Serum Neurofilaments in Motor Neuron Disease and Their Utility in Differentiating ALS, PMA and PLS.

Neurofilament levels are elevated in many neurodegenerative diseases and have shown promise as diagnostic and prognostic biomarkers in Amyotrophic Lateral Sclerosis (ALS), the most common form of Motor Neuron Disease (MND). This study assesses serum neurofilament light (NFL) and neurofilament heavy (NFH) chain concentrations in patients with ALS, other variants of motor neuron disease such as Progressive Muscular Atrophy (PMA) and Primary Lateral Sclerosis (PLS), and a range of other neurological diseases. It aims to evaluate the use of NFL and NFH to differentiate these conditions and for the prognosis of MND disease progression. NFL and NFH levels were quantified using electrochemiluminescence immunoassays (ECLIA). Both were elevated in 47 patients with MND compared to 34 patients with other neurological diseases and 33 healthy controls. NFL was able to differentiate patients with MND from the other groups with a Receiver Operating Characteristic (ROC) curve area under the curve (AUC) of 0.90 (p < 0.001). NFL correlated with the rate of disease progression in MND (rho 0.758, p < 0.001) and with the ALS Functional Rating Scale (rho -0.335, p = 0.021). NFL levels were higher in patients with ALS compared to both PMA (p = 0.032) and PLS (p = 0.012) and were able to distinguish ALS from both PMA and PLS with a ROC curve AUC of 0.767 (p = 0.005). These findings support the use of serum NFL to help diagnose and differentiate types of MND, in addition to providing prognostic information to patients and their families.

Genome-Wide Gene-Set Analysis Identifies Molecular Mechanisms Associated with ALS.

Amyotrophic lateral sclerosis (ALS) is a fatal late-onset motor neuron disease characterized by the loss of the upper and lower motor neurons. Our understanding of the molecular basis of ALS pathology remains elusive, complicating the development of efficient treatment. Gene-set analyses of genome-wide data have offered insight into the biological processes and pathways of complex diseases and can suggest new hypotheses regarding causal mechanisms. Our aim in this study was to identify and explore biological pathways and other gene sets having genomic association to ALS. Two cohorts of genomic data from the dbGaP repository were combined: (a) the largest available ALS individual-level genotype dataset (N = 12,319), and (b) a similarly sized control cohort (N = 13,210). Following comprehensive quality control pipelines, imputation and meta-analysis, we assembled a large European descent ALS-control cohort of 9244 ALS cases and 12,795 healthy controls represented by genetic variants of 19,242 genes. Multi-marker analysis of genomic annotation (MAGMA) gene-set analysis was applied to an extensive collection of 31,454 gene sets from the molecular signatures database (MSigDB). Statistically significant associations were observed for gene sets related to immune response, apoptosis, lipid metabolism, neuron differentiation, muscle cell function, synaptic plasticity and development. We also report novel interactions between gene sets, suggestive of mechanistic overlaps. A manual meta-categorization and enrichment mapping approach is used to explore the overlap of gene membership between significant gene sets, revealing a number of shared mechanisms.

HGCA2.0: An RNA-Seq Based Webtool for Gene Coexpression Analysis in Homo sapiens.

Genes with similar expression patterns in a set of diverse samples may be considered coexpressed. Human Gene Coexpression Analysis 2.0 (HGCA2.0) is a webtool which studies the global coexpression landscape of human genes. The website is based on the hierarchical clustering of 55,431 Homo sapiens genes based on a large-scale coexpression analysis of 3500 GTEx bulk RNA-Seq samples of healthy individuals, which were selected as the best representative samples of each tissue type. HGCA2.0 presents subclades of coexpressed genes to a gene of interest, and performs various built-in gene term enrichment analyses on the coexpressed genes, including gene ontologies, biological pathways, protein families, and diseases, while also being unique in revealing enriched transcription factors driving coexpression. HGCA2.0 has been successful in identifying not only genes with ubiquitous expression patterns, but also tissue-specific genes. Benchmarking showed that HGCA2.0 belongs to the top performing coexpression webtools, as shown by STRING analysis. HGCA2.0 creates working hypotheses for the discovery of gene partners or common biological processes that can be experimentally validated. It offers a simple and intuitive website design and user interface, as well as an API endpoint.

The Cellular and Molecular Signature of ALS in Muscle.

