Journal of Molecular Neuroscience最新文献

{"title":"Analysis of Common Genetic Variation of Anxiety Disorders in Essential Tremor","authors":"Yaping Yan,&nbsp;Lanxiao Cao,&nbsp;Luyan Gu,&nbsp;Congying Xu,&nbsp;Jinyu Lu,&nbsp;Dayao Lv,&nbsp;Jun Tian,&nbsp;Xinzhen Yin,&nbsp;Jiali Pu,&nbsp;Baorong Zhang,&nbsp;Guohua Zhao","doi":"10.1007/s12031-024-02226-2","DOIUrl":"10.1007/s12031-024-02226-2","url":null,"abstract":"<div><p>The objective of this study is to explore the association of common genetic variation of anxiety disorders and essential tremor (ET). We genotyped 25 anxiety-specific risk variants in a cohort of 478 unrelated ET patients and 504 age and gender-matched healthy controls from eastern China using a MassARRAY system. The association between candidate variants and ET patients was evaluated using gene-based analysis. A total of 159 patients (33.3%) had anxiety. In genotypic analysis, rs708012 (in an intergenic region) in the dominant models was found to be significantly associated with ET (<i>P</i> &lt; 0.001, OR = 0.605). In allelic analysis, the carriers of the C allele of <i>NTRK2</i> rs1187280 (<i>P</i> = 0.027, OR = 0.626), T allele of <i>TMEM106B</i> rs3807866 (<i>P</i> = 0.030, OR = 1.287), and T allele of rs708012 (<i>P</i> &lt; 0.001, OR = 0.679) occupy a larger proportion of ET patients compared with healthy controls. Anxiety-specific risk SNPs of <i>TMEM106B</i> rs3807866 increase the risk for ET, while two SNPs of <i>NTRK2</i> rs1187280 and rs708012 show a protective role.</p></div>","PeriodicalId":652,"journal":{"name":"Journal of Molecular Neuroscience","volume":"75 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143073305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"TNFSF9 Silence Impedes Cerebral Ischemia–Reperfusion Injury via Modulating SLC3A2 Expression in Brain Microvascular Endothelial Cells","authors":"Shunli Liang,&nbsp;You Wu,&nbsp;Rongbo Zhang,&nbsp;Linsheng Xu,&nbsp;Fangping Xie","doi":"10.1007/s12031-025-02310-1","DOIUrl":"10.1007/s12031-025-02310-1","url":null,"abstract":"<div><p>Cerebral ischemia–reperfusion injury (CIRI), which stays unresolved in the clinic, occurs after recanalization of blood vessels serving brain tissues in acute ischemic stroke patients and can result in massive brain cell death, and cell ferroptosis contributes greatly to this process. Our research firstly found that TNFSF9 expression harbored diagnostic value on CIRI patients and intended to further investigate its regulatory mechanism in CIRI, which might facilitate its diagnostic and therapeutic application in the clinic. The level of TNSF9 mRNA was augmented in the plasma of CIR patients, and its silence impeded ferroptosis, apoptosis, and release of inflammatory mediators of BMECs with OGD/R treatment. Besides, SP1 positively regulated TNFSF9 expression as one of its transcription factors, and TNFSF9 overexpression reversed SP1 silence-mediated inhibition on ferroptosis, apoptosis, and release of inflammatory mediators in OGD/R-treated BMECs. In addition, silencing SLC3A2 could neutralize the benefit effects of TNFSF9 downregulation on BMECs under OGD/R context in vitro, and silencing TNFSF9 neutralized necrotic volumes in rat brain induced by CIRI via modulating SLC3A2 expression in vivo. TNFSF9 regulated by SP1 aggravated CIRI via boosting ferroptosis, apoptosis, and release of inflammatory mediators of BMECs under OGD/R situation by suppressing SLC3A2 expression in vitro and in vivo.</p></div>","PeriodicalId":652,"journal":{"name":"Journal of Molecular Neuroscience","volume":"75 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143035825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of Novel Biomarkers for Ischemic Stroke Through Integrated Bioinformatics Analysis and Machine Learning","authors":"Juan Jia,&nbsp;Liang Niu,&nbsp;Peng Feng,&nbsp;Shangyu Liu,&nbsp;Hongxi Han,&nbsp;Bo Zhang,&nbsp;Yingbin Wang,&nbsp;Manxia Wang","doi":"10.1007/s12031-025-02309-8","DOIUrl":"10.1007/s12031-025-02309-8","url":null,"abstract":"<div><p>Ischemic stroke leads to permanent damage to the affected brain tissue, with strict time constraints for effective treatment. Predictive biomarkers demonstrate great potential in the clinical diagnosis of ischemic stroke, significantly enhancing the accuracy of early identification, thereby enabling clinicians to intervene promptly and reduce patient disability and mortality rates. Furthermore, the application of predictive biomarkers facilitates the development of personalized treatment plans tailored to the specific conditions of individual patients, optimizing treatment outcomes and improving prognoses. Bioinformatics