Abstract
To identify functionally related genes associated with diabetic retinopathy (DR) risk using gene set enrichment analyses applied to genome-wide association study meta-analyses. Methods: We analyzed DR GWAS meta-analyses performed on 3246 Europeans and 2611 African Americans with type 2 diabetes. Gene sets relevant to 5 key DR pathophysiology processes were investigated: tissue injury, vascular events, metabolic events and glial dysregulation, neuronal dysfunction, and inflammation. Keywords relevant to these processes were queried in 4 pathway and ontology databases. Two GSEA methods, Meta-Analysis Gene set Enrichment of variaNT Associations (MAGENTA) and Multi-marker Analysis of GenoMic Annotation (MAGMA), were used. Gene sets were defined to be enriched for gene associations with DR if the P value corrected for multiple testing (Pcorr) was <.05. Results: Five gene sets were significantly enriched for numerous modest genetic associations with DR in one method (MAGENTA or MAGMA) and also at least nominally significant (uncorrected P < .05) in the other method. These pathways were regulation of the lipid catabolic process (2-fold enrichment, Pcorr = .014); nitric oxide biosynthesis (1.92-fold enrichment, Pcorr = .022); lipid digestion, mobilization, and transport (1.6-fold enrichment, P = .032); apoptosis (1.53-fold enrichment, P = .041); and retinal ganglion cell degeneration (2-fold enrichment, Pcorr = .049). The interferon gamma (IFNG) gene, previously implicated in DR by protein-protein interactions in our GWAS, was among the top ranked genes in the nitric oxide pathway (best variant P = .0001). Conclusions: These GSEA indicate that variants in genes involved in oxidative stress, lipid transport and catabolism, and cell degeneration are enriched for genes associated with DR risk.
Original language | English |
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Pages (from-to) | 111-123 |
Number of pages | 13 |
Journal | American Journal of Ophthalmology |
Volume | 233 |
DOIs | |
Publication status | Published - Jan 2022 |
Keywords
- Diabetic Retinopathy
- Genome-wide association study
- GWAS