Genome-wide identification of the genetic basis of amyotrophic lateral sclerosis

Disruption of Intracellular Calcium Homeostasis Leads to ERLIN2-Linked Hereditary Spastic Paraplegia in Patient-Derived Stem Cell Models

Hereditary spastic paraplegia (HSP) is a category of neurodegenerative illnesses with significant clinical and genetic heterogeneity. Homozygous truncated variants of the ERLIN2 gene lead to HSP18 (MIM #611225). However, it is still unclear whether there is an autosomal dominant pathogenic pattern. The specific molecular mechanism needs to be investigated. We generated patient-derived iPSC models to study the mechanism of ERLIN2 heterogeneous variants leading to HSP. We identified a heterozygous missense variant p.Val71Ala of ERLIN2 in an HSP family. Based on IP-mass spectrometry, we found that the ERLIN2 heterozygous missense variant protein recruited the ubiquitin E3 ligase RNF213 to degrade IP3R1. The degradation of IP3R1 leads to the reduction of intracellular free calcium, which triggered endoplasmic reticulum (ER) stress-mediated apoptosis. Calcium homeostasis imbalance inhibited the MAPK signaling pathway that contributed to decreased cell proliferation. In summary, these results suggest that the autosomal dominant inheritance of heterozygous missense variants in ERLIN2 is a novel pathogenic mode of HSP. Furthermore, the disruption of intracellular calcium homeostasis is the pathological mechanism.

Multi-Omics Profiling for Health

The world has witnessed a steady rise in both non-infectious and infectious chronic diseases, prompting a cross-disciplinary approach to understand and treating disease. Current medical care focuses on treating people after they become patients rather than preventing illness, leading to high costs in treating chronic and late-stage diseases. Additionally, a "one-size-fits all" approach to health care does not take into account individual differences in genetics, environment, or lifestyle factors, decreasing the number of people benefiting from interventions. Rapid advances in omics technologies and progress in computational capabilities have led to the development of multi-omics deep phenotyping, which profiles the interaction of multiple levels of biology over time and empowers precision health approaches. This review highlights current and emerging multi-omics modalities for precision health and discusses applications in the following areas: genetic variation, cardio-metabolic diseases, cancer, infectious diseases, organ transplantation, pregnancy, and longevity/aging. We will briefly discuss the potential of multi-omics approaches in disentangling host-microbe and host-environmental interactions. We will touch on emerging areas of electronic health record and clinical imaging integration with muti-omics for precision health. Finally, we will briefly discuss the challenges in the clinical implementation of multi-omics and its future prospects.

Emerging Trends in the Field of Inflammation and Proteinopathy in ALS/FTD Spectrum Disorder

Proteinopathy and neuroinflammation are two main hallmarks of neurodegenerative diseases. They also represent rare common events in an exceptionally broad landscape of genetic, environmental, neuropathologic, and clinical heterogeneity present in patients. Here, we aim to recount the emerging trends in amyotrophic lateral sclerosis (ALS) and frontotemporal degeneration (FTD) spectrum disorder. Our review will predominantly focus on neuroinflammation and systemic immune imbalance in ALS and FTD, which have recently been highlighted as novel therapeutic targets. A common mechanism of most ALS and ~50% of FTD patients is dysregulation of TAR DNA-binding protein 43 (TDP-43), an RNA/DNA-binding protein, which becomes depleted from the nucleus and forms cytoplasmic aggregates in neurons and glia. This, in turn, via both gain and loss of function events, alters a variety of TDP-43-mediated cellular events. Experimental attempts to target TDP-43 aggregates or manipulate crosstalk in the context of inflammation will be discussed. Targeting inflammation, and the immune system in general, is of particular interest because of the high plasticity of immune cells compared to neurons.

