Identifying Key Biomarkers and Immune Infiltration in Female Patients with Ischemic Stroke Based on Weighted Gene Co-Expression Network Analysis
Stroke is one of the leading causes of death and disability worldwide. Evidence shows that ischemic stroke (IS) accounts for nearly 80 percent of all strokes and that the etiology, risk factors, and prognosis of this disease differ by gender. Female patients may bear a greater burden than male patie...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Neural Plasticity |
| Online Access: | http://dx.doi.org/10.1155/2022/5379876 |
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| _version_ | 1832545251679535104 |
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| author | Haipeng Xu Kelin He Rong Hu YanZhi Ge Xinyun Li Fengjia Ni Bei Que Yi Chen Ruijie Ma |
| author_facet | Haipeng Xu Kelin He Rong Hu YanZhi Ge Xinyun Li Fengjia Ni Bei Que Yi Chen Ruijie Ma |
| author_sort | Haipeng Xu |
| collection | DOAJ |
| description | Stroke is one of the leading causes of death and disability worldwide. Evidence shows that ischemic stroke (IS) accounts for nearly 80 percent of all strokes and that the etiology, risk factors, and prognosis of this disease differ by gender. Female patients may bear a greater burden than male patients. The immune system may play an important role in the pathophysiology of females with IS. Therefore, it is critical to investigate the key biomarkers and immune infiltration of female IS patients to develop effective treatment methods. Herein, we used weighted gene co-expression network analysis (WGCNA) to determine the key modules and core genes in female IS patients using the GSE22255, GSE37587, and GSE16561 datasets from the GEO database. Subsequently, we performed functional enrichment analysis and built a protein-protein interaction (PPI) network. Ten genes were selected as the true central genes for further investigation. After that, we explored the specific molecular and biological functions of these hub genes to gain a better understanding of the underlying pathogenesis of female IS patients. Moreover, the “Cell type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT)” was used to examine the distribution pattern of immune subtypes in female patients with IS and normal controls, revealing a new potential target for clinical treatment of the disease. |
| format | Article |
| id | doaj-art-9ed51d88b514478fbc1760c5600edeed |
| institution | Kabale University |
| issn | 1687-5443 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Neural Plasticity |
| spelling | doaj-art-9ed51d88b514478fbc1760c5600edeed2025-02-03T07:26:19ZengWileyNeural Plasticity1687-54432022-01-01202210.1155/2022/5379876Identifying Key Biomarkers and Immune Infiltration in Female Patients with Ischemic Stroke Based on Weighted Gene Co-Expression Network AnalysisHaipeng Xu0Kelin He1Rong Hu2YanZhi Ge3Xinyun Li4Fengjia Ni5Bei Que6Yi Chen7Ruijie Ma8The Third School of Clinical Medicine (School of Rehabilitation Medicine)The Third School of Clinical Medicine (School of Rehabilitation Medicine)The Third School of Clinical Medicine (School of Rehabilitation Medicine)The First Clinical Medical CollegeThe Third School of Clinical Medicine (School of Rehabilitation Medicine)The Third School of Clinical Medicine (School of Rehabilitation Medicine)The Third School of Clinical Medicine (School of Rehabilitation Medicine)The Third School of Clinical Medicine (School of Rehabilitation Medicine)The Third School of Clinical Medicine (School of Rehabilitation Medicine)Stroke is one of the leading causes of death and disability worldwide. Evidence shows that ischemic stroke (IS) accounts for nearly 80 percent of all strokes and that the etiology, risk factors, and prognosis of this disease differ by gender. Female patients may bear a greater burden than male patients. The immune system may play an important role in the pathophysiology of females with IS. Therefore, it is critical to investigate the key biomarkers and immune infiltration of female IS patients to develop effective treatment methods. Herein, we used weighted gene co-expression network analysis (WGCNA) to determine the key modules and core genes in female IS patients using the GSE22255, GSE37587, and GSE16561 datasets from the GEO database. Subsequently, we performed functional enrichment analysis and built a protein-protein interaction (PPI) network. Ten genes were selected as the true central genes for further investigation. After that, we explored the specific molecular and biological functions of these hub genes to gain a better understanding of the underlying pathogenesis of female IS patients. Moreover, the “Cell type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT)” was used to examine the distribution pattern of immune subtypes in female patients with IS and normal controls, revealing a new potential target for clinical treatment of the disease.http://dx.doi.org/10.1155/2022/5379876 |
| spellingShingle | Haipeng Xu Kelin He Rong Hu YanZhi Ge Xinyun Li Fengjia Ni Bei Que Yi Chen Ruijie Ma Identifying Key Biomarkers and Immune Infiltration in Female Patients with Ischemic Stroke Based on Weighted Gene Co-Expression Network Analysis Neural Plasticity |
| title | Identifying Key Biomarkers and Immune Infiltration in Female Patients with Ischemic Stroke Based on Weighted Gene Co-Expression Network Analysis |
| title_full | Identifying Key Biomarkers and Immune Infiltration in Female Patients with Ischemic Stroke Based on Weighted Gene Co-Expression Network Analysis |
| title_fullStr | Identifying Key Biomarkers and Immune Infiltration in Female Patients with Ischemic Stroke Based on Weighted Gene Co-Expression Network Analysis |
| title_full_unstemmed | Identifying Key Biomarkers and Immune Infiltration in Female Patients with Ischemic Stroke Based on Weighted Gene Co-Expression Network Analysis |
| title_short | Identifying Key Biomarkers and Immune Infiltration in Female Patients with Ischemic Stroke Based on Weighted Gene Co-Expression Network Analysis |
| title_sort | identifying key biomarkers and immune infiltration in female patients with ischemic stroke based on weighted gene co expression network analysis |
| url | http://dx.doi.org/10.1155/2022/5379876 |
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