Aida Kusiak

Periodontitis is an inflammatory condition affecting the supporting structures of the teeth. Periodontal conditions may increase the susceptibility of individuals to various systemic illnesses, including Alzheimer’s disease. Alzheimer’s disease is a neurodegenerative condition characterized by a gradual onset and progressive deterioration, making it the primary cause of dementia, although the exact cause of the disease remains elusive. Both Alzheimer’s disease and periodontitis share risk factors and clinical studies comparing the associations and occurrence of periodontitis among individuals with Alzheimer’s disease have suggested a potential correlation between these conditions. Brains of individuals with Alzheimer’s disease have substantiated the existence of microorganisms related to periodontitis, especially Porphyromonas gingivalis, which produces neurotoxic gingipains and may present the capability to breach the blood–brain barrier. Treponema denticola may induce tau hyperphosphorylation and lead to neuronal apoptosis. Lipopolysaccharides—components of bacterial cell membranes and mediators of inflammation—also have an impact on brain function. Further research could unveil therapeutic approaches targeting periodontal pathogens to potentially alleviate AD progression.

(1) Background: Periodontitis is an inflammatory condition that affects the tissues surrounding the tooth and causes clinical attachment loss, which is the loss of periodontal attachment (CAL). Periodontitis can advance in various ways, with some patients experiencing severe periodontitis in a short period of time while others may experience mild periodontitis for the rest of their lives. In this study, we have used an alternative methodology to conventional statistics, self-organizing maps (SOM), to group the clinical profiles of patients with periodontitis. (2) Methods: To predict the periodontitis progression and to choose the best treatment plan, we can use artificial intelligence, more precisely Kohonen’s self-organizing maps (SOM). In this study, 110 patients, both genders, between the ages of 30 and 60, were included in this retrospective analysis. (3) Results: To discover the pattern of patients according to the periodontitis grade and stage, we grouped the neurons together to form three clusters: Group 1 was made up of neurons 12 and 16 that represented a percentage of slow progression of almost 75%; Group 2 was made up of neurons 3, 4, 6, 7, 11, and 14 in which the percentage of moderate progression was almost 65%; and Group 3 was made up of neurons 1, 2, 5, 8, 9, 10, 13, and 15 that represented a percentage of rapid progression of almost 60%. There were statistically significant differences in the approximate plaque index (API), and bleeding on probing (BoP) versus groups (p < 0.0001). The post-hoc tests showed that API, BoP, pocket depth (PD), and CAL values were significantly lower in Group 1 relative to Group 2 (p < 0.05) and Group 3 (p < 0.05). A detailed statistical analysis showed that the PD value was significantly lower in Group 1 relative to Group 2 (p = 0.0001). Furthermore, the PD was significantly higher in Group 3 relative to Group 2 (p = 0.0068). There was a statistically significant CAL difference between Group 1 relative to Group 2 (p = 0.0370). (4) Conclusions: Self-organizing maps, in contrast to conventional statistics, allow us to view the issue of periodontitis advancement by illuminating how the variables are organized in one or the other of the various suppositions.