Journal of Molecular Neuroscience最新文献

Alzheimer’s disease (AD), a prevalent neurodegenerative disorder, is characterized by mitochondrial dysfunction and immune dysregulation. This study is aimed at developing a risk prediction model for AD by integrating multi-omics data and exploring the interplay between mitochondrial energy metabolism-related genes (MEMRGs) and immune cell dynamics. We integrated four GEO datasets (GSE132903, GSE29378, GSE33000, GSE5281) for differential gene expression analysis, functional enrichment, and weighted gene co-expression network analysis (WGCNA). We identified two key gene modules (turquoise and magenta) significantly correlated with AD. Subsequently, we constructed a risk prediction model incorporating five MEMRGs (MRPL15, RBP4, ABCA1, MPV17, and MRPL37) and clinical factors using LASSO regression. The model demonstrated robust predictive performance (AUC > 0.815) in both internal and external validation (GSE44770) cohorts. Downregulation of MRPL15, RBP4, MPV17, and MRPL37 in AD brain regions (validated using AlzData and qRT-PCR) suggests impaired mitochondrial function. Conversely, ABCA1 upregulation may represent a compensatory response. Furthermore, significant differences in immune cell proportions, particularly gamma delta T cells (p = 0.002) and activated CD4 memory T cells (p = 0.027), were found between AD and non-demented samples. We observed significant correlations between MEMRG expression and specific immune cell fractions, indicating a potential link between mitochondrial dysfunction and immune dysregulation in AD. Our study provides a reliable risk prediction model for AD and highlights the crucial roles of MEMRGs and immune responses in disease pathogenesis, offering potential targets for therapeutic interventions.

Hemorrhagic stroke is a known complication of glioma, yet the underlying mechanisms remain poorly understood. This study aims to investigate key biomarkers of glioma-related hemorrhage to provide insights into glioma molecular therapies. Data were obtained from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) databases to analyze differentially expressed genes (DEGs) in glioma by contrasting glioblastoma (GBM) with low-grade gliomas (LGGs). We conducted enrichment analyses using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) databases through the Database for Annotation, Visualization, and Integrated Discovery (DAVID). A STRING-based protein–protein interaction (PPI) network was developed to identify hub genes, which were subsequently analyzed for their functions in the GeneCards database. To identify angiogenesis-associated genes, we utilized the Human Protein Atlas (HPA) and Gene Expression Profiling Interactive Analysis (GEPIA) databases. A clinical pathological study was conducted using immunohistochemistry (IHC) staining to confirm the findings. In the GEO database, the GEO Series Experiments GSE26576 and GSE184941 included 4523 and 1471 differentially expressed genes (DEGs), respectively. We identified 2715 DEGs using the cBioPortal within the TCGA database. A Venn diagram identified 39 common DEGs. The KEGG pathways and Gene Ontology (GO) analysis highlighted functions related to angiogenesis. PPI network analyses pinpointed 13 hub genes. Through cross-referencing a gene set related to tumor angiogenesis in the GeneCards database, we identified MMP-2 and EGFR as key genes. In the HPA database, we observed EGFR and MMP-2 expression in the normal cerebral cortex, confirmed by IHC. In GEPIA database, high MMP-2 levels were associated with decreased survival time, while EGFR expression showed no significant differences in survival. A clinical study of 21 patients, 11 in the control group and 10 in the stroke group with glioma hemorrhage, revealed no significant differences in their characteristics or comorbidities. IDH1 positivity was higher in the control group (4/11) vs the stroke group (0/10). Tumor cells exhibited increased MMP-2 and EGFR expression, with stronger staining in the stroke group. Our study concluded that IDH1, MMP-2, and EGFR are implicated in the molecular mechanism of glioma hemorrhage as key biomarkers. MMP-2 and IDH1 are potential targets for molecular therapy.

Acute ischemic stroke (AIS) is a severe disorder characterized by complex pathophysiological processes, which can lead to disability and death. This study aimed to determine necroptosis-associated genes in acute ischemic stroke (AIS) and to investigate their potential as diagnostic and therapeutic targets for AIS. Expression profiling data were acquired from the Gene Expression Omnibus database, and necroptosis-associated genes were retrieved from GeneCards. The differentially expressed genes (DEGs) and necroptosis-related genes were intersected to obtain the necroptosis-related DEGs (NRDEGs) in AIS. In AIS, a total of 76 genes associated with necroptosis (referred to as NRDEGs) were identified. Enrichment analysis of these genes revealed that they were primarily enriched in pathways known to induce necroptosis. Using weighted gene co-expression network analysis (WGCNA), five co-expression modules consisting of NRDEGs were identified, along with two modules that exhibited a strong correlation with AIS. Protein–protein interaction (PPI) analysis resulted in the identification of 20 hub genes. The Least absolute shrinkage and selection operator (LASSO) regression model demonstrated promising potential for diagnostic prediction. The receiver operating characteristic (ROC) curve validated the diagnostic model and selected nine characteristic genes that exhibited statistically significant differences (p < 0.05). By employing consensus clustering, distinct patterns of necroptosis were identified using these nine signature genes. The results were validated by quantitative PCR (qPCR) in venous blood from patients with AIS and healthy controls and HT22 cells, as well as external datasets. Furthermore, the analyzed ceRNA network included nine lncRNAs, six miRNAs, and three mRNAs. Overall, this study offers novel insights into the molecular mechanisms underlying NRDEGs in AIS. The findings provide valuable evidence and contribute to our understanding of the disease.

