Amyotrophic Lateral Sclerosis Clinical Trials Research Articles

Prognostic Clinical and Biological Markers for Amyotrophic Lateral Sclerosis Disease Progression: Validation and Implications for Clinical Trial Design and Analysis.

With increasing recognition of the value of incorporating prognostic markers into amyotrophic lateral sclerosis (ALS) trial design and analysis plans, there is a pressing need to understand which among the prevailing clinical and biochemical markers have real value, and how they can be optimally used. A subset of patients with ALS recruited through the multi-center Phenotype-Genotype-Biomarker study (clinicaltrials.gov: NCT02327845) was identified as "trial-like" based on meeting common trial eligibility criteria. Clinical phenotyping was performed by evaluators trained in relevant assessments. Serum neurofilament light (NfL) and phosphorylated neurofilament heavy (pNfH), urinary p75ECD, plasma microRNA-181, and an array of biochemical and clinical measures were evaluated for their prognostic value. Associations with functional progression were estimated by random-slopes mixed models of ALS functional rating scale-revised (ALSFRS-R) score. Associations with survival were estimated by log-rank test and Cox proportional hazards regression. Potential sample size savings from adjusting for given biomarkers in a hypothetical trial were estimated. Baseline serum NfL is a powerful prognostic biomarker, predicting survival and ALSFRS-R rate of decline. Serum NfL <40pg/ml and >100pg/ml correspond to future ALSFRS-R slopes of ~0.5 and 1.5 points/month, respectively. Serum NfL also adds value to the best available clinical predictors, encapsulated by the European Network to Cure ALS (ENCALS) predictor score. In models of functional decline, the addition of NfL yields ~25% sample size saving above those achieved by inclusion of either clinical predictors or ENCALS score alone. The prognostic value of serum pNfH, urinary p75ECD, and plasma miR-181ab is more limited. Among the multitude of biomarkers considered, only blood NfL adds value to the ENCALS prediction model and should be incorporated into analysis plans for all ongoing and future ALS trials. Defined thresholds of NfL might also be used in trial design, for enrichment or stratified randomisation, to improve trial efficiency. NIH (U01-NS107027, U54-NS092091). ALSA (16-TACL-242).

Cultivating Patient Preferences in ALS Clinical Trials: Reliability and Prognostic Value of the Patient-Ranked Order of Function.

The Patient-Ranked Order of Function (PROOF) is a novel approach to account for patient-reported preferences in the evaluation of treatments of amyotrophic lateral sclerosis (ALS). In this study, we assess the reliability and prognostic value of different sets of patient-reported preferences that can be used for the PROOF end point. Data were obtained through online surveys over the course of 12 months using the population-based registry of the Netherlands. Patients were asked to score functional domains of the ALS Functional Rating Scale (ALSFRS-R) and rank the order of importance of each domain. Two weeks after the initial invite, the questionnaire was repeated to evaluate test-retest reliability. Vital status was extracted from the municipal population register. In total, 611 patients with ALS were followed up for survival and 382 patients were included in the test-retest reliability study. All versions of PROOF, using different sets of preferences, resulted in excellent reliability (intraclass correlation coefficients ranged from 0.89 [95% CI 0.87-0.91] to 0.97 [95% CI 0.97-0.98], all p < 0.001), without systematic differences between baseline and week 2 (mean rank difference range -1 to -3 [95% CI range -8 to 2], all p > 0.20). Preferences about future events were more variable than preferences about current symptoms. All versions of PROOF strongly predicted overall survival (hazard ratios per 10th rank percentile ranged from 0.80 to 0.83 [95% CI range 0.76-0.87], all p < 0.001) and had a more even separation of survival curves between rank-stratified subgroups compared with the ALSFRS-R total score. In a large cohort of patients, we show how patient-reported preferences can be measured and integrated reliably with the ALSFRS-R without leading to systematic bias. Patient preferences may provide unique prognostic information in addition to what is already measured conventionally. This could provide a more comprehensive understanding of how medical interventions effectively address the patient's concerns and improve what matters most to them.

