787 resultados para Type II diabetes


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The metabolic syndrome and type 1 diabetes are associated with brain alterations such as cognitive decline brain infarctions, atrophy, and white matter lesions. Despite the importance of these alterations, their pathomechanism is still poorly understood. This study was conducted to investigate brain glucose and metabolites in healthy individuals with an increased cardiovascular risk and in patients with type 1 diabetes in order to discover more information on the nature of the known brain alterations. We studied 43 20- to 45-year-old men. Study I compared two groups of non-diabetic men, one with an accumulation of cardiovascular risk factors and another without. Studies II to IV compared men with type 1 diabetes (duration of diabetes 6.7 ± 5.2 years, no microvascular complications) with non-diabetic men. Brain glucose, N-acetylaspartate (NAA), total creatine (tCr), choline, and myo-inositol (mI) were quantified with proton magnetic resonance spectroscopy in three cerebral regions: frontal cortex, frontal white matter, thalamus, and in cerebellar white matter. Data collection was performed for all participants during fasting glycemia and in a subgroup (Studies III and IV), also during a hyperglycemic clamp that increased plasma glucose concentration by 12 mmol/l. In non-diabetic men, the brain glucose concentration correlated linearly with plasma glucose concentration. The cardiovascular risk group (Study I) had a 13% higher plasma glucose concentration than the control group, but no difference in thalamic glucose content. The risk group thus had lower thalamic glucose content than expected. They also had 17% increased tCr (marker of oxidative metabolism). In the control group, tCr correlated with thalamic glucose content, but in the risk group, tCr correlated instead with fasting plasma glucose and 2-h plasma glucose concentration in the oral glucose tolerance test. Risk factors of the metabolic syndrome, most importantly insulin resistance, may thus influence brain metabolism. During fasting glycemia (Study II), regional variation in the cerebral glucose levels appeared in the non-diabetic subjects but not in those with diabetes. In diabetic patients, excess glucose had accumulated predominantly in the white matter where the metabolite alterations were also the most pronounced. Compared to the controls values, the white matter NAA (marker of neuronal metabolism) was 6% lower and mI (glia cell marker) 20% higher. Hyperglycemia is therefore a potent risk factor for diabetic brain disease and the metabolic brain alterations may appear even before any peripheral microvascular complications are detectable. During acute hyperglycemia (Study III), the increase in cerebral glucose content in the patients with type 1 diabetes was, dependent on brain region, between 1.1 and 2.0 mmol/l. An every-day hyperglycemic episode in a diabetic patient may therefore as much as double brain glucose concentration. While chronic hyperglycemia had led to accumulation of glucose in the white matter, acute hyperglycemia burdened predominantly the gray matter. Acute hyperglycemia also revealed that chronic fluctuation in blood glucose may be associated with alterations in glucose uptake or in metabolism in the thalamus. The cerebellar white matter appeared very differently from the cerebral (Study IV). In the non-diabetic men it contained twice as much glucose as the cerebrum. Diabetes had altered neither its glucose content nor the brain metabolites. The cerebellum seems therefore more resistant to the effects of hyperglycemia than is the cerebrum.

