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

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.

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.

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.

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.

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.

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.

Single-molecule imaging reveals distinct elongation and frameshifting dynamics between frames of expanded RNA repeats in C9ORF72-ALS/FTD

C9ORF72 hexanucleotide repeat expansion is the most common genetic cause of both amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). One pathogenic mechanism is the accumulation of toxic dipeptide repeat (DPR) proteins like poly-GA, GP and GR, produced by the noncanonical translation of the expanded RNA repeats. However, how different DPRs are synthesized remains elusive. Here, we use single-molecule imaging techniques to directly measure the translation dynamics of different DPRs. Besides initiation, translation elongation rates vary drastically between different frames, with GP slower than GA and GR the slowest. We directly visualize frameshift events using a two-color single-molecule translation assay. The repeat expansion enhances frameshifting, but the overall frequency is low. There is a higher chance of GR-to-GA shift than in the reversed direction. Finally, the ribosome-associated protein quality control (RQC) factors ZNF598 and Pelota modulate the translation dynamics, and the repeat RNA sequence is important for invoking the RQC pathway. This study reveals that multiple translation steps modulate the final DPR production. Understanding repeat RNA translation is critically important to decipher the DPR-mediated pathogenesis and identify potential therapeutic targets in C9ORF72-ALS/FTD.

Multiomics and machine-learning identify novel transcriptional and mutational signatures in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis is a fatal and incurable neurodegenerative disease that mainly affects the neurons of the motor system. Despite the increasing understanding of its genetic components, their biological meanings are still poorly understood. Indeed, it is still not clear to which extent the pathological features associated with amyotrophic lateral sclerosis are commonly shared by the different genes causally linked to this disorder. To address this point, we combined multiomics analysis covering the transcriptional, epigenetic and mutational aspects of heterogenous human induced pluripotent stem cell-derived C9orf72-, TARDBP-, SOD1- and FUS-mutant motor neurons as well as datasets from patients' biopsies. We identified a common signature, converging towards increased stress and synaptic abnormalities, which reflects a unifying transcriptional program in amyotrophic lateral sclerosis despite the specific profiles due to the underlying pathogenic gene. In addition, whole genome bisulphite sequencing linked the altered gene expression observed in mutant cells to their methylation profile, highlighting deep epigenetic alterations as part of the abnormal transcriptional signatures linked to amyotrophic lateral sclerosis. We then applied multi-layer deep machine-learning to integrate publicly available blood and spinal cord transcriptomes and found a statistically significant correlation between their top predictor gene sets, which were significantly enriched in toll-like receptor signalling. Notably, the overrepresentation of this biological term also correlated with the transcriptional signature identified in mutant human induced pluripotent stem cell-derived motor neurons, highlighting novel insights into amyotrophic lateral sclerosis marker genes in a tissue-independent manner. Finally, using whole genome sequencing in combination with deep learning, we generated the first mutational signature for amyotrophic lateral sclerosis and defined a specific genomic profile for this disease, which is significantly correlated to ageing signatures, hinting at age as a major player in amyotrophic lateral sclerosis. This work describes innovative methodological approaches for the identification of disease signatures through the combination of multiomics analysis and provides novel knowledge on the pathological convergencies defining amyotrophic lateral sclerosis.

Applications of multi-omics analysis in human diseases

Multi-omics usually refers to the crossover application of multiple high-throughput screening technologies represented by genomics, transcriptomics, single-cell transcriptomics, proteomics and metabolomics, spatial transcriptomics, and so on, which play a great role in promoting the study of human diseases. Most of the current reviews focus on describing the development of multi-omics technologies, data integration, and application to a particular disease; however, few of them provide a comprehensive and systematic introduction of multi-omics. This review outlines the existing technical categories of multi-omics, cautions for experimental design, focuses on the integrated analysis methods of multi-omics, especially the approach of machine learning and deep learning in multi-omics data integration and the corresponding tools, and the application of multi-omics in medical researches (e.g., cancer, neurodegenerative diseases, aging, and drug target discovery) as well as the corresponding open-source analysis tools and databases, and finally, discusses the challenges and future directions of multi-omics integration and application in precision medicine. With the development of high-throughput technologies and data integration algorithms, as important directions of multi-omics for future disease research, single-cell multi-omics and spatial multi-omics also provided a detailed introduction. This review will provide important guidance for researchers, especially who are just entering into multi-omics medical research.

