Status of ALS Treatment, Insights into Therapeutic Challenges and Dilemmas

Amyotrophic lateral sclerosis (ALS) is an extremely heterogeneous disease of motor neurons that eventually leads to death. Despite impressive advances in understanding the genetic, molecular, and pathological mechanisms of the disease, the only drug approved to date by both the FDA and EMA is riluzole, with a modest effect on survival. In this opinion view paper, we will discuss how to address some challenges for drug development in ALS at the conceptual, technological, and methodological levels. In addition, socioeconomic and ethical issues related to the legitimate need of patients to benefit quickly from new treatments will also be addressed. In conclusion, this brief review takes a more optimistic view, given the recent approval of two new drugs in some countries and the development of targeted gene therapies

Interview de Pierre-Gilles Flacsu

Librairie Chroniques & Chantelivre, Issy-les-Moulineau

Metabolomics Biomarkers: A Strategy Toward Therapeutics Improvement in ALS

Biomarkers research in amyotrophic lateral sclerosis (ALS) holds the promise of improving ALS diagnosis, follow-up of patients, and clinical trials outcomes. Metabolomics have a big impact on biomarkers identification. In this mini-review, we provide the main findings of metabolomics studies in ALS and discuss the most relevant therapeutics attempts that targeted some prominent alterations found in ALS, like glutamate excitotoxicity, oxidative stress, alterations in energetic metabolism, and creatinine levels. Metabolomics studies have reported putative diagnosis or prognosis biomarkers, but discrepancies among these studies did not allow validation of metabolic biomarkers for clinical use in ALS. In this context, we wonder whether metabolomics knowledge could improve ALS therapeutics. As metabolomics identify specific metabolic pathways modified by disease progression and/or treatment, we support that adjuvant or combined treatment should be used to rescue these pathways, creating a new perspective for ALS treatment. Some ongoing clinical trials are already trying to target these pathways. As clinical trials in ALS have been disappointing and considering the heterogeneity of the disease presentation, we support the application of a pharmacometabolomic approach to evaluate the individual response to drug treatments and their side effects, enabling the development of personalized treatments for ALS. We suggest that the best strategy to apply metabolomics for ALS therapeutics progress is to establish a metabolic signature for ALS patients in order to improve the knowledge of patient metabotypes, to choose the most adequate pharmacological treatment, and to follow the drug response and side effects, based on metabolomics biomarkers

Machine Learning in Amyotrophic Lateral Sclerosis: Achievements, Pitfalls, and Future Directions

Background: Amyotrophic Lateral Sclerosis (ALS) is a relentlessly progressive neurodegenerative condition with limited therapeutic options at present. Survival from symptom onset ranges from 3 to 5 years depending on genetic, demographic, and phenotypic factors. Despite tireless research efforts, the core etiology of the disease remains elusive and drug development efforts are confounded by the lack of accurate monitoring markers. Disease heterogeneity, late-stage recruitment into pharmaceutical trials, and inclusion of phenotypically admixed patient cohorts are some of the key barriers to successful clinical trials. Machine Learning (ML) models and large international data sets offer unprecedented opportunities to appraise candidate diagnostic, monitoring, and prognostic markers. Accurate patient stratification into well-defined prognostic categories is another aspiration of emerging classification and staging systems.Methods: The objective of this paper is the comprehensive, systematic, and critical review of ML initiatives in ALS to date and their potential in research, clinical, and pharmacological applications. The focus of this review is to provide a dual, clinical-mathematical perspective on recent advances and future directions of the field. Another objective of the paper is the frank discussion of the pitfalls and drawbacks of specific models, highlighting the shortcomings of existing studies and to provide methodological recommendations for future study designs.Results: Despite considerable sample size limitations, ML techniques have already been successfully applied to ALS data sets and a number of promising diagnosis models have been proposed. Prognostic models have been tested using core clinical variables, biological, and neuroimaging data. These models also offer patient stratification opportunities for future clinical trials. Despite the enormous potential of ML in ALS research, statistical assumptions are often violated, the choice of specific statistical models is seldom justified, and the constraints of ML models are rarely enunciated.Conclusions: From a mathematical perspective, the main barrier to the development of validated diagnostic, prognostic, and monitoring indicators stem from limited sample sizes. The combination of multiple clinical, biofluid, and imaging biomarkers is likely to increase the accuracy of mathematical modeling and contribute to optimized clinical trial designs

Decoding Amyotrophic Lateral Sclerosis: Discovery of Novel Disease-Related Biomarkers and Future Perspectives in Neurodegeneration

Amyotrophic lateral sclerosis (ALS) belongs to the group of motor neuron diseases, in which the degeneration, the weakness of voluntary muscles, and death of motor neurons gradually spread along disease progression. ALS comes from Greek language and means “no muscle nourishment” (“amyotrophic”), “area of the spinal cord where affected nerve cells are localized” (“lateral”), and “the degeneration and hardening of the spinal cord” (“sclerosis”). The fundamental contributions of the celebrated neurologist Jean-Martin Charcot at the end of the nineteenth century provided the first description of ALS...

