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Yuan J, Liao YS, Zhang TC, Tang YQ, Yu P, Liu YN, Cai DJ, Yu SG, Zhao L. Integrating Bulk RNA and Single-Cell Sequencing Data Unveils Efferocytosis Patterns and ceRNA Network in Ischemic Stroke. Transl Stroke Res 2024:10.1007/s12975-024-01255-8. [PMID: 38678526 DOI: 10.1007/s12975-024-01255-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Revised: 03/17/2024] [Accepted: 04/18/2024] [Indexed: 05/01/2024]
Abstract
Excessive inflammatory response following ischemic stroke (IS) injury is a key factor affecting the functional recovery of patients. The efferocytic clearance of apoptotic cells within ischemic brain tissue is a critical mechanism for mitigating inflammation, presenting a promising avenue for the treatment of ischemic stroke. However, the cellular and molecular mechanisms underlying efferocytosis in the brain after IS and its impact on brain injury and recovery are poorly understood. This study explored the roles of inflammation and efferocytosis in IS with bioinformatics. Three Gene Expression Omnibus Series (GSE) (GSE137482-3 m, GSE137482-18 m, and GSE30655) were obtained from NCBI (National Center for Biotechnology Information) and GEO (Gene Expression Omnibus). Differentially expressed genes (DEGs) were processed for GSEA (Gene Set Enrichment Analysis), GO (Gene Ontology Functional Enrichment Analysis), and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analyses. Efferocytosis-related genes were identified from the existing literature, following which the relationship between Differentially Expressed Genes (DEGs) and efferocytosis-related genes was examined. The single-cell dataset GSE174574 was employed to investigate the distinct expression profiles of efferocytosis-related genes. The identified hub genes were verified using the dataset of human brain and peripheral blood sample datasets GSE56267 and GSE122709. The dataset GSE215212 was used to predict competing endogenous RNA (ceRNA) network, and GSE231431 was applied to verify the expression of differential miRNAs. At last, the middle cerebral artery (MCAO) model was established to validate the efferocytosis process and the expression of hub genes. DEGs in two datasets were significantly enriched in pathways involved in inflammatory response and immunoregulation. Based on the least absolute shrinkage and selection operator (LASSO) analyses, we identified hub efferocytosis-related genes (Abca1, C1qc, Ptx3, Irf5, and Pros1) and key transcription factors (Stat5). The scRNA-seq analysis showed that these hub genes were mainly expressed in microglia and macrophages which are the main cells with efferocytosis function in the brain. We then identified miR-125b-5p as a therapeutic target of IS based on the ceRNA network. Finally, we validated the phagocytosis and clearance of dead cells by efferocytosis and the expression of hub gene Abca1 in MCAO mice models.
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Affiliation(s)
- Jing Yuan
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, 610075, Sichuan Province, China
| | - Yu-Sha Liao
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, 610075, Sichuan Province, China
| | - Tie-Chun Zhang
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, 610075, Sichuan Province, China
| | - Yu-Qi Tang
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, 610075, Sichuan Province, China
| | - Pei Yu
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, 610075, Sichuan Province, China
| | - Ya-Ning Liu
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, 610075, Sichuan Province, China
| | - Ding-Jun Cai
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, 610075, Sichuan Province, China
| | - Shu-Guang Yu
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, 610075, Sichuan Province, China
| | - Ling Zhao
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, 610075, Sichuan Province, China.
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Chen XL, Tan QD, Chen KJ, Zheng DN, Deng HW, He S, Mao FK, Hao JL, Le WD, Yang J. CircRNA and Stroke: New Insight of Potential Biomarkers and Therapeutic Targets. Neurochem Res 2024; 49:557-567. [PMID: 38063946 DOI: 10.1007/s11064-023-04077-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 11/14/2023] [Accepted: 11/25/2023] [Indexed: 02/23/2024]
Abstract
Stroke, the second-largest cause of death and the leading cause of disability globally, presents significant challenges in terms of prognosis and treatment. Identifying reliable prognosis biomarkers and treatment targets is crucial to address these challenges. Circular RNA (circRNA) has emerged as a promising research biomarkers and therapeutic targets because of its tissue specificity and conservation. However, the potential role of circRNA in stroke prognosis and treatment remains largely unexplored. This review briefly elucidate the mechanism underlying circRNA's involvement in stroke pathophysiology. Additionally, this review summarizes the impact of circRNA on different forms of strokes, including ischemic stroke and hemorrhagic stroke. And, this article discusses the positive effects of circRNA on promoting cerebrovascular repair and regeneration, maintaining the integrity of the blood-brain barrier (BBB), and reducing neuronal injury and immune inflammatory response. In conclusion, the significance of circRNA as a potential prognostic biomarker and a viable therapeutic target was underscored.
