Personalized Approach to the Treatment of Generalized Periodontitis in the Prediction of Cardiovascular Complications Based on Salivary Proteomic Profiling.

Аннотация

One known modifiable risk factor for cardiovascular diseases (CVD) is chronic generalised periodontitis (CGP).
One interesting avenue in personalised medicine is the use of oral fluid biomarkers for non-invasive monitoring of concomitant
pathology.
Purpose of the research. To create and scientifically validate an algorithm for the early prediction of cardiovascular problems
in patients with concurrent pathology based on proteomic profiling of the oral fluid, as well as a customised treatment
for CGP.
Techniques. There were 140 participants in the research (65 patients with CGP and cardiovascular risk who got personalised
treatment made up the main group; 45 patients with CGP on conventional therapy made up the comparative group;
and 30 healthy persons made up the control group). A thorough biochemical, cardiological, and dental examination was
carried out. ELISA and LC-MS/MS mass spectrometry were used to assess the proteome profile of saliva (apolipoproteins
A1, B, E, and cytokines). LASSO regression and ROC analysis were used for statistical analysis in R and Python
environments.
Outcomes. For the first time, the idea of the “salivary lipoprotein signature of periodontitis” (ApoB/ApoA1 ratio in saliva
>1.3) was confirmed as an indicator of disturbance of systemic lipid homeostasis. Unfavourable outcomes were shown
to be independently predicted by the ApoE-ε4 isoform. A prognostic model (AUC >0.90) was created and included in the
“PerioCardio-Risk” program. In 75-85% of patients, the salivary profile returned to normal and the periodontal pocket
depth was reduced by 25-35% thanks to personalised treatment.
In conclusion. It is possible to optimise CGP therapy and anticipate cardiovascular risks two to five years before they
appear clinically by including salivary proteome profiling into an interdisciplinary strategy