Biologically informed stratification of periodontal disease holds the key to achieving precision oral health

Abstract

Medicine and dentistry need to treat the individual not the "average patient." This personalized or precision approach to health care involves correctly diagnosing and properly classifying people to effectively customize prevention, diagnosis, and treatment. This is not a trivial undertaking. Achieving precision health requires making sense of big data, both at the population level and at the molecular level. The latter can include genetic, epigenetic, transcriptomic, proteomic, metabolomic data, and microbiome data. This biological information can augment established clinical measurements and supplement data on socioeconomic status, lifestyle, behaviors, and environmental conditions. Here, the central thesis is that, with sufficient data and appropriate methods, it is possible to segregate symptom-based and phenotypically based categories of patients into clinically and biologically similar groups. These groups are likely to have different clinical trajectories and benefit from different treatments. Additionally, such groups are optimal for investigations seeking to unveil the genomic basis of periodontal disease susceptibility. Analysis of these complex data to produce actionable and replicable health and disease categories requires appropriately sophisticated bioinformatics approaches and thorough validation in diverse patient samples and populations. Successful research programs will need to consider both population-level and well-controlled deep phenotyping approaches. Biologically informed stratification of periodontal disease is both feasible and desirable. Ultimately, this approach can accelerate the development of precision health through improvements in research and clinical applications.

Keywords: GWAS; genomics; periodontal disease; precision medicine; risk assessment.