Amyotrophic lateral sclerosis is a disease affecting upper and lower motor neurons. Although motor neuron death is the core event of ALS pathology, it is increasingly recognized that other tissues and cell types are affected in the disease, making potentially major contributions to the occurrence and progression of pathology. We review here the known cellular and molecular characteristics of muscle tissue affected by ALS. Evidence of toxicity in skeletal muscle tissue is considered, including metabolic dysfunctions, impaired proteostasis, and deficits in muscle regeneration and RNA metabolism. The role of muscle as a secretory organ, and effects on the skeletal muscle secretome are also covered, including the increase in secretion of toxic factors or decrease in essential factors that have consequences for neuronal function and survival.

Genome-Wide Gene-Set Analysis Approaches in Amyotrophic Lateral Sclerosis.

The rapid increase in the number of genetic variants identified to be associated with Amyotrophic Lateral Sclerosis (ALS) through genome-wide association studies (GWAS) has created an emerging need to understand the functional pathways that are implicated in the pathology of ALS. Gene-set analysis (GSA) is a powerful method that can provide insight into the associated biological pathways, determining the joint effect of multiple genetic markers. The main contribution of this review is the collection of ALS GSA studies that employ GWAS or individual-based genotype data, investigating their methodology and results related to ALS-associated molecular pathways. Furthermore, the limitations in standard single-gene analyses are summarized, highlighting the power of gene-set analysis, and a brief overview of the statistical properties of gene-set analysis and related concepts is provided. The main aims of this review are to investigate the reproducibility of the collected studies and identify their strengths and limitations, in order to enhance the experimental design and therefore the quality of the results of future studies, deepening our understanding of this devastating disease.

The Role of Sphingomyelin and Ceramide in Motor Neuron Diseases.

Amyotrophic Lateral Sclerosis (ALS), Spinal Bulbar Muscular Atrophy (SBMA), and Spinal Muscular Atrophy (SMA) are motor neuron diseases (MNDs) characterised by progressive motor neuron degeneration, weakness and muscular atrophy. Lipid dysregulation is well recognised in each of these conditions and occurs prior to neurodegeneration. Several lipid markers have been shown to predict prognosis in ALS. Sphingolipids are complex lipids enriched in the central nervous system and are integral to key cellular functions including membrane stability and signalling pathways, as well as being mediators of neuroinflammation and neurodegeneration. This review highlights the metabolism of sphingomyelin (SM), the most abundant sphingolipid, and of its metabolite ceramide, and its role in the pathophysiology of neurodegeneration, focusing on MNDs. We also review published lipidomic studies in MNDs. In the 13 studies of patients with ALS, 12 demonstrated upregulation of multiple SM species and 6 demonstrated upregulation of ceramides. SM species also correlated with markers of clinical progression in five of six studies. These data highlight the potential use of SM and ceramide as biomarkers in ALS. Finally, we review potential therapeutic strategies for targeting sphingolipid metabolism in neurodegeneration.

The Neurotoxicity of Vesicles Secreted by ALS Patient Myotubes Is Specific to Exosome-Like and Not Larger Subtypes.

Extracellular vesicles can mediate communication between tissues, affecting the physiological conditions of recipient cells. They are increasingly investigated in Amyotrophic Lateral Sclerosis, the most common form of Motor Neurone Disease, as transporters of misfolded proteins including SOD1, FUS, TDP43, or other neurotoxic elements, such as the dipeptide repeats resulting from C9orf72 expansions. EVs are classified based on their biogenesis and size and can be separated by differential centrifugation. They include exosomes, released by the fusion of multivesicular bodies with the plasma membrane, and ectosomes, also known as microvesicles or microparticles, resulting from budding or pinching of the plasma membrane. In the current study, EVs were obtained from the myotube cell culture medium of ALS patients or healthy controls. EVs of two different sizes, separating at 20,000 or 100,000 g, were then compared in terms of their effects on recipient motor neurons, astrocytes, and myotubes. Compared to untreated cells, the smaller, exosome-like vesicles of ALS patients reduced the survival of motor neurons by 31% and of myotubes by 18%, decreased neurite length and branching, and increased the proportion of stellate astrocytes, whereas neither those of healthy subjects, nor larger EVs of ALS or healthy subjects, had such effects.

Muscle cells of sporadic amyotrophic lateral sclerosis patients secrete neurotoxic vesicles.

