mHealth low-carbohydrate diet (LCD) intervention on clinical markers and cardiometabolic risk after 6 months of intervention. Methods: Data were collected via primary care physicians as part of routine T2D monitoring. These included HbA1c (primary outcome), blood pressure, blood lipids, and markers of kidney and liver function. Anthropometrics, as well as changes in the prescription of diabetes, hypertension, and dyslipidaemia medication, were also recorded. Calculated variables, total cholesterol to HDL-c, triglyceride to HDL-c, and waist to height ratios, were analysed to examine changes in cardiometabolic risk profile. Three-day food records were used to assess dietary intake and intervention adherence. Univariate regression models examined changes from baseline to 6 months. Results: Ninety-four participants remained in the study out of the ninety-nine at baseline (mean age 59 ± 11 years, 55 females). After 6 months of intervention, there were significant reductions in HbA1c by −1.0% (95% CI: −1.3 to −0.6), as well as in the liver enzymes ALT (−9.3 U/L 95% CI −16.3 to −2.4) and GGT (−18.8 U/L 95% CI: −31.4 to −6.3) across the cohort. In addition, there was a significant reduction in cardiometabolic risk, as measured by the calculated variables and a decrease in waist circumference (−4.6 cm 95% CI: −8.9 to −0.2). Conclusions: People with T2D receiving LCD education and resources through the Defeat Diabetes mHealth app (version 3.3.8) improved their glycaemic control after 6 months of intervention. Cardiometabolic risk profile and liver function also showed significant improvement. These findings indicate that the use of an LCD digital app is a valuable adjunct in the management of T2D. Full article