Background: In 2012 periodontal disease affected 46% of adults in the United States, with 8.9% classified as severe (Eke et al. 2015). Before everyone starts freaking out and drinking mouthwash, let’s talk about periodontal disease. Periodontal disease means gum disease, anything from simple gum inflammation, all the way to the loss of bone and the teeth falling out (“Periodontal Gum Disease”, 2013). Below I included a figure to show the progression of the disease.
This disease is caused by microbes in the dental plaque migrating into the gum pockets causing inflammation, which will cause the gum to recede and with it the connective tissue holding in the tooth (Teles et al. 2013). Since periodontal disease is caused by microbes, it would not be surprising if there were differences between the community of microbes living in the mouths of healthy individuals, and those with periodontal disease. For the purpose of this discussion the oral microbiome is referring to the community of bacteria in the mouth of an individual. In fact, with the use of next-gen sequencing of the oral microbiome, it may be possible to determine differences between the mircobiomes of healthy and diseased individuals. A 2012 study found that community diversity is higher in individuals with chronic periodontal disease, but the results were complicated with 123 species were more abundant in diseased individuals and with 53 species were more abundant in healthy individuals (Griffen et al. 2012).
Wouldn’t it be great to be able to tell the effectiveness of a treatment by observing the changes in the microbiome?
With the advances in sequencing technology, and the information from previous studies it is now possible to design a study to attempt to answer this question. The results of this study were published in 2014 (Schwarzberg et al.). Central Question: Do patients with periodontal disease who receive treatment experience a change in the oral microbiome that is consistent with disease or health? Treatment for periodontal disease depends on severity including deep cleaning, medications, or surgery. In order to address this we first must have a sample population that has periodontal disease and will be receiving treatment. Researchers collected samples of the microbiome from the deepest pockets in the gum, before and after treatment for periodontal disease. Using next-gen DNA sequencing, the authors determined the composition of the mircobiome. Combining this information with whether or not the patient responded to treatment, allowed the authors to discover any consistent changes of the microbiome across all the patients that responded to treatment.
Evidence: When Schwarzberg et al. compared the communities of the oral samples before and after treatment, they could not find a consistent difference, even when accounting for the treatments effectiveness. In fact they found the most similar samples were those from the same patient before and after treatment. Since there was no difference at the community level, they dug deeper into the data and examined specific genra that were known to be associated with periodontal disease (Griffen et al. 2012). They did find that Fusobacterium significantly correlated with pocket depth (a marker of disease progression) across all samples. They also did notice that Prevotella abundance tends to decrease when treatments are successful. While there are not consistent changes observed when treatment is effective, there is so much variability between patients that there is no separation of post and pre treatment communities when conduction principal coordinate analysis (PCoA plot). A PCoA plot is essentially a way of condensing all of the characteristics of community into two values, and x and y axis. This means that the closer the points are to each other, the more similar they are. This is the simplest PCoA, with only two axis’s, but in this study it was a three axis plot used. Since the points were all overlapping on the plot, and the only relationship that could be established was that a single patient’s oral microbiome before and after treatment were similar. This suggests that the personal oral microbiome may be different enough between individuals that it may be hiding any useful trends if we look at the microbiome as a whole. Additionally while there are general trends for successful treatment,mainly the changes in Fusobacterium and Prevotella discussed earlier, there are many patients who do not follow this trend. Which lead to the authors concluding that the changes of the microbiome were being hidden
My Questions: Schwarzberg et al. claims that those who had effective treatment for periodontal disease experienced a shift in microbiome back to a healthy state for the specific individual. Could this be tested either by a long term study where samples were taken before symptoms of periodontal disease were observed and then again after treatment? Patients tend to visit the same dentist for long periods of time. This is ideally suited for a long term study, especially since the sampling method required is just swabbing. So the easiest experiment would be for a single dental practice to swab patients every time they came in for a cleaning, and observe the shift in microbiomes, and compare this with data on periodontal disease for the patient. This kind of study would take many years to complete, and therefore may not be feasible without first showing that a return to a healthy microbiome is occurring after successful periodontal disease treatment in a model organism. The model organism would probably have to be dogs, since there is an issue with mice where it is impossible for them to acquire periodontal disease for the first year of their life, and constantly growing incisors can lead to issues (Struillou et al. 2010). With dogs you have the option of either conducting an experiment in the lab, or since they are kept as pets just do the same experiment outlined for humans except ask owner for permission when they visit the vet. The best way would be when pets are required to receive vaccinations. This experiment could be conducted over a much shorter period of time than the one on humans. Either way we would generate PCoA plot with 3 points from each patient, one before onset of periodontal disease, one at diagnosis, and one after successful treatment. If successful treatment results in a return to a normal microbiome for a patient we would expect the points for a patient before onset of disease and after successful treatment to be close to each other on the PCoA plot, and the point during the disease to be far away.
