Glucocorticoid receptor gene polymorphisms associated with progression of lung disease in young patients with cystic fibrosis

<p>Abstract</p> <p>Background</p> <p>The variability in the inflammatory burden of the lung in cystic fibrosis (CF) patients together with the variable effect of glucocorticoid treatment led us to hypothesize that <it>glucocorticoid receptor </it>(<it>GR</it>) gene polymorphisms may affect glucocorticoid sensitivity in CF and, consequently, may contribute to variations in the inflammatory response.</p> <p>Methods</p> <p>We evaluated the association between four <it>GR </it>gene polymorphisms, <it>TthIII</it>, <it>ER22/23EK</it>, <it>N363S </it>and <it>BclI</it>, and disease progression in a cohort of 255 young patients with CF. Genotypes were tested for association with changes in lung function tests, infection with <it>Pseudomonas aeruginosa </it>and nutritional status by multivariable analysis.</p> <p>Results</p> <p>A significant non-corrected for multiple tests association was found between <it>BclI </it>genotypes and decline in lung function measured as the forced expiratory volume in one second (FEV₁) and the forced vital capacity (FVC). Deterioration in FEV₁and FVC was more pronounced in patients with the <it>BclI </it>GG genotype compared to the group of patients with <it>BclI </it>CG and CC genotypes (p = 0.02 and p = 0.04 respectively for the entire cohort and p = 0.01 and p = 0.02 respectively for F508del homozygous patients).</p> <p>Conclusion</p> <p>The <it>BclI </it>polymorphism may modulate the inflammatory burden in the CF lung and in this way influence progression of lung function.</p

Polymorphisms in the glucocorticoid receptor gene that modulate glucocorticoid sensitivity are associated with rheumatoid arthritis

Introduction: The glucocorticoid receptor (GR) plays an important regulatory role in the immune system. Four polymorphisms in the GR gene are associated with differences in glucocorticoid (GC) sensitivity; the minor alleles of the polymorphisms N363 S and BclI are associated with relative hypersensitivity to GCs, while those of the polymorphisms ER22/23EK and 9β are associated with relative GC resistance. Because differences in GC sensitivity may influence immune effector functions, we examined whether these polymorphisms are associated with the susceptibility to develop Rheumatoid Arthritis (RA) and RA disease severity.Methods: The presence of GR polymorphisms was assessed in healthy controls (n = 5033), and in RA patients (n = 368). A second control group (n = 532) was used for confirmation of results. In RA patients, the relationship between GR polymorphisms and disease severity was examined.Results: Carriers of the N363 S and BclI minor alleles had a lower risk of developing RA: odds ratio (OR) = 0.55 (95% confidence interval (CI) 0.32-0.96, P = 0.032) and OR = 0.73 (95% CI 0.58-0.91, P = 0.006), respectively. In contrast, 9β minor allele carriers had a higher risk of developing RA: OR = 1.26 (95% CI 1.00-1.60, P = 0.050). For ER22/23EK minor allele carriers a trend to an increased risk OR = 1.42 (95% CI 0.95-2.13, P = 0.086) was found. All ER22/23EK carriers (32/32) had erosive disease, while only 77% (259/336) of the non-carriers did (P = 0.008). In addition, ER22/23EK carriers were treated more frequently with anti-tumor necrosis factor-alpha (TNFα) therapy (P < 0.05).Conclusions: The minor alleles of the 9β and ER22/23EK polymorphisms seem to be associated with increased predisposition to develop RA. Conversely, the minor alleles of the N363 S and BclI polymorphisms are associated with reduced susceptibility to develop RA. These opposite associations suggest that constitutionally determined GC resistance may predispose to development of auto-immunity, at least in RA, and vice versa

Locomotor hyperactivity in 14-3-3Zeta KO mice is associated with dopamine transporter dysfunction

Dopamine (DA) neurotransmission requires a complex series of enzymatic reactions that are tightly linked to catecholamine exocytosis and receptor interactions on pre- and postsynaptic neurons. Regulation of dopaminergic signalling is primarily achieved through reuptake of extracellular DA by the DA transporter (DAT) on presynaptic neurons. Aberrant regulation of DA signalling, and in particular hyperactivation, has been proposed as a key insult in the presentation of schizophrenia and related neuropsychiatric disorders. We recently identified 14-3-3ζ as an essential component of neurodevelopment and a central risk factor in the schizophrenia protein interaction network. Our analysis of 14-3-3ζ-deficient mice now shows that baseline hyperactivity of knockout (KO) mice is rescued by the antipsychotic drug clozapine. 14-3-3ζ KO mice displayed enhanced locomotor hyperactivity induced by the DA releaser amphetamine. Consistent with 14-3-3ζ having a role in DA signalling, we found increased levels of DA in the striatum of 14-3-3ζ KO mice. Although 14-3-3ζ is proposed to modulate activity of the rate-limiting DA biosynthesis enzyme, tyrosine hydroxylase (TH), we were unable to identify any differences in total TH levels, TH localization or TH activation in 14-3-3ζ KO mice. Rather, our analysis identified significantly reduced levels of DAT in the absence of notable differences in RNA or protein levels of DA receptors D1–D5. Providing insight into the mechanisms by which 14-3-3ζ controls DAT stability, we found a physical association between 14-3-3ζ and DAT by co-immunoprecipitation. Taken together, our results identify a novel role for 14-3-3ζ in DA neurotransmission and provide support to the hyperdopaminergic basis of pathologies associated with schizophrenia and related disorders.H Ramshaw, X Xu, EJ Jaehne, P McCarthy, Z Greenberg, E Saleh, B McClure, J Woodcock, S Kabbara, S Wiszniak, Ting-Yi Wang, C Parish, M van den Buuse, BT Baune, A Lopez and Q Schwar