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Background: Type 2 diabetes is linked to several complications which add to both physical and mental distress. Depression is a common co-morbidity of diabetes which can occur both as a cause and a consequence of type 2 diabetes. Depression has been shown to correlate with glucose regulation and treating depression might prove beneficial for glucose regulation as well as for mental well being. Another complication which might affect diabetes management is cognitive decline. Several risk factors and complications of diabetes might modify the risk for developing cognitive impairment, which is increased 1.5 times among subjects with type 2 diabetes. Type 2 diabetes, depression and impaired cognitive performance have all been linked to low birth weight. This thesis aimed to explore the effects and interactions of birth weight, depression and cognitive ability in relation to type 2 diabetes from a life course perspective. Subjects and methods: Studies I, II and V were part of the Helsinki Birth Cohort Study. 2003 subjects participated in an extensive clinical examination at an average age of 61 years. A standard glucose tolerance test (OGTT) was performed and depressive symptoms were assessed using the Beck Depression Inventory (BDI). In addition data was obtained from child welfare clinics and national registers. A subset of the cohort (n=1247) also performed a test on cognitive performance (CogState ®) at the average age of 64. Studies III and IV were randomised clinical trials where mildly depressed diabetic subjects were treated with paroxetine or placebo and the effect on metabolic parameters and quality of life was assessed. The first trial included 14 women and lasted 10 weeks, while the second trial included 43 subjects, both men and women, and lasted 6 months. Results: Type 2 diabetes was positively associated with the occurrence of depressive symptoms. Among diabetic subjects 23.6% had depressive symptoms, compared to 16.7% of subjects with normal glucose tolerance (OR = 1.77, p<0.001). Formal mediation analysis revealed that cardiovascular disease (CVD) is likely to act as a mediator in the association. Furthermore, low birth weight was found to modify the association between type 2 diabetes, CVD and depression. The association between BDI score and having type 2 diabetes or CVD was twice as strong in the subgroup with low birth weight (≤ 2500g) compared with the group with birth weight > 2500g (p for interaction 0.058). In the six months long randomised clinical trial (study IV) paroxetine had a transient beneficial effect on glycosylated haemoglobin A1c (GHbA1c) and quality of life when compared to placebo after three months of treatment. In study V we found that subjects with known diabetes had a consistently poorer level of cognitive performance than subjects with normal glucose tolerance in most of the tested cognitive domains. This effect was further amplified among those born with a small birth weight (p for interaction 0.002). Conclusions: Type 2 diabetes is associated with a higher occurrence of depressive symptoms compared to subjects with normal glucose tolerance. This association is especially strong among subjects with CVD and those born with a low birth weight. Treating depressed diabetic subjects with paroxetine has no long term effect on glucose regulation. Physicians should be aware of depression as an important co-morbidity of type 2 diabetes. Both depression and the cognitive decline often seen among diabetic subjects are increased if the subject is born with a low birth weight. Physicians should recognise low birth weight as an additional risk factor and modifier of diabetic complications.

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Aims/hypothesis: SMAD proteins are involved in multiple signalling pathways and are key modulators of gene expression. We hypothesised that genetic variation in selected SMAD genes contributes to susceptibility to diabetic nephropathy. Methods: We selected 13 haplotype tag (ht) single nucleotide polymorphisms (SNPs) from 67 variants identified by resequencing the SMAD2 and SMAD3 genes. For SMAD1, SMAD4 and SMAD5 genes, genotype data were downloaded for 217 SNPs from Phase II of the International HapMap project. Of these, 85 SNPs met our inclusion criteria, resulting in the selection of 13 tag SNPs for further investigation. A case-control approach was employed, using 267 nephropathic patients and 442 controls with type 1 diabetes from Ireland. Two further populations (totalling 1,407 patients, 2,238 controls) were genotyped to validate initial findings. Genotyping was conducted using iPLEX, TaqMan and gel electrophoresis.
Results: The distribution of genotypes was in Hardy-Weinberg equilibrium. Analysis by the ? 2 test of genotype and allele frequencies in patients versus controls in the Irish population (n?=?709) revealed evidence for the association of one allele at 5% level of significance (rs10515478, p uncorrected?=?0.006; p corrected?=?0.04). This finding represents a relatively small difference in allele frequency of 6.4% in the patient group compared with 10.7% in the control group; this difference was not supported in subsequent investigations using DNA from European individuals with similar phenotypic characteristics.
Conclusions/interpretation: We selected an appropriate subset of variants for the investigation of common genetic risk factors and assessed SMAD1 to SMAD5 genes for association with diabetic nephropathy. We conclude that common polymorphisms in these genes do not strongly influence genetic susceptibility to diabetic nephropathy in white individuals with type 1 diabetes mellitus.