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Affiliation(s)
- Xiao-Ling Chen
- School of Clinical Medicine, Southwest Medical University, Luzhou, 646000, China
- Department of Neurology, School of Medicine, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China
| | - Quan-Dan Tan
- Department of Neurology, The First Affiliated Hospital of Chengdu Medical College, Chengdu, 610072, China9, China
| | - Ke-Jie Chen
- School of Public Health, Chengdu Medical College, Chengdu, 610072, China
| | - Dan-Ni Zheng
- Brain Health Initiative, The George Institute for Global Health, University of New South Wales, Sydney, 2025, Australia
| | - Hong-Wei Deng
- Department of Neurology, The First Affiliated Hospital of Chengdu Medical College, Chengdu, 610072, China9, China
| | - Song He
- Department of Neurology, The First Affiliated Hospital of Chengdu Medical College, Chengdu, 610072, China9, China
| | - Feng-Kai Mao
- Department of Neurology, The First Affiliated Hospital of Chengdu Medical College, Chengdu, 610072, China9, China
| | - Jun-Li Hao
- School of Biomedical Sciences and Technology, Chengdu Medical College, Chengdu, 610072, China
| | - Wei-Dong Le
- Institute of Neurology, School of Medicine, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China.
| | - Jie Yang
- School of Biomedical Sciences and Technology, Chengdu Medical College, Chengdu, 610072, China.
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Geng Y, Liu Y, Wang M, Dong X, Sun X, Luo Y, Sun X. Identification and validation of platelet-related diagnostic markers and potential drug screening in ischemic stroke by integrating comprehensive bioinformatics analysis and machine learning. Front Immunol 2024; 14:1320475. [PMID: 38268925 PMCID: PMC10806171 DOI: 10.3389/fimmu.2023.1320475] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 12/18/2023] [Indexed: 01/26/2024] Open
Abstract
Background Ischemic stroke (IS), caused by blood and oxygen deprivation due to cerebral thrombosis, has links to activated and aggregated platelets. Discovering platelet-related biomarkers, developing diagnostic models, and screening antiplatelet drugs are crucial for IS diagnosis and treatment. Methods and results Combining and normalizing GSE16561 and GSE22255 datasets identified 1,753 upregulated and 1,187 downregulated genes. Fifty-one genes in the platelet-related module were isolated using weighted gene co-expression network analysis (WGCNA) and other analyses, including 50 upregulated and one downregulated gene. Subsequent enrichment and network analyses resulted in 25 platelet-associated genes and six diagnostic markers for a risk assessment model. This model's area under the ROC curve outperformed single genes, and in the peripheral blood of the high-risk group, immune infiltration indicated a higher proportion of CD4, resting CD4 memory, and activated CD4 memory T cells, along with a lower proportion of CD8 T cells in comparison to the low-risk group. Utilizing the gene expression matrix and the CMap database, we identified two potential drugs for IS. Finally, a rat MACO/R model was used to validate the diagnostic markers' expression and the drugs' predicted anticoagulant effects. Conclusion We identified six IS platelet-related biomarkers (APP, THBS1, F13A1, SRC, PPBP, and VCL) for a robust diagnostic model. The drugs alpha-linolenic acid and ciprofibrate have potential antiplatelet effects in IS. This study advances early IS diagnosis and treatment.
