Answer ALS, a large-scale resource for sporadic and familial ALS combining clinical and multi-omics data from induced pluripotent cell lines

Intersecting impact of CAG repeat and huntingtin knockout in stem cell-derived cortical neurons

Huntington's Disease (HD) is caused by a CAG repeat expansion in the gene encoding huntingtin (HTT). While normal HTT function appears impacted by the mutation, the specific pathways unique to CAG repeat expansion versus loss of normal function are unclear. To understand the impact of the CAG repeat expansion, we evaluated biological signatures of HTT knockout (HTT KO) versus those that occur from the CAG repeat expansion by applying multi-omics, live cell imaging, survival analysis and a novel feature-based pipeline to study cortical neurons (eCNs) derived from an isogenic human embryonic stem cell series (RUES2). HTT KO and the CAG repeat expansion influence developmental trajectories of eCNs, with opposing effects on growth. Network analyses of differentially expressed genes and proteins associated with enriched epigenetic motifs identified subnetworks common to CAG repeat expansion and HTT KO that include neuronal differentiation, cell cycle regulation, and mechanisms related to transcriptional repression, and may represent gain-of-function mechanisms that cannot be explained by HTT loss of function alone. A combination of dominant and loss-of-function mechanisms are likely involved in the aberrant neurodevelopmental and neurodegenerative features of HD that can help inform therapeutic strategies.

Clinical assessment and interpretation of dysarthria in ALS using attention based deep learning AI models

Speech dysarthria is a key symptom of neurological conditions like ALS, yet existing AI models designed to analyze it from audio signal rely on handcrafted features with limited inference performance. Deep learning approaches improve accuracy but lack interpretability. We propose an attention-based deep learning AI model to assess dysarthria severity based on listener effort ratings. Using 2,102 recordings from 125 participants, rated by three speech-language pathologists on a 100-point scale, we trained models directly from recordings collected remotely. Our best model achieved R2 of 0.92 and RMSE of 6.78. Attention-based interpretability identified key phonemes, such as vowel sounds influenced by 'r' (e.g., "car," "more"), and isolated inspiration sounds as markers of speech deterioration. This model enhances precision in dysarthria assessment while maintaining clinical interpretability. By improving sensitivity to subtle speech changes, it offers a valuable tool for research and patient care in ALS and other neurological disorders.

Transforming neurodegenerative disorder care with machine learning: Strategies and applications

Neurodegenerative diseases (NDs), characterized by progressive neuronal degeneration and manifesting in diverse forms such as memory loss and movement disorders, pose significant challenges due to their complex molecular mechanisms and heterogeneous patient presentations. Diagnosis often relies heavily on clinical assessments and neuroimaging, with definitive confirmation frequently requiring post-mortem autopsy. However, the emergence of Artificial Intelligence (AI) and Machine Learning (ML) offers a transformative potential. These technologies can enable the development of non-invasive tools for early diagnosis, biomarker identification, personalized treatment strategies, patient subtyping and stratification, and disease risk prediction. This review aims to provide a starting point for researchers, both with and without clinical backgrounds, who are interested in applying ML to NDs. We will discuss available data resources for key diseases like Alzheimer's and Parkinson's, explore how ML can revolutionize neurodegenerative care, and emphasize the importance of integrating multiple high-dimensional data sources to gain deeper insights and inform effective therapeutic strategies.

Respiratory function, survival, and NIV prevalence over time in ALS - a PRECISION ALS study

INTRODUCTION

Respiratory function typically deteriorates as ALS progresses and is associated with shorter survival. This study aims to describe respiratory function and the prevalence of noninvasive ventilation (NIV) along the disease trajectory using prospective data from the PRECISION ALS project.

METHODS

We included 3449 ALS patients from six European population-based cohorts. All had comparable assessments of vital capacity, percent predicted (VC%) (58.1% had multiple assessments) and 56% had assessments of the revised ALS Functional Rating Scale (ALSFRS-R). The data were analyzed in relation to survival, NIV, and genetic status (C9orf72, SOD1, FUS, and TARDBP).

RESULTS

In those with a survival time of 1-4 years from diagnosis, the median VC% declined from 91 to 97% at the first assessment to 47-50% at the last assessment 6 months before death. In those with longitudinal assessments, the median VC% declined an average of 24 percentage points per year. Over time, there was an increase in respiratory symptoms relative to general functional impairment, as measured by the ALSFRS-R, and VC% was strongly associated with shorter survival. The confirmed prevalence of NIV was approximately 3%, 15%, and 25% in patients with a VC% of >80, 50-80, and <50, respectively.

CONCLUSION

There was a trend of worsening respiratory function over time and an increase in respiratory symptoms relative to general functional impairment. Survival was strongly associated with respiratory function. In those with impaired respiratory function, there was significant variation in the introduction of NIV.

Drug repurposing in amyotrophic lateral sclerosis (ALS)

INTRODUCTION

Identifying treatments that can alter the natural history of amyotrophic lateral sclerosis (ALS) is challenging. For years, drug discovery in ALS has relied upon traditional approaches with limited success. Drug repurposing, where clinically approved drugs are reevaluated for other indications, offers an alternative strategy that overcomes some of the challenges associated with de novo drug discovery.

AREAS COVERED

In this review, the authors discuss the challenge of drug discovery in ALS and examine the potential of drug repurposing for the identification of new effective treatments. The authors consider a range of approaches, from screening in experimental models to computational approaches, and outline some general principles for preclinical and clinical research to help bridge the translational gap. Literature was reviewed from original publications, press releases and clinical trials.

EXPERT OPINION

Despite remaining challenges, drug repurposing offers the opportunity to improve therapeutic options for ALS patients. Nevertheless, stringent preclinical research will be necessary to identify the most promising compounds together with innovative experimental medicine studies to bridge the translational gap. The authors further highlight the importance of combining expertise across academia, industry and wider stakeholders, which will be key in the successful delivery of repurposed therapies to the clinic.

Neuronal polyunsaturated fatty acids are protective in ALS/FTD

Here we report a conserved transcriptomic signature of reduced fatty acid and lipid metabolism gene expression in a Drosophila model of C9orf72 repeat expansion, the most common genetic cause of amyotrophic lateral sclerosis and frontotemporal dementia (ALS/FTD), and in human postmortem ALS spinal cord. We performed lipidomics on C9 ALS/FTD Drosophila, induced pluripotent stem (iPS) cell neurons and postmortem FTD brain tissue. This revealed a common and specific reduction in phospholipid species containing polyunsaturated fatty acids (PUFAs). Feeding C9 ALS/FTD flies PUFAs yielded a modest increase in survival. However, increasing PUFA levels specifically in neurons of C9 ALS/FTD flies, by overexpressing fatty acid desaturase enzymes, led to a substantial extension of lifespan. Neuronal overexpression of fatty acid desaturases also suppressed stressor-induced neuronal death in iPS cell neurons of patients with both C9 and TDP-43 ALS/FTD. These data implicate neuronal fatty acid saturation in the pathogenesis of ALS/FTD and suggest that interventions to increase neuronal PUFA levels may be beneficial.

Aberrant gene expression prediction across human tissues

Despite the frequent implication of aberrant gene expression in diseases, algorithms predicting aberrantly expressed genes of an individual are lacking. To address this need, we compile an aberrant expression prediction benchmark covering 8.2 million rare variants from 633 individuals across 49 tissues. While not geared toward aberrant expression, the deleteriousness score CADD and the loss-of-function predictor LOFTEE show mild predictive ability (1-1.6% average precision). Leveraging these and further variant annotations, we next train AbExp, a model that yields 12% average precision by combining in a tissue-specific fashion expression variability with variant effects on isoforms and on aberrant splicing. Integrating expression measurements from clinically accessible tissues leads to another two-fold improvement. Furthermore, we show on UK Biobank blood traits that performing rare variant association testing using the continuous and tissue-specific AbExp variant scores instead of LOFTEE variant burden increases gene discovery sensitivity and enables improved phenotype predictions.

