A Systematic Bioinformatics Workflow With Meta-Analytics Identified Potential Pathogenic Factors of Alzheimer's Disease

Abstract

Potential pathogenic factors, other than well-known APP, APOE4, and PSEN, can be further identified from transcriptomics studies of differentially expressed genes (DEGs) that are specific for Alzheimer's disease (AD), but findings are often inconsistent or even contradictory. Evidence corroboration by combining meta-analysis and bioinformatics methods may help to resolve existing inconsistencies and contradictions. This study aimed to demonstrate a systematic workflow for evidence synthesis of transcriptomic studies using both meta-analysis and bioinformatics methods to identify potential pathogenic factors. Transcriptomic data were assessed from GEO and ArrayExpress after systematic searches. The DEGs and their dysregulation states from both DNA microarray and RNA sequencing datasets were analyzed and corroborated by meta-analysis. Statistically significant DEGs were used for enrichment analysis based on KEGG and protein-protein interaction network (PPIN) analysis based on STRING. AD-specific modules were further determined by the DIAMOnD algorithm, which identifies significant connectivity patterns between specific disease-associated proteins and non-specific proteins. Within AD-specific modules, the nodes of highest degrees (>95th percentile) were considered as potential pathogenic factors. After systematic searches of 225 datasets, extensive meta-analyses among 25 datasets (21 DNA microarray datasets and 4 RNA sequencing datasets) identified 9,298 DEGs. The dysregulated genes and pathways in AD were associated with impaired amyloid-β (Aβ) clearance. From the AD-specific module, Fyn, and EGFR were the most statistically significant and biologically relevant. This meta-analytical study suggested that the reduced Aβ clearance in AD pathogenesis was associated with the genes encoding Fyn and EGFR, which were key receptors in Aβ downstream signaling.

Keywords: Alzheimer’s disease; RNA sequence analysis; bioinformatics; meta-analysis; microarray analysis.

FIGURE 1

The overall study design.

FIGURE 2

The flow diagram of datasets selection, including identification, screening, eligibility and inclusion stage.

FIGURE 3

The AD-related biological pathways as impacted in health vs. AD subjects, (A) the top 10 statistically significant pathways from enrichment analysis result; (B) Alzheimer’s disease; (C) Proteasome; (D) Oxidative phosphorylation; and (E) Retrograde endocannabinoid signaling. For figure 3B-E, the red and green represent upregulation and downregulation, respectively.

FIGURE 4

The AD-related biological pathways from the subgroup amydala and hippocampus, (A) the top 10 statistically significant pathways from enrichment analysis result; (B) Alzheimer’s disease; (C) Proteasome; (D) Oxidative phosphorylation; (E) Retrograde endocannabinoid signaling; and (F) Synaptic vesicle cycle. The red and green represent upregulation and downregulation, respectively.

FIGURE 5

The AD-related biological pathways from the subgroup cerebral cortex, (A) the top 10 statistically significant pathways from enrichment analysis result; (B) Proteasome; (C) Retrograde endocannabinoid signaling; (D) MAPK signaling pathway; (E) Dopaminergic synapse; and (F) Insulin signaling pathways. The red and green represent upregulation and downregulation, respectively.

FIGURE 6

The overall quality assessment for (A) 19 studies for DNA microarray and (B) 4 studies for RNA-seq. Green color represents low risk of bias, which the authors clearly provided the information with full detail. Yellow color represents unclear risk of bias, which the authors provided the information without full detail. Red color represents high risk of bias, which the authors did not provide the correct information.

FIGURE 7

(A) The PPIN constructed from DEGs and the PPIN topology parameters. The red and green represent upregulation and downregulation, respectively. (B) A disease module, derived from the DIAMOnD algorithm, consisting of AD seed proteins (represented as squares) and their corresponding DIAMOnD proteins (represented as circles). The colors of the nodes represent upregulation (red), and downregulation (green). The edges represent seed-seed interaction (dark green), seed-DIAMOnD interaction (purple), and DIAMOnD-DIAMOnD interaction (pink).

FIGURE 8

The mechanism of action of Aβ-mediated Fyn and EGFR in AD.