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A deeper understanding of periodontitis pathophysiology is central to future development of novel biomarkers and therapeutics. The following is reported here: 1) an in silico network model of interactions among cell adhesion molecules and a network-focused microarray analysis of the corresponding genes in periodontitis; 2) analysis of secretions of adhesion molecules in gingival tissue samples from patients with periodontitis and healthy controls; and 3) effect of the human neutrophilic peptide-1 (HNP-1) on epithelial adhesion molecules.The network model identified 85 nodes in relation to the interactions of adhesion molecules. Subsequently, the relative gene expression was overlaid on the network model. Differential gene expression was analyzed, and false discovery rate control was performed for statistical assessment of the microarray data. Both tissue and cell culture samples were immunostained for desmocollin (DSC)2, occludin (OCLN), desmoglein (DSG)1, tight junction protein 2, and gap junction protein α.The differential gene expression analysis revealed that the epithelial adhesion molecules were significantly lower in abundance in individuals with periodontitis than controls. In contrast, the genes for leukocyte adhesion molecules showed a significant upregulation. Immunostainings revealed elevated secretions of both DSG1 and OCLN in periodontitis. An in vitro model suggested reduced DSC2 and OCLN secretions in the presence of HNP-1.Gene expression of gingival adhesion molecules in periodontitis is regulated by leukocyte transmigration, whereas the neutrophilic antimicrobial peptide HNP-1 is noted as a putative regulator of epithelial adhesion molecules. These observations contribute to the key mechanisms by which future biomarkers might be developed for periodontitis.