Comparative Analysis of Gene Expression Patterns for Oral Epithelium-Related Functions with Aging

Ebersole, Jeffrey L.; Orraca, Luis; Novak, M. John; Kirakodu, Sreenatha; González‐Martínez, Janis; González, Octavio A.

doi:10.1007/978-3-030-28524-1_11

Cited by 13 publications

(11 citation statements)

References 71 publications

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“…However, one primary interpretation of the data was that the effects on the circadian genes across the age groups with the development of periodontitis was actually quite similar, rather than substantially different, and in disease there was a somewhat distinctive pattern of circadian gene and local tissue biology gene expression. This observation actually differed from a number of our other analyses targeting immune and inflammatory pathways in gingival tissues that demonstrated substantial differences in expression and regulation with age and disease [ 31 , 33 , 37 , 38 , 55 , 87 – 90 ]. Thus, the effects on this pathway seemed to be “conserved” in disease.…”

Section: Discussioncontrasting

confidence: 87%

Mucosal circadian rhythm pathway genes altered by aging and periodontitis

Ebersole

González

2022

PLoS ONE

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As circadian processes can impact the immune system and are affected by infections and inflammation, this study examined the expression of circadian rhythm genes in periodontitis. Methods: Macaca mulatta were used with naturally-occurring and ligature-induced periodontitis. Gingival tissue samples were obtained from healthy, diseased, and resolved sites in four groups: young (≤3 years), adolescent (3–7 years), adult (12–26) and aged (18–23 years). Microarrays targeted circadian rhythm (n = 42), inflammation/tissue destruction (n = 11), bone biology (n = 8) and hypoxia pathway (n = 7) genes. Results: The expression of many circadian rhythm genes, across functional components of the pathway, was decreased in healthy tissues from younger and aged animals, as well as showing significant decreases with periodontitis. Negative correlations of the circadian rhythm gene levels with inflammatory mediators and tissue destructive/remodeling genes were particularly accentuated in disease. A dominance of positive correlations with hypoxia genes was observed, except HIF1A, that was uniformly negatively correlated in health, disease and resolution. Conclusions: The chronic inflammation of periodontitis exhibits an alteration of the circadian rhythm pathway, predominantly via decreased gene expression. Thus, variation in disease expression and the underlying molecular mechanisms of disease may be altered due to changes in regulation of the circadian rhythm pathway functions.

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Section: Discussioncontrasting

confidence: 87%

Mucosal circadian rhythm pathway genes altered by aging and periodontitis

Ebersole

González

2022

PLoS ONE

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“…A striking feature of the AMF gene expression patterns was exposed when examining the clustering of the AMF expression in gingival tissues from the various age groups, and in health and disease. Our previous results have supported that the transition from health to disease was a major driving feature of altered gingival gene expression patterns for multiple pathways [27,30,37,38,40,41,[58][59][60][61][62]. While some age differences were observed, the major changes appeared to be disease related.…”

Section: Discussionsupporting

confidence: 56%

Gingival Transcriptome of Innate Antimicrobial Factors and the Oral Microbiome With Aging and Periodontitis

Ebersole

Kirakodu

Linh-Trung

et al. 2022

Front. Oral. Health

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The epithelial barrier at mucosal sites comprises an important mechanical protective feature of innate immunity, and is intimately involved in communicating signals of infection/tissue damage to inflammatory and immune cells in these local environments. A wide array of antimicrobial factors (AMF) exist at mucosal sites and in secretions that contribute to this innate immunity. A non-human primate model of ligature-induced periodontitis was used to explore characteristics of the antimicrobial factor transcriptome (n = 114 genes) of gingival biopsies in health, initiation and progression of periodontal lesions, and in samples with clinical resolution. Age effects and relationship of AMF to the dominant members of the oral microbiome were also evaluated. AMF could be stratified into 4 groups with high (n = 22), intermediate (n = 29), low (n = 18) and very low (n = 45) expression in healthy adult tissues. A subset of AMF were altered in healthy young, adolescent and aged samples compared with adults (e.g., APP, CCL28, DEFB113, DEFB126, FLG2, PRH1) and were affected across multiple age groups. With disease, a greater number of the AMF genes were affected in the adult and aged samples with skewing toward decreased expression, for example WDC12, PGLYRP3, FLG2, DEFB128, and DEF4A/B, with multiple age groups. Few of the AMF genes showed a >2-fold increase with disease in any age group. Selected AMF exhibited significant positive correlations across the array of AMF that varied in health and disease. In contrast, a rather limited number of the AMF significantly correlated with members of the microbiome; most prominent in healthy samples. These correlated microbes were different in younger and older samples and differed in health, disease and resolution samples. The findings supported effects of age on the expression of AMF genes in healthy gingival tissues showing a relationship to members of the oral microbiome. Furthermore, a dynamic expression of AMF genes was related to the disease process and showed similarities across the age groups, except for low/very low expressed genes that were unaffected in young samples. Targeted assessment of AMF members from this large array may provide insight into differences in disease risk and biomolecules that provide some discernment of early transition to disease.

