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ABSTRACT Objective: To identify DNA methylation and gene expression profiles involved in obesity by implementing an integrated bioinformatics approach. Materials and methods: Gene expression (GSE94752, GSE55200, and GSE48964) and DNA methylation (GSE67024 and GSE111632) datasets were obtained from the GEO database. Differentially expressed genes (DEGs) and differentially methylated genes (DMGs) in subcutaneous adipose tissue of patients with obesity were identified using GEO2R. Methylation-regulated DEGs (MeDEGs) were identified by overlapping DEGs and DMGs. The protein-protein interaction (PPI) network was constructed with the STRING database and analyzed using Cytoscape. Functional modules and hub-bottleneck genes were identified by using MCODE and CytoHubba plugins. Functional enrichment analyses were performed based on Gene Ontology terms and KEGG pathways. To prioritize and identify candidate genes for obesity, MeDEGs were compared with obesity-related genes available at the DisGeNET database. Results: A total of 54 MeDEGs were identified after overlapping the lists of significant 274 DEGs and 11,556 DMGs. Of these, 25 were hypermethylated-low expression genes and 29 were hypomethylated-high expression genes. The PPI network showed three hub-bottleneck genes (PTGS2, TNFAIP3, and FBXL20) and one functional module. The 54 MeDEGs were mainly involved in the regulation of fibroblast growth factor production, the molecular function of arachidonic acid, and ubiquitin-protein transferase activity. Data collected from DisGeNET showed that 11 of the 54 MeDEGs were involved in obesity. Conclusion: This study identifies new MeDEGs involved in obesity and assessed their related pathways and functions. These results data may provide a deeper understanding of methylation-mediated regulatory mechanisms of obesity.
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ABSTRACT Objective: The objective of this study was to investigate the association between SNPs in the TIE2 and ANGPT-1 genes and diabetic retinopathy (DR). Subjects and methods: This study comprised 603 patients with type 2 diabetes mellitus (T2DM) and DR (cases) and 388 patients with T2DM for more than 10 years and without DR (controls). The TIE2 rs639225 (A/G) and rs638203 (A/G) SNPs and the ANGPT-1 rs4324901 (G/T) and rs2507800 (T/A) SNPs were genotyped by real-time PCR using TaqMan MGB probes. Results: The G/G genotype of the rs639225/TIE2, the G/G genotype of the rs638203/TIE2 and the T allele of the rs4324901/ANGPT-1 SNPs were associated with protection against DR after adjustment for age, glycated hemoglobin, gender, and presence of hypertension (P = 0.042, P = 0.003, and P = 0.028, respectively). No association was found between the rs2507800/ANGPT-1 SNP and DR. Conclusion: We demonstrated, for the first time, the association of TIE2 rs638203 and rsrs939225 SNPs and ANGPT-1 rs4324901 SNP with protection against DR in a Brazilian population.
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ABSTRACT Objective: The AKR1B1 gene encodes an enzyme that catalyzes the reduction of glucose into sorbitol. Chronic hyperglycemia in patients with diabetes mellitus (DM) leads to increased AKR1B1 affinity for glucose and, consequently, sorbitol accumulation. Elevated sorbitol increases oxidative stress, which is one of the main pathways related to chronic complications of diabetes, including diabetic kidney disease (DKD). Accordingly, some studies have suggested the rs759853 polymorphism in the AKR1B1 gene is associated with DKD; however, findings are still contradictory. The aim was to investigate the association of the rs759853 polymorphism in the AKR1B1 gene and DKD. Materials and methods: The sample comprised 695 patients with type 2 DM (T2DM) and DKD (cases) and 310 patients with T2DM of more than 10 years' duration, but no DKD (controls). The polymorphism was genotyped by real-time PCR. Results: Allelic and genotype frequencies of this polymorphism did not differ significantly between groups. However, the A/A genotype was associated with risk for DKD after adjustment for gender, triglycerides, BMI, presence of hypertension and diabetic retinopathy, and duration of DM, under both recessive (P = 0.048) and additive (P = 0.037) inheritance models. Conclusion: Our data suggest an association between the AKR1B1 rs759853A/A genotype and risk for DKD in Brazilians T2DM patients.