RPL6: A Key Molecule Regulating Zinc- and Magnesium-Bound Metalloproteins of Parkinson's Disease

Aging disrupts the coordination between mRNA and protein expression in mouse and human midbrain

Age-related dopamine (DA) neuron loss is a primary feature of Parkinson's disease. However, whether similar biological processes occur during healthy aging, but to a lesser degree, remains unclear. We therefore determined whether midbrain DA neurons degenerate during aging in mice and humans. In mice, we identified no difference in midbrain neuron numbers throughout aging. Despite this, we found age-related decreases in midbrain mRNA expression of tyrosine hydroxylase (Th), the rate limiting enzyme of DA synthesis. Among midbrain glutamatergic cells, we similarly identified age-related declines in vesicular glutamate transporter 2 (Vglut2) mRNA expression. In co-transmitting Th+/Vglut2+ neurons, Th and Vglut2 transcripts decreased with aging. However, Th and Vglut2 protein levels in striatal synaptic release sites (e.g., terminals and axonal projections) did not differ throughout aging. Similar to the mouse, an initial study of human brain showed no effect of aging on midbrain neuron number with a concomitant decrease in TH and VGLUT2 mRNA expression. Unlike in mice, the density of striatal TH+ dopaminergic terminals was lower in aged human subjects. However, TH and VGLUT2 protein levels were unaffected in the remaining striatal boutons. Finally, in contrast to Th and Vglut2 mRNA, expression of most ribosomal genes in Th+ neurons was either maintained or even upregulated during aging. This suggests a homeostatic mechanism where age-related declines in transcriptional efficiency are overcome by ongoing ribosomal translation. Overall, we demonstrate species-conserved transcriptional effects of aging in midbrain dopaminergic and glutamatergic neurons that are not accompanied by marked cell death or lower striatal protein expression. This opens the door to novel therapeutic approaches to maintain neurotransmission and bolster neuronal resilience.

Oxidative stress and neurodegenerative diseases: a bidirectional Mendelian randomization study

INTRODUCTION

Oxidative stress (OS) has been linked to neurodegenerative diseases in numerous epidemiological studies; however, whether it is a pathogenesis or a downstream factor remains controversial.

METHODS

A two-sample bidirectional Mendelian randomization (MR) analysis was implemented to examine evidence of causality of 15 OS injury markers with 3 major neurodegenerative diseases using available genome-wide association studies statistics. As a main approach, inverse-variance weighted (IVW) analysis was performed. The weighted-median (WM) analysis was used to validate the relationship. In order to investigate the existence of horizontal pleiotropy and correct the IVW estimate, the Radial MR approach was applied. To gauge the consistency and robustness of the findings, several sensitivity and pleiotropy analyses were used. For this analysis, p < 0.05 indicates a nominally causal association; according to the Bonferroni correction test, p < 0.0011 indicates a statistically significant causal association.

RESULTS

Via IVW and WM, in directional MR, it was genetically predicted that zinc was nominally causally correlated with the risk of Parkinson's disease but not after Bonferroni correction test; alpha-tocopherol was nominally causally correlated with the risk of Amyotrophic lateral sclerosis (ALS) but not after Bonferroni correction test; furthermore, in reverse MR, it was genetically predicted that Alzheimer's disease was causally correlated with uric acid but not after Bonferroni correction test. These above findings were stable across sensitivity and pleiotropy analyses.

CONCLUSIONS

Based on the current study, there is no authentic genetic causal association between OS biomarkers and neurodegenerative diseases. The complex relationship is required to be confirmed in future experimental research.

Magnesium (Mg) and Neurodegeneration: A Comprehensive Overview of Studies on Mg Levels in Biological Specimens in Humans Affected Some Neurodegenerative Disorders with an Update on Therapy and Clinical Trials Supplemented with Selected Animal Studies

