Prediktiva biomarkörer för karies och parodontit
- Julia Davies
- Malmö University
- The Knowledge Foundation
- Ansvarig vid Mau:
- Julia Davies
- Torbjörn Bengtsson - Örebro University
- Hazem Khalaf - Örebro University
- Rolf Lood - Lund University
- Johanna Lönn - Örebro University
- Eleonor Palm - Örebro University
- 01 september 2018 - 31 augusti 2023
The Foresight “Discovery” group includes researchers in microbiology, oral ecology, cell biology and inflammation. Our project focuses on discovery of predictive biomarkers and preventive biotherapeutics for oral disease. Previous attempts to exploit the presence of specific microorganisms in oral biofilms or individual components of the inflammatory response as predictive biomarkers for caries and periodontitis have been unsuccessful.
The novel idea behind this project is that phenotypes in biofilms or specific molecules associated with them, in combination with specific molecules involved in the host response to the same biofilms, can be used as biomarkers to predict onset of disease. Foresight follows a well-established biomarker ‘pipeline principle’ for the clinical utility of new predictive biomarkers for risk assessment. The first part is a broad, semi-quantitative discovery phase where a panel of candidate biomarkers derived from microbe-host models will be identified.
The project addresses two research questions:
- How can virulence expression in, and host responses to, dysbiotic biofilms be utilized as a platform for targeted strategies to predict oral disease?
- How can predictive biomarkers be targeted to prevent oral disease?
1. Identifying predictive biomarkers for periodontitis
Developing microbial biofilms in the gingival pocket induce inflammation in the adjacent host tissues that, in turn, drives a change in biofilm phenotype. Dysbiotic and proteolytic biofilms are an important factor in disease progression. We therefore propose that proteolytic activity per se and an array of proteolytic enzymes in the gingival pocket could be utilized as biomarkers for prediction of bone loss in periodontitis.
2. Identifying predictive biomarkers for caries
Mutans streptococci is a poor predictor of risk for caries development since these bacteria are found in people without the disease and caries can develop in individuals who lack these bacteria. Our approach is based on the ecological plaque hypothesis, which proposes that caries arises due to dysbiosis in biofilms on teeth, with enrichment of acid-tolerating phenotypes and a low-pH environment, due to frequent exposure to fermentable carbohydrates. We propose that levels of acid-tolerant bacteria and specific proteins associated with acid-adaptation in the biofilm could be used as biomarkers to predict risk for development of caries.
3. Identifying targeted biotherapeutics against biomarkers
Discovery of biomarkers to predict the onset of disease could be considered unethical without, in parallel, searching for ways to intervene in the pathogenic process. Our vision is that identification of biomarkers that are key players in oral disease processes will open up the possibility for development of new biotherapeutics that act directly on the biomarkers themselves to intervene in disease progression.