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A Diabetes Mellitus (DM) compreende um conjunto de desordens metabólicas comuns caracterizadas por hiperglicemia, que afeta diferentes órgãos do organismo. Ao longo do tempo, ocorrem danos microvasculares no glomérulo renal, retina e nervos periféricos, bem como doença macrovascular nas artérias. A composição da saliva também é afetada pela DM, com consequências na homeostasia oral. No entanto, o proteoma e o peptidoma salivar têm sido pouco explorados na DM tipo 1 e nas suas complicações crónicas. Tendo em conta o crescente interesse na saliva como fluido diagnóstico, o objetivo principal deste trabalho foi avaliar os eventos proteolíticos subjacentes à DM tipo 1 e às suas complicações microvasculares, bem como, caracterizar as alterações induzidas pela DM tipo 1 no proteoma e peptidoma salivar. A DM tipo 1 e particularmente as complicações microvasculares associadas modulam o perfil proteolítico dos fluidos biológicos, com diferenças significativas de atividade observadas na urina e saliva, atribuídas principalmente ao complexo Metaloproteinase da Matriz (MMP)-9/lipocalina associada à gelatinase de neutrófilos, aminopeptidase N, azurocidina e calicreína 1. O aumento da atividade proteolítica observado na saliva total dos diabéticos resultou no aumento da percentagem de péptidos, principalmente de um número acrescido de fragmentos de colagénio do tipo I, refletindo possivelmente um estado inflamatório crónico dos tecidos orais e periodontais. O peptidoma também corrobora uma maior suscetibilidade das proteínas salivares, especificamente, das proteínas ricas em prolina básicas (bPRP) 1, bPRP2 e proteínas ricas em prolina ácidas (aPRP) à proteólise, evidenciando a geração de fragmentos de proteínas associadas à ligação a bactérias. A análise do proteoma salivar baseada em iTRAQ mostrou uma sobre-expressão de L-plastina, fator do adenocarcinoma do pâncreas e das proteínas S100-A8 e S100-A9, enfatizando a importância do sistema imune inato na patogénese da DM tipo 1 e das complicações microvasculares associadas. A análise integrada de todas as proteínas expressas diferencialmente entre os pacientes diabéticos com ou sem complicações microvasculares e indivíduos saudáveis foi realizada com o STRING, onde se observam três conjuntos funcionalmente ligados, um compreende a interação entre o colagénio tipo I, colagénio tipo II e MMP-9, um segundo conjunto envolve a MMP-2 e o colagénio de tipo I e um terceiro conjunto composto por proteínas salivares e inflamatórias. Estes conjuntos estão associados com as vias Kegg de interação recetor-matriz extracelular, de adesão focal e migração transendotelial dos leucócitos. Por outro lado, a análise do proteoma e peptidoma salivar destacou potenciais biomarcadores para o diagnóstico e prognóstico da DM tipo 1 e das suas complicações.

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TNF microsatellite and HLA class II polymorphisms were studied in 28 recently diagnosed Brazilian patients presenting type 1 diabetes mellitus (T1DM) and in 120 healthy controls. TNFa-e and HLA-DRB1/DQB1 alleles were identified using sets of sequence-specific primers. Compared to controls, the DRB1* 03 and DQBI*02 allele groups, TNFa1 allele, and the TNFa4-b5-c1-d4-e3 and TNFa10-b5-c1-d4-e3 haplotypes were overrepresented in patients. TNF microsatellite together with HLA polymorphisms is associated with type 1 diabetes in Brazilian patients, corroborating the participation of the MHC genes in disease susceptibility.

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Background: In recent years, important advances have occurred in the determination of diagnostic criteria for the disease diabetes mellitus and in new strategies for its treatment. The purpose of this research was to develop a new method for diabetes diagnosis by microscopic and cytomorphometric analyses of the oral epithelium. Methods: the smears were obtained from three distinct oral sites: buccal mucosa (cheek), tongue dorsum, and floor of the mouth in 10 control individuals and 10 type II diabetic patients. The oral smears were stained with Papanicolaou EA-36 solution. The nuclear (NA) and cytoplasmic (CA) areas were evaluated from 50 integral cells predominant in each oral site by the use of the KS 300(TM) image analysis system (Carl Zeiss, Germany), by which the cytoplasmic/nuclear ratio (C/N) was calculated. Results: the results showed that: (i) the epithelial cells of the diabetic group exhibited figures of binucleation and occasional karyorrhexis in all layers; (ii) the NA was markedly higher (P<0.05) in the diabetic group; (iii) the CA did not exhibit a statistically significant difference (P>0.05) between these two groups; and (iv) the C/N mean was 37.4% lower in the type II diabetic group. Conclusions: These results associated with clinical observations suggest that diabetes mellitus can produce alterations in oral epithelial cells, detectable by microscopy and cytomorphometry, which can be used in the diagnosis of this disease.