Recent progress of the genetics of amyotrophic lateral sclerosis and challenges of gene therapy

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder characterized by the degeneration of motor neurons in the brain and spinal cord. The causes of ALS are not fully understood. About 10% of ALS cases were associated with genetic factors. Since the discovery of the first familial ALS pathogenic gene SOD1 in 1993 and with the technology advancement, now over 40 ALS genes have been found. Recent studies have identified ALS related genes including ANXA11, ARPP21, CAV1, C21ORF2, CCNF, DNAJC7, GLT8D1, KIF5A, NEK1, SPTLC1, TIA1, and WDR7. These genetic discoveries contribute to a better understanding of ALS and show the potential to aid the development of better ALS treatments. Besides, several genes appear to be associated with other neurological disorders, such as CCNF and ANXA11 linked to FTD. With the deepening understanding of the classic ALS genes, rapid progress has been made in gene therapies. In this review, we summarize the latest progress on classical ALS genes and clinical trials for these gene therapies, as well as recent findings on newly discovered ALS genes.

ALS is imprinted in the chromatin accessibility of blood cells

Amyotrophic Lateral Sclerosis (ALS) is a complex and incurable neurodegenerative disorder in which genetic and epigenetic factors contribute to the pathogenesis of all forms of ALS. The interplay of genetic predisposition and environmental footprints generates epigenetic signatures in the cells of affected tissues, which then alter transcriptional programs. Epigenetic modifications that arise from genetic predisposition and systemic environmental footprints should in theory be detectable not only in affected CNS tissue but also in the periphery. Here, we identify an ALS-associated epigenetic signature ('epiChromALS') by chromatin accessibility analysis of blood cells of ALS patients. In contrast to the blood transcriptome signature, epiChromALS includes also genes that are not expressed in blood cells; it is enriched in CNS neuronal pathways and it is present in the ALS motor cortex. By combining simultaneous ATAC-seq and RNA-seq with single-cell sequencing in PBMCs and motor cortex from ALS patients, we demonstrate that epigenetic changes associated with the neurodegenerative disease can be found in the periphery, thus strongly suggesting a mechanistic link between the epigenetic regulation and disease pathogenesis.

Likely Pathogenic Variants of Cav1.3 and Nav1.1 Encoding Genes in Amyotrophic Lateral Sclerosis Could Elucidate the Dysregulated Pain Pathways

Amyotrophic lateral sclerosis (ALS) is a lethal multisystem neurodegenerative disease associated with progressive loss of motor neurons, leading to death. Not only is the clinical picture of ALS heterogenous, but also the pain sensation due to different types of pain involvement. ALS used to be considered a painless disease, but research has been emerging and depicting a more complex pain representation in ALS. Pain has been detected even a couple years before the symptomatic stage of ALS, referring to primary pain associated with muscle denervation, although secondary pain due to nociceptive causes is also a part of the clinical picture. A new non-contact dying-back injury mechanism theory of ALS recently postulated that the irreversible intrafusal proprioceptive Piezo2 microinjury could be the primary damage, with underlying genetic and environmental risk factors. Moreover, this Piezo2 primary damage is also proposed to dysregulate the primary pain pathways in the spinal dorsal horn in ALS due to the lost imbalanced subthreshold Ca2+ currents, NMDA activation and lost L-type Ca2+ currents, leading to the lost activation of wide dynamic range neurons. Our investigation is the first to show that the likely pathogenic variants of the Cav1.3 encoding CACNA1D gene may play a role in ALS pathology and the associated dysregulation or loss of the pain sensation. Furthermore, our reanalysis also shows that the SCN1A gene might also contribute to the dysregulated pain sensation in ALS. Finally, the absence of pathogenic variants of Piezo2 points toward the new non-contact dying-back injury mechanism theory of ALS. However, molecular and genetic investigations are needed to identify the functionally diverse features of this proposed novel critical pathway.

