Exploring Common Therapeutic Targets for Neurodegenerative Disorders Using Transcriptome Study

Unraveling the Genetic Landscape of Neurological Disorders: Insights into Pathogenesis, Techniques for Variant Identification, and Therapeutic Approaches

Genetic abnormalities play a crucial role in the development of neurodegenerative disorders (NDDs). Genetic exploration has indeed contributed to unraveling the molecular complexities responsible for the etiology and progression of various NDDs. The intricate nature of rare and common variants in NDDs contributes to a limited understanding of the genetic risk factors associated with them. Advancements in next-generation sequencing have made whole-genome sequencing and whole-exome sequencing possible, allowing the identification of rare variants with substantial effects, and improving the understanding of both Mendelian and complex neurological conditions. The resurgence of gene therapy holds the promise of targeting the etiology of diseases and ensuring a sustained correction. This approach is particularly enticing for neurodegenerative diseases, where traditional pharmacological methods have fallen short. In the context of our exploration of the genetic epidemiology of the three most prevalent NDDs-amyotrophic lateral sclerosis, Alzheimer's disease, and Parkinson's disease, our primary goal is to underscore the progress made in the development of next-generation sequencing. This progress aims to enhance our understanding of the disease mechanisms and explore gene-based therapies for NDDs. Throughout this review, we focus on genetic variations, methodologies for their identification, the associated pathophysiology, and the promising potential of gene therapy. Ultimately, our objective is to provide a comprehensive and forward-looking perspective on the emerging research arena of NDDs.

The application of weighted gene co-expression network analysis and support vector machine learning in the screening of Parkinson's disease biomarkers and construction of diagnostic models

Background

This study aims to utilize Weighted Gene Co-expression Network Analysis (WGCNA) and Support Vector Machine (SVM) algorithm for screening biomarkers and constructing a diagnostic model for Parkinson's disease.

Methods

Firstly, we conducted WGCNA analysis on gene expression data from Parkinson's disease patients and control group using three GEO datasets (GSE8397, GSE20163, and GSE20164) to identify gene modules associated with Parkinson's disease. Then, key genes with significantly differential expression from these gene modules were selected as candidate biomarkers and validated using the GSE7621 dataset. Further functional analysis revealed the important roles of these genes in processes such as immune regulation, inflammatory response, and cell apoptosis. Based on these findings, we constructed a diagnostic model by using the expression data of FLT1, ATP6V0E1, ATP6V0E2, and H2BC12 as inputs and training and validating the model using SVM algorithm.

Results

The prediction model demonstrated an AUC greater than 0.8 in the training, test, and validation sets, thereby validating its performance through SMOTE analysis. These findings provide strong support for early diagnosis of Parkinson's disease and offer new opportunities for personalized treatment and disease management.

Conclusion

In conclusion, the combination of WGCNA and SVM holds potential in biomarker screening and diagnostic model construction for Parkinson's disease.

Comprehensive brain tissue metabolomics and biological network technology to decipher the mechanism of hydrogen-rich water on Radiation-induced cognitive impairment in rats

BACKGROUND

Hydrogen-rich water (HRW) has been shown to prevent cognitive impairment caused by ionizing radiation. This study aimed to investigate the pharmacological effects and mechanisms of HRW on ionizing radiation by coupling the brain metabolomics and biological target network methods.

METHODS AND RESULTS

HRW significantly improves the cognitive impairment in rats exposed to ionizing radiation. Based on metabolomics and biological network results, we identified 54 differential metabolites and 93 target genes. The KEGG pathway indicates that glutathione metabolism, ascorbic acid and aldehyde acid metabolism, pentose and glucuronic acid interconversion, and glycerophospholipid metabolism play important roles in ionizing radiation therapy.

CONCLUSION

Our study has systematically elucidated the molecular mechanism of HRW against ionizing radiation, which can be mediated by modulating targets, pathways and metabolite levels. This provides a new perspective for identifying the underlying pharmacological mechanism of HRW.

Contribution of A-to-I RNA editing, M6A RNA Methylation, and Alternative Splicing to physiological brain aging and neurodegenerative diseases

Aging is a physiological and progressive phenomenon in all organisms' life cycle, characterized by the accumulation of degenerative processes triggered by several alterations within molecular pathways. These changes compromise cell fate, resulting in the loss of functions in tissues throughout the body, including the brain. Physiological brain aging has been linked to structural and functional alterations, as well as to an increased risk of neurodegenerative diseases. Post-transcriptional RNA modifications modulate mRNA coding properties, stability, translatability, expanding the coding capacity of the genome, and are involved in all cellular processes. Among mRNA post-transcriptional modifications, the A-to-I RNA editing, m6A RNA Methylation and Alternative Splicing play a critical role in all the phases of a neuronal cell life cycle and alterations in their mechanisms of action significantly contribute to aging and neurodegeneration. Here we review our current understanding of the contribution of A-to-I RNA editing, m6A RNA Methylation, and Alternative Splicing to physiological brain aging process and neurodegenerative diseases.

