Interactions between cell adhesion and the synaptic vesicle cycle in Parkinson's disease

Integrative single-cell RNA sequencing and mendelian randomization analysis reveal the potential role of synaptic vesicle cycling-related genes in Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) involves alterations in synaptic vesicle cycling (SVC), which significantly affect neuronal communication and function. Therefore, a thorough investigation into the potential roles of SVC-related genes (SVCRGs) in AD can enhance the identification of critical biomarkers that may influence disease progression and treatment responses.

METHODS

The datasets used in this study were sourced exclusively from public databases. By integrating differential expression analysis with Mendelian randomization (MR), we identified SVCRGs as biomarkers for AD. Functional characterization of these biomarkers was performed, followed by integration into a nomogram. Further investigation of immune infiltration in AD patients and healthy individuals was carried out. Ultimately, the potential cellular mechanisms of AD were explored through single-cell RNA sequencing (scRNA-seq) analysis.

RESULTS

ATP6V1D, ATP6V1G2, CLTB, and NSF were identified as biomarkers, exhibiting a positive correlation with each other and a downregulated expression in AD. These markers were pinpointed as protective factors for AD [odds ratio (OR) < 1, P < 0.05], with potential to reduce the risk of the disease. Integrated into a nomogram, they demonstrated satisfactory diagnostic performance and clinical utility, surpassing the use of single gene. They were collectively enriched in pathways related to "interferon gamma response", "inflammatory response", and "TNFα signaling via NFκB". Additionally, an increase in infiltration of 17 immune cell types in AD was noted, particularly cells associated with neuroinflammation such as activated CD8 T cells and various dendritic cells (DCs), suggesting an inflammatory milieu in AD while also displaying a negative correlation with the biomarkers. The cell types were further annotated, revealing specific expressions of biomarkers and uncovering the heterogeneity of excitatory neurons. A significant reduction in the overall number of excitatory neurons under AD conditions was observed, alongside consistent expression of biomarkers during the developmental stages of excitatory neurons.

CONCLUSION

By using MR, we firstly identified four SVCRGs as protective factors for AD, functioning through pathways associated with mitochondrial dysfunction, chronic inflammation, immune dysregulation, and neuronal damage. These genes had the potential to modulate immune cell infiltration activated in AD patients and exhibited cell-type-specific expression profiles within AD-related cellular contexts. Their findings provide novel insights and valuable references for future research on AD pathogenesis and therapeutic strategies.

An amino-rich polymer-coated magnetic nanomaterial for ultra-rapid separation of phosphorylated peptides in the serum of Parkinson's disease patients

The elucidation of disease pathogenesis can be achieved by analyzing the low-abundance phosphopeptides in organisms. Herein, we developed a novel and easy-to-prepare polymer-coated nanomaterial. By improving the hydrophilicity and spatial conformation of the material, we effectively enhanced the adsorption of phosphopeptides and demonstrated excellent enrichment properties. The material was able to successfully enrich the phosphopeptides in only 1 min. Meanwhile, the material has high selectivity (1:2000), good loading capacity (100 μg/mg), excellent sensitivity (0.5 fmol), and great acid and alkali resistance. In addition, the material was applied to real samples, and 70 phosphopeptides were enriched from the serum of Parkinson's disease (PD) patients and 67 phosphopeptides were enriched from the serum of normal controls. Sequences Logo showed that PD is probably associated with threonine, glutamate, serine, and glutamine. Finally, gene ontology (GO) analysis was performed on phosphopeptides enriched in PD patients' serum. The results showed that PD patients expressed abnormal expression of the cholesterol metabolic process and cell-matrix adhesion in the biological process (BP), endoplasmic reticulum and lipoprotein in the cellular component (CC), and heparin-binding, lipid-binding, and receptor-binding in the molecular function (MF) as compared with normal individuals. All the experiments indicate that the nanomaterials have great potential in proteomics studies.