A Diagnostic Gene-Expression Signature in Fibroblasts of Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a fatal, progressive neurodegenerative disease with limited treatment options. Diagnosis can be difficult due to the heterogeneity and non-specific nature of the initial symptoms, resulting in delays that compromise prompt access to effective therapeutic strategies. Transcriptome profiling of patient-derived peripheral cells represents a valuable benchmark in overcoming such challenges, providing the opportunity to identify molecular diagnostic signatures. In this study, we characterized transcriptome changes in skin fibroblasts of sporadic ALS patients (sALS) and controls and evaluated their utility as a molecular classifier for ALS diagnosis. Our analysis identified 277 differentially expressed transcripts predominantly involved in transcriptional regulation, synaptic transmission, and the inflammatory response. A support vector machine classifier based on this 277-gene signature was developed to discriminate patients with sALS from controls, showing significant predictive power in both the discovery dataset and in six independent publicly available gene expression datasets obtained from different sALS tissue/cell samples. Taken together, our findings support the utility of transcriptional signatures in peripheral cells as valuable biomarkers for the diagnosis of ALS.

Generation of isogenic and homozygous MEN1 mutant cell lines from patient-derived iPSCs using CRISPR/Cas9

MEN1, an autosomal dominant disorder caused by mutations in the tumor suppressor gene MEN1, manifests with co-occurrence of multiple endocrine/neuroendocrine neoplasms. An iPSC line derived from an index patient carrying the mutation c.1273C>T (p.Arg465*) was edited using a single multiplex CRISPR/Cas approach to create an isogenic control non-mutated line and a homozygous double mutant line. These cell lines will be useful for elucidating subcellular MEN1 pathophysiology and for screening to identify potential MEN1 therapeutic targets.

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.

Integrated transcriptome landscape of ALS identifies genome instability linked to TDP-43 pathology

Amyotrophic Lateral Sclerosis (ALS) causes motor neuron degeneration, with 97% of cases exhibiting TDP-43 proteinopathy. Elucidating pathomechanisms has been hampered by disease heterogeneity and difficulties accessing motor neurons. Human induced pluripotent stem cell-derived motor neurons (iPSMNs) offer a solution; however, studies have typically been limited to underpowered cohorts. Here, we present a comprehensive compendium of 429 iPSMNs from 15 datasets, and 271 post-mortem spinal cord samples. Using reproducible bioinformatic workflows, we identify robust upregulation of p53 signalling in ALS in both iPSMNs and post-mortem spinal cord. p53 activation is greatest with C9orf72 repeat expansions but is weakest with SOD1 and FUS mutations. TDP-43 depletion potentiates p53 activation in both post-mortem neuronal nuclei and cell culture, thereby functionally linking p53 activation with TDP-43 depletion. ALS iPSMNs and post-mortem tissue display enrichment of splicing alterations, somatic mutations, and gene fusions, possibly contributing to the DNA damage response.

Large-scale differentiation of iPSC-derived motor neurons from ALS and control subjects

Using induced pluripotent stem cells (iPSCs) to understand the mechanisms of neurological disease holds great promise; however, there is a lack of well-curated lines from a large array of participants. Answer ALS has generated over 1,000 iPSC lines from control and amyotrophic lateral sclerosis (ALS) patients along with clinical and whole-genome sequencing data. The current report summarizes cell marker and gene expression in motor neuron cultures derived from 92 healthy control and 341 ALS participants using a 32-day differentiation protocol. This is the largest set of iPSCs to be differentiated into motor neurons, and characterization suggests that cell composition and sex are significant sources of variability that need to be carefully controlled for in future studies. These data are reported as a resource for the scientific community that will utilize Answer ALS data for disease modeling using a wider array of omics being made available for these samples.

