Identifying Key Biomarkers and Immune Infiltration in Female Patients with Ischemic Stroke Based on Weighted Gene Co-Expression Network Analysis.

Neural Plast

The Third School of Clinical Medicine (School of Rehabilitation Medicine), Zhejiang Chinese Medical University, Key Laboratory of Acupuncture and Neurology of Zhejiang Province, Hangzhou, Zhejiang, China.

Published: April 2022

AI Article Synopsis

  • Stroke is a major global health issue, with ischemic stroke (IS) making up about 80% of cases and showing different impacts on males and females, where females may face greater challenges.
  • The study utilized weighted gene co-expression network analysis (WGCNA) on various datasets to identify key genetic modules and core genes associated with IS in female patients, ultimately selecting ten significant genes for further exploration.
  • The research also employed CIBERSORT to analyze immune cell types in female IS patients compared to normal controls, highlighting new potential treatment targets based on immune profiles.

Article Abstract

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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9012649PMC
http://dx.doi.org/10.1155/2022/5379876DOI Listing

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