Journal of Molecular Neuroscience最新文献

Fragile X syndrome is the most common inherited form of intellectual disability and is caused by the transcriptional silencing of the Fmr1 gene and the lack of fragile X messenger ribonucleoprotein (FMRP). FMRP is an RNA-binding protein that regulates the synthesis of synaptic proteins which are essential for proper brain function. Although circuit hyperexcitability is a hallmark of fragile X syndrome (FXS), the cell-autonomous effects of FMRP deficiency remain poorly understood. In this work, we investigated the functional consequences of the absence of FMRP on neuronal morphology and on ionotropic glutamate receptor surface distribution, using primary cultures of mice hippocampal neurons isolated from wild-type (WT) and Fmr1 knock-out (KO) pups. MAP2 staining of Fmr1 KO neurons showed a decrease in total dendritic length and complexity of the dendritic tree, accompanied by an increase in soma size compared to WT neurons. Moreover, immunolabelling of surface glutamate receptors performed under non-permeabilising conditions showed that Fmr1 KO neurons presented a higher content of synaptic surface GluN2A and a lower content of GluN2B subunits of NMDA receptors, while GluA1 and GluA2 distribution remained unchanged. Finally, multielectrode array data showed that Fmr1 KO neurons presented reduced spontaneous activity compared to control neurons. These data support the hypothesis that at the cellular level, Fmr1 KO hippocampal neurons are less excitable due to altered input processing, driven by structural defects and altered GluN2A expression in the synaptic plasma membrane.

Thyroid hormone receptor interactor 12 (TRIP12; MIM #617,752) is an autosomal dominant hereditary disorder involved in the ubiquitin fusion degradation pathway and the regulation of DNA damage-induced chromatin ubiquitination. Positioned on chromosome 2 at position 2q36.3, TRIP12 is a member of the E3 ubiquitin ligase family. This gene plays a vital role in proteasomal degradation by catalyzing substrate ubiquitination and regulating processes such as cell cycle progression, DNA damage repair, and chromatin remodeling. Mutations in TRIP12 can result in intellectual disability (ID), Clark-Baraitser syndrome, and various physical and behavioral abnormalities. The proband, a 32-year-old male, exhibited intellectual disability, delayed speech, and behavioral abnormalities without autistic spectrum disorders. The novel TRIP12 variant was detected through WES and validated by Sanger sequencing in affected family members. In silico tools predicted the deleterious effect of the variant, and protein modeling indicated significant structural changes. RT-qPCR demonstrated increased TRIP12 mRNA levels, suggesting a compensatory mechanism for decreased protein stability. This study examines the role of the TRIP12 gene in the ubiquitin pathway and associated pathologies such as intellectual disability and developmental delay.

Alzheimer’s disease (AD) is the most prevalent form of dementia, significantly contributing to the global health burden. The progressive accumulation of amyloid-beta (Aβ) plaques and tau tangles triggers neuroinflammation, oxidative stress, and neuronal damage, highlighting the critical need for effective clearance mechanisms. Recent research has identified low-density lipoprotein receptor-related protein 1 (LRP1) as a key factor in the regulation of Aβ clearance, neuroinflammation, and blood–brain barrier integrity, particularly in relation to the liver-brain axis. This review provides a comprehensive examination of the role of LRP1 in AD, focusing on its expression in the brain and liver, its contribution to Aβ metabolism, and its potential as a therapeutic target. Using a systematic literature review, LRP1’s multifaceted roles across various biological processes were explored, including its involvement in Aβ transport, clearance via the liver, and modulation of neuroinflammation. Additionally, the impact of physical exercise, pharmacological interventions, and dietary factors on LRP1 expression levels was investigated, elucidating how these approaches may enhance Aβ clearance. The findings demonstrate that LRP1 expression decreases progressively as AD advances, and that augmenting LRP1 activity—particularly through exercise and drug therapies—can improve Aβ clearance and reduce neuroinflammatory responses. Furthermore, LRP1’s involvement in the liver-brain axis reveals its broader systemic role in AD pathology. In conclusion, targeting LRP1 offers a promising avenue for AD prevention and treatment, providing new insights into the therapeutic potential of enhancing Aβ clearance pathways through the liver-brain axis.