BACKGROUND: The cause of the motor neuron (MN) death that drives terminal pathology in amyotrophic lateral sclerosis (ALS) remains unknown, and it is thought that the cellular environment of the MN may play a key role in MN survival. Several lines of evidence implicate vesicles in ALS, including that extracellular vesicles may carry toxic elements from astrocytes towards MNs, and that pathological proteins have been identified in circulating extracellular vesicles of sporadic ALS patients. Because MN degeneration at the neuromuscular junction is a feature of ALS, and muscle is a vesicle-secretory tissue, we hypothesized that muscle vesicles may be involved in ALS pathology. METHODS: Sporadic ALS patients were confirmed to be ALS according to El Escorial criteria and were genotyped to test for classic gene mutations associated with ALS, and physical function was assessed using the ALSFRS-R score. Muscle biopsies of either mildly affected deltoids of ALS patients (n = 27) or deltoids of aged-matched healthy subjects (n = 30) were used for extraction of muscle stem cells, to perform immunohistology, or for electron microscopy. Muscle stem cells were characterized by immunostaining, RT-qPCR, and transcriptomic analysis. Secreted muscle vesicles were characterized by proteomic analysis, Western blot, NanoSight, and electron microscopy. The effects of muscle vesicles isolated from the culture medium of ALS and healthy myotubes were tested on healthy human-derived iPSC MNs and on healthy human myotubes, with untreated cells used as controls. RESULTS: An accumulation of multivesicular bodies was observed in muscle biopsies of sporadic ALS patients by immunostaining and electron microscopy. Study of muscle biopsies and biopsy-derived denervation-naïve differentiated muscle stem cells (myotubes) revealed a consistent disease signature in ALS myotubes, including intracellular accumulation of exosome-like vesicles and disruption of RNA-processing. Compared with vesicles from healthy control myotubes, when administered to healthy MNs the vesicles of ALS myotubes induced shortened, less branched neurites, cell death, and disrupted localization of RNA and RNA-processing proteins. The RNA-processing protein FUS and a majority of its binding partners were present in ALS muscle vesicles, and toxicity was dependent on the expression level of FUS in recipient cells. Toxicity to recipient MNs was abolished by anti-CD63 immuno-blocking of vesicle uptake. CONCLUSIONS: ALS muscle vesicles are shown to be toxic to MNs, which establishes the skeletal muscle as a potential source of vesicle-mediated toxicity in ALS.

Extracellular Vesicles in Amyotrophic Lateral Sclerosis.

Amyotrophic Lateral Sclerosis is a progressive neurodegenerative disease and is the most common adult motor neuron disease. The disease pathogenesis is complex with the perturbation of multiple pathways proposed, including mitochondrial dysfunction, RNA processing, glutamate excitotoxicity, endoplasmic reticulum stress, protein homeostasis and endosomal transport/extracellular vesicle (EV) secretion. EVs are nanoscopic membrane-bound particles that are released from cells, involved in the intercellular communication of proteins, lipids and genetic material, and there is increasing evidence of their role in ALS. After discussing the biogenesis of EVs, we review their roles in the propagation of pathological proteins in ALS, such as TDP-43, SOD1 and FUS, and their contribution to disease pathology. We also discuss the ALS related genes which are involved in EV formation and vesicular trafficking, before considering the EV protein and RNA dysregulation found in ALS and how these have been investigated as potential biomarkers. Finally, we highlight the potential use of EVs as therapeutic agents in ALS, in particular EVs derived from mesenchymal stem cells and EVs as drug delivery vectors for potential treatment strategies.

Epidemiology and survival trends of motor neurone disease in Northern Ireland from 2015 to 2019.