Soft-bound synaptic plasticity increases storage capacity

Accurate models of synaptic plasticity are essential to understand the adaptive properties of the nervous system and for realistic models of learning and memory. Experiments have shown that synaptic plasticity depends not only on pre- and post-synaptic activity patterns, but also on the strength of the connection itself. Namely, weaker synapses are more easily strengthened than already strong ones. This so called soft-bound plasticity automatically constrains the synaptic strengths. It is known that this has important consequences for the dynamics of plasticity and the synaptic weight distribution, but its impact on information storage is unknown. In this modeling study we introduce an information theoretic framework to analyse memory storage in an online learning setting. We show that soft-bound plasticity increases a variety of performance criteria by about 18% over hard-bound plasticity, and likely maximizes the storage capacity of synapses

Design of the ExCersion-VCI study: The effect of aerobic exercise on cerebral perfusion in patients with vascular cognitive impairment

There is evidence for a beneficial effect of aerobic exercise on cognition, but underlying mechanisms are unclear. In this study, we test the hypothesis that aerobic exercise increases cerebral blood flow (CBF) in patients with vascular cognitive impairment (VCI). This study is a multicenter single-blind randomized controlled trial among 80 patients with VCI. Most important inclusion criteria are a diagnosis of VCI with Mini-Mental State Examination ≥22 and Clinical Dementia Rating ≤0.5. Participants are randomized into an aerobic exercise group or a control group. The aerobic exercise program aims to improve cardiorespiratory fitness and takes 14 weeks, with a frequency of three times a week. Participants are provided with a bicycle ergometer at home. The control group receives two information meetings. Primary outcome measure is change in CBF. We expect this study to provide insight into the potential mechanism by which aerobic exercise improves hemodynamic status

A Comprehensive Workflow for General-Purpose Neural Modeling with Highly Configurable Neuromorphic Hardware Systems

In this paper we present a methodological framework that meets novel requirements emerging from upcoming types of accelerated and highly configurable neuromorphic hardware systems. We describe in detail a device with 45 million programmable and dynamic synapses that is currently under development, and we sketch the conceptual challenges that arise from taking this platform into operation. More specifically, we aim at the establishment of this neuromorphic system as a flexible and neuroscientifically valuable modeling tool that can be used by non-hardware-experts. We consider various functional aspects to be crucial for this purpose, and we introduce a consistent workflow with detailed descriptions of all involved modules that implement the suggested steps: The integration of the hardware interface into the simulator-independent model description language PyNN; a fully automated translation between the PyNN domain and appropriate hardware configurations; an executable specification of the future neuromorphic system that can be seamlessly integrated into this biology-to-hardware mapping process as a test bench for all software layers and possible hardware design modifications; an evaluation scheme that deploys models from a dedicated benchmark library, compares the results generated by virtual or prototype hardware devices with reference software simulations and analyzes the differences. The integration of these components into one hardware-software workflow provides an ecosystem for ongoing preparative studies that support the hardware design process and represents the basis for the maturity of the model-to-hardware mapping software. The functionality and flexibility of the latter is proven with a variety of experimental results

STDP Allows Fast Rate-Modulated Coding with Poisson-Like Spike Trains

Spike timing-dependent plasticity (STDP) has been shown to enable single neurons to detect repeatedly presented spatiotemporal spike patterns. This holds even when such patterns are embedded in equally dense random spiking activity, that is, in the absence of external reference times such as a stimulus onset. Here we demonstrate, both analytically and numerically, that STDP can also learn repeating rate-modulated patterns, which have received more experimental evidence, for example, through post-stimulus time histograms (PSTHs). Each input spike train is generated from a rate function using a stochastic sampling mechanism, chosen to be an inhomogeneous Poisson process here. Learning is feasible provided significant covarying rate modulations occur within the typical timescale of STDP (∼10–20 ms) for sufficiently many inputs (∼100 among 1000 in our simulations), a condition that is met by many experimental PSTHs. Repeated pattern presentations induce spike-time correlations that are captured by STDP. Despite imprecise input spike times and even variable spike counts, a single trained neuron robustly detects the pattern just a few milliseconds after its presentation. Therefore, temporal imprecision and Poisson-like firing variability are not an obstacle to fast temporal coding. STDP provides an appealing mechanism to learn such rate patterns, which, beyond sensory processing, may also be involved in many cognitive tasks