5 resultados para Cures pal·liatives
em CentAUR: Central Archive University of Reading - UK
Resumo:
BACKGROUND: The gene encoding for uncoupling protein-1 (UCP1) is considered to be a candidate gene for type 2 diabetes because of its role in thermogenesis and energy expenditure. The objective of the study was to examine whether genetic variations in the UCP1 gene are associated with type 2 diabetes and its related traits in Asian Indians. METHODS: The study subjects, 810 type 2 diabetic subjects and 990 normal glucose tolerant (NGT) subjects, were chosen from the Chennai Urban Rural Epidemiological Study (CURES), an ongoing population-based study in southern India. The polymorphisms were genotyped using the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. Linkage disequilibrium (LD) was estimated from the estimates of haplotypic frequencies. RESULTS: The three polymorphisms, namely -3826A-->G, an A-->C transition in the 5'-untranslated region (UTR) and Met229Leu, were not associated with type 2 diabetes. However, the frequency of the A-C-Met (-3826A-->G-5'UTR A-->C-Met229Leu) haplotype was significantly higher among the type 2 diabetic subjects (2.67%) compared with the NGT subjects (1.45%, P < 0.01). The odds ratio for type 2 diabetes for the individuals carrying the haplotype A-C-Met was 1.82 (95% confidence interval, 1.29-2.78, P = 0.009). CONCLUSIONS: The haplotype, A-C-Met, in the UCP1 gene is significantly associated with the increased genetic risk for developing type 2 diabetes in Asian Indians.
Resumo:
BACKGROUND: The aim of this study was to evaluate the association of polymorphisms of the peroxisome proliferator-activated receptor gamma (PPARG) gene and peroxisome proliferators-activated receptor gamma co-activator 1 alpha (PPARGC1A) gene with diabetic nephropathy (DN) in Asian Indians. METHODS: Six common polymorphisms, 3 of the PPARG gene [-1279G/A, Pro12Ala, and His478His (C/T)] and 3 of the PPARGC1A gene (Thr394Thr, Gly482Ser, and +A2962G) were studied in 571 normal glucose-tolerant (NGT) subjects, 255 type 2 diabetic (T2D) subjects without nephropathy, and 141 DN subjects. Genotypes were determined by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and direct sequencing. Logistic regression analysis was performed to assess the covariables associated with DN. RESULTS: Among the 6 polymorphisms examined, only the Gly482Ser of the PPARGC1A gene was significantly associated with DN. The genotype frequency of Ser/Ser genotype of the PPARGC1A gene was 8.8% (50/571) in NGT subjects, 7.8% (20/255) in T2D subjects, and 29.8% (42/141) in DN subjects. The odds ratios (ORs) for DN for the susceptible Gly/Ser and Ser/Ser genotype after adjusting for age, sex, body mass index, and duration of diabetes were 2.14 [95% confidence interval (CI), 1.23-3.72; P = 0.007] and 8.01 (95% CI, 3.89-16.47; P < 0.001), respectively. The unadjusted OR for DN for the XA genotype of the Thr394Thr polymorphism was 1.87 (95% CI, 1.20-2.92; P = 0.006) compared to T2D subjects. However, the significance was lost (P = 0.061) when adjusted for age, sex, BMI, and duration of diabetes. The +A2962G of PPARGC1A and the 3 polymorphisms of PPARG were not associated with DN. CONCLUSION: The Gly482Ser polymorphism of the PPARGC1A gene is associated with DN in Asian Indians.
Resumo:
The aim of the study was to assess the relation of adiponectin levels with the metabolic syndrome in Asian Indians, a high-risk group for diabetes and premature coronary artery disease. The study was conducted on 100 (50 men and 50 women) type 2 diabetic subjects and 100 age and sex matched subjects with normal glucose tolerance selected from the Chennai Urban Rural Epidemiology Study, an ongoing population study in Chennai in southern India. Metabolic syndrome was defined using modified Adult Treatment Panel III (ATPIII) guidelines. Adiponectin values were significantly lower in diabetic subjects (men: 5.2 vs 8.3 microg/mL, P=.00l; women: 7.6 vs 11.1 microg/mL, P<.00l) and those with the metabolic syndrome (men: 5.0 vs 6.8 microg/mL, P=.01; women: 6.5 vs 9.9 microg/mL, P=.001) compared with those without. Linear regression analysis revealed adiponectin to be associated with body mass index (P<.05), waist circumference (P<.01), fasting plasma glucose (P=.001), glycated hemoglobin (P<.001), triglycerides (P<.00l), high-density lipoprotein (HDL) cholesterol (P<.001), cholesterol/HDL ratio (P<.00l), and insulin resistance measured by homeostasis assessment model (P<.00l). Factor analysis identified 2 factors: factor 1, negatively loaded with adiponectin and HDL cholesterol and positively loaded with triglycerides, waist circumference, and insulin resistance measured by homeostasis assessment model; and factor 2, with a positive loading of waist circumference and systolic and diastolic blood pressure. Logistic regression analysis revealed adiponectin to be negatively associated with metabolic syndrome (odds ratio [OR], 0.365; P<.001) even after adjusting for age (OR, 0.344; P<.00l), sex (OR, 0.293; P<.001), and body mass index (OR, 0.292; P<.00l). Lower adiponectin levels are associated with the metabolic syndrome per se and several of its components, particularly, diabetes, insulin resistance, and dyslipidemia in this urban south Indian population.
