Journal of Diabetes and Metabolic Disorders最新文献

Introduction: : Metformin, an oral hypoglycemic agent, is generally used as the first-line treatment in type 2 diabetes mellitus (T2DM) patients. The response to metformin varies between patients, and its mechanisms remain incompletely understood. Genetic variations in proteins involved in the pharmacodynamics and pharmacokinetics of metformin, like OCT1 transporter, are suspected to explain this difference. This study investigated the association of the response to metformin in T2DM patients with the presence of rs12208357 (R61C) variant in the SLC22A1 gene.

Materials and methods: We selected 100 patients who responded and 100 patients who did not respond to metformin monotherapy after 20 weeks according to their HbA1c level change. We investigated the effect of rs12208357 on the structure, function, and stability of OCT1 protein and its interaction with metformin by in silico tools. To determine the genotype of rs12208357 we used the ARMS-PCR technique.

Results: The in silico study indicated that rs12208357 probably changes OCT1 stability, function, interaction site, and binding energy to metformin in the extracellular domain. ARMS-PCR also showed the frequency of T and C alleles were significantly different between responders and non-responders (P-value = 0.014), also there is a significant difference in CC and CT/TT genotype frequency between responders and non-responders (P-value = 0.023).

Conclusion: Based on the in silico study and ARMS-PCR experiment results, the CC genotype has a better response to metformin therapy and the carrier of the T allele (CT and TT genotype) probably has complications in glycemic control by metformin.

Objectives: The burgeoning prevalence of cardiometabolic disorders, including type 2 diabetes mellitus (T2DM) and metabolic syndrome (MetS) within Africa is concerning. Machine learning (ML) techniques offer a unique opportunity to leverage data-driven insights and construct predictive models for MetS risk, thereby enhancing the implementation of personalised prevention strategies. In this work, we employed ML techniques to develop predictive models for pre-MetS and MetS among diabetic patients.

Methods: This multi-centre cross-sectional study comprised of 919 T2DM patients. Age, gender, novel anthropometric indices along with biochemical measures were analysed using BORUTA feature selection and an ensemble majority voting classification model, which included logistic regression, k-nearest neighbour, Gaussian Naive Bayes, Gradient boosting classification, and support vector machine.

Results: Distinct metabolic profiles and phenotype clusters were associated with MetS progression. The BORUTA algorithm identified 10 and 16 significant features for pre-MetS and MetS prediction, respectively. For pre-MetS, the top-ranked features were lipid accumulation product (LAP), triglyceride-glucose index adjusted for waist-to-height ratio (TyG-WHtR), coronary risk (CR), visceral adiposity index (VAI) and abdominal volume index (AVI). For MetS prediction, the most influential features were VAI, LAP, waist triglyceride index (WTI), Very low-density cholesterol (VLDLC) and TyG-WHtR. Majority voting ensemble classifier demonstrated superior performance in predicting pre-MetS (AUC = 0.79) and MetS (AUC = 0.87).

Conclusion: Identifying these risk factors reveals the complex interplay between visceral adiposity and metabolic dysregulation in African populations, enabling early detection and treatment. Ethical integration of ML algorithms in clinical decision-making can streamline identification of high-risk individuals, optimize resource allocation, and enable precise, tailored interventions.

Supplementary information: The online version contains supplementary material available at 10.1007/s40200-024-01491-7.

Objectives: To assess the burden of chronic Non-communicable diseases (NCDs) such as diabetes and hypertension, and evaluate the utilization of drugs for their treatment among the population of Andhra Pradesh, India.

Methods: A cross-sectional study was conducted to analyse the prevalence of diabetes and hypertension, as well as the pattern of drug usage for their management. Data were collected through surveys and medical records review.

Results: The study revealed a high prevalence of diabetes and hypertension in Andhra Pradesh, with significant proportions of the population remaining untreated despite critical drug utilization. Commonly used antidiabetic drugs included metformin, glipizide, and insulin, while telmisartan, furosemide, and metoprolol were frequently utilized for hypertension treatment. Side effects associated with these drugs were reported, emphasizing the need for better public awareness campaigns, improved access to healthcare, and effective management of side effects.

Conclusions: The findings underscore the importance of early detection and preventive measures for hypertension and diabetes. There is a pressing need for tailored interventions addressing social and economic factors contributing to non-adherence to treatment regimens. While the widespread use of medications indicates significant awareness and proactive healthcare among a substantial portion of the population, the presence of individuals not adhering to their treatment suggests significant gaps in awareness and access to healthcare services. This study provides crucial insights into medication patterns for managing diabetes and hypertension in Andhra Pradesh, laying the groundwork for targeted public health interventions.

