Immunomicrobial pathogenesis of periodontitis: keystones, pathobionts, and host response
Open accessAbstract
Recent studies have uncovered novel mechanisms underlying the breakdown of periodontal host-microbe homeostasis, which can precipitate dysbiosis and periodontitis in susceptible hosts. Dysbiotic microbial communities of keystone pathogens and pathobionts are thought to exhibit synergistic virulence whereby not only can they endure the host response but can also thrive by exploiting tissue-destructive inflammation, which fuels a self-feeding cycle of escalating dysbiosis and inflammatory bone loss, potentially leading to tooth loss and systemic complications. Here, I discuss new paradigms in our understanding of periodontitis, which may shed light into other polymicrobial inflammatory disorders. In addition, I highlight gaps in knowledge required for an integrated picture of the interplay between microbes and innate and adaptive immune elements that initiate and propagate chronic periodontal inflammation.
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Crosstalk between complement and pattern recognition receptors in response to dysbiosis further reinforces the immunomicrobial nature of periodontitis, in which these factors permit dysbiosis via inflammatory destruction of periodontal tissues and the provision of proteinaceous metabolic by-products that further drive dysbiosis and tissue destruction.
“Crosstalk between complement and pattern recognition receptors in response to dysbiosis further reinforces the immunomicrobial nature of periodontitis, in which these factors permit dysbiosis via inflammatory destruction of periodontal tissues and the provision of proteinaceous metabolic by‐products that further drive dysbiosis and tissue destruction.241”
From The oral microbiome: Role of key organisms and complex networks in oral health and disease (2021) · cites this paper as [241]
Biofilm communities maintained at the dentogingival border stimulate immunologic responses at the gingiva, further driving dysbiosis and reinforcing inflammation.
“Biofilm communities maintained at the dentogingival border stimulate immunologic responses at the gingiva, further driving dysbiosis and reinforcing inflammation.241”
From The oral microbiome: Role of key organisms and complex networks in oral health and disease (2021) · cites this paper as [241]
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Torrungruang, K., Jitpakdeebordin, S., Charatkulangkun, O., & Gleebbua, Y. (2015) · PLOS ONE · doi:10.1371/journal.pone.0136646 · Cited by 102 · see citing works
Interactions Between Neutrophils and Periodontal Pathogens in Late-Onset Periodontitis
Jiang, Q., Zhao, Y., Shui, Y., Zhou, X., Cheng, L., Ren, B., Chen, Z., & Li, M. (2021) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2021.627328 · Cited by 76 · see citing works
Chapter 13: Diet and periodontal diseases
Woelber, J. P., & Tennert, C. (2020) · Monographs in Oral Science · doi:10.1159/000455380 · Cited by 54 · see citing works
Host‐microbe interactions: Profiles in the transcriptome, the proteome, and the metabolome
Nguyen, T., Sedghi, L., Ganther, S., Malone, E., Kamarajan, P., & Kapila, Y. L. (2020) · Periodontology 2000 · doi:10.1111/prd.12316 · Cited by 51 · see citing works
A Roadmap towards Precision Periodontics
Rakic, M., Pejcic, N., Perunovic, N., & Vojvodic, D. (2021) · Medicina · doi:10.3390/medicina57030233 · Cited by 36 · see citing works
Outside the limits of bacterial viability: Postbiotics in the management of periodontitis
Moraes, R. M., Schlagenhauf, U., & Anbinder, A. L. (2022) · Biochemical Pharmacology · doi:10.1016/j.bcp.2022.115072 · Cited by 29 · see citing works
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Periodontal Inflamed Surface Area (PISA) associates with composites of salivary cytokines
Tang, V., Hamidi, B., Janal, M. N., Barber, C. A., Godder, B., Palomo, L., & Kamer, A. R. (2023) · PLOS ONE · doi:10.1371/journal.pone.0280333 · Cited by 14 · see citing works
“However, sampling of GCF poses challenges: it is difficult and time consuming; it reflects gingival inflammation at a specific site and therefore numerous sites must be sampled [3]; sampling yields small amounts and GCF can easily be contaminated [4,5].”
Background
- Authors
- Hajishengallis, G.
- Affiliations
- University of Pennsylvania (US)
- Corresponding author
- Hajishengallis, George
- Venue
- Trends in Immunology
- Publisher
- Elsevier BV
- Published
- 2014-01
- Volume
- 35
- Issue
- 1
- Pages
- 3-11
- ISSN
- 1471-4906 (ISSN-L)
- PMC
- PMC3947349
- OpenAlex
- W2066151306
- Cited by
- 1,150
- References
- 83
- Citations by year
- 2026: 100 · 2025: 101 · 2024: 127 · 2023: 124 · 2022: 100 · 2021: 114 · 2020: 88 · 2019: 91 · 2018: 74 · 2017: 73 · 2016: 61 · 2015: 59 · 2014: 35 · 2013: 1
- FWCI
- 7.82
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Trends in Immunology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health
- National Institute of Dental and Craniofacial Research (DE-015254, DE017138, R01DE015254, DE021580, DE021685, RC4DE021580, R01DE021685, R01DE017138)
- Topics
- Health Sciences › Dentistry › Periodontics › Oral microbiology and periodontitis research
- Health Sciences › Medicine › Urology › Periodontal Regeneration and Treatments
- Health Sciences › Dentistry › General Dentistry › Dental Research and COVID-19
- Keywords
- periodontitis, pathobionts, periodontal dysbiosis, host-microbe homeostasis, periodontal inflammation, alveolar bone loss, tooth loss, systemic complications, innate immunity, adaptive immunity
- MeSH terms
- Cell Communication, Disease Susceptibility, Humans, Inflammation, Periodontitis, Alveolar Bone Loss, Host-Pathogen Interactions
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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