Regression to the Mean and Predictors of MRI Disease Activity in RRMS Placebo Cohorts - Is There a Place for Baseline-to-Treatment Studies in MS?

BackgroundGadolinium-enhancing (GD+) lesions and T2 lesions are MRI outcomes for phase-2 treatment trials in relapsing-remitting Multiple Sclerosis (RRMS). Little is known about predictors of lesion development and regression-to-the-mean, which is an important aspect in early baseline-to-treatment trials.ObjectivesTo quantify regression-to-the-mean and identify predictors of MRI lesion development in placebo cohorts.Methods21 Phase-2 and Phase-3 trials were identified by a systematic literature research. Random-effects meta-analyses were performed to estimate development of T2 and GD+ after 6 months (phase-2) or 2 years (phase-3). Predictors of lesion development were evaluated with mixed-effect meta-regression.ResultsThe mean number of GD+-lesions per scan was similar after 6 months (1.19, 95%CI: 0.87-1.51) and 2 years (1.19, 95%CI: 1.00-1.39). 39% of the patients were without new T2-lesion after 6 month and 19% after 2 years (95%CI: 12-25%). Mean number of baseline GD+-lesions was the best predictor for new lesions after 6 months.ConclusionBaseline GD-enhancing lesions predict evolution of Gd- and T2 lesions after 6 months and might be used to control for regression to the mean effects. Overall, proof-of-concept studies with a baseline to treatment design have to face a regression to 1.2 GD+lesions per scan within 6 months.     

Increasing hydrologic variability threatens depleted anadromous fish populations

Predicting effects of climate change on species and ecosystems depend on understanding responses to shifts in means (such as trends in global temperatures), but also shifts in climate variability. To evaluate potential responses of anadromous fish populations to an increasingly variable environment, we performed a hierarchical analysis of 21 Chinook salmon populations from the Pacific Northwest, examining support for changes in river flows and flow variability on population growth. More than half of the rivers analyzed have already experienced significant increases in flow variability over the last 60 years, and this study shows that this increase in variability in freshwater flows has a more negative effect than any other climate signal included in our model. Climate change models predict that this region will experience warmer winters and more variable flows, which may limit the ability of these populations to recover.     

Analysis of whole genome sequencing for the Escherichia coli O157:H7 typing phages

Background

Shiga toxin producing Escherichia coli O157 can cause severe bloody diarrhea and haemolytic uraemic syndrome. Phage typing of E. coli O157 facilitates public health surveillance and outbreak investigations, certain phage types are more likely to occupy specific niches and are associated with specific age groups and disease severity. The aim of this study was to analyse the genome sequences of 16 (fourteen T4 and two T7) E. coli O157 typing phages and to determine the genes responsible for the subtle differences in phage type profiles.

Results

The typing phages were sequenced using paired-end Illumina sequencing at The Genome Analysis Centre and the Animal Health and Veterinary Laboratories Agency and bioinformatics programs including Velvet, Brig and Easyfig were used to analyse them. A two-way Euclidian cluster analysis highlighted the associations between groups of phage types and typing phages. The analysis showed that the T7 typing phages (9 and 10) differed by only three genes and that the T4 typing phages formed three distinct groups of similar genomic sequences: Group 1 (1, 8, 11, 12 and 15, 16), Group 2 (3, 6, 7 and 13) and Group 3 (2, 4, 5 and 14). The E. coli O157 phage typing scheme exhibited a significantly modular network linked to the genetic similarity of each group showing that these groups are specialised to infect a subset of phage types.

Conclusion

Sequencing the typing phage has enabled us to identify the variable genes within each group and to determine how this corresponds to changes in phage type.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1470-z) contains supplementary material, which is available to authorized users.     

Constraints on adaptation of Escherichia coli to mixed‐resource environments increase over time

Can a population evolved in two resources reach the same fitness in both as specialist populations evolved in each of the individual resources? This question is central to theories of ecological specialization, the maintenance of genetic variation, and sympatric speciation, yet relatively few experiments have examined costs of generalism over long‐term adaptation. We tested whether selection in environments containing two resources limits a population's ability to adapt to the individual resources by comparing the fitness of replicate Escherichia coli populations evolved for 6000 generations in the presence of glucose or lactose alone (specialists), or in varying presentations of glucose and lactose together (generalists). We found that all populations had significant fitness increases in both resources, though the magnitude and rate of these increases differed. For the first 4000 generations, most generalist populations increased in fitness as quickly in the individual resources as the corresponding specialist populations. From 5000 generations, however, a widespread cost of adaptation affected all generalists, indicating a growing constraint on their abilities to adapt to two resources simultaneously. Our results indicate that costs of generalism are prevalent, but may influence evolutionary trajectories only after a period of cost‐free adaptation.     

Nonadditive Effects of Genes in Human Metabolomics

Genome-wide association studies (GWAS) are widely applied to analyze the genetic effects on phenotypes. With the availability of high-throughput technologies for metabolite measurements, GWAS successfully identified loci that affect metabolite concentrations and underlying pathways. In most GWAS, the effect of each SNP on the phenotype is assumed to be additive. Other genetic models such as recessive, dominant, or overdominant were considered only by very few studies. In contrast to this, there are theories that emphasize the relevance of nonadditive effects as a consequence of physiologic mechanisms. This might be especially important for metabolites because these intermediate phenotypes are closer to the underlying pathways than other traits or diseases. In this study we analyzed systematically nonadditive effects on a large panel of serum metabolites and all possible ratios (22,801 total) in a population-based study [Cooperative Health Research in the Region of Augsburg (KORA) F4, N = 1,785]. We applied four different 1-degree-of-freedom (1-df) tests corresponding to an additive, dominant, recessive, and overdominant trait model as well as a genotypic model with two degree-of-freedom (2-df) that allows a more general consideration of genetic effects. Twenty-three loci were found to be genome-wide significantly associated (Bonferroni corrected P ≤ 2.19 × 10⁻¹²) with at least one metabolite or ratio. For five of them, we show the evidence of nonadditive effects. We replicated 17 loci, including 3 loci with nonadditive effects, in an independent study (TwinsUK, N = 846). In conclusion, we found that most genetic effects on metabolite concentrations and ratios were indeed additive, which verifies the practice of using the additive model for analyzing SNP effects on metabolites.     

Myeloperoxidase-dependent Lipid Peroxidation Promotes the Oxidative Modification of Cytosolic Proteins in Phagocytic Neutrophils

Phagocytic neutrophils generate reactive oxygen species to kill microbes. Oxidant generation occurs within an intracellular phagosome, but diffusible species can react with the neutrophil and surrounding tissue. To investigate the extent of oxidative modification, we assessed the carbonylation of cytosolic proteins in phagocytic neutrophils. A 4-fold increase in protein carbonylation was measured within 15 min of initiating phagocytosis. Carbonylation was dependent on NADPH oxidase and myeloperoxidase activity and was inhibited by butylated hydroxytoluene and Trolox, indicating a role for myeloperoxidase-dependent lipid peroxidation. Proteomic analysis of target proteins revealed significant carbonylation of the S100A9 subunit of calprotectin, a truncated form of Hsp70, actin, and hemoglobin from contaminating erythrocytes. The addition of the reactive aldehyde 4-hydroxynonenal (HNE) caused carbonylation, and HNE-glutathione adducts were detected in the cytosol of phagocytic neutrophils. The post-translational modification of neutrophil proteins will influence the functioning and fate of these immune cells in the period following phagocytic activation, and provides a marker of neutrophil activation during infection and inflammation.