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Affiliation(s)
- Yifei Geng
- Institute of Medicinal Plant Development, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China
- Key Laboratory of Bioactive Substances and Resources Utilization of Chinese Herbal Medicine, Ministry of Education, Beijing, China
- Institute of Medicinal Plant Development, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing Key Laboratory of Innovative Drug Discovery of Traditional Chinese Medicine (Natural Medicine) and Translational Medicine, Beijing, China
| | - Yuchen Liu
- Department of Internal Medicine, Peking Union Medical College Hospital, Beijing, China
- School of Clinical Science, Peking Union Medical College, Chinese Academy of Medical Science, Beijing, China
| | - Min Wang
- Institute of Medicinal Plant Development, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China
- Key Laboratory of Bioactive Substances and Resources Utilization of Chinese Herbal Medicine, Ministry of Education, Beijing, China
- Institute of Medicinal Plant Development, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing Key Laboratory of Innovative Drug Discovery of Traditional Chinese Medicine (Natural Medicine) and Translational Medicine, Beijing, China
| | - Xi Dong
- Institute of Medicinal Plant Development, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China
- Key Laboratory of Bioactive Substances and Resources Utilization of Chinese Herbal Medicine, Ministry of Education, Beijing, China
- Institute of Medicinal Plant Development, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing Key Laboratory of Innovative Drug Discovery of Traditional Chinese Medicine (Natural Medicine) and Translational Medicine, Beijing, China
| | - Xiao Sun
- Institute of Medicinal Plant Development, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China
- Key Laboratory of Bioactive Substances and Resources Utilization of Chinese Herbal Medicine, Ministry of Education, Beijing, China
- Institute of Medicinal Plant Development, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing Key Laboratory of Innovative Drug Discovery of Traditional Chinese Medicine (Natural Medicine) and Translational Medicine, Beijing, China
| | - Yun Luo
- Institute of Medicinal Plant Development, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China
- Key Laboratory of Bioactive Substances and Resources Utilization of Chinese Herbal Medicine, Ministry of Education, Beijing, China
- Institute of Medicinal Plant Development, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing Key Laboratory of Innovative Drug Discovery of Traditional Chinese Medicine (Natural Medicine) and Translational Medicine, Beijing, China
| | - Xiaobo Sun
- Institute of Medicinal Plant Development, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China
- Key Laboratory of Bioactive Substances and Resources Utilization of Chinese Herbal Medicine, Ministry of Education, Beijing, China
- Institute of Medicinal Plant Development, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing Key Laboratory of Innovative Drug Discovery of Traditional Chinese Medicine (Natural Medicine) and Translational Medicine, Beijing, China
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Lu D, Cai H, Li Y, Chang W, Liu X, Dai Q, Yu W, Chen W, Qiao G, Xie H, Xiao X, Li Z. Investigating the ID3/SLC22A4 as immune-related signatures in ischemic stroke. Aging (Albany NY) 2023; 15:14803-14829. [PMID: 38112574 PMCID: PMC10781493 DOI: 10.18632/aging.205308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 11/03/2023] [Indexed: 12/21/2023]
Abstract
BACKGROUND Ischemic stroke (IS) is a fearful disease that can cause a variety of immune events. Nevertheless, precise immune-related mechanisms have yet to be systematically elucidated. This study aimed to identify immune-related signatures using machine learning and to validate them with animal experiments and single cell analysis. METHODS In this study, we screened 24 differentially expressed genes (DEGs) while identifying immune-related signatures that may play a key role in IS development through a comprehensive strategy between least absolute shrinkage and selection operation (LASSO) regression, support vector machine (SVM) and immune-related genes. In addition, we explored immune infiltration using the CIBERSORT algorithm. Finally, we performed validation in mouse brain tissue and single cell analysis. RESULTS We identified 24 DEGs for follow-up analysis. ID3 and SLC22A4 were finally identified as the better immune-related signatures through a comprehensive strategy among DEGs, LASSO, SVM and immune-related genes. RT-qPCR, western blot, and immunofluorescence revealed a significant decrease in ID3 and a significant increase in SLC22A4 in the middle cerebral artery occlusion group. Single cell analysis revealed that ID3 was mainly concentrated in endothelial_2 cells and SLC22A4 in astrocytes in the MCAO group. A CIBERSORT finds significantly altered levels of immune infiltration in IS patients. CONCLUSIONS This study focused on immune-related signatures after stroke and ID3 and SLC22A4 may be new therapeutic targets to promote functional recovery after stroke. Furthermore, the association of ID3 and SLC22A4 with immune cells may be a new direction for post-stroke immunotherapy.
