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

Min Zhu,Jianping Jia,Fangyu Li,Longfei Jia

doi:10.3389/fgene.2020.00981

Abstract

Alzheimer disease (AD) is the most common cause of dementia and creates a significant burden on society. As a result, the investigation of hub genes for the discovery of potential therapeutic targets and candidate biomarkers is warranted. In this study, we used the ComBat method to merge three gene expression datasets of AD from the Gene Expression Omnibus (GEO). During combined analysis, we identified 850 differentially expressed genes (DEGs) from the temporal cortex of AD and cognitively normal (CN) samples. We performed weighted gene coexpression network analysis to build gene coexpression networks incorporating these DEGs to identify key modules and hub genes. We found one module most strongly correlated with AD onset as the key module and 19 hub genes in the key module that were down-regulated in AD brains. According to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses, DEGs were mostly enriched in synapse function, and genes in the key module were mostly related to learning and memory. We selected five little-studied genes, AP3B2, GABRD, GPR158, KIAA0513, and MAL2, to validate their expression in AD mouse model by performing quantitative real-time polymerase chain reaction. We found that all of them were down-regulated in cortices of 8-month 5xFAD mice compared to those of wild-type mice. We then further investigated their correlations with β-secretase activity and Aβ42 levels in AD samples of different Braak stages. We found that all five hub genes had significant negative associations with β-secretase activity and that AP3B2 and KIAA0513 had significant negative associations with Aβ42 levels. We tested the differential expressions of the five hub genes in two AD GEO datasets from the blood and found that KIAA0513 was significantly up-regulated in patients with both mild cognitive impairment (MCI) and AD and was able to differentiate MCI and AD from CN in the two datasets. In conclusion, these five novel vulnerable genes were involved in AD progression, and KIAA0513 was a promising candidate biomarker for early diagnosis of AD.

Highlights

Alzheimer disease (AD) is the most common cause of dementia and is manifested as progressive impairments of memory and other cognitive domains
Quantitative real-time polymerase chain reaction was done on Applied Biosystems ViiATM 7 Real-Time PCR System using TB Green R Premix Ex Taq (#RR420, Takara, Japan). β-Actin was used as internal control, and relative expression was determined using 2− CT method
We found that the five hub genes were down-regulated as AD progressed, especially adaptor-related protein complex 3 subunit β2 (AP3B2), KIAA0513, and MAL2, which were significantly downregulated in Braak III–IV and Braak V–VI when compared with Braak 0 (P < 0.05, 0.01, respectively, Figure 8A). β-Secretase activity and Aβ42 levels in GSE106241 were identified to be up-regulated during AD progression (Figure 8A)

Summary

Introduction

Alzheimer disease (AD) is the most common cause of dementia and is manifested as progressive impairments of memory and other cognitive domains. Genome-wide association studies found AD risk genes including ABCA7, CLU, SORL1, TREM2, and so on (Campion et al, 2019; Kunkle et al, 2019). Network analyses of AD-related genes from publications revealed the complexed molecular mechanisms of AD (Hu et al, 2017). In vitro studies have identified other genes such as AChE (GarciaAyllon et al, 2011) and TFEB (Guo et al, 2017; Xu et al, 2020) playing roles in AD pathologies, which provides potential targets for AD therapy. Because AD is a complicated disease affected by age, genetic, and environmental factors, a greater number of key genes and their underlying mechanisms must be identified in order to facilitate the discovery of novel therapeutic targets and candidate biomarkers

Methods

Results

Conclusion