Novel candidate genes for atherosclerosis are identified by representational difference analysis-based transcript profiling of cholesterol-loaded macrophages

被引:13
作者
Andersson, T
Boräng, S
Larsson, M
Wirta, V
Wennborg, A
Lundeberg, J
Odeberg, J [1 ]
机构
[1] Royal Inst Technol, KTH, Stockholm Ctr Phys Astron & Biotechnol, Dept Biotechnol,Ctr Mol Biotechnol, SE-10691 Stockholm, Sweden
[2] Karolinska Inst, Novum, Dept Biosci, Huddinge, Sweden
关键词
gene expression; subtraction; virtual chip; atherosclerosis; representational difference analysis; oxidized low-density lipoprotein; THP-1; foam cell; macrophage; transcript profiling;
D O I
10.1159/000064637
中图分类号
Q2 [细胞生物学];
学科分类号
071009 ; 090102 ;
摘要
Objectives: To analyze the early gene expression in macrophages accompanying the phenotypic changes into foam cells upon exposure to oxidized low-density lipoprotein. To identify candidate genes and markers for further studies into the pathogenesis of atherosclerosis. Methods: Cells of the monocytic cell line THP-1 were activated by PMA and exposed to oxidized low-density lipoprotein. Gene expression profiles were investigated after 24 h, using a solid phase cDNA representational difference analysis (RDA) method and shotgun sequencing. Results were verified by microarray hybridization, and analyzed in the virtual chip display of a novel software tool for transcript profile exploration. Results: By comparing transcript profiles of exposed/unexposed cells, 1,984 transcript sequences, representing a total of 921 genes with altered expression levels in response to oxidized low-density lipoprotein exposure, were identified. Genes that are central to cell cycle control and proliferation, inflammatory response, and of pathways not previously implicated in atherosclerosis were identified. The data obtained is also made available on-line at http:// biobase.biotech.kth.se/thp1a for further exploration. Conclusion: The identification of new candidate genes for atherosclerotic disease through RDA-based transcript profiling facilitates further functional genomic studies in coronary artery disease. Candidate genetic polymorphism markers of potential clinical relevance can be identified by filtering information in genome variation databases through the virtual chip analysis of the transcript profiles and subsequently tested in association studies. Copyright (C) 2002 S. Karger AG, Basel.
引用
收藏
页码:304 / 314
页数:11
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