Can patiromer allow for intensified renin-angiotensin-aldosterone system blockade with losartan and spironolactone leading to decreased albuminuria in patients with chronic kidney disease, albuminuria and hyperkalaemia? An open-label randomised controlled trial: MorphCKD

INTRODUCTION

Chronic kidney disease (CKD) is associated with significantly increased morbidity and mortality. No specific treatment of the underlying condition is available for the majority of patients, but ACE-inhibitors (ACE-I) and angiotensin II-receptor blockers (ARB) slows progression in albuminuric CKD. Adding a mineralocorticoid receptor-antagonist (MRA) like spironolactone has an additive effect. However, renin-angiotensin-aldosterone system (RAAS)-blockade increases the risk of hyperkalaemia which is exacerbated by the presence of CKD. Thus, hyperkalaemia may prevent optimal use of RAAS-blockade in some patients.This project hypothesises that adding a potassium binder (patiromer) allows for improved RAAS-blockade including the use of MRA, thereby reducing albuminuria in patients with albuminuric CKD where full treatment is limited by hyperkalaemia.If successful, the study may lead to improved treatment of this subgroup of patients with CKD. Furthermore, the study will examine the feasibility of potassium binders in patients with CKD.

METHODS AND ANALYSIS

An open-label, randomised controlled trial including 140 patients with estimated glomerular filtration rate (eGFR) 25-60 mL/min/1.73 m², a urinary albumin/creatinine ratio (UACR) >500 mg/g (or 200 mg/g if diabetes mellitus) and a current or two previous plasma-potassium >4.5 mmol/L. Patients who develop hyperkaliaemia >5.5 mmol/L during a run-in phase, in which RAAS-blockade is intesified with the possible addition of spironolactone, are randomised to 12-month treatment with maximal tolerated ACE-I/ARB and spironolactone with or without patiromer.The primary endpoint is the difference in UACR measured at randomisation and 12 months compared between the two groups. Secondary endpoints include CKD progression, episodes of hyperkalaemia, blood pressure, eGFR, markers of cardiovascular disease, diet and quality of life.

ETHICS AND DISSEMINATION

This study is approved by The Central Denmark Region Committees on Health Research Ethics (REFNO 1-10-72-110-20) and is registered in the EudraCT database (REFNO 2020-001595-15). Results will be presented in peer-reviewed journals, at meetings and at international conferences.

Variance in cortical depth across the brain surface: Implications for transcranial stimulation of the brain

The distance between the surface of the scalp and the surface of the grey matter of the brain is a key factor in determining the effective dose of non-invasive brain stimulation for an individual person. The highly folded nature of the cortical surface means that the depth of a particular brain area is likely to vary between individuals. The question addressed here is: what is the variability of this measure of cortical depth? Ninety-four anatomical MRI images were taken from the OASIS database. For each image, the minimum distance from each point in the grey matter to the scalp surface was determined. Transforming these estimates into standard space meant that the coefficient of variation could be determined across the sample. The results indicated that depth variability is high across the cortical surface, even when taking sulcal depth into account. This was true even for the primary visual and motor areas, which are often used in setting TMS dosage. The correlation of the depth of these areas and the depth of other brain areas was low. The results suggest that dose setting of TMS based on visual or evoked potentials may offer poor reliability, and that individual brain images should be used when targeting non-primary brain areas.

Effect of Frozen Human Epidermis Storage Duration and Cryoprotectant on Barrier Function Using Two Model Compounds

Skin is commonly stored frozen and then thawed prior to use for in vitro permeation experiments. Does frozen storage of skin alter its barrier property? Numerous studies have found contradictory answers to this question. In this study, the steady-state flux and lag time of diethyl phthalate (DEP) were measured for fresh human skin and skin frozen at -85°C for 1, 2, 3, 6, 9, 12, and 18 months with 10% glycerol as a cryoprotective agent. No significant differences in steady-state flux were found between fresh and previously frozen samples (p = 0.6). For lag time, a significant (p = 0.002) difference was found among all groups, but comparisons with fresh skin were not significant. Does glycerol have a cryoprotective effect? The steady-state flux and lag time of DEP and caffeine were measured through human skin stored at -85°C for up to 12 months with and without 10% glycerol. No significant differences in steady-state flux or lag time were found between samples stored with or without glycerol for either DEP or caffeine (p ≥ 0.17). These findings support the use of frozen skin to measure the passive permeation of chemicals in studies unconcerned with viability and metabolism.