technologies based on high-throughput data provide a crucial foundation for comprehensively understanding the biological characteristics of ischemic stroke and discovering effective predictive targets. In this study, we evaluated gene expression data from ischemic stroke patients retrieved from the Gene Expression Omnibus (GEO) database, conducting differential expression analysis and functional analysis. Through weighted gene co-expression network analysis (WGCNA), we characterized gene modules associated with ischemic stroke. To screen candidate core genes, three machine learning algorithms were applied, including Least Absolute Shrinkage and Selection Operator (LASSO), random forest (RF), and support vector machine-recursive feature elimination (SVM-RFE), ultimately identifying five candidate core genes: MBOAT2, CKAP4, FAF1, CLEC4D, and VIM. Subsequent validation was performed using an external dataset. Additionally, the immune infiltration landscape of ischemic stroke was mapped using the CIBERSORT method, investigating the relationship between candidate core genes and immune cells in the pathogenesis of ischemic stroke, as well as the key pathways associated with the core genes. Finally, the key gene VIM was further identified and preliminarily validated through four machine learning algorithms, including generalized linear model (GLM), Extreme Gradient Boosting (XGBoost), RF, and SVM-RFE. This study contributes to advancing our understanding of biomarkers for ischemic stroke and provides a reference for the prediction and diagnosis of ischemic stroke.</p></div>","PeriodicalId":652,"journal":{"name":"Journal of Molecular Neuroscience","volume":"75 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143035822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical Diagnosis and Differential Diagnosis Between CSF1R- and AARS2-Related Leukoencephalopathy","authors":"Chenhui Mao,&nbsp;Yuyue Qiu,&nbsp;Tianyi Wang,&nbsp;Yuhan Jiang,&nbsp;Shanshan Chu,&nbsp;Wei Jin,&nbsp;Liling Dong,&nbsp;Jing Gao","doi":"10.1007/s12031-024-02281-9","DOIUrl":"10.1007/s12031-024-02281-9","url":null,"abstract":"<div><p><i>CSF1R</i>-related leukoencephalopathy (<i>CSF1R</i>-L) and <i>AARS2</i>-related leukoencephalopathy (<i>AARS2</i>-L) were two disease entities sharing similar phenotype and even pathological changes. Although clinically, radiologically, and pathologically similar, they were caused by mutation of two different genes. As the rarity of the two diseases, the differential diagnosis of them was difficult. 23 <i>CSF1R</i>-L and 6 <i>AARS2</i>-L patients were enrolled from the Leukoencephalopathy Clinic, Peking Union Medical College Hospital in China. Detailed clinical information, neuroimaging manifestations, and genetic data were collected and analyzed. Demographically, female patients were more in <i>AARS2</i>-L than <i>CSF1R</i>-L. Clinically, cognitive impairment and emotion/personality change were common in both groups. Bulbar palsy, extrapyramidal symptoms, and hemiplegia/pyramidal impairment were more common in <i>CSF1R</i>-L, while ataxia was significantly more common in <i>AARS2</i>-L. Abnormal menstruation including infertility was significantly more in <i>AARS2</i>-L. Radiologically, similar features were found, including lateral ventricle-centered white matter lesions, involving corpus callosum, avoiding U fibers. The lesions showed persistent hyperintensity on DWI image and were not contrasted after gadolinium enhancement. In <i>CSF1R</i>-L, the lesions could be widespread confluent or patchy and spotted, extending to centrum semiovale and subcortical white matter occasionally, which was significantly different from <i>AARS2</i>-L. Besides, brain stem lesion caused by pyramidal degeneration, spotted or linear calcification and obviously brain atrophy were common in <i>CSF1R</i>-L. In <i>AARS2</i>-L, periventricular white matter rarefaction was significantly common. No genotype and phenotype association was found in these two diseases. Although similar, there were several clinical and radiological features helping differentiating the two distinct diseases.