Genes and pathways underlying regional and cell type changes in Alzheimer's disease
1 Interdepartmental Program for Neuroscience and Human Genetics Department, UCLA, 2309 Gonda Bldg, 695 Charles E Young Dr. South, Los Angeles, CA 90095-1761, USA
2 Department of Pathology, Oregon Health & Science University, Department of Pathology L113, Portland, OR 97239, USA
3 Human Genetics Department, UCLA, 2309 Gonda Bldg, 695 Charles E Young Dr. South, Los Angeles, CA 90095-1761, USA
4 Human Genetics Department and Biostatistics Department, UCLA, 4357A Gonda Bldg, 695 Charles E Young Dr. South, Los Angeles, CA 90095-1761, USA
5 Human Genetics Department and Neurology Department, UCLA, 2309 Gonda Bldg, 695 Charles E Young Dr. South, Los Angeles, CA 90095-1761, USA
Genome Medicine 2013, 5:48 doi:10.1186/gm452Published: 25 May 2013
Transcriptional studies suggest Alzheimer's disease (AD) involves dysfunction of many cellular pathways, including synaptic transmission, cytoskeletal dynamics, energetics, and apoptosis. Despite known progression of AD pathologies, it is unclear how such striking regional vulnerability occurs, or which genes play causative roles in disease progression.
To address these issues, we performed a large-scale transcriptional analysis in the CA1 and relatively less vulnerable CA3 brain regions of individuals with advanced AD and nondemented controls. In our study, we assessed differential gene expression across region and disease status, compared our results to previous studies of similar design, and performed an unbiased co-expression analysis using weighted gene co-expression network analysis (WGCNA). Several disease genes were identified and validated using qRT-PCR.
We find disease signatures consistent with several previous microarray studies, then extend these results to show a relationship between disease status and brain region. Specifically, genes showing decreased expression with AD progression tend to show enrichment in CA3 (and vice versa), suggesting transcription levels may reflect a region's vulnerability to disease. Additionally, we find several candidate vulnerability (ABCA1, MT1H, PDK4, RHOBTB3) and protection (FAM13A1, LINGO2, UNC13C) genes based on expression patterns. Finally, we use a systems-biology approach based on WGCNA to uncover disease-relevant expression patterns for major cell types, including pathways consistent with a key role for early microglial activation in AD.
These results paint a picture of AD as a multifaceted disease involving slight transcriptional changes in many genes between regions, coupled with a systemic immune response, gliosis, and neurodegeneration. Despite this complexity, we find that a consistent picture of gene expression in AD is emerging.