Dataset Information

Evaluating the antidiabetic effects of R-verapamil in type 1 and type 2 diabetes mellitus mouse models.

ABSTRACT: The global incidence of diabetes mellitus (DM) is increasing. Types 1 and 2 DM are associated with declining β-cell function. Verapamil (50% S-verapamil and 50% R-verapamil) can treat DM by downregulating thioredoxin-interacting protein (TXNIP), which induces islet β-cell apoptosis. However, it may also induce cardiovascular side effects as S-verapamil is negatively inotropic. In contrast, R-verapamil only weakly induces adverse cardiac effects. In this study, we aimed to determine the antidiabetic efficacy and cardiovascular safety of R-verapamil. We examined R- and S-verapamil binding through in vitro studies. Streptozotocin-induced type 1 and db/db type 2 DM mouse models were used to assess the antidiabetic efficacy of verapamil. IL-6, blood glucose (BG), Txnip expression, and β-cells were evaluated in streptozotocin-induced diabetic mice, while body weight, BG, and serum insulin were measured in the db/db mice. In the type 1 DM study, 100 mg/kg/day R-verapamil and racemic verapamil lowered BG, downregulated Txnip expression, and reduced β-cell apoptosis. In the type 2 DM study, the optimal R-verapamil dosage was 60 mg/kg/day and it lowered BG and raised serum insulin. However, efficacy did not increase with R-verapamil dosage. R-verapamil combined with metformin/acarbose improved BG and serum insulin more effectively than metformin/acarbose alone or verapamil combined with acarbose. R-verapamil had weaker cardiovascular side effects than S-verapamil. R-verapamil was 9.0× and 3.4× less effective than S-verapamil at inhibiting atrial inotropy and ileal contractility, respectively. It was also 8.7× weaker than S-verapamil as an agonist of somatostatin receptor type 2 (SSTR2), inhibiting ileal neurogenic contraction. Hence, R-verapamil may be an optimal DM treatment as it is safe, improves glycemic control, and preserves β-cell function both as monotherapy and in combination with metformin or acarbose. R-Verapamil has potential for delaying or arresting DM progression and improving patients' quality of life.

SUBMITTER: Chen YS

PROVIDER: S-EPMC8345870 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundThe changes of endothelial function in type 2 diabetes mellitus (T2DM) patients are closely associated with the development of cardiovascular disease (CVD). However, it is still unclear whether commonly used antidiabetic drugs can improve endothelial function. Flow-mediated dilation (FMD) is a noninvasive tool for evaluating endothelial function, which typically examines changes in the brachial artery diameter in response to ischemia using ultrasound. We performed a network meta-analysis (NMA) to explore the associations between changes in endothelial function and antidiabetic drugs by evaluating FMD in T2DM patients.MethodsWe systematically searched several electronic databases for randomized controlled trials (RCTs) published from inception until January 25, 2022 with no language restriction. The primary outcome was FMD change in all studies, and we performed subgroup analysis in T2DM patients without CVD. NMA was performed to calculate the mean differences (MDs) with 95% confidence intervals (CIs).ResultsFrom the 1,987 candidate articles identified in the initial search, 30 RCTs were eventually included in the analysis. In all studies, glucagon-like peptide-1 receptor (GLP-1R) agonists [MD = 3.70 (1.39-5.97)], TZD [MD = 1.96 (0.006-3.89)] produced improvement of FMD change compared to lifestyle intervention. GLP-1R agonists [MD = 3.33 (1.36-5.34) and MD = 3.30 (1.21-5.43)] showed significantly greater improvements in FMD change in pairwise comparisons with sulfonylureas and placebo. SGLT-2i also showed efficacy compared to sulfonylureas (MD = 1.89, 95% CI, 0.10, 3.75). In studies of T2DM patients without CVD, GLP-1R agonists [MD = 3.53 (1.24-5.76)], and TZD [MD = 2.30 (0.27-3.24)] produced improvements in FMD change compared to lifestyle treatment. GLP-1R agonists [MD = 3.25 (1.13-5.40), and MD = 3.85 (1.68-6.13)] showed significantly greater improvements in pairwise comparisons with sulfonylureas, and placebo.ConclusionIn T2DM patients, both GLP-1R agonists, SGLT-2i and TZD have favorable effects to improve endothelial function in T2DM patients. In T2DM patients without CVD, GLP-1R agonists had a greater effect to improve endothelial function than sulfonylureas. These suggested that GLP-1R agonists are associated with significantly improved endothelial function in T2DM patients.

