A mega-analysis of expression quantitative trait loci in retinal tissue

QTL mapping of human retina DNA methylation identifies 87 gene-epigenome interactions in age-related macular degeneration

DNA methylation provides a crucial epigenetic mark linking genetic variations to environmental influence. We have analyzed array-based DNA methylation profiles of 160 human retinas with co-measured RNA-seq and >8 million genetic variants, uncovering sites of genetic regulation in cis (37,453 methylation quantitative trait loci and 12,505 expression quantitative trait loci) and 13,747 DNA methylation loci affecting gene expression, with over one-third specific to the retina. Methylation and expression quantitative trait loci show non-random distribution and enrichment of biological processes related to synapse, mitochondria, and catabolism. Summary data-based Mendelian randomization and colocalization analyses identify 87 target genes where methylation and gene-expression changes likely mediate the genotype effect on age-related macular degeneration. Integrated pathway analysis reveals epigenetic regulation of immune response and metabolism including the glutathione pathway and glycolysis. Our study thus defines key roles of genetic variations driving methylation changes, prioritizes epigenetic control of gene expression, and suggests frameworks for regulation of macular degeneration pathology by genotype-environment interaction in retina.

Whole genome sequencing of 4,787 individuals identifies gene-based rare variants in age-related macular degeneration

Genome-wide association studies have contributed extensively to the discovery of disease-associated common variants. However, the genetic contribution to complex traits is still largely difficult to interpret. We report a genome-wide association study of 2394 cases and 2393 controls for age-related macular degeneration (AMD) via whole-genome sequencing, with 46.9 million genetic variants. Our study reveals significant single-variant association signals at four loci and independent gene-based signals in CFH, C2, C3, and NRTN. Using data from the Exome Aggregation Consortium (ExAC) for a gene-based test, we demonstrate an enrichment of predicted rare loss-of-function variants in CFH, CFI, and an as-yet unreported gene in AMD, ORMDL2. Our method of using a large variant list without individual-level genotypes as an external reference provides a flexible and convenient approach to leverage the publicly available variant datasets to augment the search for rare variant associations, which can explain additional disease risk in AMD.

Integrating genetic regulation and single-cell expression with GWAS prioritizes causal genes and cell types for glaucoma

Primary open-angle glaucoma (POAG), characterized by retinal ganglion cell death, is a leading cause of irreversible blindness worldwide. However, its molecular and cellular causes are not well understood. Elevated intraocular pressure (IOP) is a major risk factor, but many patients have normal IOP. Colocalization and Mendelian randomization analysis of >240 POAG and IOP genome-wide association study (GWAS) loci and overlapping expression and splicing quantitative trait loci (e/sQTLs) in 49 GTEx tissues and retina prioritizes causal genes for 60% of loci. These genes are enriched in pathways implicated in extracellular matrix organization, cell adhesion, and vascular development. Analysis of single-nucleus RNA-seq of glaucoma-relevant eye tissues reveals that the POAG and IOP colocalizing genes and genome-wide associations are enriched in specific cell types in the aqueous outflow pathways, retina, optic nerve head, peripapillary sclera, and choroid. This study nominates IOP-dependent and independent regulatory mechanisms, genes, and cell types that may contribute to POAG pathogenesis.

QTL mapping of human retina DNA methylation identifies 87 gene-epigenome interactions in age-related macular degeneration

DNA methylation (DNAm) provides a crucial epigenetic mark linking genetic variations to environmental influence. We analyzed array-based DNAm profiles of 160 human retinas with co-measured RNA-seq and > 8 million genetic variants, uncovering sites of genetic regulation in cis (37,453 mQTLs and 12,505 eQTLs) and 13,747 eQTMs (DNAm loci affecting gene expression), with over one-third specific to the retina. mQTLs and eQTMs show non-random distribution and enrichment of biological processes related to synapse, mitochondria, and catabolism. Summary data-based Mendelian randomization and colocalization analyses identify 87 target genes where methylation and gene-expression changes likely mediate the genotype effect on age-related macular degeneration (AMD). Integrated pathway analysis reveals epigenetic regulation of immune response and metabolism including the glutathione pathway and glycolysis. Our study thus defines key roles of genetic variations driving methylation changes, prioritizes epigenetic control of gene expression, and suggests frameworks for regulation of AMD pathology by genotype-environment interaction in retina.

