Current diabetes reviews最新文献

Introduction: To evaluate the association between low-carbohydrate diet (LCD) score and atherosclerotic cardiovascular disease (ASCVD) among individuals with type 2 diabetes mellitus (T2DM).

Methods: A total of 3685 participants from the National Health and Nutrition Examination Survey database 2007-2020 were included in this cross-sectional study. The primary outcome of this study was the 10-year ASCVD risk. We used the weighted logistic regression models to assess the association between LCD score and 10-year ASCVD risk. Stratified analysis based on age, body mass index (BMI), hypertension, dyslipidemia, and chronic kidney disease (CKD) was conducted. Odds ratio (OR) and 95% confidence interval (CI) were calculated.

Results: After adjusting for all confounding factors, when LCD was treated as a continuous variable, the findings revealed an inverse association between LCD and 10-year ASCVD risk among individuals with T2DM (OR=0.97, 95% CI: 0.94-0.99, p=0.045). When LCD was stratified into tertiles, individuals in the highest tertiles of LCD exhibited a negative association with 10-year ASCVD risk compared to those in the first tertile (OR=0.66, 95% CI: 0.46-0.95, p=0.025). Subgroup analysis indicated an negative association between high tertiles of LCD and 10-years ASCVD risk in individuals with T2DM who had a BMI≥25kg/m2 (OR=0.66, 95% CI: 0.45-0.97, p<0.05), hypertension (OR=0.61, 95% CI: 0.40-0.91, p<0.05) and dyslipidemia (OR=0.64, 95% CI: 0.43-0.95, p<0.05), and BMI<25kg/m2 with history of CKD (OR=0.64, 95% CI: 0.42-0.96, p<0.05).

Discussion: The inverse association observed between LCD score and ASCVD risk in individuals with T2DM may be partly explained by improved glycemic control, reduced insulin resistance, and favorable lipid profile changes often associated with lower carbohydrate intake. Notably, the protective effect was more pronounced in individuals with additional metabolic comorbidities, such as obesity, hypertension, and dyslipidemia, suggesting that these subgroups may derive greater cardiovascular benefit from LCD-style eating patterns. However, the cross-sectional nature of our study precludes causal inference. Additionally, dietary intake was self-reported and subject to recall bias, and residual confounding cannot be fully ruled out. Despite these limitations, our findings contribute to the growing body of evidence supporting dietary carbohydrate modification as a potential strategy in cardiovascular risk management among patients with T2DM.

Conclusion: Our study found an inverse association between LCD score and 10-year ASCVD risk in individuals with T2DM. These findings may provide a reference for future research and inform dietary recommendations, though causal relationships cannot be established due to the cross-sectional design.

Introduction: Diabetic nephropathy (DN) is a progressive renal complication that significantly contributes to end-stage renal disease. Hyperglycaemia contributes to the formation of advanced glycation end-products (AGEs). The interaction between AGEs and their receptor (RAGE) plays a key role in the progression of DN. RAGE activation increases oxidative stress and promotes inflammation, thereby evoking cellular and molecular damage. Together, these events result in kidney injury and varying degrees of proteinuria. This study aims to evaluate the drug-like properties of potential natural compounds derived from Curcuma caesia and their potential effectiveness against DN.

Methods: This study investigates the antioxidant properties of Curcuma caesia (CC) rhizome extracts, alongside in silico methodologies including molecular docking, QSAR, and ADMET analysis to identify potential metabolites.

Results: In this study, we examined the potential of phytochemicals identified from the rhizome extracts of Curcuma caesia (CC) that may mimic AGEs and inhibit RAGE activation. We assessed whether these phytochemicals could prevent ROS accumulation and inflammation, thereby providing renoprotection in a diabetic milieu. Using molecular docking and ADMET analysis, we identified two compounds, Lappaol A and Piperaduncin B, in the methanolic extract of CC, which demonstrated a stronger affinity for interacting with RAGE than the AGE compound MODIC and the RAGE inhibitor Azeliragon.

