Background
Age-related macular degeneration (AMD) is a leading cause of blindness that
affects the central region of the retinal pigmented epithelium (RPE), choroid, and
neural retina. Initially characterized by an accumulation of sub-RPE deposits, AMD
leads to progressive retinal degeneration, and in advanced cases, irreversible
vision loss. Although genetic analysis, animal models, and cell culture systems
have yielded important insights into AMD, the molecular pathways underlying AMD's
onset and progression remain poorly delineated. We sought to better understand the
molecular underpinnings of this devastating disease by performing the first
comparative transcriptome analysis of AMD and normal human donor eyes.
Methods
RPE-choroid and retina tissue samples were obtained from a common cohort of 31
normal, 26 AMD, and 11 potential pre-AMD human donor eyes. Transcriptome profiles
were generated for macular and extramacular regions, and statistical and
bioinformatic methods were employed to identify disease-associated gene signatures
and functionally enriched protein association networks. Selected genes of high
significance were validated using an independent donor cohort.
Results
We identified over 50 annotated genes enriched in cell-mediated immune responses
that are globally over-expressed in RPE-choroid AMD phenotypes. Using a machine
learning model and a second donor cohort, we show that the top 20 global genes are
predictive of AMD clinical diagnosis. We also discovered functionally enriched
gene sets in the RPE-choroid that delineate the advanced AMD phenotypes,
neovascular AMD and geographic atrophy. Moreover, we identified a graded increase
of transcript levels in the retina related to wound response, complement cascade,
and neurogenesis that strongly correlates with decreased levels of
phototransduction transcripts and increased AMD severity. Based on our findings,
we assembled protein-protein interactomes that highlight functional networks
likely to be involved in AMD pathogenesis.
Conclusions
We discovered new global biomarkers and gene expression signatures of AMD. These
results are consistent with a model whereby cell-based inflammatory responses
represent a central feature of AMD etiology, and depending on genetics,
environment, or stochastic factors, may give rise to the advanced AMD phenotypes
characterized by angiogenesis and/or cell death. Genes regulating these
immunological activities, along with numerous other genes identified here,
represent promising new targets for AMD-directed therapeutics and diagnostics.
Please see related commentary:
http://www.biomedcentral.com/1741-7015/10/21/abstract