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The objective of this study was to determine the frequencies of autoantibodies to heterogeneous islet-cell cytoplasmic antigens (ICA), glutamic acid decarboxylase(65) (GAD(65)A), insulinoma-associated antigen-2 (IA-2A) and insulin (IAA)-and human leukocyte antigen (HLA) class II markers (HLA-DR and -DQ) in first degree relatives of heterogeneous Brazilian patients with type I diabetes(T1DM). A major focus of this study was to determine the influence of age, gender, proband characteristics and ancestry on the prevalence of autoantibodies and HLA-DR and -DQ alleles on disease progression and genetic predisposition to T1DM among the first-degree relatives. IAA, ICA, GAD(65)A, IA-2A and HLA- class II alleles were determined in 546 first-degree-relatives, 244 siblings, 55 offspring and 233 parents of 178 Brazilian patients with T1DM. Overall, 8.9% of the relatives were positive for one or more autoantibodies. IAA was the only antibody detected in parents. GAD(65) was the most prevalent antibody in offspring and siblings as compared to parents and it was the sole antibody detected in offspring. Five siblings were positive for the IA-2 antibody. A significant number (62.1%) of siblings had 1 or 2 high risk HLA haplotypes. During a 4-year follow-up study, 5 siblings (expressing HLA-DR3 or -DR4 alleles) and 1 offspring positive for GAD(65)A progressed to diabetes. The data indicated that the GAD(65) and IA-2 antibodies were the strongest predictors of T1DM in our study population. The high risk HLA haplotypes alone were not predictive of progression to overt diabetes.

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Background: This study evaluates cardiovascular risk factors associated with progression of coronary artery disease (CAD) in patientswith silent ischemia followingmyocardial infarction. Hypothesis: Coronary artery disease only progresses slowly with comprehensive risk factor intervention. Methods: A total of 104 of 201 patients (51.7%) of the Swiss Interventional Study on Silent Ischemia Type II (SWISSI II) with baseline and follow-up coronary angiography were included. All patients received comprehensive cardiovascular risk factor intervention according to study protocol. Logistic regression was used to evaluate associationsbetween baseline cardiovascular risk factors and CAD progression. Results: The mean duration of follow-upwas 10.3 ± 2.4 years. At baseline, 77.9% of patients were smokers, 45.2% had hypertension, 73.1% had dyslipidemia, 7.7% had diabetes, and 48.1% had a family history of CAD. At last follow-up, only 27 patients of the initial 81 smokers still smoked, only 2.1% of the patients had uncontrolled hypertension, 10.6%of the patientshad uncontrolled dyslipidemia, and 2.1%of the patientshad uncontrolled diabetes. Coronary artery disease progression was found in up to 81 (77.9%) patients. Baseline diabetes and younger age were associatedwith increased odds of CAD progression.The time intervalbetween baseline and follow-up angiography was also associatedwith CAD progression. Conclusion: Coronary artery disease progressionwas highly prevalent in these patients despite comprehensive risk factor intervention. Further research is needed to optimize treatment of known risk factors and to identify other unknown and potentiallymodifiable risk factors.

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Abstract Background and Aims: Data on the influence of calibration on accuracy of continuous glucose monitoring (CGM) are scarce. The aim of the present study was to investigate whether the time point of calibration has an influence on sensor accuracy and whether this effect differs according to glycemic level. Subjects and Methods: Two CGM sensors were inserted simultaneously in the abdomen on either side of 20 individuals with type 1 diabetes. One sensor was calibrated predominantly using preprandial glucose (calibration(PRE)). The other sensor was calibrated predominantly using postprandial glucose (calibration(POST)). At minimum three additional glucose values per day were obtained for analysis of accuracy. Sensor readings were divided into four categories according to the glycemic range of the reference values (low, ≤4 mmol/L; euglycemic, 4.1-7 mmol/L; hyperglycemic I, 7.1-14 mmol/L; and hyperglycemic II, >14 mmol/L). Results: The overall mean±SEM absolute relative difference (MARD) between capillary reference values and sensor readings was 18.3±0.8% for calibration(PRE) and 21.9±1.2% for calibration(POST) (P<0.001). MARD according to glycemic range was 47.4±6.5% (low), 17.4±1.3% (euglycemic), 15.0±0.8% (hyperglycemic I), and 17.7±1.9% (hyperglycemic II) for calibration(PRE) and 67.5±9.5% (low), 24.2±1.8% (euglycemic), 15.5±0.9% (hyperglycemic I), and 15.3±1.9% (hyperglycemic II) for calibration(POST). In the low and euglycemic ranges MARD was significantly lower in calibration(PRE) compared with calibration(POST) (P=0.007 and P<0.001, respectively). Conclusions: Sensor calibration predominantly based on preprandial glucose resulted in a significantly higher overall sensor accuracy compared with a predominantly postprandial calibration. The difference was most pronounced in the hypo- and euglycemic reference range, whereas both calibration patterns were comparable in the hyperglycemic range.

