利用网络医学鉴定阿尔茨海默病和糖尿病的MicroRNA药物靶点。

Ricardo Castillo-Velázquez, Julio E Castañeda-Delgado, Mariana H García-Hernández, Bruno Rivas-Santiago, Sofia Ruiz-Hernández, Eyra Liliana Ortiz-Pérez, Juan C López-Alvarenga, Gildardo Rivera, Edgar E Lara-Ramírez
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引用次数: 0

摘要

2型糖尿病(T2D)是发展为阿尔茨海默病(AD)的已知危险因素。最近的研究表明,这两种疾病具有复杂而相关的病理生理过程。网络医学方法可以帮助阐明不同疾病之间常见的失调过程,如AD和T2D。因此,这项工作的目的是确定AD和T2D中的差异表达基因(DEGs),并应用网络医学方法来鉴定参与AD-T2D关联的microrna (miRNAs)。方法:对384份对照样本和399份AD和T2D疾病样本的基因表达芯片数据集进行分析,获得两种疾病共有的基因表达基因;使用网络医学方法预测与这些deg相关的mirna。最后,确定了靶向这些可能失调的mirna的潜在小分子。结果:AD和T2D共享82个下调deg的一小部分。这些基因与化学突触失调的本体相关(p < 0.01)。deg与AD和T2D特定组织中表达的12种mirna相关。这些mirna也主要与突触解除管制和癌症相关的本体术语以及AKT信号通路相关。类固醇抗炎药、抗肿瘤药物和葡萄糖代谢物被预测为12种共享mirna的潜在调节因子。讨论:整合DEGs和mirna的网络医学方法能够识别AD和T2D病理生理基础的共享的、潜在的不受调节的生物过程和途径。这些共同的分子机制也与目前临床实践中使用的药物有关,这表明这一策略可能为未来的药物再利用工作提供信息。然而,需要进一步深入的生物学验证来证实这些发现。结论:网络医学可以识别出12种参与AD-T2D关联的mirna,这些mirna可以作为设计新疗法的药物靶点;然而,已鉴定的mirna需要进一步的实验证实。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identification of MicroRNA Drug Targets for Alzheimer's and Diabetes Mellitus Using Network Medicine.

Introduction: Type 2 diabetes mellitus (T2D) is a known risk factor for developing Alzheimer's disease (AD). Recent research shows that both diseases share complex and related pathophysiological processes. Network medicine approaches can help to elucidate common dysregulated processes among different diseases, such as AD and T2D. Thus, the aim of this work was to determine differentially expressed genes (DEGs) in AD and T2D and to apply a network medicine approach to identify the microRNAs (miRNAs) involved in the AD-T2D association.

Methods: Gene expression microarray data sets consisting of 384 control samples and 399 samples belonging to AD and T2D disease were analyzed to obtain DEGs shared by both diseases; the miRNAs associated with these DEGs were predicted using a network medicine approach. Finally, potential small molecules targeting these potentially deregulated miRNAs were identified.

Results: AD and T2D shared a small subset of 82 downregulated DEGs. These genes were significantly associated (p < 0.01) with the ontology terms of chemical synaptic deregulation. DEGs were associated with 12 miRNAs expressed in specific tissues for AD and T2D. Such miRNAs were also primarily associated with the ontology terms related to synaptic deregulation and cancer, and AKT signaling pathways. Steroid anti-inflammatory drugs, antineoplastics, and glucose metabolites were predicted to be potential regulators of the 12 shared miRNAs.

Discussion: The network medicine approach integrating DEGs and miRNAs enabled the identification of shared, potentially deregulated biological processes and pathways underlying the pathophysiology of AD and T2D. These common molecular mechanisms were also linked to drugs currently used in clinical practice, suggesting that this strategy may inform future drug repurposing efforts. Nonetheless, further in-depth biological validation is required to confirm these findings.

Conclusion: Network medicine allowed identifying 12 miRNAs involved in the AD-T2D association, and these could be drug targets for the design of new treatments; however, the identified miRNAs need further experimental confirmation.

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