Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy最新文献

Purpose: This study aims to determine apolipoprotein B-48 (ApoB48) levels before and after a high-fat diet in individuals with metabolic syndrome (MetS), and to explore its relationship with MetS. It provides new risk markers for exploring the mechanism of MetS and offers important theoretical basis and candidate targets for subsequent research.

Patients and methods: A total of 192 adult Chinese volunteers were enrolled in this cross-sectional study. Participants were divided into control and MetS groups according to the NCEP ATP III diagnostic criteria for MetS. All participants underwent oral fat tolerance testing (OFTT). Serum concentrations of fasting and postprandial ApoB48 were measured, and their relationships with each MetS component were analyzed.

Results: Among 192 participants, 81 were diagnosed with MetS. Both fasting and postprandial ApoB48 concentrations were higher in the MetS group than in the control group (P < 0.05). The incidence of MetS increased with rising ApoB48 levels. In both groups, ApoB48 concentrations initially increased and then decreased after OFTT, peaking at 4 h postprandially, with higher peak values observed in the MetS group. Fasting and 2-h postprandial ApoB48 levels had the strongest correlations with MetS.

Conclusion: Higher ApoB48 levels before and after OFTT were positively correlated with an increased risk of MetS and were higher than those in the healthy population. Fasting ApoB48 and 2-h postprandial ApoB48 levels after a high-fat meal may be potential markers of MetS.

Purpose: To develop and validate an individualized risk prediction model for carotid atherosclerosis (CAS) in non-obese patients with type 2 diabetes mellitus (T2DM), addressing the need for a non-invasive and practical screening tool.

Patients and methods: This retrospective study analyzed data from a cohort of 1014 non-obese T2DM patients (mean age: 58.65±11.95 years; 691 males and 323 females) enrolled between 2016 and 2025. We collected a comprehensive set of clinical variables, including demographics, body mass index (BMI), blood pressure, lipid profile, hepatic and renal function, and glycemic indicators. The population was randomly divided into a training set and an internal validation set. Feature selection was performed using univariate and multivariate logistic analysis to identify significant predictors. A nomogram was subsequently constructed based on these independent risk factors. The model's performance was rigorously evaluated by assessing its discriminative ability with the area under the receiver operating characteristic curve (AUC), its calibration with calibration plots, and its potential clinical net benefit with decision curve analysis (DCA).

Results: The final prediction model incorporated five key clinical variables: age, gender, systolic blood pressure, low-density lipoprotein cholesterol, and fasting blood glucose. The nomogram demonstrated strong and consistent performance, achieving AUC values of 0.828 in the training set and 0.824 in the validation set, indicating high discriminatory power. Calibration curves showed excellent agreement between predicted probabilities and actual observed outcomes. Furthermore, decision curve analysis confirmed the clinical utility of the model for a wide range of risk thresholds.

Conclusion: The validated nomogram provides a reliable and easily applicable tool for the early identification of CAS risk in non-obese individuals with T2DM. This model facilitates personalized risk assessment and supports clinical decision-making for targeted preventive strategies, potentially reducing the incidence of associated cardiovascular and cerebrovascular events.

Flavonoids are widely present in various plants and possess multiple biological activities, such as anti-inflammation, antioxidation and anticancer. In the realm of disease prevention and therapeutic interventions, a noteworthy function is assumed by these entities, evident from their significant research potentiality and intrinsic value. Characterized by an excessive lipid accumulation within the hepatic cells, metabolic associated fatty liver disease (MAFLD) manifests as a prevalent chronic ailment of the liver. The "multiple hits" theory suggests that its occurrence is the result of systemic homeostasis imbalance, influenced by factors such as abnormal lipid metabolism, inflammatory reaction, oxidative stress, insulin resistance, and gut microbiota. However, there are no effective clinical drugs for it. Recent studies have found that flavonoid active components can alleviate MAFLD through multiple pathways, including regulating abnormal lipid metabolism, inhibiting inflammatory response, alleviating oxidative stress, improving insulin resistance, regulating gut microbiota, and regulating liver autophagy. Therefore, this paper summarizes the pharmacological action and related mechanisms of flavonoid active components in improving MAFLD. This manuscript may provide a reference for seeking a novel therapeutic agent for MAFLD management.

Objective: To investigate the associations of anthropometric indicators and left ventricular hypertrophy (LVH) in middle-aged and elderly individuals with type 2 diabetes mellitus (T2DM).

