Literature DB >> 34993975

Identification of hub genes related to immune cell infiltration in periodontitis using integrated bioinformatic analysis.

Xudong Gao1, Chenxi Jiang1, Siqi Yao1, Li Ma1, Xiaoxuan Wang1,2, Zhengguo Cao1,2.   

Abstract

BACKGROUND AND
OBJECTIVE: Periodontitis is an inflammatory disease of the periodontium. However, the hub genes in periodontitis and their correlation with immune cells are not clear. This study aimed to identify hub genes and immune infiltration properties in periodontitis and to explore the correlation between hub genes and immune cells.
MATERIAL AND METHODS: Differentially expressed genes (DEGs) analysis and weighted gene co-expression network analysis (WGCNA) were performed both on GSE10334 and GSE173078 datasets. Hub genes were identified via WGCNA and DEGs. The proportions of infiltrating immune cells were calculated by CIBERSORT algorithm, and single-cell RNA-sequencing dataset GSE164241 was used to explore cell-type-specific expression profiles of hub genes.
RESULTS: Eight hub genes (DERL3, FKBP11, LAX1, CD27, SPAG4, ST6GAL1, MZB1, and SEL1L3) were selected via WGCNA and DEGs by combining GSE10334 and GSE173078 datasets. CIBERSORT analysis showed a significant difference in the proportion of B cells, dendritic cells resting, and neutrophils in the gingival tissues between healthy and periodontitis patients, and expressions of these genes were highly correlated with the infiltration of B cells in periodontitis. Furthermore, real-time quantitative PCR results further confirmed the overexpression of hub genes. Analysis of GSE164241dataset further identified that most of hub genes were mainly expressed in B cells.
CONCLUSIONS: By integrating WGCNA, DEGs, and CIBERSORT analysis, eight genes were identified to be the hub genes of periodontitis and most of them were mainly expressed in B cells encouraging further researches on B cells in periodontitis pathogenesis.
© 2022 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Entities:  

Keywords:  B-lymphocytes; bio-informatics; immunity; inflammation; periodontal disease

Mesh:

Substances:

Year:  2022        PMID: 34993975     DOI: 10.1111/jre.12970

Source DB:  PubMed          Journal:  J Periodontal Res        ISSN: 0022-3484            Impact factor:   4.419


  2 in total

1.  Identifying key genes in CD4+ T cells of systemic lupus erythematosus by integrated bioinformatics analysis.

Authors:  Zutong Li; Zhilong Wang; Tian Sun; Shanshan Liu; Shuai Ding; Lingyun Sun
Journal:  Front Genet       Date:  2022-08-15       Impact factor: 4.772

2.  Identification of Endoplasmic Reticulum Stress-Related Biomarkers of Periodontitis Based on Machine Learning: A Bioinformatics Analysis.

Authors:  Qingyu Zhang; Yuheng Jiao; Ning Ma; Li Zhang; Yuqi Song
Journal:  Dis Markers       Date:  2022-08-29       Impact factor: 3.464

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.