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.

Statins effectively lower LDL cholesterol levels in large studies and the observed interindividual response variability may be partially explained by genetic variation. Here we perform a pharmacogenetic meta-analysis of genome-wide association studies (GWAS) in studies addressing the LDL cholesterol response to statins, including up to 18,596 statin-treated subjects. We validate the most promising signals in a further 22,318 statin recipients and identify two loci, SORT1/CELSR2/PSRC1 and SLCO1B1, not previously identified in GWAS. Moreover, we confirm the previously described associations with APOE and LPA. Our findings advance the understanding of the pharmacogenetic architecture of statin response.

OBJECTIVECirculating levels of soluble receptor for advanced glycation end products (sRAGE) likely comprise both a secreted isoform (esRAGE) and wild-type RAGE cleaved from the cell membrane. Both sRAGE and esRAGE have been proposed as biomarkers of cardiovascular disease (CVD), but prospective data are limited. We examined the relationship of sRAGE and esRAGE to incident coronary heart disease (CHD) and stroke in type 2 diabetic patients followed for 3.9 years in a trial of atorvastatin: the Collaborative Atorvastatin Diabetes Study (CARDS).RESEARCH DESIGN AND METHODSWe used a nested case-control design sampling all incident cases of CVD with available plasma and randomly selecting three control subjects, who were free of CVD throughout follow-up, per case. Analysis was by Cox regression with adjustment for treatment allocation and relevant covariates.RESULTSsRAGE and esRAGE were strongly correlated (ρ = 0.88) and were both higher in those with lower BMI (P < 0.001), higher adiponectin (P < 0.001), lower estimated glomerular filtration rate (P = 0.009), and white ethnicity (P < 0.001). Both sRAGE and esRAGE were associated with incident CHD events, independently of treatment allocation and the above factors; hazard ratio (HR) = 1.74 (95% CI 1.25–2.41; P = 0.002) for a doubling of the sRAGE level; HR = 1.45 (1.11–1.89; P = 0.006) for a doubling of the esRAGE level. There was no significant association with stroke; HR for sRAGE = 0.66 (0.38–1.14). Atorvastatin, 10 mg daily, did not alter sRAGE.CONCLUSIONSHigher levels of sRAGE and esRAGE are associated with incident CHD but not stroke in type 2 diabetes.

Study queStionWhat is the predicted risk of acute kidney injury after orthopaedic surgery and does it affect short term and long term survival? MethodSThe cohort comprised adults resident in the National Health Service Tayside region of Scotland who underwent orthopaedic surgery from 1 January 2005 to 31 December 2011. The model was developed in 6220 patients (two hospitals) and externally validated in 4395 patients from a third hospital. Several preoperative variables were selected for candidate predictors, based on literature, clinical expertise, and availability in the orthopaedic surgery setting. The main outcomes were the development of any severity of acute kidney injury (stages 1-3) within the first postoperative week, and 90 day, one year, and longer term survival. Study anSwer and liMitationSUsing logistic regression analysis, independent predictors of acute kidney injury were older age, male sex, diabetes, number of prescribed drugs, lower estimated glomerular filtration rate, use of angiotensin converting enzyme inhibitors or angiotensin receptor blockers, and American Society of Anesthesiologists grade. The model's predictive performance for discrimination was good (C statistic 0.74 in development cohort, 0.70 in validation cohort). Calibration was good in the development cohort and after recalibration in the validation cohort. Only the highest risks were over-predicted. Survival was worse in patients with acute kidney injury compared with those without (adjusted hazard ratio 1.53, 95% confidence interval 1.38 to 1.70). This was most noticeable in the short term (adjusted hazard ratio: 90 day 2.36, 1.94 to 2.87) and diminished over time (90 day-one year 1.40, 1.10 to 1.79; >1 year 1.28, 1.10 to 1.48). The model used routinely collected data in the orthopaedic surgery setting therefore some variables that could potentially improve predictive performance were not available. However, the readily available predictors make the model easily applicable.what thiS Study addS A preoperative risk prediction model consisting of seven predictors for acute kidney injury was developed, with good predictive performance in patients undergoing orthopaedic surgery. Survival was significantly poorer in patients even with mild (stage 1) postoperative acute kidney injury.