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中国东北汉族急性心肌梗死患者外周血中的差异基因表达谱

Differential gene expression profiles in peripheral blood in Northeast Chinese Han people with acute myocardial infarction.

作者信息

Fan Lin, Meng Heyu, Guo Xudong, Li Xiangdong, Meng Fanbo

机构信息

China-Japan Union Hospital, Jilin University, Jilin, China.

Medical College of Yanbian University, Yanji, China.

出版信息

Genet Mol Biol. 2018 Jan-Mar;41(1):59-66. doi: 10.1590/1678-4685-GMB-2017-0075.

Abstract

This study aimed to use gene chips to investigate differential gene expression profiles in the occurrence and development of acute myocardial infarction (AMI). The study included 12 AMI patients and 12 healthy individuals. Total mRNA of peripheral bloodwas extracted and reversed-transcribed to cDNA for microarray analysis. After establishing two pools with three subjects each (3 AMI patients and 3 healthy individuals), the remaining samples were used for RT-qPCR to confirm the microarray data. From the microarray results, seven genes were randomly selected for RT-qPCR. RT-qPCR results were analyzed by the 2-ΔΔCt method. Microarray analysis showed that 228 genes were up- regulated and 271 were down-regulated (p ≤ 0.05, |logFC| > 1). Gene ontology showed that these genes belong to 128 cellular components, 521 biological processes, and 151 molecular functions. KEGG pathway analysis showed that these genes are involved in 107 gene pathways. RT-qPCR results for the seven genes showed expression levels consistent with those obtained by microarray. Thus, microarray data could be used to select the pathogenic genes for AMI. Investigating the abnormal expression of these differentially expressed genes might suggest efficient strategies for the prevention, diagnosis, and treatment of AMI.

摘要

本研究旨在利用基因芯片研究急性心肌梗死(AMI)发生发展过程中的差异基因表达谱。该研究纳入了12例AMI患者和12名健康个体。提取外周血总mRNA并逆转录为cDNA用于微阵列分析。在建立了两个各包含三名受试者的样本池(3例AMI患者和3名健康个体)后,其余样本用于RT-qPCR以确认微阵列数据。从微阵列结果中随机选择7个基因进行RT-qPCR。RT-qPCR结果采用2-ΔΔCt法进行分析。微阵列分析显示,228个基因上调,271个基因下调(p≤0.05,|logFC|>1)。基因本体分析表明,这些基因属于128个细胞成分、521个生物学过程和151个分子功能。KEGG通路分析表明,这些基因参与107条基因通路。7个基因的RT-qPCR结果显示表达水平与微阵列结果一致。因此,微阵列数据可用于筛选AMI的致病基因。研究这些差异表达基因的异常表达可能为AMI的预防、诊断和治疗提供有效策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa8f/5901496/178a2ad5d77d/1415-4757-GMB-41-01-2017-0075-gf01.jpg

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