Diabetic kidney disease, or diabetic nephropathy (DN), is a major complication of diabetes and the leading cause of end-stage renal disease (ESRD) that requires dialysis treatment or kidney transplantation. In addition to the decrease in the quality of life, DN accounts for a large proportion of the excess mortality associated with type 1 diabetes (T1D). Whereas the degree of glycemia plays a pivotal role in DN, a subset of individuals with poorly controlled T1D do not develop DN. Furthermore, strong familial aggregation supports genetic susceptibility to DN. However, the genes and the molecular mechanisms behind the disease remain poorly understood, and current therapeutic strategies rarely result in reversal of DN. In the GEnetics of Nephropathy: an International Effort (GENIE) consortium, we have undertaken a meta-analysis of genome-wide association studies (GWAS) of T1D DN comprising ∼2.4 million single nucleotide polymorphisms (SNPs) imputed in 6,691 individuals. After additional genotyping of 41 top ranked SNPs representing 24 independent signals in 5,873 individuals, combined meta-analysis revealed association of two SNPs with ESRD: rs7583877 in the AFF3 gene (P = 1.2×10−8) and an intergenic SNP on chromosome 15q26 between the genes RGMA and MCTP2, rs12437854 (P = 2.0×10−9). Functional data suggest that AFF3 influences renal tubule fibrosis via the transforming growth factor-beta (TGF-β1) pathway. The strongest association with DN as a primary phenotype was seen for an intronic SNP in the ERBB4 gene (rs7588550, P = 2.1×10−7), a gene with type 2 diabetes DN differential expression and in the same intron as a variant with cis-eQTL expression of ERBB4. All these detected associations represent new signals in the pathogenesis of DN.

on behalf of the FinnDiane Study Group* OBJECTIVE-Poor glycemic control, elevated triglycerides, and albuminuria are associated with vascular complications in diabetes. However, few studies have investigated combined associations between metabolic markers, diabetic kidney disease, retinopathy, hypertension, obesity, and mortality. Here, the goal was to reveal previously undetected association patterns between clinical diagnoses and biochemistry in the FinnDiane dataset.RESEARCH DESIGN AND METHODS-At baseline, clinical records, serum, and 24-h urine samples of 2,173 men and 2,024 women with type 1 diabetes were collected. The data were analyzed by the self-organizing map, which is an unsupervised pattern recognition algorithm that produces a two-dimensional layout of the patients based on their multivariate biochemical profiles. At follow-up, the results were compared against allcause mortality during 6.5 years (295 deaths). RESULTS-The highest mortality was associated with advanced kidney disease. Other risk factors included 1) a profile of insulin resistance, abdominal obesity, high cholesterol, triglycerides, and low HDL 2 cholesterol, and 2) high adiponectin and high LDL cholesterol for older patients. The highest population-adjusted risk of death was 10.1-fold (95% CI 7.3-13.1) for men and 10.7-fold (7.9 -13.7) for women. Nonsignificant risk was observed for a profile with good glycemic control and high HDL 2 cholesterol and for a low cholesterol profile with a short diabetes duration.CONCLUSIONS-The self-organizing map analysis enabled detailed risk estimates, described the associations between known risk factors and complications, and uncovered statistical patterns difficult to detect by classical methods. The results also suggest that diabetes per se, without an adverse metabolic phenotype, does not contribute to increased mortality. Diabetes 57:2480-2487, 2008 P atients with type 1 diabetes are susceptible to severe microvascular complications such as proliferative retinopathy and chronic kidney disease, which are often accompanied by cardiovascular disease and premature death (1,2). Currently, the risk assessment and diagnostics rely on the urine albumin excretion, serum creatinine, and lipid profile (3,4). In many cases, however, the biochemical measurements are treated as independent factors without explicit attention to the overall metabolic imbalance behind the complications. Although the risk factors for cardiovascular disease and diabetes complications have been verified statistically in large clinical studies (5-7), the overall picture on the mutual relationships and their relevance for risk assessment remains fragmented.The metabolic syndrome (8) is one attempt to describe the co-occurrence of vascular complications and insulin resistance, but so far its applicability to type 1 diabetes and its exact definition remain controversial (9,10). Moreover, gradually developing conditions, such as cardiovascular disease, do not present a physiologically clear border between health and disease, so quanti...

We formed the GEnetics of Nephropathy–an International Effort (GENIE) consortium to examine previously reported genetic associations with diabetic nephropathy (DN) in type 1 diabetes. GENIE consists of 6,366 similarly ascertained participants of European ancestry with type 1 diabetes, with and without DN, from the All Ireland-Warren 3-Genetics of Kidneys in Diabetes U.K. and Republic of Ireland (U.K.-R.O.I.) collection and the Finnish Diabetic Nephropathy Study (FinnDiane), combined with reanalyzed data from the Genetics of Kidneys in Diabetes U.S. Study (U.S. GoKinD). We found little evidence for the association of the EPO promoter polymorphism, rs161740, with the combined phenotype of proliferative retinopathy and end-stage renal disease in U.K.-R.O.I. (odds ratio [OR] 1.14, P = 0.19) or FinnDiane (OR 1.06, P = 0.60). However, a fixed-effects meta-analysis that included the previously reported cohorts retained a genome-wide significant association with that phenotype (OR 1.31, P = 2 × 10−9). An expanded investigation of the ELMO1 locus and genetic regions reported to be associated with DN in the U.S. GoKinD yielded only nominal statistical significance for these loci. Finally, top candidates identified in a recent meta-analysis failed to reach genome-wide significance. In conclusion, we were unable to replicate most of the previously reported genetic associations for DN, and significance for the EPO promoter association was attenuated.

Aims/hypothesis This study aimed to investigate whether variation in long-term glycaemia in type 1 diabetes as measured by HbA 1c variability is associated with the cumulative incidence and risk of retinopathy requiring laser treatment. Methods The effect of HbA 1c variability was assessed in 2,019 Finnish Diabetic Nephropathy (FinnDiane) study patients. The patients were studied in two partially overlapping subcohorts with either verified first laser treatment (n=1,459) or retinopathy severity graded from ophthalmic records with the Early Treatment of Diabetic Retinopathy Study (ETDRS) scale (n=1,346). The ratio of intrapersonal SD and mean of serially measured HbA 1c was considered an estimate of HbA 1c variability.Results A subcohort of 1,459 patients did not have laser treatment prior to the first FinnDiane visit and 174 of these patients were treated during a mean follow-up period of 5.2 ±2.2 years. The 5 year cumulative incidence of laser treatment was 19% (95% CI 15, 24) in the highest quartile of HbA 1c variability and 10% (95% CI 7, 12) in the lowest quartile (p<0.001, Gray's test) with a corresponding HR of 1.6 (95% CI 1.1, 2.5; p=0.02) adjusted for renal status, diabetes duration, mean HbA 1c , blood pressure, sex and number of HbA 1c measurements. In a subcohort of 1,346 patients, 434 patients had proliferative diabetic retinopathy (PDR). Patients in the highest quartile of HbA 1c variability had an increased risk of PDR compared with the lowest quartile (HR 1.7 [95% CI 1.3, 2.2]; p<0.001]). Conclusions/interpretation HbA 1c variability was associated with an increased cumulative incidence and risk of retinopathy requiring laser treatment in type 1 diabetes.