The eQTL colocalization and transcriptome-wide association study identify potentially causal genes responsible for economic traits in Simmental beef cattle

BACKGROUND

A detailed understanding of genetic variants that affect beef merit helps maximize the efficiency of breeding for improved production merit in beef cattle. To prioritize the putative variants and genes, we ran a comprehensive genome-wide association studies (GWAS) analysis for 21 agronomic traits using imputed whole-genome variants in Simmental beef cattle. Then, we applied expression quantitative trait loci (eQTL) mapping between the genotype variants and transcriptome of three tissues (longissimus dorsi muscle, backfat, and liver) in 120 cattle.

RESULTS

We identified 1,580 association signals for 21 beef agronomic traits using GWAS. We then illuminated 854,498 cis-eQTLs for 6,017 genes and 46,970 trans-eQTLs for 1,903 genes in three tissues and built a synergistic network by integrating transcriptomics with agronomic traits. These cis-eQTLs were preferentially close to the transcription start site and enriched in functional regulatory regions. We observed an average of 43.5% improvement in cis-eQTL discovery using multi-tissue eQTL mapping. Fine-mapping analysis revealed that 111, 192, and 194 variants were most likely to be causative to regulate gene expression in backfat, liver, and muscle, respectively. The transcriptome-wide association studies identified 722 genes significantly associated with 11 agronomic traits. Via the colocalization and Mendelian randomization analyses, we found that eQTLs of several genes were associated with the GWAS signals of agronomic traits in three tissues, which included genes, such as NADSYN1, NDUFS3, LTF and KIFC2 in liver, GRAMD1C, TMTC2 and ZNF613 in backfat, as well as TIGAR, NDUFS3 and L3HYPDH in muscle that could serve as the candidate genes for economic traits.

CONCLUSIONS

The extensive atlas of GWAS, eQTL, fine-mapping, and transcriptome-wide association studies aid in the suggestion of potentially functional variants and genes in cattle agronomic traits and will be an invaluable source for genomics and breeding in beef cattle.

Mendelian Randomization and Transcriptome-Wide Association Analysis Identified Genes That Were Pleiotropically Associated with Intraocular Pressure

BACKGROUND

Intraocular pressure (IOP) is a major modifiable risk factor for glaucoma. However, the mechanisms underlying the controlling of IOP remain to be elucidated.

OBJECTIVE

To prioritize genes that are pleiotropically associated with IOP.

METHODS

We adopted a two-sample Mendelian randomization method, named summary-based Mendelian randomization (SMR), to examine the pleiotropic effect of gene expression on IOP. The SMR analyses were based on summarized data from a genome-wide association study (GWAS) on IOP. We conducted separate SMR analyses using Genotype-Tissue Expression (GTEx) and Consortium for the Architecture of Gene Expression (CAGE) expression quantitative trait loci (eQTL) data. Additionally, we performed a transcriptome-wide association study (TWAS) to identify genes whose cis-regulated expression levels were associated with IOP.

RESULTS

We identified 19 and 25 genes showing pleiotropic association with IOP using the GTEx and CAGE eQTL data, respectively. RP11-259G18.3 (P_SMR = 2.66 × 10^-6), KANSL1-AS1 (P_SMR = 2.78 × 10^-6), and RP11-259G18.2 (P_SMR = 2.91 × 10^-6) were the top three genes using the GTEx eQTL data. LRRC37A4 (P_SMR = 1.19 × 10^-5), MGC57346 (P_SMR = 1.19 × 10^-5), and RNF167 (P_SMR = 1.53 × 10^-5) were the top three genes using the CAGE eQTL data. Most of the identified genes were found in or near the 17q21.31 genomic region. Additionally, our TWAS analysis identified 18 significant genes whose expression was associated with IOP. Of these, 12 and 4 were also identified by the SMR analysis using the GTEx and CAGE eQTL data, respectively.