Focal cortical dysplasia (FCD) II is a cortical malformation characterized by cortical architectural abnormalities, dysmorphic neurons, with or without balloon cells. Here, we systematically explored the pathophysiological role of the GATOR1 subunit NPRL3 variants including a novel mutation from iPSCs derived from one FCD II patient. Three FCD II children aged 0.5–7 years who underwent cerebral lesion resection in our hospital from March 2019 to October 2019 were included in this study. We generated patient-derived iPSCs and performed whole-exome sequencing to accurately identify somatic cells with mutations. The effect of the newly identified NPRL3 mutation found in one of our FCD II patients was evaluated using the personalized cortical organoid model and the NPRL3 knockout HEK293T cells. Whole-exome sequencing of iPSCs derived from FCD II patients revealed a novel NPRL3 C.767G > C (p.R256P) heterozygous mutation. Cortical organoids generated from iPSCs of FCD II patients were larger than control iPSCs, with increased number of p-S6⁺ cells and NeuN⁺ neurons. In NPRL3 knockout HEK293T cells, overexpression of NPRL3  together with NPRL2 protein is necessary to reduce p-S6 level upon amino acid starvation. The reduced binding between NPRL3 ^Arg256Pro and NPRL2 protein leads to downregulation of the relative total protein amount of both proteins in the cell. Our study describes a novel cortical organoid model generated from iPSCs of the FCD patients to investigate the underlying mechanism of NPRL3-related epilepsy. The mutation of NPRL3 ^Arg256Pro impaired the function of NPRL3 protein via affecting the binding with NPRL2 protein, which resulted in unstable protein monomer.

Elevated inflammatory reactions are a significant component in cerebral ischemia–reperfusion injury (CIRI). Activation of α7-Nicotinic Acetylcholine Receptor (α7nAChR) reduces stroke-induced inflammation in rats, but the anti-inflammatory pathway in microglia under CIRI condition remains unclear. This study employed qRT-PCR, protein assays, NanoString analysis, and bioinformatics to examine the effects of PNU282987 treatment (α7nAChR agonist) on BV2 microglial functional differentiation in oxygen–glucose deprivation/reoxygenation (OGDR) condition. OGDR significantly increased the gene expression of pro-inflammatory markers such as TNF-α, IL-6, and IL1β, while α7nAChR agonists reduced these markers. The anti-inflammatory gene marker IL-10 was upregulated by α7nAChR agonist treatment. Downstream pathway marker analysis showed that both gene and protein expression of NFκB was associated with anti-inflammatory effects. Blocking microRNA-21 with antagomir reversed the anti-inflammatory effects. NanoString analysis revealed that microRNA-21 inhibition significantly affected inflammation-related genes, including AL1RAP, TLR9, FLT1, PTGIR, NFκB, TREM2, TNF, SMAD7, FOS, CCL5, IFIT1, CFB, CXCL10, IFI44, DDIT3, IRF7, OASL1, IL1A, IFIT2, C3, CD40, STAT2, IFIT3, IL1RN, OAS1A, CSF1, CCL4, CCL2, CCL3, BCL2L1, and ITGB2. Enrichment analysis of upregulated genes identified Gene Ontology Biological Processes related to cytokine responses and TNF-associated pathways. This study highlights α7nAChR activation as a key regulator of anti-inflammatory responses in BV2 microglia under OGDR conditions, with micro-RNA21 identified as a crucial mediator of receptor-driven neuroprotection via the TNF-α/NFκB signalling pathway.

Background and Objectives

Data on the association between BDNF rs6265 and multiple sclerosis (MS) are scarce and heterogeneous.

Materials and Methods

We undertook a case–control study design. Newly diagnosed individuals with MS based on the 2017 revision of the McDonald criteria were recruited from the Neurology Department of the General University Hospital of Larissa. Healthy controls with a free medical and family history were also recruited. The relationship between BDNF rs6265 and MS was defined as the primary outcome. The association between rs6265 and age of MS onset, spinal lesions, and clinical manifestations at the time of MS onset were defined as the secondary outcomes.

