Dataset Information

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

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.

SUBMITTER: Miller JA

PROVIDER: S-EPMC2902235 | biostudies-literature | 2008 Feb

REPOSITORIES: biostudies-literature

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

Miller Jeremy A JA Oldham Michael C MC Geschwind Daniel H DH

The Journal of neuroscience : the official journal of the Society for Neuroscience 20080201 6

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 functio ...[more]

PMID: 18256261

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Project description:Aging is a major risk factor for late-onset Alzheimer's disease (LOAD). How aging contributes to the development of LOAD remains elusive. In this study, we examined multiple large-scale transcriptomic datasets from both normal aging and LOAD brains to understand the molecular interconnection between aging and LOAD. We found that shared gene expression changes between aging and LOAD are mostly seen in the hippocampal and several cortical regions. In the hippocampus, the expression of phosphoprotein, alternative splicing and cytoskeleton genes are commonly changed in both aging and AD, while synapse, ion transport, and synaptic vesicle genes are commonly down-regulated. Aging-specific changes are associated with acetylation and methylation, while LOAD-specific changes are more related to glycoprotein (both up- and down-regulations), inflammatory response (up-regulation), myelin sheath and lipoprotein (down-regulation). We also found that normal aging brain transcriptomes from relatively young donors (45-70 years old) clustered into several subgroups and some subgroups showed gene expression changes highly similar to those seen in LOAD brains. Using brain transcriptomic datasets from another cohort of older individuals (>70 years), we found that samples from cognitively normal older individuals clustered with the "healthy aging" subgroup while AD samples mainly clustered with the "AD similar" subgroups. This may imply that individuals in the healthy aging subgroup will likely remain cognitively normal when they become older and vice versa. In summary, our results suggest that on the transcriptome level, aging and LOAD have strong interconnections in some brain regions in a subpopulation of cognitively normal aging individuals. This supports the theory that the initiation of LOAD occurs decades earlier than the manifestation of clinical phenotype and it may be essential to closely study the "normal brain aging" to identify the very early molecular events that may lead to LOAD development.

Dataset Information

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

Publications

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

Similar Datasets

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