Large-scale analyses of CAV1 and CAV2 suggest their expression is higher in post-mortem ALS brain tissue and affects survival

Introduction: Caveolin-1 and Caveolin-2 (CAV1 and CAV2) are proteins associated with intercellular neurotrophic signalling. There is converging evidence that CAV1 and CAV2 (CAV1/2) genes have a role in amyotrophic lateral sclerosis (ALS). Disease-associated variants have been identified within CAV1/2 enhancers, which reduce gene expression and lead to disruption of membrane lipid rafts. Methods: Using large ALS whole-genome sequencing and post-mortem RNA sequencing datasets (5,987 and 365 tissue samples, respectively), and iPSC-derived motor neurons from 55 individuals, we investigated the role of CAV1/2 expression and enhancer variants in the ALS phenotype. Results: We report a differential expression analysis between ALS cases and controls for CAV1 and CAV2 genes across various post-mortem brain tissues and three independent datasets. CAV1 and CAV2 expression was consistently higher in ALS patients compared to controls, with significant results across the primary motor cortex, lateral motor cortex, and cerebellum. We also identify increased survival among carriers of CAV1/2 enhancer mutations compared to non-carriers within Project MinE and slower progression as measured by the ALSFRS. Carriers showed a median increase in survival of 345 days. Discussion: These results add to an increasing body of evidence linking CAV1 and CAV2 genes to ALS. We propose that carriers of CAV1/2 enhancer mutations may be conceptualised as an ALS subtype who present a less severe ALS phenotype with a longer survival duration and slower progression. Upregulation of CAV1/2 genes in ALS cases may indicate a causal pathway or a compensatory mechanism. Given prior research supporting the beneficial role of CAV1/2 expression in ALS patients, we consider a compensatory mechanism to better fit the available evidence, although further investigation into the biological pathways associated with CAV1/2 is needed to support this conclusion.

Amyotrophic lateral sclerosis: a neurodegenerative disorder poised for successful therapeutic translation

Amyotrophic lateral sclerosis (ALS) is a devastating disease caused by degeneration of motor neurons. As with all major neurodegenerative disorders, development of disease-modifying therapies has proven challenging for multiple reasons. Nevertheless, ALS is one of the few neurodegenerative diseases for which disease-modifying therapies are approved. Significant discoveries and advances have been made in ALS preclinical models, genetics, pathology, biomarkers, imaging and clinical readouts over the last 10-15 years. At the same time, novel therapeutic paradigms are being applied in areas of high unmet medical need, including neurodegenerative disorders. These developments have evolved our knowledge base, allowing identification of targeted candidate therapies for ALS with diverse mechanisms of action. In this Review, we discuss how this advanced knowledge, aligned with new approaches, can enable effective translation of therapeutic agents from preclinical studies through to clinical benefit for patients with ALS. We anticipate that this approach in ALS will also positively impact the field of drug discovery for neurodegenerative disorders more broadly.

Predicting the prevalence of complex genetic diseases from individual genotype profiles using capsule networks

Diseases that have a complex genetic architecture tend to suffer from considerable amounts of genetic variants that, although playing a role in the disease, have not yet been revealed as such. Two major causes for this phenomenon are genetic variants that do not stack up effects, but interact in complex ways; in addition, as recently suggested, the omnigenic model postulates that variants interact in a holistic manner to establish disease phenotypes. Here we present DiseaseCapsule, as a capsule-network-based approach that explicitly addresses to capture the hierarchical structure of the underlying genome data, and has the potential to fully capture the non-linear relationships between variants and disease. DiseaseCapsule is the first such approach to operate in a whole-genome manner when predicting disease occurrence from individual genotype profiles. In experiments, we evaluated DiseaseCapsule on amyotrophic lateral sclerosis (ALS) and Parkinson’s disease, with a particular emphasis on ALS, which is known to have a complex genetic architecture and is affected by 40% missing heritability. On ALS, DiseaseCapsule achieves 86.9% accuracy on hold-out test data in predicting disease occurrence, thereby outperforming all other approaches by large margins. Also, DiseaseCapsule required sufficiently less training data for reaching optimal performance. Last but not least, the systematic exploitation of the network architecture yielded 922 genes of particular interest, and 644 ‘non-additive’ genes that are crucial factors in DiseaseCapsule, but remain masked within linear schemes.

