Disrupted glycosylation of lipids and proteins is a cause of neurodegeneration

Glycosyltransferases represent a large family of enzymes that catalyse the biosynthesis of oligosaccharides, polysaccharides, and glycoconjugates. A number of studies have implicated glycosyltransferases in the pathogenesis of neurodegenerative diseases but differentiating cause from effect has been difficult. We have recently discovered that mutations proximal to the substrate binding site of glycosyltransferase 8 domain containing 1 (GLT8D1) are associated with familial amyotrophic lateral sclerosis (ALS). We demonstrated that ALS-associated mutations reduce activity of the enzyme suggesting a loss-of-function mechanism that is an attractive therapeutic target. Our work is the first evidence that isolated dysfunction of a glycosyltransferase is sufficient to cause a neurodegenerative disease, but connection between neurodegeneration and genetic variation within glycosyltransferases is not new. Previous studies have identified associations between mutations in UGT8 and sporadic ALS, and between ST6GAL1 mutations and conversion of mild cognitive impairment into clinical Alzheimer’s disease. In this review we consider potential mechanisms connecting glycosyltransferase dysfunction to neurodegeneration. The most prominent candidates are ganglioside synthesis and impaired addition of O-linked β-N-acetylglucosamine (O-GlcNAc) groups to proteins important for axonal and synaptic function. Special consideration is given to examples where genetic mutations within glycosyltransferases are associated with neurodegeneration in recognition of the fact that these changes are likely to be upstream causes present from birth

Simulations of Electron Acceleration at Collisionless Shocks: The Effects of Surface Fluctuations

Energetic electrons are a common feature of interplanetary shocks and planetary bow shocks, and they are invoked as a key component of models of nonthermal radio emission, such as solar radio bursts. A simulation study is carried out of electron acceleration for high Mach number, quasi-perpendicular shocks, typical of the shocks in the solar wind. Two dimensional self-consistent hybrid shock simulations provide the electric and magnetic fields in which test particle electrons are followed. A range of different shock types, shock normal angles, and injection energies are studied. When the Mach number is low, or the simulation configuration suppresses fluctuations along the magnetic field direction, the results agree with theory assuming magnetic moment conserving reflection (or Fast Fermi acceleration), with electron energy gains of a factor only 2 - 3. For high Mach number, with a realistic simulation configuration, the shock front has a dynamic rippled character. The corresponding electron energization is radically different: Energy spectra display: (1) considerably higher maximum energies than Fast Fermi acceleration; (2) a plateau, or shallow sloped region, at intermediate energies 2 - 5 times the injection energy; (3) power law fall off with increasing energy, for both upstream and downstream particles, with a slope decreasing as the shock normal angle approaches perpendicular; (4) sustained flux levels over a broader region of shock normal angle than for adiabatic reflection. All these features are in good qualitative agreement with observations, and show that dynamic structure in the shock surface at ion scales produces effective scattering and can be responsible for making high Mach number shocks effective sites for electron acceleration.Comment: 26 pages, 12 figure

Concurrent sodium channelopathies and amyotrophic lateral sclerosis supports shared pathogenesis

Amyotrophic lateral sclerosis (ALS) is an invariably fatal adult-onset neurodegenerative disorder; approximately 10% of ALS is monogenic but all ALS exhibits significant heritability. The skeletal muscle sodium channelopathies are a group of inherited, non-dystrophic ion channel disorders caused by heterozygous point mutations in the SCN4A gene, leading to clinical manifestations of congenital myotonia, paramyotonia, and periodic paralysis syndromes. We provide clinical and genetic evidence of concurrence of these two rare disorders which implies a possible shared underlying pathophysiology in two patients. We then identify an enrichment of ALS-associated mutations in another sodium channel, SCN7A, from whole genome sequencing data of 4495 ALS patients and 1925 controls passing multiple testing correction (67 variants, p = 0.0002, Firth logistic regression). These findings suggest dysfunctional sodium channels may play a role upstream in the pathogenesis of ALS in a subset of patients, potentially opening the door to novel personalized medicine approaches