Induced Pluripotent Stem Cells and Their Applications in Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease that results in the loss of motor function in the central nervous system (CNS) and ultimately death. The mechanisms underlying ALS pathogenesis have not yet been fully elucidated, and ALS cannot be treated effectively. Most studies have applied animal or single-gene intervention cell lines as ALS disease models, but they cannot accurately reflect the pathological characteristics of ALS. Induced pluripotent stem cells (iPSCs) can be reprogrammed from somatic cells, possessing the ability to self-renew and differentiate into a variety of cells. iPSCs can be obtained from ALS patients with different genotypes and phenotypes, and the genetic background of the donor cells remains unchanged during reprogramming. iPSCs can differentiate into neurons and glial cells related to ALS. Therefore, iPSCs provide an excellent method to evaluate the impact of diseases on ALS patients. Moreover, patient-derived iPSCs are obtained from their own somatic cells, avoiding ethical concerns and posing only a low risk of immune rejection. The iPSC technology creates new hope for ALS treatment. Here, we review recent studies on iPSCs and their applications in disease modeling, drug screening and cell therapy in ALS, with a particular focus on the potential for ALS treatment.

Neurodegeneration cell per cell

The clinical definition of neurodegenerative diseases is based on symptoms that reflect terminal damage of specific brain regions. This is misleading as it tells little about the initial disease processes. Circuitry failures that underlie the clinical symptomatology are themselves preceded by clinically mostly silent, slowly progressing multicellular processes that trigger or are triggered by the accumulation of abnormally folded proteins such as Aβ, Tau, TDP-43, and α-synuclein, among others. Methodological advances in single-cell omics, combined with complex genetics and novel ways to model complex cellular interactions using induced pluripotent stem (iPS) cells, make it possible to analyze the early cellular phase of neurodegenerative disorders. This will revolutionize the way we study those diseases and will translate into novel diagnostics and cell-specific therapeutic targets, stopping these disorders in their early track before they cause difficult-to-reverse damage to the brain.

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.

Genetics of amyotrophic lateral sclerosis: seeking therapeutic targets in the era of gene therapy

Amyotrophic lateral sclerosis (ALS) is an intractable disease that causes respiratory failure leading to mortality. The main locus of ALS is motor neurons. The success of antisense oligonucleotide (ASO) therapy in spinal muscular atrophy (SMA), a motor neuron disease, has triggered a paradigm shift in developing ALS therapies. The causative genes of ALS and disease-modifying genes, including those of sporadic ALS, have been identified one after another. Thus, the freedom of target choice for gene therapy has expanded by ASO strategy, leading to new avenues for therapeutic development. Tofersen for superoxide dismutase 1 (SOD1) was a pioneer in developing ASO for ALS. Improving protocols and devising early interventions for the disease are vital. In this review, we updated the knowledge of causative genes in ALS. We summarized the genetic mutations identified in familial ALS and their clinical features, focusing on SOD1, fused in sarcoma (FUS), and transacting response DNA-binding protein. The frequency of the C9ORF72 mutation is low in Japan, unlike in Europe and the United States, while SOD1 and FUS are more common, indicating that the target mutations for gene therapy vary by ethnicity. A genome-wide association study has revealed disease-modifying genes, which could be the novel target of gene therapy. The current status and prospects of gene therapy development were discussed, including ethical issues. Furthermore, we discussed the potential of axonal pathology as new therapeutic targets of ALS from the perspective of early intervention, including intra-axonal transcription factors, neuromuscular junction disconnection, dysregulated local translation, abnormal protein degradation, mitochondrial pathology, impaired axonal transport, aberrant cytoskeleton, and axon branching. We simultaneously discuss important pathological states of cell bodies: persistent stress granules, disrupted nucleocytoplasmic transport, and cryptic splicing. The development of gene therapy based on the elucidation of disease-modifying genes and early intervention in molecular pathology is expected to become an important therapeutic strategy in ALS.