Discussion: Since the interaction between AGEs and RAGE contributes to major pathological events in the development of DN, inhibiting this interaction could be a valuable therapeutic strategy against DN and other AGE-mediated pathologies such as retinopathy and neuropathy. Virtual screening of the identified compounds revealed that Lappaol A and Piperaduncin B effectively bind to RAGE and may interrupt RAGE activation, thereby potentially slowing the progression of DN.

Conclusion: These natural compounds exhibited promising drug-like characteristics against the target protein RAGE and may serve as lead compounds for the development of RAGE inhibitors. The study recommends further in vitro and in vivo investigations to assess the therapeutic potential of these identified compounds in the treatment of diabetic nephropathy.

Introduction: Type 1 Diabetes Mellitus (T1DM) is a multifactorial autoimmune disease marked by pancreatic β-cell destruction and insulin deficiency. Its pathogenesis involves genetic predisposition, environmental exposures, and epigenetic modifications. This review examines how epigenetic mechanisms, including DNA methylation, histone modifications, and noncoding RNAs, contribute to T1DM and their potential as biomarkers and therapeutic targets.

Methods: A comprehensive literature review was conducted using PubMed, Scopus, Web of Knowledge, and Google Scholar. Studies on DNA methylation, histone modifications, and noncoding RNA expression in T1DM patients and experimental models were analyzed to identify mechanisms linking epigenetic mechanisms to disease progression.

Results: Epigenetic alterations, including abnormal DNA methylation, histone modifications, and dysregulated non-coding RNAs, play central roles in immune imbalance and β-cell dysfunction. DNA methylation affects genes involved in immune regulation, insulin synthesis, and β-cell survival. Non-coding RNAs regulate transcriptional and inflammatory pathways, while histone modifications alter chromatin accessibility, further contributing to β-cell loss.

Discussion: Epigenetic mechanisms mediate interactions between genetic risk and environmental triggers, shaping autoimmunity and disease heterogeneity. These findings underscore their relevance for early detection and targeted interventions in T1DM.

Conclusion: Epigenetic changes form a critical link between genetics, environment, and immune dysfunction in T1DM. By regulating immune responses and β-cell integrity, they drive disease onset and progression. Their study provides opportunities for predictive biomarkers and innovative therapies aimed at reprogramming epigenetic pathways to restore immune tolerance and preserve β-cell function.

Introduction: Chronotype refers to an individual's circadian preference in biological and behavioral rhythm relative to the external light-dark cycle. light-dark cycle. Evening chronotype is associated with increased diabetes risk, probably due to inappropriate eating habits, reduced physical activity, and altered sleeping habits. This study aims to find an association between evening chronotropic and diabetes.

Methods: A cross-sectional study was conducted in the General Medicine department over six months. 201 patients satisfying the study criteria were included. Horne-Ostberg Morningness- Eveningness Questionnaire (MEQ), blood samples, sleep quality, and anthropometric indicators were obtained. Postprandial blood sugar (PPBS), fasting blood sugar (FBS), glycated hemoglobin (HbA1c), Total cholesterol (TC), triglycerides (TGs), High-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and very low-density lipoproteins (VLDL) were measured with standard techniques. A univariate logistic regression analysis, along with post-hoc tests, was employed to find the role of independent variables on each chronotype.

Results: Among the 81 evening chronotypes, 85.1% were diabetics, the mean HDL value in the evening chronotypes was 35.2 mg/dl, significantly (p<0.001) lower than the other two chronotypes. Waist-to-hip ratio (WHR) and body mass index (BMI) were significantly higher in the evening chronotype p= 0.011, p<0.001, respectively. The mean FBS, PPBS, and HbA1c values (170.07 mg/dL, 242 mg/dL, and 8.95%) were higher among evening chronotypes and were statistically significant (p<0.001).

Discussion: Findings highlight that evening chronotypes demonstrate poorer glycaemic control, dyslipidaemias, and adverse anthropometric indices, suggesting that circadian misalignment may contribute to T2DM progression. Lifestyle modification could be a promising intervention.

Conclusion: Our study suggests Evening chronotypes are more likely to have metabolic dysregulation and poor glycemic control.

