TY - JOUR
T1 - Genes and pathways underlying regional and cell type changes in Alzheimer's disease
AU - Miller, Jeremy A.
AU - Woltjer, Randall L.
AU - Goodenbour, Jeff M.
AU - Horvath, Steve
AU - Geschwind, Daniel H.
N1 - Funding Information:
We thank Ezra Rosen, Brent Bill, Jennifer Lowe, and Neelroop Parikshak for reading the manuscript for clarity, and Eric Wexler, Chandran Vijayendran, Patricia Kramer, and Jeffrey Kaye for valuable conversations. Tissue and clinical characterization for this experiment was graciously provided by the Oregon Alzheimer’s Disease Center and the Oregon Brain Aging Study (OBAS): Office of Research and Development, Clinical Sciences Research and Development Service, funded by NIH NIA P30 AG008017 and the Department of Veterans Affairs, as well as by the Human Brain and Spinal Fluid Resource Center, VA West Los Angeles Healthcare Center, 11301 Wilshire Blvd, Los Angeles, CA 90073, which is sponsored by NINDS/NIMH, National Multiple Sclerosis Society, and the Department of Veterans Affairs. This work was supported by National Research Service Award F31 AG031649 from the National Institute on Aging (NIA) (to JAM); NIH/National Institute of Mental Health Merit Award R37 MH 60233-09S1 (to DHG); NIH/NIA Award R01 AG26938-05 (to DHG); the Oregon Alzheimer’s Disease Center grant P30AG008017 (to RLW); and Consortium for Frontotemporal Dementia Research Award 108400 (to DHG and JMG).
PY - 2013/5/25
Y1 - 2013/5/25
N2 - Background: 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.Methods: 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.Results: 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.Conclusions: 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.
AB - Background: 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.Methods: 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.Results: 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.Conclusions: 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.
UR - http://www.scopus.com/inward/record.url?scp=84878007793&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84878007793&partnerID=8YFLogxK
U2 - 10.1186/gm452
DO - 10.1186/gm452
M3 - Article
AN - SCOPUS:84878007793
SN - 1756-994X
VL - 5
JO - Genome Medicine
JF - Genome Medicine
IS - 5
M1 - 48
ER -