Novel Insight Into the Role of Immune Dysregulation in Amyotrophic Lateral Sclerosis Based on Bioinformatic Analysis

Key Genes in Olfactory Disorder in Experimental Autoimmune Encephalomyelitis Identified by Transcriptomic Analysis of the Olfactory Bulbs

Experimental autoimmune encephalomyelitis (EAE) is an animal model of multiple sclerosis that shows demyelination in the central nervous system and functional deficits, including olfactory impairment. However, the genes related to olfactory impairment in EAE are unknown. We evaluated hub genes of the olfactory bulb in EAE mice. Differentially expressed genes (cut-offs, fold change > 2 and adjusted p < 0.05) and their related pathways in olfactory bulbs were subjected to gene ontology (GO) pathway analysis, gene set enrichment analysis (GSEA). Protein-protein interactions with selected genes were evaluated using the Search Tool for the Retrieval of Interacting Genes/Proteins. Gene regulatory networks (GRNs) which were constructed at the post-transcriptional level, including the genes-transcription factors (TFs) and gene-microRNAs (miRNAs) interaction networks. Twelve hub genes were found, three of which (Ctss, Itgb2, and Tlr2) were validated by RT-qPCR to be related to GO pathways such as immune response and regulation of immune response. GSEA showed that neuron-related genes-including Atp6v1g2, Egr1, and Gap43-and their pathways were significantly downregulated. GRNs analysis of six genes (Ctss, Itgb2, Tlr2, Atp6v1g2, Egr1, and Gap43) revealed 37 TFs and 84 miRNAs were identified as potential regulators of six genes, indicating significant interaction among six genes, TFs, and miRNAs. Collectively, these results suggest that transcriptomic analysis of the olfactory bulb of EAE mice can provide insight into olfactory dysfunction and reveal therapeutic targets for olfactory impairment.

Exploring the Disease-Associated Microglia State in Amyotrophic Lateral Sclerosis

BACKGROUND

Neuroinflammation, and specifically microglia, plays an important but not-yet well-understood role in the pathophysiology of amyotrophic lateral sclerosis (ALS), constituting a potential therapeutic target for the disease. Recent studies have described the involvement of different microglial transcriptional patterns throughout neurodegenerative processes, identifying a new state of microglia: disease-associated microglia (DAM). The aim of this study is to investigate expression patterns of microglial-related genes in ALS spinal cord.

METHODS

We analyzed mRNA expression levels via RT-qPCR of several microglia-related genes in their homeostatic and DAM state in postmortem tissue (anterior horn of the spinal cord) from 20 subjects with ALS-TDP43 and 19 controls donors from the Navarrabiomed Biobank.

RESULTS

The expression levels of TREM2, MS4A, CD33, APOE and TYROBP were found to be elevated in the spinal cord from ALS subjects versus controls (p-value < 0.05). However, no statistically significant gene expression differences were observed for TMEM119, SPP1 and LPL.

CONCLUSIONS

This study suggests that a DAM-mediated inflammatory response is present in ALS, and TREM2 plays a significant role in immune function of microglia. It also supports the role of C33 and MS4A in the physiopathology of ALS.

Genome-Wide Gene-Set Analysis Identifies Molecular Mechanisms Associated with ALS

Amyotrophic lateral sclerosis (ALS) is a fatal late-onset motor neuron disease characterized by the loss of the upper and lower motor neurons. Our understanding of the molecular basis of ALS pathology remains elusive, complicating the development of efficient treatment. Gene-set analyses of genome-wide data have offered insight into the biological processes and pathways of complex diseases and can suggest new hypotheses regarding causal mechanisms. Our aim in this study was to identify and explore biological pathways and other gene sets having genomic association to ALS. Two cohorts of genomic data from the dbGaP repository were combined: (a) the largest available ALS individual-level genotype dataset (N = 12,319), and (b) a similarly sized control cohort (N = 13,210). Following comprehensive quality control pipelines, imputation and meta-analysis, we assembled a large European descent ALS-control cohort of 9244 ALS cases and 12,795 healthy controls represented by genetic variants of 19,242 genes. Multi-marker analysis of genomic annotation (MAGMA) gene-set analysis was applied to an extensive collection of 31,454 gene sets from the molecular signatures database (MSigDB). Statistically significant associations were observed for gene sets related to immune response, apoptosis, lipid metabolism, neuron differentiation, muscle cell function, synaptic plasticity and development. We also report novel interactions between gene sets, suggestive of mechanistic overlaps. A manual meta-categorization and enrichment mapping approach is used to explore the overlap of gene membership between significant gene sets, revealing a number of shared mechanisms.

