Diabetes & vascular disease research最新文献

ObjectiveSodium-glucose cotransporter 2 (SGLT2) inhibitors have been studied for their effects on cardiovascular disease, cognitive impairment, dementia, Parkinson's disease, and cerebrovascular disease, with evidence suggesting a reduced risk of mortality. This study aimed to examine the association between SGLT2 inhibitors and cerebrovascular event recurrence.MethodsThe cohort was extracted from the Korean National Health Insurance Service Database, including individuals aged 19 or older diagnosed with type 2 diabetes. SGLT2 inhibitor users were compared with metformin users using 1:4 propensity score matching.ResultsAmong study subjects, 1563 (7.8%) experienced recurrent cerebrovascular events. SGLT2 inhibitor users showed lower recurrence of cerebral infarction compared to metformin users (adjusted hazard ratio=0.84, p=0.010). Among the types of cerebrovascular diseases, ischemic stroke was associated with a significantly lower risk of recurrence in SGLT2 inhibitor users than metformin users (aHR=0.70, p=0.020). In the SGLT2 inhibitor group, concurrent use of DPP4 inhibitors was associated with a reduced risk of cerebrovascular event recurrence (aHR=0.69, p=0.011).ConclusionSGLT2 inhibitor use was associated with a significantly lower risk of recurrent cerebral infarction compared to metformin, suggesting a potential role in the secondary prevention of cerebrovascular events in patients with type 2 diabetes.

IntroductionPreviously, we observed that subgroups of type 2 diabetes (T2D) - mild obesity-related diabetes (MOD), mild age-related diabetes (MARD), severe insulin-resistant diabetes (SIRD) - had distinct characteristics and complications. This study aims to investigate if movement behaviour also differs by T2D subgroup. Given that physical activity (PA) reduces the risk of complications, identifying less active subgroups could inform more targeted interventions.MethodsUsing age at T2D onset, body mass index, hbA1c, homeostasis model assessment 2 estimates of beta-cell function and insulin resistance, 706 study participants were classified into T2D subgroups. Using time spent in light PA, moderate-vigorous PA, day inactivity and night sleep per 24-hour, the participants were classified into three profiles. Regression models were used to examine the association between T2D subgroup (exposure) and movement behaviour (outcome).ResultsCompared to MOD, the relative risk ratio (RRR) of having the least active profile was 0.69 (95%CI 0.43-1.10), while the RRR of having the most active profile was 1.53 (95%CI 0.82-2.83) for MARD. The RRRs of having the least and most active profile was 1.32 (95%CI 0.85-2.04) and 1.44 (95%CI 0.76-2.72) respectively for SIRD.ConclusionUnderstanding the relationship between T2D subgroups and movement behaviour is a step towards advocating for PA intervention tailored to each subgroup's unique characteristics.

BackgroundCoronary heart disease (CHD) is a prevalent complication associated with type 2 diabetes mellitus (T2DM), and the incidence of T2DM with CHD has seen a steady rise over the preceding years.ObjectiveTo investigate the altered expression of LINC00893 and miR-103a-3p in T2DM and T2DM with CHD, as well as to assess their clinical significance in T2DM-CHD.MethodsThe LINC00893 and miR-103a-3p expression was detected by RT-qPCR. ROC curves were used to analyze the diagnostic significance of LINC00893 and miR-103a-3p in T2DM patients with CHD. The Kaplan-Meier curve was used to analyze the prognostic significance of LINC00893 in the occurrence of Major Adverse Cardiovascular Events (MACEs) of T2DM with CHD patients. Dual-luciferase reporter assay was used to confirm the regulatory relationship between LINC00893 and miR-103a-3p.ResultLINC00893 and miR-103a-3p were down-regulated and up-regulated in T2DM with CHD patients, respectively and had diagnostic value in T2DM with CHD patients. In addition, patients with low levels of LINC00893 are more likely to develop MACE, and LINC00893 could regulate the expression of miR-103a-3p.ConclusionLINC00893 may affect disease progression in T2DM patients with CHD by regulating miR-103a-3p.

