Uromodulin concentrations are not associated with incident CKD among persons with coronary artery disease

<p>Abstract</p> <p>Background</p> <p>A common variant of the UMOD gene was linked with prevalent chronic kidney disease (CKD) in large, genomics consortia. One community-based study found that urine concentrations of the uromodulin protein forecast risk of incident CKD. This study within persons with known coronary artery disease (CAD) evaluated whether uromodulin concentrations could distinguish CKD risk.</p> <p>Methods</p> <p>In the Heart and Soul Study, the UMOD snp (12917707) was genotyped in 879 individuals with baseline creatinine clearance (CrCl) measured from a 24-hour urine collection. Uromodulin protein was measured from stored urine specimens among a subset of 120 participants, balanced by genotype. Incident CKD cases (N = 102) were defined by an initial CrCl > 70 ml/min and a 5-year follow-up CrCl <60 ml/min; controls (N = 94) were matched on age, sex, and race.</p> <p>Results</p> <p>Among 527 self-described White participants with DNA, 373 (71%) were homozygous for the dominant allele (G/G), 133 (25%) were heterozygous (G/T) and only 21 (4%) were homozygous for the minor allele (T/T). The T/T genotype had an approximately 11 ml/min higher CrCl than the other 2 groups, but this difference did not reach statistical significance (p = 0.20). The T/T genotype had significantly lower uromodulin levels than the common G/G genotype, and the G/T genotype had intermediate levels. However, uromodulin concentrations were similar between cases and controls (44 vs. 48 mg/dL, p = 0.88).</p> <p>Conclusions</p> <p>This study among a cohort of persons with established CAD found no association between urine uromodulin and incident CKD, although UMOD genotype was associated with urine uromodulin concentrations.</p

A bidirectional Mendelian randomization study supports causal effects of kidney function on blood pressure

Blood pressure and kidney function have a bidirectional relation. Hypertension has long been considered as a risk factor for kidney function decline. However, whether intensive blood pressure control could promote kidney health has been uncertain. The kidney is known to have a major role in affecting blood pressure through sodium extraction and regulating electrolyte balance. This bidirectional relation makes causal inference between these two traits difficult. Therefore, to examine the causal relations between these two traits, we performed two-sample Mendelian randomization analyses using summary statistics of large-scale genome-wide association studies. We selected genetic instruments more likely to be specific for kidney function using meta-analyses of complementary kidney function biomarkers (glomerular filtration rate estimated from serum creatinine [eGFRcr], and blood urea nitrogen from the CKDGen Consortium). Systolic and diastolic blood pressure summary statistics were from the International Consortium for Blood Pressure and UK Biobank. Significant evidence supported the causal effects of higher kidney function on lower blood pressure. Based on the mode-based Mendelian randomization method, the effect estimates for one standard deviation (SD) higher in log-transformed eGFRcr was -0.17 SD unit (95 % confidence interval: -0.09 to -0.24) in systolic blood pressure and -0.15 SD unit (95% confidence interval: -0.07 to -0.22) in diastolic blood pressure. In contrast, the causal effects of blood pressure on kidney function were not statistically significant. Thus, our results support causal effects of higher kidney function on lower blood pressure and suggest preventing kidney function decline can reduce the public health burden of hypertension

Drosophila Sperm Swim Backwards in the Female Reproductive Tract and Are Activated via TRPP2 Ion Channels

