Integrated bioinformatics-based identification of diagnostic markers in Alzheimer disease

Abstract

Alzheimer disease (AD) is a progressive neurodegenerative disease resulting from the accumulation of extracellular amyloid beta (Aβ) and intracellular neurofibrillary tangles. There are currently no objective diagnostic measures for AD. The aim of this study was to identify potential diagnostic markers for AD and evaluate the role of immune cell infiltration in disease pathogenesis. AD expression profiling data for human hippocampus tissue (GSE48350 and GSE5281) were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified using R software and the Human Protein Atlas database was used to screen AD-related DEGs. We performed functional enrichment analysis and established a protein–protein interaction (PPI) network to identify disease-related hub DEGs. The fraction of infiltrating immune cells in samples was determined with the Microenvironment Cell Populations-counter method. The random forest algorithm was used to develop a prediction model and receiver operating characteristic (ROC) curve analysis was performed to validate the diagnostic utility of the candidate AD markers. The correlation between expression of the diagnostic markers and immune cell infiltration was also analyzed. A total of 107 AD-related DEGs were screened in this study, including 28 that were upregulated and 79 that were downregulated. The DEGs were enriched in the Gene Ontology terms GABAergic synapse, Morphine addiction, Nicotine addiction, Phagosome, and Synaptic vesicle cycle. We identified 10 disease-related hub genes and 20 candidate diagnostic genes. Synaptophysin (SYP) and regulator of G protein signaling 4 (RGS4) (area under the ROC curve = 0.909) were verified as potential diagnostic markers for AD in the GSE28146 validation dataset. Natural killer cells, B lineage cells, monocytic lineage cells, endothelial cells, and fibroblasts were found to be involved in AD; additionally, the expression levels of both SYP and RGS4 were negatively correlated with the infiltration of these immune cell types. These results suggest that SYP and RGS4 are potential diagnostic markers for AD and that immune cell infiltration plays an important role in AD development and progression.

Identification ferroptosis-related hub genes and diagnostic model in Alzheimer’s disease

“…Studies have shown that ATP6V1G2 as significantly regulated by DNA methylation at hub CpGs in AD ( Kim et al, 2023 ). RGS4, a regulator of G-protein signaling, has been identified as a potential biomarker for AD in multiple studies ( Zou et al, 2019 ; Chen et al, 2022 ), and this finding has been confirmed in our result as well. Although these genes exhibit consistent strong correlations in both datasets, there are some genes whose correlations show completely opposite patterns between the two datasets.…”