Emerging risk factors and markers of chronic kidney disease progression

Risk of chronic kidney disease in patients with non-alcoholic fatty liver disease: is there a link?

Non-alcoholic fatty liver disease (NAFLD) has emerged as a growing public health problem worldwide. Increasing recognition of the importance of NAFLD and its association with the features of the metabolic syndrome has stimulated an interest in its putative role in the development and progression of chronic kidney disease (CKD). Accumulating evidence suggests that NAFLD and CKD share many important cardio-metabolic risk factors and common pathogenetic mechanisms and that NAFLD is associated with an increased prevalence and incidence of CKD. This association appears to be independent of obesity, hypertension, and other potentially confounding factors, and it occurs both in patients without diabetes and in those with diabetes. Although further research is needed to establish a definitive conclusion, these observations raise the possibility that NAFLD is not only a marker of CKD but also might play a part in the pathogenesis of CKD, possibly through the systemic release of several pro-inflammatory/pro-coagulant mediators from the steatotic/inflamed liver or through the contribution of NAFLD itself to insulin resistance and atherogenic dyslipidemia. However, given the heterogeneity and small number of observational longitudinal studies, further research is urgently required to corroborate the prognostic significance of NAFLD for the incidence of CKD, and to further elucidate the complex and intertwined mechanisms that link NAFLD and CKD. If confirmed in future large-scale prospective studies, the potential adverse impact of NAFLD on kidney disease progression will deserve particular attention, especially with respect to the implications for screening and surveillance strategies in the growing number of patients with NAFLD.

Acute kidney injury in childhood: should we be worried about progression to CKD?

While emerging evidence indicates that the incidence of both acute kidney injury (AKI) and chronic kidney disease (CKD) in children is rising and that the etiologies are dramatically changing, relatively little is currently known regarding the potential for transition from AKI to CKD. Major barriers to assessing for a potential AKI to CKD link have included lack of a standard pediatric AKI definition, narrow focus only on children with AKI who receive renal replacement therapy, and reliance on serum creatinine as the main biomarker to detect and diagnose AKI and CKD. Recent data have validated a multi-dimensional AKI classification system for children and have suggested chronic kidney sequelae in pediatric populations with AKI or at risk for AKI. In addition, a number of novel AKI biomarkers are being rigorously validated as early indicators of incipient CKD. Our goals for this article are to (1) review the recent changes in pediatric AKI and CKD epidemiology, (2) explore the evidence for a potential AKI to CKD link, and (3) propose new clinical and research paradigms to better elucidate the progression from AKI to CKD.

The association of mid-regional pro-adrenomedullin and mid-regional pro-atrial natriuretic peptide with mortality in an incident dialysis cohort

High levels of the plasma peptides mid-regional pro-adrenomedullin (MR-proADM) and mid-regional pro-atrial natriuretic peptide (MR-proANP) are associated with clinical outcomes in the general population. Data in patients with chronic kidney disease are sparse. We therefore investigated the association of MR-proANP and MR-proADM levels with all-cause and cardiovascular (CV) mortality, CV events and peripheral arterial disease in 201 incident dialysis patients of the INVOR-Study prospectively followed for a period of up to more than 7 years. The overall mortality rate was 43%, thereof 43% due to CV events. Both baseline MR-proANP and MR-proADM were associated with higher risk of all-cause (HR = 1.44, p = 0.001 and HR = 1.32, p = 0.002, respectively) and CV mortality (HR = 1.75, p<0.001 and HR = 1.41, p = 0.007, respectively) after adjustment for age, sex, previous CV events, diabetes mellitus and time-dependent type of renal replacement therapy. We then stratified patients in high risk (both peptides in the upper tertile), intermediate risk (only one of the two peptides in the upper tertile) and low risk (none in the upper tertile). Although demographic, clinical and laboratory variables were similar among the intermediate and high risk group, to be with both parameters in the upper tertile was associated with a 3-fold higher risk for all-cause (HR = 2.87, p<0.001) and CV mortality (HR = 3.58, p = 0.001). In summary, among incident dialysis patients MR-proANP and MR-proADM were shown to be associated with all-cause and CV mortality, with the highest risk when both parameters were in the upper tertiles.

The use of targeted biomarkers for chronic kidney disease

There is a paucity of sensitive and specific biomarkers for the early prediction of CKD progression. The recent application of innovative technologies such as functional genomics, proteomics, and biofluid profiling has uncovered several new candidates that are emerging as predictive biomarkers of CKD. The most promising among these include urinary proteins such as neutrophil gelatinase-associated lipocalin, kidney injury molecule-1, and liver-type fatty acid binding protein. In addition, an improved understanding of the complex pathophysiologic processes underlying CKD progression has also provided discriminatory biomarkers of CKD progression that are being actively evaluated. Candidates included in this category are plasma proteins such as asymmetric dimethylarginine, adiponectin, apolipoprotein A-IV, fibroblast growth factor 23, neutrophil gelatinase-associated lipocalin, and the natriuretic peptides, as well as urinary N-acetyl-β-d-glucosaminidase. This review represents a critical appraisal of the current status of these emerging CKD biomarkers. Currently, none of these are ready for routine clinical use. Additional large, multicenter prospective studies are needed to validate the biomarkers, identify thresholds and cut-offs for prediction of CKD progression and adverse events, assess the effects of confounding variables, and establish the ideal assays.

Lost in the space of bioinformatic tools: a constantly updated survival guide for genetic epidemiology. The GenEpi Toolbox

Genome-wide association studies (GWASs) led to impressive advances in the elucidation of genetic factors underlying complex phenotypes and diseases. However, the ability of GWAS to identify new susceptibility loci in a hypothesis-free approach requires tools to quickly retrieve comprehensive information about a genomic region and analyze the potential effects of coding and non-coding SNPs in a candidate gene region. Furthermore, once a candidate region is chosen for resequencing and fine-mapping studies, the identification of several rare mutations is likely and requires strong bioinformatic support to properly evaluate and prioritize the found mutations for further analysis. Due to the variety of regulatory layers that can be affected by a mutation, a comprehensive in-silico evaluation of candidate SNPs can be a demanding and very time-consuming task. Although many bioinformatic tools that significantly simplify this task were made available in the last years, their utility is often still unknown to researches not intensively involved in bioinformatics. We present a comprehensive guide of 64 tools and databases to bioinformatically analyze gene regions of interest to predict SNP effects. In addition, we discuss tools to perform data mining of large genetic regions, predict the presence of regulatory elements, make in-silico evaluations of SNPs effects and address issues ranging from interactome analysis to graphically annotated proteins sequences. Finally, we exemplify the use of these tools by applying them to hits of a recently performed GWAS. Taken together a combination of the discussed tools are summarized and constantly updated in the web-based "GenEpi Toolbox" (http://genepi_toolbox.i-med.ac.at) and can help to get a glimpse at the potential functional relevance of both large genetic regions and single nucleotide mutations which might help to prioritize the next steps.