Meta analysis of alzheimer’s disease at the gene expression level

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2017

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İzgi, Hamit

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In this study, publicly available microarray gene expression datasets are used to investigate common gene expression changes in different postmortem brain regions in Alzheimer’s Disease (AD) patients compared to control subjects, and to find possible functional associations related to these changes. The hypothesis is that pathogenesis of the disease converges into common patterns of dysregulation/alteration or dysfunction in molecular pathways across different brain regions in AD. In total, I studied 13 datasets, one of which was excluded from the analysis in quality checks, resulting in 12 datasets spanning 7 different brain regions. Instead of using the standard approach to identify differentially expressed genes in each dataset independently, I used an alternative scheme, focusing on shared trends across all datasets, and testing their significance using cross-dataset structured permutations. Among more than 8000 common genes in all 12 datasets, I identified those showing shared upregulated (631) or downregulation (580) trends in AD across all datasets, which was highly significant compared to permutations. I then performed GO Biological Process enrichment analysis on both gene sets. There were 343 GO BP categories enriched for upregulated genes and 94 GO BP categories enriched for downregulated genes. Among 343 GO categories enriched for upregulated genes, the most noticeable ones include protein modification, differentiation, and the cell cycle. Furthermore, cell-cell signaling, synaptic activity and energy metabolism related pathways are enriched in downregulated genes. These findings are in line with the effects of pathological changes in AD and suggests that different brain regions share common pathways deregulated by AD.

Subject Keywords

Brain, Gene expression., Alzheimer's disease.

URI

http://etd.lib.metu.edu.tr/upload/12620729/index.pdf
https://hdl.handle.net/11511/26240

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Graduate School of Natural and Applied Sciences, Thesis

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Citation Formats

H. İzgi, “Meta analysis of alzheimer’s disease at the gene expression level,” M.S. - Master of Science, Middle East Technical University, 2017.