Identification of potential pathways and biomarkers linked to progression in ALS

OBJECTIVE

To identify potential diagnostic and prognostic biomarkers for clinical management and clinical trials in amyotrophic lateral sclerosis.

METHODS

We analysed proteomics data of ALS patient-induced pluripotent stem cell-derived motor neurons available through the AnswerALS consortium. After stratifying patients using clinical ALSFRS-R and ALS-CBS scales, we identified differentially expressed proteins indicative of ALS disease severity and progression rate as candidate ALS-related and prognostic biomarkers. Pathway analysis for identified proteins was performed using STITCH. Protein sets were correlated with the effects of drugs using the Connectivity Map tool to identify compounds likely to affect similar pathways. RNAi screening was performed in a Drosophila TDP-43 ALS model to validate pathological relevance. A statistical classification machine learning model was constructed using ridge regression that uses proteomics data to differentiate ALS patients from controls.

RESULTS

We identified 76, 21, 71 and 1 candidate ALS-related biomarkers and 22, 41, 27 and 64 candidate prognostic biomarkers from patients stratified by ALSFRS-R baseline, ALSFRS-R progression slope, ALS-CBS baseline and ALS-CBS progression slope, respectively. Nineteen proteins enhanced or suppressed pathogenic eye phenotypes in the ALS fly model. Nutraceuticals, dopamine pathway modulators, statins, anti-inflammatories and antimicrobials were predicted starting points for drug repurposing using the connectivity map tool. Ten diagnostic biomarker proteins were predicted by machine learning to identify ALS patients with high accuracy and sensitivity.

INTERPRETATION

This study showcases the powerful approach of iPSC-motor neuron proteomics combined with machine learning and biological confirmation in the prediction of novel mechanisms and diagnostic and predictive biomarkers in ALS.

PolyAMiner-Bulk: A Machine Learning Based Bioinformatics Algorithm to Infer and Decode Alternative Polyadenylation Dynamics from bulk RNA-seq data

More than half of human genes exercise alternative polyadenylation (APA) and generate mRNA transcripts with varying 3' untranslated regions (UTR). However, current computational approaches for identifying cleavage and polyadenylation sites (C/PASs) and quantifying 3'UTR length changes from bulk RNA-seq data fail to unravel tissue- and disease-specific APA dynamics. Here, we developed a next-generation bioinformatics algorithm and application, PolyAMiner-Bulk, that utilizes an attention-based machine learning architecture and an improved vector projection-based engine to infer differential APA dynamics accurately. When applied to earlier studies, PolyAMiner-Bulk accurately identified more than twice the number of APA changes in an RBM17 knockdown bulk RNA-seq dataset compared to current generation tools. Moreover, on a separate dataset, PolyAMiner-Bulk revealed novel APA dynamics and pathways in scleroderma pathology and identified differential APA in a gene that was identified as being involved in scleroderma pathogenesis in an independent study. Lastly, we used PolyAMiner-Bulk to analyze the RNA-seq data of post-mortem prefrontal cortexes from the ROSMAP data consortium and unraveled novel APA dynamics in Alzheimer's Disease. Our method, PolyAMiner-Bulk, creates a paradigm for future alternative polyadenylation analysis from bulk RNA-seq data.

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.

NeuroLINCS Proteomics: Defining human-derived iPSC proteomes and protein signatures of pluripotency

The National Institute of Health (NIH) Library of integrated network-based cellular signatures (LINCS) program is premised on the generation of a publicly available data resource of cell-based biochemical responses or "signatures" to genetic or environmental perturbations. NeuroLINCS uses human inducible pluripotent stem cells (hiPSCs), derived from patients and healthy controls, and differentiated into motor neuron cell cultures. This multi-laboratory effort strives to establish i) robust multi-omic workflows for hiPSC and differentiated neuronal cultures, ii) public annotated data sets and iii) relevant and targetable biological pathways of spinal muscular atrophy (SMA) and amyotrophic lateral sclerosis (ALS). Here, we focus on the proteomics and the quality of the developed workflow of hiPSC lines from 6 individuals, though epigenomics and transcriptomics data are also publicly available. Known and commonly used markers representing 73 proteins were reproducibly quantified with consistent expression levels across all hiPSC lines. Data quality assessments, data levels and metadata of all 6 genetically diverse human iPSCs analysed by DIA-MS are parsable and available as a high-quality resource to the public.

