Department of Cardiology, Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University, Guangzhou, China.
Department of Cardiology, The Eighth Affiliated Hospital of Sun Yat-Sen University, Shenzhen, Guangdong, China.
Aging (Albany NY). 2021 Mar 5;13(6):8944-8959. doi: 10.18632/aging.202713.
Currently, the role of lncRNA in myocardial infarction (MI) is poorly understood. 17 co-expression modules were determined, specifically, the greenyellow, saddlebrown, grey60, royalblue, lightgreen, white, and pink modules were specifically expressed in the acute phase of MI, and brown, darkred, and royalblue, while greenyellow modules were specifically expressed in MI compared with CAD. 12 time-dependent of lncRNA/mRNA clusters with consistent expression trends were also identified. MI-associated modules were mainly enriched to immune, cell cycle, and metabolic pathways. We further obtained a network of 1816 lncRNA-mRNAs with higher expression correlations among these lncRNAs by analyzing the topological properties of the network. Herein, lncRNA RP11-847H18.2 and KLHL28, SPRTN, and EPM2AIP1 were determined as gene markers specifically expressed in MI, and they demonstrated a high predictive performance for MI diagnosis and prognosis. Three drugs, namely, Calcium citrate, Calcium Phosphate, and Calcium phosphate dihydrate, were identified as potential precursors of MI. Finally, gene and lncRNA diagnostic models were developed based on these genes and lncRNAs, with their AUCs averaged above 0.89 in both training and validation datasets. The findings of this study improve the diagnosis and prognosis of MI and personalized treatment of MI.
目前，lncRNA 在心肌梗死（MI）中的作用尚不清楚。确定了 17 个共表达模块，具体来说，绿色黄色、马鞍棕色、灰色 60、皇家蓝色、浅绿色、白色和粉红色模块在 MI 的急性期特异性表达，而棕色、暗红色和皇家蓝色模块在 MI 中与 CAD 特异性表达。还确定了 12 个具有一致表达趋势的时间依赖性 lncRNA/mRNA 聚类。与 MI 相关的模块主要富集到免疫、细胞周期和代谢途径。通过分析网络的拓扑特性，我们进一步获得了一个由 1816 个 lncRNA-mRNA 组成的网络，这些 lncRNA 之间的表达相关性较高。在此，确定了 lncRNA RP11-847H18.2 和 KLHL28、SPRTN 和 EPM2AIP1 作为 MI 特异性表达的基因标记，它们对 MI 诊断和预后具有较高的预测性能。鉴定出三种药物，即柠檬酸钙、磷酸钙和磷酸二氢钙，可能是 MI 的潜在前体。最后，基于这些基因和 lncRNA 开发了基因和 lncRNA 诊断模型，在训练和验证数据集中的 AUC 平均值均高于 0.89。这项研究的结果改善了 MI 的诊断和预后以及 MI 的个性化治疗。
