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Ranked as the world's second leading cause of mortality, ischemic stroke (IS) imposes a significant global burden, marked by its substantial incidence and economic impact across nations and regions, chiefly attributed to its elevated disability rates. Alzheimer's disease (AD) is linked to a heightened susceptibility to IS. However, few studies have been reported to explain the potential correlation between IS and AD. We investigated the relationship and relevant mechanisms between IS and AD using single-cell RNA sequencing and multiple bioinformatics approaches. By intersecting differentially expressed genes and WGCNA critical module genes, we obtained 15 IS related AD genes. According to the KEGG pathway analysis, the IS related AD disease genes were significantly enriched in the parkinson disease pathway, oxidative phosphorylation pathway, thermogenesis pathway, alzheimer disease pathway and neurodegeneration pathway. Finally, five genes associated with immunity (TXN, HINT1, TOMM7, COX7C, RPL17) were identified in IS related AD. Significantly, it was found that all hub genes were mainly highly expressed in epithelial cells, endothelial cells, monocytes and oligodendrocytes by single cell RNA sequencing. We believe these hub genes may regulate the immune pathway which may contribute to the development of IS related AD. In addition, these genes may be potential targets for the treatment of IS related AD. [ABSTRACT FROM AUTHOR]

As a high level of mortality and morbidity disease, ruptured cerebral aneurysms (RCA) is the most common cause of intracranial hemorrhage. The expression profiles of GSE13353, GSE26969 were downloaded from the Gene Expression Omnibus (GEO) database to obtain differentially expressed genes (DEGs) between RCA and unruptured cerebral aneurysms (URCA). The Least Absolute Shrinkage Selection Operator (LASSO) and the SVM-RFE (SVM-RFE) analysis were used to screen the potential diagnostic genes for RCA, which were further tested in the validation cohort (GSE54083). The TRRUST database was used to predict transcription factors (TF) and the JASPAR database was used to validate the marker genes and STAT1 binding sites. Finally, the CMAP database was used to predict RCA-associated drugs for clinical transformation. A total of 120 DEGs were identified. The functional enrichment analysis revealed that NF-kappa B signaling pathway, tuberculosis, rheumatoid arthritis were enriched in the RCA group. NANS, NTRK3, OLFML2A were identified as diagnostic biomarkers of RCA. Transcription of all three marker genes is regulated by the predicted transcription factor STAT1, the CMAP database was eventually used to screen 10 most promising drugs for the treatment of RCA. NANS, NTRK3, OLFML2A may become new candidate biomarkers of RCA, moreover, STAT1 plays an important role in the development of RCA. The mentioned immune cells may play a key role in the development and progression of RCA. MEK and MAP kinase inhibitors are the most likely drug mechanisms for RCA therapy. [ABSTRACT FROM AUTHOR]