Gene targeting in amyotrophic lateral sclerosis using causality-based feature selection and machine learning

BACKGROUND

Amyotrophic lateral sclerosis (ALS) is a rare progressive neurodegenerative disease that affects upper and lower motor neurons. As the molecular basis of the disease is still elusive, the development of high-throughput sequencing technologies, combined with data mining techniques and machine learning methods, could provide remarkable results in identifying pathogenetic mechanisms. High dimensionality is a major problem when applying machine learning techniques in biomedical data analysis, since a huge number of features is available for a limited number of samples. The aim of this study was to develop a methodology for training interpretable machine learning models in the classification of ALS and ALS-subtypes samples, using gene expression datasets.

METHODS

We performed dimensionality reduction in gene expression data using a semi-automated preprocessing systematic gene selection procedure using Statistically Equivalent Signature (SES), a causality-based feature selection algorithm, followed by Boosted Regression Trees (XGBoost) and Random Forest to train the machine learning classifiers. The SHapley Additive exPlanations (SHAP values) were used for interpretation of the machine learning classifiers. The methodology was developed and tested using two distinct publicly available ALS RNA-seq datasets. We evaluated the performance of SES as a dimensionality reduction method against: (a) Least Absolute Shrinkage and Selection Operator (LASSO), and (b) Local Outlier Factor (LOF).

RESULTS

The proposed methodology achieved 85.18% accuracy for the classification of cerebellum or frontal cortex samples as C9orf72-related familial ALS, sporadic ALS or healthy samples. Importantly, the genes identified as the most determinative have also been reported as disease-associated in ALS literature. When tested in the evaluation dataset, the methodology achieved 88.89% accuracy for the classification of sporadic ALS motor neuron samples. When LASSO was used as feature selection method instead of SES, the accuracy of the machine learning classifiers ranged from 74.07 to 96.30%, depending on tissue assessed, while LOF underperformed significantly (77.78% accuracy for the classification of pooled cerebellum and frontal cortex samples).

CONCLUSIONS

Using SES, we addressed the challenge of high dimensionality in gene expression data analysis, and we trained accurate machine learning ALS classifiers, specific for the gene expression patterns of different disease subtypes and tissue samples, while identifying disease-associated genes.

A New Phase of Networking: The Molecular Composition and Regulatory Dynamics of Mammalian Stress Granules

Stress granules (SGs) are cytosolic biomolecular condensates that form in response to cellular stress. Weak, multivalent interactions between their protein and RNA constituents drive their rapid, dynamic assembly through phase separation coupled to percolation. Though a consensus model of SG function has yet to be determined, their perceived implication in cytoprotective processes (e.g., antiviral responses and inhibition of apoptosis) and possible role in the pathogenesis of various neurodegenerative diseases (e.g., amyotrophic lateral sclerosis and frontotemporal dementia) have drawn great interest. Consequently, new studies using numerous cell biological, genetic, and proteomic methods have been performed to unravel the mechanisms underlying SG formation, organization, and function and, with them, a more clearly defined SG proteome. Here, we provide a consensus SG proteome through literature curation and an update of the user-friendly database RNAgranuleDB to version 2.0 (http://rnagranuledb.lunenfeld.ca/). With this updated SG proteome, we use next-generation phase separation prediction tools to assess the predisposition of SG proteins for phase separation and aggregation. Next, we analyze the primary sequence features of intrinsically disordered regions (IDRs) within SG-resident proteins. Finally, we review the protein- and RNA-level determinants, including post-translational modifications (PTMs), that regulate SG composition and assembly/disassembly dynamics.

Advances in sequencing technologies for amyotrophic lateral sclerosis research

Amyotrophic lateral sclerosis (ALS) is caused by upper and lower motor neuron loss and has a fairly rapid disease progression, leading to fatality in an average of 2-5 years after symptom onset. Numerous genes have been implicated in this disease; however, many cases remain unexplained. Several technologies are being used to identify regions of interest and investigate candidate genes. Initial approaches to detect ALS genes include, among others, linkage analysis, Sanger sequencing, and genome-wide association studies. More recently, next-generation sequencing methods, such as whole-exome and whole-genome sequencing, have been introduced. While those methods have been particularly useful in discovering new ALS-linked genes, methodological advances are becoming increasingly important, especially given the complex genetics of ALS. Novel sequencing technologies, like long-read sequencing, are beginning to be used to uncover the contribution of repeat expansions and other types of structural variation, which may help explain missing heritability in ALS. In this review, we discuss how popular and/or upcoming methods are being used to discover ALS genes, highlighting emerging long-read sequencing platforms and their role in aiding our understanding of this challenging disease.

