Kidney transplantation is an optimal method for treatment of end-stage kidney failure. However, kidney transplant rejection (KTR) is commonly observed to have negative effects on allograft function. MicroRNAs (miRNAs) are small non-coding RNAs with regulatory role in KTR genesis, the identification of miRNA biomarkers for accurate diagnosis and subtyping of KTR is therefore of clinical significance for active intervention and personalized therapy. In this study, an integrative bioinformatics model was developed based on multi-omics network characterization for miRNA biomarker discovery in KTR. Compared with existed methods, the topological importance of miRNA targets was prioritized based on cross-level miRNA-mRNA and protein–protein interaction network analyses. The biomarker potential of identified miRNAs was computationally validated and explored by receiver-operating characteristic (ROC) evaluation and integrated “miRNA-gene-pathway” pathogenic survey. Three miRNAs, i.e., miR-145-5p, miR-155-5p, and miR-23b-3p, were screened as putative biomarkers for KTR monitoring. Among them, miR-155-5p was a previously reported signature in KTR, whereas the remaining two were novel candidates both for KTR diagnosis and subtyping. The ROC analysis convinced the power of identified miRNAs as single and combined biomarkers for KTR prediction in kidney tissue and blood samples. Functional analyses, including the latent crosstalk among HLA-related genes, immune signaling pathways and identified miRNAs, provided new insights of these miRNAs in KTR pathogenesis. A network-based bioinformatics approach was proposed and applied to identify candidate miRNA biomarkers for KTR study. Biological and clinical validations are further needed for translational applications of the findings.

中文翻译：

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多组学网络表征揭示了新的 microRNA 生物标志物以及肾移植排斥诊断和亚型分型的机制


肾移植是治疗终末期肾衰竭的最佳方法。然而，通常观察到肾移植排斥（KTR）对同种异体移植物功能产生负面影响。 MicroRNA (miRNA) 是在 KTR 发生中具有调节作用的小非编码 RNA，因此鉴定 miRNA 生物标志物以准确诊断 KTR 和进行亚型分型对于积极干预和个性化治疗具有临床意义。在这项研究中，基于多组学网络表征开发了一个综合生物信息学模型，用于 KTR 中 miRNA 生物标志物的发现。与现有方法相比，基于跨水平 miRNA-mRNA 和蛋白质-蛋白质相互作用网络分析，优先考虑 miRNA 靶标的拓扑重要性。通过接受者操作特征（ROC）评估和综合“miRNA-基因-通路”致病性调查，对已识别的 miRNA 的生物标志物潜力进行了计算验证和探索。筛选出三种 miRNA，即 miR-145-5p、miR-155-5p 和 miR-23b-3p，作为 KTR 监测的假定生物标志物。其中，miR-155-5p是先前报道的KTR中的特征，而其余两个是KTR诊断和亚型分型的新候选者。 ROC 分析证实了鉴定的 miRNA 作为肾组织和血液样本中 KTR 预测的单一和组合生物标志物的能力。功能分析，包括 HLA 相关基因、免疫信号通路和已鉴定的 miRNA 之间的潜在串扰，为这些 miRNA 在 KTR 发病机制中提供了新的见解。提出并应用基于网络的生物信息学方法来识别 KTR 研究的候选 miRNA 生物标志物。研究结果的转化应用还需要进一步的生物学和临床验证。