BackgroundAlthough diabetic kidney disease demonstrates both familial clustering and single nucleotide polymorphism heritability, the specific genetic factors influencing risk remain largely unknown.MethodsTo identify genetic variants predisposing to diabetic kidney disease, we performed genome-wide association study (GWAS) analyses. Through collaboration with the Diabetes Nephropathy Collaborative Research Initiative, we assembled a large collection of type 1 diabetes cohorts with harmonized diabetic kidney disease phenotypes. We used a spectrum of ten diabetic kidney disease definitions based on albuminuria and renal function.ResultsOur GWAS meta-analysis included association results for up to 19,406 individuals of European descent with type 1 diabetes. We identified 16 genome-wide significant risk loci. The variant with the strongest association (rs55703767) is a common missense mutation in the collagen type IV alpha 3 chain (COL4A3) gene, which encodes a major structural component of the glomerular basement membrane (GBM). Mutations in COL4A3 are implicated in heritable nephropathies, including the progressive inherited nephropathy Alport syndrome. The rs55703767 minor allele (Asp326Tyr) is protective against several definitions of diabetic kidney disease, including albuminuria and ESKD, and demonstrated a significant association with GBM width; protective allele carriers had thinner GBM before any signs of kidney disease, and its effect was dependent on glycemia. Three other loci are in or near genes with known or suggestive involvement in this condition (BMP7) or renal biology (COLEC11 and DDR1).ConclusionsThe 16 diabetic kidney disease–associated loci may provide novel insights into the pathogenesis of this condition and help identify potential biologic targets for prevention and treatment.

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Objective: Type 2 diabetes mellitus appears to involve an interaction between susceptible genetic backgrounds and environmental factors including highly calorific diets. As it is important to identify modifiable risk factors that may help reduce the risk of type 2 diabetes mellitus, the aim of the present study was to determine the association between egg consumption and the risk of type 2 diabetes mellitus. Design: A specifically designed questionnaire was used to collect information on possible risk factors of type 2 diabetes mellitus. The odds ratios and 95 % confidence intervals for type 2 diabetes mellitus were calculated by conditional logistic regression. Setting: A case-control study in a Lithuanian out-patient clinic was performed in 2001. Subjects: A total of 234 cases with a newly confirmed diagnosis of type 2 diabetes mellitus and 468 controls free of the disease. Results: Variables such as BMI, family history of diabetes, cigarette smoking, education, morning exercise and plasma TAG level were retained in multivariate logistic regression models as confounders because their inclusion changed the value of the odds ratio by more than 10 % in any exposure category. After adjustment for possible confounders more than twofold increased risk of type 2 diabetes mellitus was determined for individuals consuming 3-4?9 eggs/week (OR 5 2?60; 95 % CI 1?34, 5?08) and threefold increased risk of the disease was determined for individuals consuming $5 eggs/week (OR 5 3?02; 95 % CI 1?14, 7?98) compared with those eating ,1 egg/week. Conclusions: Our data support a possible relationship of egg consumption and increased risk of type 2 diabetes mellitus.

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