Systems genomics in age-related macular degeneration

Abstract

Genomic studies in age-related macular degeneration (AMD) have identified genetic variants that account for the majority of AMD risk. An important next step is to understand the functional consequences and downstream effects of the identified AMD-associated genetic variants. Instrumental for this next step are 'omics' technologies, which enable high-throughput characterization and quantification of biological molecules, and subsequent integration of genomics with these omics datasets, a field referred to as systems genomics. Single cell sequencing studies of the retina and choroid demonstrated that the majority of candidate AMD genes identified through genomic studies are expressed in non-neuronal cells, such as the retinal pigment epithelium (RPE), glia, myeloid and choroidal cells, highlighting that many different retinal and choroidal cell types contribute to the pathogenesis of AMD. Expression quantitative trait locus (eQTL) studies in retinal tissue have identified putative causal genes by demonstrating a genetic overlap between gene regulation and AMD risk. Linking genetic data to complement measurements in the systemic circulation has aided in understanding the effect of AMD-associated genetic variants in the complement system, and supports that protein QTL (pQTL) studies in plasma or serum samples may aid in understanding the effect of genetic variants and pinpointing causal genes in AMD. A recent epigenomic study fine-mapped AMD causal variants by determing regulatory regions in RPE cells differentiated from induced pluripotent stem cells (iPSC-RPE). Another approach that is being employed to pinpoint causal AMD genes is to produce synthetic DNA assemblons representing risk and protective haplotypes, which are then delivered to cellular or animal model systems. Pinpointing causal genes and understanding disease mechanisms is crucial for the next step towards clinical translation. Clinical trials targeting proteins encoded by the AMD-associated genomic loci C3, CFB, CFI, CFH, and ARMS2/HTRA1 are currently ongoing, and a phase III clinical trial for C3 inhibition recently showed a modest reduction of lesion growth in geographic atrophy. The EYERISK consortium recently developed a genetic test for AMD that allows genotyping of common and rare variants in AMD-associated genes. Polygenic risk scores (PRS) were applied to quantify AMD genetic risk, and may aid in predicting AMD progression. In conclusion, genomic studies represent a turning point in our exploration of AMD. The results of those studies now serve as a driving force for several clinical trials. Expanding to omics and systems genomics will further decipher function and causality from the associations that have been reported, and will enable the development of therapies that will lessen the burden of AMD.

Keywords: Age-related macular degeneration; Clinical trial; Complement system; Expression quantitative trait locus; Induced pluripotent stem cells; Omics; Polygenic risk scores; Single cell sequencing; Systems genomics; iPSc-RPE.

Fig 1.

Looking back facilitates a look forward to appreciate key elements in GWAS advances of aAMD research. Sample sizes (orange) of GWAS studies reveal an exponential growth, enabling the detection of additional AMD-associated loci (green), while effect sizes (black) of common variants are predicted to decrease sharply in the next few years. In addition, the number of common variants identified (dark blue) rose steeply from 2011 onwards due to the use of genotype imputation (Yu et al., 2011). The next significant transformation will take place with the introduction of whole genome sequencing (WGS), which, in combination with increasing sample sizes, will allow the unbiased identification of numerous rare genetic variants associated with the disease (light blue).

Fig 2.

(A) Single-nucleus RNAseq profiling of human ocular tissue identifies all major cell types in the retina, RPE, and choroid. (B) Expression from snRNAseq shows that the majority of candidate genes from the AMD GWAS are expressed in non-neuronal cells such as RPE, glia, myeloid, and choroidal cells.

Fig 3.

(A) Approach for estimating eQTL, using ocular tissue and expression of TRPM1 as an example. (B) Colocalization between GWAS statistics for risk of AMD, and eQTL in the RPE/choroid tissue suggest TRPM1 is the causal gene at this locus.

Fig 4.

iPSC-RPE can be used to prioritize and functionally characterize causal variants at AMD risk loci. iPSC-RPE from six subjects in the iPSCORE resource were generated and shown to have molecular and morphological characteristics similar to native RPE. We generated ATAC-seq, RNA-seq and H3K27ac ChIP-seq data from the iPSC-RPE. To fine map AMD risk loci we used fgwas to integrate these molecular phenotype data with AMD GWAS. rs943080 was identified as the probably causal variant in the VEGFA locus.