Transcriptional pathways of definitive ALS genes implicate novel disease-associated target genes

Genetic and molecular insights into amyotrophic lateral sclerosis: Exploring key pathways and disease mechanisms

Aim: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterised by progressive motor neuron degeneration. Despite identification of multiple susceptibility loci, the genetic and molecular basis of ALS pathogenesis remains incompletely understood. The present study aimed to integrate functional and metabolic analyses with GWAS-derived variants to investigate key genes, pathways, and cellular mechanisms underlying ALS. Methodology: Genetic variants associated with ALS were retrieved from published GWAS datasets and analysed through integrative bioinformatic approaches, including Gene Ontology (GO) enrichment and KEGG pathway mapping. Cell Marker enrichment assessed immune cell involvement, whilst metabolomic profiling examined lipid metabolism alterations. Unsupervised machine learning, encompassing clustering and principal component analysis (PCA), identified patterns across susceptibility loci on chromosomes 9, 12 and 19. Results: Core susceptibility genes identified included C9orf72, UNC13A and ITPR2. Enrichment analyses revealed disruptions in synaptic vesicle docking, neurotransmitter release, calcium homeostasis, oxidative stress, and neuroinflammation. Metabolomic profiling implicated disturbed lipid metabolism, whilst chromosomal clustering highlighted a genetic basis for disease heterogeneity. Interpretation: These findings underscore the multifactorial nature of ALS across genetic, molecular and metabolic dimensions, identifying potential molecular targets to guide future therapeutic development. Key words: ALS, Calcium signalling, GWAS, Neurodegeneration, Synaptic dysfunction

Gene expression in amyotrophic lateral sclerosis: an integrative narrative review of microarray findings, pathogenic mechanisms, and technical challenges

Abstract Amyotrophic Lateral Sclerosis (ALS) is a devastating and progressive neurodegenerative disorder with a complex and multifactorial pathogenesis characterized by the loss of upper and lower motor neurons. Despite advances in molecular biology, its pathogenesis remains incompletely understood. This narrative review synthesizes findings from key microarray studies, focusing on dysregulated pathways such as ribosomal function, protein synthesis, and metabolic processes within motor nerves and Schwann cells. We further explore the emerging role of competitive endogenous RNA (ceRNA) networks, particularly those involving long non-coding RNAs (lncRNAs), as revealed by advanced bioinformatics in Alzheimer's disease research. Drawing on this conceptual framework, we discuss how similar regulatory mechanisms might operate in ALS, identifying this as a promising direction for future investigation rather than an established finding. A critical analysis of the technical limitations of microarrays—including small sample sizes, the curse of dimensionality, and challenges in validation—is presented. Finally, we discuss future perspectives, advocating for the integration of microarray data with multi-omics approaches, the application of sophisticated machine learning and deep learning techniques, and the use of distributed computing to overcome current analytical bottlenecks. This integrative approach aims to bridge molecular discoveries with methodological advancements, fostering a deeper understanding of ALS pathogenesis and highlighting novel therapeutic targets.

Circular RNAs in amyotrophic lateral sclerosis.

RNA-seq data from ALS patients confirmed significant alterations in the expression of host genes of ALS-related circRNAs and hub proteins in ALS-affected CNS tissues, and these findings identify circRNAs as potential key contributors to ALS pathogenesis.

Gene regulatory co-expression networks decipher potential lncRNA-miRNA-mRNA interactions modulating transcription regulation in neurodegeneration

Neurodegenerative diseases are complex disorders characterised by progressive neuronal loss and widespread transcriptomic dysregulation; however, the coordinated interactions among coding and non-coding RNAs that contribute to disease progression remain incompletely understood. In this study, RNA-seq datasets from disease-relevant neuronal populations and brain regions representing Alzheimer’s disease (AD), Parkinson’s disease (PD) and amyotrophic lateral sclerosis (ALS) were analysed using an integrative network-based framework. Differential expression analysis coupled with weighted gene co-expression network analysis identified modules significantly correlated with disease and prioritised highly connected hub genes. Integration of these hub genes with curated RNA interaction database enabled the construction of candidate lncRNA-miRNA-mRNA regulatory networks. Functional enrichment analysis revealed Gene Ontology biological processes associated with synaptic signalling, mitochondrial function, RNA metabolism and neuroinflammatory responses across neurodegenerative conditions. The inferred regulatory networks suggested both disease-specific and shared post-transcriptional regulatory modules involving key hub genes and non-coding RNAs. Additionally, putative sequence variants were identified within untranslated regions of selected hub genes, suggesting potential alterations in miRNA-mediated regulations. Therefore, this study provides a systems-level view of transcriptomic dysregulation across major neurodegenerative diseases and identifies candidate regulatory interactions and molecular targets for future functional investigation.

Exploring shared genetic pathways and gene interplay in major neurodegenerative diseases: a comprehensive review.

This review examines the common genetic pathways, along with the interactions between genes of major neurodegenerative diseases, with a focus on the key genes, such as APOE, SNCA, MAPT, TARDBP, LRRK2 and HTT.

Parietal Cortex Transcriptomics Refines Parkinson Disease GWAS Nomination and Highlights STAT3 as a Putative Upstream Glial Regulator