A Systematic Review of Extracellular Matrix-Related Alterations in Parkinson's Disease

The role of the extracellular matrix (ECM) in Parkinson's disease (PD) is not well understood, even though it is critical for neuronal structure and signaling. This systematic review identified the top deregulated ECM-related pathways in studies that used gene set enrichment analyses (GSEA) to document transcriptomic, proteomic, or genomic alterations in PD. PubMed and Google scholar were searched for transcriptomics, proteomics, or genomics studies that employed GSEA on data from PD tissues or cells and reported ECM-related pathways among the top-10 most enriched versus controls. Twenty-seven studies were included, two of which used multiple omics analyses. Transcriptomics and proteomics studies were conducted on a variety of tissue and cell types. Of the 17 transcriptomics studies (16 data sets), 13 identified one or more adhesion pathways in the top-10 deregulated gene sets or pathways, primarily related to cell adhesion and focal adhesion. Among the 8 proteomics studies, 5 identified altered overarching ECM gene sets or pathways among the top 10. Among the 4 genomics studies, 3 identified focal adhesion pathways among the top 10. The findings summarized here suggest that ECM organization/structure and cell adhesion (particularly focal adhesion) are altered in PD and should be the focus of future studies.

Molecular insights into PCB neurotoxicity: Comparing transcriptomic responses across dopaminergic neurons, population blood cells, and Parkinson's disease pathology

Parkinson's disease (PD) is a complex neurodegenerative disorder influenced by genetic factors and environmental exposures. Polychlorinated biphenyls (PCBs), a group of synthetic organic compounds, have been identified as potential environmental risk factors for neurodegenerative diseases, including PD. We explored PCB-induced neurotoxicity mechanisms using iPSC-derived dopaminergic neurons and assessed their transcriptomic responses to varying PCB concentrations (0.01 μM, 0.5 μM, and 10 μM). Specifically, we focused on PCB-180, a congener known for its accumulation in human brains. The exposure durations were 24 h and 74 h, allowing us to capture both short-term and more prolonged effects on gene expression patterns. We observed that PCB exposure led to the suppression of oxidative phosphorylation, synaptic function, and neurotransmitter release, implicating these pathways in PCB-induced neurotoxicity. In our comparative analysis, we noted similarities in PCB-induced changes with other PD-related compounds like MPP+ and rotenone. Our findings also aligned with gene expression changes in human blood derived from a population exposed to PCBs, highlighting broader inflammatory responses. Additionally, molecular patterns seen in iPSC-derived neurons were confirmed in postmortem PD brain tissues, validating our in vitro results. In conclusion, our study offers novel insights into the multifaceted impacts of PCB-induced perturbations on various cellular contexts relevant to PD. The use of iPSC-derived dopaminergic neurons allowed us to decipher intricate transcriptomic alterations, bridging the gap between in vitro and in vivo findings. This work underscores the potential role of PCB exposure in neurodegenerative diseases like PD, emphasizing the need to consider both systemic and cell specific effects.

Common microRNA regulated pathways in Alzheimer's and Parkinson's disease

MicroRNAs (miRNAs) are small non-coding RNAs involved in gene regulation. Recently, miRNA dysregulation has been found in neurodegenerative diseases such as Alzheimer's disease (AD) and Parkinson's disease (PD). The diagnosis of Alzheimer's and Parkinson's is currently challenging, mainly occurring when pathology is already present, and although treatments are available for both diseases, the role of treatment is primarily to prevent or delay the progress of the diseases instead of fully overcoming the diseases. Therefore, the challenge in the near future will be to determine effective drugs to tackle the dysregulated biological pathways in neurodegenerative diseases. In the present study, we describe the dysregulation of miRNAs in blood of Alzheimer's and Parkinson's patients with the aim to identify common mechanisms between the 2 pathologies and potentially to identify common therapeutic targets which can stop or delay the progression of two most frequent neuropathologies. Two independent systematic reviews, bioinformatic analysis, and experiment validation were performed to identify whether AD and PD share common pathways. A total of 15 common miRNAs were found in the literature and 13 common KEGG pathways. Among the common miRNAs, two were selected for validation in a small cohort of AD and PD patients. Let-7f-5p and miR-29b-3p showed to be good predictors in blood of PD patients.

Biomedical knowledge graph learning for drug repurposing by extending guilt-by-association to multiple layers

Computational drug repurposing aims to identify new indications for existing drugs by utilizing high-throughput data, often in the form of biomedical knowledge graphs. However, learning on biomedical knowledge graphs can be challenging due to the dominance of genes and a small number of drug and disease entities, resulting in less effective representations. To overcome this challenge, we propose a "semantic multi-layer guilt-by-association" approach that leverages the principle of guilt-by-association - "similar genes share similar functions", at the drug-gene-disease level. Using this approach, our model DREAMwalk: Drug Repurposing through Exploring Associations using Multi-layer random walk uses our semantic information-guided random walk to generate drug and disease-populated node sequences, allowing for effective mapping of both drugs and diseases in a unified embedding space. Compared to state-of-the-art link prediction models, our approach improves drug-disease association prediction accuracy by up to 16.8%. Moreover, exploration of the embedding space reveals a well-aligned harmony between biological and semantic contexts. We demonstrate the effectiveness of our approach through repurposing case studies for breast carcinoma and Alzheimer's disease, highlighting the potential of multi-layer guilt-by-association perspective for drug repurposing on biomedical knowledge graphs.