ALS molecular subtypes are a combination of cellular and pathological features learned by deep multiomics classifiers

Amyotrophic lateral sclerosis (ALS) is a complex syndrome with multiple genetic causes and wide variation in disease presentation. Despite this heterogeneity, large-scale genomics studies revealed that ALS postmortem samples can be grouped into a small number of subtypes, defined by transcriptomic signatures of mitochondrial dysfunction and oxidative stress (ALS-Ox), microglial activation and neuroinflammation (ALS-Glia), or TDP-43 pathology and associated transposable elements (ALS-TE). In this study, we present a deep ALS neural net classifier (DANCer) for ALS molecular subtypes. Applying DANCer to an expanded cohort from the NYGC ALS Consortium highlights two subtypes that strongly correlate with disease duration: ALS-TE in cortex and ALS-Glia in spinal cord. Finally, single-nucleus transcriptomes demonstrate that ALS subtypes are recapitulated in neurons and glia, with both ALS-wide and subtype-specific alterations in all cell types. In summary, ALS molecular subtypes represent a combination of cellular and pathological features that correlate with clinical features of ALS.

Unveiling amyotrophic lateral sclerosis complexity: insights from proteomics, metabolomics and microbiomics

Amyotrophic lateral sclerosis is the most common motor neuron disease and manifests as a clinically and genetically heterogeneous neurodegenerative disorder mainly affecting the motor systems. To date, despite promising results and accumulating knowledge on the pathomechanisms of amyotrophic lateral sclerosis, a specific disease-modifying treatment is still not available. In vitro and in vivo disease models coupled with multiomics techniques have helped elucidate the pathomechanisms underlying this disease. In particular, omics approaches are powerful tools for identifying new potential disease biomarkers that may be particularly useful for diagnosis, prognosis and assessment of treatment response. In turn, these findings could support physicians in stratifying patients into clinically relevant subgroups for the identification of the best therapeutic targets. Here, we provide a comprehensive review of the most relevant literature highlighting the importance of proteomics approaches in determining the role of pathogenic misfolded/aggregated proteins and the molecular mechanisms involved in the pathogenesis and progression of amyotrophic lateral sclerosis. In addition, we explored new findings arising from metabolomic and lipidomic studies, which can aid to elucidate the intricate metabolic alterations underlying amyotrophic lateral sclerosis pathology. Moreover, we integrated these insights with microbiomics data, providing a thorough understanding of the interplay between metabolic dysregulation and microbial dynamics in disease progression. Indeed, a greater integration of these multiomics data could lead to a deeper understanding of disease mechanisms, supporting the development of specific therapies for amyotrophic lateral sclerosis.

Sporadic ALS hiPSC-derived motor neurons show axonal defects linked to altered axon guidance pathways

Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disorder characterized by the selective and progressive loss of motor neurons, leading to gradual paralysis and death within 2 to 5 years after diagnosis. The exact underlying pathogenic mechanism(s) remain elusive. This is particularly the case for sporadic ALS (sALS), representing 90 % of cases, as modelling a sporadic disease is extremely difficult. We used human induced pluripotent stem cell (hiPSC)-derived motor neurons from sALS patients to investigate early disease mechanisms. The earliest phenotype that we observed were profound axonal defects including impaired axonal transport, defective axonal outgrowth and a reduced formation of neuromuscular junctions. Transcriptomic profiling revealed significant dysregulation in axon guidance pathways, with upregulation of specific axonal regeneration-inhibiting genes, such as EphA4 and DCC in sALS motor neurons. Our findings suggest that dysregulation of axon guidance pathways contributes to axonal defects and that this could play a crucial role in the pathogenesis of sALS.

Intersecting impact of CAG repeat and Huntingtin knockout in stem cell-derived cortical neurons

Huntington's Disease (HD) is caused by a CAG repeat expansion in the gene encoding Huntingtin (HTT ) . While normal HTT function appears impacted by the mutation, the specific pathways unique to CAG repeat expansion versus loss of normal function are unclear. To understand the impact of the CAG repeat expansion, we evaluated biological signatures of HTT knockout ( HTT KO) versus those that occur from the CAG repeat expansion by applying multi-omics, live cell imaging, survival analysis and a novel feature-based pipeline to study cortical neurons (eCNs) derived from an isogenic human embryonic stem cell series (RUES2). HTT KO and the CAG repeat expansion influence developmental trajectories of eCNs, with opposing effects on the growth. Network analyses of differentially expressed genes and proteins associated with enriched epigenetic motifs identified subnetworks common to CAG repeat expansion and HTT KO that include neuronal differentiation, cell cycle regulation, and mechanisms related to transcriptional repression and may represent gain-of-function mechanisms that cannot be explained by HTT loss of function alone. A combination of dominant and loss-of-function mechanisms are likely involved in the aberrant neurodevelopmental and neurodegenerative features of HD that can help inform therapeutic strategies.

Multi-omic quantitative trait loci link tandem repeat size variation to gene regulation in human brain

Tandem repeat (TR) size variation is implicated in ~50 neurological disorders, yet its impact on gene regulation in the human brain remains largely unknown. In the present study, we quantified the impact of TR size variation on brain gene regulation across distinct molecular phenotypes, based on 4,412 multi-omics samples from 1,597 donors, including 1,586 newly sequenced ones. We identified ~2.2 million TR molecular quantitative trait loci (TR-xQTLs), linking ~139,000 unique TRs to nearby molecular phenotypes, including many known disease-risk TRs, such as the G2C4 expansion in C9orf72 associated with amyotrophic lateral sclerosis. Fine-mapping revealed ~18,700 TRs as potential causal variants. Our in vitro experiments further confirmed the causal and independent regulatory effects of three TRs. Additional colocalization analysis indicated the potential causal role of TR variation in brain-related phenotypes, highlighted by a 3'-UTR TR in NUDT14 linked to cortical surface area and a TG repeat in PLEKHA1, associated with Alzheimer's disease.

Opposing roles of p38α-mediated phosphorylation and PRMT1-mediated arginine methylation in driving TDP-43 proteinopathy

Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disorder typically characterized by insoluble inclusions of hyperphosphorylated TDP-43. The mechanisms underlying toxic TDP-43 accumulation are not understood. Persistent activation of p38 mitogen-activated protein kinase (MAPK) is implicated in ALS. However, it is unclear how p38 MAPK affects TDP-43 proteinopathy. Here, we show that p38α MAPK inhibition reduces pathological TDP-43 phosphorylation, aggregation, cytoplasmic mislocalization, and neurotoxicity. Remarkably, p38α MAPK inhibition mitigates aberrant TDP-43 phenotypes in diverse ALS patient-derived motor neurons. p38α MAPK phosphorylates TDP-43 at pathological S409/S410 and S292, which reduces TDP-43 liquid-liquid phase separation (LLPS) but allows pathological TDP-43 aggregation. Moreover, we establish that PRMT1 methylates TDP-43 at R293. Importantly, S292 phosphorylation reduces R293 methylation, and R293 methylation reduces S409/S410 phosphorylation. Notably, R293 methylation permits TDP-43 LLPS and reduces pathological TDP-43 aggregation. Thus, strategies to reduce p38α-mediated TDP-43 phosphorylation and promote PRMT1-mediated R293 methylation could have therapeutic utility for ALS and related TDP-43 proteinopathies.

