Personalized Medicine and Molecular Interaction Networks in Amyotrophic Lateral Sclerosis (ALS): Current Knowledge

Synucleinopathy in Amyotrophic Lateral Sclerosis: A Potential Avenue for Antisense Therapeutics?

Amyotrophic lateral sclerosis (ALS) is the most common adult-onset motor neuron disease classified as both a neurodegenerative and neuromuscular disorder. With a complex aetiology and no current cure for ALS, broadening the understanding of disease pathology and therapeutic avenues is required to progress with patient care. Alpha-synuclein (αSyn) is a hallmark for disease in neurodegenerative disorders, such as Parkinson's disease, Lewy body dementia, and multiple system atrophy. A growing body of evidence now suggests that αSyn may also play a pathological role in ALS, with αSyn-positive Lewy bodies co-aggregating alongside known ALS pathogenic proteins, such as SOD1 and TDP-43. This review endeavours to capture the scope of literature regarding the aetiology and development of ALS and its commonalities with "synucleinopathy disorders". We will discuss the involvement of αSyn in ALS and motor neuron disease pathology, and the current theories and strategies for therapeutics in ALS treatment, as well as those targeting αSyn for synucleinopathies, with a core focus on small molecule RNA technologies.

Exosomes in Ageing and Motor Neurone Disease: Biogenesis, Uptake Mechanisms, Modifications in Disease and Uses in the Development of Biomarkers and Therapeutics

Intercellular communication between neurons and their surrounding cells occurs through the secretion of soluble molecules or release of vesicles such as exosomes into the extracellular space, participating in brain homeostasis. Under neuro-degenerative conditions associated with ageing, such as amyotrophic lateral sclerosis (ALS), Alzheimer's or Parkinson's disease, exosomes are suspected to propagate toxic proteins. The topic of this review is the role of exosomes in ageing conditions and more specifically in ALS. Our current understanding of exosomes and exosome-related mechanisms is first summarized in a general sense, including their biogenesis and secretion, heterogeneity, cellular interaction and intracellular fate. Their role in the Central Nervous System (CNS) and ageing of the neuromotor system is then considered in the context of exosome-induced signaling. The review then focuses on exosomes in age-associated neurodegenerative disease. The role of exosomes in ALS is highlighted, and their use as potential biomarkers to diagnose and prognose ALS is presented. The therapeutic implications of exosomes for ALS are considered, whether as delivery vehicles, neurotoxic targets or as corrective drugs in and of themselves. A diverse set of mechanisms underpin the functional roles, both confirmed and potential, of exosomes, generally in ageing and specifically in motor neurone disease. Aspects of their contents, biogenesis, uptake and modifications offer many plausible routes towards the development of novel biomarkers and therapeutics.

Patient Flows, Patient Distribution Computations and Medicines Accounting in the Pharmacoeconomic Models Through Procurement Perspective

Purpose

Stimulating cost reduction of pharmaceutical companies to optimize the structure of distribution of patients by the level of treatment costs in various programs.

Patients and Methods

In this article, we rise up the issues of pharmacoeconomic modeling related to the description of the patient flows in the pharmacoeconomic model and methods to determining the course dose of drugs under the restriction of integer computations. We established two possible ways of distributing patients through treatment regimens in pharmacoeconomic models, also analyzed the effects of simultaneous and uniform entry of patients into the model. Also, we considered the limitations and possibilities of calculations based on the active substance and packaging, as well as the transition factor of the remainder of the drug in the next time period.

Results

A mathematical model of the analysis of the system assessment of patients by the level of risk of abandoning a healthy lifestyle in connection with the growing problems of the difficult-to-control process is developed. The use of a rational data convolution mode allowed us to obtain a criterion for the optimality of the process and a logical point of stability of the pharmaceutical company by rationally applying treatment methods according to established standards (percentage base). This approach makes it possible to influence the management of private clinics through clear ideas on the algorithms for prescribing drugs in each group of patients and their zoning in the vector recovery mode.

