Identification of core genes related to severity of respiratory syncytial virus bronchiolitis based on RNA sequencing data
10.3760/cma.j.cn112309-20210825-00278
- VernacularTitle:基于RNA测序数据筛选与呼吸道合胞病毒毛细支气管炎疾病严重程度相关的核心基因
- Author:
Tingting WENG
1
;
Leying WANG
;
Haiyan LI
;
Chunchan LIANG
;
Zhenwei LIU
;
Lin DONG
Author Information
1. 温州医科大学附属第二医院、育英儿童医院儿童呼吸科，温州 325027
- Keywords:
RNA-sequencing;
Weighted gene co-expression network analysis;
Respiratory syncytial virus;
Bronchiolitis;
Disease severity
- From:
Chinese Journal of Microbiology and Immunology
2022;42(5):396-403
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To identify the core genes related to the disease severity of respiratory syncytial virus (RSV) bronchiolitis in children using RNA sequencing (RNA-seq) and weighted gene co-expression network analysis (WGCNA), aiming to provide reference for predicting the condition of RSV infection.Methods:Twenty-two patients admitted to the Second Affiliated Hospital of Wenzhou Medical University with RSV bronchiolitis from October 1, 2019 to February 29, 2020 were enrolled as the case group. They were divided into three groups based on the severity of the disease: mild group, moderate group and severe group. Twenty-two healthy children were selected as the control group. Total RNA was extracted from whole blood leukocytes and analyzed by RNA-seq to compare the differentially expressed genes (DEGs) between children with RSV bronchiolitis and healthy children. The gene co-expression modules related to disease severity and biological indicators for disease severity assessment were identified.Results:The median age of the 22 patients (19 males and 3 females) was 3 months. The median age of the 22 healthy children (14 males and 8 females) was 4 months. There was no significant difference in age or gender between the two groups. There were 8 cases in the mild group, 7 cases in the moderate group and 7 cases in the severe group. Through significance analysis, 416 DEGs were found in the mild group, 586 in the moderate group and 846 in the severe group. According to WGCNA analysis, 10 co-expression modules were found, among which brown module ( r=0.62, P<0.001) was significantly correlated with disease severity. The protein-protein interaction network of DEGs in brown module was constructed and the top 30 core genes were selected according to the connectivity of gene nodes, among which the genes with high correlation were RBX1 and PSMA7. The expression of RBX1 and PSMA7 genes was up-regulated in the severe group, but their expression in the mild and moderate groups was not significantly different from that in the control group. Conclusions:RBX1 and PSMA7 genes might be biological predictors of disease severity in RSV bronchiolitis.
