Bioinformatic Prediction of Leader Genes in Human Periodontitis
Bioinformatic Prediction of Leader Genes in Human Periodontitis
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DOI：
10.1902/jop.2008.080062
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发表时间：
2008-10-01
影响因子：
4.3
通讯作者：
Nicolini, Claudio
中科院分区：
文献类型：
--
作者：
Covani, Ugo;Marconcini, Simone;Nicolini, Claudio
背景：参与不同生物过程的基因形成复杂的相互作用网络。然而，只有少数基因与网络中的其他基因有大量的相互作用。在先前关于T淋巴细胞细胞周期的生物信息学和实验研究中，这些基因被识别并命名为“领导基因”。在这项工作中，我们对人类牙周炎相关基因进行了初步鉴定，并根据它们相互作用的次数进行了排序，以期对牙周炎的分子机制有一个初步的、更广泛的认识，并计划有针对性的实验。对这些基因之间的相互作用进行了定位，并给出了显著性评分。计算每个基因的加权链数(涉及给定基因的每个交互作用的加权分数和)。根据这一参数对基因进行聚类。结果：共鉴定出61个与牙周炎相关或潜在参与牙周炎的基因。只有5个基因被确定为领导基因，而其他12个基因被排在紧随其后的聚类中。对于17个基因中的10个，有证据表明与牙周炎有关；发现了7个可能与这种疾病有关的新基因。仅有两个主要基因与牙周炎有关。结论：我们应用了一种有效的生物信息学算法来增加我们对牙周炎分子机制的了解。即使有从头分析的局限性，这项理论研究也可以提出针对重要基因的特别实验，因此，比大规模分子基因组学更简单。此外，先导基因的识别可能会提示新的潜在危险因素和治疗靶点。J Perodontol 2008；79：1974-1983。
Background: Genes involved in different biologic processes form complex interaction networks. However, only a few have a high number of interactions with the other genes in the network. In previous bioinformatics and experimental studies concerning the T lymphocyte cell cycle, these genes were identified and termed "leader genes." In this work, genes involved in human periodontitis were tentatively identified and ranked according to their number of interactions to obtain a preliminary, broader view of molecular mechanisms of periodontitis and plan targeted experimentation.Methods: Genes were identified with interrelated queries of several databases. The interactions among these genes were mapped and given a significance score. The weighted number of links (weighted sum of scores for every interaction in which the given gene is involved) was calculated for each gene. Genes were clustered according to this parameter. The genes in the highest cluster were termed leader genes.Results: Sixty-one genes involved or potentially involved in periodontitis were identified. Only five were identified as leader genes, whereas 12 others were ranked in an immediately lower cluster. For 10 of 17 genes there is evidence of involvement in periodontitis; seven new genes that are potentially involved in this disease were identified. The involvement in periodontitis has been completely established for only two leader genes.Conclusions: We applied a validated bioinformatics algorithm to increase our knowledge of molecular mechanisms of periodontitis. Even with the limitations of this ab initio analysis, this theoretical study can suggest ad hoc experimentation targeted on significant genes and, therefore, simpler than mass-scale molecular genomics. Moreover, the identification of leader genes might suggest new potential risk factors and therapeutic targets. J Periodontol 2008;79:1974-1983.