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Aging-associated changes in cardiac gene expression: large scale transcriptome analysis.

S V Anisimov, Kenneth R. Boheler

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Abstract

Aging and aging-related diseases are associated with altered patterns of gene expression, involving quantitative and qualitative changes in the abundance of specific transcripts. A complete and simultaneous analysis of gene expression should therefore lead to important insights into the transcriptional mechanisms underlying the aging process. Recently, we have employed high-throughput gene expression profiling to study transcriptional activity in heart. Two technologies, serial analysis of gene expression (SAGE) and gene expression arrays, allow rapid, large-scale expression profiling, which provides information about the dynamics of total gene expression with age and which can be employed to identify candidate genes that may serve as diagnostic and prognostic markers in age-associated cardiac diseases. The accompanying gene predictions from high-throughput gene expression profiling provide a starting point for understanding the function, the complexity of interactions, and the role of genes in promoting cellular/organismal phenotypes during senescence and disease. In this review we describe the current state of transcriptome profiling by SAGE and microarrays and discuss how results generated with these approaches in heart can be applied to the study of aging and the treatment of cardiovascular diseases.

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Aging and aging-related diseases are associated with altered patterns of gene expression, involving quantitative and qualitative changes in the abundance of specific transcripts. A complete and simultaneous analysis of gene expression should therefore lead to important insights into the transcriptional mechanisms underlying the aging process. Recently, we have employed high-throughput gene expression profiling to study transcriptional activity in heart. Two technologies, serial analysis of gene expression (SAGE) and gene expression arrays, allow rapid, large-scale expression profiling, which provides information about the dynamics of total gene expression with age and which can be employed to identify candidate genes that may serve as diagnostic and prognostic markers in age-associated cardiac diseases. The accompanying gene predictions from high-throughput gene expression profiling provide a starting point for understanding the function, the complexity of interactions, and the role of genes in promoting cellular/organismal phenotypes during senescence and disease. In this review we describe the current state of transcriptome profiling by SAGE and microarrays and discuss how results generated with these approaches in heart can be applied to the study of aging and the treatment of cardiovascular diseases.

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Available abstract

Aging and aging-related diseases are associated with altered patterns of gene expression, involving quantitative and qualitative changes in the abundance of specific transcripts. A complete and simultaneous analysis of gene expression should therefore lead to important insights into the transcriptional mechanisms underlying the aging process. Recently, we have employed high-throughput gene expression profiling to study transcriptional activity in heart. Two technologies, serial analysis of gene expression (SAGE) and gene expression arrays, allow rapid, large-scale expression profiling, which provides information about the dynamics of total gene expression with age and which can be employed to identify candidate genes that may serve as diagnostic and prognostic markers in age-associated cardiac diseases. The accompanying gene predictions from high-throughput gene expression profiling provide a starting point for understanding the function, the complexity of interactions, and the role of genes in promoting cellular/organismal phenotypes during senescence and disease. In this review we describe the current state of transcriptome profiling by SAGE and microarrays and discuss how results generated with these approaches in heart can be applied to the study of aging and the treatment of cardiovascular diseases.

Key concepts: Gene expression profiling, Transcriptome, Gene expression, Biology, DNA microarray, Serial analysis of gene expression, Gene, Computational biology

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