title: Relationship between human periodontitis and type 2 diabetes at a genomic level: a data-mining study.
abstract: BACKGROUND
  The leader gene approach is a data-mining method based on the systematic search for the genes involved in a specific process and their ranking according to the interconnections with the other genes identified. The application of this algorithm to human periodontitis gave promising results. The present study used this algorithm to formulate new hypotheses about the association between periodontitis and type 2 diabetes.
  
  
  METHODS
  The genes involved in a given process were identified via interrelated queries of several databases. The interactions among such genes were mapped and given a significance score. The weighted number of links (sum of weighted scores for every interaction in which a gene is involved) was calculated for each gene. Genes were clustered according to this parameter; those in the highest cluster were termed leader genes. This algorithm was applied to diabetes and sinusitis. Sinusitis was chosen as a control because it is an inflammatory infectious disease like periodontitis. The results were compared to those previously calculated for periodontitis.
  
  
  RESULTS
  Periodontitis and diabetes share four leader genes; all leader genes are linked in a complex map of interactions. Periodontitis and sinusitis share no leader genes; no interactions were identified.
  
  
  CONCLUSIONS
  Even with the limitations of ab initio analyses, these theoretical results might suggest the existence of some common genomic pathways between periodontitis and type 2 diabetes, despite the different pathogenesis of these diseases. In particular, the shared leader genes could have an important role in this relationship, which may be investigated further with targeted experimentation.
authors: Tirrenian Stomatologic Institute, Lido di Camaiore, Lucca, Italy.
authors: Ugo
authors: U
authors: Covani
authors: Simone
authors: S
authors: Marconcini
authors: Giacomo
authors: G
authors: Derchi
authors: Antonio
authors: A
authors: Barone
authors: Luca
authors: L
authors: Giacomelli
mesh_terms: D000465:Algorithms; D002874:Chromosome Mapping; D019295:Computational Biology; D030541:Databases, Genetic; D003924:Diabetes Mellitus, Type 2 / Q000235:genetics*; D051380:GRB2 Adaptor Protein / Q000235:genetics; D005786:Gene Expression Regulation / Q000235:genetics; D008040:Genetic Linkage / Q000235:genetics; D015894:Genome, Human / Q000235:genetics*; D006801:Humans; D016247:Information Storage and Retrieval; D005810:Multigene Family / Q000235:genetics; D052002:NF-kappa B p50 Subunit / Q000235:genetics; D010518:Periodontitis / Q000235:genetics*; D019869:Phosphatidylinositol 3-Kinases / Q000235:genetics; D050721:Proto-Oncogene Proteins c-cbl / Q000235:genetics; D012852:Sinusitis / Q000235:genetics; D051996:Transcription Factor RelA / Q000235:genetics
chemical_list: D051380:GRB2 Adaptor Protein; D052002:NF-kappa B p50 Subunit; C489548:NFKB1 protein, human; C498143:RELA protein, human; D051996:Transcription Factor RelA; D050721:Proto-Oncogene Proteins c-cbl; D019869:Phosphatidylinositol 3-Kinases; C067419:CBL protein, human