Comparison of Demographics: National Amyotrophic Lateral Sclerosis Registry and Clinical Trials Data.

To characterize the participant demographics in the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) database compared with the web-portal National Amyotrophic Lateral Sclerosis (ALS) Registry (the Registry). Demographics and ALS symptom information were compared between the self-reported registrant data in the Registry web portal (2010-2021) and the latest available PRO-ACT data (updated August 2022), which is a collection of clinical trials data. Greater percentages of younger (≤ 59years old) but smaller percentages of older (60 + years old) participants were represented in PRO-ACT compared to Registry. Enrollment for minority race groups was greater in the Registry portal data, but race information was largely missing/unknown in PRO-ACT database. Median age at the time of diagnosis and age at the time of symptom onset were significantly higher for Registry enrollees compared to the participants of PRO-ACT. Symptom onset sites were similarly reported, but duration between self-noted symptom onset and diagnosis was slight, but significantly longer for the Registry enrollees (11 vs. 9months). Hispanic were as likely as non-Hispanic to participate in research studies, based on the Registry data. There was a notable difference in the age distribution and minority representation of enrollees between the PRO-ACT and Registry study populations. Age distribution in the PRO-ACT database skewed to a younger and less diverse cohort. Despite the clinical heterogeneity and complex disease mechanism of ALS, identifying the underrepresented demographic niche in the PRO-ACT and Registry study populations can help improve patient participation and criteria for patient selection to enhance generalizability.

Multicenter expanded access program for access to investigational products for amyotrophic lateral sclerosis.

Expanded access (EA) is a Food and Drug Administration-regulated pathway to provide access to investigational products (IPs) to individuals with serious diseases who are ineligible for clinical trials. The aim of this report is to share the design and operations of a multicenter, multidrug EA program for amyotrophic lateral sclerosis (ALS) across nine US centers. A central coordination center was established to design and conduct the program. Templated documents and processes were developed to streamline study design, regulatory submissions, and clinical operations across protocols. The program included three protocols and provided access to IPs that were being tested in respective regimens of the HEALEY ALS Platform Trial (verdiperstat, CNM-Au8, and pridopidine). Clinical and safety data were collected in all EA protocols (EAPs). The program cohorts comprised participants who were not eligible for the platform trial, including participants at advanced stages of disease progression and with long disease duration. A total of 85 participants were screened across the 3 EAPs from July 2021 to September 2022. The screen failure rate was 3.5%. Enrollment for the regimens of the platform trial was completed as planned and results informed the duration of the corresponding EAP. The verdiperstat EAP was concluded in December 2022. Mean duration of participation in the verdiperstat EAP was 5.8 ± 4.1 months. The CNM-Au8 and pridopidine EAPs are ongoing. Multicenter EAPs conducted in parallel to randomized clinical trials for ALS can successfully enroll participants who do not qualify for clinical trials.

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.

Categorization of the amyotrophic lateral sclerosis population via the clinical determinant of post-onset ΔFS for study design and medical practice.

The amyotrophic lateral sclerosis (ALS) functional rating scale-revised (ALSFRS-R) has become the most widely utilized measure of disease severity in patients with ALS, with change in ALSFRS-R from baseline being a trusted primary outcome measure in ALS clinical trials. This is despite the scale having several established limitations, and although alternative scales have been proposed, it is unlikely that these will displace ALSFRS-R in the foreseeable future. Here, we discuss the merits of delta FS (ΔFS), the slope or rate of ALSFRS-R decline over time, as a relevant tool for innovative ALS study design, with an as yet untapped potential for optimization of drug effectiveness and patient management. In our view, categorization of the ALS population via the clinical determinant of post-onset ΔFS is an important study design consideration. It serves not only as a critical stratification factor and basis for patient enrichment but also as a tool to explore differences in treatment response across the overall population; thereby, facilitating identification of responder subgroups. Moreover, because post-onset ΔFS is derived from information routinely collected as part of standard patient care and monitoring, it provides a suitable patient selection tool for treating physicians. Overall, post-onset ΔFS is a very attractive enrichment tool that is, can and should be regularly incorporated into ALS trial design.