Resumo:
Adiponectin is an adipose tissue specific protein that is decreased in subjects with obesity and type 2 diabetes. The objective of the present study was to examine whether variants in the regulatory regions of the adiponectin gene contribute to type 2 diabetes in Asian Indians. The study comprised of 2,000 normal glucose tolerant (NGT) and 2,000 type 2 diabetic, unrelated subjects randomly selected from the Chennai Urban Rural Epidemiology Study (CURES), in southern India. Fasting serum adiponectin levels were measured by radioimmunoassay. We identified two proximal promoter SNPs (-11377C-->G and -11282T-->C), one intronic SNP (+10211T-->G) and one exonic SNP (+45T-->G) by SSCP and direct sequencing in a pilot study (n = 500). The +10211T-->G SNP alone was genotyped using PCR-RFLP in 4,000 study subjects. Logistic regression analysis revealed that subjects with TG genotype of +10211T-->G had significantly higher risk for diabetes compared to TT genotype [Odds ratio 1.28; 95% Confidence Interval (CI) 1.07-1.54; P = 0.008]. However, no association with diabetes was observed with GG genotype (P = 0.22). Stratification of the study subjects based on BMI showed that the odds ratio for obesity for the TG genotype was 1.53 (95%CI 1.3-1.8; P < 10(-7)) and that for GG genotype, 2.10 (95% CI 1.3-3.3; P = 0.002). Among NGT subjects, the mean serum adiponectin levels were significantly lower among the GG (P = 0.007) and TG (P = 0.001) genotypes compared to TT genotype. Among Asian Indians there is an association of +10211T-->G polymorphism in the first intron of the adiponectin gene with type 2 diabetes, obesity and hypoadiponectinemia.
Resumo:
Background Lifestyle factors such as diet and physical activity have been shown to modify the association between fat mass and obesity–associated (FTO) gene variants and metabolic traits in several populations; however, there are no gene-lifestyle interaction studies, to date, among Asian Indians living in India. In this study, we examined whether dietary factors and physical activity modified the association between two FTO single nucleotide polymorphisms (rs8050136 and rs11076023) (SNPs) and obesity traits and type 2 diabetes (T2D). Methods The study included 734 unrelated T2D and 884 normal glucose-tolerant (NGT) participants randomly selected from the urban component of the Chennai Urban Rural Epidemiology Study (CURES). Dietary intakes were assessed using a validated interviewer administered semi-quantitative food frequency questionnaire (FFQ). Physical activity was based upon the self-report. Interaction analyses were performed by including the interaction terms in the linear/logistic regression model. Results There was a significant interaction between SNP rs8050136 and carbohydrate intake (% energy) (Pinteraction = 0.04), where the ‘A’ allele carriers had 2.46 times increased risk of obesity than those with ‘CC’ genotype (P = 3.0 × 10−5) among individuals in the highest tertile of carbohydrate intake (% energy, 71 %). A significant interaction was also observed between SNP rs11076023 and dietary fibre intake (Pinteraction = 0.0008), where individuals with AA genotype who are in the 3rd tertile of dietary fibre intake had 1.62 cm lower waist circumference than those with ‘T’ allele carriers (P = 0.02). Furthermore, among those who were physically inactive, the ‘A’ allele carriers of the SNP rs8050136 had 1.89 times increased risk of obesity than those with ‘CC’ genotype (P = 4.0 × 10−5). Conclusions This is the first study to provide evidence for a gene-diet and gene-physical activity interaction on obesity and T2D in an Asian Indian population. Our findings suggest that the association between FTO SNPs and obesity might be influenced by carbohydrate and dietary fibre intake and physical inactivity. Further understanding of how FTO gene influences obesity and T2D through dietary and exercise interventions is warranted to advance the development of behavioral intervention and personalised lifestyle strategies, which could reduce the risk of metabolic diseases in this Asian Indian population.