ALSFRS-R-SE: an adapted, annotated, and self-explanatory version of the revised amyotrophic lateral sclerosis functional rating scale

BACKGROUND

The ALS Functional Rating Scale in its revised version (ALSFRS-R) is a disease-specific severity score that reflects motor impairment and functional deterioration in people with amyotrophic lateral sclerosis (ALS). It has been widely applied in both clinical practice and ALS research. However, in Germany, several variants of the scale, each differing slightly from the others, have developed over time and are currently in circulation. This lack of uniformity potentially hampers data interpretation and may decrease item validity. Furthermore, shortcomings within the standard ALSFRS-R questions and answer options can limit the quality and conclusiveness of collected data.

METHODS

In a multistage consensus-building process, 18 clinical ALS experts from the German ALS/MND network analyzed the ALSFRS-R in its current form and created an adapted, annotated, and revised scale that closely adheres to the well-established standardized English version.

RESULTS

Ten German-language variants of the ALSFRS-R were collected, three of which contained instructions for self-assessment. All of these variants were compiled and a comprehensive linguistic revision was undertaken. A short introduction was added to the resulting scale, comprising general instructions for use and explanations for each of the five reply options per item. This adapted version of the scale, named ALSFRS-R-SE (with the "SE" referring to "self-explanatory"), was carefully reviewed for language and comprehensibility, in both German and English.

CONCLUSION

An adapted and annotated version of the ALSFRS-R scale was developed through a multistage consensus process. The decision to include brief explanations of specific scale items and reply options was intended to facilitate ALSFRS-R-SE assessments by both healthcare professionals and patients. Further studies are required to investigate the accuracy and utility of the ALSFRS-R-SE in controlled trials and clinical real-world settings.

A guide to multi-omics data collection and integration for translational medicine

The emerging high-throughput technologies have led to the shift in the design of translational medicine projects towards collecting multi-omics patient samples and, consequently, their integrated analysis. However, the complexity of integrating these datasets has triggered new questions regarding the appropriateness of the available computational methods. Currently, there is no clear consensus on the best combination of omics to include and the data integration methodologies required for their analysis. This article aims to guide the design of multi-omics studies in the field of translational medicine regarding the types of omics and the integration method to choose. We review articles that perform the integration of multiple omics measurements from patient samples. We identify five objectives in translational medicine applications: (i) detect disease-associated molecular patterns, (ii) subtype identification, (iii) diagnosis/prognosis, (iv) drug response prediction, and (v) understand regulatory processes. We describe common trends in the selection of omic types combined for different objectives and diseases. To guide the choice of data integration tools, we group them into the scientific objectives they aim to address. We describe the main computational methods adopted to achieve these objectives and present examples of tools. We compare tools based on how they deal with the computational challenges of data integration and comment on how they perform against predefined objective-specific evaluation criteria. Finally, we discuss examples of tools for downstream analysis and further extraction of novel insights from multi-omics datasets.

An alternative splicing modulator decreases mutant HTT and improves the molecular fingerprint in Huntington's disease patient neurons