</p></div>","PeriodicalId":652,"journal":{"name":"Journal of Molecular Neuroscience","volume":"75 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143057733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Decoding the Role of Kinesin Superfamily Proteins in Glioma Progression","authors":"Mohamed J. Saadh,&nbsp;Zahraa Sabah Ghnim,&nbsp;Morug Salih Mahdi,&nbsp;Muktesh Chandra,&nbsp;Suhas Ballal,&nbsp;Lakshay Bareja,&nbsp;Kamlesh Chaudhary,&nbsp;R. S. K. Sharma,&nbsp;Sofia Gupta,&nbsp;Waam Mohammed Taher,&nbsp;Mariem Alwan,&nbsp;Mahmood Jasem Jawad,&nbsp;Atheer Khdyair Hamad","doi":"10.1007/s12031-025-02308-9","DOIUrl":"10.1007/s12031-025-02308-9","url":null,"abstract":"<div><p>Glioma is a highly aggressive and invasive brain tumor with limited treatment options, highlighting the need for novel therapeutic approaches. Kinesin superfamily proteins (KIFs) are a diverse group of motor proteins that play essential roles in cellular processes such as mitosis, intracellular transport, and signal transduction, all of which are crucial for tumorigenesis. This review focuses on the multifaceted role of KIFs in glioma, examining their clinical relevance, contribution to tumor progression, and potential as therapeutic targets. We discuss how KIFs influence key aspects of glioma biology, including cell proliferation, invasion, migration, and metastasis. Furthermore, we explore the regulation of the cell cycle and critical signaling pathways associated with glioma, such as PI3K-Akt, Wnt/β-catenin, and Hedgehog signaling by KIFs. The review also addresses the emerging interplay between KIFs and non-coding RNAs, including circular RNAs (circRNAs) and microRNAs (miRNAs), in glioma progression. Finally, we examine current therapeutic strategies targeting KIFs, including immunotherapy, chemotherapy, and small-molecule inhibitors, and their potential to improve treatment outcomes for glioma patients. By synthesizing these insights, this review underscores the significance of KIFs in glioma pathogenesis and their promise as novel therapeutic targets in the fight against glioma.</p></div>","PeriodicalId":652,"journal":{"name":"Journal of Molecular Neuroscience","volume":"75 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143021487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Role of the Dysregulation of circRNAs Expression in Glioblastoma Multiforme","authors":"Yafei Wang,&nbsp;Ying Yu,&nbsp;Jiahua Yu,&nbsp;Cheng Wang,&nbsp;Yunkun Wang,&nbsp;Runxi Fu,&nbsp;Chenran Zhang","doi":"10.1007/s12031-024-02285-5","DOIUrl":"10.1007/s12031-024-02285-5","url":null,"abstract":"<div><p>Primary brain tumors that were the most severe and aggressive were called glioblastoma multiforme (GBM). Cancers are caused in part by aberrant expression of circular RNA. Often referred to as competitive endogenous RNA (ceRNA), circRNA molecules act as “miRNA sponges” in cells by decreasing the inhibitory impact of miRNA on their target genes and hence raising the expression levels of those genes. circRNA molecules are rich in miRNA binding sites. The discovery of more structurally diverse and GBM-related circRNAs has great promise for the use of GMB prognostic biomarkers and therapeutic targets, as well as for comprehending the molecular regulatory mechanisms of GBM. In this work, we present an overview of the circRNA expression patterns associated with GBM and offer a potential integrated electrochemical strategy for detecting circRNA with extreme sensitivity in the diagnosis of glioblastoma.</p><h3>Graphical Abstract</h3><p>The circular RNA (circRNA) regulates both physiological and pathological processes in glioblastoma multiforme disease. Hence, it could serve as a biomarker as well as a therapeutic target.</p>\u0000<div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":652,"journal":{"name":"Journal of Molecular Neuroscience","volume":"75 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142995624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diagnostic Value of Serum miR-499a-5p in Chinese Children with Autism Spectrum Disorders","authors":"Jie Ren,&nbsp;Yanle Bai,&nbsp;Jielin Gao,&nbsp;Yafei Hou,&nbsp;Jie Mao,&nbsp;Fengxiao Gao,&nbsp;Jiaqi Wang","doi":"10.1007/s12031-024-02296-2","DOIUrl":"10.1007/s12031-024-02296-2","url":null,"abstract":"<div><p>The purpose of this study was to investigate the expression of miR-499a-5p in children with autism spectrum disorders (ASD) and its value in early diagnosis of ASD. This is a retrospective case–control study that included 40 children with ASD as a case group and 43 healthy children as a control group. Magnetic resonance imaging (MRI) was performed on all subjects, and the children were scored with childhood autism rating scale (CARS) and autism behavior checklist (ABC). The expression of miR-499a-5p in serum was detected by RT-qPCR, and the diagnostic value of miR-499a-5p in ASD was evaluated by ROC curve. Pearson correlation coefficient was used to evaluate the correlation between miR-499a-5p levels and scores. Compared with healthy children, the expression level of serum miR-499a-5p was significantly reduced in children with ASD. ROC curve showed that miR-499a-5p