Methods: This was a cross-sectional study. A total of 3330 individuals were recruited from three tertiary hospitals across China between July 2018 and June 2023. Demographic characteristics, biochemical parameters, and echocardiographic measurements were systematically collected. Anthropometric indices, including body mass index (BMI), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), body adiposity index (BAI), body roundness index (BRI), and weight-adjusted-waist index (WWI) were calculated using standardized protocols. Multivariable binary logistic regression models were employed to evaluate the associations between anthropometric indices and LVH. The diagnostic accuracy was assessed using receiver operating characteristic (ROC) curve analysis.

Results: Multivariable logistic regression analysis revealed that WHR (OR:1.128, 95% CI:1.043, 1.220) and BRI (OR:1.455, 95% CI:1.011, 2.094) were independently associated with increased LVH risk in middle-aged males. Among middle-aged females, BAI (OR:1.112, 95% CI:1.046, 1.182), WHtR (OR:1.048, 95% CI:1.007, 1.090), and BRI (OR:1.234, 95% CI:1.040, 1.465) demonstrated significant associations with LVH. However, in the elderly population, none of the variables showed a statistically significant association with LVH (P>0.05). ROC curve analysis identified WHR as the strongest predictor in middle-aged males (AUC:0.674, 95% CI:0.584, 0.764), whereas BAI exhibited the highest discriminatory accuracy among middle-aged females (AUC:0.578, 95% CI:0.523, 0.633).

Conclusion: Sex-specific associations between obesity indices and LVH were observed in middle-aged individuals with T2DM, necessitating distinct risk-stratification strategies: prioritizing abdominal obesity in males and comprehensive adiposity distribution in females. Notably, the broad relevance of BRI in both sexes highlights its clinical utility.

Aim: To assess the association between sodium-glucose cotransporter 2 (SGLT2) inhibitor use and the risk of tumor development and survival outcomes in patients with type 2 diabetes.

Methods: This retrospective cohort study included 350 patients with type 2 diabetes treated at our institution between January 2021 and January 2025. Patients were categorized into an observation group (n = 189) receiving SGLT2 inhibitors and a control group (n = 161) treated with other antidiabetic medications. Clinical characteristics, glycemic control, cumulative drug exposure, and tumor incidence (lung, colorectal, prostate, breast, bladder, and hepatic cancers) were analyzed. Kaplan-Meier methods were used to evaluate cancer incidence and mortality outcomes.

Results: Overall tumor incidence was significantly lower in the SGLT2 inhibitor group than in the control group (P < 0.001), mainly due to reduced lung (P = 0.018) and ovarian cancers (P = 0.017). Smoking, alcohol consumption, and poor glycemic control were associated with higher overall and site-specific tumor risks. The SGLT2 inhibitor group showed better metabolic profiles, with lower FBG, HbA1c, LDL, TC, TG, and higher HDL levels (all P < 0.05), as well as improved renal function indicated by lower BUN and creatinine and higher eGFR (all P < 0.001). Kaplan-Meier analysis demonstrated significantly longer progression-free and overall survival in the SGLT2 inhibitor group (both P < 0.01).

Conclusion: SGLT2 inhibitors reduced overall tumor risk, especially lung and ovarian cancers, and improved metabolic and survival outcomes in type 2 diabetes.

Purpose: This randomized controlled mixed methods pilot study evaluated the preliminary signal of effectiveness of a culturally tailored intervention embedded within a standard Diabetes Self-Management Education (DSME) program.

Patients and methods: Fourteen Black adults with uncontrolled diabetes (A1C ≥ 7.5) enrolled in the study. The study was conducted at a community center and over the phone within a US Midwestern State. All participants participated in a 6-week evidence-based DSME program, with a subset of participants (n=7) randomized to the intervention receiving additional education sessions and race-congruent phone-based peer support throughout the 6-month intervention. Changes in Hemoglobin A1c (A1C) (primary outcome) and self-reported medication adherence (secondary outcome), and other psychosocial outcomes (beliefs about diabetes, self-efficacy, diabetes empowerment, etc.) were assessed at 3 and 6 months using paired t-tests. Between-group differences were analyzed using the Mann-Whitney U-test and within-group differences were analyzed using Wilcoxon signed-rank test. Qualitative data on participant's perceived impact of the intervention on primary and secondary outcomes were collected through semi-structured interviews and analyzed to identify themes. Subsequently, a mixed methods analysis was conducted to compare quantitative and qualitative findings.

Results: At 6-months, A1C was statistically significantly lower in the intervention group (7.9% (SD =0.4; 95% CI [7.6-8.2]); n=7) compared to the control group (10.6% (SD =0.7; 95% CI [9.9-11.2]); p =0.01; d=0.73; n = 6). There were no significant between-group differences (p =0.22) in medication adherence between the 2 groups. Qualitative themes related to beliefs about medicines, diabetes distress, etc. were identified, and integrated with quantitative psychosocial outcomes further explaining the findings.