Quantitation of glucose uptake in tumors by dynamic FDG-PET has less glucose bias and lower variability when adjusted for partial saturation of glucose transport

Background

A retrospective analysis of estimates of tumor glucose uptake from 1,192 dynamic 2-deoxy-2-(¹⁸F)fluoro-D-glucose-positron-emission tomography [FDG-PET] scans showed strong correlations between blood glucose and both the uptake rate constant [K_i] and the metabolic rate of glucose [MRGluc], hindering the interpretation of PET scans acquired under conditions of altered blood glucose. We sought a method to reduce this glucose bias without increasing the between-subject or test-retest variability and did this by considering that tissue glucose transport is a saturable yet unsaturated process best described as a nonlinear function of glucose levels.

Methods

Patlak-Gjedde analysis was used to compute K_i from 30-min dynamic PET scans in tumor-bearing mice. MRGluc was calculated by factoring in the blood glucose level and a lumped constant equal to unity. Alternatively, we assumed that glucose consumption is saturable according to Michaelis-Menten kinetics and estimated a hypothetical maximum rate of glucose consumption [MRGluc^MAX] by multiplying K_i and (K_M + [glucose]), where K_M is a half-saturation Michaelis constant for glucose uptake. Results were computed for 112 separate studies of 8 to 12 scans each; test-retest statistics were measured in a suitable subset of 201 mice.

Results

A K_M value of 130 mg/dL was determined from the data based on minimizing the average correlation between blood glucose and the uptake metric. Using MRGluc^MAX resulted in the following benefits compared to using MRGluc: (1) the median correlation with blood glucose was practically zero, and yet (2) the test-retest coefficient of variation [COV] was reduced by 13.4%, and (3) the between-animal COVs were reduced by15.5%. In statistically equivalent terms, achieving the same reduction in between-animal COV while using the traditional MRGluc would require a 40% increase in sample size.

Conclusions

MRGluc appeared to overcorrect tumor FDG data for changing glucose levels. Applying partial saturation correction using MRGluc^MAX offered reduced bias, reduced variability, and potentially increased statistical power. We recommend further investigation of MRGluc^MAX in quantitative studies of tumor FDG uptake.

Baseline characteristics and statistical implications for the OECD 210 fish early-life stage chronic toxicity test

The fish toxicity assay most commonly used to establish chronic effects is the Organisation for Economic Co-operation and Development (OECD) 210, fish early-life stage test. However, the authors are not aware of any systematic analysis of the experimental design or statistical characteristics of the test since the test guideline was adopted nearly 20 years ago. Here, the authors report the results of an analysis of data compiled from OECD 210 tests conducted by industry labs. The distribution of responses observed in control treatments was analyzed, with the goal of understanding the implication of this variability on the sensitivity of the OECD 210 test guideline and providing recommendations on revised experimental design requirements of the test. Studies were confined to fathead minnows, rainbow trout, and zebrafish. Dichotomous endpoints (hatching success and posthatch survival) were examined for indications of overdispersion to evaluate whether significant chamber-to-chamber variability was present. Dichotomous and continuous (length, wet wt, dry wt) measurement endpoints were analyzed to determine minimum sample size requirements to detect differences from control responses with specified power. Results of the analysis indicated that sensitivity of the test could be improved by maximizing the number of replicate chambers per treatment concentration, increasing the acceptable level of control hatching success and larval survival compared to current levels, using wet weight measurements rather than dry weight, and focusing test efforts on species that demonstrate less variability in outcome measures. From these analyses, the authors provide evidence of the impact of expected levels of variability on the sensitivity of traditional OECD 210 studies and the implications for defining a target for future animal alternative methods for chronic toxicity testing in fish.