Sperm have but one purpose, to fertilize an egg. In various species including Drosophila melanogaster female sperm storage is a necessary step in the reproductive process. Amo is a homolog of the human transient receptor potential channel TRPP2 (also known as PKD2), which is mutated in autosomal dominant polycystic kidney disease. In flies Amo is required for sperm storage. Drosophila males with Amo mutations produce motile sperm that are transferred to the uterus but they do not reach the female storage organs. Therefore Amo appears to be a mediator of directed sperm motility in the female reproductive tract but the underlying mechanism is unknown.Amo exhibits a unique expression pattern during spermatogenesis. In spermatocytes, Amo is restricted to the endoplasmic reticulum (ER) whereas in mature sperm, Amo clusters at the distal tip of the sperm tail. Here we show that flagellar localization of Amo is required for sperm storage. This raised the question of how Amo at the rear end of sperm regulates forward movement into the storage organs. In order to address this question, we used in vivo imaging of dual labelled sperm to demonstrate that Drosophila sperm navigate backwards in the female reproductive tract. In addition, we show that sperm exhibit hyperactivation upon transfer to the uterus. Amo mutant sperm remain capable of reverse motility but fail to display hyperactivation and directed movement, suggesting that these functions are required for sperm storage in flies.Amo is part of a signalling complex at the leading edge of the sperm tail that modulates flagellar beating and that guides a backwards path into the storage organs. Our data support an evolutionarily conserved role for TRPP2 channels in cilia

Association of rs780094 in \u3ci\u3eGCKR\u3c/i\u3e with Metabolic Traits and Incident Diabetes and Cardiovascular Disease: The ARIC Study

Objective: The minor T-allele of rs780094 in the glucokinase regulator gene (GCKR) associates with a number of metabolic traits including higher triglyceride levels and improved glycemic regulation in study populations of mostly European ancestry. Using data from the Atherosclerosis Risk in Communities (ARIC) Study, we sought to replicate these findings, examine them in a large population-based sample of African American study participants, and to investigate independent associations with other metabolic traits in order to determine if variation in GKCR contributes to their observed clustering. In addition, we examined the association of rs780094 with incident diabetes, coronary heart disease (CHD), and stroke over up mean follow-up times of 8, 15, and 15 years, respectively. Research Design and Methods: Race-stratified analyses were conducted among 10,929 white and 3,960 black participants aged 45–64 at baseline assuming an additive genetic model and using linear and logistic regression and Cox proportional hazards models. Results: Previous findings replicated among white participants in multivariable adjusted models: the T-allele of rs780094 was associated with lower fasting glucose (p = 10-7) and insulin levels (p = 10-6), lower insulin resistance (HOMA-IR, p=10-9), less prevalent diabetes (p = 10-6), and higher CRP (p = 10-8), 2-h postprandial glucose (OGTT, p = 10-6), and triglyceride levels (p = 10-31). Moreover, the T-allele was independently associated with higher HDL cholesterol levels (p = 0.022), metabolic syndrome prevalence (p = 0.043), and lower beta-cell function measured as HOMA-B (p = 0.011). Among black participants, the T-allele was associated only with higher triglyceride levels (p = 0.004) and lower insulin levels (p = 0.002) and HOMA-IR (p = 0.013). Prospectively, the T-allele was associated with reduced incidence of diabetes (p = 10-4) among white participants, but not with incidence of CHD or stroke. Conclusions: Our findings indicate rs780094 has independent associations with multiple metabolic traits as well as incident diabetes, but not incident CHD or stroke. The magnitude of association between the SNP and most traits was of lower magnitude among African American compared to white participants

Association of Estimated Glomerular Filtration Rate and Urinary Uromodulin Concentrations with Rare Variants Identified by UMOD Gene Region Sequencing