Conclusion

Initial data and sample size: 552 measurements of the intervals of changes in the subject's indicators in seconds (smoothing and scaling the data to the level of the base (analytical) period or the final (barrier) period). Regular use of this approach makes it possible to reserve the resources of the body of a healthy and physically active person in a timely manner for a very reliable functioning of all body systems, taking into account the dosed intake of prescribed drugs and the conditions of comfortable (decent) maintenance of patients during the course of treatment according to the method chosen by the doctor.

Optimized Molecular Interaction Networks for the Study of Skeletal Muscle

BACKGROUND

Molecular interaction networks (MINs) aim to capture the complex relationships between interacting molecules within a biological system. MINs can be constructed from existing knowledge of molecular functional associations, such as protein-protein binding interactions (PPI) or gene co-expression, and these different sources may be combined into a single MIN. A given MIN may be more or less optimal in its representation of the important functional relationships of molecules in a tissue.

OBJECTIVE

The aim of this study was to establish whether a combined MIN derived from different types of functional association could better capture muscle-relevant biology compared to its constituent single-source MINs.

METHODS

MINs were constructed from functional association databases for both protein-binding and gene co-expression. The networks were then compared based on the capture of muscle-relevant genes and gene ontology (GO) terms, tested in two different ways using established biological network clustering algorithms. The top performing MINs were combined to test whether an optimal MIN for skeletal muscle could be constructed.

RESULTS

The STRING PPI network was the best performing single-source MIN among those tested. Combining STRING with interactions from either the MyoMiner or CoXPRESSdb gene co-expression sources resulted in a combined network with improved performance relative to its constituent networks.

CONCLUSION

MINs constructed from multiple types of functional association can better represent the functional relationships of molecules in a given tissue. Such networks may be used to improve the analysis and interpretation of functional genomics data in the study of skeletal muscle and neuromuscular diseases. Networks and clusters described by this study, including the combinations of STRING with MyoMiner or with CoXPRESSdb, are available for download from https://www.sys-myo.com/myominer/download.php.

What Can Machine Learning Approaches in Genomics Tell Us about the Molecular Basis of Amyotrophic Lateral Sclerosis?

Amyotrophic Lateral Sclerosis (ALS) is the most common late-onset motor neuron disorder, but our current knowledge of the molecular mechanisms and pathways underlying this disease remain elusive. This review (1) systematically identifies machine learning studies aimed at the understanding of the genetic architecture of ALS, (2) outlines the main challenges faced and compares the different approaches that have been used to confront them, and (3) compares the experimental designs and results produced by those approaches and describes their reproducibility in terms of biological results and the performances of the machine learning models. The majority of the collected studies incorporated prior knowledge of ALS into their feature selection approaches, and trained their machine learning models using genomic data combined with other types of mined knowledge including functional associations, protein-protein interactions, disease/tissue-specific information, epigenetic data, and known ALS phenotype-genotype associations. The importance of incorporating gene-gene interactions and cis-regulatory elements into the experimental design of future ALS machine learning studies is highlighted. Lastly, it is suggested that future advances in the genomic and machine learning fields will bring about a better understanding of ALS genetic architecture, and enable improved personalized approaches to this and other devastating and complex diseases.

Molecular Diagnosis and Novel Therapies for Neuromuscular Diseases

With the development of novel targeted therapies, including exon skipping/inclusion and gene replacement therapy, the field of neuromuscular diseases has drastically changed in the last several years. Until 2016, there had been no FDA-approved drugs to treat Duchenne muscular dystrophy (DMD), the most common muscular dystrophy. However, several new personalized therapies, including antisense oligonucleotides eteplirsen for DMD exon 51 skipping and golodirsen and viltolarsen for DMD exon 53 skipping, have been approved in the last 4 years. We are witnessing the start of a therapeutic revolution in neuromuscular diseases. However, the studies also made clear that these therapies are still far from a cure. Personalized genetic medicine for neuromuscular diseases faces several key challenges, including the difficulty of obtaining appropriate cell and animal models and limited its applicability. This Special Issue “Molecular Diagnosis and Novel Therapies for Neuromuscular/Musculoskeletal Diseases” highlights key areas of research progress that improve our understanding and the therapeutic outcomes of neuromuscular diseases in the personalized medicine era.

