Plasma neurofilament light levels show elevation two years prior to diagnosis of amyotrophic lateral sclerosis in the UK Biobank.

Objective: Amyotrophic lateral sclerosis (ALS) is a debilitating neurodegenerative disease with profound unmet need. In patients carrying genetic mutations, elevations in neurofilament light (NfL) have been shown to precede symptom onset, however, the natural history of NfL in general ALS patients is less characterized.

Methods: We performed a secondary analysis of the UK Biobank Pharma Proteomics Project (UKB-PPP), a subset of the UK Biobank, a population-based cohort study in the United Kingdom, to examine plasma NfL levels in 237 participants subsequently diagnosed with ALS.

Electrical impedance myography detects dystrophin-related muscle changes in mdx mice.

Background: The lack of functional dystrophin protein in Duchenne muscular dystrophy (DMD) causes chronic skeletal muscle inflammation and degeneration. Therefore, the restoration of functional dystrophin levels is a fundamental approach for DMD therapy. Electrical impedance myography (EIM) is an emerging tool that provides noninvasive monitoring of muscle conditions and has been suggested as a treatment response biomarker in diverse indications.

Using a smartwatch and smartphone to assess early Parkinson's disease in the WATCH-PD study.

Digital health technologies can provide continuous monitoring and objective, real-world measures of Parkinson's disease (PD), but have primarily been evaluated in small, single-site studies. In this 12-month, multicenter observational study, we evaluated whether a smartwatch and smartphone application could measure features of early PD. 82 individuals with early, untreated PD and 50 age-matched controls wore research-grade sensors, a smartwatch, and a smartphone while performing standardized assessments in the clinic.

Urine titin as a novel biomarker for Duchenne muscular dystrophy.

Duchenne muscular dystrophy (DMD) is the most severe form of muscular dystrophy that is caused by lack of dystrophin, a critical structural protein in skeletal muscle. DMD treatments, and quantitative biomarkers to assess the efficacy of potential treatments, are urgently needed. Previous evidence has shown that titin, a muscle cell protein, is increased in the urine of patients with DMD, suggesting its usefulness as a DMD biomarker.

Qualitative measures that assess functional disability and quality of life in ALS.

Background: Selection of appropriate trial endpoints and outcome measures is particularly important in rare disease and rapidly progressing disease such as amyotrophic lateral sclerosis (ALS) where the challenges to conducting clinical trials, are substantial: patient and disease heterogeneity, limited understanding of exact disease pathophysiology, and lack of robust and available biomarkers. To address these challenges in ALS, the Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised version (ALSFRS-R) was developed and has become a key primary endpoint in ALS clinical trials to assess functional disability and disease progression, often replacing survival as a primary outcome. However, increased understanding of the ALS disease journey and improvements in assistive technology for ALS patients have exposed issues with the ALSFRS-R, including non-linearity, multidimensionality and floor and ceiling effects that could challenge its continued utility as a primary outcome measure in ALS clinical trials.

A Descriptive Review of Global Real World Evidence Efforts to Advance Drug Discovery and Clinical Development in Amyotrophic Lateral Sclerosis.

Understanding patient clinical progression is a key gateway to planning effective clinical trials and ultimately enabling bringing treatments to patients in need. In a rare disease like amyotrophic lateral sclerosis (ALS), studies of disease natural history critically depend on collaboration between clinical centers, regions, and countries to enable creation of platforms to allow patients, caregivers, clinicians, and researchers to come together and more fully understand the condition. Rare disease registries and collaborative platforms such as those developed in ALS collect real-world data (RWD) in standardized formats, including clinical and biological specimen data used to evaluate risk factors and natural history of disease, treatment patterns and clinical (ClinROs) and patient- reported outcomes (PROs) and validate novel endpoints.

ALSUntangled 59: Tamoxifen.

Here we use the ALSUntangled methodology to review Tamoxifen as an ALS treatment. We show that it has plausible mechanisms, a positive preclinical study, a case report and 2 small trials suggesting benefits. We show that it appears reasonably safe, though there is a small risk of developing cancer with long term use.

Precompetitive Consensus Building to Facilitate the Use of Digital Health Technologies to Support Parkinson Disease Drug Development through Regulatory Science.

Innovative tools are urgently needed to accelerate the evaluation and subsequent approval of novel treatments that may slow, halt, or reverse the relentless progression of Parkinson disease (PD). Therapies that intervene early in the disease continuum are a priority for the many candidates in the drug development pipeline. There is a paucity of sensitive and objective, yet clinically interpretable, measures that can capture meaningful aspects of the disease.

Design and analysis of a clinical trial using previous trials as historical control.

Background/aims: For single arm trials, a treatment is evaluated by comparing an outcome estimate to historically reported outcome estimates. Such a is often analyzed as if the estimates from previous trials were known without variation and there is no trial-to-trial variation in their estimands. We develop a test of treatment efficacy and sample size calculation for historically controlled trials that considers these sources of variation.

Stratification of amyotrophic lateral sclerosis patients: a crowdsourcing approach.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease where substantial heterogeneity in clinical presentation urgently requires a better stratification of patients for the development of drug trials and clinical care. In this study we explored stratification through a crowdsourcing approach, the DREAM Prize4Life ALS Stratification Challenge. Using data from >10,000 patients from ALS clinical trials and 1479 patients from community-based patient registers, more than 30 teams developed new approaches for machine learning and clustering, outperforming the best current predictions of disease outcome.

Invasive Hemodynamic Monitoring of Aortic and Pulmonary Artery Hemodynamics in a Large Animal Model of ARDS.

