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Genes Critical for Developing Periodontitis: Lessons from Mouse Models

Overview of attention for article published in Frontiers in immunology, October 2017
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Title
Genes Critical for Developing Periodontitis: Lessons from Mouse Models
Published in
Frontiers in immunology, October 2017
DOI 10.3389/fimmu.2017.01395
Pubmed ID
Authors

Teun J. de Vries, Stefano Andreotta, Bruno G. Loos, Elena A. Nicu

Abstract

Since the etiology of periodontitis in humans is not fully understood, genetic mouse models may pinpoint indispensable genes for optimal immunological protection of the periodontium against tissue destruction. This review describes the current knowledge of genes that are involved for a proper maintenance of a healthy periodontium in mice. Null mutations of genes required for leukocyte cell-cell recognition and extravasation (e.g., Icam-1, P-selectin, Beta2-integrin/Cd18), for pathogen recognition and killing (e.g., Tlr2, Tlr4, Lamp-2), immune modulatory molecules (e.g., Cxcr2, Ccr4, IL-10, Opg, IL1RA, Tnf-α receptor, IL-17 receptor, Socs3, Foxo1), and proteolytic enzymes (e.g., Mmp8, Plasmin) cause periodontitis, most likely due to an inefficient clearance of bacteria and bacterial products. Several mechanisms resulting in periodontitis can be recognized: (1) inefficient bacterial control by the polymorphonuclear neutrophils (defective migration, killing), (2) inadequate antigen presentation by dendritic cells, or (3) exaggerated production of pro-inflammatory cytokines. In all these cases, the local immune reaction is skewed toward a Th1/Th17 (and insufficient activation of the Th2/Treg) with subsequent osteoclast activation. Finally, genotypes are described that protect the mice from periodontitis: the SCID mouse, and mice lacking Tlr2/Tlr4, the Ccr1/Ccr5, the Tnf-α receptor p55, and Cathepsin K by attenuating the inflammatory reaction and the osteoclastogenic response.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 50 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 16%
Student > Bachelor 7 14%
Student > Master 6 12%
Student > Doctoral Student 3 6%
Student > Postgraduate 3 6%
Other 5 10%
Unknown 18 36%
Readers by discipline Count As %
Medicine and Dentistry 11 22%
Biochemistry, Genetics and Molecular Biology 9 18%
Immunology and Microbiology 4 8%
Agricultural and Biological Sciences 3 6%
Pharmacology, Toxicology and Pharmaceutical Science 2 4%
Other 3 6%
Unknown 18 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 November 2017.
All research outputs
#20,663,600
of 25,382,440 outputs
Outputs from Frontiers in immunology
#24,755
of 31,537 outputs
Outputs of similar age
#263,070
of 339,185 outputs
Outputs of similar age from Frontiers in immunology
#488
of 580 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 31,537 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.4. This one is in the 13th percentile – i.e., 13% of its peers scored the same or lower than it.
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We're also able to compare this research output to 580 others from the same source and published within six weeks on either side of this one. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.