A Comprehensive Bioinformatics Approach to Identify Molecular Signatures and Key Pathways for the Huntington Disease

Network pharmacology approach to unravel the neuroprotective potential of natural products: a narrative review

Aging is a slow and irreversible biological process leading to decreased cell and tissue functions with higher risks of multiple age-related diseases, including neurodegenerative diseases. It is widely accepted that aging represents the leading risk factor for neurodegeneration. The pathogenesis of these diseases involves complex interactions of genetic mutations, environmental factors, oxidative stress, neuroinflammation, and mitochondrial dysfunction, which complicate treatment with traditional mono-targeted therapies. Network pharmacology can help identify potential gene or protein targets related to neurodegenerative diseases. Integrating advanced molecular profiling technologies and computer-aided drug design further enhances the potential of network pharmacology, enabling the identification of biomarkers and therapeutic targets, thus paving the way for precision medicine in neurodegenerative diseases. This review article delves into the application of network pharmacology in understanding and treating neurodegenerative disorders such as Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, Huntington's disease, and spinal muscular atrophy. Overall, this article emphasizes the importance of addressing aging as a central factor in developing effective disease-modifying therapies, highlighting how network pharmacology can unravel the complex biological networks associated with aging and pave the way for personalized medical strategies.

Seven Hub Genes Associated with Huntington's Disease and Diagnostic and Therapeutic Potentials Identified by Computational Biology

Huntington's disease (HD) is characterized by progressive motor dysfunction and cognitive decline. Early diagnosis and new therapeutic targets are essential for effective interventions. We performed integrative analyses of mRNA profiles from three microarrays and one RNA-seq dataset from the Gene Expression Omnibus database. The datasets included were GSE8762, GSE24250, GSE45516, and GSE64810. Data pre-processing included background correction, normalization, log2 transformation, probe-to-gene symbol mapping, and differential expression analysis. We identified 80 differentially expressed genes (DEGs) based on a significance threshold (p < 0.05) and absolute log fold change (logFC) >0.65. Additionally, we conducted Gene Ontology (GO) and pathway analyses of the identified genes. Protein-protein interactions among DEGs revealed a network from which seven hub genes (VIM, COL1A1, COL3A1, COL1A2, DCN, CXCR2, and S100A9) were identified using the cytoHubba plugin in Cytoscape software. Two top DEGs, IGHG1 (up-regulated) and PITX1 (up-regulated), also hold potential as therapeutic targets. Insofar as biological contextualization of the findings is concerned, the top enriched GO terms were skeletal system development, blood vessel development, and vasculature development. Molecular function terms highlighted signaling receptor binding, extracellular matrix structural constituent, and platelet-derived growth factor binding. Notably, the significant KEGG pathways included amoebiasis, the AGE-RAGE signaling pathway in diabetic complications, and the relaxin signaling pathway. In conclusion, the present computational biology integrative analyses of multiple datasets discovered new DEGs and seven hub genes, shedding light on molecular mechanisms of HD. These findings call for translational clinical omics research and may potentially lead to future precision medicine interventions and novel diagnostic biomarkers and therapeutic targets.

Multi-epitope immunocapture of huntingtin reveals striatum-selective molecular signatures

Huntington's disease (HD) is a debilitating neurodegenerative disorder affecting an individual's cognitive and motor abilities. HD is caused by a mutation in the huntingtin gene producing a toxic polyglutamine-expanded protein (mHTT) and leading to degeneration in the striatum and cortex. Yet, the molecular signatures that underlie tissue-specific vulnerabilities remain unclear. Here, we investigate this aspect by leveraging multi-epitope protein interaction assays, subcellular fractionation, thermal proteome profiling, and genetic modifier assays. The use of human cell, mouse, and fly models afforded capture of distinct subcellular pools of epitope-enriched and tissue-dependent interactions linked to dysregulated cellular pathways and disease relevance. We established an HTT association with nearly all subunits of the transcriptional regulatory Mediator complex (20/26), with preferential enrichment of MED15 in the tail domain. Using HD and KO models, we find HTT modulates the subcellular localization and assembly of the Mediator. We demonstrated striatal enriched and functional interactions with regulators of calcium homeostasis and chromatin remodeling, whose disease relevance was supported by HD fly genetic modifiers assays. Altogether, we offer insights into tissue- and localization-dependent (m)HTT functions and pathobiology.