D4Z4 Methylation Levels Combined with a Machine Learning Pipeline Highlight Single CpG Sites as Discriminating Biomarkers for FSHD Patients

The study describes a protocol for methylation analysis integrated with Machine Learning (ML) algorithms developed to classify Facio-Scapulo-Humeral Dystrophy (FSHD) subjects. The DNA methylation levels of two D4Z4 regions (DR1 and DUX4-PAS) were assessed by an in-house protocol based on bisulfite sequencing and capillary electrophoresis, followed by statistical and ML analyses. The study involved two independent cohorts, namely a training group of 133 patients with clinical signs of FSHD and 150 healthy controls (CTRL) and a testing set of 27 FSHD patients and 25 CTRL. As expected, FSHD patients showed significantly reduced methylation levels compared to CTRL. We utilized single CpG sites to develop a ML pipeline able to discriminate FSHD subjects. The model identified four CpGs sites as the most relevant for the discrimination of FSHD subjects and showed high metrics values (accuracy: 0.94, sensitivity: 0.93, specificity: 0.96). Two additional models were developed to differentiate patients with lower D4Z4 size and patients who might carry pathogenic variants in FSHD genes, respectively. Overall, the present model enables an accurate classification of FSHD patients, providing additional evidence for DNA methylation as a powerful disease biomarker that could be employed for prioritizing subjects to be tested for FSHD.

Intersection of network medicine and machine learning towards investigating the key biomarkers and pathways underlying amyotrophic lateral sclerosis: a systematic review

BACKGROUND

Network medicine is an emerging area of research that focuses on delving into the molecular complexity of the disease, leading to the discovery of network biomarkers and therapeutic target discovery. Amyotrophic lateral sclerosis (ALS) is a complicated rare disease with unknown pathogenesis and no available treatment. In ALS, network properties appear to be potential biomarkers that can be beneficial in disease-related applications when explored independently or in tandem with machine learning (ML) techniques.

OBJECTIVE

This systematic literature review explores recent trends in network medicine and implementations of network-based ML algorithms in ALS. We aim to provide an overview of the identified primary studies and gather details on identifying the potential biomarkers and delineated pathways.

METHODS

The current study consists of searching for and investigating primary studies from PubMed and Dimensions.ai, published between 2018 and 2022 that reported network medicine perspectives and the coupling of ML techniques. Each abstract and full-text study was individually evaluated, and the relevant studies were finally included in the review for discussion once they met the inclusion and exclusion criteria.

RESULTS

We identified 109 eligible publications from primary studies representing this systematic review. The data coalesced into two themes: application of network science to identify disease modules and promising biomarkers in ALS, along with network-based ML approaches. Conclusion This systematic review gives an overview of the network medicine approaches and implementations of network-based ML algorithms in ALS to determine new disease genes, and identify critical pathways and therapeutic target discovery for personalized treatment.

Macrophage-Targeted Sodium Chlorite (NP001) Slows Progression of Amyotrophic Lateral Sclerosis (ALS) through Regulation of Microbial Translocation

