Chen Xing
National Center for Mathematics and Interdisciplinary Sciences, Chinese Academy of Sciences, Beijing, 100190, China.
Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190, China.
Sci Rep. 2015 Nov 18;5:16840. doi: 10.1038/srep16840.
Accumulating experimental studies have demonstrated important associations between alterations and dysregulations of lncRNAs and the development and progression of various complex human diseases. Developing effective computational models to integrate vast amount of heterogeneous biological data for the identification of potential disease-lncRNA associations has become a hot topic in the fields of human complex diseases and lncRNAs, which could benefit lncRNA biomarker detection for disease diagnosis, treatment, and prevention. Considering the limitations in previous computational methods, the model of KATZ measure for LncRNA-Disease Association prediction (KATZLDA) was developed to uncover potential lncRNA-disease associations by integrating known lncRNA-disease associations, lncRNA expression profiles, lncRNA functional similarity, disease semantic similarity, and Gaussian interaction profile kernel similarity. KATZLDA could work for diseases without known related lncRNAs and lncRNAs without known associated diseases. KATZLDA obtained reliable AUCs of 7175, 0.7886, 0.7719 in the local and global leave-one-out cross validation and 5-fold cross validation, respectively, significantly improving previous classical methods. Furthermore, case studies of colon, gastric, and renal cancer were implemented and 60% of top 10 predictions have been confirmed by recent biological experiments. It is anticipated that KATZLDA could be an important resource with potential values for biomedical researches.
越来越多的实验研究表明，lncRNAs的改变和失调与各种复杂人类疾病的发生和发展之间存在重要关联。开发有效的计算模型来整合大量异质生物数据以识别潜在的疾病-lncRNA关联，已成为人类复杂疾病和lncRNAs领域的一个热门话题，这可能有助于lncRNA生物标志物检测用于疾病诊断、治疗和预防。考虑到先前计算方法的局限性，开发了用于lncRNA-疾病关联预测的KATZ度量模型（KATZLDA），通过整合已知的lncRNA-疾病关联、lncRNA表达谱、lncRNA功能相似性、疾病语义相似性和高斯相互作用谱核相似性来揭示潜在的lncRNA-疾病关联。KATZLDA可用于没有已知相关lncRNAs的疾病和没有已知相关疾病的lncRNAs。KATZLDA在局部和全局留一法交叉验证以及5折交叉验证中分别获得了可靠的AUC值7175、0.7886、0.7719，显著优于先前的经典方法。此外，还对结肠癌、胃癌和肾癌进行了案例研究，前10个预测中有60%已被最近的生物学实验证实。预计KATZLDA可能成为具有生物医学研究潜在价值的重要资源。