BACKGROUND AND PURPOSE: This study evaluates the incidence, prevalence and survival trends of motor neurone disease (MND) in Northern Ireland from 2015 to 2019. METHODS: A capture-recapture analysis was performed using five independent data sources. Incidence and prevalence rates were standardized to the European Standard Population. Survival outcomes were analysed using Kaplan-Meier curves and Cox regression analysis. RESULTS: Amongst 254 total cases of MND, capture-recapture analysis estimated three missing cases (case ascertainment 98.8%). Age standardized incidence of captured cases was 3.12 per 100,000 (2.73, 3.50) and standardized prevalence ranged from 9.45 to 6.49 per 100,000 from 2015 to 2019. Standardized incidence and prevalence rates in 2006 were 1.4 and 3.3 per 100,000 respectively. Of identified cases, 133 (52.4%) were male; 94.5% had amyotrophic lateral sclerosis; median age of onset was 67 years; median time to diagnosis was 12 months (95% confidence interval 11.2, 12.8); survival from diagnosis was 12 months (95% confidence interval 10.6, 15.4); 25 (9.8%) reported a family history of MND or frontotemporal dementia; and a known MND-associated genetic mutation was identified in 7.9% of total cases, of which the most common was C9orf72 (5.7% of all patients). Factors associated with improved survival were younger age at onset, longer time to diagnosis, attendance at regional MND clinic, and initial neurology presentation as outpatient (all p < 0.001). CONCLUSION: The incidence and prevalence of MND in Northern Ireland has increased over the last 10 years, in line with increasing rates reported from other European countries. Improved survival was associated with younger age at onset, longer time to diagnosis, attendance at a regional MND clinic and outpatient presentation to a Neurology Department.

snpQT: flexible, reproducible, and comprehensive quality control and imputation of genomic data.

Quality control of genomic data is an essential but complicated multi-step procedure, often requiring separate installation and expert familiarity with a combination of different bioinformatics tools. Software incompatibilities, and inconsistencies across computing environments, are recurrent challenges, leading to poor reproducibility. Existing semi-automated or automated solutions lack comprehensive quality checks, flexible workflow architecture, and user control. To address these challenges, we have developed snpQT: a scalable, stand-alone software pipeline using nextflow and BioContainers, for comprehensive, reproducible and interactive quality control of human genomic data. snpQT offers some 36 discrete quality filters or correction steps in a complete standardised pipeline, producing graphical reports to demonstrate the state of data before and after each quality control procedure. This includes human genome build conversion, population stratification against data from the 1,000 Genomes Project, automated population outlier removal, and built-in imputation with its own pre- and post- quality controls. Common input formats are used, and a synthetic dataset and comprehensive online tutorial are provided for testing, educational purposes, and demonstration. The snpQT pipeline is designed to run with minimal user input and coding experience; quality control steps are implemented with numerous user-modifiable thresholds, and workflows can be flexibly combined in custom combinations. snpQT is open source and freely available at https://github.com/nebfield/snpQT. A comprehensive online tutorial and installation guide is provided through to GWAS (https://snpqt.readthedocs.io/en/latest/), introducing snpQT using a synthetic demonstration dataset and a real-world Amyotrophic Lateral Sclerosis SNP-array dataset.

A Dystrophin Exon-52 Deleted Miniature Pig Model of Duchenne Muscular Dystrophy and Evaluation of Exon Skipping.

Duchenne muscular dystrophy (DMD) is a lethal X-linked recessive disorder caused by mutations in the DMD gene and the subsequent lack of dystrophin protein. Recently, phosphorodiamidate morpholino oligomer (PMO)-antisense oligonucleotides (ASOs) targeting exon 51 or 53 to reestablish the DMD reading frame have received regulatory approval as commercially available drugs. However, their applicability and efficacy remain limited to particular patients. Large animal models and exon skipping evaluation are essential to facilitate ASO development together with a deeper understanding of dystrophinopathies. Using recombinant adeno-associated virus-mediated gene targeting and somatic cell nuclear transfer, we generated a Yucatan miniature pig model of DMD with an exon 52 deletion mutation equivalent to one of the most common mutations seen in patients. Exon 52-deleted mRNA expression and dystrophin deficiency were confirmed in the skeletal and cardiac muscles of DMD pigs. Accordingly, dystrophin-associated proteins failed to be recruited to the sarcolemma. The DMD pigs manifested early disease onset with severe bodywide skeletal muscle degeneration and with poor growth accompanied by a physical abnormality, but with no obvious cardiac phenotype. We also demonstrated that in primary DMD pig skeletal muscle cells, the genetically engineered exon-52 deleted pig DMD gene enables the evaluation of exon 51 or 53 skipping with PMO and its advanced technology, peptide-conjugated PMO. The results show that the DMD pigs developed here can be an appropriate large animal model for evaluating in vivo exon skipping efficacy.

Exosomes in Ageing and Motor Neurone Disease: Biogenesis, Uptake Mechanisms, Modifications in Disease and Uses in the Development of Biomarkers and Therapeutics.