Amyotrophic lateral sclerosis (ALS) is a heterogeneous, progressive, and universally fatal neurodegenerative disease. A subset of ALS patients has measurable plasma levels of lipopolysaccharide (LPS) and C-reactive protein (CRP) consistent with low-grade microbial translocation (MT). Unless interrupted, MT sets up a self-perpetuating loop of inflammation associated with systemic macrophage activation. To test whether MT contributed to ALS progression, blood specimens from a phase 2 study of NP001 in ALS patients were evaluated for changes in activity in treated patients as compared to controls over the 6-month study. In this post hoc analysis, plasma specimens from baseline and six-month timepoints were analyzed. Compared with baseline values, biomarkers related to MT were significantly decreased (LPS, LPS binding protein (LBP), IL-18, Hepatocyte growth factor (HGF), soluble CD163 (sCD163)) in NP001-treated patients as compared to controls, whereas wound healing and immunoregulatory factors were increased (IL-10, Epidermal growth factor (EGF), neopterin) by the end of study. These biomarker results linked to the positive clinical trial outcome confirm that regulation of macrophage activation may be an effective approach for the treatment of ALS and, potentially, other neuroinflammatory diseases related to MT.

TDP-43 and NEAT long non-coding RNA: Roles in neurodegenerative disease

Understanding and ameliorating neurodegenerative diseases represents a key challenge for supporting the health span of the aging population. Diverse protein aggregates have been implicated in such neurodegenerative disorders, including amyloid-β, α-synuclein, tau, fused in sarcoma (FUS), and transactivation response element (TAR) DNA-binding protein 43 (TDP-43). Recent years have seen significant growth in our mechanistic knowledge of relationships between these proteins and some of the membrane-less nuclear structures that fulfill key roles in the cell function. These include the nucleolus, nuclear speckles, and paraspeckles. The ability of macromolecular protein:RNA complexes to partition these nuclear condensates through biophysical processes that involve liquid-liquid phase separation (LLPS) has also gained attention recently. The paraspeckle, which is scaffolded by the architectural long-non-coding RNA nuclear enriched abundant transcript 1 (NEAT1) plays central roles in RNA processing and metabolism and has been linked dynamically to TDP-43. In this mini-review, we outline essential early and recent insights in relation to TDP-43 proteinopathies. We then appraise the relationships between TDP-43 and NEAT1 in the context of neuronal paraspeckles and neuronal stress. We highlight key areas for investigation based on recent advances in our understanding of how TDP-43 affects neuronal function, especially in relation to messenger ribosomal nucleic acid (mRNA) splicing. Finally, we offer perspectives that should be considered for translational pipelines in order to improve health outcomes for the management of neurodegenerative diseases.

Synergistic association of resveratrol and histone deacetylase inhibitors as treatment in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease associated with motor neuron degeneration, progressive paralysis and finally death. Despite the research efforts, currently there is no cure for ALS. In recent years, multiple epigenetic mechanisms have been associated with neurodegenerative diseases. A pathological role for histone hypoacetylation and the abnormal NF-κB/RelA activation involving deacetylation of lysines, with the exclusion of lysine 310, has been established in ALS. Recent findings indicate that the pathological acetylation state of NF-κB/RelA and histone 3 (H3) occurring in the SOD1(G93A) murine model of ALS can be corrected by the synergistic combination of low doses of the AMP-activated kinase (AMPK)-sirtuin 1 pathway activator resveratrol and the histone deacetylase (HDAC) inhibitors MS-275 (entinostat) or valproate. The combination of the epigenetic drugs, by rescuing RelA and the H3 acetylation state, promotes a beneficial and sexually dimorphic effect on disease onset, survival and motor neurons degeneration. In this mini review, we discuss the potential of the epigenetic combination of resveratrol with HDAC inhibitors in the ALS treatment.

Amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis is a fatal CNS neurodegenerative disease. Despite intensive research, current management of amyotrophic lateral sclerosis remains suboptimal from diagnosis to prognosis. Recognition of the phenotypic heterogeneity of amyotrophic lateral sclerosis, global CNS dysfunction, genetic architecture, and development of novel diagnostic criteria is clarifying the spectrum of clinical presentation and facilitating diagnosis. Insights into the pathophysiology of amyotrophic lateral sclerosis, identification of disease biomarkers and modifiable risks, along with new predictive models, scales, and scoring systems, and a clinical trial pipeline of mechanism-based therapies, are changing the prognostic landscape. Although most recent advances have yet to translate into patient benefit, the idea of amyotrophic lateral sclerosis as a complex syndrome is already having tangible effects in the clinic. This Seminar will outline these insights and discuss the status of the management of amyotrophic lateral sclerosis for the general neurologist, along with future prospects that could improve care and outcomes for patients with amyotrophic lateral sclerosis.