Autism spectrum disorders (ASD) are characterized by clinical heterogeneity and may be associated with cerebral folate deficiency (CFD). Among the causes, folate receptor alpha autoantibodies (FRAA) and variants of the SLC19A1 gene are commonly highlighted. The aim of this study was to analyze the rs1051266 variant of the SLC19A1 gene in patients with ASD and CFD and to determine its relationship with clinical and laboratory parameters. The study included 227 children with ASD, 156 of whom had CFD. FRAA detection, genotyping of the rs1051266 variant, and folate metabolism marker measurement (homocysteine, vitamins B9, B12, B6) were performed. FRAA binding was detected in 39.2% of ASD patients, blocking FRAA in 3.5%, and a specific soluble folate receptor in 13.2%. The 80GA genotype was the most common (46.3%), and homocysteine levels tended to be moderately elevated (upper quartile – 7.0). Significant correlations were found between homocysteine levels and vitamins B9, B12, and B6 (p < 0.05) and between verbal impairments and vitamin B12 (p = 0.043). In ASD and CFD patients, the 80GG genotype was more frequent (p = 0.03) and vitamin B12 levels were elevated (p = 0.021). In the ASD group, correlations were found between the 80AA genotype and demyelination (p = 0.020) and between homocysteine levels and demyelination (p = 0.042). In conclusion, the rs1051266 variant of the SLC19A1 gene modifies the clinical course of ASD. Patients with ASD and CFD exhibited high variability in folate metabolism markers. These findings underline the need for further research on folate transport genetics for personalized prevention and treatment strategies for ASD and CFD.

The function of CD73 (Cluster of Differentiation 73), an enzyme involved in the formation of adenosine (ADO), in the development of glioblastomas has been demonstrated. Indeed, ADO helps tumor angiogenesis by stimulating endothelial cell migration, proliferation, and tube formation. However, the details of the molecular mechanisms are not yet fully understood. Given the importance of angiogenesis in cancer progression, invasion, and metastasis, this study aimed to investigate how the inhibition of CD73 by adenosine-5′-(α, β-methylene) diphosphate (APCP) affects the angiogenesis process of experimental orthotopic glioblastoma at mRNAs, microRNAs, and protein levels. According to the real-time-polymerase chain reaction (RT-PCR) results, inhibition of CD73 decreased the angiogenesis of glioblastoma by reducing the expression of vascular endothelial growth factor (VEGF) and hypoxia-inducible factor 1-alpha (HIF-1α) by ****P < 0.0001 and **P < 0.01, respectively. Furthermore, immunohistochemical staining showed that this treatment protocol attenuated the expression of VEGF and CD31. Moreover, APCP treatment significantly increased miR-16 expression in glioblastoma model rats by P < 0.001, but no significant change in miR-29A expression was observed. The results showed that the treatment did not lead to systemic damage or significant weight loss. Our results suggest that inhibition of CD73 may reduce the formation of new tumor vessels by inhibiting the VEGF, HIF-1α, and CD31 in this process. Therefore, CD73 may be a practical target and provide new opportunities to improve the treatment of malignant brain tumors.

Growth-associated protein 43 (GAP-43), a key regulator of synaptic plasticity, neuronal growth, and memory, has recently been identified as a crucial biomarker for synaptic dysfunction in mild cognitive impairment (MCI) and Alzheimer’s disease (AD) dementia. This study aimed to explore the mechanisms underlying GAP-43’s role in cognitive impairment by examining the relationship between CSF GAP-43 levels and amyloid-β (Aβ) accumulation in brain regions like the frontal, temporal, and parietal lobes. This study included 332 participants sourced from the Alzheimer’s Disease Neuroimaging Initiative (ADNI), categorized into three groups: 93 cognitively normal (CN), 218 with MCI, and 21 with AD dementia. Cognitive status was assessed with ADAS-Cog 13, CSF GAP-43 levels via ELISA, and Aβ accumulation using florbetapir PET imaging and Syngo.PET for SUVr values in key brain regions. The results revealed that CSF GAP-43 levels were highest in the AD dementia group, followed by the MCI group, and lowest in the CN group, with a significant difference (p < 0.001), indicating a link between elevated CSF GAP-43 and cognitive impairment. In MCI group, CSF GAP-43 positively correlated with Aβ accumulation in all regions: Globally (β = 0.362, p < 0.001), frontal (β = 0.388, p < 0.001), temporal (β = 0.382, p < 0.001), and parietal lobes (β = 0.344, p < 0.001). In contrast, the AD dementia group exhibited negative correlations between CSF GAP-43 levels and Aβ accumulation, significantly in the frontal (β =  − 0.513, p = 0.035) and parietal lobes (β =  − 0.513, p = 0.035), suggesting a shift in the CSF GAP-43-Aβ relationship in AD dementia. Mediation analysis, adjusted for age, gender, education, and ApoE ɛ4 status, revealed that elevated CSF GAP-43 is linked to increased cognitive impairment via increasing Aβ accumulation solely in MCI, with significant effects in global (β = 0.0894, CI: [0.0427, 0.1457]), frontal (β = 0.0895, CI: [0.0422, 0.1443]), temporal (β = 0.0941, CI: [0.0466, 0.1522]), and parietal (β = 0.0499, CI: [0.0100, 0.0945]) regions. Thus, elevated CSF GAP-43 may contribute to cognitive impairment by promoting Aβ accumulation in individuals with MCI, while in AD dementia, it may be associated with reduced Aβ accumulation, potentially reflecting a compensatory or disease-stage-dependent effect. This dynamic relationship suggests that GAP-43 could play a dual role in neurodegeneration, influencing Aβ pathology differently across disease stages.