Apilimod dimesylate in C9orf72 amyotrophic lateral sclerosis: a randomized phase 2a clinical trial.

Apilimod dimesylate is a first-in-class phosphoinositide kinase, FYVE-type zinc finger-containing (PIKfyve) inhibitor with a favourable clinical safety profile and has demonstrated activity in preclinical C9orf72 and TDP-43 amyotrophic lateral sclerosis (ALS) models. In this ALS clinical trial, the safety, tolerability, CNS penetrance and modulation of pharmacodynamic target engagement biomarkers were evaluated. This phase 2a, randomized, double-blind, placebo-controlled, biomarker-end-point clinical trial was conducted in four US centres (ClinicalTrials.gov NCT05163886). Participants with C9orf72 repeat expansions were randomly assigned (2:1) to receive twice-daily oral treatment with 125 mg apilimod dimesylate capsules or matching placebo for 12 weeks, followed by a 12-week open-label extension. Safety was measured as the occurrence of treatment-emergent or serious adverse events attributable to the study drug and tolerability at trial completion or treatment over 12 weeks. Changes from baseline in plasma and CSF and concentrations of apilimod dimesylate and its active metabolites and of pharmacodynamic biomarkers of PIKfyve inhibition [soluble glycoprotein nonmetastatic melanoma protein B (sGPNMB) upregulation] and disease-specific CNS target engagement [poly(GP)] were measured. Between 16 December 2021 and 7 July 2022, 15 eligible participants were enrolled. There were no drug-related serious adverse events reported in the trial. Fourteen (93%) participants completed the double-blind period with 99% dose compliance [n = 9 (90%) apilimod dimesylate; n = 5 (100%) placebo]. At Week 12, apilimod dimesylate was measurable in CSF at 1.63 ng/ml [standard deviation (SD): 0.937]. At Week 12, apilimod dimesylate increased plasma sGPNMB by >2.5-fold (P < 0.001), indicating PIKfyve inhibition, and lowered CSF poly(GP) protein levels by 73% (P < 0.001), indicating CNS tissue-level proof of mechanism. Apilimod dimesylate met prespecified key safety and biomarker end-points in this phase 2a trial and demonstrated CNS penetrance and pharmacodynamic target engagement. Apilimod dimesylate was observed to result in the greatest reduction in CSF poly(GP) levels observed to date in C9orf72 clinical trials.

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

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

Discovery of DNL343: A Potent, Selective, and Brain-Penetrant eIF2B Activator Designed for the Treatment of Neurodegenerative Diseases.

Eukaryotic translation initiation factor 2B (eIF2B) is a key component of the integrated stress response (ISR), which regulates protein synthesis and stress granule formation in response to cellular insult. Modulation of the ISR has been proposed as a therapeutic strategy for treatment of neurodegenerative diseases such as vanishing white matter (VWM) disease and amyotrophic lateral sclerosis (ALS) based on its ability to improve cellular homeostasis and prevent neuronal degeneration. Herein, we report the small-molecule discovery campaign that identified potent, selective, and CNS-penetrant eIF2B activators using both structure- and ligand-based drug design. These discovery efforts culminated in the identification of DNL343, which demonstrated a desirable preclinical drug profile, including a long half-life and high oral bioavailability across preclinical species. DNL343 was progressed into clinical studies and is currently undergoing evaluation in late-stage clinical trials for ALS.

Mismatch between clinically defined classification of ALS stage and the burden of cerebral pathology.