Intercellular communication between neurons and their surrounding cells occurs through the secretion of soluble molecules or release of vesicles such as exosomes into the extracellular space, participating in brain homeostasis. Under neuro-degenerative conditions associated with ageing, such as amyotrophic lateral sclerosis (ALS), Alzheimer's or Parkinson's disease, exosomes are suspected to propagate toxic proteins. The topic of this review is the role of exosomes in ageing conditions and more specifically in ALS. Our current understanding of exosomes and exosome-related mechanisms is first summarized in a general sense, including their biogenesis and secretion, heterogeneity, cellular interaction and intracellular fate. Their role in the Central Nervous System (CNS) and ageing of the neuromotor system is then considered in the context of exosome-induced signaling. The review then focuses on exosomes in age-associated neurodegenerative disease. The role of exosomes in ALS is highlighted, and their use as potential biomarkers to diagnose and prognose ALS is presented. The therapeutic implications of exosomes for ALS are considered, whether as delivery vehicles, neurotoxic targets or as corrective drugs in and of themselves. A diverse set of mechanisms underpin the functional roles, both confirmed and potential, of exosomes, generally in ageing and specifically in motor neurone disease. Aspects of their contents, biogenesis, uptake and modifications offer many plausible routes towards the development of novel biomarkers and therapeutics.

RIPK3-mediated cell death is involved in DUX4-mediated toxicity in facioscapulohumeral dystrophy.

BACKGROUND: Facioscapulohumeral dystrophy (FSHD) is caused by mutations leading to the aberrant expression of the DUX4 transcription factor in muscles. DUX4 was proposed to induce cell death, but the involvement of different death pathways is still discussed. A possible pro-apoptotic role of DUX4 was proposed, but as FSHD muscles are characterized by necrosis and inflammatory infiltrates, non-apoptotic pathways may be also involved. METHODS: We explored DUX4-mediated cell death by focusing on the role of one regulated necrosis pathway called necroptosis, which is regulated by RIPK3. We investigated the effect of necroptosis on cell death in vitro and in vivo experiments using RIPK3 inhibitors and a RIPK3-deficient transgenic mouse model. RESULTS: We showed in vitro that DUX4 expression causes a caspase-independent and RIPK3-mediated cell death in both myoblasts and myotubes. In vivo, RIPK3-deficient animals present improved body and muscle weights, a reduction of the aberrant activation of the DUX4 network genes, and an improvement of muscle histology. CONCLUSIONS: These results provide evidence for a role of RIPK3 in DUX4-mediated cell death and open new avenues of research.

Arabidopsis Coexpression Tool: a tool for gene coexpression analysis in Arabidopsis thaliana.

Gene coexpression analysis refers to the discovery of sets of genes which exhibit similar expression patterns across multiple transcriptomic data sets, such as microarray experiment data of public repositories. Arabidopsis Coexpression Tool (ACT), a gene coexpression analysis web tool for Arabidopsis thaliana, identifies genes which are correlated to a driver gene. Primary microarray data from ATH1 Affymetrix platform were processed with Single-Channel Array Normalization algorithm and combined to produce a coexpression tree which contains ∼21,000 A. thaliana genes. ACT was developed to present subclades of coexpressed genes, as well as to perform gene set enrichment analysis, being unique in revealing enriched transcription factors targeting coexpressed genes. ACT offers a simple and user-friendly interface producing working hypotheses which can be experimentally verified for the discovery of gene partnership, pathway membership, and transcriptional regulation. ACT analyses have been successful in identifying not only genes with coordinated ubiquitous expressions but also genes with tissue-specific expressions.

Optimized Molecular Interaction Networks for the Study of Skeletal Muscle.