Amyotrophic Lateral Sclerosis Pathoetiology and Pathophysiology: Roles of Astrocytes, Gut Microbiome, and Muscle Interactions via the Mitochondrial Melatonergic Pathway, with Disruption by Glyphosate-Based Herbicides

The pathoetiology and pathophysiology of motor neuron loss in amyotrophic lateral sclerosis (ALS) are still to be determined, with only a small percentage of ALS patients having a known genetic risk factor. The article looks to integrate wider bodies of data on the biological underpinnings of ALS, highlighting the integrative role of alterations in the mitochondrial melatonergic pathways and systemic factors regulating this pathway across a number of crucial hubs in ALS pathophysiology, namely glia, gut, and the muscle/neuromuscular junction. It is proposed that suppression of the mitochondrial melatonergic pathway underpins changes in muscle brain-derived neurotrophic factor, and its melatonergic pathway mimic, N-acetylserotonin, leading to a lack of metabolic trophic support at the neuromuscular junction. The attenuation of the melatonergic pathway in astrocytes prevents activation of toll-like receptor agonists-induced pro-inflammatory transcription factors, NF-kB, and yin yang 1, from having a built-in limitation on inflammatory induction that arises from their synchronized induction of melatonin release. Such maintained astrocyte activation, coupled with heightened microglia reactivity, is an important driver of motor neuron susceptibility in ALS. Two important systemic factors, gut dysbiosis/permeability and pineal melatonin mediate many of their beneficial effects via their capacity to upregulate the mitochondrial melatonergic pathway in central and systemic cells. The mitochondrial melatonergic pathway may be seen as a core aspect of cellular function, with its suppression increasing reactive oxygen species (ROS), leading to ROS-induced microRNAs, thereby altering the patterning of genes induced. It is proposed that the increased occupational risk of ALS in farmers, gardeners, and sportsmen and women is intimately linked to exposure, whilst being physically active, to the widely used glyphosate-based herbicides. This has numerous research and treatment implications.

Genome-Wide Gene-Set Analysis Approaches in Amyotrophic Lateral Sclerosis

The rapid increase in the number of genetic variants identified to be associated with Amyotrophic Lateral Sclerosis (ALS) through genome-wide association studies (GWAS) has created an emerging need to understand the functional pathways that are implicated in the pathology of ALS. Gene-set analysis (GSA) is a powerful method that can provide insight into the associated biological pathways, determining the joint effect of multiple genetic markers. The main contribution of this review is the collection of ALS GSA studies that employ GWAS or individual-based genotype data, investigating their methodology and results related to ALS-associated molecular pathways. Furthermore, the limitations in standard single-gene analyses are summarized, highlighting the power of gene-set analysis, and a brief overview of the statistical properties of gene-set analysis and related concepts is provided. The main aims of this review are to investigate the reproducibility of the collected studies and identify their strengths and limitations, in order to enhance the experimental design and therefore the quality of the results of future studies, deepening our understanding of this devastating disease.

Intersection of network medicine and machine learning towards investigating the key biomarkers and pathways underlying amyotrophic lateral sclerosis: a systematic review

BACKGROUND

Network medicine is an emerging area of research that focuses on delving into the molecular complexity of the disease, leading to the discovery of network biomarkers and therapeutic target discovery. Amyotrophic lateral sclerosis (ALS) is a complicated rare disease with unknown pathogenesis and no available treatment. In ALS, network properties appear to be potential biomarkers that can be beneficial in disease-related applications when explored independently or in tandem with machine learning (ML) techniques.

OBJECTIVE

This systematic literature review explores recent trends in network medicine and implementations of network-based ML algorithms in ALS. We aim to provide an overview of the identified primary studies and gather details on identifying the potential biomarkers and delineated pathways.

