Gene Clustering Analysis in Human Osseous Remodeling.

Background: Tentative bioinformatic predictions were performed to comprehend the complexity of the gene interaction networks of the T lymphocyte cell cycle and of human periodontitis. This study aims to identify and rank genes involved in osseous augmentation or bone remodeling to obtain groups with more numerous predicted associations called the leader gene clusters. Methods: An iterative search (consisting of a consecutive expansion-filtering loop) was performed for which only genes involved in a specific process were identified. For each gene, predicted associations with all other involved genes were obtained from a Web-available database (Search Tool for the Retrieval of Interacting Genes/Proteins) and the weighted number of links (WNL), given by the sum of only high-confidence predicted associations (results with a score ≥0.9), allowing gene ranking. Genes belonging to higher clustering classes were identified. Results: A total of 161 genes potentially involved in bone-volume augmentation and 128 genes connected with the bone-remodeling phenomenon were identified. For the bone-volume augmentation process, only one gene belonged to the leader gene group, whereas six other genes were classified as cluster B genes; for the bone-remodeling phenomenon, three leader genes were identified, whereas six other genes formed the cluster B group. No one gene belonged to leader gene clusters of both processes, whereas one gene of each higher cluster group belonged to the immediately lower cluster of the opposite process. Only three genes of the higher clusters were experimentally involved in both analyses. Conclusions: A de nova identification was performed based on the data mining of leader genes involved in bone-volume augmentation or bone remodeling to acquire primeval information about their molecular basis and to plan future ad hoc targeted experiments. For several genes of the upper clusters, an active role in the bone processes was already known, but the present analysis suggested that they play a major role in the analyzed phenomena. The role of the transcription factors as leader genes and the numerous orphan genes (genes with WNL = 0) recovered probably attest to a lack of information regarding these processes, which could be further clarified through specific DNA microarray experiments. [ABSTRACT FROM AUTHOR]