Screening of crosstalk and pyroptosis-related genes linking periodontitis and osteoporosis based on bioinformatics and machine learning
Background and objectiveThis study aimed to identify crosstalk genes between periodontitis (PD) and osteoporosis (OP) and potential relationships between crosstalk and pyroptosis-related genes.MethodsPD and OP datasets were downloaded from the GEO database and were performed differential expression...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-08-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2022.955441/full |
| _version_ | 1828427988619755520 |
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| author | Jia Liu Ding Zhang Yu Cao Huichao Zhang Jianing Li Jingyu Xu Ling Yu Surong Ye Luyi Yang |
| author_facet | Jia Liu Ding Zhang Yu Cao Huichao Zhang Jianing Li Jingyu Xu Ling Yu Surong Ye Luyi Yang |
| author_sort | Jia Liu |
| collection | DOAJ |
| description | Background and objectiveThis study aimed to identify crosstalk genes between periodontitis (PD) and osteoporosis (OP) and potential relationships between crosstalk and pyroptosis-related genes.MethodsPD and OP datasets were downloaded from the GEO database and were performed differential expression analysis to obtain DEGs. Overlapping DEGs got crosstalk genes linking PD and OP. Pyroptosis-related genes were obtained from literature reviews. Pearson coefficients were used to calculate crosstalk and pyroptosis-related gene correlations in the PD and OP datasets. Paired genes were obtained from the intersection of correlated genes in PD and OP. PINA and STRING databases were used to conduct the crosstalk-bridge-pyroptosis genes PPI network. The clusters in which crosstalk and pyroptosis-related genes were mainly concentrated were defined as key clusters. The key clusters’ hub genes and the included paired genes were identified as key crosstalk-pyroptosis genes. Using ROC curve analysis and XGBoost screened key genes. PPI subnetwork, gene–biological process and gene-pathway networks were constructed based on key genes. In addition, immune infiltration was analyzed on the PD dataset using the CIBERSORT algorithm.ResultsA total of 69 crosstalk genes were obtained. 13 paired genes and hub genes TNF and EGFR in the key clusters (cluster2, cluster8) were identified as key crosstalk-pyroptosis genes. ROC and XGBoost showed that PRKCB, GSDMD, ARMCX3, and CASP3 were more accurate in predicting disease than other key crosstalk-pyroptosis genes while better classifying properties as a whole. KEGG analysis showed that PRKCB, GSDMD, ARMCX3, and CASP3 were involved in neutrophil extracellular trap formation and MAPK signaling pathway pathways. Immune infiltration results showed that all four key genes positively correlated with plasma cells and negatively correlated with T cells follicular helper, macrophages M2, and DCs.ConclusionThis study shows a joint mechanism between PD and OP through crosstalk and pyroptosis-related genes. The key genes PRKCB, GSDMD, ARMCX3, and CASP3 are involved in the neutrophil extracellular trap formation and MAPK signaling pathway, affecting both diseases. These findings may point the way to future research. |
| first_indexed | 2024-12-10T17:11:09Z |
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| institution | Directory Open Access Journal |
| issn | 1664-3224 |
| language | English |
| last_indexed | 2024-12-10T17:11:09Z |
| publishDate | 2022-08-01 |
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| series | Frontiers in Immunology |
| spelling | doaj.art-dd9408fb93f0466cafd7d37c68175c332022-12-22T01:40:19ZengFrontiers Media S.A.Frontiers in Immunology1664-32242022-08-011310.3389/fimmu.2022.955441955441Screening of crosstalk and pyroptosis-related genes linking periodontitis and osteoporosis based on bioinformatics and machine learningJia Liu0Ding Zhang1Yu Cao2Huichao Zhang3Jianing Li4Jingyu Xu5Ling Yu6Surong Ye7Luyi Yang8Department of Orthodontics, Hospital of Stomatology, Jilin University, Changchun, ChinaDepartment of Spine Surgery, China-Japan Union Hospital, Jilin University, Changchun, ChinaDepartment of Orthodontics, Hospital of Stomatology, Jilin University, Changchun, ChinaDepartment of Orthodontics, Hospital of Stomatology, Jilin University, Changchun, ChinaDepartment of