Further Reading: If you are interested in the microbiome as it relates to oral health there is an article, The oral microbiome – an update for oral healthcare professionals, from the British Dental Journal that does a good job of summarizing the current knowledge in a relatively easy to read scientific review paper. Additionally there was recently a study that showed that in mice models, diabetes favored periodontitis (Xiao et al. 2017). Here is the link for the press release, as well as the actual article.
- Buguliskis, P. J. (2017, July 13). Mouth Microbiome Altered by Diabetes Fosters Periodontitis. Retrieved October 28, 2017, from Link
- Eke, P. I., Dye, B. A., Wei, L., Slade, G. D., Thornton-Evans, G. O., Borgnakke, W. S & Genco, R. J. (2015). Update on prevalence of periodontitis in adults in the United States: NHANES 2009 to 2012. Journal of periodontology, 86(5), 611-622. DOI:10.1902/jop.2015.140520
- Griffen, A. L., Beall, C. J., Campbell, J. H., Firestone, N. D., Kumar, P. S., Yang, Z. K., … & Leys, E. J. (2012). Distinct and complex bacterial profiles in human periodontitis and health revealed by 16S pyrosequencing. The ISME journal, 6(6), 1176-1185. PMC3358035
- Gromadzki, S. (n.d.). Periodontal disease, Pyorrhea, Gum disease, Periodontitis, Bad breath, Halitosis. Retrieved November 02, 2017, from Link
- Kilian, M., Chapple, I. L. C., Hannig, M., Marsh, P. D., Meuric, V., Pedersen, A. M. L., … & Zaura, E. (2016). The oral microbiome–an update for oral healthcare professionals. British dental journal, 221(10), 657-666. DOI:10.1038/sj.bdj.2016.865
- Periodontal (Gum) Disease: Causes, Symptoms, and Treatments. (2013, September). Retrieved October 14, 2017, from Link
- Schwarzberg, K., Le, R., Bharti, B., Lindsay, S., Casaburi, G., Salvatore, F., … & Caporaso, J. G. (2014). The personal human oral microbiome obscures the effects of treatment on periodontal disease. PLoS One, 9(1), DOI: 10.1371/journal.pone.0086708
- Struillou, X., Boutigny, H., Soueidan, A., & Layrolle, P. (2010). Experimental animal models in periodontology: a review. The open dentistry journal, 4, 37. PMC2885595
- Teles, R., Teles, F., Frias‐Lopez, J., Paster, B., & Haffajee, A. (2013). Lessons learned and unlearned in periodontal microbiology. Periodontology 2000, 62(1), 95-162. PMC3912758
- Xiao, E., Mattos, M., Vieira, G. H. A., Chen, S., Corrêa, J. D., Wu, Y., … & Graves, D. T. (2017). Diabetes Enhances IL-17 Expression and Alters the Oral Microbiome to Increase Its Pathogenicity. Cell Host & Microbe, 22(1), 120-128. DOI: 10.1016/j.chom.2017.06.014