Identification of molecular targets and small drug candidates for Huntington's disease via bioinformatics and a network-based screening approach

Huntington's disease (HD) is a gradually severe neurodegenerative ailment characterised by an increase of a specific trinucleotide repeat sequence (cytosine-adenine-guanine, CAG). It is passed down as a dominant characteristic that worsens over time, creating a significant risk. Despite being monogenetic, the underlying mechanisms as well as biomarkers remain poorly understood. Furthermore, early detection of HD is challenging, and the available diagnostic procedures have low precision and accuracy. The research was conducted to provide knowledge of the biomarkers, pathways and therapeutic targets involved in the molecular processes of HD using informatic based analysis and applying network-based systems biology approaches. The gene expression profile datasets GSE97100 and GSE74201 relevant to HD were studied. As a consequence, 46 differentially expressed genes (DEGs) were identified. 10 hub genes (TPM1, EIF2S3, CCN2, ACTN1, ACTG2, CCN1, CSRP1, EIF1AX, BEX2 and TCEAL5) were further differentiated in the protein-protein interaction (PPI) network. These hub genes were typically down-regulated. Additionally, DEGs-transcription factors (TFs) connections (e.g. GATA2, YY1 and FOXC1), DEG-microRNA (miRNA) interactions (e.g. hsa-miR-124-3p and has-miR-26b-5p) were also comprehensively forecast. Additionally, related gene ontology concepts (e.g. sequence-specific DNA binding and TF activity) connected to DEGs in HD were identified using gene set enrichment analysis (GSEA). Finally, in silico drug design was employed to find candidate drugs for the treatment HD, and while the possible modest therapeutic compounds (e.g. cortistatin A, 13,16-Epoxy-25-hydroxy-17-cheilanthen-19,25-olide, Hecogenin) against HD were expected. Consequently, the results from this study may give researchers useful resources for the experimental validation of Huntington's diagnosis and therapeutic approaches.

The multifaceted roles of COL4A4 in lung adenocarcinoma: An integrated bioinformatics and experimental study

BACKGROUND

Abnormal expression of collagen IV subunits has been reported in cancers, but the significance is not clear. No study has reported the significance of COL4A4 in lung adenocarcinoma (LUAD).

METHODS

COL4A4 expression data, single-cell sequencing data and clinical data were downloaded from public databases. A range of bioinformatics and experimental methods were adopted to analyze the association of COL4A4 expression with clinical parameters, tumor microenvironment (TME), drug resistance and immunotherapy response, and to investigate the roles and underlying mechanism of COL4A4 in LUAD.

RESULTS

COL4A4 is differentially expressed in most of cancers analyzed, being associated with prognosis, tumor stemness, immune checkpoint gene expression and TME parameters. In LUAD, COL4A4 expression is down-regulated and associated with various TME parameters, response to immunotherapy and drug resistance. LUAD patients with lower COL4A4 have worse prognosis. Knockdown of COL4A4 significantly inhibited the expression of cell-cycle associated genes, and the expression and activation of signaling pathways including JAK/STAT3, p38, and ERK pathways, and induced quiescence in LUAD cells. Besides, it significantly induced the expression of a range of bioactive molecule genes that have been shown to have critical roles in TME remodeling and immune regulation.

CONCLUSIONS

COL4A4 is implicated in the pathogenesis of cancers including LUAD. Its function may be multifaceted. It can modulate the activity of LUAD cells, TME remodeling and tumor stemness, thus affecting the pathological process of LUAD. COL4A4 may be a prognostic molecular marker and a potential therapeutic target.

The Role of Innovation Technology in the Rehabilitation of Patients Affected by Huntington's Disease: A Scoping Review

Huntington's disease is an autosomal dominant neurodegenerative disease caused by the repetition of cytosine, adenine, and guanine trinucleotides on the short arm of chromosome 4p16.3 within the Huntingtin gene. In this study, we aim to examine and map the existing evidence on the use of innovations in the rehabilitation of Huntington's disease. A scoping review was conducted on innovative rehabilitative treatments performed on patients with Huntington's disease. A search was performed on PubMed, Embase, Web of Science, and Cochrane databases to screen references of included studies and review articles for additional citations. Of an initial 1117 articles, only 20 met the search criteria. These findings showed that available evidence is still limited and that studies generally had small sample sizes and a high risk of bias. Regarding cognitive rehabilitation, it has emerged that VR- and PC-based methods as well as NIBS techniques are feasible and may have promising effects in individuals with Huntington's disease. On the other hand, scarce evidence was found for cognitive and motor training that might have a slight impact on overall cognitive function in individuals with Huntington's disease. Data show that further investigation is needed to explore the effects of innovative rehabilitation tools on cognition, especially considering that cognitive and psychiatric symptoms can precede the onset of motor symptoms by many years.