Chitinase Signature in the Plasticity of Neurodegenerative Diseases

Several reports have pointed out that Chitinases are expressed and secreted by various cell types of central nervous system (CNS), including activated microglia and astrocytes. These cells play a key role in neuroinflammation and in the pathogenesis of many neurodegenerative disorders. Increased levels of Chitinases, in particular Chitotriosidase (CHIT-1) and chitinase-3-like protein 1 (CHI3L1), have been found increased in several neurodegenerative disorders. Although having important biological roles in inflammation, to date, the molecular mechanisms of Chitinase involvement in the pathogenesis of neurodegenerative disorders is not well-elucidated. Several studies showed that some Chitinases could be assumed as markers for diagnosis, prognosis, activity, and severity of a disease and therefore can be helpful in the choice of treatment. However, some studies showed controversial results. This review will discuss the potential of Chitinases in the pathogenesis of some neurodegenerative disorders, such as Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis, and multiple sclerosis, to understand their role as distinctive biomarkers of neuronal cell activity during neuroinflammatory processes. Knowledge of the role of Chitinases in neuronal cell activation could allow for the development of new methodologies for downregulating neuroinflammation and consequently for diminishing negative neurological disease outcomes.

Metabolomics as a Crucial Tool to Develop New Therapeutic Strategies for Neurodegenerative Diseases

Neurodegenerative diseases (NDs), such as Alzheimer’s (AD), Parkinson’s (PD), and amyotrophic lateral sclerosis (ALS), share common pathological mechanisms, including metabolism alterations. However, their specific neuronal cell types affected and molecular biomarkers suggest that there are both common and specific alterations regarding metabolite levels. In this review, we were interested in identifying metabolite alterations that have been reported in preclinical models of NDs and that have also been documented as altered in NDs patients. Such alterations could represent interesting targets for the development of targeted therapy. Importantly, the translation of such findings from preclinical to clinical studies is primordial for the study of possible therapeutic agents. We found that N-acetyl-aspartate (NAA), myo-inositol, and glutamate are commonly altered in the three NDs investigated here. We also found other metabolites commonly altered in both AD and PD. In this review, we discuss the studies reporting such alterations and the possible pathological mechanism underlying them. Finally, we discuss clinical trials that have attempted to develop treatments targeting such alterations. We conclude that the treatment combination of both common and differential alterations would increase the chances of patients having access to efficient treatments for each ND.

Overlap between Central and Peripheral Transcriptomes in Parkinson’s Disease but Not Alzheimer’s Disease

Most neurodegenerative disorders take decades to develop, and their early detection is challenged by confounding non-pathological ageing processes. Therefore, the discovery of genes and molecular pathways in both peripheral and brain tissues that are highly predictive of disease evolution is necessary. To find genes that influence Alzheimer’s disease (AD) and Parkinson’s disease (PD) pathogenesis, human RNA-Seq transcriptomic data from Brodmann Area 9 (BA9) of the dorsolateral prefrontal cortex (DLPFC), whole blood (WB), and peripheral blood mononuclear cells (PBMC) were analysed using a combination of differential gene expression and a random forest-based machine learning algorithm. The results suggest that there is little overlap between PD and AD, and the AD brain signature is unique mainly compared to blood-based samples. Moreover, the AD-BA9 was characterised by changes in ‘nervous system development’ with Myocyte-specific enhancer factor 2C (Mef2C), encoding a transcription factor that induces microglia activation, a prominent feature. The peripheral AD transcriptome was associated with alterations in ‘viral process’, and FYN, which has been previously shown to link amyloid-beta and tau, was the prominent feature. However, in the absence of any overlap with the central transcriptome, it is unclear whether peripheral FYN levels reflect AD severity or progression. In PD, central and peripheral signatures are characterised by anomalies in ‘exocytosis’ and specific genes related to the SNARE complex, including Vesicle-associated membrane protein 2 (VAMP2), Syntaxin 1A (STX1A), and p21-activated kinase 1 (PAK1). This is consistent with our current understanding of the physiological role of alpha-synuclein and how alpha-synuclein oligomers compromise vesicle docking and neurotransmission. Overall, the results describe distinct disease-specific pathomechanisms, both within the brain and peripherally, for the two most common neurodegenerative disorders.

Differential Analysis of A-to-I mRNA Edited Sites in Parkinson's Disease

Parkinson's disease (PD) is a widespread neuronal degenerative disorder with unexplored etiology. It is associated with various pathological events. In particular, the prefrontal cortex Brodmann area 9 (BA9) region is affected in PD. This frontal lobe brain region plays an important role in cognitive, motor, and memory-related functions. BA9 develops Lewy bodies in PD patients and shows essential changes in transcriptome and proteome, connected with mitochondria related pathways, protein folding pathways, and metallothioneins. Recently, altered adenosine to inosine mRNA editing patterns have been detected in various neurological pathologies. In this article, we present an investigation of differences in A-to-I RNA editing levels and specificity of mRNA editing sites in brain tissues of healthy and PD patients based on RNA sequencing data. Overall, decreased editing levels in the brains of PD patients were observed, potential editing sites with altered editing during PD were identified, and the role of different adenosine deaminases in this process was analyzed.