Abstract：
In addition to being the most prevalent form of neurodegeneration among the elderly, AD is a devastating multifactorial disease. Currently, treatments address only its symptoms. Several clinical studies have shown that the disease begins to manifest decades before the first symptoms appear, indicating that studying early changes is crucial to improving early diagnosis and discovering novel treatments. Our study used bioinformatics and systems biology to identify biomarkers in AD that could be used for diagnosis and prognosis. The procedure was performed on data from the GEO database, and GO and KEGG enrichment analysis were performed. Then, we set up a network of interactions between proteins. Several miRNA prediction tools including miRDB, miRWalk, and TargetScan were used. The ceRNA network led to the identification of eight mRNAs, four circRNAs, seven miRNAs, and seven lncRNAs. Multiple mechanisms, including the cell cycle and DNA replication, have been linked to the promotion of AD development by the ceRNA network. By using the ceRNA network, it should be possible to extract prospective biomarkers and therapeutic targets for the treatment of AD. It is possible that the processes involved in DNA cell cycle and the replication of DNA contribute to the development of Alzheimer\'s disease.
摘要：
除了是老年人中最普遍的神经变性形式，AD是一种破坏性的多因素疾病。目前,治疗仅解决其症状。一些临床研究表明，这种疾病在最初的症状出现之前几十年就开始显现，这表明研究早期变化对于改善早期诊断和发现新的治疗方法至关重要。我们的研究使用生物信息学和系统生物学来鉴定可用于诊断和预后的AD生物标志物。该程序是对GEO数据库中的数据执行的，并进行GO和KEGG富集分析。然后，我们建立了蛋白质之间相互作用的网络。几种miRNA预测工具，包括miRDB，miRWalk,使用TargetScan。ceRNA网络导致了8个mRNA的鉴定，四个circRNAs，七个miRNA，和七个lncRNAs。多种机制，包括细胞周期和DNA复制，已通过ceRNA网络促进AD的发展。通过使用ceRNA网络，应该有可能提取用于AD治疗的前瞻性生物标志物和治疗靶点。参与DNA细胞周期和DNA复制的过程可能有助于阿尔茨海默病的发展。