Huntington's disease (HD) is a neurodegenerative disorder caused by poly-Q expansion in the Huntingtin (HTT) protein. Here, we delineate elevated mutant HTT (mHTT) levels in patient-derived cells including fibroblasts and iPSC derived cortical neurons using mesoscale discovery (MSD) HTT assays. HD patients' fibroblasts and cortical neurons recapitulate aberrant alternative splicing as a molecular fingerprint of HD. Branaplam is a splicing modulator currently tested in a phase II study in HD (NCT05111249). The drug lowers total HTT (tHTT) and mHTT levels in fibroblasts, iPSC, cortical progenitors, and neurons in a dose dependent manner at an IC₅₀ consistently below 10 nM without inducing cellular toxicity. Branaplam promotes inclusion of non-annotated novel exons. Among these Branaplam-induced exons, there is a 115 bp frameshift-inducing exon in the HTT transcript. This exon is observed upon Branaplam treatment in Ctrl and HD patients leading to a profound reduction of HTT RNA and protein levels. Importantly, Branaplam ameliorates aberrant alternative splicing in HD patients' fibroblasts and cortical neurons. These findings highlight the applicability of splicing modulators in the treatment of CAG repeat disorders and decipher their molecular effects associated with the pharmacokinetic and -dynamic properties in patient-derived cellular models.

Safety and tolerability of bosutinib in patients with amyotrophic lateral sclerosis (iDReAM study): A multicentre, open-label, dose-escalation phase 1 trial

BACKGROUND

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease caused by the loss of motor neurons, and development of effective medicines is urgently required. Induced pluripotent stem cell (iPSC)-based drug repurposing identified the Src/c-Abl inhibitor bosutinib, which is approved for the treatment of chronic myelogenous leukemia (CML), as a candidate for the molecular targeted therapy of ALS.

METHODS

An open-label, multicentre, dose-escalation phase 1 study using a 3 + 3 design was conducted in 4 hospitals in Japan to evaluate the safety and tolerability of bosutinib in patients with ALS. Furthermore, the exploratory efficacy was evaluated using Revised ALS Functional Rating Scale (ALSFRS-R), predictive biomarkers including plasma neurofilament light chain (NFL) were explored, and single-cell RNA sequencing of iPSC-derived motor neurons was conducted. Patients, whose total ALSFRS-R scores decreased by 1-3 points during the 12-week, received escalating doses starting from 100 mg quaque die (QD) up to 400 mg QD based on dose-limiting toxicity (DLT) occurrence, and all participants who received one dose of the study drug were included in the primary analysis. This trial is registered with ClinicalTrials.gov, NCT04744532, as Induced pluripotent stem cell-based Drug Repurposing for Amyotrophic Lateral Sclerosis Medicine (iDReAM) study.

FINDINGS

Between March 29, 2019 and May 7, 2021, 20 patients were enrolled, 13 of whom received bosutinib treatment and 12 were included in the safety and efficacy analyses. No DLTs were observed up to 300 mg QD, but DLTs were observed in 3/3 patients of the 400 mg QD cohort. In all patients receiving 100 mg-400 mg, the prevalent adverse events (AEs) were gastrointestinal AEs in 12 patients (92.3%), liver function related AEs in 7 patients (53.8%), and rash in 3 patients (23.1%). The safety profile was consistent with that known for CML treatment, and ALS-specific AEs were not observed. A subset of patients (5/9 patients) was found to respond well to bosutinib treatment over the 12-week treatment period. It was found that the treatment-responsive patients could be distinguished by their lower levels of plasma NFL. Furthermore, single-cell RNA sequencing of iPSC-derived motor neurons revealed the pathogenesis related molecular signature in patients with ALS showing responsiveness to bosutinib.

INTERPRETATION

This is the first trial of a Src/c-Abl inhibitor, bosutinib, for patients with ALS. The safety and tolerability of bosutinib up to 300 mg, not 400 mg, in ALS were described, and responsiveness of patients on motor function was observed. Since this was an open-label trial within a short period with a limited number of patients, further clinical trials will be required.

FUNDING

AMED and iPS Cell Research Fund.

Intravenous edaravone treatment in ALS and survival: An exploratory, retrospective, administrative claims analysis

BACKGROUND

We aimed to evaluate overall survival in US patients with amyotrophic lateral sclerosis (ALS) treated with intravenous (IV) edaravone compared with those not treated with IV edaravone in a real-world setting.