Spinal cord ischemia revealed by a Brown-Sequard syndrome and caused by a calcified thoracic disc extrusion with spontaneous regression: a case report and review of the literature

Background: Thoracic disc herniation is relatively uncommon, accounting for less than 1% of all spinal herniations. Although most often asymptomatic, they may represent a rare cause of spinal cord ischemia. Case report: We report the case of a healthy 43-year-old North African male who presented with a Brown-Sequard syndrome revealing a spinal cord ischemia caused by a thoracic disc extrusion. The initial MRI revealed a calcified disc extrusion at the level of T5-T6 without significant spinal cord compression or signal abnormality. A pattern consistent with a medullary ischemia only appeared 48 h later. The patient was treated conservatively with Aspirin and Heparin, which were discontinued later because of a negative cardiovascular work-up. The calcified disc extrusion, which was later recognized as the cause of the ischemia, decreased spontaneously over time and the patient recovered within a few months. Conclusions: Our case highlights the challenge in diagnosing and managing this uncommon condition. We propose a literature review showing the different therapeutic strategies and their corresponding clinical outcomes

Motor imagery in amyotrophic lateral Sclerosis: An fMRI study of postural control

BACKGROUND: The functional reorganization of brain networks sustaining gait is poorly characterized in amyotrophic lateral sclerosis (ALS) despite ample evidence of progressive disconnection between brain regions. The main objective of this fMRI study is to assess gait imagery-specific networks in ALS patients using dynamic causal modeling (DCM) complemented by parametric empirical Bayes (PEB) framework. METHOD: Seventeen lower motor neuron predominant (LMNp) ALS patients, fourteen upper motor neuron predominant (UMNp) ALS patients and fourteen healthy controls participated in this study. Each subject performed a dual motor imagery task: normal and precision gait. The Movement Imagery Questionnaire (MIQ-rs) and imagery time (IT) were used to evaluate gait imagery in each participant. In a neurobiological computational model, the circuits involved in imagined gait and postural control were investigated by modelling the relationship between normal/precision gait and connection strengths. RESULTS: Behavioral results showed significant increase in IT in UMNp patients compared to healthy controls (P(corrected) < 0.05) and LMNp (P(corrected) < 0.05). During precision gait, healthy controls activate the model's circuits involved in the imagined gait and postural control. In UMNp, decreased connectivity (inhibition) from basal ganglia (BG) to supplementary motor area (SMA) and from SMA to posterior parietal cortex (PPC) is observed. Contrary to healthy controls, DCM detects no cerebellar-PPC connectivity in neither UMNp nor LMNp ALS. During precision gait, bilateral connectivity (excitability) between SMA and BG is observed in the LMNp group contrary to UMNp and healthy controls. CONCLUSIONS: Our findings demonstrate the utility of implementing both DCM and PEB to characterize connectivity patterns in specific patient phenotypes. Our approach enables the identification of specific circuits involved in postural deficits, and our findings suggest a putative excitatory–inhibitory imbalance. More broadly, our data demonstrate how clinical manifestations are underpinned by network-specific disconnection phenomena in ALS

The Neurotoxicity of Vesicles Secreted by ALS Patient Myotubes Is Specific to Exosome-Like and Not Larger Subtypes

Extracellular vesicles can mediate communication between tissues, affecting the physiological conditions of recipient cells. They are increasingly investigated in Amyotrophic Lateral Sclerosis, the most common form of Motor Neurone Disease, as transporters of misfolded proteins including SOD1, FUS, TDP43, or other neurotoxic elements, such as the dipeptide repeats resulting from C9orf72 expansions. EVs are classified based on their biogenesis and size and can be separated by differential centrifugation. They include exosomes, released by the fusion of multivesicular bodies with the plasma membrane, and ectosomes, also known as microvesicles or microparticles, resulting from budding or pinching of the plasma membrane. In the current study, EVs were obtained from the myotube cell culture medium of ALS patients or healthy controls. EVs of two different sizes, separating at 20,000 or 100,000 g, were then compared in terms of their effects on recipient motor neurons, astrocytes, and myotubes. Compared to untreated cells, the smaller, exosome-like vesicles of ALS patients reduced the survival of motor neurons by 31% and of myotubes by 18%, decreased neurite length and branching, and increased the proportion of stellate astrocytes, whereas neither those of healthy subjects, nor larger EVs of ALS or healthy subjects, had such effects

The Neurotoxicity of Vesicles Secreted by ALS Patient Myotubes Is Specific to Exosome-Like and Not Larger Subtypes

Extracellular vesicles can mediate communication between tissues, affecting the physiological conditions of recipient cells. They are increasingly investigated in Amyotrophic Lateral Sclerosis, the most common form of Motor Neurone Disease, as transporters of misfolded proteins including SOD1, FUS, TDP43, or other neurotoxic elements, such as the dipeptide repeats resulting from C9orf72 expansions. EVs are classified based on their biogenesis and size and can be separated by differential centrifugation. They include exosomes, released by the fusion of multivesicular bodies with the plasma membrane, and ectosomes, also known as microvesicles or microparticles, resulting from budding or pinching of the plasma membrane. In the current study, EVs were obtained from the myotube cell culture medium of ALS patients or healthy controls. EVs of two different sizes, separating at 20,000 or 100,000 g, were then compared in terms of their effects on recipient motor neurons, astrocytes, and myotubes. Compared to untreated cells, the smaller, exosome-like vesicles of ALS patients reduced the survival of motor neurons by 31% and of myotubes by 18%, decreased neurite length and branching, and increased the proportion of stellate astrocytes, whereas neither those of healthy subjects, nor larger EVs of ALS or healthy subjects, had such effects