This study aimed to investigate the clinical stratification of amyotrophic lateral sclerosis (ALS) patients in relation to in vivo cerebral degeneration. One hundred forty-nine ALS patients and one hundred forty-four healthy controls (HCs) were recruited from the Canadian ALS Neuroimaging Consortium (CALSNIC). Texture analysis was performed on T1-weighted scans to extract the texture feature "autocorrelation" (autoc), an imaging biomarker of cerebral degeneration. Patients were stratified at baseline into early and advanced disease stages based on criteria adapted from ALS clinical trials and the King's College staging system, as well as into slow and fast progressors (disease progression rates, DPR). Patients had increased autoc in the internal capsule. These changes extended beyond the internal capsule in early-stage patients (clinical trial-based criteria), fast progressors, and in advanced-stage patients (King's staging criteria). Longitudinal increases in autoc were observed in the postcentral gyrus, corticospinal tract, posterior cingulate cortex, and putamen; whereas decreases were observed in corpus callosum, caudate, central opercular cortex, and frontotemporal areas. Both longitudinal increases and decreases of autoc were observed in non-overlapping regions within insula and precentral gyrus. Within-criteria comparisons of autoc revealed more pronounced changes at baseline and longitudinally in early- (clinical trial-based criteria) and advanced-stage (King's staging criteria) patients and fast progressors. In summary, comparative patterns of baseline and longitudinal progression in cerebral degeneration are dependent on sub-group selection criteria, with clinical trial-based stratification insufficiently characterizing disease stage based on pathological cerebral burden.

Use of biomarkers in clinical trials and future developments that will help identify novel biomarkers.

Engineering new solutions for therapeutic benefit in Amyotrophic Lateral Sclerosis (ALS) has proved a difficult task to accomplish. This is largely the reflection of complexities at multiple levels, that require solutions to improve cost-effectiveness and outcomes. The main obstacle related to the condition's clinical heterogeneity, chiefly the broad difference in survival observed among ALS patients, imposes large populations studies and long follow-up to evaluate any efficacy. The emerging solution is composite clinical and biological parameters enabling prognostic stratification into homogeneous phenotypes for more affordable studies. From a therapeutic development perspective, the choice of a medicinal product requires the availability of treatment-specific biomarkers of target engagement to identify off-target effects based on the compound's putative modality of action. More importantly, there are no established biomarkers of treatment response that can complement clinical outcome measures and support futility and end of treatment analyses of efficacy. Ultimately the onus rests on the development of biomarkers encompassing the unmet needs of clinical trial design, from inclusion to efficacy. These readouts of the pathological process may be used in combination with clinical and paraclinical outcome measured, significantly reducing the time and financial burden of clinical studies. Progress towards a biomarker-driven clinical trial design in ALS has been possible thanks to the accurate detection of neurofilaments and of other immunological mediators in biological fluids with the disease progression, a step change enabling the testing of novel therapeutic agents in a new clinical trial setting. However, further progress remains to be made to find treatment specific target engagement biomarkers along with readouts of treatment response that can be reliably applied to all emerging therapies and clinical studies. Here we will cover the basic notions of biomarker development in ALS clinical trials, the most crucial unanswered questions and the unmet needs in the ALS biomarkers space.

Individualized predictions for clinical milestone in amyotrophic lateral sclerosis: A multialgorithmic approach.

The phenotypic heterogeneity and complex disease trajectory complicate the ability to predict specific clinical milestone for individual patients with amyotrophic lateral sclerosis (ALS). Here we developed individualized prediction models to estimate the time to the loss of autonomy in swallowing function. Utilizing the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) database, we built three models of distinct time-to-event prediction algorithms: accelerated failure time (AFT), cox proportional hazard (COX) and random survival forest (RSF) for an individualized risk assessment of the swallowing milestone. The target variable was defined as the time to a decline in the ALSFRS-R swallowing item score to 1 or below, indicating a need for supplementary tube feeding. Internal cross-validation revealed the median concordance index (C-index) of 0.851 (IQR, 0.842-0.859) for AFT, 0.850 (0.841-0.859) for COX and 0.846 (0.839-0.854) for RSF, and all models demonstrated good distributional calibration with predicted and observed event probabilities closely matched across different time intervals. For external validation with a registry dataset with characteristics different from PRO-ACT, the discriminative power was replicated with comparable C-indices for all models, whereas the calibration revealed a left-skewed distribution suggesting a bias towards overestimation of event probabilities in real-world data. While all models were effective at stratifying patients, the results of RSF model, unlike AFT and COX, did not match well with the KM curves of the corresponding risk groups, supporting the importance of nuanced understanding of data structure and algorithmic properties. Our models are implemented into a web application which could be applied to individualized counselling, management and clinical trial design for gastrostomy intervention. Further studies for model optimization will advance personalized care in patients with ALS.

