18 resultados para Typ 2-diabetes
Resumo:
Abstract Background To identify the most appropriate cut-off points of fasting glycemia for the screening of diabetes mellitus type 2 (DM2) with the comparison of the properties of capillary glycemia (CG) and venous blood plasma glycemia (PG) in a population of Japanese origin from the community of Mombuca, Guatapará - SP, Brazil. Methods This was a population-based descriptive cross-sectional study conducted on a sample of 131 individuals of both genders aged 20 years or more (66.8% of the target population). CG was measured with a glucometer in a blood sample obtained from the fingertip and PG was determined by an enzymatic method (hexokinase) in venous blood plasma, after a 10-14 hour fast in both cases. Data were analyzed by the receiver operating characteristic (ROC) curve in order to identify the best cut-off point for fasting glycemia (CG and PG) for the diagnosis of DM, using the 2-hour plasma glycemia > 200 mg/dl as gold - standard. Results The ROC curve revealed that the best cut-off point for the screening of DM was 110 mg/dl for CG and 105 mg/dl for PG, values that would optimize the relation between individuals with positive and false-positive results. The area under the ROC curve was 0.814 for CG (p < 0.01) and 0.836 for PG (p < 0.01). Conclusions The cut-off points of 105 mg/dl(5.8 mmol/l) for PG and of 110 mg/dl(6.1 mmol/l) for CG appear to be the most appropriate for the screening of DM2 in the population under study, with emphasis on the fact that the value recommended for CG is 5 mg/dl higher than that for PG, in contrast to WHO recommendations.
Resumo:
Objective: This study aims to explore the possible relationship between the expression level of S100 beta protein mRNA with diabetes mellitus type 2 in adipocytes from patients with this disease in comparison with normoglycemic individuals. Materials and methods: Samples of adipose tissue of eight patients from the coronary section of the Institute Dante Pazzanese of Cardiology (IDPC), four in Group Diabetes and four of Normoglycemic group, were evaluated by RT-PCR real time. Results: An increase around 15 times values, between the threshold cycle (Delta Ct), of mRNA expression of S100 beta protein in adipocytes of the diabetes group was observed in comparison to the control group (p = 0.015). Conclusion: Our results indicate, for the first time, that there is coexistence of increased expression of the S100 beta and the type 2 diabetes mellitus gene. Arq Bras Endocrinol Metab. 2012;56(7):435-40
Resumo:
Abstract Background Regardless the regulatory function of microRNAs (miRNA), their differential expression pattern has been used to define miRNA signatures and to disclose disease biomarkers. To address the question of whether patients presenting the different types of diabetes mellitus could be distinguished on the basis of their miRNA and mRNA expression profiling, we obtained peripheral blood mononuclear cell (PBMC) RNAs from 7 type 1 (T1D), 7 type 2 (T2D), and 6 gestational diabetes (GDM) patients, which were hybridized to Agilent miRNA and mRNA microarrays. Data quantification and quality control were obtained using the Feature Extraction software, and data distribution was normalized using quantile function implemented in the Aroma light package. Differentially expressed miRNAs/mRNAs were identified using Rank products, comparing T1DxGDM, T2DxGDM and T1DxT2D. Hierarchical clustering was performed using the average linkage criterion with Pearson uncentered distance as metrics. Results The use of the same microarrays platform permitted the identification of sets of shared or specific miRNAs/mRNA interaction for each type of diabetes. Nine miRNAs (hsa-miR-126, hsa-miR-1307, hsa-miR-142-3p, hsa-miR-142-5p, hsa-miR-144, hsa-miR-199a-5p, hsa-miR-27a, hsa-miR-29b, and hsa-miR-342-3p) were shared among T1D, T2D and GDM, and additional specific miRNAs were identified for T1D (20 miRNAs), T2D (14) and GDM (19) patients. ROC curves allowed the identification of specific and relevant (greater AUC values) miRNAs for each type of diabetes, including: i) hsa-miR-1274a, hsa-miR-1274b and hsa-let-7f for T1D; ii) hsa-miR-222, hsa-miR-30e and hsa-miR-140-3p for T2D, and iii) hsa-miR-181a and hsa-miR-1268 for GDM. Many of these miRNAs targeted mRNAs associated with diabetes pathogenesis. Conclusions These results indicate that PBMC can be used as reporter cells to characterize the miRNA expression profiling disclosed by the different diabetes mellitus manifestations. Shared miRNAs may characterize diabetes as a metabolic and inflammatory disorder, whereas specific miRNAs may represent biological markers for each type of diabetes, deserving further attention.