Results

We genotyped a total of 200 patients with MS and 205 healthy controls, yielding a sample power of approximately 80%. BDNF rs6265 was in Hardy–Weinberg Equilibrium among healthy participants (p = 0.64). No significant relationship was revealed between rs6265 and MS [log-additive OR = 0.83 (0.57,1.21), over-dominant OR = 0.73 (0.48,1.14), recessive OR = 1.24 (0.37,4.12), dominant OR = 0.77 (0.50,1.17), co-dominant OR1 = 0.74 (0.48,1.14) and co-dominant OR2 = 1.13 (0.34,3.80)]. Additionally, rs6265 was unrelated to the age of MS onset according to both unadjusted and sex-adjusted cox-proportional models. Finally, rs6265 was not associated with the presence of spinal lesions (cervical or thoracic) at MS onset, according to both unadjusted and age and sex-adjusted logistic regression models.

Conclusions

We failed to establish an association between BDNF rs6265 and the risk of MS, the age of onset, the presence of spinal lesions, and the clinical manifestations at the onset.

Depression is a common disease that affects 3.8% of the global population. Despite various antidepressant treatments, one-third of patients do not respond to antidepressants, therefore augmentation with mood stabilizers such as lithium may be required in this group. One of the suggested pathomechanisms of depression is the dysregulation of the hypothalamic–pituitary–adrenal (HPA) axis and recent reports showed that microRNAs (miRNA) can impact its activity by epigenetic regulation. We aimed to explore the miRNA expression profile in the depression model and its changes upon short-term and chronic lithium treatment in the rat brain (pituitary, hypothalamus, and hippocampus). We used a chronic mild stress rat model of depression and short- and long-term lithium treatment. The behavior was assessed by an open-field test. The miRNA expression profile in the pituitary was estimated by sequencing and validated in the hypothalamus and hippocampus with qPCR. We found several miRNAs in the pituitary that were significantly altered between CMS-exposed and control rats as well as after short- and long-term lithium treatment. MicroRNAs chosen for validation in the hypothalamus and hippocampus (rno-miR-146a-5p, rno-miR-127-3p) showed no significant changes in expression. We performed in silico analysis and estimated potential pathways involved in lithium action for miRNAs differentially expressed in the pituitary at different time points. Specific microRNA subsets showed altered expression in the pituitary in depression model upon short- and long-term lithium treatment. We identified that biological pathways of target genes for these altered miRNAs differ, with the Foxo pathway potentially involved in disease development.

Ischemic stroke is a leading cause of mortality and disability globally. Understanding the role of chemokine-related differently expressed genes (CDGs) in ischemic stroke pathophysiology is essential for advancing diagnostic and therapeutic strategies. We conducted comprehensive analyses using the GSE16561 dataset: chemokine pathway enrichment via GSVA, differential expression of 12 CDGs, Pearson correlation, and functional enrichment analyses (GO and KEGG). Machine learning algorithms were employed to develop diagnostic models, evaluated using ROC curve analysis. A nomogram was constructed and validated with independent datasets (GSE58294). Gene set enrichment analysis (GSEA) and immuno-infiltration analysis were also performed. Chemokine pathway scores were significantly elevated in ischemic stroke, indicating their potential involvement. Logistic regression emerged as the most effective diagnostic model, with CXCL16 and SEMA3E as significant biomarkers. The nomogram exhibited high discriminatory ability (AUC = 0.964), well-calibrated predictions, and clinical utility across datasets. GSEA highlighted key biological pathways associated with CXCL16 and SEMA3E. Immuno-infiltration analysis revealed significant differences in immune cell infiltration between control and ischemic stroke groups, with distinct correlations between CXCL16 and SEMA3E expression and immune cell populations. This study highlights the deregulation of CDGs in ischemic stroke and their implications in critical biological processes. CXCL16 and SEMA3E are identified as key biomarkers with potential diagnostic utility. Insights from gene set enrichment and immuno-infiltration analyses provide mechanistic understanding, suggesting novel therapeutic targets and enhancing clinical decision-making in ischemic stroke management.

Advanced glycation end products (AGEs) have attracted interest as therapeutic targets for neurodegenerative diseases. AGEs facilitate the onset and progression of various neurogenerative disorders due to their ability to promote cross-linking and aggregation of proteins. Further, the interaction between AGEs and receptor for AGEs (RAGE) activates neuroinflammatory, oxidative stress and excitotoxicity processes that contribute to neuronal cell death. Various therapeutic efforts have targeted lowering the production of AGEs, inhibiting RAGE or inhibiting some of the processes of the AGE-RAGE axis as potential treatments for these disorders. Whereas effective treatments for many neurodegenerative disorders remain elusive, such efforts offer promise to slow the progression of diseases such as Alzheimer’s disease (AD), Parkinson’s disease (PD) and Huntington’s disease (HD).