Neurodegenerative diseases, characterized by neuron loss, are a group of neurological disorders that adversely affect the lives of millions of people worldwide. Although several medicines have been approved for managing neurodegenerative diseases, new therapies allowing for a significant slowdown in the progression of neurodegenerative syndromes are constantly being sought. Magnesium (Mg), a crucial mineral necessary for the functioning of organisms, is important to normal central nervous system (CNS) activity. Although the effects of this bioelement on the CNS are relatively well recognized, its role in the pathophysiology of neurological disorders in humans is not yet well characterized. Therefore, the main goal of this review is to collect data about a possible association between Mg and neurodegenerative disorders such as Alzheimer's disease (AD), Parkinson's Disease (PD), and Amyotrophic lateral sclerosis (ALS) in humans. Hence, the levels of Mg in blood, cerebrospinal fluid (CSF), urine, and hair from subjects with AD, PD, and ALS are compiled to detect possible variations in the levels of this mineral in the biological specimens of people with neurodegenerative illnesses. Additionally, the findings from an animal model are summarized to offer the reader a deeper insight into studies on Mg in the context of neuroprotection and neurodegeneration. Data provided in the present review indicate that Mg, due to its neuroprotective, antioxidant, anti-inflammatory, and mitochondrial-supportive properties, could be a potential therapeutic agent for AD, PD, and ALS. However, more epidemiological studies with standardized methods of dietary assessment and Mg measurement are necessary to recognize its exact role in neurodegenerative disorders. Moreover, extensive well-designed clinical trials are also needed to establish definitive therapeutic protocols and optimal dosages, and to ensure long-term safety of this mineral supplementation in AD, PD, and ALS patients.

Comparative analysis of phosphorylated proteomes between plerocercoid and adult Spirometra mansoni reveals phosphoproteomic profiles of the medical tapeworm

BACKGROUND

Plerocercoid larvae of the tapeworm Spirometra mansoni can infect both humans and animals, leading to severe parasitic zoonosis worldwide. Despite ongoing research efforts, our understanding of the developmental process of S. mansoni remains inadequate. To better characterize posttranslational regulation associated with parasite growth, development, and reproduction, a comparative phosphoproteomic study was conducted on the plerocercoid and adult stages of S. mansoni.

METHODS

In this study, site-specific phosphoproteomic analysis was conducted via 4D label-free quantitative analysis technology to obtain primary information about the overall phosphorylation status of plerocercoids and adults.

RESULTS

A total of 778 differentially abundant proteins (DAPs) were detected between adults and plerocercoids, of which 704 DAPs were upregulated and only 74 were downregulated. DAPs involved in metabolic activity were upregulated in plerocercoid larvae compared with adults, whereas DAPs associated with binding were upregulated in adults. Gene Ontology (GO) and Kyoto Encyclopedia of Genes (KEGG) analyses indicated that most DAPs involved in signal transduction and environmental information processing pathways were highly active in adults. DAPs upregulated in the plerocercoid group were enriched mainly in metabolic activities. The kinases PKACA, GSK3B, and smMLCK closely interact, suggesting potential active roles in the growth and development of S. mansoni.

CONCLUSIONS

The dataset presented in this study offers a valuable resource for forthcoming research on signaling pathways as well as new insights into functional studies on the molecular mechanisms of S. mansoni.

The Role of Magnesium in Parkinson's Disease: Status Quo and Implications for Future Research

Neurodegenerative diseases represent an increasing economic, social, and, above all, medical burden worldwide. The second most prevalent disease in this category is Parkinson's disease, surpassed only by Alzheimer's. It is a treatable but still incurable systemic disease with a pathogenesis that has not yet been elucidated. Several theories are currently being developed to explain the causes and progression of Parkinson's disease. Magnesium is one of the essential macronutrients and is absolutely necessary for life as we know it. The magnesium cation performs several important functions in the cell in the context of energetic metabolism, substrate metabolism, cell signalling, and the regulation of the homeostasis of other ions. Several of these cellular processes have been simultaneously described as being disrupted in the development and progression of Parkinson's disease. The relationship between magnesium homeostasis and the pathogenesis of Parkinson's disease has received little scientific attention to date. The aim of this review is to summarise and critically evaluate the current state of knowledge on the possible role of magnesium in the pathogenesis of Parkinson's disease and to outline possible future directions for research in this area.

