Progression and Regression: Distinct Developmental Patterns of Diabetic Retinopathy in Patients With Type 2 Diabetes Treated in the Diabetes Care System West-Friesland, the Netherlands

OBJECTIVE: To identify distinct developmental patterns of diabetic retinopathy (DR) and assess the risk factor levels of patients in these clusters. RESEARCH DESIGN AND METHODS: A cohort of 3,343 patients with type 2 diabetes mellitus (T2DM) monitored and treated in the Diabetes Care System West-Friesland, the Netherlands, was followed from 2 to 6 years. Risk factors were measured, and two-field fundus photographs were taken annually and graded according to the EURODIAB study group. Latent class growth modeling was used to identify distinct developmental patterns of DR over time. RESULTS: Five clusters of patients with distinct developmental patterns of DR were identified: A, patients without any signs of DR (88.9%); B, patients with a slow regression from minimal background to no DR (4.9%); C, patients with a slow progression from minimal background to moderate nonproliferative DR (4.0%); D, patients with a fast progression from minimal or moderate nonproliferative to (pre)proliferative or treated DR (1.4%); and E, patients with persistent proliferative DR (0.8%). Patients in clusters A and B were characterized by lower risk factor levels, such as diabetes duration, HbA(1c), and systolic blood pressure compared with patients in progressive clusters (C-E). CONCLUSIONS: Clusters of patients with T2DM with markedly different patterns of DR development were identified, including a cluster with regression of DR. These clusters enable a more detailed examination of the influence of various risk factors on DR

Common Variants in the Type 2 Diabetes KCNQ1 Gene Are Associated with Impairments in Insulin Secretion During Hyperglycaemic Glucose Clamp

Background: Genome-wide association studies in Japanese populations recently identified common variants in the KCNQ1 gene to be associated with type 2 diabetes. We examined the association of these variants within KCNQ1 with type 2 diabetes in a Dutch population, investigated their effects on insulin secretion and metabolic traits and on the risk of developing complications in type 2 diabetes patients. Methodology: The KCNQ1 variants rs151290, rs2237892, and rs2237895 were genotyped in a total of 4620 type 2 diabetes patients and 5285 healthy controls from the Netherlands. Data on macrovascular complications, nephropathy and retinopathy were available in a subset of diabetic patients. Association between genotype and insulin secretion/action was assessed in the additional sample of 335 individuals who underwent a hyperglycaemic clamp. Principal Findings: We found that all the genotyped KCNQ1 variants were significantly associated with type 2 diabetes in our Dutch population, and the association of rs151290 was the strongest (OR 1.20, 95% CI 1.07-1.35, p = 0.002). The risk C-allele of rs151290 was nominally associated with reduced first-phase glucose-stimulated insulin secretion, while the non-risk T-allele of rs2237892 was significantly correlated with increased second-phase glucose-stimulated insulin secretion (p = 0.025 and 0.0016, respectively). In addition, the risk C-allele of rs2237892 was associated with higher LDL and total cholesterol levels (p = 0.015 and 0.003, respectively). We found no evidence for an association of KCNQ1 with diabetic complications. Conclusions: Common variants in the KCNQ1 gene are associated with type 2 diabetes in a Dutch population, which can be explained at least in part by an effect on insulin secretion. Furthermore, our data suggest that KCNQ1 is also associated with lipid metabolism

The Diabetes Pearl: Diabetes biobanking in The Netherlands

Contains fulltext : 109720.pdf (publisher's version ) (Open Access)ABSTRACT: BACKGROUND: Type 2 diabetes is associated with considerable comorbidity and severe complications, which reduce quality of life of the patients and require high levels of healthcare. The Diabetes Pearl is a large cohort of patients diagnosed with type 2 diabetes, covering different geographical areas in the Netherlands. The aim of the study is to create a research infrastructure that will allow the study of risk factors, including biomarkers and genetic determinants for severe diabetes complications. METHODS/DESIGN: Baseline examinations began November 2009 and will continue through 2012. By the end of 2012, it is expected that 7000 patients with type 2 diabetes will be included in the Diabetes Pearl cohort. To ensure quality of the data collected, standard operation procedures were developed and used in all 8 recruitment centers. From all patients who provide informed consent, the following information is collected: personal information, medication use, physical examination (antropometry, blood pressure, electrocardiography (ECG), retina photographs, ankle-brachial index, peripheral vibration perception), self-report questionnaire (socio-economic status, lifestyle, (family) history of disease, and psychosocial well-being), laboratory measurements (glucose, A1c, lipid profile, kidney function), biobank material (storage of urine and blood samples and isolated DNA). All gathered clinical data and biobank information is uploaded to a database for storage on a national level. Biobanks are maintained locally at all recruitment centers. DISCUSSION: The Diabetes Pearl is large-scale cohort of type 2 diabetes patients in the Netherlands aiming to study risk factors, including biomarkers and genetic markers, for disease deterioration and the development of severe diabetes complications. As a result of the well-designed research design and the national coverage, the Diabetes Pearl data can be of great value to national and international researchers with an interest in diabetes related research

Effect of <i>KCNQ1</i> variants rs151290, rs2237892 and rs2237895 on quantitative metabolic traits in non-diabetic individuals.

a<p>Adjusted for age, sex and study center.</p>b<p>p-value for the additive model.</p><p>The data are presented as mean±SD. All variables were log-transformed before analysis. Alleles in bold are the risk alleles for type 2 diabetes identified by previous studies. BMI: Body Mass Index. HbA_1c: haemoglobin A_1c (glucose bound to haemoglobin). HDL: high density lipoprotein. LDL: low density lipoprotein.</p

Clinical characteristics of the study participants.

<p>The data are presented as mean ± SD. BMI: Body Mass Index. HbA_1c: haemoglobin A_1c. HDL: high density lipoprotein. LDL: low density lipoprotein. T2D: type 2 diabetes.</p