A literature review of end-stage renal disease and cachexia:Understanding experience to inform evidence-based healthcare

Introduction: Cachexia is a major cause of morbidity and mortality in people who have end-stage renal disease (ESRD). The majority of research into cachexia in ESRD has focused on the biological aspects of the syndrome and potential treatment modalities. While this research is necessary, it predominately focuses on the physical impact of cachexia in ESRD. The multi-dimensional psychosocial ramifications of this syndrome have been highlighted in other end-stage illness trajectories, but have not been systematically explored in persons who have ESRD. Aim: This paper discusses why this research is necessary, alongside further studies to help define the pathophysiology of this syndrome. Conclusion: The rich insightful data gained from understanding the patients' illness experience will positively contribute to the limited knowledge base available and inform future holistic patient-centred care delivery which recognises and responds to not only the biological but also the psychosocial impact of cachexia. © 2013 European Dialysis and Transplant Nurses Association/European Renal Care Association.

Advances in joint modelling: A review of recent developments with application to the survival of end stage renal disease patients

The use of joint modelling approaches is becoming increasingly popular when an association exists between survival and longitudinal processes. Widely recognized for their gain in efficiency, joint models also offer a reduction in bias compared with naïve methods. With the increasing popularity comes a constantly expanding literature on joint modelling approaches. The aim of this paper is to give an overview of recent literature relating to joint models, in particular those that focus on the time-to-event survival process. A discussion is provided on the range of survival submodels that have been implemented in a joint modelling framework. A particular focus is given to the recent advancements in software used to build these models. Illustrated through the use of two different real-life data examples that focus on the survival of end-stage renal disease patients, the use of the JM and joineR packages within R are demonstrated. The possible future direction for this field of research is also discussed. © 2013 International Statistical Institute.

Survival in dialysis patients is different between patients with diabetes as primary renal disease and patients with diabetes as a co-morbid condition.

AIMS/HYPOTHESIS:

A previous study in Dutch dialysis patients showed no survival difference between patients with diabetes as primary renal disease and those with diabetes as a co-morbid condition. As this was not in line with our hypothesis, we aimed to verify these results in a larger international cohort of dialysis patients.

METHODS:

For the present prospective study, we used data from the European Renal Association-European Dialysis and Transplant Association (ERA-EDTA) Registry. Incident dialysis patients with data on co-morbidities (n?=?15,419) were monitored until kidney transplantation, death or end of the study period (5 years). Cox regression was performed to compare survival for patients with diabetes as primary renal disease, patients with diabetes as a co-morbid condition and non-diabetic patients.

RESULTS:

Of the study population, 3,624 patients (24%) had diabetes as primary renal disease and 1,193 (11%) had diabetes as a co-morbid condition whereas the majority had no diabetes (n?=?10,602). During follow-up, 7,584 (49%) patients died. In both groups of diabetic patients mortality was higher compared with the non-diabetic patients. Mortality was higher in patients with diabetes as primary renal disease than in patients with diabetes as a co-morbid condition, adjusted for age, sex, country and malignancy (HR 1.20, 95% CI 1.10, 1.30). An analysis stratified by dialysis modality yielded similar results.

CONCLUSIONS/INTERPRETATION:

Overall mortality was significantly higher in patients with diabetes as primary renal disease compared with those with diabetes as a co-morbid condition. This suggests that survival in diabetic dialysis patients is affected by the extent to which diabetes has induced organ damage.

CD2AP is associated with end-stage renal disease in patients with type 1 diabetes

CD2-associated protein (CD2AP) is essential for podocyte function. CD2AP mutations have been found in patients with focal segmental glomerulosclerosis, a disease histologically resembling diabetic nephropathy and often progressing to end-stage renal disease (ESRD). We hypothesised that variations in the CD2AP gene may contribute to susceptibility to glomerular injury in diabetes and investigated if single-nucleotide polymorphisms (SNPs) in CD2AP are associated with diabetic nephropathy in patients with type 1 diabetes. The discovery cohort consisted of 2,251 Finnish patients with type 1 diabetes. SNPs were selected from the HapMap database to cover the CD2AP gene. The associations between genotyped SNPs and diabetic nephropathy or ESRD were analysed with the chi-squared test and logistic regression. Three SNPs were selected for replication in cohorts from Denmark, Italy, the United Kingdom and Ireland. None of the 15 successfully genotyped SNPs were associated with diabetic nephropathy when compared to patients with normal albumin excretion rate. However, when genotype frequencies in patients with ESRD were compared with all other patients, two CD2AP SNPs, rs9369717 and rs9349417, were found to be associated with ESRD. The meta-analysis of the original and two additional European cohorts resulted in significant p values

