Spinocerebellar ataxia 27B: episodic symptoms and acetazolamide response in 34 patients

Ashton C et al report a retrospective multi-centre cohort of 34 patients from Canada, France, Austria and Australia with spinocerebellar ataxia 27B, describing the common feature of episodic ataxia and other episodic features, as well as the inefficacy of acetazolamide in these patients

Frequency of GAA-FGF14 Ataxia in a Large Cohort of Brazilian Patients With Unsolved Adult-Onset Cerebellar Ataxia

OBJECTIVES: Intronic FGF14 GAA repeat expansions have recently been found to be a common cause of hereditary ataxia (GAA-FGF14 ataxia; SCA27B). The global epidemiology and regional prevalence of this newly reported disorder remain to be established. In this study, we investigated the frequency of GAA-FGF14 ataxia in a large cohort of Brazilian patients with unsolved adult-onset ataxia. METHODS: We recruited 93 index patients with genetically unsolved adult-onset ataxia despite extensive genetic investigation and genotyped the FGF14 repeat locus. Patients were recruited across 4 different regions of Brazil. RESULTS: Of the 93 index patients, 8 (9%) carried an FGF14 (GAA)≥250 expansion. The expansion was also identified in 1 affected relative. Seven patients were of European descent, 1 was of African descent, and 1was of admixed American ancestry. One patient carrying a (GAA)376 expansion developed ataxia at age 28 years, confirming that GAA-FGF14 ataxia can occur before the age of 30 years. One patient displayed episodic symptoms, while none had downbeat nystagmus. Cerebellar atrophy was observed on brain MRI in 7 of 8 patients (87%). DISCUSSION: Our results suggest that GAA-FGF14 ataxia is a common cause of adult-onset ataxia in the Brazilian population, although larger studies are needed to fully define its epidemiology

Beyond degree and betweenness centrality: Alternative topological measures to predict viral targets

<div><p>The availability of large-scale screens of host-virus interaction interfaces enabled the topological analysis of viral protein targets of the host. In particular, host proteins that bind viral proteins are generally hubs and proteins with high betweenness centrality. Recently, other topological measures were introduced that a virus may tap to infect a host cell. Utilizing experimentally determined sets of human protein targets from Herpes, Hepatitis, HIV and Influenza, we pooled molecular interactions between proteins from different pathway databases. Apart from a protein’s degree and betweenness centrality, we considered a protein’s pathway participation, ability to topologically control a network and protein PageRank index. In particular, we found that proteins with increasing values of such measures tend to accumulate viral targets and distinguish viral targets from non-targets. Furthermore, all such topological measures strongly correlate with the occurrence of a given protein in different pathways. Building a random forest classifier that is based on such topological measures, we found that protein PageRank index had the highest impact on the classification of viral (non-)targets while proteins' ability to topologically control an interaction network played the least important role.</p></div

Can Chromatin Accessibility be Exploited for Axon Regeneration?

Several studies have demonstrated that the intrinsic ability of neurons to regenerate their axons can be stimulated by maneuvers that favor the open state of chromatin, such as inhibiting histone deacetylase activity or increasing histone acetyltransferase activity. Taken together, these experiments suggest that axon regenerative ability can be increased by promoting chromatin accessibility. In this article, we assess the direct evidence in the literature for this hypothesis and re-examine other axon regeneration-promoting manipulations to see if they provide additional support. We find that several interventions known to enhance intrinsic axonal growth capability also increase chromatin accessibility. Although the support for this correlation is strong in the literature, we conclude with a word of caution about therapeutics attempting to exploit this relationship

Enrichment of viral targets in sets of hubs and bottleneck nodes.

<p><b>(A)</b> Defining the top 20% of most connected proteins as hubs, we determined the enrichment of targets of Hepatitis, Herpes, HIV, Influenza and other viruses in such sets. Randomly sampling sets of targeted proteins 10,000 times, we observed that targets were significantly enriched in the set of hubs and <i>vice versa</i> (P<10⁻⁴). In <b>(B)</b>, we defined the top 20% of proteins with highest betweeness as bottleneck nodes. Randomly sampling sets of targeted proteins 10,000 times, we found that bottleneck protein preferably were targeted by viruses while the opposite held for non-bottleneck proteins (P<10⁻⁴).</p