Transcriptomic and Behavioral Studies of Small Yellow Croaker (Larimichthyspolyactis) in Response to Noise Exposure

Noise has the potential to induce physiological stress in marine fishes, which may lead to all sorts of ecological consequences. In the current study, we used the RNA-sequencing (RNA-seq) method to sequence the whole transcriptome of the brain in small yellow croaker (Larimichthys polyactis). The animals were exposed to a mix of noises produced by different types of boat played back in a tank, then the brain tissues were collected after the fish had been exposed to a 120 dB noise for 0.5 h. In total, 762 differently expressed genes (DEGs) between the two groups were identified, including 157 up regulated and 605 down regulated genes in the noise exposure group compared with the control group. Gene ontology (GO) enrichment analysis indicated that the most up regulated gene categories included synaptic membranes, receptor-mediated endocytosis and the neurotransmitter secretion process. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways found that endocytosis, cell adhesion molecules and the extracellular matrix (ECM) receptor interaction pathway were over-represented. Specifically, ECM-related genes, including lamin2, lamin3, lamin4, coll1a2, coll5a1 and col4a5 were down regulated in the noise exposure group, implying the impaired composition of the ECM. In addition, the behavioral experiment revealed that L. polyactis exhibited avoidance behaviors to run away from the noise source at the beginning of the noise exposure period. At the end of the noise exposure period, L. polyactis kept motionless on the surface of the water and lost the ability to keep their balance. Taken together, our results indicate that exposure to noise stress contributes to neurological dysfunction in the brain and impaired locomotor ability in L. polyactis.

Transcriptome analysis in LRRK2 and idiopathic Parkinson's disease at different glucose levels

Type-2 diabetes (T2D) and glucose metabolic imbalances have been linked to neurodegenerative diseases, including Parkinson's disease (PD). To detect potential effects of different glucose levels on gene expression, by RNA-seq we analyzed the transcriptome of dermal fibroblasts from idiopathic PD (iPD) patients, LRRK2-associated PD (L2PD) patients, and healthy controls (total n = 21 cell lines), which were cultured at two different glucose concentrations (25 and 5 mM glucose). In PD patients we identified differentially expressed genes (DEGs) that were related to biological processes mainly involving the plasmatic cell membrane, the extracellular matrix, and also neuronal functions. Such pathway deregulation was largely similar in iPD or L2PD fibroblasts. Overall, the gene expression changes detected in this study were associated with PD independently of glucose concentration.

Identification of cerebrospinal fluid biomarkers for parkinsonism using a proteomics approach

The aim of our study was to investigate cerebrospinal fluid (CSF) tryptic peptide profiles as potential diagnostic biomarkers for the discrimination of parkinsonian disorders. CSF samples were collected from individuals with parkinsonism, who had an uncertain diagnosis at the time of inclusion and who were followed for up to 12 years in a longitudinal study. We performed shotgun proteomics to identify tryptic peptides in CSF of Parkinson's disease (PD, n = 10), multiple system atrophy patients (MSA, n = 5) and non-neurological controls (n = 10). We validated tryptic peptides with differential levels between PD and MSA using a newly developed selected reaction monitoring (SRM) assay in CSF of PD (n = 46), atypical parkinsonism patients (AP; MSA, n = 17; Progressive supranuclear palsy; n = 8) and non-neurological controls (n = 39). We identified 191 tryptic peptides that differed significantly between PD and MSA, of which 34 met our criteria for SRM development. For 14/34 peptides we confirmed differences between PD and AP. These tryptic peptides discriminated PD from AP with moderate-to-high accuracy. Random forest modelling including tryptic peptides plus either clinical assessments or other CSF parameters (neurofilament light chain, phosphorylated tau protein) and age improved the discrimination of PD vs. AP. Our results show that the discovery of tryptic peptides by untargeted and subsequent validation by targeted proteomics is a suitable strategy to identify potential CSF biomarkers for PD versus AP. Furthermore, the tryptic peptides, and corresponding proteins, that we identified as differential biomarkers may increase our current knowledge about the disease-specific pathophysiological mechanisms of parkinsonism.