BackgroundHypoglycemia in type 2 diabetes patients is associated with metabolic abnormalities and inflammation that affect vascular beds. The relationship between hypoglycemia and panvascular disease (PVD) is not clear. This study aimed to investigate the association between PVD and hypoglycemia, and to identify potential mediators.MethodThis retrospective cross-sectional study enrolled Patients from two centers in Chongqing China, and the results were further validated using UK Biobank data. Logistic regression was used to test the association of hypoglycemia and PVD. Stratification and interaction analyses to test the effects across study subgroups. Forward (hypoglycemia to PVD) and reverse (PVD to hypoglycemia) relationships were analyzed by structural equation modeling (SEM), which included interleukin-6, neutrophil-to-lymphocyte ratio, uric acid, hemoglobin A1c, and systolic blood pressure.Results22,128 patients diagnosed with T2DM at two large centers and 44442 T2DM participants from the UK Biobank were enrolled. A significant association between hypoglycemia and PVD was found. Subgroup analysis found hypoglycemia was more strongly associated with PVD in patients with inflammatory abnormalities and metabolic dysfunction. SEM suggested a correlation structure between hypoglycemia and PVD which might mutually aggravated each other through inflammation and metabolism pathways.ConclusionThis is the first study that described the correlation structure between hypoglycemia and PVD with a large population. Within this potential mutual association, inflammation and metabolism might be mediators. Our study also highlights the insufficient attention clinicians pay to hypoglycemia and PVD, and further attention is needed in future clinical practice and research.

BackgroundThe evaluation of user satisfaction with an automated insulin delivery (AID) system is crucial. The aim was to assess the change in user satisfaction after upgrading from a previous to a next generation sensor integrated in the same AID system.MethodsA prospective intervention study was conducted. Type 1 diabetes subjects simultaneously upgraded from Guardian-Sensor®4 to Simplera-Sync^TM, integrated in the MiniMed^TM-780G system. User satisfaction was evaluated at baseline and after 3 months of use of Simplera-Sync^TM by the Glucose Monitoring Experience Questionnaire (GME-Q), a validated questionnaire designed to evaluate the experience with a glucose monitoring system. Glucose control and use of the system were also compared.ResultsNinety-one subjects were included (age: 38 ± 15 years-old, 59% female). GME-Q global score increased from 3.84 ± 0.49 to 4.40 ± 0.46. All subscales, effectiveness, convenience, and intrusiveness also improved. Sensor use increased from 93% [91, 95] to 98% [96, 99] and time in automode from 94% [92, 97] to 100% [97, 100], with 50% of the subjects achieving 100% of time in automode. A reduction in time in moderate hypoglycaemia and the number of hypoglycaemia episodes was observed.ConclusionUpgrading to a new sensor, as part of an AID system, can improve user satisfaction and allow for increased sensor use and time in automation.

BackgroundDepression and insulin resistance-measured by the estimated glucose disposal rate (eGDR)-are both linked to cardiovascular disease (CVD), but whether eGDR mediates this relationship remains unclear. We examined the mediating role of eGDR and its joint and interactive effects with depression on incident CVD.MethodsData were derived from the China Health and Retirement Longitudinal Study (2011-2020). Participants without baseline CVD and with complete eGDR and CESD-10 data were included. eGDR was calculated as 21.158 - (0.09 × waist circumference) - (3.407 × hypertension) - (0.551 × HbA1c). Depressive symptoms were defined as CESD-10 ≥ 12. Cox models adjusted for demographic and lifestyle factors assessed CVD risk across four groups defined by eGDR and depression status.ResultsDuring a median 9-years follow-up, 1643 CVD events occurred. Participants with low eGDR and depression had the highest CVD risk (HR = 1.87, 95% CI: 1.40-2.49, p < 0.001). Additive interaction analysis indicated biological synergy (relative excess risk = 1.37; attributable proportion = 0.32). eGDR mediated 9.82% of the depression-CVD association. Interactions were stronger in older adults.ConclusionLow eGDR and depressive symptoms synergistically elevate CVD risk, highlighting the importance of integrating metabolic and psychological assessments in CVD prevention.