is of high diagnostic value for ASD. The results of MRI suggested that the volume of the amygdala in ASD children was significantly larger than that in healthy children, while the volume of the caudate nucleus was significantly reduced. Correlation results showed that the scores of CARS and ABC in the ASD group were significantly negatively correlated with the levels of miR-499a-5p. In the ASD group, the volume of the amygdala was negatively correlated with the level of miR-499a-5p, while the volume of the caudate nucleus was positively correlated with the level of miR-499a-5p. The decreased expression of miR-499a-5p in the serum of children with ASD was significantly related to the changes in brain volume of children with ASD, and the miRNA showed good diagnostic accuracy in children with ASD.</p></div>","PeriodicalId":652,"journal":{"name":"Journal of Molecular Neuroscience","volume":"75 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142995755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring Brain Imaging and Genetic Risk Factors in Different Progression States of Alzheimer’s Disease Through OSnetNMF-Based Methods","authors":"Min Gao,&nbsp;Wei Kong,&nbsp;Kun Liu,&nbsp;Gen Wen,&nbsp;Yaling Yu,&nbsp;Yuemin Zhu,&nbsp;Zhihan Jiang,&nbsp;Kai Wei","doi":"10.1007/s12031-024-02274-8","DOIUrl":"10.1007/s12031-024-02274-8","url":null,"abstract":"<div><p>Alzheimer's disease (AD) is a neurodegenerative disease with no effective treatment, often preceded by mild cognitive impairment (MCI). Multimodal imaging genetics integrates imaging and genetic data to gain a deeper understanding of disease progression and individual variations. This study focuses on exploring the mechanisms that drive the transition from normal cognition to MCI and ultimately to AD. As an effective joint feature extraction and dimensionality reduction method, non-negative matrix factorization (NMF) and its improved variants, particularly the network-based non-negative matrix factorization (netNMF), have been widely used in multimodal analysis to mine brain imaging and genetic data by considering the interactions between different features. However, many of these methods overlook the importance of the coefficient matrix and do not address issues related to data accuracy and feature redundancy. To address these limitations, we propose an orthogonal sparse network non-negative matrix factorization (OSnetNMF) algorithm, which introduces orthogonal and sparse constraints based on netNMF. By establishing linear relationships between structural magnetic resonance imaging (sMRI) and corresponding gene expression data, OSnetNMF reduces feature redundancy and decreases correlation between data, resulting in more accurate and reliable biomarker extraction. Experiments demonstrate that the OSnetNMF algorithm can accurately identify risk regions of interest (ROIs) and key genes that characterize AD progression, revealing significant trends in ROI pairs such as l4thVen-HIF1A, rBst-MPO, and rBst-PTK2B. Comparative experiments show that the improved algorithm outperforms traditional methods, identifying more disease-related biomarkers and achieving better reconstruction performance.</p></div>","PeriodicalId":652,"journal":{"name":"Journal of Molecular Neuroscience","volume":"75 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142994546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Precision Prediction of Alzheimer’s Disease: Integrating Mitochondrial Energy Metabolism and Immunological Insights","authors":"Wenlong Du,&nbsp;Shihui Yu,&nbsp;Ruiyao Liu,&nbsp;Qingqing Kong,&nbsp;Xin Hao,&nbsp;Yi Liu","doi":"10.1007/s12031-024-02291-7","DOIUrl":"10.1007/s12031-024-02291-7","url":null,"abstract":"<div><p>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 &gt; 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 (<i>p</i> = 0.002) and activated CD4 memory T cells (<i>p</i> = 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.</p></div>","PeriodicalId":652,"journal":{"name":"Journal of Molecular Neuroscience","volume":"75 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142976572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of Key Biomarkers Associated with Glioma Hemorrhage: Evidence from Bioinformatic Analysis and Clinical Validation","authors":"Zhe Shen,&nbsp;Tao Li,&nbsp;Bo Yang","doi":"10.1007/s12031-024-02294-4","DOIUrl":"10.1007/s12031-024-02294-4","url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":652,"journal":{"name":"Journal of Molecular Neuroscience","volume":"75 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142976573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}