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A novel adaptive approach for glucose control in individuals with type 1 diabetes under sensor-augmented pump therapy is proposed. The controller, is based on Actor-Critic (AC) learning and is inspired by the principles of reinforcement learning and optimal control theory. The main characteristics of the proposed controller are (i) simultaneous adjustment of both the insulin basal rate and the bolus dose, (ii) initialization based on clinical procedures, and (iii) real-time personalization. The effectiveness of the proposed algorithm in terms of glycemic control has been investigated in silico in adults, adolescents and children under open-loop and closed-loop approaches, using announced meals with uncertainties in the order of ±25% in the estimation of carbohydrates. The results show that glucose regulation is efficient in all three groups of patients, even with uncertainties in the level of carbohydrates in the meal. The percentages in the A+B zones of the Control Variability Grid Analysis (CVGA) were 100% for adults, and 93% for both adolescents and children. The AC based controller seems to be a promising approach for the automatic adjustment of insulin infusion in order to improve glycemic control. After optimization of the algorithm, the controller will be tested in a clinical trial.

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In this paper, a simulation model of glucose-insulin metabolism for Type 1 diabetes patients is presented. The proposed system is based on the combination of Compartmental Models (CMs) and artificial Neural Networks (NNs). This model aims at the development of an accurate system, in order to assist Type 1 diabetes patients to handle their blood glucose profile and recognize dangerous metabolic states. Data from a Type 1 diabetes patient, stored in a database, have been used as input to the hybrid system. The data contain information about measured blood glucose levels, insulin intake, and description of food intake, along with the corresponding time. The data are passed to three separate CMs, which produce estimations about (i) the effect of Short Acting (SA) insulin intake on blood insulin concentration, (ii) the effect of Intermediate Acting (IA) insulin intake on blood insulin concentration, and (iii) the effect of carbohydrate intake on blood glucose absorption from the gut. The outputs of the three CMs are passed to a Recurrent NN (RNN) in order to predict subsequent blood glucose levels. The RNN is trained with the Real Time Recurrent Learning (RTRL) algorithm. The resulted blood glucose predictions are promising for the use of the proposed model for blood glucose level estimation for Type 1 diabetes patients.

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Whole genome linkage analysis of type 1 diabetes using affected sib pair families and semi-automated genotyping and data capture procedures has shown how type 1 diabetes is inherited. A major proportion of clustering of the disease in families can be accounted for by sharing of alleles at susceptibility loci in the major histocompatibility complex on chromosome 6 (IDDM1) and at a minimum of 11 other loci on nine chromosomes. Primary etiological components of IDDM1, the HLA-DQB1 and -DRB1 class II immune response genes, and of IDDM2, the minisatellite repeat sequence in the 5' regulatory region of the insulin gene on chromosome 11p15, have been identified. Identification of the other loci will involve linkage disequilibrium mapping and sequencing of candidate genes in regions of linkage.

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Type 1 diabetes (T1D) is a multifactorial autoimmune disease, with strong genetic component. Several susceptibility loci contribute to genetic predisposition to T1D. One of these loci have been mapped to chromosome 1q42 in UK and US joined affected family data sets but needs to be replicated in other populations. In this study, we evaluated sixteen microsatellites located on 1q42 for linkage with T1D in 97 Russian affected sibling pairs. A 2.7-cm region of suggestive linkage to T1D between markers D1S1644 and D1S225 was found by multipoint linkage analysis. The peak of linkage was shown for D1S2847 (P = 0.0005). Transmission disequilibrium test showed significant undertransmission of the 156-bp allele of D1S2847 from parents to diabetic children (28 transmissions vs. 68 nontransmissions, P = 0.043) in Russian affected families. A preferential transmission from parents to diabetic offspring was also shown for the T(-25) and T1362 alleles of the C/T(-25) and C/T1362 dimorphisms, both located at the TAF5L gene, which is situated 103 kb from D1S2847. Together with the A/C744 TAF5L SNP, these markers share common T(-25)/A744/T1362 and C(-25)/C744/T1362 haplotypes associated with higher and lower risk of diabetes (Odds Ratio = 2.15 and 0.62, respectively). Our results suggest that the TAF5L gene, encoding TAF5L-like RNA polymerase II p300/CBP associated factor (PCAF)-associated factor, could represent the susceptibility gene for T1D on chromosome 1q42 in Russian affected patients.