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Affiliation(s)
- Dading Lu
- Department of Stroke Center, The First Hospital of China Medical University, Heping, Shenyang, Liaoning, China
- Department of Neurology, The First Hospital of China Medical University, Heping, Shenyang, Liaoning, China
- Department of Neurosurgery, The First Hospital of China Medical University, Heping, Shenyang, Liaoning, China
| | - Heng Cai
- Department of Neurosurgery, Shengjing Hospital, Shenyang, China medical University, Heping, Shenyang, China
| | - Yugang Li
- Department of Stroke Center, The First Hospital of China Medical University, Heping, Shenyang, Liaoning, China
| | - Wenyuan Chang
- Department of Neurology, The First Hospital of China Medical University, Heping, Shenyang, Liaoning, China
| | - Xiu Liu
- The First Clinical College, China Medical University, Shenbei, Shenyang, China
| | - Qiwei Dai
- Department of Neurosurgery, Shengjing Hospital, Shenyang, China medical University, Heping, Shenyang, China
| | - Wanning Yu
- Department of Neurosurgery, Shengjing Hospital, Shenyang, China medical University, Heping, Shenyang, China
| | - Wangli Chen
- Department of Neurosurgery, Shengjing Hospital, Shenyang, China medical University, Heping, Shenyang, China
| | - Guomin Qiao
- Department of Neurosurgery, Shengjing Hospital, Shenyang, China medical University, Heping, Shenyang, China
| | - Haojie Xie
- Department of Neurosurgery, Shengjing Hospital, Shenyang, China medical University, Heping, Shenyang, China
| | - Xiong Xiao
- Department of Neurosurgery, Shengjing Hospital, Shenyang, China medical University, Heping, Shenyang, China
| | - Zhiqing Li
- Department of Stroke Center, The First Hospital of China Medical University, Heping, Shenyang, Liaoning, China
- Department of Neurology, The First Hospital of China Medical University, Heping, Shenyang, Liaoning, China
- Department of Neurosurgery, The First Hospital of China Medical University, Heping, Shenyang, Liaoning, China
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Xie H, Huang Y, Zhan Y. Construction of a novel circRNA-miRNA-ferroptosis related mRNA network in ischemic stroke. Sci Rep 2023; 13:15077. [PMID: 37699956 PMCID: PMC10497552 DOI: 10.1038/s41598-023-41028-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 08/21/2023] [Indexed: 09/14/2023] Open
Abstract
Molecule alterations are important to explore the pathological mechanism of ischemic stroke (IS). Ferroptosis, a newly recognized type of regulated cell death, is related to IS. Identification of the interactions between circular RNA (circRNA), microRNA (miRNA) and ferroptosis related mRNA may be useful to understand the molecular mechanism of IS. The circRNA, miRNA and mRNA transcriptome data in IS, downloaded from the Gene Expression Omnibus (GEO) database, was used for differential expression analysis. Ferroptosis related mRNAs were identified from the FerrDb database, followed by construction of circRNA-miRNA-ferroptosis related mRNA network. Enrichment and protein-protein interaction analysis of mRNAs in circRNA-miRNA-mRNA network was performed, followed by expression validation by reverse transcriptase polymerase chain reaction and online dataset. A total of 694, 41 and 104 differentially expressed circRNAs, miRNAs and mRNAs were respectively identified in IS. Among which, dual specificity phosphatase 1 (DUSP1), nuclear receptor coactivator 4 (NCOA4) and solute carrier family 2 member 3 (SLC2A3) were the only three up-regulated ferroptosis related mRNAs. Moreover, DUSP1, NCOA4 and SLC2A3 were significantly up-regulated in IS after 3, 5 and 24 h of the attack. Based on these three ferroptosis related mRNAs, 4 circRNA-miRNA-ferroptosis related mRNA regulatory relationship pairs were identified in IS, including hsa_circ_0071036/hsa_circ_0039365/hsa_circ_0079347/hsa_circ_0008857-hsa-miR-122-5p-DUSP1, hsa_circ_0067717/hsa_circ_0003956/hsa_circ_0013729-hsa-miR-4446-3p-SLC2A3, hsa_circ_0059347/hsa_circ_0001414/hsa_circ_0049637-hsa-miR-885-3p-SLC2A3, and hsa_circ_0005633/hsa_circ_0004479-hsa-miR-4435-NCOA4. In addition, DUSP1 is involved in the signaling pathway of fluid shear stress and atherosclerosis. Relationship of regulatory action between circRNAs, miRNAs and ferroptosis related mRNAs may be associated with the development of IS.