Common Factors in Neurodegeneration: A Meta-Study Revealing Shared Patterns on a Multi-Omics Scale

Neurodegenerative diseases such as Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), and amyotrophic lateral sclerosis (ALS) are heterogeneous, progressive diseases with frequently overlapping symptoms characterized by a loss of neurons. Studies have suggested relations between neurodegenerative diseases for many years (e.g., regarding the aggregation of toxic proteins or triggering endogenous cell death pathways). We gathered publicly available genomic, transcriptomic, and proteomic data from 177 studies and more than one million patients to detect shared genetic patterns between the neurodegenerative diseases on three analyzed omics-layers. The results show a remarkably high number of shared differentially expressed genes between the transcriptomic and proteomic levels for all conditions, while showing a significant relation between genomic and proteomic data between AD and PD and AD and ALS. We identified a set of 139 genes being differentially expressed in several transcriptomic experiments of all four diseases. These 139 genes showed overrepresented gene ontology (GO) Terms involved in the development of neurodegeneration, such as response to heat and hypoxia, positive regulation of cytokines and angiogenesis, and RNA catabolic process. Furthermore, the four analyzed neurodegenerative diseases (NDDs) were clustered by their mean direction of regulation throughout all transcriptomic studies for this set of 139 genes, with the closest relation regarding this common gene set seen between AD and HD. GO-Term and pathway analysis of the proteomic overlap led to biological processes (BPs), related to protein folding and humoral immune response. Taken together, we could confirm the existence of many relations between Alzheimer's disease, Parkinson's disease, Huntington's disease, and amyotrophic lateral sclerosis on transcriptomic and proteomic levels by analyzing the pathways and GO-Terms arising in these intersections. The significance of the connection and the striking relation of the results to processes leading to neurodegeneration between the transcriptomic and proteomic data for all four analyzed neurodegenerative diseases showed that exploring many studies simultaneously, including multiple omics-layers of different neurodegenerative diseases simultaneously, holds new relevant insights that do not emerge from analyzing these data separately. Furthermore, the results shed light on processes like the humoral immune response that have previously been described only for certain diseases. Our data therefore suggest human patients with neurodegenerative diseases should be addressed as complex biological systems by integrating multiple underlying data sources.

Transcriptional alterations in skin fibroblasts from Parkinson's disease patients with parkin mutations

Mutations in the parkin gene (PRKN) are the most common cause of autosomal-recessive juvenile Parkinson's disease (PD). PRKN encodes an E3 ubiquitin ligase that is involved in multiple regulatory functions including proteasomal-mediated protein turnover, mitochondrial function, mitophagy, and cell survival. However, the precise molecular events mediated by PRKN mutations in PRKN-associated PD (PRKN-PD) remain unknown. To elucidate the cellular impact of parkin mutations, we performed an RNA sequencing study in skin fibroblasts from PRKN-PD patients carrying different PRKN mutations (n = 4) and genetically unrelated healthy subjects (n = 4). We identified 343 differentially expressed genes in PRKN-PD fibroblasts. Gene ontology and canonical pathway analysis revealed enrichment of differentially expressed genes in processes such as cell adhesion, cell growth, and amino acid and folate metabolism among others. Our findings indicate that PRKN mutations are associated with large global gene expression changes as observed in fibroblasts from PRKN-PD patients and support the view of PD as a systemic disease affecting also non-neural peripheral tissues such as the skin.

Estrogen deficiency is associated with hippocampal morphological remodeling of early postmenopausal mice

Estrogen (E₂) deficiency is reported to involve in the impairment of cognition in postmenopausal women. However, the morphological basis is still unclear. In the present study, using transmission electron microscopy (TEM), we observed the ultrastructure of hippocampus in female C57BL/6 mice at the age of 18 months (18 M) which is considered as the early stage of postmenopause (n = 8). Compared with control mice aged 6 M (n = 8), we identified that the morphological changes in the hippocampus of these menopausal mice were mitochondrial damage, lipofuscin deposition and microtubule degradation. Notably, after E₂ was subcutaneously injected into mice aged 16 M with a dosage of 3.5 μg/kg every three days for two months in the 18 M + E₂ group (n = 8), mitochondrial damage and lipofuscin deposition in the DG region of hippocampus were prevented, but the degraded microtubules in the hippocampus of postmenopausal mice were failed to restore. These data suggest that hippocampal ultrastructure remodeling in mice can be initiated at the early stage of postmenopause, E₂ supplementation could only have an effect on mitochondrial damage and lipofuscin increase.