Conclusion: The findings suggest a signal of evidence for a future adequately powered, randomized controlled trial, testing whether the addition of the theory and evidence-informed culturally specific components of the intervention improve outcomes compared to the DSME program alone.

Objective: Managing diabetes daily can be an emotional burden for older adults. Research shows that self-compassion, which refers to the ability to be kind and understanding toward oneself, can help improve emotional well-being. This study aimed to develop a machine learning prediction model to identify the influencing factors of self-compassion among community-dwelling older adults with type 2 diabetes.

Methods: We conducted this study in Jiaxing, China, during July and August 2024. We invited community-dwelling older adults with type 2 diabetes to complete a questionnaire that measured their levels of self-compassion, depression, and anxiety. Our goal was to find which of 26 different personal and health-related factors most influenced self-compassion. To achieve this, we used several machine learning algorithms to build and compare predictive models, selecting the best-performing one. Finally, we applied a technique called SHapley Additive exPlanations (SHAP) to clearly understand and interpret how each factor impacts self-compassion.

Results: The random forest model performed the best. SHAP analysis indicated that depression, hemoglobin A1c (HbA1C), waist circumference, and anxiety were risk factors of self-compassion, while fasting blood-glucose (FBG) was a protective factor.

Conclusion: This study provides a reliable tool for identifying older adults with type 2 diabetes who may benefit from support. The findings suggest that healthcare providers should prioritize managing depression and anxiety, along with controlling HbA1c and waist circumference, to enhance self-compassion. These results can be translated into a practical risk scorecard to guide personalized care strategies in community health settings.

Objective: To investigate fasting C-peptide to high-density lipoprotein cholesterol ratio (FHR) as a predictor for non-alcoholic fatty liver disease (NAFLD) in Chinese adults with type 2 diabetes mellitus (T2DM).

Methods: This study enrolled 718 participants with T2DM from Shenzhen People's Hospital, China. Participants were stratified by FCP/HDL-C ratio (FHR) quartiles. Multiple linear regression assessed the association between FHR and NAFLD. A generalized additive model (GAM) tested for nonlinearity. Subgroup analyses evaluated result robustness. The area under the curve (AUC) evaluated the performance of the FHR model for NAFLD occurrence.

Results: After adjusting for relevant variables, FHR was positively correlated with NAFLD (OR = 1.30, 95% CI (1.15, 1.48)). FHR demonstrated a nonlinear association with NAFLD, characterized by a threshold value of 1.23. The effect sizes and confidence intervals on the left and right sides of the inflection point were 3.07 (1.51, 6.24) and 1.20 (1.05, 1.37), respectively. Subgroup analysis showed a stronger correlation could be detected in patients with systolic blood pressure (SBP) <140 mmHg, alanine transaminase (ALT) > 40U/L, fasting blood glucose (FBG) ⩽7 mmol/L, urinary albumin to creatinine ratio (UACR) ⩽30mg/g, triglyceride (TG) ⩽1.7 mmol/L and the patients with drinking history. The FHR ratio model exhibited better discriminative ability in NAFLD (AUC = 0.697) compared to individual FCP (AUC = 0.649) or HDL-C (AUC = 0.635) alone.

Conclusion: The association between FHR and NAFLD was nonlinear, with a positive relationship observed when FHR exceeded the threshold of 1.23.

Background: The association between Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) and the development of new carotid plaque in young adults requires further evidence from prospective studies.

Methods:  In this study, young adults underwent abdominal and a carotid ultrasounds measurement were included. The carotid plaque progression was assessed in 2 years after baseline. MASLD is defined according to the liver ultrasound findings and self-reported alcohol consumption. Stepped adjusting multivariable logistic regression were employed to analyze the association between MASLD and the outcome. Subgroup analysis was conducted among sex and different amount of metabolic risk factors.

Results: A total of 36.54% (2411/6598) of all participants had MASLD at baseline. Among them, 626 (9.49%) participants were found new onset of carotid plaque in two years. Subjects who had progression of plaque had higher proportion of MASLD (53.99% vs 34.71%, SMD=0.396). Statistically significant positive associations were observed in unadjusted logistic regression models in overall or each sex, respectively. After fully adjustment, the association was only significant among female (OR:2.19, 95% CI: 1.28-3.72) and those had no metabolic risk factor (OR:1.67,95% CI:1.01-2.76). No significant associations were identified in all male subgroups, whereas the associations were still existing among female subgroups.

Conclusion: MASLD was found to be a risk factor of progression of carotid plaque among females and those who had not suffered from metabolic risk factor. Prevention should be focused on young adults who have MASLD at physical examination to reduce their risk of future atherosclerosis.