阿尔茨海默病小鼠脑组织长链非编码RNA与信使RNA表达谱及调控网络的分析

目的 分析阿尔茨海默病（AD）小鼠脑组织长链非编码RNA（LncRNA）和信使RNA（mRNA）表达谱,构建竞争内源性RNA（ceRNA）调控网络,探讨差异表达LncRNA在AD发病机制中的潜在作用。方法 选取3只10月龄雄性APP/PS1转基因小鼠作为AD组,3只年龄及体质量相匹配的普通C57小鼠作为对照组。使用基因芯片技术检测2组小鼠脑组织LncRNA和mRNA的表达,筛选出差异表达的LncRNA和mRNA。对部分差异表达的LncRNA进行实时定量聚合酶链反应（qRT-PCR）。对差异表达的mRNA进行基因本体论（GO）和京都基因、基因组百科全书（KEGG）通路分析。随机挑选6个差异表达LncRNA构建ceRNA网络,进行AD的靶基因功能预测分析。结果 与对照组相比,AD组小鼠脑组织差异表达1.5倍以上的LncRNA有933个,其中上调222个,下调711个;差异表达1.5倍以上的mRNA有529个,其中上调189个,下调340个。qRT-PCR检测结果显示,AD组与对照组比较,7个差异表达的LncRNA上调或下调趋势与基因芯片结果一致,差异均有统计学意义（P值均<0.05）。GO和KEGG通路分析结果显示,差异表达基因主要参与氨基酸代谢、炎症反应和免疫反应。ceRNA调控网络靶基因的功能富集分析显示,LncRNA在胰岛素抵抗以及糖尿病并发症中的AGE-RAGE信号通路中显著富集。结论 AD小鼠脑组织LncRNA表达谱发生显著变化,由LncRNA Dgkb、Svip等构建的ceRNA调控网络有助于增进对AD发病分子机制的研究,差异表达的LncRNA或通路有可能成为潜在的治疗靶点。

Analysis of LncRNA and mRNA expression profiles and regulatory network in the brain tissue of a mouse model with Alzheimer's disease

Objective This study aims to investigate the expression profiles of long non-coding RNA(LncRNA) and messenger RNA (mRNA) in the brain tissue of a mouse model with Alzheimer's disease (AD), construct a regulatory network of competing endogenous RNA(ceRNA), and analyze the potential role of differentially expressed LncRNA in the pathogenesis of AD. Methods Three 10-month-old male APP/PS1 transgenic mice were selected as AD group, and three ordinary C57 mice matched for age and body weight were selected as control group. The expression levels of LncRNA and mRNA in the brain tissues of the two groups were detected by gene chip technology, and differentially expressed LncRNA and mRNA were screened. Real-time quantitative polymerase chain reaction (qRT-PCR) was performed on differentially expressed LncRNAs to verify the reliability of the gene chip results. Differentially expressed mRNAs were evaluated by Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway analyses. Six differentially expressed LncRNAs were selected to construct the ceRNA network and predict the function of target genes. Results Compared with the control group, 933 LncRNAs were differentially expressed by more than 1.5 times in the AD group, 222 of which were up-regulated and 711 were down-regulated. A total of 529 mRNAs were differentially expressed by more than 1.5 times, of which 189 were up-regulated and 340 were down-regulated. The results of qRT-PCR showed that the up-or down-regulation trend of 7 differentially expressed LncRNAs was consistent with the gene chip results, and the differences were statistically significant (all P values <0.05). The GO and KEGG pathway analysis showed that the differentially expressed genes were mainly involved in amino acid metabolism, inflammation response, and immune response. Functional enrichment analysis of the ceRNA regulatory network target genes showed that LncRNA was significantly enriched in insulin resistance and AGE-RAGE signaling pathways in diabetic complications. Conclusion The expression profiles of LncRNAs in the brain tissue of APP/PS1 mice significantly changed. The ceRNA regulatory network constructed by LncRNA Dgkb and Svip can enhance research on the molecular mechanism of AD pathogenesis, and differentially expressed LncRNAs or pathways may become potential therapeutic targets.