Update on genetics of amyotrophic lateral sclerosis

PURPOSE OF REVIEW

ALS genetics are highly dynamic and of great interest for the ALS research community. Each year, by using ever-growing datasets and cutting-edge methodology, an array of novel ALS-associated genes and downstream pathomechanisms are discovered. The increasing plenty and complexity of insights warrants regular summary by-reviews.

RECENT FINDINGS

Most recent disease gene discoveries constitute the candidate and risk genes SPTLC1 , KANK1 , CAV1 , HTT , and WDR7 , as well as seven novel risk loci. Cell type and functional enrichment analyses enlighten the genetic basis of selective motor neuron vulnerability in ALS demonstrating high expression of ALS-associated genes in cortical motor neurons and highlight the pathogenic significance of cell-autonomous processes. Major pathomechanistic insights have been gained regarding known ALS genes/proteins, specifically C9orf72 , TDP43, ANXA11 , and KIF5A . The first ASO-based gene-specific therapy trials in familial forms of ALS have yielded equivocal results stressing the re-evaluation of pathomechanisms linked to SOD1 and C9orf72 mutations.

SUMMARY

The genetic and molecular basis of ALS is increasingly examined on single-cell resolution. In the past 2 years, the understanding of the downstream mechanisms of several ALS genes and TDP-43 proteinopathy has been considerably extended. These insights will result in novel gene specific therapy approaches for sporadic ALS and genetic subtypes.

Biochemical Pathways of Cellular Mechanosensing/Mechanotransduction and Their Role in Neurodegenerative Diseases Pathogenesis

In this review, we shed light on recent advances regarding the characterization of biochemical pathways of cellular mechanosensing and mechanotransduction with particular attention to their role in neurodegenerative disease pathogenesis. While the mechanistic components of these pathways are mostly uncovered today, the crosstalk between mechanical forces and soluble intracellular signaling is still not fully elucidated. Here, we recapitulate the general concepts of mechanobiology and the mechanisms that govern the mechanosensing and mechanotransduction processes, and we examine the crosstalk between mechanical stimuli and intracellular biochemical response, highlighting their effect on cellular organelles' homeostasis and dysfunction. In particular, we discuss the current knowledge about the translation of mechanosignaling into biochemical signaling, focusing on those diseases that encompass metabolic accumulation of mutant proteins and have as primary characteristics the formation of pathological intracellular aggregates, such as Alzheimer's Disease, Huntington's Disease, Amyotrophic Lateral Sclerosis and Parkinson's Disease. Overall, recent findings elucidate how mechanosensing and mechanotransduction pathways may be crucial to understand the pathogenic mechanisms underlying neurodegenerative diseases and emphasize the importance of these pathways for identifying potential therapeutic targets.

Multiomic analysis reveals cell-type-specific molecular determinants of COVID-19 severity

The determinants of severe COVID-19 in healthy adults are poorly understood, which limits the opportunity for early intervention. We present a multiomic analysis using machine learning to characterize the genomic basis of COVID-19 severity. We use single-cell multiome profiling of human lungs to link genetic signals to cell-type-specific functions. We discover >1,000 risk genes across 19 cell types, which account for 77% of the SNP-based heritability for severe disease. Genetic risk is particularly focused within natural killer (NK) cells and T cells, placing the dysfunction of these cells upstream of severe disease. Mendelian randomization and single-cell profiling of human NK cells support the role of NK cells and further localize genetic risk to CD56bright NK cells, which are key cytokine producers during the innate immune response. Rare variant analysis confirms the enrichment of severe-disease-associated genetic variation within NK-cell risk genes. Our study provides insights into the pathogenesis of severe COVID-19 with potential therapeutic targets.