Systematic Analysis of Biological Processes Reveals Gene Co-expression Modules Driving Pathway Dysregulation in Alzheimer's Disease

Alzheimer's disease (AD) manifests as a complex systems pathology with intricate interplay among various genes and biological processes. Traditional differential gene expression (DEG) analysis, while commonly employed to characterize AD-driven perturbations, does not sufficiently capture the full spectrum of underlying biological processes. Utilizing single-nucleus RNA-sequencing data from postmortem brain samples across key regions-middle temporal gyrus, superior frontal gyrus, and entorhinal cortex-we provide a comprehensive systematic analysis of disrupted processes in AD. We go beyond the DEG-centric analysis by integrating pathway activity analysis with weighted gene co-expression patterns to comprehensively map gene interconnectivity, identifying region- and cell-type-specific drivers of biological processes associated with AD. Our analysis reveals profound modular heterogeneity in neurons and glia as well as extensive AD-related functional disruptions. Co-expression networks highlighted the extended involvement of astrocytes and microglia in biological processes beyond neuroinflammation, such as calcium homeostasis, glutamate regulation, lipid metabolism, vesicle-mediated transport, and TOR signaling. We find limited representation of DEGs within dysregulated pathways across neurons and glial cells, suggesting that differential gene expression alone may not adequately represent the disease complexity. Further dissection of inferred gene modules revealed distinct dynamics of hub DEGs in neurons versus glia, suggesting that DEGs exert more impact on neurons compared to glial cells in driving modular dysregulations underlying perturbed biological processes. Interestingly, we observe an overall downregulation of astrocyte and microglia modules across all brain regions in AD, indicating a prevailing trend of functional repression in glial cells across these regions. Notable genes from the CALM and HSP90 families emerged as hub genes across neuronal modules in all brain regions, suggesting conserved roles as drivers of synaptic dysfunction in AD. Our findings demonstrate the importance of an integrated, systems-oriented approach combining pathway and network analysis to comprehensively understand the cell-type-specific roles of genes in AD-related biological processes.

Aging disrupts the coordination between mRNA and protein expression in mouse and human midbrain

Age-related dopamine (DA) neuron loss is a primary feature of Parkinson's disease. However, it remains unclear whether similar biological processes occur during healthy aging, albeit to a lesser degree. We therefore determined whether midbrain DA neurons degenerate during aging in mice and humans. In mice, we identified no changes in midbrain neuron numbers throughout aging. Despite this, we found age-related decreases in midbrain mRNA expression of tyrosine hydroxylase (Th), the rate limiting enzyme of DA synthesis. Among midbrain glutamatergic cells, we similarly identified age-related declines in vesicular glutamate transporter 2 (Vglut2) mRNA expression. In co-transmitting Th +/Vglut2 + neurons, Th and Vglut2 transcripts decreased with aging. Importantly, striatal Th and Vglut2 protein expression remained unchanged. In translating our findings to humans, we found no midbrain neurodegeneration during aging and identified age-related decreases in TH and VGLUT2 mRNA expression similar to mouse. Unlike mice, we discovered diminished density of striatal TH+ dopaminergic terminals in aged human subjects. However, TH and VGLUT2 protein expression were unchanged in the remaining striatal boutons. Finally, in contrast to Th and Vglut2 mRNA, expression of most ribosomal genes in Th + neurons was either maintained or even upregulated during aging. This suggests a homeostatic mechanism where age-related declines in transcriptional efficiency are overcome by ongoing ribosomal translation. Overall, we demonstrate species-conserved transcriptional effects of aging in midbrain dopaminergic and glutamatergic neurons that are not accompanied by marked cell death or lower striatal protein expression. This opens the door to novel therapeutic approaches to maintain neurotransmission and bolster neuronal resilience.

Systematic Analysis of Biological Processes Reveals Gene Co-expression Modules Driving Pathway Dysregulation in Alzheimer's Disease

