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. 2021 Dec;12(2):9598-9609.
doi: 10.1080/21655979.2021.1999549.

Identification of hub genes associated with cognition in the hippocampus of Alzheimer's Disease

Yu-Jia Liu  1   2   3 , Tian-Tian Liu  1   2   3 , Lin-Hao Jiang  1   2   3 , Qian Liu  1   2   3 , Zheng-Liang Ma  1 , Tian-Jiao Xia  2   3 , Xiao-Ping Gu  1
Affiliations

Identification of hub genes associated with cognition in the hippocampus of Alzheimer's Disease

Yu-Jia Liu et al. Bioengineered. 2021 Dec.

Abstract

Alzheimer's Disease (AD) is a neurodegenerative disease featured by cognitive impairment. This bioinformatic analysis was used to identify hub genes related to cognitive dysfunction in AD. The gene expression profile GSE48350 in the hippocampus of AD patients aged >70 years was obtained from the Gene Expression Omnibus (GEO) database. A total of 96 differentially expressed genes (DEGs) were identified, and subjected to Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses; a protein-protein interaction (PPI) network was constructed. The DEGs were enriched in synapse-related changes. A protein cluster was teased out of PPI. Furthermore, the cognition ranked the first among all the terms of biological process (BP). Next, 4 of 10 hub genes enriched in cognition were identified. The function of these genes was validated using APP/PS1 mice. Cognitive performance was validated by Morris Water Maze (MWM), and gene expression by RT-qPCR, Cholecystokinin (CCK), Tachykinin precursor 1 (TAC1), Calbindin 1 (CALB1) were downregulated in the hippocampus. These genes can provide new directions in the research of the molecular mechanism of AD.

Keywords: Alzheimer’s disease; GSE48350; bioinformatic analysis; cognition.

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Conflict of interest statement

No potential conflict of interest was reported by the author(s).

Figures

Figure 1.
Figure 1.
The visualization of differential gene expression profile (a) A volcano plot of the expression of DEGs in the whole gene profile, significantly upregulated genes are indicated in red, downregulated in green (b) Cluster pattern of Heat map concerning DEGs, high level expressions are indicated in red, low level in blue
Figure 2.
Figure 2.
GO and KEGG pathway enrichment results of DEGs: (a) cellular component, (b) molecular function, (c) biological process, (d) KEGG pathways
Figure 3.
Figure 3.
PPI network and GO/KEGG pathway enrichment results of genes in the cluster (a) DEGs in Protein-protein interaction network. Nodes in red represent upregulated genes and nodes in blue represent downregulated genes, the internal circle indicates the cluster (b) cellular component, (c) molecular function (d) biological process, (e) KEGG pathway
Figure 3.
Figure 3.
Continued
Figure 4.
Figure 4.
Venn diagrams for identification of hub genes (a) 10 hub genes were identified via the intersection of four algorithms (b) 4 genes related to the cognition according to biological process of Gene Ontology database. CALB1, Calbindin 1. TAC1, Tachykinin precursor 1. CCK, cholecystokinin. CNR1, cannabinoid receptor type 1
Figure 5.
Figure 5.
Validation of APP/PS1 mice. A. APP/PS1 mice spent more time finding the platform than wildtype mice in training phase, Day1(60 ± 0 vs 47.90 ± 10.86, P = 0.038), Day2(57.90 ± 6.50 vs 35.56 ± 12.48, P = 0.009), Day3(56.48 ± 6.30 vs 28.30 ± 9.20, P < 0.0001), Day4(49.54 ± 6.92 vs 22.38 ± 5.35, P < 0.0001), Day5(49.17 ± 10.06 vs 16.46 ± 8.94, P = 0.001). B. In probe test, the number of crossing removed platform location declined in APP/PS1 mice (P = 0.018) C. In probe test, the time stayed in the platform quadrant declined in APP/PS1 mice (P = 0.011)
Figure 6.
Figure 6.
mRNA expression of four hub genes in two groups. CALB1, CCK, TAC1 showed a significant difference between the two groups. CALB1(P = 0.01), TAC1(P = 0.039), CCK (P = 0.02), CNR1 (P = 0.29)
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Grants and funding

This study was supported by the National Natural Science Foundation of China [81701371, 81730033]; the National Key R&D Program of China (GXP, grant numbers 2018YFC2001901); the Natural Science Foundation of Jiangsu Province of China [BK20170654]; and the Key Talents of 13th Five-Year Plan for Strengthening Health of Jiangsu Province [ZDRCA2016069].
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