At-home wearables and machine learning sensitively capture disease progression in amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis causes degeneration of motor neurons, resulting in progressive muscle weakness and impairment in motor function. Promising drug development efforts have accelerated in amyotrophic lateral sclerosis, but are constrained by a lack of objective, sensitive, and accessible outcome measures. Here we investigate the use of wearable sensors, worn on four limbs at home during natural behavior, to quantify motor function and disease progression in 376 individuals with amyotrophic lateral sclerosis. We use an analysis approach that automatically detects and characterizes submovements from passively collected accelerometer data and produces a machine-learned severity score for each limb that is independent of clinical ratings. We show that this approach produces scores that progress faster than the gold standard Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (-0.86 ± 0.70 SD/year versus -0.73 ± 0.74 SD/year), resulting in smaller clinical trial sample size estimates (N = 76 versus N = 121). This method offers an ecologically valid and scalable measure for potential use in amyotrophic lateral sclerosis trials and clinical care.

A machine-learning based objective measure for ALS disease severity.

Amyotrophic Lateral Sclerosis (ALS) disease severity is usually measured using the subjective, questionnaire-based revised ALS Functional Rating Scale (ALSFRS-R). Objective measures of disease severity would be powerful tools for evaluating real-world drug effectiveness, efficacy in clinical trials, and for identifying participants for cohort studies. We developed a machine learning (ML) based objective measure for ALS disease severity based on voice samples and accelerometer measurements from a four-year longitudinal dataset. 584 people living with ALS consented and carried out prescribed speaking and limb-based tasks. 542 participants contributed 5814 voice recordings, and 350 contributed 13,009 accelerometer samples, while simultaneously measuring ALSFRS-R scores. Using these data, we trained ML models to predict bulbar-related and limb-related ALSFRS-R scores. On the test set (n = 109 participants) the voice models achieved a multiclass AUC of 0.86 (95% CI, 0.85-0.88) on speech ALSFRS-R prediction, whereas the accelerometer models achieved a median multiclass AUC of 0.73 on 6 limb-related functions. The correlations across functions observed in self-reported ALSFRS-R scores were preserved in ML-derived scores. We used these models and self-reported ALSFRS-R scores to evaluate the real-world effects of edaravone, a drug approved for use in ALS. In the cohort of 54 test participants who received edaravone as part of their usual care, the ML-derived scores were consistent with the self-reported ALSFRS-R scores. At the individual level, the continuous ML-derived score can capture gradual changes that are absent in the integer ALSFRS-R scores. This demonstrates the value of these tools for assessing disease severity and, potentially, drug effects.

Hypothesis and Theory: Roles of Arginine Methylation in C9orf72-Mediated ALS and FTD.

Hexanucleotide repeat expansion (G4C2n) mutations in the gene C9ORF72 account for approximately 30% of familial cases of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), as well as approximately 7% of sporadic cases of ALS. G4C2n mutations are known to result in the production of five species of dipeptide repeat proteins (DRPs) through non-canonical translation processes. Arginine-enriched dipeptide repeat proteins, glycine-arginine (polyGR), and proline-arginine (polyPR) have been demonstrated to be cytotoxic and deleterious in multiple experimental systems. Recently, we and others have implicated methylation of polyGR/polyPR arginine residues in disease processes related to G4C2n mutation-mediated neurodegeneration. We previously reported that inhibition of asymmetric dimethylation (ADMe) of arginine residues is protective in cell-based models of polyGR/polyPR cytotoxicity. These results are consistent with the idea that PRMT-mediated arginine methylation in the context of polyGR/polyPR exposure is harmful. However, it remains unclear why. Here we discuss the influence of arginine methylation on diverse cellular processes including liquid-liquid phase separation, chromatin remodeling, transcription, RNA processing, and RNA-binding protein localization, and we consider how methylation of polyGR/polyPR may disrupt processes essential for normal cellular function and survival.

Type I PRMT Inhibition Protects Against C9ORF72 Arginine-Rich Dipeptide Repeat Toxicity.

Repeat expansion mutations in the C9ORF72 gene are the most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Repeat-associated non-AUG translation of this expansion produces dipeptide repeat proteins (DRPs). The arginine containing DRPs, polyGR and polyPR, are consistently reported to be the most toxic. Here we demonstrated that small molecule inhibition of type I protein arginine methyltransferases (PRMT) protects against polyGR and polyPR toxicity. Furthermore, our findings suggest that asymmetric dimethylation of polyGR and polyPR by Type I PRMTs plays important roles in their cytotoxicity.

Primary Neurons and Differentiated NSC-34 Cells Are More Susceptible to Arginine-Rich ALS Dipeptide Repeat Protein-Associated Toxicity than Non-Differentiated NSC-34 and CHO Cells.

A repeat expansion mutation in the C9orf72 gene is the most common known genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). In this study, using multiple cell-based assay systems, we reveal both increased dipeptide repeat protein (DRP) toxicity in primary neurons and in differentiated neuronal cell lines. Using flow cytometry and confocal laser scanning microscopy of cells treated with fluorescein isothiocyanate (FITC)-labeled DRPs, we confirm that poly-glycine-arginine (GR) and poly-proline-arginine (PR) DRPs entered cells more readily than poly-glycine-proline (GP) and poly-proline-alanine (PA) DRPs. Our findings suggest that the toxicity of C9-DRPs may be influenced by properties associated with differentiated and aging motor neurons. Further, our findings provide sensitive cell-based assay systems to test phenotypic rescue ability of potential interventions.