RESUMO
BACKGROUND: Type 2 diabetes mellitus (T2DM) is a metabolic disease of impaired glucose utilization. Uncontrolled high sugar levels lead to advanced glycation end products (AGEs), which affects several metabolic pathways by its receptor of advanced glycation end products (RAGE) and causes diabetic complication. MiRNAs are small RNA molecules which regulate genes linked to diabetes and affect AGEs pathogenesis, and target tissues, influencing health and disease processes. AIM: To explore miRNA roles in T2DM's metabolic pathways for potential therapeutic and diagnostic advancements in diabetes complications. METHODS: We systematically searched the electronic database PubMed using keywords. We included free, full-length research articles that evaluate the role of miRNAs in T2DM and its complications, focusing on genetic and molecular disease mechanisms. After assessing the full-length papers of the shortlisted articles, we included 12 research articles. RESULTS: Several types of miRNAs are linked in metabolic pathways which are affected by AGE/RAGE axis in T2DM and its complications. miR-96-5p, miR-7-5p, miR-132, has_circ_0071106, miR-143, miR-21, miR-145-5p, and more are associated with various aspects of T2DM, including disease risk, diagnostic markers, complications, and gene regulation. CONCLUSION: Targeting the AGE/RAGE axis, with a focus on miRNA regulation, holds promise for managing T2DM and its complications. MiRNAs have therapeutic potential as they can influence the metabolic pathways affected by AGEs and RAGE, potentially reducing inflammation, oxidative stress, and vascular complications. Additionally, miRNAs may serve as early diagnostic biomarkers for T2DM. Further research in this area may lead to innovative therapeutic strategies for diabetes and its associated complications.
RESUMO
BACKGROUND: It is increasingly common to find patients affected by a combination of type 2 diabetes mellitus (T2DM) and coronary artery disease (CAD), and studies are able to correlate their relationships with available biological and clinical evidence. The aim of the current study was to apply association rule mining (ARM) to discover whether there are consistent patterns of clinical features relevant to these diseases. ARM leverages clinical and laboratory data to the meaningful patterns for diabetic CAD by harnessing the power help of data-driven algorithms to optimise the decision-making in patient care. AIM: To reinforce the evidence of the T2DM-CAD interplay and demonstrate the ability of ARM to provide new insights into multivariate pattern discovery. METHODS: This cross-sectional study was conducted at the Department of Biochemistry in a specialized tertiary care centre in Delhi, involving a total of 300 consented subjects categorized into three groups: CAD with diabetes, CAD without diabetes, and healthy controls, with 100 subjects in each group. The participants were enrolled from the Cardiology IPD & OPD for the sample collection. The study employed ARM technique to extract the meaningful patterns and relationships from the clinical data with its original value. RESULTS: The clinical dataset comprised 35 attributes from enrolled subjects. The analysis produced rules with a maximum branching factor of 4 and a rule length of 5, necessitating a 1% probability increase for enhancement. Prominent patterns emerged, highlighting strong links between health indicators and diabetes likelihood, particularly elevated HbA1C and random blood sugar levels. The ARM technique identified individuals with a random blood sugar level > 175 and HbA1C > 6.6 are likely in the "CAD-with-diabetes" group, offering valuable insights into health indicators and influencing factors on disease outcomes. CONCLUSION: The application of this method holds promise for healthcare practitioners to offer valuable insights for enhancing patient treatment targeting specific subtypes of CAD with diabetes. Implying artificial intelligence techniques with medical data, we have shown the potential for personalized healthcare and the development of user-friendly applications aimed at improving cardiovascular health outcomes for this high-risk population to optimise the decision-making in patient care.
RESUMO
BACKGROUND: Type 2 diabetes mellitus (T2DM) is a metabolic disease of impaired glucose utilization. Imbalance in generation and elimination of free radicals generate oxidative stress which modulates glucose metabolism and insulin regulation, resulting in the occurrence and progression of diabetes and associated complications. Antioxidant supplements in T2DM can be seen as a potential preventive and effective therapeutic strategy. AIM: To compare randomized controlled trials (RCTs) in which antioxidants have been shown to have a therapeutic effect in T2DM patients. METHODS: We systematically searched the electronic database PubMed by keywords. RCTs evaluating the effect of antioxidant therapy on glycaemic control as well as oxidant and antioxidant status as primary outcomes were included. The outcomes considered were: A reduction in blood glucose; changes in oxidative stress and antioxidant markers. Full-length papers of the shortlisted articles were assessed for the eligibility criteria and 17 RCTs were included. RESULTS: The administration of fixed-dose antioxidants significantly reduces fasting blood sugar and glycated hemoglobin and is associated with decreased malondialdehyde, advanced oxidation protein products, and increased total antioxidant capacity. CONCLUSION: Antioxidant supplements can be a beneficial approach for the treatment of T2DM.