Approaches to Gene Modulation Therapy for ALS

Amyotrophic lateral sclerosis (ALS) is a devastating motor neuron disease for which there is currently no robust therapy. Recent progress in understanding ALS disease mechanisms and genetics in combination with innovations in gene modulation strategies creates promising new options for the development of ALS therapies. In recent years, six gene modulation therapies have been tested in ALS patients. These target gain-of-function pathology of the most common ALS genes, SOD1, C9ORF72, FUS, and ATXN2, using adeno-associated virus (AAV)-mediated microRNAs and antisense oligonucleotides (ASOs). Here, we review the latest clinical and preclinical advances in gene modulation approaches for ALS, including gene silencing, gene correction, and gene augmentation. These techniques have the potential to positively impact the direction of future research trials and transform ALS treatments for this grave disease.

Progress in Amyotrophic Lateral Sclerosis Gene Discovery: Reflecting on Classic Approaches and Leveraging Emerging Technologies

Amyotrophic lateral sclerosis (ALS) is the most prominent motor neuron disease in humans. Its etiology consists of progressive motor neuron degeneration resulting in a rapid decline in motor function starting in the limbs or bulbar muscles and eventually fatally impairing central organs most typically resulting in loss of respiration. Pathogenic variants in 4 main genes, SOD1, TARDBP, FUS, and C9orf72, have been well characterized as causative for more than a decade now. However, these only account for a small fraction of all ALS cases. In this review, we highlight many additional variants that appear to be causative or confer increased risk for ALS, and we reflect on the technologies that have led to these discoveries. Next, we call attention to new challenges and opportunities for ALS and suggest next steps to increase our understanding of ALS genetics. Finally, we conclude with a synopsis of gene therapy paradigms and how increased understanding of ALS genetics can lead us to developing effective treatments. Ultimately, a consolidated update of the field can provide a launching point for researchers and clinicians to improve our search for ALS-related genes, defining pathogenic mechanisms, form diagnostics, and develop therapies.

Purinergic P2X7 Receptor: A Therapeutic Target in Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease characterized by upper and lower motor neuron loss. The pathomechanisms of ALS are still poorly understood with current hypotheses involving genetic mutations, excitotoxicity, and reactive oxygen species formation. In the absence of a disease-altering clinically approved therapeutic, there is an ever-increasing need to identify new targets to develop drugs that delay disease onset and/or progression. The purinergic P2X₇ receptor (P2X₇R) has been implicated widely across the ALS realm, providing a potential therapeutic strategy. This review summarizes the current understanding of ALS, the P2X₇R and its role in ALS, the current landscape of P2X₇R antagonists, and the in vivo potential of these antagonists in preclinical ALS models.

C9orf72-Derived Proline:Arginine Poly-Dipeptides Modulate Cytoskeleton and Mechanical Stress Response

Proline:arginine (PR) poly-dipeptides from the GGGGCC repeat expansion in C9orf72 have cytotoxicity and bind intermediate filaments (IFs). However, it remains unknown how PR poly-dipeptides affect cytoskeletal organization and focal adhesion (FA) formation. Here, we show that changes to the cytoskeleton and FA by PR poly-dipeptides result in the alteration of cell stiffness and mechanical stress response. PR poly-dipeptides increased the junctions and branches of the IF network and increased cell stiffness. They also changed the distribution of actin filaments and increased the size of FA and intracellular calcium concentration. PR poly-dipeptides or an inhibitor of IF organization prevented cell detachment. Furthermore, PR poly-dipeptides induced upregulation of mechanical stress response factors and led to a maladaptive response to cyclic stretch. These results suggest that the effects of PR poly-dipeptides on mechanical properties and mechanical stress response may serve as a pathogenesis of C9orf72-related neurodegeneration.

Advancing discovery of risk-altering variants for complex diseases by functionally informed fine-mapping

Pinpointing causal variants at risk loci identified by genome-wide association studies (GWAS) has been a great challenge. In this issue of Neuron, Zhang et al. present a fine-mapping approach, RefMap, integrating functional genomics with GWAS summary statistics to prioritize causal variants for amyotrophic lateral sclerosis.