Alzheimer's disease (AD) manifests as a complex systems pathology with intricate interplay among various genes and biological processes. Traditional differential gene expression (DEG) analysis, while commonly employed to characterize AD-driven perturbations, does not sufficiently capture the full spectrum of underlying biological processes. Utilizing single-nucleus RNA-sequencing data from postmortem brain samples across key regions-middle temporal gyrus, superior frontal gyrus, and entorhinal cortex-we provide a comprehensive systematic analysis of disrupted processes in AD. We go beyond the DEG-centric analysis by integrating pathway activity analysis with weighted gene co-expression patterns to comprehensively map gene interconnectivity, identifying region- and cell-type-specific drivers of biological processes associated with AD. Our analysis reveals profound modular heterogeneity in neurons and glia as well as extensive AD-related functional disruptions. Co-expression networks highlighted the extended involvement of astrocytes and microglia in biological processes beyond neuroinflammation, such as calcium homeostasis, glutamate regulation, lipid metabolism, vesicle-mediated transport, and TOR signaling. We find limited representation of DEGs within dysregulated pathways across neurons and glial cells, indicating that differential gene expression alone may not adequately represent the disease complexity. Further dissection of inferred gene modules revealed distinct dynamics of hub DEGs in neurons versus glia, highlighting the differential impact of DEGs on neurons compared to glial cells in driving modular dysregulations underlying perturbed biological processes. Interestingly, we note an overall downregulation of both astrocyte and microglia modules in AD across all brain regions, suggesting a prevailing trend of functional repression in glial cells across these regions. Notable genes, including those of the CALM and HSP90 family genes emerged as hub genes across neuronal modules in all brain regions, indicating conserved roles as drivers of synaptic dysfunction in AD. Our findings demonstrate the importance of an integrated, systems-oriented approach combining pathway and network analysis for a comprehensive understanding of the cell-type-specific roles of genes in AD-related biological processes.

RNA-seq analysis of gene expression profiles in posttraumatic stress disorder, Parkinson's disease and schizophrenia identifies roles for common and distinct biological pathways

Evidence suggests that shared pathophysiological mechanisms in neuropsychiatric disorders (NPDs) may contribute to risk and resilience. We used single-gene and network-level transcriptomic approaches to investigate shared and disorder-specific processes underlying posttraumatic stress disorder (PTSD), Parkinson's disease (PD) and schizophrenia in a South African sample. RNA-seq was performed on blood obtained from cases and controls from each cohort. Gene expression and weighted gene correlation network analyses (WGCNA) were performed using DESeq2 and CEMiTool, respectively. Significant differences in gene expression were limited to the PTSD cohort. However, WGCNA implicated, amongst others, ribosomal expression, inflammation and ubiquitination as key players in the NPDs under investigation. Differential expression in ribosomal-related pathways was observed in the PTSD and PD cohorts, and focal adhesion and extracellular matrix pathways were implicated in PD and schizophrenia. We propose that, despite different phenotypic presentations, core transdiagnostic mechanisms may play important roles in the molecular aetiology of NPDs.

Identifying COVID-19-Specific Transcriptomic Biomarkers with Machine Learning Methods

COVID-19, a severe respiratory disease caused by a new type of coronavirus SARS-CoV-2, has been spreading all over the world. Patients infected with SARS-CoV-2 may have no pathogenic symptoms, i.e., presymptomatic patients and asymptomatic patients. Both patients could further spread the virus to other susceptible people, thereby making the control of COVID-19 difficult. The two major challenges for COVID-19 diagnosis at present are as follows: (1) patients could share similar symptoms with other respiratory infections, and (2) patients may not have any symptoms but could still spread the virus. Therefore, new biomarkers at different omics levels are required for the large-scale screening and diagnosis of COVID-19. Although some initial analyses could identify a group of candidate gene biomarkers for COVID-19, the previous work still could not identify biomarkers capable for clinical use in COVID-19, which requires disease-specific diagnosis compared with other multiple infectious diseases. As an extension of the previous study, optimized machine learning models were applied in the present study to identify some specific qualitative host biomarkers associated with COVID-19 infection on the basis of a publicly released transcriptomic dataset, which included healthy controls and patients with bacterial infection, influenza, COVID-19, and other kinds of coronavirus. This dataset was first analysed by Boruta, Max-Relevance and Min-Redundancy feature selection methods one by one, resulting in a feature list. This list was fed into the incremental feature selection method, incorporating one of the classification algorithms to extract essential biomarkers and build efficient classifiers and classification rules. The capacity of these findings to distinguish COVID-19 with other similar respiratory infectious diseases at the transcriptomic level was also validated, which may improve the efficacy and accuracy of COVID-19 diagnosis.