Novel genetic susceptibility loci for diabetic end-stage renal disease identified through robust naive Bayes classification

Aims/hypothesis: Diabetic nephropathy is a major diabetic complication, and diabetes is the leading cause of end-stage renal disease (ESRD). Family studies suggest a hereditary component for diabetic nephropathy. However, only a few genes have been associated with diabetic nephropathy or ESRD in diabetic patients. Our aim was to detect novel genetic variants associated with diabetic nephropathy and ESRD. Methods: We exploited a novel algorithm, ‘Bag of Naive Bayes’, whose marker selection strategy is complementary to that of conventional genome-wide association models based on univariate association tests. The analysis was performed on a genome-wide association study of 3,464 patients with type 1 diabetes from the Finnish Diabetic Nephropathy (FinnDiane) Study and subsequently replicated with 4,263 type 1 diabetes patients from the Steno Diabetes Centre, the All Ireland-Warren 3-Genetics of Kidneys in Diabetes UK collection (UK–Republic of Ireland) and the Genetics of Kidneys in Diabetes US Study (GoKinD US). Results: Five genetic loci (WNT4/ZBTB40-rs12137135, RGMA/MCTP2-rs17709344, MAPRE1P2-rs1670754, SEMA6D/SLC24A5-rs12917114 and SIK1-rs2838302) were associated with ESRD in the FinnDiane study. An association between ESRD and rs17709344, tagging the previously identified rs12437854 and located between the RGMA and MCTP2 genes, was replicated in independent case–control cohorts. rs12917114 near SEMA6D was associated with ESRD in the replication cohorts under the genotypic model (p < 0.05), and rs12137135 upstream of WNT4 was associated with ESRD in Steno. Conclusions/interpretation: This study supports the previously identified findings on the RGMA/MCTP2 region and suggests novel susceptibility loci for ESRD. This highlights the importance of applying complementary statistical methods to detect novel genetic variants in diabetic nephropathy and, in general, in complex diseases.

Trace Element Abundance and Renal Disease

This research investigates the relationship between elevated trace elements in soils, stream sediments and stream water and the prevalence of Chronic Kidney Disease (CKD). The study uses a collaboration of datasets provided from the UK Renal Registry Report (UKRR) on patients with renal diseases requiring treatment including Renal Replacement Therapy (RRT), the soil geochemical dataset for Northern Ireland provided by the Tellus Survey, Geological Survey of Northern Ireland (GSNI) and the bioaccessibility of Potentially Toxic Elements (PTEs) from soil samples which were obtained from the Unified Barge Method (UBM). The relationship between these factors derives from the UKRR report which highlights incidence rates of renal impaired patients showing regional variation with cases of unknown aetiology. Studies suggest a potential cause of the large variation and uncertain aetiology is associated with underlying environmental factors such as the oral bioaccessibility of trace elements in the gastrointestinal tract.
As previous research indicates that long term exposure is related to environmental factors, Northern Ireland is ideally placed for this research as people traditionally live in the same location for long periods of time. Exploratory data analysis and multivariate analyses are used to examine the soil, stream sediments and stream water geochemistry data for a range of key elements including arsenic, lead, cadmium and mercury identified from a review of previous renal disease literature. The spatial prevalence of patients with long term CKD is analysed on an area basis. Further work includes cluster analysis to detect areas of low or high incidences of CKD that are significantly correlated in space, Geographical Weighted Regression (GWR) and Poisson kriging to examine locally varying relationship between elevated concentrations of PTEs and the prevalence of CKD.

Latent learning in end stage renal disease (ESRD)

Cognitive functions such as attention and memory are known to be impaired in End Stage Renal Disease (ESRD), but the sites of the neural changes underlying these impairments are uncertain. Patients and controls took part in a latent learning task, which had previously shown a dissociation between patients with Parkinson’s disease and those with medial temporal damage. ESRD patients (n=24) and age and education-matched controls (n=24) were randomly assigned to either an exposed or unexposed condition. In Phase 1 of the task, participants learned that a cue (word) on the back of a schematic head predicted that the subsequently seen face would be smiling. For the exposed (but not unexposed) condition, an additional (irrelevant) colour cue was shown during presentation. In Phase 2, a different association, between colour and facial expression, was learned. Instructions were the same for each phase: participants had to predict whether the subsequently viewed face was going to be happy or sad. No difference in error rate between the groups was found in Phase 1, suggesting that patients and controls learned at a similar rate. However, in Phase 2, a significant interaction was found between group and condition, with exposed controls performing significantly worse than unexposed (therefore demonstrating learned irrelevance). In contrast, exposed patients made a similar number of errors to unexposed in Phase 2. The pattern of results in ESRD was different from that previously found in Parkinson’s disease, suggesting a different neural origin.