Ma Xiao-Lin, Yang Xu, Fan Rui
Department of Cardiology, The People's Hospital of Xuancheng City, Xuancheng, Anhui 242000, P.R. China.
Department of Cardiovascular Disease, The Second People's Hospital of Yunnan Province, Kunming, Yunnan 650021, P.R. China.
Exp Ther Med. 2019 Mar;17(3):2129-2136. doi: 10.3892/etm.2019.7195. Epub 2019 Jan 22.
Coronary artery disease (CAD) is a leading cause of death, and microRNAs (miRNAs) are widely involved in physiological and pathological processes of CAD. We chose the targetscore method calculated via the variational Bayesian Gaussian mixture model (VB-GMM) as the prediction method of target genes. By observing the density overlap, we selected the thresholds of miRNA-1 and miRNA-155. In total, 18 target genes of miRNA-1, and 19 target genes of miRNA-155 were identified. The threshold of miRNA-146a was selected using the |logFC| value, and 16 target genes were screened out. In this study, our major contribution was to predict the target messenger RNAs (mRNAs) of the chosen miRNAs with the gene expression profiles, which can effectively reduce the workload of screening. Although the validated genes constituted only a small part in the final prediction results, it is a good sign for research in the future. It means that we could provide new research aims for future studies focusing on miRNA regulatory mechanisms.
冠状动脉疾病（CAD）是主要的死亡原因之一，而微小RNA（miRNA）广泛参与CAD的生理和病理过程。我们选择通过变分贝叶斯高斯混合模型（VB-GMM）计算的目标得分方法作为目标基因的预测方法。通过观察密度重叠，我们选择了miRNA-1和miRNA-155的阈值。总共鉴定出18个miRNA-1的目标基因和19个miRNA-155的目标基因。使用|logFC|值选择miRNA-146a的阈值，并筛选出16个目标基因。在本研究中，我们的主要贡献是利用基因表达谱预测所选miRNA的靶信使核糖核酸（mRNA），这可以有效减少筛选工作量。虽然验证的基因在最终预测结果中只占一小部分，但这对未来研究来说是个好迹象。这意味着我们可以为未来专注于miRNA调控机制的研究提供新的研究目标。
