Background: Intracranial aneurysms (IAs) pose a significant and intricate challenge. Elucidating the interplay between DNA methylation and IA pathogenesis is paramount to identify potential biomarkers and therapeutic interventions. Methods: We employed a comprehensive bioinformatics investigation of DNA methylation in IA, utilizing a transcriptomics-based methodology that encompassed 100 machine learning algorithms, genome-wide association studies (GWAS), Mendelian randomization (MR), and summary-data-based Mendelian randomization (SMR). Our sophisticated analytical strategy allowed for a systematic assessment of differentially methylated genes and their implications on the onset, progression, and rupture of IA. Results: We identified DNA methylation-related genes (MRGs) and associated molecular pathways, and the MR and SMR analyses provided evidence for potential causal links between the observed DNA methylation events and IA predisposition. Conclusion: These insights not only augment our understanding of the molecular underpinnings of IA but also underscore potential novel biomarkers and therapeutic avenues. Although our study faces inherent limitations and hurdles, it represents a groundbreaking initiative in deciphering the intricate relationship between genetic, epigenetic, and environmental factors implicated in IA pathogenesis. Graphical

Background: Immunogenic Cell Death (ICD) is a novel way to regulate cell death and can sufficiently activate adaptive immune responses. Its role in immunity is still emerging. However, the involvement of ICD in Intracranial Aneurysms (IA) remains unclear. This study aimed to identify biomarkers associated with ICDs and determine the relationship between them and the immune microenvironment during the onset and progression of IAMethods: The IA gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) in IA were identified and the effects of the ICD on immune microenvironment signatures were studied. Techniques like Lasso, Bayes, DT, FDA, GBM, NNET, RG, SVM, LR, and multivariate analysis were used to identify the ICD gene signatures in IA. A consensus clustering algorithm was used for conducting the unsupervised cluster analysis of the ICD patterns in IA. Furthermore, enrichment analysis was carried out for investigating the various immune responses and other functional pathways. Along with functional annotation, the weighted gene co-expression network analysis (WGCNA), protein-protein interaction (PPI) network and module construction, identification of the hub gene, and co-expression analysis were also carried out.Results: The above techniques were used for establishing the ICD gene signatures of HMGB1, HMGN1, IL33, BCL2, HSPA4, PANX1, TLR9, CLEC7A, and NLRP3 that could easily distinguish IA from normal samples. The unsupervised cluster analysis helped in identifying three ICD gene patterns in different datasets. Gene enrichment analysis revealed that the IA samples showed many differences in pathways such as the cytokine-cytokine receptor interaction, regulation of actin cytoskeleton, chemokine signaling pathway, NOD-like receptor signaling pathway, viral protein interaction with the cytokines and cytokine receptors, and a few other signaling pathways compared to normal samples. In addition, the three ICD modification modes showed obvious differences in their immune microenvironment and the biological function pathways. Eight ICD-regulators were identified and showed meaningful associations with IA, suggesting they could severe as potential prognostic biomarkers.Conclusions: A new gene signature for IA based on ICD features was created. This signature shows that the ICD pattern and the immune microenvironment are closely related to IA and provide a basis for optimizing risk monitoring, clinical decision-making, and developing novel treatment strategies for patients with IA.