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Affiliation(s)
- Huirong Xie
- Department of Neurology, Lishui Municipal Central Hospital, Lishui Hospital of Zhejiang University, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui Clinical Research Center for Neurological Diseases, 289 Kuocang Road, Lishui, 323000, Zhejiang, China.
| | - Yijie Huang
- Department of Neurology, Lishui Municipal Central Hospital, Lishui Hospital of Zhejiang University, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui Clinical Research Center for Neurological Diseases, 289 Kuocang Road, Lishui, 323000, Zhejiang, China
| | - Yanli Zhan
- Cerebrovascular Research Laboratory, Lishui Municipal Central Hospital, Lishui Hospital of Zhejiang University, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui Clinical Research Center for Neurological Diseases, 289 Kuocang Road, Lishui, 323000, Zhejiang, China
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Shen J, Feng Y, Lu M, He J, Yang H. Predictive model, miRNA-TF network, related subgroup identification and drug prediction of ischemic stroke complicated with mental disorders based on genes related to gut microbiome. Front Neurol 2023; 14:1189746. [PMID: 37305753 PMCID: PMC10250745 DOI: 10.3389/fneur.2023.1189746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 05/02/2023] [Indexed: 06/13/2023] Open
Abstract
Background Patients with comorbid schizophrenia, depression, drug use, and multiple psychiatric diagnoses have a greater risk of carotid revascularization following stroke. The gut microbiome (GM) plays a crucial role in the attack of mental illness and IS, which may become an index for the diagnosis of IS. A genomic study of the genetic commonalities between SC and IS, as well as its mediated pathways and immune infiltration, will be conducted to determine how schizophrenia contributes to the high prevalence of IS. According to our study, this could be an indicator of ischemic stroke development. Methods We selected two datasets of IS from the Gene Expression Omnibus (GEO), one for training and the other for the verification group. Five genes related to mental disorders and GM were extracted from Gene cards and other databases. Linear models for microarray data (Limma) analysis was utilized to identify differentially expressed genes (DEGs) and perform functional enrichment analysis. It was also used to conduct machine learning exercises such as random forest and regression to identify the best candidate for immune-related central genes. Protein-protein interaction (PPI) network and artificial neural network (ANN) were established for verification. The receiver operating characteristic (ROC) curve was drawn for the diagnosis of IS, and the diagnostic model was verified by qRT-PCR. Further immune cell infiltration analysis was performed to study the IS immune cell imbalance. We also performed consensus clustering (CC) to analyze the expression of candidate models under different subtypes. Finally, miRNA, transcription factors (TFs), and drugs related to candidate genes were collected through the Network analyst online platform. Results Through comprehensive analysis, a diagnostic prediction model with good effect was obtained. Both the training group (AUC 0.82, CI 0.93-0.71) and the verification group (AUC 0.81, CI 0.90-0.72) had a good phenotype in the qRT-PCR test. And in verification group 2 we validated between the two groups with and without carotid-related ischemic cerebrovascular events (AUC 0.87, CI 1-0.64). Furthermore, we investigated cytokines in both GSEA and immune infiltration and verified cytokine-related responses by flow cytometry, particularly IL-6, which played an important role in IS occurrence and progression. Therefore, we speculate that mental illness may affect the development of IS in B cells and IL-6 in T cells. MiRNA (hsa-mir-129-2-3p, has-mir-335-5p, and has-mir-16-5p) and TFs (CREB1, FOXL1), which may be related to IS, were obtained. Conclusion Through comprehensive analysis, a diagnostic prediction model with good effect was obtained. Both the training group (AUC 0.82, CI 0.93-0.71) and the verification group (AUC 0.81, CI 0.90-0.72) had a good phenotype in the qRT-PCR test. And in verification group 2 we validated between the two groups with and without carotid-related ischemic cerebrovascular events (AUC 0.87, CI 1-0.64). MiRNA (hsa-mir-129-2-3p, has-mir-335-5p, and has-mir-16-5p) and TFs (CREB1, FOXL1), which may be related to IS, were obtained.
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Affiliation(s)
- Jing Shen
- The Affiliated Jiangsu Shengze Hospital of Nanjing Medical University, Nanjing, China
| | - Yu Feng
- The University of New South Wales, Sydney, NSW, Australia
- The University of Melbourne, Parkville, VIC, Australia
| | - Minyan Lu
- The Affiliated Jiangsu Shengze Hospital of Nanjing Medical University, Nanjing, China
| | - Jin He
- The Affiliated Jiangsu Shengze Hospital of Nanjing Medical University, Nanjing, China
| | - Huifeng Yang
- The Affiliated Jiangsu Shengze Hospital of Nanjing Medical University, Nanjing, China
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