Periodontitis, a formidable global health burden, is a common
chronic disease that destroys tooth-supporting tissues.
Biomarkers of the early phase of this progressive disease are of utmost importance for global health. In this context, saliva represents a non-invasive biosample. By using systems biology tools, we aimed to (1) identify an integrated interactome between
matrix metalloproteinase (
MMP)-REDOX/
nitric oxide (NO) and apoptosis upstream pathways of periodontal
inflammation, and (2) characterize the attendant topological network properties to uncover putative
biomarkers to be tested in saliva from patients with
periodontitis. Hence, we first generated a
protein-
protein network model of interactions ("BIOMARK" interactome) by using the STRING 10 database, a search tool for the retrieval of interacting genes/
proteins, with "Experiments" and "Databases" as input options and a confidence score of 0.400. Second, we determined the centrality values (closeness, stress, degree or connectivity, and betweenness) for the "BIOMARK" members by using the Cytoscape software. We found
Ubiquitin C (UBC), Jun proto-oncogene (JUN), and matrix metalloproteinase-14 (MMP14) as the most central hub- and non-hub-bottlenecks among the 211 genes/
proteins of the whole interactome. We conclude that UBC, JUN, and MMP14 are likely an optimal candidate group of host-derived
biomarkers, in combination with oral pathogenic bacteria-derived
proteins, for detecting
periodontitis at its early phase by using salivary samples from patients. These findings therefore have broader relevance for systems medicine in global health as well.