METHODS

The current study consists of searching for and investigating primary studies from PubMed and Dimensions.ai, published between 2018 and 2022 that reported network medicine perspectives and the coupling of ML techniques. Each abstract and full-text study was individually evaluated, and the relevant studies were finally included in the review for discussion once they met the inclusion and exclusion criteria.

RESULTS

We identified 109 eligible publications from primary studies representing this systematic review. The data coalesced into two themes: application of network science to identify disease modules and promising biomarkers in ALS, along with network-based ML approaches. Conclusion This systematic review gives an overview of the network medicine approaches and implementations of network-based ML algorithms in ALS to determine new disease genes, and identify critical pathways and therapeutic target discovery for personalized treatment.

Motor neuron-derived induced pluripotent stem cells as a drug screening platform for amyotrophic lateral sclerosis

The development of cell culture models that recapitulate the etiology and features of nervous system diseases is central to the discovery of new drugs and their translation onto therapies. Neuronal tissues are inaccessible due to skeletal constraints and the invasiveness of the procedure to obtain them. Thus, the emergence of induced pluripotent stem cell (iPSC) technology offers the opportunity to model different neuronal pathologies. Our focus centers on iPSCs derived from amyotrophic lateral sclerosis (ALS) patients, whose pathology remains in urgent need of new drugs and treatment. In this sense, we aim to revise the process to obtain motor neurons derived iPSCs (iPSC-MNs) from patients with ALS as a drug screening model, review current 3D-models and offer a perspective on bioinformatics as a powerful tool that can aid in the progress of finding new pharmacological treatments.

Prognostic Biomarkers in Uveal Melanoma: The Status Quo, Recent Advances and Future Directions

Simple Summary

Although rare, uveal melanoma (UM) is the most common cancer that develops inside adult eyes. The prognosis is poor, since 50% of patients will develop lethal metastases in the first decade, especially to the liver. Once metastases are detected, life expectancy is limited, given that the available treatments are mostly unsuccessful. Thus, there is a need to find methods that can accurately predict UM prognosis and also effective therapeutic strategies to treat this cancer. In this manuscript, we initially compile the current knowledge on epidemiological, clinical, pathological and molecular features of UM. Then, we cover the most relevant prognostic factors currently used for the evaluation and follow-up of UM patients. Afterwards, we highlight emerging molecular markers in UM published over the last three years. Finally, we discuss the problems preventing meaningful advances in the treatment and prognostication of UM patients, as well as forecast new roadblocks and paths of UM-related research.

Abstract

Uveal melanoma (UM) is the most common malignant intraocular tumour in the adult population. It is a rare cancer with an incidence of nearly five cases per million inhabitants per year, which develops from the uncontrolled proliferation of melanocytes in the choroid (≈90%), ciliary body (≈6%) or iris (≈4%). Patients initially present either with symptoms like blurred vision or photopsia, or without symptoms, with the tumour being detected in routine eye exams. Over the course of the disease, metastases, which are initially dormant, develop in nearly 50% of patients, preferentially in the liver. Despite decades of intensive research, the only approach proven to mildly control disease spread are early treatments directed to ablate liver metastases, such as surgical excision or chemoembolization. However, most patients have a limited life expectancy once metastases are detected, since there are limited therapeutic approaches for the metastatic disease, including immunotherapy, which unlike in cutaneous melanoma, has been mostly ineffective for UM patients. Therefore, in order to offer the best care possible to these patients, there is an urgent need to find robust models that can accurately predict the prognosis of UM, as well as therapeutic strategies that effectively block and/or limit the spread of the metastatic disease. Here, we initially summarized the current knowledge about UM by compiling the most relevant epidemiological, clinical, pathological and molecular data. Then, we revisited the most important prognostic factors currently used for the evaluation and follow-up of primary UM cases. Afterwards, we addressed emerging prognostic biomarkers in UM, by comprehensively reviewing gene signatures, immunohistochemistry-based markers and proteomic markers resulting from research studies conducted over the past three years. Finally, we discussed the current hurdles in the field and anticipated the future challenges and novel avenues of research in UM.