A network biology approach to unraveling inherited axonopathies

Abstract Inherited axonopathies represent a spectrum of disorders unified by the common pathological mechanism of length-dependent axonal degeneration. Progressive axonal degeneration can lead to both Charcot-Marie-Tooth type 2 (CMT2) and Hereditary Spastic Paraplegia (HSP) depending on the affected neurons: peripheral motor and sensory nerves or central nervous system axons of the corticospinal tract and dorsal columns, respectively. Inherited axonopathies display an extreme degree of genetic heterogeneity of Mendelian high-penetrance genes. High locus heterogeneity is potentially advantageous to deciphering disease etiology by providing avenues to explore biological pathways in an unbiased fashion. Here, we investigate ‘gene modules’ in inherited axonopathies through a network-based analysis of the Human Integrated Protein-Protein Interaction rEference (HIPPIE) database. We demonstrate that CMT2 and HSP disease proteins are significantly more connected than randomly expected. We define these connected disease proteins as ‘proto-modules’ and show the topological relationship of these proto-modules by evaluating their overlap through a shortest-path based measurement. In particular, we observe that the CMT2 and HSP proto-modules significantly overlapped, demonstrating a shared genetic etiology. Comparison of both modules with other diseases revealed an overlapping relationship between HSP and hereditary ataxia and between CMT2 + HSP and hereditary ataxia. We then use the DIseAse Module Detection (DIAMOnD) algorithm to expand the proto-modules into comprehensive disease modules. Analysis of disease modules thus obtained reveals an enrichment of ribosomal proteins and pathways likely central to inherited axonopathy pathogenesis, including protein processing in the endoplasmic reticulum, spliceosome, and mRNA processing. Furthermore, we determine pathways specific to each axonopathy by analyzing the difference of the axonopathy modules. CMT2-specific pathways include glycolysis and gluconeogenesis-related processes, while HSP-specific pathways include processes involved in viral infection response. Unbiased characterization of inherited axonopathy disease modules will provide novel candidate disease genes, improve interpretation of candidate genes identified through patient data, and guide therapy development

Prediction of viral targets.

<p><b>(A)</b> The heatmap indicated Pearson correlation values between the distributions of degree, betweenness centrality, number of pathways a protein is involved in, protein PageRank index and indispensability of a protein. Notably, degree, protein PageRank, betweenness centrality and appearance in pathways appeared best correlated while indispensability of proteins showed lowest levels of correlation with other topological measures. <b>(B)</b> Considering target sets of Hepatitis, Herpes, HIV, Influenza and other viruses, we randomly sampled sets of non-targeted proteins of equal size. Determining the area under the ROC curves (AUC), we observed that protein PageRank index and pathway participation of a protein allowed the most thorough classification of (non-)targets. <b>(C)</b> As a corollary, we utilized all five topological measures to predict viral targets using a random forest. We found that protein PageRank had the highest impact on the classification process, a result that was independent of the underlying virus. In <b>(D)</b>, we randomly sampled sets of non-targeted proteins 1,000 times that were equal in size to the set of HIV targets and determined the area under the ROC curve (AUC) of the classification process with a random forest. In particular, we predicted if a protein was (not) targeted as a function of the three most (protein PageRank index, degree and pathway appearance) and least important topological features (betweenness centrality, pathway appearance, control). Notably, the distributions of AUC values thus obtained were statistically significant (Student’s t-test, P < 10⁻²⁰), suggesting that most important features allowed a significantly better classification result.</p

Network controllers and proteins with high protein page rank are enriched with viral targets.

<p>In <b>(A)</b> we determined indispensable, neutral and dispensable proteins in the underlying protein interaction network. Randomizing such sets 10,000 times, we observed that proteins that are indispensable for the control of the underlying network preferably occurred in an increasing number of pathways. In turn, we found the opposite for dispensable proteins. <b>(B)</b> Randomizing sets of proteins that are targeted by Hepatitis, Herpes, HIV, Influenza and other viruses 10,000 times, we observed that indispensable proteins are preferably targeted by viruses (P<10⁻⁴) while the opposite held for dispensable nodes. <b>(C)</b> Randomizing the set of top PageRank proteins, we determined their enrichment in sets of indispensable, neutral and dispensable proteins. We observed that indispensable and neutral nodes significantly accumulated top PageRank proteins. In the inset, we observed that proteins in an increasing number of pathways were enriched with top PageRank proteins. <b>(D)</b> Randomizing sets of targets of Hepatitis, Herpes, HIV, Influenza and other viruses 10,000 times we observed that proteins with highest protein PageRank were significantly targeted (P<10⁻⁴).</p

Computational Identification of Kinases That Control Axon Growth in Mouse

The determination of signaling pathways and transcriptional networks that control various biological processes is a major challenge from both basic science and translational medicine perspectives. Because such analysis can point to critical disease driver nodes to target for therapeutic purposes, we combined data from phenotypic screening experiments and gene expression studies of mouse neurons to determine information flow through a molecular interaction network using a network propagation approach. We hypothesized that differences in information flow between control and injured conditions prioritize relevant driver nodes that cause this state change. Identifying paths likely taken from potential source nodes to a set of transcription factors (TFs), called sinks, we found that kinases are enriched among source genes sending significantly different amounts of information to TFs in an axonal injury model. Additionally, TFs found to be differentially active during axon growth were enriched in the set of sink genes that received significantly altered amounts of information from source genes. Notably, such enrichment levels hold even when restricting the set of source genes to only those kinases observed to support or hamper neurite growth. That way, we found a set of 71 source genes that send significantly different levels of information to axon growth-relevant TFs. We analyzed their information flow changes in response to axonal injury and their influences on TFs predicted to facilitate or antagonize axon growth. Finally, we drew a network diagram of the interactions and changes in information flow between these source genes and their axon growth-relevant sink TFs