METHODS

This exploratory retrospective comparative effectiveness observational analysis included patients with ALS who were enrolled in an administrative claims database from 8 August 2017 to 31 March 2020. Propensity score matching identified IV edaravone-treated patients (cases) and non-edaravone-treated patients (controls) matched for covariates: age, race, geographic region, sex, pre-index disease duration, insurance, history of cardiovascular disease, riluzole prescription, gastrostomy tube placement, artificial nutrition, noninvasive ventilation, and all-cause hospitalisation. For cases, the index date was the date of the first claim for IV edaravone. For controls, it was the date IV edaravone was available (8 August 2017). The effect of IV edaravone on all-cause mortality was estimated with shared frailty Cox regression analysis.

FINDINGS

318 cases were matched to 318 controls. In both groups, 208 patients (65.4%) had a history of riluzole prescription. As of 31 March 2021, there were 155 deaths (48.7%) among the cases and 196 among the controls (61.6%). Median overall survival time was 29.5 months with edaravone and 23.5 months without, respectively, and the risk of death was 27% lower in cases than in controls (HR, 0.73; 95% CI, 0.59-0.91; p=0.005).

INTERPRETATION

In this real-world analysis, IV edaravone treatment in a large predominantly riluzole-treated US cohort was associated with prolonged overall survival compared with not using IV edaravone. Data from adequately powered RCTs are needed to support this finding.

FUNDING

Funded by Mitsubishi Tanabe Pharma America.

Nutrition and stem cell integrity in aging

Adult stem cells (SCs) represent the regenerative capacity of organisms throughout their lifespan. The maintenance of robust SC populations capable of renewing organs and physiological systems is one hallmark of healthy aging. The local environment of SCs, referred to as the niche, includes the nutritional milieu, which is essential to maintain the quantity and quality of SCs available for renewal and regeneration. There is increased recognition that SCs have unique metabolism and conditional nutrient needs compared to fully differentiated cells. However, the contribution of SC nutrition to overall human nutritional requirements is an understudied and underappreciated area of investigation. Nutrient needs vary across the lifespan and are modified by many factors including individual health, disease, physiological states including pregnancy, age, sex, and during recovery from injury. Although current nutrition guidance is generally derived for apparently healthy populations and to prevent nutritional deficiency diseases, there are increased efforts to establish nutrient-based and food-based recommendations based on reducing chronic disease. Understanding the dynamics of SC nutritional needs throughout the life span, including the role of nutrition in extending biological age by blunting biological systems decay, is fundamental to establishing food and nutrient guidance for chronic disease reduction and health maintenance. This review summarizes a 3-day symposium of the Marabou Foundation (www.marabousymposium.org) held to examine the metabolic properties and unique nutritional needs of adult SCs and their role in healthy aging and age-related chronic disease.

Poly(ADP-ribose) promotes toxicity of C9ORF72 arginine-rich dipeptide repeat proteins

Arginine-rich dipeptide repeat proteins (R-DPRs), abnormal translational products of a GGGGCC hexanucleotide repeat expansion in C9ORF72, play a critical role in C9ORF72-related amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), the most common genetic form of the disorders (c9ALS/FTD). R-DPRs form liquid condensates in vitro, induce stress granule formation in cultured cells, aggregate, and sometimes coaggregate with TDP-43 in postmortem tissue from patients with c9ALS/FTD. However, how these processes are regulated is unclear. Here, we show that loss of poly(ADP-ribose) (PAR) suppresses neurodegeneration in c9ALS/FTD fly models and neurons differentiated from patient-derived induced pluripotent stem cells. Mechanistically, PAR induces R-DPR condensation and promotes R-DPR-induced stress granule formation and TDP-43 aggregation. Moreover, PAR associates with insoluble R-DPR and TDP-43 in postmortem tissue from patients. These findings identified PAR as a promoter of R-DPR toxicity and thus a potential target for treating c9ALS/FTD.