Background: Recent genome-wide association studies (GWAS) have identified common variants in the UMOD region associated with kidney function and disease in the general population. To identify novel rare variants as well as common variants that may account for this GWAS signal, the exons and 4 kb upstream region of UMOD were sequenced. Methodology/Principal Findings Individuals (n = 485) were selected based on presence of the GWAS risk haplotype and chronic kidney disease (CKD) in the ARIC Study and on the extremes of of the UMOD gene product, uromodulin, in urine (Tamm Horsfall protein, THP) in the Framingham Heart Study (FHS). Targeted sequencing was conducted using capillary based Sanger sequencing (3730 DNA Analyzer). Variants were tested for association with THP concentrations and estimated glomerular filtration rate (eGFR), and identified non-synonymous coding variants were genotyped in up to 22,546 follow-up samples. Twenty-four and 63 variants were identified in the 285 ARIC and 200 FHS participants, respectively. In both studies combined, there were 33 common and 54 rare (MAF<0.05) variants. Five non-synonymous rare variants were identified in FHS; borderline enrichment of rare variants was found in the extremes of THP (SKAT p-value = 0.08). Only V458L was associated with THP in the FHS general-population validation sample (p = 9*10$^{−3}$, n = 2,522), but did not show direction-consistent and significant association with eGFR in both the ARIC (n = 14,635) and FHS (n = 7,520) validation samples. Pooling all non-synonymous rare variants except V458L together showed non-significant associations with THP and eGFR in the FHS validation sample. Functional studies of V458L revealed no alternations in protein trafficking. Conclusions/Significance: Multiple novel rare variants in the UMOD region were identified, but none were consistently associated with eGFR in two independent study samples. Only V458L had modest association with THP levels in the general population and thus could not account for the observed GWAS signal

Multicentric validation of proteomic biomarkers in urine specific for diabetic nephropathy

Background: Urine proteome analysis is rapidly emerging as a tool for diagnosis and prognosis in disease states. For diagnosis of diabetic nephropathy (DN), urinary proteome analysis was successfully applied in a pilot study. The validity of the previously established proteomic biomarkers with respect to the diagnostic and prognostic potential was assessed on a separate set of patients recruited at three different European centers. In this case-control study of 148 Caucasian patients with diabetes mellitus type 2 and duration &gt;= 5 years, cases of DN were defined as albuminuria &gt;300 mg/d and diabetic retinopathy (n = 66). Controls were matched for gender and diabetes duration (n = 82). Methodology/Principal Findings: Proteome analysis was performed blinded using high-resolution capillary electrophoresis coupled with mass spectrometry (CE-MS). Data were evaluated employing the previously developed model for DN. Upon unblinding, the model for DN showed 93.8% sensitivity and 91.4% specificity, with an AUC of 0.948 (95% CI 0.898-0.978). Of 65 previously identified peptides, 60 were significantly different between cases and controls of this study. In &lt;10% of cases and controls classification by proteome analysis not entirely resulted in the expected clinical outcome. Analysis of patient's subsequent clinical course revealed later progression to DN in some of the false positive classified DN control patients. Conclusions: These data provide the first independent confirmation that profiling of the urinary proteome by CE-MS can adequately identify subjects with DN, supporting the generalizability of this approach. The data further establish urinary collagen fragments as biomarkers for diabetes-induced renal damage that may serve as earlier and more specific biomarkers than the currently used urinary albumin

Variants of GCKR Affect Both β-Cell and Kidney Function in Patients With Newly Diagnosed Type 2 Diabetes: The Verona Newly Diagnosed Type 2 Diabetes Study 2

In genome-wide association studies, performed mostly in nondiabetic individuals, genetic variability of glucokinase regulatory protein (GCKR) affects type 2 diabetes-relatedphenotypes, kidney function, and risk of chronic kidney disease (CKD). We tested whether GCKR variability affects type 2 diabetes or kidney-related phenotypes in newly diagnosed type 2diabetes. In 509 GAD-negative patients with newly diagnosedtype 2 diabetes,we 1) genotyped six single nucleotide polymorphisms in GCKR genomic region: rs6717980, rs1049817, rs6547626, rs780094, rs2384628, and rs8731; 2) assessedclinical phenotypes, insulin sensitivity by the euglycemic insulin clamp, and b-cell function by state-of-the-art modeling of glucose/C-peptide curves during an oral glucose tolerance test;and 3) estimated glomerular filtration rate (eGFR) by the Modification of Diet in Renal Disease formula.The major alleles of rs6717980 and rs2384628 were associated with reduced b-cell function (P<0.05), with mutual additive effects of each variant (P<0.01). The minoralleles of rs1049817 and rs6547626 and the major allele of rs780094 were associated withreduced eGFR according to a recessive model (P<0.03), but with no mutual additive effects of the variants. Additional associations were found between rs780094 and 2-h plasma glucose(P<0.05) and rs8731 and insulin sensitivity (P<0.05) and triglycerides (P<0.05). Our findings are compatible with the idea that GCKR variability may play a pathogenetic role in both type 2 diabetes and CKD. Genotyping GCKR in patients withnewly diagnosed type 2 diabetes might help in identifying patients at high risk for metabolic derangements or CKD