BackgroundDiabetes-related foot ulcers (DFUs), often complicated by peripheral arterial disease (PAD), remain a major therapeutic challenge. In patients unsuitable for revascularization, alternative treatments are essential. This study is the first to evaluate bipolar radiofrequency (RF) ablation as part of lumbar sympathetic block (LSB) for enhancing wound healing in DFU patients with critical limb ischemia.MethodsThis retrospective cohort study included 31 DFU patients with severe PAD who were not candidates for revascularization. Group 1 (n = 18) received LSB with bipolar RF plus medical care; Group 2 (n = 13) received medical care alone. Wound healing, amputation rates, pain scores (NRS, DN4), and complications were analyzed.ResultsComplete wound healing was significantly higher in Group 1 (55.5%) than in Group 2 (15.3%) (p = 0.031). Amputation was required in 23.1% of Group 2 patients, while none occurred in Group 1 (p = 0.063). Group 1 showed significant reductions in DN4 (p = 0.0057) and NRS (p = 0.0013) at 6 months. No complications related to LSB were observed.ConclusionsLSB with bipolar RF ablation is a safe, potentially effective option for DFU patients with PAD not eligible for revascularization. It significantly improves wound healing and pain outcomes. Larger prospective studies are needed to confirm these results.

BackgroundAtherosclerosis (AS) and type 2 diabetes mellitus (T2DM) frequently coexist, jointly accelerating cardiovascular complications through shared inflammatory and metabolic pathways. Despite extensive research, the molecular mechanisms linking these chronic diseases remain incompletely defined.PurposeThis study aimed to delineate the shared transcriptional signatures and identify candidate biomarkers contributing to T2DM-associated AS progression using an integrative multi-omics strategy.Research DesignA retrospective bioinformatics investigation integrating differential expression analysis, co-expression network modeling, protein-interaction profiling, immune deconvolution, and machine-learning-based biomarker prioritization was conducted.Study Sample: Publicly available transcriptomic datasets were obtained from the NCBI Gene Expression Omnibus, including AS tissue samples (GSE100927), pancreatic islet samples from individuals with T2DM (GSE25724), and two independent datasets for external validation (GSE30169 and GSE26168).Data Collection and/or AnalysisDifferentially expressed genes (DEGs) were identified for AS (n = 3,368) and T2DM (n = 4,553). DEG intersection and Weighted Gene Co-expression Network Analysis (WGCNA) revealed 443 shared crosstalk genes. Enrichment analyses highlighted immune activation processes (e.g., leukocyte-mediated immunity, lysosomal pathways) and metabolic dysregulation (e.g., mitochondrial-mediated apoptosis, TGF-β signaling). A protein-protein interaction network was constructed, identifying high-degree hub genes such as HLA-DRB1, JAK3, and MFN1. Immune cell profiling using CIBERSORTx compared disease microenvironments, demonstrating increased M1 macrophages and helper T cells in AS, and elevated monocytes and B cells in T2DM (p < 0.05). A fine-tuned TabNet model ranked predictive biomarkers (e.g., BTK, ZAP70, CD4) showing strong diagnostic performance (AUC = 0.85 for AS; 0.79 for T2DM).ResultsThe integrative multi-omics workflow uncovered a robust set of immune-metabolic crosstalk genes shared between AS and T2DM. Hub-gene analysis and immune infiltration patterns demonstrated convergent dysregulation in lysosomal activity, mitochondrial integrity, and adaptive immune signaling. Machine-learning prioritization further identified a subset of biomarkers capable of discriminating disease states with high accuracy, strengthening their translational potential.ConclusionsThis study provides a comprehensive molecular framework linking T2DM and AS, revealing previously unrecognized lysosomal and mitochondrial pathways that may drive their synergistic pathology. The identified biomarkers and immune signatures offer promising avenues for early diagnosis and targeted therapeutic development in patients with comorbid T2DM and atherosclerosis.