Proteome Analysis of Potential Synaptic Vesicle Cycle Biomarkers in the Cerebrospinal Fluid of Patients with Sporadic Creutzfeldt-Jakob Disease

Sporadic Creutzfeldt-Jakob disease (sCJD) is the most frequent fatal human prion disease with a rapid progression and unknown mechanism. The synaptic vesicle (SV) cycle pathway has been a hot research field associated with many neurodegenerative diseases that affect synaptic function and thus may affect pathogenesis of the disorder. Here, we used the iTRAQ-based proteomic method and a KEGG pathway enrichment analysis to meticulously analyze all pathways involved in sCJD disease. In total, 1670 proteins were validated in pooled cerebrospinal fluid (CSF) from 20 patients with sCJD compared with that from 13 patients without CJD. The demographic analysis demonstrated that 557 proteins were upregulated and 595 proteins were downregulated with a 1.5-fold change, and 690 proteins involved in 39 pathways changed significantly (p ≤ 0.05) according to the enrichment analysis. The SV cycle pathway and proteins involved were further evaluated, and 14 proteins were confirmed to participate in the SV cycle pathway due to increased expression. Six key proteins, such as AP2A1, SYT1, SNAP25, STXBP1, CLTB, and Rab3a, showed the same trend by western blot as detected by iTRAQ. This is the first study to use high-throughput proteomics to accurately identify and quantify proteins in the SV cycle pathway of a neurodegenerative disease. These results will help define the mechanism and provide new insight into the pathogenetic factors involved in the SV cycle pathway in patients with sCJD. We hope that promising biomarkers can be identified in the CSF of patients with sCJD and other neurodegenerative disorders to help predict disease progression.

eSNPO: An eQTL-based SNP Ontology and SNP functional enrichment analysis platform

Genome-wide association studies (GWASs) have mined many common genetic variants associated with human complex traits like diseases. After that, the functional annotation and enrichment analysis of significant SNPs are important tasks. Classic methods are always based on physical positions of SNPs and genes. Expression quantitative trait loci (eQTLs) are genomic loci that contribute to variation in gene expression levels and have been proven efficient to connect SNPs and genes. In this work, we integrated the eQTL data and Gene Ontology (GO), constructed associations between SNPs and GO terms, then performed functional enrichment analysis. Finally, we constructed an eQTL-based SNP Ontology and SNP functional enrichment analysis platform. Taking Parkinson Disease (PD) as an example, the proposed platform and method are efficient. We believe eSNPO will be a useful resource for SNP functional annotation and enrichment analysis after we have got significant disease related SNPs.

Microarray Expression Analysis for the Paradoxical Roles of Acanthopanax senticosus Harms in Treating α-Synucleinopathies

α-Synuclein is a key player in the pathogenesis of neurodegenerative disorders with Lewy bodies. Our previous studies have also showed that Acanthopanax senticosus harms (AS) could significantly suppress α-synuclein overexpression and toxicity. Identifying the RNAs related to α-synucleinopathies may facilitate understanding the pathogenesis of the diseases and the safe application of AS in the clinic. Microarray expression profiling of long non-coding RNAs (lncRNAs) and mRNAs was undertaken in control non-transgenic and human α-synuclein transgenic mice. The effects of AS on central nervous system (CNS) in pathology and physiology were investigated based on the lncRNA/mRNA targets analysis. In total, 341 lncRNAs and 279 mRNAs were differentially expressed by α-synuclein stimulus, among which 29 lncRNAs and 25 mRNAs were involved in the anti-α-synucleinopathies mechanism of AS. However, the levels of 19/29 lncRNAs and 12/25 mRNAs in AS group were similar to those in α-synuclein group, which may cause potential neurotoxicity analogous to α-synuclein. This study demonstrated that some of lncRNAs/mRNAs were involved in α-synuclein related pathophysiology, and AS produced the bidirectional effects on CNS under pathological and physiological conditions.