491 resultados para diabetes nurse


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AIM: To evaluate the association with diabetic kidney disease of single nucleotide polymorphisms (SNPs) that may contribute to mitochondrial dysfunction.

METHODS: The mitochondrial genome and 1039 nuclear genes that are integral to mitochondrial function were investigated using a case (n=823 individuals with diabetic kidney disease) vs. control (n=903 individuals with diabetes and no renal disease) approach. All people included in the analysis were of white European origin and were diagnosed with Type 1 diabetes before the age of 31 years. Replication was conducted in 5093 people with similar phenotypes to those of the discovery collection. Association analyses were performed using the plink genetic analysis toolset, with adjustment for relevant covariates.

RESULTS: A total of 25 SNPs were evaluated in the mitochondrial genome, but none were significantly associated with diabetic kidney disease or end-stage renal disease. A total of 38 SNPs in nuclear genes influencing mitochondrial function were nominally associated with diabetic kidney disease and 16 SNPS were associated with end-stage renal disease, secondary to diabetic kidney disease, with meta-analyses confirming the same direction of effect. Three independent signals (seven SNPs) were common to the replication data for both phenotypes with Type 1 diabetes and persistent proteinuria or end-stage renal disease.

CONCLUSIONS: Our results suggest that SNPs in nuclear genes that influence mitochondrial function are significantly associated with diabetic kidney disease in a white European population

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AIMS: Epigenetic modifications, such as DNA methylation, can influence the risk of developing kidney disease. We studied methylation profiles in genes related to mitochondrial function to assess whether differences in these epigenetic features were associated with diabetic kidney disease in people with Type 1 diabetes.

METHODS: A case-control association study was undertaken (n = 196 individuals with diabetic kidney disease vs. n = 246 individuals without renal disease). Participants were White and diagnosed with Type 1 diabetes before 31 years of age. Genes that encode mitochondrial proteins (n = 780) were downloaded from mitoproteome. org. DNA methylation profiles from blood-derived DNA were generated using the Illumina Infinium HumanMethylation450 (262 samples) and Illumina Infinium HumanMethylation27 (192 samples) arrays. Beta values (β) were calculated and quality control was conducted, including evaluating blind duplicate DNA samples.

RESULTS: Fifty-four Cytosine-phosphate-Guanine probes across 51 unique genes were significantly associated (P ≤ 10(-8) ) with diabetic kidney disease across both the 450K and the 27K methylation arrays. A subanalysis, employing the 450K array, identified 755 Cytosine-phosphate-Guanine probes in 374 genes that were significantly associated (P ≤ 10(-8) ) with end-stage renal disease. Forty-six of the top-ranked variants for diabetic kidney disease were also identified as being differentially methylated in individuals with end-stage renal disease. The largest change in methylation (Δβ = 0.2) was observed for cg03169527 in the TAMM41 gene, chromosome 3p25.2. Three genes, PMPCB, TSFM and AUH, were observed with differential methylation at multiple Cytosine-phosphate-Guanine sites each (P < 10(-12) ).

CONCLUSIONS: Differential methylation in genes that influence mitochondrial function are associated with kidney disease in individuals with Type 1 diabetes

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Aims/hypothesis
The receptor for AGEs (RAGE) is linked to proinflammatory pathology in a range of tissues. The objective of this study was to assess the potential modulatory role of RAGE in diabetic retinopathy.
Methods
Diabetes was induced in wild-type (WT) and Rage −/− mice (also known as Ager −/− mice) using streptozotocin while non-diabetic control mice received saline. For all groups, blood glucose, HbA1c and retinal levels of methylglyoxal (MG) were evaluated up to 24 weeks post diabetes induction. After mice were killed, retinal glia and microglial activation, vasopermeability, leucostasis and degenerative microvasculature changes were determined. 

Results
Retinal expression of RAGE in WT diabetic mice was increased after 12 weeks (p < 0.01) but not after 24 weeks. Rage −/− mice showed comparable diabetes but accumulated less MG and this corresponded to enhanced activity of the MG-detoxifying enzyme glyoxalase I in their retina when compared with WT mice. Diabetic Rage −/− mice showed significantly less vasopermeability, leucostasis and microglial activation (p < 0.05–0.001). Rage −/− mice were also protected against diabetes-related retinal acellular capillary formation (p < 0.001) but not against pericyte loss. 

Conclusions/interpretation Rage −/− in diabetic mice is protective against many retinopathic lesions, especially those related to innate immune responses. Inhibition of RAGE could be a therapeutic option to prevent diabetic retinopathy.

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OBJECTIVE: To assess the relationship between second and third trimester glycemic control and adverse outcomes in pregnant women with type 1 diabetes, as uncertainty exists about optimum glycemic targets.