Predicting amyotrophic lateral sclerosis (ALS) progression with machine learning

ObjectiveTo predict ALS progression with varying observation and prediction window lengths, using machine learning (ML).MethodsWe used demographic, clinical, and laboratory parameters from 5030 patients in the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) database to model ALS disease progression as fast (at least 1.5 points decline in ALS Functional Rating Scale-Revised (ALSFRS-R) per month) or non-fast, using Extreme Gradient Boosting (XGBoost) and Bayesian Long Short Term Memory (BLSTM). XGBoost identified predictors of progression while BLSTM provided a confidence level for each prediction.ResultsML models achieved area under receiver-operating-characteristics curve (AUROC) of 0.570-0.748 and were non-inferior to clinician assessments. Performance was similar with observation lengths of a single visit, 3, 6, or 12 months and on a holdout validation dataset, but was better for longer prediction lengths. 21 important predictors were identified, with the top 3 being days since disease onset, past ALSFRS-R and forced vital capacity. Nonstandard predictors included phosphorus, chloride and albumin. BLSTM demonstrated higher performance for the samples about which it was most confident. Patient screening by models may reduce hypothetical Phase II/III clinical trial sizes by 18.3%.ConclusionSimilar accuracies across ML models using different observation lengths suggest that a clinical trial observation period could be shortened to a single visit and clinical trial sizes reduced. Confidence levels provided by BLSTM gave additional information on the trustworthiness of predictions, which could aid decision-making. The identified predictors of ALS progression are potential biomarkers and therapeutic targets for further research.

Relationship between quantitative strength and functional outcomes in the phase 2 FORTITUDE-ALS trial

Objective To assess the relationship among measurements of strength, function, and quality of life in an amyotrophic lateral sclerosis (ALS) clinical trial. Methods In the FORTITUDE-ALS clinical trial (NCT03160898), 456 participants in the full-analysis set were treated with either reldesemtiv or placebo for 12 weeks; this post hoc analysis included all participants regardless of treatment assignments. Assessments included slow vital capacity (SVC), the ALS Functional Rating Scale-Revised (ALSFRS-R), and the 5-item ALS Assessment Questionnaire (ALSAQ-5). Muscle strength was measured quantitatively with hand-held dynamometry, and grip strength with a dedicated dynamometer. The relationship between strength and ALSFRS-R fine and gross motor domain scores, or responses to ALSAQ-5 questions on hand function and walking, was assessed with Spearman’s rank correlation. The relationship between mean upper- or lower-extremity muscle strength and specific ALSFRS-R domains was modeled using principal-components analysis. Results Upper-extremity muscle strength and hand grip were highly correlated with ALSFRS-R fine motor scores and the ALSAQ-5 hand function question. Similarly, lower-extremity strength correlated well with ALSFRS-R gross motor domain and the ALSAQ-5 walking question. For SVC, correlation was poor with the ALSFRS-R respiratory domain, but stronger with the total score, potentially reflecting the insensitivity of the respiratory questions in the scale. Upper- and lower-extremity strength were both strong predictors of ALSFRS-R domain scores. Conclusions In this analysis of data from an ALS clinical trial, muscle strength quantified by dynamometry was strongly correlated with functional capacity. These results suggest that muscle strength directly relates to specific functions of importance to people with ALS.

The natural history of ALS: Baseline characteristics from a multicenter clinical cohort