Background: The role of epigenetic modulation in immunity is receiving increased recognition—particularly in the context of RNA N6-methyladenosine (m6A) modifications. Nevertheless, it is still uncertain whether m6A methylation plays a role in the onset and progression of intracranial aneurysms (IAs). This study aimed to establish the function of m6A RNA methylation in IA, as well as its correlation with the immunological microenvironment.Methods: Our study included a total of 97 samples (64 IA, 33 normal) in the training set and 60 samples (44 IA, 16 normal) in the validation set to systematically assess the pattern of RNA modifications mediated by 22 m6A regulators. The effects of m6A modifications on immune microenvironment features, i.e., immune response gene sets, human leukocyte antigen (HLA) genes, and infiltrating immune cells were explored. We employed Lasso, machine learning, and logistic regression for the purpose of identifying an m6A regulator gene signature of IA with external data validation. For the unsupervised clustering analysis of m6A modification patterns in IA, consensus clustering methods were employed. Enrichment analysis was used to assess immune response activity along with other functional pathways. The identification of m6A methylation markers was identified based on a protein–protein interaction network and weighted gene co-expression network analysis.Results: We identified an m6A regulator signature of IGFBP2, IGFBP1, IGF2BP2, YTHDF3, ALKBH5, RBM15B, LRPPRC, and ELAVL1, which could easily distinguish individuals with IA from healthy individuals. Unsupervised clustering revealed three m6A modification patterns. Gene enrichment analysis illustrated that the tight junction, p53 pathway, and NOTCH signaling pathway varied significantly in m6A modifier patterns. In addition, the three m6A modification patterns showed significant differences in m6A regulator expression, immune microenvironment, and bio-functional pathways. Furthermore, macrophages, activated T cells, and other immune cells were strongly correlated with m6A regulators. Eight m6A indicators were discovered—each with a statistically significant correlation with IA—suggesting their potential as prognostic biological markers.Conclusion: Our study demonstrates that m6A RNA methylation and the immunological microenvironment are both intricately correlated with the onset and progression of IA. The novel insight into patterns of m6A modification offers a foundation for the development of innovative treatment approaches for IA.

BACKGROUND: Pipeline embolization devices (PEDs) have been increasingly used for the treatment of posterior circulation aneurysms. OBJECTIVE: To investigate the safety and efficacy of PED in the treatment of small to medium unruptured vertebral artery intracranial aneurysms (VAIAs). METHODS: Data from 76 patients with 78 unruptured small and medium (≤12 mm) VAIAs were analyzed. Data for this study come from the PLUS study, which was conducted at 14 centers in China from 2014 to 2019. Univariate analyses were performed to evaluate predictors of the occlusion and complication. RESULTS: Seventy-eight aneurysms in 76 patients were treated with PED. The mean aneurysm size was 8.28 ± 2.13 mm, and all PEDs were successfully placed. The median follow-up was 7 months and available for 67 (85.9%) aneurysms. Complete occlusion was seen in 60 (89.6%) aneurysms, which 86.6% met the primary efficacy outcome. All patients received clinical follow-up, the combined major morbidity and mortality was 2.6%, and 98.7% of patients had a good prognosis. Ischemic stroke occurred in 10.5% of patients, and adjuvant coil and successful after adjustment were predictors of ischemic stroke in the early postoperative and follow-up, respectively. There was no significant difference in the occlusion rate of aneurysm involving posterior inferior cerebellar artery (P = .78). In cases where posterior inferior cerebellar artery was covered by PED, there was no significant difference in ischemic stroke. CONCLUSION: In the treatment of unruptured ≤12 mm VAIAs, PED has a high surgical success rate, a high degree of occlusion, and low morbidity and mortality. PED may be a promising endovascular technique.

Background: Intracranial aneurysms pose a significant health issue, affecting 3–5% of the adult population. The pipeline embolization device (PED) has emerged as a promising treatment for these lesions. This study aimed to investigate the impact of operator experience on complication and poor outcome rates, as well as the learning curve for PED. Methods: A total of 217 patients were consecutively enroled from four eligible centres and divided into three groups based on the number of procedures performed: group 1 (first 10 procedures), group 2 (11–20 procedures), and group 3(>20 procedures). Major complications include operation-related ischaemic or haemorrhagic events and mass effect deterioration. Poor outcome was defined as a modified Rankin Scale score greater than 2 at discharge. Cumulative summation (CUSUM) analysis was generated to assess the learning curve according to major complications and poor outcome. Results: The study found that major complications and poor outcomes occurred in 5.1% and 2.3% of cases, respectively. The rate of major complications decreased from 10.0% in group 1 to 2.9% in group 3 (P=0.053), while the rate of poor outcomes decreased from 7.5% in group 1 to 0.7% in group 3 (P=0.015). Multivariable regression analysis adjusted for covariates showed that operator experience was associated with a lower rate of poor outcomes (P=0.034). CUSUM analysis demonstrated that the learning curve for avoiding major complications and poor outcomes required 27 (mean=13) and 40 (mean=20) cases, respectively. Conclusions: These findings suggest that PED treatment requires a learning curve of 40 cases to achieve reproducibility regarding complications and functional results. Additionally, major complications and poor outcomes significantly decreases after the first 20 procedures. CUSUM analysis can serve as a useful tool for monitoring and assessing surgical performance.