Effect of ACE and AT-2 inhibitors on mortality and progression to microalbuminuria in a nested case-control study of diabetic nephropathy in diabetes mellitus type 2: results from the GENDIAN study

Meta-analysis uncovers genome-wide significant variants for rapid kidney function decline

Rapid decline of glomerular filtration rate estimated from creatinine (eGFRcrea) is associated with severe clinical endpoints. In contrast to cross-sectionally assessed eGFRcrea, the genetic basis for rapid eGFRcrea decline is largely unknown. To help define this, we meta-analyzed 42 genome-wide association studies from the Chronic Kidney Diseases Genetics Consortium and United Kingdom Biobank to identify genetic loci for rapid eGFRcrea decline. Two definitions of eGFRcrea decline were used: 3 mL/min/1.73m2/year or more ("Rapid3"; encompassing 34,874 cases, 107,090 controls) and eGFRcrea decline 25% or more and eGFRcrea under 60 mL/min/1.73m2 at follow-up among those with eGFRcrea 60 mL/min/1.73m2 or more at baseline ("CKDi25"; encompassing 19,901 cases, 175,244 controls). Seven independent variants were identified across six loci for Rapid3 and/or CKDi25: consisting of five variants at four loci with genome-wide significance (near UMOD-PDILT (2), PRKAG2, WDR72, OR2S2) and two variants among 265 known eGFRcrea variants (near GATM, LARP4B). All these loci were novel for Rapid3 and/or CKDi25 and our bioinformatic follow-up prioritized variants and genes underneath these loci. The OR2S2 locus is novel for any eGFRcrea trait including interesting candidates. For the five genome-wide significant lead variants, we found supporting effects for annual change in blood urea nitrogen or cystatin-based eGFR, but not for GATM or LARP4B. Individuals at high compared to those at low genetic risk (8-14 vs. 0-5 adverse alleles) had a 1.20-fold increased risk of acute kidney injury (95% confidence interval 1.08-1.33). Thus, our identified loci for rapid kidney function decline may help prioritize therapeutic targets and identify mechanisms and individuals at risk for sustained deterioration of kidney function.

Association of smoking and cardiometabolic parameters with albuminuria in people with type 2 diabetes mellitus: a systematic review and meta-analysis

AIMS

Smoking is a strong risk factor for albuminuria in people with type 2 diabetes mellitus (T2DM). However, it is unclear whether this sequela of smoking is brought about by its action on cardiometabolic parameters or the relationship is independent. The aim of this systematic review is to explore this relationship.

METHODS

Electronic databases on cross-sectional and prospective studies in Medline and Embase were searched from January 1946 to May 2018. Adult smokers with T2DM were included, and other types of diabetes were excluded.

RESULTS

A random effects meta-analysis of 20,056 participants from 13 studies found that the odds ratio (OR) of smokers developing albuminuria compared to non-smokers was 2.13 (95% CI 1.32, 3.45). Apart from smoking, the odds ratio of other risk factors associated with albuminuria were: age 1.24 (95% CI 0.84, 1.64), male sex 1.39 (95% CI 1.16, 1.67), duration of diabetes 1.78 (95% CI 1.32, 2.23), HbA1c 0.63 (95% CI 0.45, 0.81), SBP 6.03 (95% CI 4.10, 7.97), DBP 1.85 (95% CI 1.08, 2.62), total cholesterol 0.06 (95% CI - 0.05, 0.17) and HDL cholesterol - 0.01 (95% CI - 0.04, 0.02), triglyceride 0.22 (95% CI 0.12, 0.33) and BMI 0.40 (95% CI 0.00-0.80). When the smoking status was adjusted in a mixed effect meta-regression model, the duration of diabetes was the only statistically significant factor that influenced the prevalence of albuminuria. In smokers, each year's increase in the duration of T2DM was associated with an increased risk of albuminuria of 0.19 units (95% CI 0.07, 0.31) on the log odds scale or increased the odds approximately by 23%, compared to non-smokers. Prediction from the meta-regression model also suggested that the odds ratios of albuminuria in smokers after a diabetes duration of 9 years and 16 years were 1.53 (95% CI 1.10, 2.13) and 5.94 (95% CI 2.53, 13.95), respectively.

CONCLUSIONS

Continuing to smoke and the duration of diabetes are two strong predictors of albuminuria in smokers with T2DM. With a global surge in younger smokers developing T2DM, smoking cessation interventions at an early stage of disease trajectory should be promoted.