RESUMO
BACKGROUND: Coronary artery disease (CAD) is a major cause of death worldwide, and India contributes to about one-fifth of total CAD deaths. The development of CAD has been linked to the accumulation of Nε-carboxymethyl-lysine (CML) in heart muscle, which correlates with fibrosis. AIM: To assess the impact of CML and inflammatory markers on the biochemical and cardiovascular characteristics of CAD patients with and without diabetes. METHODS: We enrolled 200 consecutive CAD patients who were undergoing coronary angiography and categorized them into two groups based on their serum glycosylated hemoglobin (HbA1c) levels (group I: HbA1c ≥ 6.5; group II: HbA1c < 6.5). We analyzed the levels of lipoproteins, plasma HbA1c levels, CML, interleukin-6 (IL-6), tumor necrosis factor alpha (TNF-α), and nitric oxide. RESULTS: Group I (81 males and 19 females) patients had a mean age of 54.2 ± 10.2 years, with a mean diabetes duration of 4.9 ± 2.2 years. Group II (89 males and 11 females) patients had a mean age of 53.2 ± 10.3 years. Group I had more severe CAD, with a higher percentage of patients with single vessel disease and greater stenosis severity in the left anterior descending coronary artery compared to group II. Group I also exhibited a larger left atrium diameter. Group I patients exhibited significantly higher levels of CML, TNF-α, and IL-6 and lower levels of nitric oxide as compared with group II patients. Additionally, CML showed a significant positive correlation with IL-6 (r = 0.596, P = 0.001) and TNF-α (r = 0.337, P = 0.001) and a negative correlation with nitric oxide (r=-4.16, P = 0.001). Odds ratio analysis revealed that patients with CML in the third quartile (264.43-364.31 ng/mL) were significantly associated with diabetic CAD at unadjusted and adjusted levels with covariates. CONCLUSION: CML and inflammatory markers may play a significant role in the development of CAD, particularly in diabetic individuals, and may serve as potential biomarkers for the prediction of CAD in both diabetic and non-diabetic patients.
RESUMO
Objective: Type 2 Diabetes is a glucose metabolic disorder occurred by insulin insensitivity in which folate metabolism plays an important role. it is believed that polymorphism of Methylenetetrahydrofolate reductase (MTHFR) C677T linked with type 2 diabetes mellitus. However, results are conflicted. therefore, in this study we re-examine the relationship between MTHFR C677T in type 2 diabetes mellitus patients. Methods: Present research work included 100 newly diagnosed type 2 diabetic mellitus (T2DM) cases and 100 healthy individuals. After the blood sample collection all the biochemical parameters were evaluated among the T2DM cases and healthy individuals. DNA and RNA extraction from whole blood was done to study the MTHFR gene polymorphism by allele specific polymerase chain reaction method and its expression analysis was done by quantitative real time polymerase chain reaction method. Results: The significant difference was observed in genotype distribution among case and control group (p=0.0002). Compared with wildtype CC genotype, CT heterozygous (OR=2.95, 95% Cl=1.62-5.38) and TT homozygous (OR=3.20, CI=1.79-5.73) suggest to have effect of MTHFR polymorphism on type 2 mellitus risk. Moreover, relative MTHFR mRNA expression was found for wild type CC genotype 3.02-fold, CT heterozygous genotype 2.57 fold and mutant TT homozygous genotype 0.50-fold which is down regulated (p<0.0001). Conclusion: Our results indicates that the polymorphism in MTHFR C677T plays significant role in type II diabetes risk. MTHFR CT heterozygous and mutant TT genotype showed reduced mRNA expression among the T2DM patients. However, large scale case-control studies are needed to strengthen such conclusion in the future.