Bioinformatics for mass spectrometry-based metabolomics

The broad view of the state of biological systems cannot be complete without the added value of integrating proteomic and genomic data with metabolite measurement. By definition, metabolomics aims at quantifying not less than the totality of small molecules present in a biofluid, tissue, organism, or any material beyond living systems. To cope with the complexity of the task, mass spectrometry (MS) is the most promising analytical environment to fulfill increasing appetite for more accurate and larger view of the metabolome while providing sufficient data generation throughput. Bioinformatics and associated disciplines naturally play a central role in bridging the gap between fast evolving technology and domain experts. Here, we describe the strategies to translate crude MS information into features characteristics of metabolites, and resources available to guide scientists along the metabolomics pipeline. A particular emphasis is put on pragmatic solutions to interpret the outcome of metabolomics experiments at the level of signal processing, statistical treatment, and biochemical understanding.

Reproducibility, Sources of Variability, Pooling, and Sample Size: Important Considerations for the Design of High-Density Oligonucleotide Array Experiments

We have undertaken a series of experiments to examine several issues that directly affect design of gene expression studies using Affymetrix GeneChip arrays: probe-level analysis, need for technical replication, relative contribution of various sources of variability, and utility of pooling RNA from different samples. Probe-level data were analyzed by Affymetrix MAS 5.0, and three model-based methods, PM-MM and PM-only models by dChip, and the RMA model by Bioconductor, with the latter two providing the best performance. We found that replicate chips of the same RNA have limited value in reducing total variability, and for relatively highly expressed genes in this biologically homogeneous animal model of aging, about 11% of total variation is due to day effects and the remainder is approximately equally split between sample and residual sources. We also found that pooling samples is neither advantageous nor detrimental. Finally we suggest a strategy for sample size calculations using formulas appropriate when coefficients of variation are known, target effects are expressed as fold changes, and data can be assumed to be approximately lognormally distributed.

Sample-size calculation for a log-transformed outcome measure

The outcome measure of interest in clinical trials sometimes requires transformation to the logarithmic scale for analysis. This paper examines sample-size calculation for both independent groups and matched-pairs trials for log-transformed outcomes. For both types of trial, we demonstrate how the calculation can be formulated in terms of a relative treatment effect and a statement of relative variability, both specified on the original scale of measurement. For a comparison of two independent groups, the relative treatment effect is the ratio of group geometric means (or alternatively, group arithmetic means) and the coefficient of variation is used as a summary of relative variability. For a matched-pairs comparison, the appropriate relative treatment effect is the geometric mean of the within-pair ratios, and relative variability can be specified as an upper bound on within-pair ratios under a null hypothesis of the relative effect being equal to 1 (i.e., no difference). We discuss the clinical study that motivated this work and demonstrate the application of the sample-size calculation to this study.

Variability of human brain structure size: ages 4-20 years

Understanding variability of human brain structure sizes during development is important for the design and interpretation of pediatric neuroimaging studies. In this study we analyze the effects of hemisphere, sex and age on size variability of the total cerebrum, cerebellum, lateral ventricles, temporal lobe, amygdala, hippocampus, superior temporal gyrus, corpus callosum, caudate, putamen, and globus pallidus in 115 healthy children and adolescents, ages 4-20 years. Variability differed significantly across structures, with the lateral ventricles demonstrating the highest coefficient of variation and the putamen the lowest. Males varied significantly more than females in the left cerebrum and left superior temporal gyrus, whereas females varied more than males in the right caudate and right putamen. Age effects were seen in increased variability after puberty for the lateral ventricles, hippocampus and superior temporal gyrus. These variances are important determinants of minimum sample sizes required to detect group differences in both cross-sectional and longitudinal studies.