CORE--GENE EXPRESSION PROFILING

免疫功能表现出与衰老相关的缺陷，如T细胞对抗原的反应性降低。我们假设，幼年动物和老年动物相同的细胞群体之间的功能差异将在基因表达表型改变中表现出来。为了验证这一假设，我们将使用DNA微阵列，允许并行研究数千个转录本。由于解释数据所需的技术和分析工具的复杂性和成本，微阵列表达分析很难在单个实验室的水平上实施和支持。因此，我们将把表达谱集中在基因表达谱的核心中。这一核心将与OHSU的基因微阵列共享资源(GMSR)合作，从而利用这个完善的服务中心的现有资源。我们将使用包含GMSR印刷的大约8900个不同克隆的人类cDNA阵列，为leinsohn、Nikolich-Zugich和Picker的项目进行基因表达谱分析。阵列分析将包括从选定的CELT种群中分离RNA、RNA扩增、标记和杂交。数据量化和归一化将与来自无关猕猴外周血单核细胞的通用参考进行比较。微阵列结果的数据分析将得到生物统计和生物信息学核心的支持，生物统计和生物信息学核心是GMSR生物信息学单位的延伸。我们期望在年老的T细胞和抗原提呈细胞中检测到有统计学意义的转录变化。成绩单更改 最重要的是，将在不相关的恒河猴群体中选择定量PCR进行确认。这些结果有望确定反映这些细胞衰老过程的特征，因此可能与观察到的免疫反应缺陷有机械联系。

Immunological functions display aging-associated defects such as decreased reactivity to antigen by T cells. We hypothesize that functional differences between equivalent cell populations from young and old animals will manifest themselves in altered gene expression phenotypes. To test this hypothesis we will employ DNA microarrays that allow to study thousands of transcripts in parallel. Due to the complexity and cost of both the technology and the analysis tools needed to interpret the data, microarray expression analysis is difficult to implement and support at the level of the individual laboratory. Therefore, we will centralize expression profiling in a core for gene expression profiling. This core will work together with the Gene Microarray Shared Resource (GMSR) of OHSU thus leveraging existing resources at this well established service center. We will perform gene expression profiling for projects by Lewinsohn, Nikolich-Zugich, and Picker using human cDNA arrays containing approximately 8900 different clones printed by the GMSR. Array analysis will encompass isolation of RNA from selected celt populations, RNA amplification, labeling and hybridization. Data quantitation and normalization will be performed in comparison to a universal reference derived from peripheral blood mononuclear cells of unrelated rhesus macaques. Data analysis of microarray results will be supported by the Biostatistics and Bionformatics Core which is an extension of the bioinformatics unit of the GMSR. We expect to detect statistically significant transcriptional changes in aged versus young T cells and antigen presenting cells. Transcripts changing most significantly will be selected for confirmation by quantitative PCR in an unrelated groups of rhesus macaques. The results are expected to identify profiles that reflect the aging process in these cells and might thus be linked mechanistically to the observed defects in immune responses.