One of the leading causes of morbidity and mortality in patients with heart failure is right ventricular (RV) dysfunction, especially if it is due to pulmonary hypertension. For a better understanding and treatment of this disease, precise hemodynamic monitoring of left and right ventricular parameters is important. For this reason, it is essential to establish experimental pig models of cardiac hemodynamics and measurements for research purpose.

Laquinimod Treatment Improves Myelination Deficits at the Transcriptional and Ultrastructural Levels in the YAC128 Mouse Model of Huntington Disease.

Laquinimod, an immunomodulatory agent under clinical development for Huntington disease (HD), has recently been shown to confer behavioural improvements that are coupled with prevention of atrophy of the white matter (WM)-rich corpus callosum (CC) in the YAC128 HD mice. However, the nature of the WM improvements is not known yet. Here we investigated the effects of laquinimod on HD-related myelination deficits at the cellular, molecular and ultrastructural levels.

Predicting disease progression in amyotrophic lateral sclerosis.

Objective: It is essential to develop predictive algorithms for Amyotrophic Lateral Sclerosis (ALS) disease progression to allow for efficient clinical trials and patient care. The best existing predictive models rely on several months of baseline data and have only been validated in clinical trial research datasets. We asked whether a model developed using clinical research patient data could be applied to the broader ALS population typically seen at a tertiary care ALS clinic.

Epidemiology of Amyotrophic Lateral Sclerosis: A Population-Based Study in Israel.

Background: Globally, the annual incidence and prevalence of amyotrophic lateral sclerosis (ALS) are estimated at 1.9 and 4.5 per 100,000 population, respectively.

Big data to smart data in Alzheimer's disease: Real-world examples of advanced modeling and simulation.

Many disease-modifying clinical development programs in Alzheimer's disease (AD) have failed to date, and development of new and advanced preclinical models that generate actionable knowledge is desperately needed. This review reports on computer-based modeling and simulation approach as a powerful tool in AD research. Statistical data-analysis techniques can identify associations between certain data and phenotypes, such as diagnosis or disease progression.

Item response theory analysis of the Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised in the Pooled Resource Open-Access ALS Clinical Trials Database.

Our objective was to examine dimensionality and item-level performance of the Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-R) across time using classical and modern test theory approaches. Confirmatory factor analysis (CFA) and Item Response Theory (IRT) analyses were conducted using data from patients with amyotrophic lateral sclerosis (ALS) Pooled Resources Open-Access ALS Clinical Trials (PRO-ACT) database with complete ALSFRS-R data (n = 888) at three time-points (Time 0, Time 1 (6-months), Time 2 (1-year)). Results demonstrated that in this population of 888 patients, mean age was 54.

Being PRO-ACTive: What can a Clinical Trial Database Reveal About ALS?

Advancing research and clinical care, and conducting successful and cost-effective clinical trials requires characterizing a given patient population. To gather a sufficiently large cohort of patients in rare diseases such as amyotrophic lateral sclerosis (ALS), we developed the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) platform. The PRO-ACT database currently consists of >8600 ALS patient records from 17 completed clinical trials, and more trials are being incorporated.

Crowdsourced analysis of clinical trial data to predict amyotrophic lateral sclerosis progression.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with substantial heterogeneity in its clinical presentation. This makes diagnosis and effective treatment difficult, so better tools for estimating disease progression are needed. Here, we report results from the DREAM-Phil Bowen ALS Prediction Prize4Life challenge.

The PRO-ACT database: design, initial analyses, and predictive features.

Objective: To pool data from completed amyotrophic lateral sclerosis (ALS) clinical trials and create an open-access resource that enables greater understanding of the phenotype and biology of ALS.

Methods: Clinical trials data were pooled from 16 completed phase II/III ALS clinical trials and one observational study. Over 8 million de-identified longitudinally collected data points from over 8,600 individuals with ALS were standardized across trials and merged to create the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) database.

Multiple kernel learning captures a systems-level functional connectivity biomarker signature in amyotrophic lateral sclerosis.

There is significant clinical and prognostic heterogeneity in the neurodegenerative disorder amyotrophic lateral sclerosis (ALS), despite a common immunohistological signature. Consistent extra-motor as well as motor cerebral, spinal anterior horn and distal neuromuscular junction pathology supports the notion of ALS a system failure. Establishing a disease biomarker is a priority but a simplistic, coordinate-based approach to brain dysfunction using MRI is not tenable.

Single neurons in M1 and premotor cortex directly reflect behavioral interference.

Some motor tasks, if learned together, interfere with each other's consolidation and subsequent retention, whereas other tasks do not. Interfering tasks are said to employ the same internal model whereas noninterfering tasks use different models. The division of function among internal models, as well as their possible neural substrates, are not well understood.

Emergence of novel representations in primary motor cortex and premotor neurons during associative learning.

Neurons in the motor areas of cortex play a key role in associating sensory instructions with movements. However, their ability to acquire and maintain representations of novel stimulus features, especially when these features are behaviorally relevant, remains unknown. We investigated neuronal changes in these areas during and after associative learning, by training monkeys on a novel reaching task that required associating target colors with movement directions.

Segregation between acquisition and long-term memory in sensorimotor learning.

It is widely accepted that learning first involves generating new memories and then consolidating them into long-term memory. Thus learning is generally viewed as a single continuous process with two sequential stages; acquisition and consolidation. Here, we tested an alternative hypothesis proposing that acquisition and consolidation take place, at least partly, in parallel.