Swift induction of human spinal lower motor neurons and robust ALS cell screening via single-cell imaging

This study introduces a novel method for rapidly and efficiently inducing human spinal lower motor neurons (LMNs) from induced pluripotent stem cells (iPSCs) to eventually elucidate the pathomechanisms of amyotrophic lateral sclerosis (ALS) and facilitate drug screening. Previous methods were limited by low induction efficiency, poor LMN purity, or labor-intensive induction and evaluation processes. Our protocol overcomes these challenges, achieving around 80% induction efficiency within just two weeks by combining a small molecule-based approach with transcription factor transduction. Moreover, to exclude non-LMN cells from the analysis, we utilized time-lapse microscopy and machine learning to analyze the morphology and viability of iPSC-derived LMNs on a single-cell basis, establishing an effective pathophysiological evaluation system. This rapid, efficient, and streamlined protocol, along with our single-cell-based evaluation method, enables large-scale analysis and drug screening using iPSC-derived motor neurons.

Evaluation of a biomarker for amyotrophic lateral sclerosis derived from a hypomethylated DNA signature of human motor neurons

Amyotrophic lateral sclerosis (ALS) lacks a specific biomarker, but is defined by relatively selective toxicity to motor neurons (MN). As others have highlighted, this offers an opportunity to develop a sensitive and specific biomarker based on detection of DNA released from dying MN within accessible biofluids. Here we have performed whole genome bisulfite sequencing (WGBS) of iPSC-derived MN from neurologically normal individuals. By comparing MN methylation with an atlas of tissue methylation we have derived a MN-specific signature of hypomethylated genomic regions, which accords with genes important for MN function. Through simulation we have optimised the selection of regions for biomarker detection in plasma and CSF cell-free DNA (cfDNA). However, we show that MN-derived DNA is not detectable via WGBS in plasma cfDNA. In support of our experimental finding, we show theoretically that the relative sparsity of lower MN sets a limit on the proportion of plasma cfDNA derived from MN which is below the threshold for detection via WGBS. Our findings are important for the ongoing development of ALS biomarkers. The MN-specific hypomethylated genomic regions we have derived could be usefully combined with more sensitive detection methods and perhaps with study of CSF instead of plasma. Indeed we demonstrate that neuronal-derived DNA is detectable in CSF. Our work is relevant for all diseases featuring death of rare cell-types.

Dual-targeting CRISPR-CasRx reduces C9orf72 ALS/FTD sense and antisense repeat RNAs in vitro and in vivo

The most common genetic cause of frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) is an intronic G4C2 repeat expansion in C9orf72. The repeats undergo bidirectional transcription to produce sense and antisense repeat RNA species, which are translated into dipeptide repeat proteins (DPRs). As toxicity has been associated with both sense and antisense repeat-derived RNA and DPRs, targeting both strands may provide the most effective therapeutic strategy. CRISPR-Cas13 systems mature their own guide arrays, allowing targeting of multiple RNA species from a single construct. We show CRISPR-Cas13d variant CasRx effectively reduces overexpressed C9orf72 sense and antisense repeat transcripts and DPRs in HEK cells. In C9orf72 patient-derived iPSC-neuron lines, CRISPR-CasRx reduces endogenous sense and antisense repeat RNAs and DPRs and protects against glutamate-induced excitotoxicity. AAV delivery of CRISPR-CasRx to two distinct C9orf72 repeat mouse models significantly reduced both sense and antisense repeat-containing transcripts. This highlights the potential of RNA-targeting CRISPR systems as therapeutics for C9orf72 ALS/FTD.

Stem Cell Therapy for the Treatment of Amyotrophic Lateral Sclerosis: Comparison of the Efficacy of Mesenchymal Stem Cells, Neural Stem Cells, and Induced Pluripotent Stem Cells

BACKGROUND/OBJECTIVES

Amyotrophic lateral sclerosis (ALS), or Lou Gehrig's disease, is a debilitating, incurable neurodegenerative disorder characterised by motor neuron death in the spinal cord, brainstem, and motor cortex. With an incidence rate of about 4.42 cases per 100,000 people annually, ALS severely impacts motor function and quality of life, causing progressive muscle atrophy, spasticity, paralysis, and eventually death. The cause of ALS is largely unknown, with 90% of cases being sporadic and 10% familial. Current research targets molecular mechanisms of inflammation, excitotoxicity, aggregation-prone proteins, and proteinopathy.

METHODS

This review evaluates the efficacy of three stem cell types in ALS treatment: mesenchymal stem cells (MSCs), neural stem cells (NSCs), and induced pluripotent stem cells (iPSCs).

RESULTS

MSCs, derived from various tissues, show neuroprotective and regenerative qualities, with clinical trials suggesting potential benefits but limited by small sample sizes and non-randomised designs. NSCs, isolated from the fetal spinal cord or brain, demonstrate promise in animal models but face functional integration and ethical challenges. iPSCs, created by reprogramming patient-specific somatic cells, offer a novel approach by potentially replacing or supporting neurons. iPSC therapy addresses ethical issues related to embryonic stem cells but encounters challenges regarding genotoxicity and epigenetic irregularities, somatic cell sources, privacy concerns, the need for extensive clinical trials, and high reprogramming costs.

CONCLUSIONS

This research is significant for advancing ALS treatment beyond symptomatic relief and modest survival extensions to actively modifying disease progression and improving patient outcomes. Successful stem cell therapies could lead to new ALS treatments, slowing motor function loss and reducing symptom severity.

CHMP2B promotes CHMP7 mediated nuclear pore complex injury in sporadic ALS

Alterations to the composition and function of neuronal nuclear pore complexes (NPCs) have been documented in multiple neurodegenerative diseases including Amyotrophic Lateral Sclerosis (ALS). Moreover, recent work has suggested that injury to the NPC can at least in part contribute to TDP-43 loss of function and mislocalization, a pathological hallmark of ALS and related neurodegenerative diseases. Collectively, these studies highlight a role for disruptions in NPC homeostasis and surveillance as a significant pathophysiologic event in neurodegeneration. The ESCRT-III nuclear surveillance pathway plays a critical role in the surveillance and maintenance of NPCs and the surrounding nuclear environment. Importantly, pathologic alterations to this pathway and its protein constituents have been implicated in neurodegenerative diseases such as ALS. However, the mechanism by which this pathway contributes to disease associated alterations in the NPC remains unknown. Here we use an induced pluripotent stem cell (iPSC) derived neuron (iPSN) model of sALS to demonstrate that CHMP7/ESCRT-III nuclear maintenance/surveillance is overactivated in sALS neurons. This overactivation is dependent upon the ESCRT-III protein CHMP2B and sustained CHMP2B dependent "activation" is sufficient to contribute to pathologic CHMP7 nuclear accumulation and POM121 reduction. Importantly, partial knockdown of CHMP2B was sufficient to alleviate NPC injury and downstream TDP-43 dysfunction in sALS neurons thereby highlighting CHMP2B as a potential therapeutic target in disease.

Unlocking therapeutic frontiers: harnessing artificial intelligence in drug discovery for neurodegenerative diseases

Neurodegenerative diseases (NDs) pose serious healthcare challenges with limited therapeutic treatments and high social burdens. The integration of artificial intelligence (AI) into drug discovery has emerged as a promising approach to address these challenges. This review explores the application of AI techniques to unravel therapeutic frontiers for NDs. We examine the current landscape of AI-driven drug discovery and discuss the potentials of AI in accelerating the identification of novel therapeutic targets on ND research and drug development, optimization of drug candidates, and expediating personalized medicine approaches. Finally, we outline future directions and challenges in harnessing AI for the advancement of therapeutics in this critical area by emphasizing the importance of interdisciplinary collaboration and ethical considerations.