Objective: To investigate the relationship between glycosylated Hemoglobin (HbA1c) levels and bone mineral density (BMD) in individuals with varying glycemic statuses, including diabetes, prediabetes, and controls.

Methods: This cross-sectional study conducted in Bengaluru, India, included 336 participants aged 20 to 60. Blood samples were taken to assess fasting blood glucose, HbA1c, and lipid profile. Participants were divided into tertiles based on HbA1c levels: low(HbA1c ≤ 5.5%), moderate(HbA1c > 5.5-6.0%), and high(HbA1c ≥ 6.1%).Dual energy-X-ray absorptiometry(DXA) measured hip, spine, and total BMD as indicators of bone health.

Results: Intermediate and high HbA1c tertiles had a significantly higher hip and total BMD compared to low HbA1c tertiles (p < 0.001 and p = 0.006 for hip and total BMD). Spine BMD was comparable between the three groups. After adjusting for age, gender and BMI, a potential independent effect of glycemic control on hip BMD was observed (Low vs. intermediate and high glycemic status: β: 0.041, 95% C.I.: 0.003, 0.078, p = 0.034).

Conclusion: Elevated HbA1c might be associated with higher hip and overall BMD as observed through DXA. Nonetheless, this doesn't necessarily imply better bone health; further evaluation is advised to prevent fractures.

Supplementary information: The online version contains supplementary material available at 10.1007/s40200-024-01473-9.

Diabetes mellitus, a metabolic syndrome characterized by hyperglycemia and insulin dysfunction, often leads to serious complications such as neuropathy, nephropathy, retinopathy, and cardiovascular disease. Incretins, gut peptide hormones released post-nutrient intake, have shown promising therapeutic effects on these complications due to their wide-ranging biological impacts on various body systems. This review focuses on the role of incretin-based therapies, particularly Glucagon-like peptide-1 (GLP-1) agonists and dipeptidyl peptidase-4 (DPP-4) inhibitors, in managing diabetes and its complications. We also discuss the potential of novel agents like semaglutide, a recently approved oral compound, and dual/triple agonists targeting GLP-1/GIP, GLP-1/glucagon, and GLP-1/GIP/glucagon receptors, which are currently under investigation. The review aims to provide a comprehensive understanding of the beneficial impacts of natural incretins and the therapeutic potential of incretin-based therapies in diabetes management.

Objectives: Despite their documented significance in type 2 diabetes (T2DM) management, social determinants of health (SDOHs) including material needs security and mental health outcomes are understudied in the Middle East and North Africa (MENA) region. This study aims to assess the relation between material needs security and mental health outcomes in Lebanese adults with T2DM.

Methods: Subjects with T2DM (N = 300) were recruited from primary health care centers in Lebanon. Sociodemographic, material need variables, depression measured by Patient Health Questionnaire (PHQ-9), and diabetes fatalism measured by Diabetes Fatalism Scale (DFS) were collected.

Results: Most of the participants were men, married and with lower educational levels. Multivariate analyses revealed that having material needs security was associated with diabetes fatalism (β = -0.63(-1.13; -0.12)), and depression (β = -0.46(-0.78; -0.13)). Also, higher age (β = 3.49(0.91; 6.06)) and education (β = 3.42(1.18; 5.66)), and lower income (β = 3.25(0.62; 5.88)) were independently associated with diabetes fatalism. Being male was the only independent variable associated with less depression (β = -1.56(-2.97; -0.14)).

Conclusion: Our study highlights the importance of material needs security on mental health outcomes for adults with T2DM in the MENA region. Clinicians are encouraged to assess the impact of material needs on mental health outcomes. Further research is needed to understand potential pathways/mechanisms and options for effective interventions and policymaking.

Patients with diabetes often experience reduced bone strength, resulting in a higher fracture risk. This decline and increased susceptibility stem from intricate interactions within the bone microstructure. However, current gold standard methods for assessing bone strength, such as bone mineral density, and widely-used fracture risk assessment tools do not accurately predict fracture risk in diabetic patients. Therefore, it is crucial to incorporate additional indicators that evaluate bone quality and specific markers relevant to diabetes to enhance the accuracy of predictive models. Moreover, the selection of appropriate algorithms for model construction is essential. This review aims to introduce indicators from both imaging examinations and laboratory indicators that hold significant value for inclusion in fracture risk prediction models for diabetic patients. Additionally, this study provides an overview of the research progress in fracture risk prediction models for diabetic patients, serving as a valuable reference for clinical practice.