Membrane lipid raft homeostasis is directly linked to neurodegeneration

Age-associated neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS), Parkinson's disease (PD) and Alzheimer's disease (AD) are an unmet health need, with significant economic and societal implications, and an ever-increasing prevalence. Membrane lipid rafts (MLRs) are specialised plasma membrane microdomains that provide a platform for intracellular trafficking and signal transduction, particularly within neurons. Dysregulation of MLRs leads to disruption of neurotrophic signalling and excessive apoptosis which mirrors the final common pathway for neuronal death in ALS, PD and AD. Sphingomyelinase (SMase) and phospholipase (PL) enzymes process components of MLRs and therefore play central roles in MLR homeostasis and in neurotrophic signalling. We review the literature linking SMase and PL enzymes to ALS, AD and PD with particular attention to attractive therapeutic targets, where functional manipulation has been successful in preclinical studies. We propose that dysfunction of these enzymes is upstream in the pathogenesis of neurodegenerative diseases and to support this we provide new evidence that ALS risk genes are enriched with genes involved in ceramide metabolism (P=0.019, OR = 2.54, Fisher exact test). Ceramide is a product of SMase action upon sphingomyelin within MLRs, and it also has a role as a second messenger in intracellular signalling pathways important for neuronal survival. Genetic risk is necessarily upstream in a late age of onset disease such as ALS. We propose that manipulation of MLR structure and function should be a focus of future translational research seeking to ameliorate neurodegenerative disorders

NetDiff – Bayesian model selection for differential gene regulatory network inference

Differential networks allow us to better understand the changes in cellular processes that are exhibited in conditions of interest, identifying variations in gene regulation or protein interaction between, for example, cases and controls, or in response to external stimuli. Here we present a novel methodology for the inference of differential gene regulatory networks from gene expression microarray data. Specifically we apply a Bayesian model selection approach to compare models of conserved and varying network structure, and use Gaussian graphical models to represent the network structures. We apply a variational inference approach to the learning of Gaussian graphical models of gene regulatory networks, that enables us to perform Bayesian model selection that is significantly more computationally efficient than Markov Chain Monte Carlo approaches. Our method is demonstrated to be more robust than independent analysis of data from multiple conditions when applied to synthetic network data, generating fewer false positive predictions of differential edges. We demonstrate the utility of our approach on real world gene expression microarray data by applying it to existing data from amyotrophic lateral sclerosis cases with and without mutations in C9orf72, and controls, where we are able to identify differential network interactions for further investigation

Advances in the genetic classification of amyotrophic lateral sclerosis

Purpose of review Amyotrophic lateral sclerosis (ALS) is an archetypal complex disease wherein disease risk and severity are, for the majority of patients, the product of interaction between multiple genetic and environmental factors. We are in a period of unprecedented discovery with new large-scale genome-wide association study (GWAS) and accelerating discovery of risk genes. However, much of the observed heritability of ALS is undiscovered and we are not yet approaching elucidation of the total genetic architecture, which will be necessary for comprehensive disease subclassification. Recent findings We summarize recent developments and discuss the future. New machine learning models will help to address nonlinear genetic interactions. Statistical power for genetic discovery may be boosted by reducing the search-space using cell-specific epigenetic profiles and expanding our scope to include genetically correlated phenotypes. Structural variation, somatic heterogeneity and consideration of environmental modifiers represent significant challenges which will require integration of multiple technologies and a multidisciplinary approach, including clinicians, geneticists and pathologists. Summary The move away from fully penetrant Mendelian risk genes necessitates new experimental designs and new standards for validation. The challenges are significant, but the potential reward for successful disease subclassification is large-scale and effective personalized medicine

Phenome-wide Mendelian randomisation analysis identifies causal factors for age-related macular degeneration

Background: Age-related macular degeneration (AMD) is a leading cause of blindness in the industrialised world and is projected to affect >280 million people worldwide by 2040. Aiming to identify causal factors and potential therapeutic targets for this common condition, we designed and undertook a phenome-wide Mendelian randomisation (MR) study. Methods: We evaluated the effect of 4591 exposure traits on early AMD using univariable MR. Statistically significant results were explored further using: validation in an advanced AMD cohort; MR Bayesian model averaging (MR-BMA); and multivariable MR. Results: Overall, 44 traits were found to be putatively causal for early AMD in univariable analysis. Serum proteins that were found to have significant relationships with AMD included S100-A5 (odds ratio [OR] = 1.07, p-value = 6.80E−06), cathepsin F (OR = 1.10, p-value = 7.16E−05), and serine palmitoyltransferase 2 (OR = 0.86, p-value = 1.00E−03). Univariable MR analysis also supported roles for complement and immune cell traits. Although numerous lipid traits were found to be significantly related to AMD, MR-BMA suggested a driving causal role for serum sphingomyelin (marginal inclusion probability [MIP] = 0.76; model-averaged causal estimate [MACE] = 0.29). Conclusions: The results of this MR study support several putative causal factors for AMD and highlight avenues for future translational research

Exaggerated Texture and Grain Growth in a Supperplastic SiAlON

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65254/1/j.1151-2916.1992.tb05497.x.pd