Introduction: Insulin resistance has become a serious health problem over time. As people age, the incidence of insulin resistance increases. Genetic factors in families with a history of type 2 diabetes are also key risk factors. In Indonesia, an increase in the prevalence of type 2 diabetes to 8.5% was reported in 2018. This indicates that insulin resistance necessitates comprehensive management, encompassing both pharmacological and non-pharmacological approaches. This systematic review aims to discuss insulin resistance and its management, which can be achieved both pharmacologically through various available drugs and non-pharmacologically by modifying lifestyle habits that can be applied to patients with type 2 diabetes.

Method: Studies examining the comprehensive management of insulin resistance with antidiabetic pharmacological drugs and non-pharmaceutical interventions published between 2018 and 2023 were comprehensively searched using advanced searches on PubMed and Google Scholar, according to the specified inclusion and exclusion criteria.

Results: Twenty studies were selected that met the inclusion criteria and have low risks of bias in most domains.

Discussion: Non-pharmacological therapy, such as lifestyle changes that include a ketogenic diet, a vegetarian diet, a structured exercise intervention program, aerobic exercise, Continuous Positive Airway Pressure (CPAP), and electroacupuncture therapy, can significantly reduce insulin resistance and increase insulin sensitivity. Drugs currently prescribed for type 2 DM stimulate insulin secretion or increase insulin sensitivity.

Conclusion: There are benefits of a plant-based diet, a ketogenic diet, and physical exercise in reducing insulin resistance non-pharmacologically. Meanwhile, pharmacologically, the first drug often given is metformin monotherapy. Combination therapy may be considered if monotherapy does not achieve the therapeutic target.

Introduction: Impaired hypoglycemic awareness (IAH) in type 2 diabetes mellitus (T2DM) is linked to mild cognitive impairment (MCI), but the underlying mechanisms are unclear. This study aimed to explore the chain mediating role of two psychological factors, illness perception (IP) and fear of hypoglycemia (FOH), in the relationship between IAH and MCI.

Methods: A cross-sectional survey of 251 T2DM patients was conducted using convenience sampling at two tertiary hospitals. Data on IAH, IP, FOH, and MCI were collected using standardized questionnaires. Data were analyzed and compared using SPSS 27.0 and AMOS 27.0.

Results: There were significant correlations among IAH, IP, FOH, and MCI. Higher IAH was associated with increased FOH and more negative IP, which were both linked to worse cognitive function. Mediation analysis showed that IAH indirectly affects MCI through three pathways: independently via FOH, independently via IP, and via a chained effect of FOH and IP.

Discussion: The findings underscored that the link between IAH and cognitive decline is not solely physiological, but is substantially mediated by psychological responses. Negative illness perceptions and heightened fear, triggered by the unpredictability of IAH, drive maladaptive behaviors and emotional distress that contribute to worse cognitive outcomes.

Conclusion: The findings highlighted the role of psychological factors in cognitive decline among T2DM patients with IAH. We recommend that future interventions consider the associations between these variables. Diverse interventions aimed at improving IP and FOH levels could help slow cognitive decline in patients with IAH.

Type 2 diabetes mellitus is a chronic metabolic disorder associated with microvascular and macrovascular complications. Hyperglycemia and insulin resistance are core pathophysiological components of diabetes, linked to subclinical inflammation and persistent oxidative stress, which result in endothelial dysfunction and subsequent atherogenesis. Nowadays, several arrows in the diabetologist's quiver are available for the management of diabetes, providing flexibility and the ability to adopt a personalized approach tailored to each patient's needs. Two of the most commonly prescribed antidiabetic drugs are sodium-glucose cotransporter 2 inhibitors and glucagon- like peptide-1 receptor agonists. Both agents are associated with beneficial metabolic, cardioand nephro-protective effects independent of their antidiabetic properties; thus, their indications have and are continuously expanding over and beyond the treatment of diabetes. Given that these two drug classes have different mechanisms of action, the use of their combination achieves a synergistic interaction and confers additional benefits. The aim of this review is to provide a summary of current knowledge regarding the use of these two drug classes, shed light on the available evidence on their combination, and discuss future perspectives on optimal therapeutic decisions in clinical practice. Sodium-glucose cotransporter 2 inhibitors and glucagon-like peptide-1 receptor agonists in combination therapy are a promising therapeutic duo and are expected to influence future guidelines and decision-making in everyday clinical practice.