Background: Diabetes is becoming a worldwide concern. Optimal diabetes control reduces diabetes complications.

Objectives: We aimed to measure the principal diabetes care parameters to recognize the main deficits in care for patients with diabetes in the region.

Methods: This cross-sectional study is based on the Khuzestan Comprehensive Health Study (KCHS) data. Of all participants, 4673 (15.3%) were identified to have diabetes. We invited the known cases of diabetes to complete a checklist about their diabetes through face-to-face interviews, and we obtained a blood sample to measure their HbA1c.

Results: Of all participants of the KCHS study, 312 patients with diabetes who met the inclusion criteria were identified. Mean (± SD) HbA1c was 8.5% (± 1.8), and 225 (72.1%) of the participants had poor glycemic control. About 45.2% had blood pressure less than 130/80 mmHg, and 24% had FBS lower than 130 mg/dl. Nearly 37.8% of the participants had LDL < 100 mg/dl and 40% TG < 150 mg/dl. Of all participants, 38.5% had undergone retinal examination, 13.8% had their foot examined, and 39.4% had done urine micro-albumin /Cr test. HbA1c level had a statistically significant relationship with gender (P = 0.012), occupation (P = 0.007), nephropathy (P = 0.004) and retinopathy (P < 0.001).

Conclusions: This study showed that less than half of the participants achieved the optimal ADA goals for diabetes care, therefore it is necessary to revise the basic protocols of diabetes care in the region to improve diabetes management.

Objectives: Recent studies have confirmed the involvement of mannose-binding lectin (MBL) in the pathogenesis of vascular complications in individuals with diabetes. Due to the discrepancy between the results of studies, a meta-analysis was conducted to evaluate MBL levels in patients with diabetes and its vascular complications.

Methods: We reviewed all observational studies published in PubMed/Medline, Scopus, EMBASE, and Web of Science Core Collection databases to identify relevant studies up to 1 April 2024. To account for describing heterogeneity among the studies, I² and χ² statistics were utilized. Also, a random-effects model was employed to combine the studies. The Newcastle Ottawa Scale (NOS) checklist was applied for quality assessment of each study.

Results: Twenty-eight papers were encompassed in this meta-analysis. The mean difference in MBL levels between patients with diabetic nephropathy and diabetic retinopathy differed significantly compared with the healthy control group and the diabetic group without vascular complications (P-value < 0.05). Moreover, the pooled results revealed a significant relationship between MBL levels and the incidence of vascular complications (pooled HR = 1.44, 95% CI: 1.07-1.95, P-value < 0.05) and disease-related mortality (pooled HR = 1.52, 95% CI: 1.07-2.16, P-value < 0.05) among diabetic patients. Also, there was a direct association between incidence of nephropathy in diabetics and higher levels of MBL (pooled HR = 2.16, 95% CI: 1.52-3.08, P-value < 0.05).

Conclusion: Diabetic patients with elevated MBL levels are potentially at increased risk of vascular complications such as nephropathy and retinopathy. Therefore, by determining MBL status in diabetic patients, it is possible to predict the progress and possible consequences of the disease.

Introduction: Heterozygous mutations in the GCK gene result in mildly elevated glucose levels from birth, and the homozygous loss-of-function mutations leads to permanent neonatal diabetes. In the present study we aim to investigate the cause of diabetes in an adult female patient with unusual course of diabetes.

Case presentation: We evaluate a female patient who previously encountered significant hyperglycemia during the infancy and subsequently experienced a relatively uneventful childhood. In later years, she faced significant hyperglycemia and retinopathy that required laser photocoagulation. Her treatment history included periods of oral hypoglycemic agents or insulin, which occasionally led to hypoglycemia, as well as extended intervals without treatment. However, she never required hospitalization for diabetic ketoacidosis. The patient's family history was significant, with her parents being cousins and having a history of prediabetes and gestational diabetes in several family members. Autoantibody tests for type 1 diabetes were negative. Next-generation sequencing analysis of the coding regions and conserved splice sites of several genes identified a homozygous GCK (T/T) missense (His424Tyr) variant, which was validated by Sanger sequencing. Heterozygous C/T mutations were revealed in the parents.

Discussion and conclusion: This case highlights the importance of considering homozygous GCK mutations as a potential cause of persistent neonatal diabetes, especially in patients with a history of elevated glucose levels from infancy, a family history of early-onset non-progressive diabetes and gestational diabetes, and parental consanguinity. Genetic testing can help identify the underlying genetic etiology in such cases. Early diagnosis is crucial to guide appropriate treatment and management strategies.