HbA1c as a risk factor for heart failure in persons with diabetes: the Atherosclerosis Risk in Communities (ARIC) study

Heart failure (HF) incidence in diabetes in both the presence and absence of CHD is rising. Prospective population-based studies can help describe the relationship between HbA1c, a measure of glycaemia control, and HF risk

Genetic polymorphisms located in genes related to immune and inflammatory processes are associated with end-stage renal disease: a preliminary study

Background Chronic kidney disease progression has been linked to pro-inflammatory cytokines and markers of inflammation. These markers are also elevated in end-stage renal disease (ESRD), which constitutes a serious public health problem. Objective To investigate whether single nucleotide polymorphisms (SNPs) located in genes related to immune and inflammatory processes, could be associated with ESRD development. Design and methods A retrospective case-control study was carried out on 276 patients with ESRD and 288 control subjects. Forty-eight SNPs were genotyped via SNPlex platform. Logistic regression was used to assess the relationship between each sigle polymorphism and the development of ESRD. Results Four polymorphisms showed association with ESRD: rs1801275 in the interleukin 4 receptor (IL4R) gene (OR: 0.66 (95%CI=0.46-0.95); p=0.025; overdominant model), rs4586 in chemokine (C-C motif) ligand 2 (CCL2) gene (OR: 0.70 (95%CI=0.54-0.90); p=0.005; additive model), rs301640 located in an intergenic binding site for signal transducer and activator of transcription 4 (STAT4) (OR: 1.82 (95%CI=1.17-2.83); p=0.006; additive model) and rs7830 in the nitric oxide synthase 3 (NOS3) gene (OR: 1.31 (95%CI=1.01-1.71); p=0.043; additive model). After adjusting for multiple testing, results lost significance. Conclusion Our preliminary data suggest that four genetic polymorphisms located in genes related to inflammation and immune processes could help to predict the risk of developing ESRD.This work was supported by grants from Instituto de Salud Carlos III (Ref: PI08/0738 and PI11/00245) to SR and Junta de Castilla y Leon (Ref: GRS 234/A/08) to ET. 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Using multiple measures for quantitative trait association analyses: application to estimated glomerular filtration rate

Studies of multiple measures of a quantitative trait can have greater precision and thus statistical power compared to single measure studies, but this has rarely been studied in the relation to quantitative trait measurement error models in genetic association studies. Using estimated glomerular filtration rate (eGFR), a quantitative measure of kidney function, as an example we constructed measurement error models of a quantitative trait with systematic and random error components. We then examined the effects on precision of the parameter estimate between genetic loci and eGFR resulting from varying the correlation and contribution of the error components. We also compared the empirical results from 3 genome-wide association studies (GWAS) of kidney function in 9049 European Americans: a single measure, a 3-measure model of the same biomarker of kidney function, and a 6-measure model of different biomarkers of kidney function. Simulations showed that given the same amount of overall errors, inclusion of measures with less correlated systematic errors led to greater gain in precision. The empirical GWAS results confirmed that both the 3- and 6-measure models detected more eGFR-associated genomic loci with stronger statistical association than the single-measure model despite some heterogeneity among the measures. Multiple measures of a quantitative trait can increase the statistical power of a study without additional participant recruitment. However, careful attention must be paid to the correlation of systematic errors and inconsistent associations when different biomarkers or methods are used to measure the quantitative trait