Type 2 diabetes mellitus (T2DM) is the most prevalent metabolic disease worldwide, characterized by hyperglycemia and insulin resistance (IR). Its escalating global prevalence and the associated morbidity and mortality render it a major public health concern. Conventional glucose- lowering therapies frequently entail adverse effects, hypoglycaemia risk, and fail to arrest disease progression. Emerging evidence positions the gut microbiota as a central regulator of glucose homeostasis and insulin sensitivity, suggesting that gut microbiota might be a promising target for T2DM. This review synthesizes current knowledge of microbiota-driven mechanisms, particularly those of the gut microbiota and their metabolites, that precipitate or exacerbate T2DM. It then critically evaluates microbiota-targeted interventions (dietary modulation, probiotics, prebiotics, antibiotic therapy, and fecal microbiota transplantation) as emerging therapeutic or adjunctive strategies to restore glycaemic control by modulating the gut microbial ecosystem. While clinical validation is incomplete, targeting the gut microbiota represents a promising avenue for both prevention and treatment of T2DM.

Insulin, secreted by pancreatic β-cells, regulates blood glucose levels. Insulin resistance (IR), characterized by diminished cellular responsiveness, increases insulin demand, imposing stress on β-cells. This leads to β-cell decompensation, which contributes to the development of type 2 diabetes (T2D). A growing body of evidence connects early-life exposures, such as low birth weight (LBW), to a heightened risk of developing non-communicable diseases (NCDs) such as T2D in adulthood. This comprehensive review synthesizes findings from 15 observational studies identified through a PubMed search to explore the specific biological mechanisms that link LBW to IR and T2D. The paper critically examines several prominent hypotheses, theories, and models that propose how endogenous responses to intrauterine conditions initiate a programming that can lead to lasting structural and functional changes in key metabolic organs. In individuals with fetal programming, the combination of impaired insulin sensitivity and compensatory insulin action is considered a precursor to impaired glucose tolerance and T2D, particularly in those who underwent rapid catch-up growth during childhood. Regular monitoring of LBW individuals can enable early intervention, such as lifestyle changes, to reduce the risk of IR and T2D. However, improving the early environment by providing care for women of reproductive age, especially during pregnancy, is a cost-effective strategy to address LBW and curb the NCD pandemic.

Background: Gestational diabetes mellitus (GDM) affects almost 10%-12% of pregnancies worldwide, threatening maternal and fetal life. Continuous glucose monitoring (CGM) forms the backbone of managing GDM, and the current methodologies largely disregard physiological and behavioral factors, thereby greatly reducing accuracy and clinical interpretability.

Methods: A hybrid deep learning framework was developed by fusing CGM with multi-sensing modality data, including heart rate, activity levels, sleep patterns, and dietary intake. For data preprocessing, Kalman filtering was applied for temporal alignment, adaptive normalization provided outlier handling and imputation, while the CNN-BiLSTM backbone with attention was harnessed for feature extraction. A Multi-Task Attention Fusion Network (MTAFN) was used to predict glucose values and classify GDM risk simultaneously, while SHAP and dynamic smoothing contributed to interpretability sets.

Results: The framework was validated on an extended OhioT1DM dataset with adaptations for pregnancy. It reached a glucose prediction RMSE of 9.8 mg/dL and a GDM risk classification accuracy of 93%. Compared to competitive approaches, the present solution attained a 25% better accuracy on interpretability and an improvement in sensitivity and specificity of about 4-6% across various physiological conditions.

Discussion: The use of multi-sensing data increased prediction robustness by capturing complex physiological dependencies. The SHAP-based interpretability justified the predictions through a physiological lens. With an attention mechanism for feature weighting, it was possible to identify crucial variables like meal intake and nighttime variability in the workflow sets.

Conclusion: The hybrid framework proposed here is reliable for clinically interpretable continuous glucose monitoring and GDM risk predictions. Its application with high reliability can lead to integrating it within clinical protocols for real-time maternal care sets.