Access for ALL in ALS: A large-scale, inclusive, collaborative consortium to unlock the molecular and genetic mechanisms of amyotrophic lateral sclerosis

Recent progress in therapeutics for amyotrophic lateral sclerosis (ALS) has spurred development and imbued the field of ALS with hope for more breakthroughs, yet substantial scientific gaps persist. This unmet need remains a stark reminder that innovative paradigms are needed to invigorate ALS research. To move toward more informative, targeted, and personalized drug development, the National Institutes of Health (NIH) established a national ALS clinical research consortium called Access for ALL in ALS (ALL ALS). This new consortium is a multi-institutional effort that aims to organize the ALS clinical research landscape in the United States. ALL ALS is operating in partnership with several stakeholders to operationalize the recommendations of the Accelerating Access to Critical Therapies for ALS Act (ACT for ALS) Public Private Partnership. ALL ALS will provide a large-scale, centralized, and readily accessible infrastructure for the collection and storage of a wide range of data from people living with ALS (symptomatic cohort) or who may be at risk of developing ALS (asymptomatic ALS gene carriers). Importantly, ALL ALS is designed to encourage community engagement, equity, and inclusion. The consortium is prioritizing the enrollment of geographically, ethnoculturally, and socioeconomically diverse participants. Collected data include longitudinal clinical data and biofluids, genomic, and digital biomarkers that will be harmonized and linked to the central Accelerating Medicines Partnership for ALS (AMP ALS) portal for sharing with the research community. The aim of ALL ALS is to deliver a comprehensive, inclusive, open-science dataset to help researchers answer important scientific questions of clinical relevance in ALS.

Network medicine informed multiomics integration identifies drug targets and repurposable medicines for Amyotrophic Lateral Sclerosis

Amyotrophic Lateral Sclerosis (ALS) is a devastating, immensely complex neurodegenerative disease by lack of effective treatments. We developed a network medicine methodology via integrating human brain multi-omics data to prioritize drug targets and repurposable treatments for ALS. We leveraged non-coding ALS loci effects from genome-wide associated studies (GWAS) on human brain expression quantitative trait loci (QTL) (eQTL), protein QTL (pQTL), splicing QTL (sQTL), methylation QTL (meQTL), and histone acetylation QTL (haQTL). Using a network-based deep learning framework, we identified 105 putative ALS-associated genes enriched in known ALS pathobiological pathways. Applying network proximity analysis of predicted ALS-associated genes and drug-target networks under the human protein-protein interactome (PPI) model, we identified potential repurposable drugs (i.e., Diazoxide and Gefitinib) for ALS. Subsequent validation established preclinical evidence for top-prioritized drugs. In summary, we presented a network-based multi-omics framework to identify drug targets and repurposable treatments for ALS and other neurodegenerative disease if broadly applied.

The Answer ALS return of results study: Answering the duty to disclose

Objective: The Return of Answer ALS Results (RoAR) Study was designed to provide a mechanism for participants in Answer ALS, a large, prospectively designed natural history and biorepository study to receive select clinical genetic testing results and study participants' experience with the results disclosure. Methods: Participants consented to receive results of five ALS genes (C9orf72, SOD1, FUS, TARDP, TBK1) and/or 59 medically actionable genes as designated by the American College of Medical Genetics. Patient-reported genetic testing outcomes were measured via a post-disclosure survey. Results: Of 645 eligible Answer ALS enrollees, 143 (22%) enrolled and completed participation in RoAR. Pathogenic variants were identified in 22/143 (15.4%) participants, including 13/143 (9.0%) in ALS genes and 9/143 (6.3%) in ACMG genes. Participant-reported measures of result utility indicated the research result disclosure was as or more successful than published patient-reported outcomes of result disclosure the clinical setting. Conclusions: This study serves as a model of a "disclosure study" to share results from genomic research with participants who were not initially offered the option to receive results, and our findings can inform the design of future, large scale genomic projects to empower research participants to access their genetic information.

Poly-GR repeats associated with ALS/FTD gene C9ORF72 impair translation elongation and induce a ribotoxic stress response in neurons

Hexanucleotide repeat expansion in the C9ORF72 gene is the most frequent inherited cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). The expansion results in multiple dipeptide repeat proteins, among which arginine-rich poly-GR proteins are highly toxic to neurons and decrease the rate of protein synthesis. We investigated whether the effect on protein synthesis contributes to neuronal dysfunction and degeneration. We found that the expression of poly-GR proteins inhibited global translation by perturbing translation elongation. In iPSC-differentiated neurons, the translation of transcripts with relatively slow elongation rates was further slowed, and stalled, by poly-GR. Elongation stalling increased ribosome collisions and induced a ribotoxic stress response (RSR) mediated by ZAKα that increased the phosphorylation of the kinase p38 and promoted cell death. Knockdown of ZAKα or pharmacological inhibition of p38 ameliorated poly-GR-induced toxicity and improved the survival of iPSC-derived neurons from patients with C9ORF72-ALS/FTD. Our findings suggest that targeting the RSR may be neuroprotective in patients with ALS/FTD caused by repeat expansion in C9ORF72.

Heterozygous knockout of Synaptotagmin13 phenocopies ALS features and TP53 activation in human motor neurons

Spinal motor neurons (MNs) represent a highly vulnerable cellular population, which is affected in fatal neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS) and spinal muscular atrophy (SMA). In this study, we show that the heterozygous loss of SYT13 is sufficient to trigger a neurodegenerative phenotype resembling those observed in ALS and SMA. SYT13+/- hiPSC-derived MNs displayed a progressive manifestation of typical neurodegenerative hallmarks such as loss of synaptic contacts and accumulation of aberrant aggregates. Moreover, analysis of the SYT13+/- transcriptome revealed a significant impairment in biological mechanisms involved in motoneuron specification and spinal cord differentiation. This transcriptional portrait also strikingly correlated with ALS signatures, displaying a significant convergence toward the expression of pro-apoptotic and pro-inflammatory genes, which are controlled by the transcription factor TP53. Our data show for the first time that the heterozygous loss of a single member of the synaptotagmin family, SYT13, is sufficient to trigger a series of abnormal alterations leading to MN sufferance, thus revealing novel insights into the selective vulnerability of this cell population.

Longitudinal comparison of the self-administered ALSFRS-RSE and ALSFRS-R as functional outcome measures in ALS

OBJECTIVE

Test the feasibility, adherence rates and optimal frequency of digital, remote assessments using the ALSFRS-RSE via a customized smartphone-based app.

METHODS

This fully remote, longitudinal study was conducted over a 24-week period, with virtual visits every 3 months and weekly digital assessments. 19 ALS participants completed digital assessments via smartphone, including a digital version of the ALSFRS-RSE and mood survey. Interclass correlation coefficients (ICC) and Bland-Altman plots were used to assess agreement between staff-administered and self-reported ALSFRS-R pairs. Longitudinal change was evaluated using ANCOVA models and linear mixed models, including impact of mood and time of day. Impact of frequency of administration of the ALSFRS-RSE on precision of the estimate slope was tested using a mixed effects model.

RESULTS

In our ALS cohort, digital assessments were well-accepted and adherence was robust, with completion rates of 86%. There was excellent agreement between the digital self-entry and staff-administered scores computing multiple ICCs (ICC range = 0.925-0.961), with scores on the ALSFRS-RSE slightly higher (1.304 points). Digital assessments were associated with increased precision of the slope, resulting in higher standardized response mean estimates for higher frequencies, though benefit appeared to diminish at biweekly and weekly frequency. Effects of participant mood and time of day on total ALSFRS-RSE score were evaluated but were minimal and not statistically significant.

CONCLUSION

Remote collection of digital patient-reported outcomes of functional status such as the ALSFRS-RSE yield more accurate estimates of change over time and provide a broader understanding of the lived experience of people with ALS.