Autoimmune encephalitis (AE) is an immune-mediated non-infectious disease, and novel and robust biomarkers are needed to improve the diagnosis and prognostic outcomes of AE. Oxidative stress is a ubiquitous cellular process causing damage to various biological molecules. The aim of our study was to understand the clinical implication and mechanism underlying oxidative stress in AE. Liquid chromatography-mass spectrometry analysis was conducted on the serum of eight patients with AE and seven healthy controls, and oxidative stress was characterized. Experimental autoimmune encephalitis (EAE) models were established in C57BL/6 and SJL mice for investigation of the therapeutic effect and mechanism of anti-oxidative stress N-acetylcysteine (NAC). We provided proteomic landscape in the serum of AE and identified antioxidant ALB, APOE, GPX3, and SOD3 as serum diagnostic markers of AE. The antioxidant markers were lowly expressed both in the serum of AE patients and central nervous system (CNS) of EAE mice. NAC administration improved clinical signs and motor function and alleviated nerve injury of EAE mice as well as lowered oxidative stress (decreased MDA content and ROS accumulation and elevated SOD activity and GSH content). ALB, APOE, GPX3, and SOD3 expressions were elevated by NAC in the CNS of EAE mice. Moreover, NAC reduced tissue-resident CD4⁺ and CD8⁺ T cells and GFAP-marked astrocytes and Iba-1-marked microglia in EAE mice, thus alleviating autoimmunity-mediated damage and neuroinflammation. Our findings facilitate the discovery of novel oxidative stress-related biomarkers for AE and reveal the promise of anti-oxidative stress for AE management.

Low-grade gliomas (LGG) are malignant brain tumors that arise from the brain’s support cells (glial cells). LGG are the most common kind of central nervous system tumors in children and adolescents, accounting for around half of all cases. Tumor Protein p53 (TP53) regulates or promotes DNA damage and repair via a variety of cell cycle, apoptosis, and genomic stability pathways. However, the clinical role of TP53 status in LGG patients is still unknown. Hence, we analyzed clinical data from the Cancer Genomic Atlas (TCGA) of LGG patients to see if TP53 status affects clinical outcomes, molecular signatures of chemokines and microRNAs, and immune cell infiltrations within the tumor’s microenvironment of LGG patients. According to our findings, the most common phenotype in LGG patients is wild-type TP53, which is related to poor clinical outcomes and the expression of Chemokine ligand 14 (CXCL14) in many clinical parameters such as age, gender, stage, race, and purity. Besides, in LGG patients, wild-type TP53 controls prognostic microRNAs such as has-miR-10a-3p and has-miR-155-5p. Furthermore, through activating GATA Binding Protein 3 (GATA3) and decreasing Fatty Acid Synthase (FASN), wild-type TP53 orchestrates M1 macrophage and CD8⁺ T cell infiltration, as well as the formation of brown adipose tissue and decreased white adipose tissue. In this regard, the TP53-CXCL14-GATA3 axis has the potential to predict poor clinical outcomes in patients with wild-type TP53 LGG.

Parkinson’s disease recognition (PDR) involves identifying Parkinson’s disease using clinical evaluations, imaging studies, and biomarkers, focusing on early symptoms like tremors, rigidity, and bradykinesia to facilitate timely treatment. However, due to noise, variability, and the non-stationary nature of EEG signals, distinguishing PD remains a challenge. Traditional deep learning methods struggle to capture the intricate temporal and spatial dependencies in EEG data, limiting their precision. To address this, a novel fusion framework called graph embedding class-based convolutional recurrent attention network with Brown Bear Optimization Algorithm (GECCR2ANet + BBOA) is introduced for EEG-based PD recognition. Preprocessing is conducted using numerical operations and noise removal with weighted guided image filtering and entropy evaluation weighting (WGIF-EEW). Feature extraction is performed via the improved VGG19 with graph triple attention network (IVGG19-GTAN), which captures spatial and temporal dependencies in EEG data. The extracted features are classified using the graph embedding class-based convolutional recurrent attention network (GECCR2ANet), further optimized through the Brown Bear Optimization Algorithm (BBOA) to enhance classification accuracy. The model achieves 99.9% accuracy, 99.4% sensitivity, and a 99.3% F1-score on the UNM dataset, and 99.8% accuracy, 99.1% sensitivity, and 99.2% F1-score on the UC San Diego dataset, significantly outperforming existing methods. Additionally, it records an error rate of 0.5% and a computing time of 0.25 s. Previous models like 2D-MDAGTS, A-TQWT, and CWCNN achieved below 95% accuracy, while the proposed model’s 99.9% accuracy underscores its superior performance in real-world clinical applications, enhancing early PD detection and improving diagnostic efficiency.