Background Amyotrophic lateral sclerosis (ALS) is a rare disease with urgent need for improved treatment. Despite the acceleration of research in recent years, there is a need to understand the full natural history of the disease. As only 40% of people living with ALS are eligible for typical clinical trials, clinical trial datasets may not generalize to the full ALS population. While biomarker and cohort studies have more generous inclusion criteria, these too may not represent the full range of phenotypes, particularly if the burden for participation is high. To permit a complete understanding of the heterogeneity of ALS, comprehensive data on the full range of people with ALS is needed. Methods The ALS Natural History Consortium (ALS NHC) consists of nine ALS clinics and was created to build a comprehensive dataset reflective of the ALS population. At each clinic, most patients are asked to participate and about 95% do. After obtaining consent, a minimum dataset is abstracted from each participant’s electronic health record. Participant burden is therefore minimal. Results Data on 1925 ALS patients were submitted as of 9 December 2022. ALS NHC participants were more heterogeneous relative to anonymized clinical trial data from the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) database. The ALS NHC includes ALS patients of older age of onset and a broader distribution of El Escorial categories, than the PRO-ACT database. Conclusions ALS NHC participants had a higher diversity of diagnostic and demographic data compared to ALS clinical trial participants. Key Messages What is already known on this topic: Current knowledge of the natural history of ALS derives largely from regional and national registries that have broad representation of the population of people living with ALS but do not always collect covariates and clinical outcomes. Clinical studies with rich datasets of participant characteristics and validated clinical outcomes have stricter inclusion and exclusion criteria that may not be generalizable to the full ALS population. What this study adds: To bridge this gap, we collected baseline characteristics for a sample of the population of people living with ALS seen at a consortium of ALS clinics that collect extensive, pre-specified participant-level data, including validated outcome measures. How this study might affect research, practice, or policy: A clinic-based longitudinal dataset can improve our understanding of the natural history of ALS and can be used to inform the design and analysis of clinical trials and health economics studies, to help the prediction of clinical course, to find matched controls for open label extension trials and expanded access protocols, and to document real-world evidence of the impact of novel treatments and changes in care practice.

Multimodal MRI improves diagnostic accuracy and sensitivity to longitudinal change in amyotrophic lateral sclerosis

BackgroundRecent advances in MRI acquisitions and image analysis have increased the utility of neuroimaging in understanding disease-related changes. In this work, we aim to demonstrate increased sensitivity to disease progression as well as improved diagnostic accuracy in Amyotrophic lateral sclerosis (ALS) with multimodal MRI of the brain and cervical spinal cord.MethodsWe acquired diffusion MRI data from the brain and cervical cord, and T1 data from the brain, of 20 participants with ALS and 20 healthy control participants. Ten ALS and 14 control participants, and 11 ALS and 13 control participants were re-scanned at 6-month and 12-month follow-ups respectively. We estimated cross-sectional differences and longitudinal changes in diffusion metrics, cortical thickness, and fixel-based microstructure measures, i.e. fiber density and fiber cross-section.ResultsWe demonstrate improved disease diagnostic accuracy and sensitivity through multimodal analysis of brain and spinal cord metrics. The brain metrics also distinguished lower motor neuron-predominant ALS participants from control participants. Fiber density and cross-section provided the greatest sensitivity to longitudinal change. We demonstrate evidence of progression in a cohort of 11 participants with slowly progressive ALS, including in participants with very slow change in ALSFRS-R. More importantly, we demonstrate that longitudinal change is detectable at a six-month follow-up visit. We also report correlations between ALSFRS-R and the fiber density and cross-section metrics.ConclusionsOur findings suggest that multimodal MRI is useful in improving disease diagnosis, and fixel-based measures may serve as potential biomarkers of disease progression in ALS clinical trials.

Development of a Rasch-Built Amyotrophic Lateral Sclerosis Impairment Multidomain Scale to Measure Disease Progression in ALS.