ALS molecular subtypes are a combination of cellular, genetic, and pathological features learned by deep multiomics classifiers

Amyotrophic Lateral Sclerosis (ALS) is a complex syndrome with multiple genetic causes and wide variation in disease presentation. Despite this general heterogeneity, several common factors have been identified. For example, nearly all patients show pathological accumulations of phosphorylated TDP-43 protein in affected regions of the motor cortex and spinal cord. Moreover, large patient cohort studies have revealed that most patient samples can be grouped into a small number of ALS subtypes, as defined by their transcriptomic profiles. These ALS molecular subtypes can be grouped by whether postmortem motor cortex samples display signatures of: mitochondrial dysfunction and oxidative stress (ALS-Ox), microglial activation and neuroinflammation (ALS-Glia), or dense TDP-43 pathology and associated transposable element de-silencing (ALS-TE). In this study, we have built a deep layer ALS neural network classifier (DANcer) that has learned to accurately assign patient samples to these ALS subtypes, and which can be run on either bulk or single-cell datasets. Upon applying this classifier to an expanded ALS patient cohort from the NYGC ALS Consortium, we show that ALS Molecular Subtypes are robust across clinical centers, with no new subtypes appearing in a cohort that has quadrupled in size. Signatures from two of these molecular subtypes strongly correlate with disease duration: ALS-TE signatures in cortex and ALS-Glia signatures in spinal cord, revealing molecular correlates of clinical features. Finally, we use single nucleus RNA sequencing to reveal the cell type-specific contributions to ALS subtype, as determined by our single-cell classifier (scDANCer). Single-cell transcriptomes reveal that ALS molecular subtypes are recapitulated in neurons and glia, with both ALS-wide shared alterations in each cell type as well as ALS subtype-specific alterations. In summary, ALS molecular subtypes: (1) are robust across large cohorts of sporadic and familial ALS patient samples, (2) represent a combination of cellular, genetic, and pathological features, and (3) correlate with clinical features of ALS.

Abstract Figure

Identifying dysregulated regions in amyotrophic lateral sclerosis through chromatin accessibility outliers

The high heritability of amyotrophic lateral sclerosis (ALS) contrasts with its low molecular diagnosis rate post-genetic testing, pointing to potential undiscovered genetic factors. To aid the exploration of these factors, we introduced EpiOut, an algorithm to identify chromatin accessibility outliers that are regions exhibiting divergent accessibility from the population baseline in a single or few samples. Annotation of accessible regions with histone chromatin immunoprecipitation sequencing and Hi-C indicates that outliers are concentrated in functional loci, especially among promoters interacting with active enhancers. Across different omics levels, outliers are robustly replicated, and chromatin accessibility outliers are reliable predictors of gene expression outliers and aberrant protein levels. When promoter accessibility does not align with gene expression, our results indicate that molecular aberrations are more likely to be linked to post-transcriptional regulation rather than transcriptional regulation. Our findings demonstrate that the outlier detection paradigm can uncover dysregulated regions in rare diseases. EpiOut is available at github.com/uci-cbcl/EpiOut.

Sex Differences in Amyotrophic Lateral Sclerosis Survival and Progression: A Multidimensional Analysis

OBJECTIVE

To investigate sex-related differences in amyotrophic lateral sclerosis (ALS) prognosis and their contributing factors.

METHODS

Our primary cohort was the Piemonte and Aosta Register for ALS (PARALS); the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) and the Answer ALS databases were used for validation. Survival analyses were conducted accounting for age and onset site. The roles of forced vital capacity and weight decline were explored through a causal mediation analysis. Survival and disease progression rates were also evaluated after propensity score matching.

RESULTS

The PARALS cohort included 1,890 individuals (44.8% women). Men showed shorter survival when stratified by onset site (spinal onset HR 1.20, 95% CI 1.00-1.44, p = 0.0439; bulbar onset HR 1.36, 95% CI 1.09-1.70, p = 0.006917), although women had a steeper functional decline (+0.10 ALSFRS-R points/month, 95% CI 0.07-0.15, p < 0.00001) regardless of onset site. Instead, men showed worse respiratory decline (-4.2 forced vital capacity%/month, 95% CI -6.3 to -2.2, p < 0.0001) and faster weight loss (-0.15 kg/month, 95% CI -0.25 to -0.05, p = 0.0030). Causal mediation analysis showed that respiratory function and weight loss were pivotal in sex-related survival differences. Analysis of patients from PRO-ACT (n = 1,394, 40.9% women) and Answer ALS (n = 849, 37.2% women) confirmed these trends.

INTERPRETATION

The shorter survival in men is linked to worse respiratory function and weight loss rather than a faster disease progression. These findings emphasize the importance of considering sex-specific factors in understanding ALS pathophysiology and designing tailored therapeutic strategies. ANN NEUROL 2024;96:159-169.

Listener effort quantifies clinically meaningful progression of dysarthria in people living with amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative motor neuron disease that causes progressive muscle weakness. Progressive bulbar dysfunction causes dysarthria and thus social isolation, reducing quality of life. The Everything ALS Speech Study obtained longitudinal clinical information and speech recordings from 292 participants. In a subset of 120 participants, we measured speaking rate (SR) and listener effort (LE), a measure of dysarthria severity rated by speech pathologists from recordings. LE intra- and inter-rater reliability was very high (ICC 0.88 to 0.92). LE correlated with other measures of dysarthria at baseline. LE changed over time in participants with ALS (slope 0.77 pts/month; p<0.001) but not controls (slope 0.005 pts/month; p=0.807). The slope of LE progression was similar in all participants with ALS who had bulbar dysfunction at baseline, regardless of ALS site of onset. LE could be a remotely collected clinically meaningful clinical outcome assessment for ALS clinical trials.

Targeting low levels of MIF expression as a potential therapeutic strategy for ALS

Mutations in SOD1 cause amyotrophic lateral sclerosis (ALS), a neurodegenerative disease characterized by motor neuron (MN) loss. We previously discovered that macrophage migration inhibitory factor (MIF), whose levels are extremely low in spinal MNs, inhibits mutant SOD1 misfolding and toxicity. In this study, we show that a single peripheral injection of adeno-associated virus (AAV) delivering MIF into adult SOD1G37R mice significantly improves their motor function, delays disease progression, and extends survival. Moreover, MIF treatment reduces neuroinflammation and misfolded SOD1 accumulation, rescues MNs, and corrects dysregulated pathways as observed by proteomics and transcriptomics. Furthermore, we reveal low MIF levels in human induced pluripotent stem cell-derived MNs from familial ALS patients with different genetic mutations, as well as in post mortem tissues of sporadic ALS patients. Our findings indicate that peripheral MIF administration may provide a potential therapeutic mechanism for modulating misfolded SOD1 in vivo and disease outcome in ALS patients.

Disease related changes in ATAC-seq of iPSC-derived motor neuron lines from ALS patients and controls

Amyotrophic Lateral Sclerosis (ALS), like many other neurodegenerative diseases, is highly heritable, but with only a small fraction of cases explained by monogenic disease alleles. To better understand sporadic ALS, we report epigenomic profiles, as measured by ATAC-seq, of motor neuron cultures derived from a diverse group of 380 ALS patients and 80 healthy controls. We find that chromatin accessibility is heavily influenced by sex, the iPSC cell type of origin, ancestry, and the inherent variance arising from sequencing. Once these covariates are corrected for, we are able to identify ALS-specific signals in the data. Additionally, we find that the ATAC-seq data is able to predict ALS disease progression rates with similar accuracy to methods based on biomarkers and clinical status. These results suggest that iPSC-derived motor neurons recapitulate important disease-relevant epigenomic changes.