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“…Integrins expressed in periodontal tissues are involved in regulating cell attachment, maintaining tissue integrity, and mediating cell signaling, gene expression, and cytokine activation [ 41 ]. In addition, it was shown that ITGAM was significantly increased in the gingival tissue of the aged nonhuman primate model [ 42 ]. A proteomics study has revealed a significant elevation of ITGAM in gingival tissue of chronic periodontitis patients [ 43 ].…”

Section: Discussionmentioning

confidence: 99%

Integrated analysis and exploration of potential shared gene signatures between carotid atherosclerosis and periodontitis

2022

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Background Increasing evidence has suggested an association between carotid atherosclerosis (CAS) and periodontitis (PD); however, the mechanisms have not been fully understood. This study aims to investigate the shared genes and molecular mechanisms underlying the co-pathogenesis of CAS and PD. Methods Gene Expression Omnibus (GEO) datasets GSE100927 and GSE10334 were downloaded, and differentially expressed genes (DEGs) shared by both datasets were identified. The functional enrichment analysis of these overlapping DEGs was then conducted. A protein-protein interaction (PPI) network was created using the STRING database and Cytoscape software, and PPI key genes were identified using the cytoHubba plugin. Then, weighted gene co-expression network analysis (WGCNA) was performed on GSE100927 and GSE10334, and the gene modules most correlated with CAS and PD were identified as key modules. The genes in key modules overlapping with PPI key genes were determined to be the key crosstalk genes. Subsequently, the key crosstalk genes were validated in three independent external datasets (GSE43292 [CAS microarray dataset], GSE16134 [PD microarray dataset], and GSE28829 [CAS microarray dataset]). In addition, the immune cell patterns of PD and CAS were evaluated by single-sample gene set enrichment analysis (ssGSEA), and the correlation of key crosstalk genes with each immune cell was calculated. Finally, we investigated the transcription factors (TFs) that regulate key crosstalk genes using NetworkAnalyst 3.0 platform. Results 355 overlapping DEGs of CAS and PD were identified. Functional enrichment analysis highlighted the vital role of immune and inflammatory pathways in CAS and PD. The PPI network was constructed, and eight PPI key genes were identified by cytoHubba, including CD4, FCGR2A, IL1B, ITGAM, ITGAX, LCK, PTPRC, and TNF. By WGCNA, the turquoise module was identified as the most correlated module with CAS, and the blue module was identified as the most correlated module with PD. Ultimately, ITGAM and LCK were identified as key crosstalk genes as they appeared both in key modules and PPI key genes. Expression levels of ITGAM and LCK were significantly elevated in the case groups of the test datasets (GSE100927 and GSE10334) and validation datasets (GSE43292, GSE16134, and GSE28829). In addition, the expression of multiple immune cells was significantly elevated in PD and CAS compared to controls, and the two key crosstalk genes were both significantly associated with CD4 T cells. Finally, SPI1 was identified as a potential key TF, which regulates the two key crosstalk genes. Conclusion This study identified the key crosstalk genes and TF in PD and CAS, which provides new insights for further studies on the co-morbidity mechanisms of CAS and PD from an immune and inflammatory perspective.

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Comparative Analysis of Gene Expression Patterns for Oral Epithelium-Related Functions with Aging

Cited by 13 publications

References 71 publications

Mucosal circadian rhythm pathway genes altered by aging and periodontitis

Mucosal circadian rhythm pathway genes altered by aging and periodontitis

Gingival Transcriptome of Innate Antimicrobial Factors and the Oral Microbiome With Aging and Periodontitis

Integrated analysis and exploration of potential shared gene signatures between carotid atherosclerosis and periodontitis

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