Meta-Analysis of Gene Expression Changes in the Blood of Patients with Mild Cognitive Impairment and Alzheimer's Disease Dementia

Abstract

Background: Dementia is a major public health concern affecting approximately 47 million people worldwide. Mild cognitive impairment (MCI) is one form of dementia that affects an individual's memory with or without affecting their daily life. Alzheimer's disease dementia (ADD) is a more severe form of dementia that usually affects elderly individuals. It remains unclear whether MCI is a distinct disorder from or an early stage of ADD.

Methods: Gene expression data from blood were analyzed to identify potential biomarkers that may be useful for distinguishing between these two forms of dementia.

Results: A meta-analysis revealed 91 genes dysregulated in individuals with MCI and 387 genes dysregulated in ADD. Pathway analysis identified seven pathways shared between MCI and ADD and nine ADD-specific pathways. Fifteen transcription factors were associated with MCI and ADD, whereas seven transcription factors were specific for ADD. Mir-335-5p was specific for ADD, suggesting that it may be useful as a biomarker. Diseases that are associated with MCI and ADD included developmental delays, cognition impairment, and movement disorders.

Conclusion: These results provide a better molecular understanding of peripheral changes that occur in MCI and ADD patients and may be useful in the identification of diagnostic and prognostic biomarkers.

Keywords: Alzheimer’s disease; dementia; gene expression; mild cognitive impairment; network analysis.

Figure 1

Flowchart of the study. The BaseSpace Correlation Engine (BSCE) was searched and blood gene expression studies with data from mild cognitive impairment (MCI) and Alzheimer’s disease dementia (ADD) were included in this study. Venn diagram analysis was used to identify shared dysregulated genes. The MCI and ADD dysregulated genes were analyzed for shared functional pathways, transcription factors, and miRNAs regulation as well as disease associations. The arrows represent the flow of the steps in the study.

Figure 2

Venn diagram analysis of the genes down and up regulated in MCI and ADD. (a,b) The genes downregulated (a) and upregulated (b) in the MCI arrays (GSE63063, GPL10558, and GPL6947 platforms) were downloaded from BSCE and analyzed by Venn diagrams using the following website http://www.interactivenn.net/. (c,d) The genes downregulated (c) and upregulated (d) in the ADD arrays (GSE63063 GPL10558 and GPL6947 platforms, MTAB-6094, and GSE97760) were downloaded from BSCE and analyzed by Venn diagrams.

Figure 3

Pathway analysis. The genes that were commonly dysregulated in the MCI arrays (a,b) and in at least two of the ADD arrays (c,d) were obtained from the Venn diagram analysis. The genes lists were uploaded to https://www.networkanalyst.ca/NetworkAnalyst/faces/home.xhtml where an enrichment network analysis was performed using the Kyoto Encyclopedia of Genes and Genome (KEGG) database.

Figure 4

Transcription factors analysis. The genes commonly dysregulated in the MCI arrays and in at least two out of the ADD arrays were obtained using Venn diagram analysis. The gene lists were uploaded to https://www.networkanalyst.ca/NetworkAnalyst/faces/home.xhtml. The gene-transcription factor interaction network was performed with ENCODE, ChEA, and JASPAR. A Venn diagram analysis was performed to identify the transcription factors identified by the three methods. (a,b) represent the results of the Venn diagram analysis performed with MCI and ADD genes, respectively. The transcription factors interacting with the MCI and ADD genes were listed in (c,d), respectively. Transcription factors in blue are common in MCI and ADD analysis whereas the transcription factors in red were specific to ADD regulation.