Chronic kidney disease: novel insights from genome-wide association studies

Chronic kidney disease (CKD) is common, affecting about 10% of the general population, and causing significant morbidity and mortality. Apart from the risk conferred by traditional cardiovascular risk factors, there is a strong genetic component. The method of a genome-wide association study (GWAS) is a powerful hypothesis-free approach to unravel this component by association analyses of CKD with several million genetic variants distributed across the genome. Since the publication of the first GWAS in 2005, this method has led to the discovery of novel loci for numerous human common diseases and phenotypes. Here, we review the recent successes of meta-analyses of GWAS on renal phenotypes. UMOD, SHROOM3, STC1, LASS2, GCKR, ALMS1, TFDP2, DAB2, SLC34A1, VEGFA, PRKAG2, PIP5K1B, ATXN2/SH2B3, DACH1, UBE2Q2, and SLC7A9 were uncovered as loci associated with estimated glomerular filtration rate (eGFR) and CKD, and CUBN as a locus for albuminuria in cross-sectional data of general population studies. However, less than 1.5% of the total variance of eGFR and albuminuria is explained by the identified variants, and the relative risk for CKD is modified by at most 20% per locus. In African Americans, much of the risk for end-stage nondiabetic kidney disease is explained by common variants in the MYH9/APOL1 locus, and in individuals of European descent, variants in HLA-DQA1 and PLA(2)R1 implicate most of the risk for idiopathic membranous nephropathy. In contrast, genetic findings in the analysis of diabetic nephropathy are inconsistent. Uncovering variants explaining more of the genetically determined variability of kidney function is hampered by the multifactorial nature of CKD and different mechanisms involved in progressive CKD stages, and by the challenges in elucidating the role of low-frequency variants. Meta-analyses with larger sample sizes and analyses of longitudinal renal phenotypes using higher-resolution genotyping data are required to uncover novel loci associated with severe renal phenotypes.

Detection of autosomal dominant polycystic kidney disease by NMR spectroscopic fingerprinting of urine

Autosomal dominant polycystic kidney disease (ADPKD) is a frequent cause of kidney failure; however, urinary biomarkers for the disease are lacking. In a step towards identifying such markers, we used multidimensional-multinuclear nuclear magnetic resonance (NMR) spectroscopy with support vector machine-based classification and analyzed urine specimens of 54 patients with ADPKD and slightly reduced estimated glomerular filtration rates. Within this cohort, 35 received medication for arterial hypertension and 19 did not. The results were compared with NMR profiles of 46 healthy volunteers, 10 ADPKD patients on hemodialysis with residual renal function, 16 kidney transplant patients, and 52 type 2 diabetic patients with chronic kidney disease. Based on the average of 51 out of 701 NMR features, we could reliably discriminate ADPKD patients with moderately advanced disease from ADPKD patients with end-stage renal disease, patients with chronic kidney disease of other etiologies, and healthy probands with an accuracy of >80%. Of the 35 patients with ADPKD receiving medication for hypertension, most showed increased excretion of proteins and also methanol. In contrast, elevated urinary methanol was not found in any of the control and other patient groups. Thus, we found that NMR fingerprinting of urine differentiates ADPKD from several other kidney diseases and individuals with normal kidney function. The diagnostic and prognostic potential of these profiles requires further evaluation.

Mining the genome for susceptibility to diabetic nephropathy: the role of large-scale studies and consortia

Approximately 30% of individuals with type 1 and type 2 diabetes develop persistent albuminuria, lose renal function, and are at increased risk for cardiovascular and other microvascular complications. Diabetes and kidney diseases rank within the top 10 causes of death in Westernized countries and cause significant morbidity. Given these observations, genetic, genomic, and proteomic investigations have been initiated to better define basic mechanisms for disease initiation and progression, to identify individuals at risk for diabetic complications, and to develop more efficacious therapies. In this review we have focused on linkage analyses of candidate genes or chromosomal regions, or coarse genome-wide scans, which have mapped either categorical (chronic kidney disease or end-stage renal disease) or quantitative kidney traits (albuminuria/proteinuria or glomerular filtration rate). Most loci identified to date have not been replicated, however, several linked chromosomal regions are concordant between independent samples, suggesting the presence of a diabetic nephropathy gene. Two genes, carnosinase (CNDP1) on 18q, and engulfment and cell motility 1 (ELMO1) on 7p14, have been identified as diabetic nephropathy susceptibility genes, but these results require authentication. The availability of patient data sets with large sample sizes, improvements in informatics, genotyping technology, and statistical methodologies should accelerate the discovery of valid diabetic nephropathy susceptibility genes.