DNA methylation plays a significant role in many diseases. Age-related macular degeneration (AMD) is a leading cause of vision loss for people aged 50 years and above, but the etiology and pathogenesis are largely unknown. This study aimed to identify the aberrantly methylated differentially expressed genes (DEGs) in AMD and predict the related pathways on the basis of public data.
Aberrant methylation can influence the functions of key genes by altering their expression. Here, we found out DEGs by overlapping public microarray data (GSE29801 and GSE102952). Functional and enrichment analyses of selected genes were performed using the DAVID database. Subsequently, protein–protein interaction (PPI) networks were constructed by using STRING and visualized in cytoscape to determine hub genes. Finally, we collected AMD patients’ blood samples to identify the methylation statuses of these hub genes by using methylated DNA immunoprecipitation.
In total, 156 hypermethylation-low expression genes and 127 hypomethylation-high expression genes were predicted. The hypermethylation-low expression genes were enriched in biological processes of response to cardiac conduction, ATP binding, and cell–cell junction assembly. The top 5 hub genes of the PPI network were
HSP90AA1
,
HSPA1L
,
HSPE1
,
HSP90B1
, and
NOP56
. Meanwhile, the hypomethylation-high expression genes were enriched in the biological processes of response to positive regulation of the MAPK cascade, actin cytoskeleton reorganization, dentate gyrus development, and cell migration. The top 5 hub genes of this PPI network were
PIK3R1
,
EZR
,
IGF2
,
SLC2A1
, and
CDKN1C
. Moreover, the methylation statuses of
NOP56
,
EZR
,
IGF2
,
SLC2A1
,
CDKN1C
were confirmed to be altered in the blood of AMD patients.
This study indicated possible aberrantly methylated DEGs and differentially expressed pathways in AMD by bioinformatics analysis, providing novel insights for unraveling the pathogenesis of AMD. Hub genes, including
NOP56
,
EZR
,
IGF2
,
SLC2A1
,
CDKN1C
, might serve as aberrant methylation-based candidate biomarkers for AMD in future applications.