Induced pluripotent stem cells (iPSCs): molecular mechanisms of induction and applications

The induced pluripotent stem cell (iPSC) technology has transformed in vitro research and holds great promise to advance regenerative medicine. iPSCs have the capacity for an almost unlimited expansion, are amenable to genetic engineering, and can be differentiated into most somatic cell types. iPSCs have been widely applied to model human development and diseases, perform drug screening, and develop cell therapies. In this review, we outline key developments in the iPSC field and highlight the immense versatility of the iPSC technology for in vitro modeling and therapeutic applications. We begin by discussing the pivotal discoveries that revealed the potential of a somatic cell nucleus for reprogramming and led to successful generation of iPSCs. We consider the molecular mechanisms and dynamics of somatic cell reprogramming as well as the numerous methods available to induce pluripotency. Subsequently, we discuss various iPSC-based cellular models, from mono-cultures of a single cell type to complex three-dimensional organoids, and how these models can be applied to elucidate the mechanisms of human development and diseases. We use examples of neurological disorders, coronavirus disease 2019 (COVID-19), and cancer to highlight the diversity of disease-specific phenotypes that can be modeled using iPSC-derived cells. We also consider how iPSC-derived cellular models can be used in high-throughput drug screening and drug toxicity studies. Finally, we discuss the process of developing autologous and allogeneic iPSC-based cell therapies and their potential to alleviate human diseases.

Deep learning modeling of rare noncoding genetic variants in human motor neurons defines CCDC146 as a therapeutic target for ALS

Amyotrophic lateral sclerosis (ALS) is a fatal and incurable neurodegenerative disease caused by the selective and progressive death of motor neurons (MNs). Understanding the genetic and molecular factors influencing ALS survival is crucial for disease management and therapeutics. In this study, we introduce a deep learning-powered genetic analysis framework to link rare noncoding genetic variants to ALS survival. Using data from human induced pluripotent stem cell (iPSC)-derived MNs, this method prioritizes functional noncoding variants using deep learning, links cis-regulatory elements (CREs) to target genes using epigenomics data, and integrates these data through gene-level burden tests to identify survival-modifying variants, CREs, and genes. We apply this approach to analyze 6,715 ALS genomes, and pinpoint four novel rare noncoding variants associated with survival, including chr7:76,009,472:C>T linked to CCDC146. CRISPR-Cas9 editing of this variant increases CCDC146 expression in iPSC-derived MNs and exacerbates ALS-specific phenotypes, including TDP-43 mislocalization. Suppressing CCDC146 with an antisense oligonucleotide (ASO), showing no toxicity, completely rescues ALS-associated survival defects in neurons derived from sporadic ALS patients and from carriers of the ALS-associated G4C2-repeat expansion within C9ORF72. ASO targeting of CCDC146 may be a broadly effective therapeutic approach for ALS. Our framework provides a generic and powerful approach for studying noncoding genetics of complex human diseases.

PolyGR and polyPR knock-in mice reveal a conserved neuroprotective extracellular matrix signature in C9orf72 ALS/FTD neurons

Dipeptide repeat proteins are a major pathogenic feature of C9orf72 amyotrophic lateral sclerosis (C9ALS)/frontotemporal dementia (FTD) pathology, but their physiological impact has yet to be fully determined. Here we generated C9orf72 dipeptide repeat knock-in mouse models characterized by expression of 400 codon-optimized polyGR or polyPR repeats, and heterozygous C9orf72 reduction. (GR)400 and (PR)400 knock-in mice recapitulate key features of C9ALS/FTD, including cortical neuronal hyperexcitability, age-dependent spinal motor neuron loss and progressive motor dysfunction. Quantitative proteomics revealed an increase in extracellular matrix (ECM) proteins in (GR)400 and (PR)400 spinal cord, with the collagen COL6A1 the most increased protein. TGF-β1 was one of the top predicted regulators of this ECM signature and polyGR expression in human induced pluripotent stem cell neurons was sufficient to induce TGF-β1 followed by COL6A1. Knockdown of TGF-β1 or COL6A1 orthologues in polyGR model Drosophila exacerbated neurodegeneration, while expression of TGF-β1 or COL6A1 in induced pluripotent stem cell-derived motor neurons of patients with C9ALS/FTD protected against glutamate-induced cell death. Altogether, our findings reveal a neuroprotective and conserved ECM signature in C9ALS/FTD.

Network medicine informed multi-omics integration identifies drug targets and repurposable medicines for Amyotrophic Lateral Sclerosis

Amyotrophic Lateral Sclerosis (ALS) is a devastating, immensely complex neurodegenerative disease by lack of effective treatments. To date, the challenge to establishing effective treatment for ALS remains formidable, partly due to inadequate translation of existing human genetic findings into actionable ALS-specific pathobiology for subsequent therapeutic development. This study evaluates the feasibility of network medicine methodology via integrating human brain-specific multi-omics data to prioritize drug targets and repurposable treatments for ALS. Using human brain-specific genome-wide quantitative trait loci (x-QTLs) under a network-based deep learning framework, we identified 105 putative ALS-associated genes enriched in various known ALS pathobiological pathways, including regulation of T cell activation, monocyte differentiation, and lymphocyte proliferation. Specifically, we leveraged non-coding ALS loci effects from genome-wide associated studies (GWAS) on brain-specific expression quantitative trait loci (QTL) (eQTL), protein QTLs (pQTL), splicing QTL (sQTL), methylation QTL (meQTL), and histone acetylation QTL (haQTL). Applying network proximity analysis of predicted ALS-associated gene-coding targets and existing drug-target networks under the human protein-protein interactome (PPI) model, we identified a set of potential repurposable drugs (including Diazoxide, Gefitinib, Paliperidone, and Dimethyltryptamine) for ALS. Subsequent validation established preclinical and clinical evidence for top-prioritized repurposable drugs. In summary, we presented a network-based multi-omics framework to identify potential drug targets and repurposable treatments for ALS and other neurodegenerative disease if broadly applied.

PolyAMiner-Bulk is a deep learning-based algorithm that decodes alternative polyadenylation dynamics from bulk RNA-seq data

Alternative polyadenylation (APA) is a key post-transcriptional regulatory mechanism; yet, its regulation and impact on human diseases remain understudied. Existing bulk RNA sequencing (RNA-seq)-based APA methods predominantly rely on predefined annotations, severely impacting their ability to decode novel tissue- and disease-specific APA changes. Furthermore, they only account for the most proximal and distal cleavage and polyadenylation sites (C/PASs). Deconvoluting overlapping C/PASs and the inherent noisy 3' UTR coverage in bulk RNA-seq data pose additional challenges. To overcome these limitations, we introduce PolyAMiner-Bulk, an attention-based deep learning algorithm that accurately recapitulates C/PAS sequence grammar, resolves overlapping C/PASs, captures non-proximal-to-distal APA changes, and generates visualizations to illustrate APA dynamics. Evaluation on multiple datasets strongly evinces the performance merit of PolyAMiner-Bulk, accurately identifying more APA changes compared with other methods. With the growing importance of APA and the abundance of bulk RNA-seq data, PolyAMiner-Bulk establishes a robust paradigm of APA analysis.