Omics-based exploration and functional validation of neurotrophic factors and histamine as therapeutic targets in ALS

A plethora of genetic and molecular mechanisms have been implicated in the pathophysiology of the heterogeneous and multifactorial amyotrophic lateral sclerosis (ALS) disease, and hence the conventional "one target-one drug" paradigm has failed so far to provide effective therapeutic solutions, precisely because of the complex nature of ALS. This review intends to highlight how the integration of emerging "omics" approaches may provide a rational foundation for the comprehensive exploration of molecular pathways and dynamic interactions involved in ALS, for the identification of candidate targets and biomarkers that will assist in the rapid diagnosis and prognosis, lastly for the stratification of patients into different subgroups with the aim of personalized therapeutic strategies. To this purpose, particular emphasis will be placed on some potential therapeutic targets, including neurotrophic factors and histamine signaling that both have emerged as dysregulated at different omics levels in specific subgroups of ALS patients, and have already shown promising results in in vitro and in vivo models of ALS. To conclude, we will discuss about the utility of using integrated omics coupled with network-based approaches to provide additional guidance for personalization of medicine applications in ALS.

Molecular and Cellular Mechanisms Affected in ALS

Amyotrophic lateral sclerosis (ALS) is a terminal late-onset condition characterized by the loss of upper and lower motor neurons. Mutations in more than 30 genes are associated to the disease, but these explain only ~20% of cases. The molecular functions of these genes implicate a wide range of cellular processes in ALS pathology, a cohesive understanding of which may provide clues to common molecular mechanisms across both familial (inherited) and sporadic cases and could be key to the development of effective therapeutic approaches. Here, the different pathways that have been investigated in ALS are summarized, discussing in detail: mitochondrial dysfunction, oxidative stress, axonal transport dysregulation, glutamate excitotoxicity, endosomal and vesicular transport impairment, impaired protein homeostasis, and aberrant RNA metabolism. This review considers the mechanistic roles of ALS-associated genes in pathology, viewed through the prism of shared molecular pathways.

Circulating RNAs as Potential Biomarkers in Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a complex multi-system neurodegenerative disorder with currently limited diagnostic and no therapeutic options. Despite the intense efforts no clinically applicable biomarkers for ALS are yet established. Most current research is thus focused, in particular, in identifying potential non-invasive circulating biomarkers for more rapid and accurate diagnosis and monitoring of the disease. In this review, we have focused on messenger RNA (mRNA), non-coding RNAs (lncRNAs), micro RNAs (miRNAs) and circular RNA (circRNAs) as potential biomarkers for ALS in peripheral blood serum, plasma and cells. The most promising miRNAs include miR-206, miR-133b, miR-27a, mi-338-3p, miR-183, miR-451, let-7 and miR-125b. To test clinical potential of this miRNA panel, a useful approach may be to perform such analysis on larger multi-center scale using similar experimental design. However, other types of RNAs (lncRNAs, circRNAs and mRNAs) that, together with miRNAs, represent RNA networks, have not been yet extensively studied in blood samples of patients with ALS. Additional research has to be done in order to find robust circulating biomarkers and therapeutic targets that will distinguish key RNA interactions in specific ALS-types to facilitate diagnosis, predict progression and design therapy.

Spatiotemporal dynamics of molecular pathology in amyotrophic lateral sclerosis

Paralysis occurring in amyotrophic lateral sclerosis (ALS) results from denervation of skeletal muscle as a consequence of motor neuron degeneration. Interactions between motor neurons and glia contribute to motor neuron loss, but the spatiotemporal ordering of molecular events that drive these processes in intact spinal tissue remains poorly understood. Here, we use spatial transcriptomics to obtain gene expression measurements of mouse spinal cords over the course of disease, as well as of postmortem tissue from ALS patients, to characterize the underlying molecular mechanisms in ALS. We identify pathway dynamics, distinguish regional differences between microglia and astrocyte populations at early time points, and discern perturbations in several transcriptional pathways shared between murine models of ALS and human postmortem spinal cords.