Qibing Wu, Yixi Niu, Hanmo Li, Yaping Pan, Chen Li
{"title":"全面分析与 Sialylation 相关的基因谱系及其对牙周炎免疫微环境的影响。","authors":"Qibing Wu, Yixi Niu, Hanmo Li, Yaping Pan, Chen Li","doi":"10.1007/s10753-024-02177-1","DOIUrl":null,"url":null,"abstract":"<p><p>Periodontitis is a chronic inflammatory disease strongly influenced by host's immune response. Aberrant sialylation on cell surface plays a key role in inflammation and immunity. This study aims to identify sialylation-related genes associated with periodontitis and explore their impact on periodontal immune microenvironment. Differential expression analysis and machine learning were employed to determine core sialylation-related genes after datasets were retrieved and integrated. A diagnostic model incorporating these genes was constructed, following the immune cell infiltration analysis. Consensus clustering and weighted gene co-expression network analysis stratified periodontitis patients into subgroups and identified associated module genes. Single-cell sequencing data was further utilized to investigate the impact of sialylation on the periodontal immune microenvironment with pseudo-time series analysis and cell communication analysis. Periodontitis had a higher sialylation score with six key sialylation genes (CHST2, SELP, ST6GAL1, ST3GAL1, NEU1, FCN1) identified. The multi-gene diagnostic model demonstrated high accuracy and efficacy. Significant associations were observed between the key genes and immune cell populations, such as monocytes and B cells, in the periodontal immune microenvironment. Clustering analysis revealed two distinct sialylation-related subgroups with differential immune profiles. Single-cell data showed a significantly higher expression of sialylation-related genes in monocytes, which was found to significantly impact their developmental processes as well as their intercellular communication with B cells. The six identified sialylation-related genes hold potential as periodontitis biomarkers. High sialylation expression can impact the differentiation and cell-cell communication of monocytes. Sialylation-related genes are closely associated with alterations in the periodontal immune microenvironment.</p>","PeriodicalId":13524,"journal":{"name":"Inflammation","volume":" ","pages":""},"PeriodicalIF":4.5000,"publicationDate":"2024-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comprehensive Analysis of Sialylation-Related Gene Profiles and Their Impact on the Immune Microenvironment in Periodontitis.\",\"authors\":\"Qibing Wu, Yixi Niu, Hanmo Li, Yaping Pan, Chen Li\",\"doi\":\"10.1007/s10753-024-02177-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Periodontitis is a chronic inflammatory disease strongly influenced by host's immune response. Aberrant sialylation on cell surface plays a key role in inflammation and immunity. This study aims to identify sialylation-related genes associated with periodontitis and explore their impact on periodontal immune microenvironment. Differential expression analysis and machine learning were employed to determine core sialylation-related genes after datasets were retrieved and integrated. A diagnostic model incorporating these genes was constructed, following the immune cell infiltration analysis. Consensus clustering and weighted gene co-expression network analysis stratified periodontitis patients into subgroups and identified associated module genes. Single-cell sequencing data was further utilized to investigate the impact of sialylation on the periodontal immune microenvironment with pseudo-time series analysis and cell communication analysis. Periodontitis had a higher sialylation score with six key sialylation genes (CHST2, SELP, ST6GAL1, ST3GAL1, NEU1, FCN1) identified. The multi-gene diagnostic model demonstrated high accuracy and efficacy. Significant associations were observed between the key genes and immune cell populations, such as monocytes and B cells, in the periodontal immune microenvironment. Clustering analysis revealed two distinct sialylation-related subgroups with differential immune profiles. Single-cell data showed a significantly higher expression of sialylation-related genes in monocytes, which was found to significantly impact their developmental processes as well as their intercellular communication with B cells. The six identified sialylation-related genes hold potential as periodontitis biomarkers. High sialylation expression can impact the differentiation and cell-cell communication of monocytes. Sialylation-related genes are closely associated with alterations in the periodontal immune microenvironment.</p>\",\"PeriodicalId\":13524,\"journal\":{\"name\":\"Inflammation\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":4.5000,\"publicationDate\":\"2024-11-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Inflammation\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s10753-024-02177-1\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CELL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Inflammation","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s10753-024-02177-1","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CELL BIOLOGY","Score":null,"Total":0}
Comprehensive Analysis of Sialylation-Related Gene Profiles and Their Impact on the Immune Microenvironment in Periodontitis.
Periodontitis is a chronic inflammatory disease strongly influenced by host's immune response. Aberrant sialylation on cell surface plays a key role in inflammation and immunity. This study aims to identify sialylation-related genes associated with periodontitis and explore their impact on periodontal immune microenvironment. Differential expression analysis and machine learning were employed to determine core sialylation-related genes after datasets were retrieved and integrated. A diagnostic model incorporating these genes was constructed, following the immune cell infiltration analysis. Consensus clustering and weighted gene co-expression network analysis stratified periodontitis patients into subgroups and identified associated module genes. Single-cell sequencing data was further utilized to investigate the impact of sialylation on the periodontal immune microenvironment with pseudo-time series analysis and cell communication analysis. Periodontitis had a higher sialylation score with six key sialylation genes (CHST2, SELP, ST6GAL1, ST3GAL1, NEU1, FCN1) identified. The multi-gene diagnostic model demonstrated high accuracy and efficacy. Significant associations were observed between the key genes and immune cell populations, such as monocytes and B cells, in the periodontal immune microenvironment. Clustering analysis revealed two distinct sialylation-related subgroups with differential immune profiles. Single-cell data showed a significantly higher expression of sialylation-related genes in monocytes, which was found to significantly impact their developmental processes as well as their intercellular communication with B cells. The six identified sialylation-related genes hold potential as periodontitis biomarkers. High sialylation expression can impact the differentiation and cell-cell communication of monocytes. Sialylation-related genes are closely associated with alterations in the periodontal immune microenvironment.
期刊介绍:
Inflammation publishes the latest international advances in experimental and clinical research on the physiology, biochemistry, cell biology, and pharmacology of inflammation. Contributions include full-length scientific reports, short definitive articles, and papers from meetings and symposia proceedings. The journal''s coverage includes acute and chronic inflammation; mediators of inflammation; mechanisms of tissue injury and cytotoxicity; pharmacology of inflammation; and clinical studies of inflammation and its modification.