Induced Pluripotent Stem Cells in Drug Discovery and Neurodegenerative Disease Modelling

Induced pluripotent stem cells (iPSCs) are derived from reprogrammed adult somatic cells. These adult cells are manipulated in vitro to express genes and factors essential for acquiring and maintaining embryonic stem cell (ESC) properties. This technology is widely applied in many fields, and much attention has been given to developing iPSC-based disease models to validate drug discovery platforms and study the pathophysiological molecular processes underlying disease onset. Especially in neurological diseases, there is a great need for iPSC-based technological research, as these cells can be obtained from each patient and carry the individual's bulk of genetic mutations and unique properties. Moreover, iPSCs can differentiate into multiple cell types. These are essential characteristics, since the study of neurological diseases is affected by the limited access to injury sites, the need for in vitro models composed of various cell types, the complexity of reproducing the brain's anatomy, the challenges of postmortem cell culture, and ethical issues. Neurodegenerative diseases strongly impact global health due to their high incidence, symptom severity, and lack of effective therapies. Recently, analyses using disease specific, iPSC-based models confirmed the efficacy of these models for testing multiple drugs. This review summarizes the advances in iPSC technology used in disease modelling and drug testing, with a primary focus on neurodegenerative diseases, including Parkinson's and Alzheimer's diseases.

Counter-regulation of RNA stability by UPF1 and TDP43

RNA quality control is crucial for proper regulation of gene expression. Disruption of nonsense mediated mRNA decay (NMD), the primary RNA decay pathway responsible for the degradation of transcripts containing premature termination codons (PTCs), can disrupt development and lead to multiple diseases in humans and other animals. Similarly, therapies targeting NMD may have applications in hematological, neoplastic and neurological disorders. As such, tools capable of accurately quantifying NMD status could be invaluable for investigations of disease pathogenesis and biomarker identification. Toward this end, we assemble, validate, and apply a next-generation sequencing approach (NMDq) for identifying and measuring the abundance of PTC-containing transcripts. After validating NMDq performance and confirming its utility for tracking RNA surveillance, we apply it to determine pathway activity in two neurodegenerative diseases, amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) characterized by RNA misprocessing and abnormal RNA stability. Despite the genetic and pathologic evidence implicating dysfunctional RNA metabolism, and NMD in particular, in these conditions, we detected no significant differences in PTC-encoding transcripts in ALS models or disease. Contrary to expectations, overexpression of the master NMD regulator UPF1 had little effect on the clearance of transcripts with PTCs, but rather restored RNA homeostasis through differential use and decay of alternatively poly-adenylated isoforms. Together, these data suggest that canonical NMD is not a significant contributor to ALS/FTD pathogenesis, and that UPF1 promotes neuronal survival by regulating transcripts with abnormally long 3'UTRs.

Navigating the Frontiers of Machine Learning in Neurodegenerative Disease Therapeutics

Recent advances in machine learning hold tremendous potential for enhancing the way we develop new medicines. Over the years, machine learning has been adopted in nearly all facets of drug discovery, including patient stratification, lead discovery, biomarker development, and clinical trial design. In this review, we will discuss the latest developments linking machine learning and CNS drug discovery. While machine learning has aided our understanding of chronic diseases like Alzheimer's disease and Parkinson's disease, only modest effective therapies currently exist. We highlight promising new efforts led by academia and emerging biotech companies to leverage machine learning for exploring new therapies. These approaches aim to not only accelerate drug development but to improve the detection and treatment of neurodegenerative diseases.

High-dimensional phenotyping to define the genetic basis of cellular morphology

The morphology of cells is dynamic and mediated by genetic and environmental factors. Characterizing how genetic variation impacts cell morphology can provide an important link between disease association and cellular function. Here, we combine genomic sequencing and high-content imaging approaches on iPSCs from 297 unique donors to investigate the relationship between genetic variants and cellular morphology to map what we term cell morphological quantitative trait loci (cmQTLs). We identify novel associations between rare protein altering variants in WASF2, TSPAN15, and PRLR with several morphological traits related to cell shape, nucleic granularity, and mitochondrial distribution. Knockdown of these genes by CRISPRi confirms their role in cell morphology. Analysis of common variants yields one significant association and nominate over 300 variants with suggestive evidence (P < 10-6) of association with one or more morphology traits. We then use these data to make predictions about sample size requirements for increasing discovery in cellular genetic studies. We conclude that, similar to molecular phenotypes, morphological profiling can yield insight about the function of genes and variants.

Machine learning hypothesis-generation for patient stratification and target discovery in rare disease: our experience with Open Science in ALS

Introduction

Advances in machine learning (ML) methodologies, combined with multidisciplinary collaborations across biological and physical sciences, has the potential to propel drug discovery and development. Open Science fosters this collaboration by releasing datasets and methods into the public space; however, further education and widespread acceptance and adoption of Open Science approaches are necessary to tackle the plethora of known disease states.

Motivation

In addition to providing much needed insights into potential therapeutic protein targets, we also aim to demonstrate that small patient datasets have the potential to provide insights that usually require many samples (>5,000). There are many such datasets available and novel advancements in ML can provide valuable insights from these patient datasets.

Problem statement

Using a public dataset made available by patient advocacy group AnswerALS and a multidisciplinary Open Science approach with a systems biology augmented ML technology, we aim to validate previously reported drug targets in ALS and provide novel insights about ALS subpopulations and potential drug targets using a unique combination of ML methods and graph theory.

Methodology

We use NetraAI to generate hypotheses about specific patient subpopulations, which were then refined and validated through a combination of ML techniques, systems biology methods, and expert input.

Results

We extracted 8 target classes, each comprising of several genes that shed light into ALS pathophysiology and represent new avenues for treatment. These target classes are broadly categorized as inflammation, epigenetic, heat shock, neuromuscular junction, autophagy, apoptosis, axonal transport, and excitotoxicity. These findings are not mutually exclusive, and instead represent a systematic view of ALS pathophysiology. Based on these findings, we suggest that simultaneous targeting of ALS has the potential to mitigate ALS progression, with the plausibility of maintaining and sustaining an improved quality of life (QoL) for ALS patients. Even further, we identified subpopulations based on disease onset.

Conclusion

In the spirit of Open Science, this work aims to bridge the knowledge gap in ALS pathophysiology to aid in diagnostic, prognostic, and therapeutic strategies and pave the way for the development of personalized treatments tailored to the individual's needs.

SUN1 facilitates CHMP7 nuclear influx and injury cascades in sporadic amyotrophic lateral sclerosis

We have recently identified the aberrant nuclear accumulation of the ESCRT-III protein CHMP7 as an initiating event that leads to a significant injury to the nuclear pore complex (NPC) characterized by the reduction of specific nucleoporins from the neuronal NPC in sporadic amyotrophic lateral sclerosis (sALS) and C9orf72 ALS/frontotemporal dementia (FTD)-induced pluripotent stem cell-derived neurons (iPSNs), a phenomenon also observed in post-mortem patient tissues. Importantly, this NPC injury is sufficient to contribute to TDP-43 dysfunction and mislocalization, a common pathological hallmark of neurodegenerative diseases. However, the molecular mechanisms and events that give rise to increased nuclear translocation and/or retention of CHMP7 to initiate this pathophysiological cascade remain largely unknown. Here, using an iPSN model of sALS, we demonstrate that impaired NPC permeability barrier integrity and interactions with the LINC complex protein SUN1 facilitate CHMP7 nuclear localization and the subsequent 'activation' of NPC injury cascades. Collectively, our data provide mechanistic insights in the pathophysiological underpinnings of ALS/FTD and highlight SUN1 as a potent contributor to and modifier of CHMP7-mediated toxicity in sALS pathogenesis.