RESEARCH DESIGN AND METHODS: Pregnancy outcomes were assessed prospectively in 725 women with type 1 diabetes from the Diabetes and Pre-eclampsia Intervention Trial. HbA1c (A1C) values at 26 and 34 weeks' gestation were categorized into five groups, the lowest, <6.0% (42 mmol/mol), being the reference. Average pre- and postprandial results from an eight-point capillary glucose profile the previous day were categorized into five groups, the lowest (preprandial <5.0 mmol/L and postprandial <6.0 mmol/L) being the reference.

RESULTS: An A1C of 6.0-6.4% (42-47 mmol/mol) at 26 weeks' gestation was associated with a significantly increased risk of large for gestational age (LGA) (odds ratio 1.7 [95% CI 1.0-3.0]) and an A1C of 6.5-6.9% (48-52 mmol/mol) with a significantly increased risk of preterm delivery (odds ratio 2.5 [95% CI 1.3-4.8]), pre-eclampsia (4.3 [1.7-10.8]), need for a neonatal glucose infusion (2.9 [1.5-5.6]), and a composite adverse outcome (3.2 [1.3-8.0]). These risks increased progressively with increasing A1C. Results were similar at 34 weeks' gestation. Glucose data showed less consistent trends, although the risk of a composite adverse outcome increased with preprandial glucose levels between 6.0 and 6.9 mmol/L at 34 weeks (3.3 [1.3-8.0]).

CONCLUSIONS: LGA increased significantly with an A1C ≥6.0 (42 mmol/mol) at 26 and 34 weeks' gestation and with other adverse outcomes with an A1C ≥6.5% (48 mmol/mol). The data suggest that there is clinical utility in regular measurement of A1C during pregnancy.

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Introduction
Despite excellent first year outcomes in kidney transplantation, there remain significant long-term complications related to new-onset diabetes after transplantation (NODAT). The purpose of this study was to validate the findings of previous investigations of candidate gene variants in patients undergoing a protocolised, contemporary immunosuppression regimen, using detailed serial biochemical testing to identify NODAT development.

Methods
One hundred twelve live and deceased donor renal transplant recipients were prospectively followed-up for NODAT onset, biochemical testing at days 7, 90, and 365 after transplantation. Sixty-eight patients were included after exclusion for non-white ethnicity and pre-transplant diabetes. Literature review to identify candidate gene variants was undertaken as described previously.

Results
Over 25% of patients developed NODAT. In an adjusted model for age, sex, BMI, and BMI change over 12 months, five out of the studied 37 single nucleotide polymorphisms (SNPs) were significantly associated with NODAT: rs16936667:PRDM14 OR 10.57;95% CI 1.8–63.0;p = 0.01, rs1801282:PPARG OR 8.5; 95% CI 1.4–52.7; p = 0.02, rs8192678:PPARGC1A OR 0.26; 95% CI 0.08–0.91; p = 0.03, rs2144908:HNF4A OR 7.0; 95% CI 1.1–45.0;p = 0.04 and rs2340721:ATF6 OR 0.21; 95%CI 0.04–1.0; p = 0.05.

Conclusion
This study represents a replication study of candidate SNPs associated with developing NODAT and implicates mTOR as the central regulator via altered insulin sensitivity, pancreatic β cell, and mitochondrial survival and dysfunction as evidenced by the five SNPs.

General significance
1) Highlights the importance of careful biochemical phenotyping with oral glucose tolerance tests to diagnose NODAT in reducing time to diagnosis and missed cases.
2)This alters potential genotype:phenotype association.
3)The replication study generates the hypothesis that mTOR signalling pathway may be involved in NODAT development.

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BACKGROUND: The month of diagnosis in childhood type 1 diabetes shows seasonal variation.

OBJECTIVE: We describe the pattern and investigate if year-to-year irregularities are associated with meteorological factors using data from 50 000 children diagnosed under the age of 15 yr in 23 population-based European registries during 1989-2008.

METHODS: Tests for seasonal variation in monthly counts aggregated over the 20 yr period were performed. Time series regression was used to investigate if sunshine hour and average temperature data were predictive of the 240 monthly diagnosis counts after taking account of seasonality and long term trends.

RESULTS: Significant sinusoidal pattern was evident in all but two small centers with peaks in November to February and relative amplitudes ranging from ±11 to ±38% (median ±17%). However, most centers showed significant departures from a sinusoidal pattern. Pooling results over centers, there was significant seasonal variation in each age-group at diagnosis, with least seasonal variation in those under 5 yr. Boys showed greater seasonal variation than girls, particularly those aged 10-14 yr. There were no differences in seasonal pattern between four 5-yr sub-periods. Departures from the sinusoidal trend in monthly diagnoses in the period were significantly associated with deviations from the norm in average temperature (0.8% reduction in diagnoses per 1 °C excess) but not with sunshine hours.

CONCLUSIONS: Seasonality was consistently apparent throughout the period in all age-groups and both sexes, but girls and the under 5 s showed less marked variation. Neither sunshine hour nor average temperature data contributed in any substantial way to explaining departures from the sinusoidal pattern.