Identification and analysis of neutrophil extracellular trap-related genes in periodontitis via bioinformatics and experimental verification
Abstract Background Emerging evidence highlights the significant role of neutrophil extracellular traps (NETs) in periodontitis, though the precise mechanisms remain insufficiently understood. This study intends to investigate the comprehensive effects of NET-related genes (NRGs) on periodontitis by...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-08-01
|
| Series: | BMC Oral Health |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12903-025-06663-2 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849331635128893440 |
|---|---|
| author | Miao Yu Zhenqi Ye Zixin Ye Yaping Wu Xiang Wu |
| author_facet | Miao Yu Zhenqi Ye Zixin Ye Yaping Wu Xiang Wu |
| author_sort | Miao Yu |
| collection | DOAJ |
| description | Abstract Background Emerging evidence highlights the significant role of neutrophil extracellular traps (NETs) in periodontitis, though the precise mechanisms remain insufficiently understood. This study intends to investigate the comprehensive effects of NET-related genes (NRGs) on periodontitis by bioinformatic analysis. Methods The microarray datasets were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed NRGs (DE-NRGs) were identified and functionally annotated. Then, machine learning algorithms were exploited to screen hub NRGs, and a predictive model was constructed based on these hub NRGs. Moreover, the expression level of CXCR4, one of the hub NRGs, was experimentally validated. Results Eighty-three DE-NRGs were identified and mainly correlated with multiple periodontitis-related pathways. Then, a diagnostic NRG signature based on 7-hub NRGs (LPAR3, CXCR4, F3, MAPK7, KCNN3, SYK, and HIF1A) was constructed using two different machine learning algorithms. The diagnostic NRG signature demonstrated favorable predictive efficacy, with an AUC of 0.929 in the training and 0.936 in the validation cohorts. The mouse periodontitis model verified that CXCR4 and HIF1A was markedly upregulated in periodontitis tissues. Conclusion This study reveals that NRGs hold great potential as a robust and promising parameter for assessing periodontitis diagnosis. Targeting NRGs could represent a potential direction for future research into periodontitis treatment. Clinical trial number Not applicable. |
| format | Article |
| id | doaj-art-43168901d26d4e4b90a57e11bfeb6a8e |
| institution | Kabale University |
| issn | 1472-6831 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Oral Health |
| spelling | doaj-art-43168901d26d4e4b90a57e11bfeb6a8e2025-08-20T03:46:28ZengBMCBMC Oral Health1472-68312025-08-0125111610.1186/s12903-025-06663-2Identification and analysis of neutrophil extracellular trap-related genes in periodontitis via bioinformatics and experimental verificationMiao Yu0Zhenqi Ye1Zixin Ye2Yaping Wu3Xiang Wu4State Key Laboratory Cultivation Base of Research, Prevention and Treatment for Oral DiseasesDepartment of Stomatology, The First Affiliated Hospital of Wannan Medical CollegeState Key Laboratory Cultivation Base of Research, Prevention and Treatment for Oral DiseasesDepartment of Oral and Maxillofacial Surgery, The Affiliated Stomatological Hospital of Nanjing Medical UniversityDepartment of General Dentistry, The Affiliated Stomatological Hospital of Nanjing Medical UniversityAbstract Background Emerging evidence highlights the significant role of neutrophil extracellular traps (NETs) in periodontitis, though the precise mechanisms remain insufficiently understood. This study intends to investigate the comprehensive effects of NET-related genes (NRGs) on periodontitis by bioinformatic analysis. Methods The microarray datasets were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed NRGs (DE-NRGs) were identified and functionally annotated. Then, machine learning algorithms were exploited to screen hub NRGs, and a predictive model was constructed based on these hub NRGs. Moreover, the expression level of CXCR4, one of the hub NRGs, was experimentally validated. Results Eighty-three DE-NRGs were identified and mainly correlated with multiple periodontitis-related pathways. Then, a diagnostic NRG signature based on 7-hub NRGs (LPAR3, CXCR4, F3, MAPK7, KCNN3, SYK, and HIF1A) was constructed using two different machine learning algorithms. The diagnostic NRG signature demonstrated favorable predictive efficacy, with an AUC of 0.929 in the training and 0.936 in the validation cohorts. The mouse periodontitis model verified that CXCR4 and HIF1A was markedly upregulated in periodontitis tissues. Conclusion This study reveals that NRGs hold great potential as a robust and promising parameter for assessing periodontitis diagnosis. Targeting NRGs could represent a potential direction for future research into periodontitis treatment. Clinical trial number Not applicable.https://doi.org/10.1186/s12903-025-06663-2PeriodontitisNeutrophil extracellular trapsImmune infiltrationBioinformatics |
| spellingShingle | Miao Yu Zhenqi Ye Zixin Ye Yaping Wu Xiang Wu Identification and analysis of neutrophil extracellular trap-related genes in periodontitis via bioinformatics and experimental verification BMC Oral Health Periodontitis Neutrophil extracellular traps Immune infiltration Bioinformatics |
| title | Identification and analysis of neutrophil extracellular trap-related genes in periodontitis via bioinformatics and experimental verification |
| title_full | Identification and analysis of neutrophil extracellular trap-related genes in periodontitis via bioinformatics and experimental verification |
| title_fullStr | Identification and analysis of neutrophil extracellular trap-related genes in periodontitis via bioinformatics and experimental verification |
| title_full_unstemmed | Identification and analysis of neutrophil extracellular trap-related genes in periodontitis via bioinformatics and experimental verification |
| title_short | Identification and analysis of neutrophil extracellular trap-related genes in periodontitis via bioinformatics and experimental verification |
| title_sort | identification and analysis of neutrophil extracellular trap related genes in periodontitis via bioinformatics and experimental verification |
| topic | Periodontitis Neutrophil extracellular traps Immune infiltration Bioinformatics |
| url | https://doi.org/10.1186/s12903-025-06663-2 |
| work_keys_str_mv | AT miaoyu identificationandanalysisofneutrophilextracellulartraprelatedgenesinperiodontitisviabioinformaticsandexperimentalverification AT zhenqiye identificationandanalysisofneutrophilextracellulartraprelatedgenesinperiodontitisviabioinformaticsandexperimentalverification AT zixinye identificationandanalysisofneutrophilextracellulartraprelatedgenesinperiodontitisviabioinformaticsandexperimentalverification AT yapingwu identificationandanalysisofneutrophilextracellulartraprelatedgenesinperiodontitisviabioinformaticsandexperimentalverification AT xiangwu identificationandanalysisofneutrophilextracellulartraprelatedgenesinperiodontitisviabioinformaticsandexperimentalverification |