Effects of PB‐TURSO on the transcriptional and metabolic landscape of sporadic ALS fibroblasts

Objective

Methods

Results

Interpretation

Considerations for Amyotrophic Lateral Sclerosis (ALS) Clinical Trial Design

Thoughtful clinical trial design is critical for efficient therapeutic development, particularly in the field of amyotrophic lateral sclerosis (ALS), where trials often aim to detect modest treatment effects among a population with heterogeneous disease progression. Appropriate outcome measure selection is necessary for trials to provide decisive and informative results. Investigators must consider the outcome measure's reliability, responsiveness to detect change when change has actually occurred, clinical relevance, and psychometric performance. ALS clinical trials can also be performed more efficiently by utilizing statistical enrichment techniques. Innovations in ALS prediction models allow for selection of participants with less heterogeneity in disease progression rates without requiring a lead-in period, or participants can be stratified according to predicted progression. Statistical enrichment can reduce the needed sample size and improve study power, but investigators must find a balance between optimizing statistical efficiency and retaining generalizability of study findings to the broader ALS population. Additional progress is still needed for biomarker development and validation to confirm target engagement in ALS treatment trials. Selection of an appropriate biofluid biomarker depends on the treatment mechanism of interest, and biomarker studies should be incorporated into early phase trials. Inclusion of patients with ALS as advisors and advocates can strengthen clinical trial design and study retention, but more engagement efforts are needed to improve diversity and equity in ALS research studies. Another challenge for ALS therapeutic development is identifying ways to respect patient autonomy and improve access to experimental treatment, something that is strongly desired by many patients with ALS and ALS advocacy organizations. Expanded access programs that run concurrently to well-designed and adequately powered randomized controlled trials may provide an opportunity to broaden access to promising therapeutics without compromising scientific integrity or rushing regulatory approval of therapies without adequate proof of efficacy.

Aberrant NOVA1 function disrupts alternative splicing in early stages of amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a fatal disease characterized by aberrant alternative splicing (AS). Nuclear loss and cytoplasmic accumulation of the splicing factor TDP-43 in motor neurons (MN) are hallmarks of ALS at late stages of the disease. However, it is unknown if altered AS is present before TDP-43 pathology occurs. Here, we investigate altered AS and its origins in early stages of ALS using human induced pluripotent stem cell-derived motor neurons (MNs) from sporadic and familial ALS patients. We find high levels of the RNA-binding proteins NOVA1, NOVA2, and RBFOX2 in the insoluble protein fractions and observe that AS events in ALS-associated MNs are enriched for binding sites of these proteins. Our study points to an early disrupted function of NOVA1 that drives AS changes in a complex fashion, including events caused by a consistent loss of NOVA1 function. NOVA1 exhibits increased cytoplasmic protein levels in early stage MNs without TDP-43 pathology in ALS postmortem tissue. As nuclear TDP-43 protein level depletes, NOVA1 is reduced. Potential indications for a reduction of NOVA1 also came from mice over-expressing TDP-43 lacking its nuclear localization signal and iPSC-MN stressed with puromycin. This study highlights that additional RBP-RNA perturbations in ALS occur in parallel to TDP-43.

Identification of Therapeutic Targets for Amyotrophic Lateral Sclerosis Using PandaOmics – An AI-Enabled Biological Target Discovery Platform

Amyotrophic lateral sclerosis (ALS) is a severe neurodegenerative disease with ill-defined pathogenesis, calling for urgent developments of new therapeutic regimens. Herein, we applied PandaOmics, an AI-driven target discovery platform, to analyze the expression profiles of central nervous system (CNS) samples (237 cases; 91 controls) from public datasets, and direct iPSC-derived motor neurons (diMNs) (135 cases; 31 controls) from Answer ALS. Seventeen high-confidence and eleven novel therapeutic targets were identified and will be released onto ALS.AI (http://als.ai/). Among the proposed targets screened in the c9ALS Drosophila model, we verified 8 unreported genes (KCNB2, KCNS3, ADRA2B, NR3C1, P2RY14, PPP3CB, PTPRC, and RARA) whose suppression strongly rescues eye neurodegeneration. Dysregulated pathways identified from CNS and diMN data characterize different stages of disease development. Altogether, our study provides new insights into ALS pathophysiology and demonstrates how AI speeds up the target discovery process, and opens up new opportunities for therapeutic interventions.