Project description:AimsTo reduce the burden of type 2 diabetes (T2DM), the disease decision model plays a vital role in supporting decision-making. Currently, there is no comprehensive summary and assessment of the existing decision models for T2DM. The objective of this review is to provide an overview of the characteristics and capabilities of published decision models for T2DM. We also discuss which models are suitable for different study demands.Materials and methodsFour databases (PubMed, Web of Science, Embase, and the Cochrane Library) were electronically searched for papers published from inception to August 2020. Search terms were: "Diabetes-Mellitus, Type 2", "cost-utility", "quality-of-life", and "decision model". Reference lists of the included studies were manually searched. Two reviewers independently screened the titles and abstracts following the inclusion and exclusion criteria. If there was insufficient information to include or exclude a study, then a full-text version was sought. The extracted information included basic information, study details, population characteristics, basic modeling methodologies, model structure, and data inputs for the included applications, model outcomes, model validation, and uncertainty.ResultsFourteen unique decision models for T2DM were identified. Markov chains and risk equations were utilized by four and three models, respectively. Three models utilized both. Except for the Archimedes model, all other models (n = 13) implemented an annual cycle length. The time horizon of most models was flexible. Fourteen models had differences in the division of health states. Ten models emphasized macrovascular and microvascular complications. Six models included adverse events. Majority of the models (n = 11) were patient-level simulation models. Eleven models simulated annual changes in risk factors (body mass index, glycemia, HbA1c, blood pressure (systolic and/or diastolic), and lipids (total cholesterol and/or high-density lipoprotein)). All models reported the main data sources used to develop health states of complications. Most models (n = 11) could deal with the uncertainty of models, which were described in varying levels of detail in the primary studies. Eleven studies reported that one or more validation checks were performed.ConclusionsThe existing decision models for T2DM are heterogeneous in terms of the level of detail in the classification of health states. Thus, more attention should be focused on balancing the desired level of complexity against the required level of transparency in the development of T2DM decision models.

Project description:BackgroundObservational studies and conventional Mendelian randomization (MR) studies showed inconclusive evidence to support the association between omega-3 fatty acids and type 2 diabetes. We aim to evaluate the causal effect of omega-3 fatty acids on type 2 diabetes mellitus (T2DM), and the distinct intermediate phenotypes linking the two.MethodsTwo-sample MR was performed using genetic instruments derived from a recent genome-wide association study (GWAS) of omega-3 fatty acids (N = 114,999) from UK Biobank and outcome data obtained from a large-scale T2DM GWAS (62,892 cases and 596,424 controls) in European ancestry. MR-Clust was applied to determine clustered genetic instruments of omega-3 fatty acids that influences T2DM. Two-step MR analysis was used to identify potential intermediate phenotypes (e.g. glycemic traits) that linking omega-3 fatty acids with T2DM.ResultsUnivariate MR showed heterogenous effect of omega-3 fatty acids on T2DM. At least two pleiotropic effects between omega-3 fatty acids and T2DM were identified using MR-Clust. For cluster 1 with seven instruments, increasing omega-3 fatty acids reduced T2DM risk (OR: 0.52, 95%CI 0.45-0.59), and decreased HOMA-IR (β = - 0.13, SE = 0.05, P = 0.02). On the contrary, MR analysis using 10 instruments in cluster 2 showed that increasing omega-3 fatty acids increased T2DM risk (OR:1.10; 95%CI 1.06-1.15), and decreased HOMA-B (β = - 0.04, SE = 0.01, P = 4.52 × 10-5). Two-step MR indicated that increasing omega-3 fatty acid levels decreased T2DM risk via decreasing HOMA-IR in cluster 1, while increased T2DM risk via decreasing HOMA-B in cluster 2.ConclusionsThis study provides evidence to support two distinct pleiotropic effects of omega-3 fatty acids on T2DM risk influenced by different gene clusters, which could be partially explained by distinct effects of omega-3 fatty acids on insulin resistance and beta cell dysfunction. The pleiotropic feature of omega-3 fatty acids variants and its complex relationships with T2DM need to be carefully considered in future genetic and clinical studies.

Dataset Information

Evaluating the antidiabetic effects of R-verapamil in type 1 and type 2 diabetes mellitus mouse models.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets