Transcriptomic analysis of probable asymptomatic and symptomatic Alzheimer brains

Abstract

Individuals with intact cognition and neuropathology consistent with Alzheimer's disease (AD) are referred to as asymptomatic AD (AsymAD). These individuals are highly likely to develop AD, yet transcriptomic changes in the brain which might reveal mechanisms for their AD vulnerability are currently unknown. Entorhinal cortex, frontal cortex, temporal cortex and cerebellum tissue from 27 control, 33AsymAD and 52 AD human brains were microarray expression profiled. Differential expression analysis identified a significant increase of transcriptomic activity in the frontal cortex of AsymAD subjects, suggesting fundamental changes in AD may initially begin within the frontal cortex region prior to AD diagnosis. Co-expression analysis identified an overactivation of the brain "glutamate-glutamine cycle", and disturbances in the brain energy pathways in both AsymAD and AD subjects, while connectivity of key hub genes in this network indicates a shift from an already increased cell proliferation in AsymAD subjects to stress response and removal of amyloidogenic proteins in AD subjects. This study provides new insight into the earliest biological changes occurring in the brain prior to the manifestation of clinical AD symptoms and provides new potential therapeutic targets for early disease intervention.

Identification of KIAA0513 and Other Hub Genes Associated With Alzheimer Disease Using Weighted Gene Coexpression Network Analysis

“…Expression data of 823 DEGs were extracted from GSE118553 (27 DEGs not available; Patel et al, 2019 ) and used to conduct WGCNA ( Figure 4 ). By setting the soft-threshold power as 5 (scale-free R 2 = 0.9, slope = -0.96; Figure 4B and Supplementary Figure 5 ) and cut height as 0.25, we acquired eight modules ( Figures 4C,D ), with non-clustering DEGs in the gray module.…”

“…All 19 hub genes underwent expression validation in GSE132903 ( Piras et al, 2019 ), GSE122063 ( McKay et al, 2019 ), GSE36980 ( Hokama et al, 2014 ), GSE5281 ( Liang et al, 2007 , 2008a , b ; Readhead et al, 2018 ), and GSE118553 ( Patel et al, 2019 ) datasets. Except for CRYM , GABRD , PHYHIP , SCN2B , and TERF2IP in GSE36980 and CAMKK2 , PHYHIP , and GPR158 in GSE132903, all other hub genes were significantly down-regulated in AD samples from the five datasets ( P < 0.05, 0.01, 0.001, or 0.0001; Figure 6 and Supplementary Figure 7 ).…”

“…Datasets GSE122063 (28 AD, 22 CN; McKay et al, 2019 ), GSE36980 (10 AD, 19 CN; Hokama et al, 2014 ), and GSE5281 (16 AD, 12 CN; Liang et al, 2007 , 2008a , b ; Readhead et al, 2018 ) had similar sample sizes and were chosen for the combined analysis in the current study. Dataset GSE118553 (52 AD, 31 CN; Patel et al, 2019 ) was used to build the coexpression network and to perform GSEA. Dataset GSE106241 ( Marttinen et al, 2019 ) was used to test the expression of hub genes in different Braak stages and to explore the correlation with β-secretase activity and Aβ42 levels.…”

“…We used the DEGs from the combined analysis to perform WGCNA using expression data from GSE118553 ( Patel et al, 2019 ). The R package “WGCNA” was used to conduct this analysis and to find clinical trait–related modules and hub genes among the DEGs ( Langfelder and Horvath, 2008 , 2012 ).…”

“…GSEA (version 4.0.3, Broad Institute, Inc., Massachusetts Institute of Technology, and Regents of the University of California) was conducted to explore the possible biological functions of the hub genes ( Mootha et al, 2003 ; Subramanian et al, 2005 ). AD samples in GSE118553 ( Patel et al, 2019 ) were divided into two groups according to the expression level of the hub genes. The database “c2.cp.kegg.v7.0.symbols.gmt” was chosen for enrichment.…”