Analysis of potential diagnostic genes for eosinophilic chronic rhinosinusitis with nasal polyps based on GEO datasets
10.16066/j.1672-7002.2023.12.008
- VernacularTitle:基于GEO数据集分析嗜酸性粒细胞型慢性鼻窦炎伴鼻息肉的潜在诊断基因
- Author:
Yuqing HUANG
1
;
Chen MENG
;
Jianhong LIAO
;
Bing YAN
;
Luo ZHANG
;
Chengshuo WANG
Author Information
1. 首都医科大学附属北京同仁医院耳鼻咽喉头颈外科,耳鼻咽喉头颈科学教育部重点实验室(首都医科大学),北京市耳鼻咽喉科研究所,教育部工程中心,鼻病研究北京市重点实验室,中国医学科学院慢性鼻病创新单元,北京 100730
- Keywords:
Eosinophils;
Sinusitis;
Genomics;
Database;
eosinophilic chronic rhinosinusitis with nasal polyps;
non-eosinophilic chronic rhinosinusitis with nasal polyps;
transcriptomics;
GEO database;
diagnostic model
- From:
Chinese Archives of Otolaryngology-Head and Neck Surgery
2023;30(12):781-784
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVE To utilize RNA sequencing(RNA-seq)data from the GEO database to identify genes with potential diagnostic value for eosinophilic chronic rhinosinusitis with nasal polyps(ECRSwNP).METHODS Three datasets were obtained,and samples were divided into ECRSwNP and nonECRSwNP groups based on the expression levels of CST1 and CLC.A diagnostic model for ECRSwNP was established using R software and algorithms,and its accuracy was assessed.RESULTS The samples were grouped as follows:GSE136825(ECRSwNP 7,nonECRSwNP 19),GSE72713(ECRSwNP 3,nonECRSwNP 3),and GSE179265(ECRSwNP 11,nonECRSwNP 2).The diagnostic performance of the upregulated gene model(ADH1C,CCL26,HRH1,NOS2)and the downregulated gene model(LCN2,MUC5B,PLAT,TMEM45A,XDH)constructed based on the support vector machine(SVM)algorithm for ECRSwNP was excellent.CONCLUSION The diagnostic genes identified by the SVM model may serve as biological markers for the non-invasive diagnosis of ECRSwNP and potentially play a crucial role in the pathogenesis of ECRSwNP.