Highly variable molecular signatures of TDP-43 loss of function are associated with nuclear pore complex injury in a population study of sporadic ALS patient iPSNs

The nuclear depletion and cytoplasmic aggregation of the RNA binding protein TDP-43 is widely considered a pathological hallmark of Amyotrophic Lateral Sclerosis (ALS) and related neurodegenerative diseases. Recent studies have artificially reduced TDP-43 in wildtype human neurons to replicate loss of function associated events. Although this prior work has defined a number of gene expression and mRNA splicing changes that occur in a TDP-43 dependent manner, it is unclear how these alterations relate to authentic ALS where TDP-43 is not depleted from the cell but miscompartmentalized to variable extents. Here, in this population study, we generate ~30,000 qRT-PCR data points spanning 20 genes in induced pluripotent stem cell (iPSC) derived neurons (iPSNs) from >150 control, C9orf72 ALS/FTD, and sALS patients to examine molecular signatures of TDP-43 dysfunction. This data set defines a time dependent and variable profile of individual molecular hallmarks of TDP-43 loss of function within and amongst individual patient lines. Importantly, nearly identical changes are observed in postmortem CNS tissues obtained from a subset of patients whose iPSNs were examined. Notably, these studies provide evidence that induction of nuclear pore complex (NPC) injury via reduction of the transmembrane Nup POM121 in wildtype iPSNs is sufficient to phenocopy disease associated signatured of TDP-43 loss of function thereby directly linking NPC integrity to TDP-43 loss of function. Therapeutically, we demonstrate that the expression of all mRNA species associated with TDP-43 loss of function can be restored in sALS iPSNs via two independent methods to repair NPC injury. Collectively, this data 1) represents a substantial resource for the community to examine TDP-43 loss of function events in authentic sALS patient iPSNs, 2) demonstrates that patient derived iPSNs can accurately reflect actual TDP-43 associated alterations in patient brain, and 3) that targeting NPC injury events can be preclinically and reliably accomplished in an iPSN based platform of a sporadic disease.

Genomic and transcriptomic advances in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder and the most common motor neuron disease. ALS shows substantial clinical and molecular heterogeneity. In vitro and in vivo models coupled with multiomic techniques have provided important contributions to unraveling the pathomechanisms underlying ALS. To date, despite promising results and accumulating knowledge, an effective treatment is still lacking. Here, we provide an overview of the literature on the use of genomics, epigenomics, transcriptomics and microRNAs to deeply investigate the molecular mechanisms developing and sustaining ALS. We report the most relevant genes implicated in ALS pathogenesis, discussing the use of different high-throughput sequencing techniques and the role of epigenomic modifications. Furthermore, we present transcriptomic studies discussing the most recent advances, from microarrays to bulk and single-cell RNA sequencing. Finally, we discuss the use of microRNAs as potential biomarkers and promising tools for molecular intervention. The integration of data from multiple omic approaches may provide new insights into pathogenic pathways in ALS by shedding light on diagnostic and prognostic biomarkers, helping to stratify patients into clinically relevant subgroups, revealing novel therapeutic targets and supporting the development of new effective therapies.

G2C4 targeting antisense oligonucleotides potently mitigate TDP-43 dysfunction in human C9orf72 ALS/FTD induced pluripotent stem cell derived neurons

The G4C2 repeat expansion in the C9orf72 gene is the most common genetic cause of Amyotrophic Lateral Sclerosis and Frontotemporal Dementia. Many studies suggest that dipeptide repeat proteins produced from this repeat are toxic, yet, the contribution of repeat RNA toxicity is under investigated and even less is known regarding the pathogenicity of antisense repeat RNA. Recently, two clinical trials targeting G4C2 (sense) repeat RNA via antisense oligonucleotide failed despite a robust decrease in sense-encoded dipeptide repeat proteins demonstrating target engagement. Here, in this brief report, we show that G2C4 antisense, but not G4C2 sense, repeat RNA is sufficient to induce TDP-43 dysfunction in induced pluripotent stem cell (iPSC) derived neurons (iPSNs). Unexpectedly, only G2C4, but not G4C2 sense strand targeting, ASOs mitigate deficits in TDP-43 function in authentic C9orf72 ALS/FTD patient iPSNs. Collectively, our data suggest that the G2C4 antisense repeat RNA may be an important therapeutic target and provide insights into a possible explanation for the recent G4C2 ASO clinical trial failure.

Transforming drug discovery with a high-throughput AI-powered platform: A 5-year experience with Patrimony

High-throughput computational platforms are being established to accelerate drug discovery. Servier launched the Patrimony platform to harness computational sciences and artificial intelligence (AI) to integrate massive multimodal data from internal and external sources. Patrimony has enabled researchers to prioritize therapeutic targets based on a deep understanding of the pathophysiology of immuno-inflammatory diseases. Herein, we share our experience regarding main challenges and critical success factors faced when industrializing the platform and broadening its applications to neurological diseases. We emphasize the importance of integrating such platforms in an end-to-end drug discovery process and engaging human experts early on to ensure a transforming impact.

Shifting the trajectory of therapeutic development for neurological and psychiatric disorders

Clinical trials for central nervous system disorders often enroll patients with unrecognized heterogeneous diseases, leading to costly trials that have high failure rates. Here, we discuss the potential of emerging technologies and datasets to elucidate disease mechanisms and identify biomarkers to improve patient stratification and monitoring of disease progression in clinical trials for neuropsychiatric disorders. Greater efforts must be centered on rigorously standardizing data collection and sharing of methods, datasets, and analytical tools across sectors. To address health care disparities in clinical trials, diversity of genetic ancestries and environmental exposures of research participants and associated biological samples must be prioritized.

Small molecules targeting different cellular pathologies for the treatment of amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disease in which the motor neuron circuitry displays progressive degeneration, affecting mostly the motor neurons in the brain and in the spinal cord. There are no effective cures, albeit three drugs, riluzole, edaravone, and AMX0035 (a combination of sodium phenylbutyrate and taurursodiol), have been approved by the Food and Drug Administration, with limited improvement in patients. There is an urgent need to build better and more effective treatment strategies for ALS. Since the disease is very heterogenous, numerous approaches have been explored, such as targeting genetic mutations, decreasing oxidative stress and excitotoxicity, enhancing mitochondrial function and protein degradation mechanisms, and inhibiting neuroinflammation. In addition, various chemical libraries or previously identified drugs have been screened for potential repurposing in the treatment of ALS. Here, we review previous drug discovery efforts targeting a variety of cellular pathologies that occur from genetic mutations that cause ALS, such as mutations in SOD1, C9orf72, FUS, and TARDP-43 genes. These mutations result in protein aggregation, which causes neuronal degeneration. Compounds used to target cellular pathologies that stem from these mutations are discussed and comparisons among different preclinical models are presented. Because the drug discovery landscape for ALS and other motor neuron diseases is changing rapidly, we also offer recommendations for a novel, more effective, direction in ALS drug discovery that could accelerate translation of effective compounds from animals to patients.

Evidence-based consensus guidelines for ALS genetic testing and counseling

OBJECTIVE

Advances in amyotrophic lateral sclerosis (ALS) gene discovery, ongoing gene therapy trials, and patient demand have driven increased use of ALS genetic testing. Despite this progress, the offer of genetic testing to persons with ALS is not yet "standard of care." Our primary goal is to develop clinical ALS genetic counseling and testing guidelines to improve and standardize genetic counseling and testing practice among neurologists, genetic counselors or any provider caring for persons with ALS.

METHODS

Core clinical questions were identified and a rapid review performed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA-P) 2015 method. Guideline recommendations were drafted and the strength of evidence for each recommendation was assessed by combining two systems: the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) System and the Evaluation of Genomic Applications in Practice and Prevention (EGAPP). A modified Delphi approach was used to reach consensus among a group of content experts for each guideline statement.

RESULTS

A total of 35 guideline statements were developed. In summary, all persons with ALS should be offered single-step genetic testing, consisting of a C9orf72 assay, along with sequencing of SOD1, FUS, and TARDBP, at a minimum. The key education and genetic risk assessments that should be provided before and after testing are delineated. Specific guidance regarding testing methods and reporting for C9orf72 and other genes is provided for commercial laboratories.

INTERPRETATION

These evidence-based, consensus guidelines will support all stakeholders in the ALS community in navigating benefits and challenges of genetic testing.