Endodontics, Hospital of Stomatology, Jilin University, Changchun, ChinaDepartment of Orthodontics, Hospital of Stomatology, Jilin University, Changchun, ChinaDepartment of Orthodontics, Hospital of Stomatology, Jilin University, Changchun, ChinaDepartment of Orthodontics, Hospital of Stomatology, Jilin University, Changchun, ChinaDepartment of Orthodontics, Hospital of Stomatology, Jilin University, Changchun, ChinaBackground and objectiveThis study aimed to identify crosstalk genes between periodontitis (PD) and osteoporosis (OP) and potential relationships between crosstalk and pyroptosis-related genes.MethodsPD and OP datasets were downloaded from the GEO database and were performed differential expression analysis to obtain DEGs. Overlapping DEGs got crosstalk genes linking PD and OP. Pyroptosis-related genes were obtained from literature reviews. Pearson coefficients were used to calculate crosstalk and pyroptosis-related gene correlations in the PD and OP datasets. Paired genes were obtained from the intersection of correlated genes in PD and OP. PINA and STRING databases were used to conduct the crosstalk-bridge-pyroptosis genes PPI network. The clusters in which crosstalk and pyroptosis-related genes were mainly concentrated were defined as key clusters. The key clusters’ hub genes and the included paired genes were identified as key crosstalk-pyroptosis genes. Using ROC curve analysis and XGBoost screened key genes. PPI subnetwork, gene–biological process and gene-pathway networks were constructed based on key genes. In addition, immune infiltration was analyzed on the PD dataset using the CIBERSORT algorithm.ResultsA total of 69 crosstalk genes were obtained. 13 paired genes and hub genes TNF and EGFR in the key clusters (cluster2, cluster8) were identified as key crosstalk-pyroptosis genes. ROC and XGBoost showed that PRKCB, GSDMD, ARMCX3, and CASP3 were more accurate in predicting disease than other key crosstalk-pyroptosis genes while better classifying properties as a whole. KEGG analysis showed that PRKCB, GSDMD, ARMCX3, and CASP3 were involved in neutrophil extracellular trap formation and MAPK signaling pathway pathways. Immune infiltration results showed that all four key genes positively correlated with plasma cells and negatively correlated with T cells follicular helper, macrophages M2, and DCs.ConclusionThis study shows a joint mechanism between PD and OP through crosstalk and pyroptosis-related genes. The key genes PRKCB, GSDMD, ARMCX3, and CASP3 are involved in the neutrophil extracellular trap formation and MAPK signaling pathway, affecting both diseases. These findings may point the way to future research.https://www.frontiersin.org/articles/10.3389/fimmu.2022.955441/fullperiodontitisosteoporosispyroptosisgeonomicscommunity discoveryXGBoost |
| spellingShingle | Jia Liu Ding Zhang Yu Cao Huichao Zhang Jianing Li Jingyu Xu Ling Yu Surong Ye Luyi Yang Screening of crosstalk and pyroptosis-related genes linking periodontitis and osteoporosis based on bioinformatics and machine learning Frontiers in Immunology periodontitis osteoporosis pyroptosis geonomics community discovery XGBoost |
| title | Screening of crosstalk and pyroptosis-related genes linking periodontitis and osteoporosis based on bioinformatics and machine learning |
| title_full | Screening of crosstalk and pyroptosis-related genes linking periodontitis and osteoporosis based on bioinformatics and machine learning |
| title_fullStr | Screening of crosstalk and pyroptosis-related genes linking periodontitis and osteoporosis based on bioinformatics and machine learning |
| title_full_unstemmed | Screening of crosstalk and pyroptosis-related genes linking periodontitis and osteoporosis based on bioinformatics and machine learning |
| title_short | Screening of crosstalk and pyroptosis-related genes linking periodontitis and osteoporosis based on bioinformatics and machine learning |
| title_sort | screening of crosstalk and pyroptosis related genes linking periodontitis and osteoporosis based on bioinformatics and machine learning |
| topic | periodontitis osteoporosis pyroptosis geonomics community discovery XGBoost |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2022.955441/full |
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