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阿尔茨海默病与正常衰老中转录变化的系统水平分析。

A systems level analysis of transcriptional changes in Alzheimer's disease and normal aging.

作者信息

Miller Jeremy A, Oldham Michael C, Geschwind Daniel H

机构信息

Center for Neurobehavioral Genetics, University of California, Los Angeles, Los Angeles, California 90095-1769, USA.

出版信息

J Neurosci. 2008 Feb 6;28(6):1410-20. doi: 10.1523/JNEUROSCI.4098-07.2008.

Abstract

Alzheimer's disease (AD) is a debilitating neurodegenerative disorder affecting millions of elderly individuals worldwide. Advances in the genetics of AD have led to new levels of understanding and treatment opportunities. Here, we used a systems biology approach based on weighted gene coexpression network analysis to determine transcriptional networks in AD. This method permits a higher order depiction of gene expression relationships and identifies modules of coexpressed genes that are functionally related, rather than producing massive gene lists. Using this framework, we characterized the transcriptional network in AD, identifying 12 distinct modules related to synaptic and metabolic processes, immune response, and white matter, nine of which were related to disease progression. We further examined the association of gene expression changes with progression of AD and normal aging, and were able to compare functional modules of genes defined in both conditions. Two biologically relevant modules were conserved between AD and aging, one related to mitochondrial processes such as energy metabolism, and the other related to synaptic plasticity. We also identified several genes that were central, or hub, genes in both aging and AD, including the highly abundant signaling molecule 14.3.3 zeta (YWHAZ), whose role in AD and aging is uncharacterized. Finally, we found that presenilin 1 (PSEN1) is highly coexpressed with canonical myelin proteins, suggesting a role for PSEN1 in aspects of glial-neuronal interactions related to neurodegenerative processes.

摘要

阿尔茨海默病(AD)是一种使人衰弱的神经退行性疾病,影响着全球数百万老年人。AD遗传学的进展带来了新的理解水平和治疗机会。在这里,我们使用了一种基于加权基因共表达网络分析的系统生物学方法来确定AD中的转录网络。这种方法允许对基因表达关系进行更高层次的描述,并识别功能相关的共表达基因模块,而不是生成大量的基因列表。使用这个框架,我们对AD中的转录网络进行了表征,识别出12个与突触和代谢过程、免疫反应及白质相关的不同模块,其中9个与疾病进展相关。我们进一步研究了基因表达变化与AD进展和正常衰老的关联,并能够比较在这两种情况下定义的基因功能模块。在AD和衰老之间有两个生物学相关的模块是保守的,一个与能量代谢等线粒体过程相关,另一个与突触可塑性相关。我们还鉴定出了几个在衰老和AD中都是核心或枢纽的基因,包括高度丰富的信号分子14.3.3 zeta(YWHAZ),其在AD和衰老中的作用尚不清楚。最后,我们发现早老素1(PSEN1)与典型的髓磷脂蛋白高度共表达,这表明PSEN1在与神经退行性过程相关的胶质-神经元相互作用方面发挥作用。

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