BACKGROUND: Molecular interaction networks (MINs) aim to capture the complex relationships between interacting molecules within a biological system. MINs can be constructed from existing knowledge of molecular functional associations, such as protein-protein binding interactions (PPI) or gene co-expression, and these different sources may be combined into a single MIN. A given MIN may be more or less optimal in its representation of the important functional relationships of molecules in a tissue. OBJECTIVE: The aim of this study was to establish whether a combined MIN derived from different types of functional association could better capture muscle-relevant biology compared to its constituent single-source MINs. METHODS: MINs were constructed from functional association databases for both protein-binding and gene co-expression. The networks were then compared based on the capture of muscle-relevant genes and gene ontology (GO) terms, tested in two different ways using established biological network clustering algorithms. The top performing MINs were combined to test whether an optimal MIN for skeletal muscle could be constructed. RESULTS: The STRING PPI network was the best performing single-source MIN among those tested. Combining STRING with interactions from either the MyoMiner or CoXPRESSdb gene co-expression sources resulted in a combined network with improved performance relative to its constituent networks. CONCLUSION: MINs constructed from multiple types of functional association can better represent the functional relationships of molecules in a given tissue. Such networks may be used to improve the analysis and interpretation of functional genomics data in the study of skeletal muscle and neuromuscular diseases. Networks and clusters described by this study, including the combinations of STRING with MyoMiner or with CoXPRESSdb, are available for download from https://www.sys-myo.com/myominer/download.php.

Understanding Neuromuscular Health and Disease: Advances in Genetics, Omics, and Molecular Function.

The field of neuromuscular research has seen considerable recent advances in the molecular and cellular understanding of muscle biology, and the treatment of neuromuscular disease [...].

eSkip-Finder: a machine learning-based web application and database to identify the optimal sequences of antisense oligonucleotides for exon skipping.

Exon skipping using antisense oligonucleotides (ASOs) has recently proven to be a powerful tool for mRNA splicing modulation. Several exon-skipping ASOs have been approved to treat genetic diseases worldwide. However, a significant challenge is the difficulty in selecting an optimal sequence for exon skipping. The efficacy of ASOs is often unpredictable, because of the numerous factors involved in exon skipping. To address this gap, we have developed a computational method using machine-learning algorithms that factors in many parameters as well as experimental data to design highly effective ASOs for exon skipping. eSkip-Finder (https://eskip-finder.org) is the first web-based resource for helping researchers identify effective exon skipping ASOs. eSkip-Finder features two sections: (i) a predictor of the exon skipping efficacy of novel ASOs and (ii) a database of exon skipping ASOs. The predictor facilitates rapid analysis of a given set of exon/intron sequences and ASO lengths to identify effective ASOs for exon skipping based on a machine learning model trained by experimental data. We confirmed that predictions correlated well with in vitro skipping efficacy of sequences that were not included in the training data. The database enables users to search for ASOs using queries such as gene name, species, and exon number.

What Can Machine Learning Approaches in Genomics Tell Us about the Molecular Basis of Amyotrophic Lateral Sclerosis?

Amyotrophic Lateral Sclerosis (ALS) is the most common late-onset motor neuron disorder, but our current knowledge of the molecular mechanisms and pathways underlying this disease remain elusive. This review (1) systematically identifies machine learning studies aimed at the understanding of the genetic architecture of ALS, (2) outlines the main challenges faced and compares the different approaches that have been used to confront them, and (3) compares the experimental designs and results produced by those approaches and describes their reproducibility in terms of biological results and the performances of the machine learning models. The majority of the collected studies incorporated prior knowledge of ALS into their feature selection approaches, and trained their machine learning models using genomic data combined with other types of mined knowledge including functional associations, protein-protein interactions, disease/tissue-specific information, epigenetic data, and known ALS phenotype-genotype associations. The importance of incorporating gene-gene interactions and cis-regulatory elements into the experimental design of future ALS machine learning studies is highlighted. Lastly, it is suggested that future advances in the genomic and machine learning fields will bring about a better understanding of ALS genetic architecture, and enable improved personalized approaches to this and other devastating and complex diseases.

Molecular and Cellular Mechanisms Affected in ALS.

Amyotrophic lateral sclerosis (ALS) is a terminal late-onset condition characterized by the loss of upper and lower motor neurons. Mutations in more than 30 genes are associated to the disease, but these explain only ~20% of cases. The molecular functions of these genes implicate a wide range of cellular processes in ALS pathology, a cohesive understanding of which may provide clues to common molecular mechanisms across both familial (inherited) and sporadic cases and could be key to the development of effective therapeutic approaches. Here, the different pathways that have been investigated in ALS are summarized, discussing in detail: mitochondrial dysfunction, oxidative stress, axonal transport dysregulation, glutamate excitotoxicity, endosomal and vesicular transport impairment, impaired protein homeostasis, and aberrant RNA metabolism. This review considers the mechanistic roles of ALS-associated genes in pathology, viewed through the prism of shared molecular pathways.