基于功能一致性和网络拓扑属性预测冠心病致病基因

基于功能一致性利用蛋白质互作网络挖掘潜在的疾病致病基因，对于了解疾病致病机理和改进临床治疗至关重要．基于基因功能一致性和其在蛋白质互作网络中的拓扑属性将基因与疾病之间建立关联，对疾病风险位点内的基因进行了致病风险预测，并通过GO及KEGG功能富集分析方法进一步筛选，预测出新的致病基因．预测出了51个新的冠心病致病基因，分析发现大部分基因参与了冠心病的致病过程．为疾病基因的挖掘提出一个新的思路，从而有助于复杂疾病致病机理的研究．

Predicting disease genes of coronary artery disease based on functional consistency and network topological features

The identification of genes responsible for human diseases based on functional consistency and network topological features is of great importance for both understanding human disease pathogenesis and improving clinical practice. A novel method based on the functional consistency and network topological features was introduced to establish an association between genes and diseases. Using this method, candidate disease genes were predicted from disease risk loci. Then, the candidate genes sharing the same or similar functions with known disease genes in the functional enrichment analysis of GeneOntology and KEGG databases as final disease genes were determined. 51 genes were predicted to be the disease genes for coronary artery disease and most of them participate in the development of disease by literature retrieval. The method provided additional insights for the finding disease genes, which will be helpful for the studies on the pathogenesis of human complex diseases.