Transcriptomic phases of periodontitis lesions using the nonhuman primate model
Abstract We used a nonhuman primate model of ligature-induced periodontitis to identify patterns of gingival transcriptomic after changes demarcating phases of periodontitis lesions (initiation, progression, resolution). A total of 18 adult Macaca mulatta (12–22 years) had ligatures placed (premolar...
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| Autores principales: | , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/48c76a8884504a86b2dcc36917ce6dcb |
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| Sumario: | Abstract We used a nonhuman primate model of ligature-induced periodontitis to identify patterns of gingival transcriptomic after changes demarcating phases of periodontitis lesions (initiation, progression, resolution). A total of 18 adult Macaca mulatta (12–22 years) had ligatures placed (premolar, 1st molar teeth) in all 4 quadrants. Gingival tissue samples were obtained (baseline, 2 weeks, 1 and 3 months during periodontitis and at 5 months resolution). Gene expression was analyzed by microarray [Rhesus Gene 1.0 ST Array (Affymetrix)]. Compared to baseline, a large array of genes were significantly altered at initiation (n = 6049), early progression (n = 4893), and late progression (n = 5078) of disease, with the preponderance being up-regulated. Additionally, 1918 genes were altered in expression with disease resolution, skewed towards down-regulation. Assessment of the genes demonstrated specific profiles of epithelial, bone/connective tissue, apoptosis/autophagy, metabolism, regulatory, immune, and inflammatory responses that were related to health, stages of disease, and tissues with resolved lesions. Unique transcriptomic profiles occured during the kinetics of the periodontitis lesion exacerbation and remission. We delineated phase specific gene expression profiles of the disease lesion. Detection of these gene products in gingival crevicular fluid samples from human disease may contribute to a better understanding of the biological dynamics of the disease to improve patient management. |
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