Differential Network Analyses of Alzheimer’s Disease Identify Early Events in Alzheimer’s Disease Pathology

Author:

Xia Jing1,Rocke David M.2,Perry George34,Ray Monika2

Affiliation:

1. Department of Mathematics, University of California, Davis, CA 95616, USA

2. Division of Biostatistics, School of Medicine, University of California, Davis, One Shields Avenue, Davis, CA 95616, USA

3. Department of Biology, University of Texas, San Antonio, TX 78249, USA

4. Neurosciences Institute, University of Texas, San Antonio, TX 78249, USA

Abstract

In late-onset Alzheimer’s disease (AD), multiple brain regions are not affected simultaneously. Comparing the gene expression of the affected regions to identify the differences in the biological processes perturbed can lead to greater insight into AD pathogenesis and early characteristics. We identified differentially expressed (DE) genes from single cell microarray data of four AD affected brain regions: entorhinal cortex (EC), hippocampus (HIP), posterior cingulate cortex (PCC), and middle temporal gyrus (MTG). We organized the DE genes in the four brain regions into region-specific gene coexpression networks. Differential neighborhood analyses in the coexpression networks were performed to identify genes with low topological overlap (TO) of their direct neighbors. The low TO genes were used to characterize the biological differences between two regions. Our analyses show that increased oxidative stress, along with alterations in lipid metabolism in neurons, may be some of the very early events occurring in AD pathology. Cellular defense mechanisms try to intervene but fail, finally resulting in AD pathology as the disease progresses. Furthermore, disease annotation of the low TO genes in two independent protein interaction networks has resulted in association between cancer, diabetes, renal diseases, and cardiovascular diseases.

Funder

National Institutes of Health

Publisher

Hindawi Limited

Subject

Behavioral Neuroscience,Cellular and Molecular Neuroscience,Cognitive Neuroscience,Clinical Neurology,Neurology,Ageing

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