Immune abnormalities and differential gene expression in the hippocampus and peripheral blood of patients with Alzheimer's disease

Xiaonan Wang; Di Wang; Fei Su; Chunmei Li; Min Chen

doi:10.21037/atm-21-4974

Immune abnormalities and differential gene expression in the hippocampus and peripheral blood of patients with Alzheimer's disease

Ann Transl Med. 2022 Jan;10(2):29. doi: 10.21037/atm-21-4974.

Authors

Xiaonan Wang^{1

2}, Di Wang^{1

2}, Fei Su³, Chunmei Li^{1

2}, Min Chen^{1

2}

Affiliations

¹ Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
² Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
³ Clinical Biobank, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.

Abstract

Background: Despite decades of research, no precise mechanisms of Alzheimer's disease (AD) development have been elucidated. This study aimed to investigate novel diagnostic biomarkers in both peripheral blood cells and hippocampus tissue, and the pathogenesis of memory impairment in AD.

Methods: mRNA microarray data, including hippocampus samples (GSE1297 and GSE5281) and peripheral blood mononuclear cells (PBMCs) (GSE63060 and GSE63061), associated with AD were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between AD and normal-aging samples were screened through a comprehensive analysis of multiple gene expression spectra after gene reannotation and batch normalization. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were used to analyze hub genes and to discover potential biomarkers related to AD. Protein-protein interaction (PPI) network maps were constructed to visualize the correlation between possible genes. The CIBERSORT algorithm was built to explore the patterns of PBMC infiltration to investigate the role of inflammation in the pathogenesis of AD.

Results: The bioinformatics analysis indicated 1,261 DEGs in the hippocampal samples and 290 in PBMCs when comparing patients with AD with normal-aging individuals. We selected 28 genes co-expressed in the hippocampus and PBMCs. A functional analysis of differential genes revealed that they were primarily involved in neuronal death, immune response, and mitochondrial function. Further, immune cell infiltration patterns demonstrated that the levels of naive CD4⁺ T cells, resting natural killer cells, M0 macrophages, and activated mast cells were higher in the peripheral blood of patients with AD, while resting memory CD4⁺ T cells were significantly lower.

Conclusions: The key gene changes present in both the hippocampus and PBMCs highly suggest their utility as an AD biomarker. In addition, according to our present results, immune abnormalities may have an important role in AD pathophysiology. When patients display these peripheral blood immune abnormalities, they may be recognized as being at high risk of developing AD.

Keywords: Alzheimer’s disease (AD); Gene Expression Omnibus (GEO) database; bioinformatics; gene expression; immune features.