Current scales used in amyotrophic lateral sclerosis (ALS) attempt to summarize different functional domains or "dimensions" into 1 overall score, which may not accurately characterize the individual patient's disease severity or prognosis. The use of composite score risks declaring treatments ineffective if not all dimensions of ALS disease progression are affected equally. We aimed to develop the ALS Impairment Multidomain Scale (AIMS) to comprehensively characterize disease progression and increase the likelihood of identifying effective treatments. The Revised ALS Functional Rating Scale (ALSFRS-R) and a preliminary questionnaire, based on literature review and patient input, were completed online by patients from the Netherlands ALS registry at bimonthly intervals over a period of 12 months. A 2-week test-retest, factor analysis, Rasch analysis, and a signal-to-noise optimization strategy were performed to create a multidomain scale. Reliability, longitudinal decline, and associations with survival were evaluated. The sample size required to detect a 35% reduction in progression rate over 6 or 12 months was assessed for a clinical trial that defines the ALSFRS-R or AIMS subscales as a primary endpoint family. The preliminary questionnaire, consisting of 110 questions, was completed by 367 patients. Three unidimensional subscales were identified, and a multidomain scale was constructed with 7 bulbar, 11 motor, and 5 respiratory questions. Subscales fulfilled Rasch model requirements, with excellent test-retest reliability of 0.91-0.94 and a strong relationship with survival (p < 0.001). Compared with the ALSFRS-R, signal-to-noise ratios were higher as patients declined more uniformly per subscale. Consequently, the estimated sample size reductions achieved with the AIMS compared with those achieved with the ALSFRS-R were 16.3% and 25.9% for 6-month and 12-month clinical trials, respectively. We developed the AIMS, consisting of unidimensional bulbar, motor, and respiratory subscales, which may characterize disease severity better than a total score. AIMS subscales have high test-retest reliability, are optimized to measure disease progression, and are strongly related to survival time. The AIMS can be easily administered and may increase the likelihood of identifying effective treatments in ALS clinical trials.

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

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

Analysis of Amyotrophic Lateral Sclerosis (ALS) Clinical Trials Posted on www.clinicaltrials.gov from 1999–2022. (P10-8.011)

<h3>Objective:</h3> To create a database of Amyotrophic Lateral Sclerosis (ALS) clinical trials on www.clinicaltrials.gov and analyze trends over the past three decades. <h3>Background:</h3> ALS is a progressive neurodegenerative disease of the brain and spinal cord neurons with a typical lifespan of 3–5 years from symptom onset. Clinical trials have evolved over the past three decades as more awareness and research funding have been dedicated to understanding and treating ALS, partially due to the ALS Ice Bucket Challenge in 2014. A review of the evolution of study design and parameters over time provides insights into the future of clinical trials and is reflective of improvements in the science. <h3>Design/Methods:</h3> “ALS” and “Amyotrophic Lateral Sclerosis” were searched on www.clinicaltrial.gov in August 2022. A database was created to capture information on trials: year posted, study type, primary endpoints, and inclusion criteria. <h3>Results:</h3> The term ALS had 777 results and Amyotrophic Lateral Sclerosis had 891 results, for a total of 954 unique clinical trials from 1999 to 2022. Two hundred and seventy-three trials were removed due to non-ALS trials (other neurological disorders, drug name with ALS, or advanced life support) and 681 were analyzed. Thirty-four countries were represented with the United States (n=288, 43%), France (n=71, 11%), and Italy (n=28, 4.1%) having the highest number. The largest number of new trials posted in one year was in 2021 with 81. Forty-eight percent of studies are completed, and 146 (21%) are actively recruiting. Length of time to primary endpoint ranged between one day to ten years. 40% of studies did not specify ALS diagnostic criteria for eligibility and 4% required genetic testing. <h3>Conclusions:</h3> Analyzing current and past trends of ALS clinical trials will help guide future trial designs in the hopes to optimize ALS outcomes and trials. <b>Disclosure:</b> Dr. Zelikovich has nothing to disclose. Eric Anderson has nothing to disclose. Dr. Rubin has received personal compensation in the range of $500-$4,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for NeuroAlert. Dr. Rubin has received personal compensation in the range of $500-$4,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for Merck Manual. Dr. Andrews has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Biogen. Dr. Andrews has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Wave Life Sciences. Dr. Andrews has received personal compensation in the range of $0-$499 for serving as a Consultant for Cytokinetics. Dr. Andrews has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for AL-S Pharma.

Evaluating the Effect of Sodium Phenylbutyrate and Taurursodiol on Survival Outcomes in Amyotrophic Lateral Sclerosis Using a Propensity Score–Matched Cohort From the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) Database (S33.005)

Evaluating the Effect of Sodium Phenylbutyrate and Taurursodiol on Survival Outcomes in Amyotrophic Lateral Sclerosis Using a Propensity Score–Matched Cohort From the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) Database (S33.005)