دورية أكاديمية
Identification of key genes and immune infiltration in peripheral blood biomarker analysis of delayed cerebral ischemia: Valproic acid as a potential therapeutic drug.
| العنوان: | Identification of key genes and immune infiltration in peripheral blood biomarker analysis of delayed cerebral ischemia: Valproic acid as a potential therapeutic drug. |
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| المؤلفون: | Wu Z; Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China; Tianjin Neurological Institute, Key Laboratory of Post-Neuroinjury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin Medical University General Hospital, Tianjin, China., Zhao Z; Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China; Tianjin Neurological Institute, Key Laboratory of Post-Neuroinjury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin Medical University General Hospital, Tianjin, China., Li Y; Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China; Tianjin Neurological Institute, Key Laboratory of Post-Neuroinjury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin Medical University General Hospital, Tianjin, China., Wang C; Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China; Tianjin Neurological Institute, Key Laboratory of Post-Neuroinjury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin Medical University General Hospital, Tianjin, China., Cheng C; Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China; Tianjin Neurological Institute, Key Laboratory of Post-Neuroinjury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin Medical University General Hospital, Tianjin, China., Li H; Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China; Tianjin Neurological Institute, Key Laboratory of Post-Neuroinjury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin Medical University General Hospital, Tianjin, China., Zhao M; Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China; Tianjin Neurological Institute, Key Laboratory of Post-Neuroinjury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin Medical University General Hospital, Tianjin, China., Li J; Neurosurgery Third Department, Baoding NO.1 Central Hospital, 320 Changcheng North Street, Baoding City, Hebei Province, China., Law Wen Xin E; Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China; Tianjin Neurological Institute, Key Laboratory of Post-Neuroinjury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin Medical University General Hospital, Tianjin, China., Zhang N; Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China; Tianjin Neurological Institute, Key Laboratory of Post-Neuroinjury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin Medical University General Hospital, Tianjin, China., Zhao Y; Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China; Tianjin Neurological Institute, Key Laboratory of Post-Neuroinjury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin Medical University General Hospital, Tianjin, China. Electronic address: tjmuzhaoyan@163.com., Yang X; Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China; Tianjin Neurological Institute, Key Laboratory of Post-Neuroinjury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin Medical University General Hospital, Tianjin, China. Electronic address: yangxinyu@tmu.edu.cn. |
| المصدر: | International immunopharmacology [Int Immunopharmacol] 2024 Aug 20; Vol. 137, pp. 112408. Date of Electronic Publication: 2024 Jun 18. |
| نوع المنشور: | Journal Article |
| اللغة: | English |
| بيانات الدورية: | Publisher: Elsevier Science Country of Publication: Netherlands NLM ID: 100965259 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1878-1705 (Electronic) Linking ISSN: 15675769 NLM ISO Abbreviation: Int Immunopharmacol Subsets: MEDLINE |
| أسماء مطبوعة: | Original Publication: Amsterdam ; New York : Elsevier Science, c2001- |
| مواضيع طبية MeSH: | Brain Ischemia*/drug therapy , Brain Ischemia*/genetics , Brain Ischemia*/blood , Brain Ischemia*/immunology , Valproic Acid*/therapeutic use , Biomarkers*/blood, Humans ; Animals ; Mice ; Subarachnoid Hemorrhage/blood ; Subarachnoid Hemorrhage/immunology ; Subarachnoid Hemorrhage/genetics ; Subarachnoid Hemorrhage/drug therapy ; Computational Biology ; Databases, Genetic ; Machine Learning |
| مستخلص: | Background: Delayed cerebral ischemia (DCI) is a common and serious complication of subarachnoid hemorrhage (SAH). Its pathogenesis is not fully understood. Here, we developed a predictive model based on peripheral blood biomarkers and validated the model using several bioinformatic multi-analysis methods. Methods: Six datasets were obtained from the GEO database. Characteristic genes were screened using weighted correlation network analysis (WGCNA) and differentially expressed genes. Three machine learning algorithms, elastic networks-LASSO, support vector machines (SVM-RFE) and random forests (RF), were also used to construct diagnostic prediction models for key genes. To further evaluate the performance and predictive value of the diagnostic models, nomogram model were constructed, and the clinical value of the models was assessed using Decision Curve Analysis (DCA), Area Under the Check Curve (AUC), Clinical Impact Curve (CIC), and validated in the mouse single-cell RNA-seq dataset. Mendelian randomization(MR) analysis explored the causal relationship between SAH and stroke, and the intermediate influencing factors. We validated this by retrospectively analyzing the qPCR levels of the most relevant genes in SAH and SAH-DCI patients. This experiment demonstrated a statistically significant difference between SAH and SAH-DCI and normal group controls. Finally, potential small molecule compounds interacting with the selected features were screened from the Comparative Toxicogenomics Database (CTD). Results: The fGSEA results showed that activation of Toll-like receptor signaling and leukocyte transendothelial cell migration pathways were positively correlated with the DCI phenotype, whereas cytokine signaling pathways and natural killer cell-mediated cytotoxicity were negatively correlated. Consensus feature selection of DEG genes using WGCNA and three machine learning algorithms resulted in the identification of six genes (SPOCK2, TRRAP, CIB1, BCL11B, PDZD8 and LAT), which were used to predict DCI diagnosis with high accuracy. Three external datasets and the mouse single-cell dataset showed high accuracy of the diagnostic model, in addition to high performance and predictive value of the diagnostic model in DCA and CIC. MR analysis looked at stroke after SAH independent of SAH, but associated with multiple intermediate factors including Hypertensive diseases, Total triglycerides levels in medium HDL and Platelet count. qPCR confirmed that significant differences in DCI signature genes were observed between the SAH and SAH-DCI groups. Finally, valproic acid became a potential therapeutic agent for DCI based on the results of target prediction and molecular docking of the characterized genes. Conclusion: This diagnostic model can identify SAH patients at high risk for DCI and may provide potential mechanisms and therapeutic targets for DCI. Valproic acid may be an important future drug for the treatment of DCI. Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. (Copyright © 2024 Elsevier B.V. All rights reserved.) |
| فهرسة مساهمة: | Keywords: Delayed cerebral ischemia; Immune cell subtype distribution pattern; Ischemic stroke; Machine learning; Subarachnoid hemorrhage; Weighted gene coexpression network analysis |
| المشرفين على المادة: | 614OI1Z5WI (Valproic Acid) 0 (Biomarkers) |
| تواريخ الأحداث: | Date Created: 20240619 Date Completed: 20240710 Latest Revision: 20240710 |
| رمز التحديث: | 20240710 |
| DOI: | 10.1016/j.intimp.2024.112408 |
| PMID: | 38897129 |
| قاعدة البيانات: | MEDLINE |
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