CONCLUSIONS

Our findings suggest that the 17q21.31 genomic region may play a critical role in the regulation of IOP.

Genome-wide analysis of genetic pleiotropy and causal genes across three age-related ocular disorders

Age-related macular degeneration (AMD), cataract, and glaucoma are leading causes of blindness worldwide. Previous genome-wide association studies (GWASs) have revealed a variety of susceptible loci associated with age-related ocular disorders, yet the genetic pleiotropy and causal genes across these diseases remain poorly understood. By leveraging large-scale genetic and observational data from ocular disease GWASs and UK Biobank (UKBB), we found significant pairwise genetic correlations and consistent epidemiological associations among these ocular disorders. Cross-disease meta-analysis uncovered seven pleiotropic loci, three of which were replicated in an additional cohort. Integration of variants in pleiotropic loci and multiple single-cell omics data identified that Müller cells and astrocytes were likely trait-related cell types underlying ocular comorbidity. In addition, we comprehensively integrated eye-specific gene expression quantitative loci (eQTLs), epigenomic profiling, and 3D genome data to prioritize causal pleiotropic genes. We found that pleiotropic genes were essential in nerve development and eye pigmentation, and targetable by aflibercept and pilocarpine for the treatment of AMD and glaucoma. These findings will not only facilitate the mechanistic research of ocular comorbidities but also benefit the therapeutic optimization of age-related ocular diseases.

The Role of Gene Expression Regulation on Genetic Risk of Age-Related Macular Degeneration

Age-related macular degeneration (AMD) is a major cause of irreversible vision loss in the elderly. It is a complex multifactorial disease that is caused by the cumulative impact of genetic predisposition, environmental stress, and advanced aging. Knowledge of genetic risk factors underlying AMD susceptibility has advanced rapidly in the past decade that can be largely credited to genome-wide association studies (GWAS) and next-generation sequencing (NGS) efforts. GWAS have identified 34 genetic risk loci for AMD; the majority of which are in the noncoding genome. Several lines of evidence suggest that a complex trait-associated variant is likely to regulate the gene expression (acting as expression quantitative trait loci (eQTLs)), and there is a significant enrichment of GWAS-associated variants within eQTLs. In the last two years, eQTL studies in AMD-relevant tissues have provided functional interpretation of several AMD-GWAS loci. This review highlights the knowledge gained to date and discusses future directions to bridge the gap between genetic predisposition and biological mechanisms to reap the full benefits of GWAS findings.

Systems genomics in age-related macular degeneration

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.

A genome-wide analysis of 340 318 participants identifies four novel loci associated with the age of first spectacle wear

Refractive errors, particularly myopia, are the most common eye conditions, often leading to serious visual impairment. The age of onset is correlated with the severity of refractive error in adulthood observed in epidemiological and genetic studies and can be used as a proxy in refractive error genetic studies. To further elucidate genetic factors that influence refractive error, we analysed self-reported age of refractive error correction data from the UK Biobank European and perform genome-wide time-to-event analyses on the age of first spectacle wear (AFSW). Genome-wide proportional hazards ratio analyses were conducted in 340 318 European subjects. We subsequently assessed the similarities and differences in the genetic architectures of refractive error correction from different causes. All-cause AFSW was genetically strongly correlated (rg = -0.68) with spherical equivalent (the measured strength of spectacle lens required to correct the refractive error) and was used as a proxy for refractive error. Time-to-event analyses found genome-wide significant associations at 44 independent genomic loci, many of which (GJD2, LAMA2, etc.) were previously associated with refractive error. We also identified six novel regions associated with AFSW, the most significant of which was on chromosome 17q (P = 3.06 × 10-09 for rs55882072), replicating in an independent dataset. We found that genes associated with AFSW were significantly enriched for expression in central nervous system tissues and were involved in neurogenesis. This work demonstrates the merits of time-to-event study design in the genetic investigation of refractive error and contributes additional knowledge on its genetic risk factors in the general population.

Transcriptomic and proteomic retinal pigment epithelium signatures of age-related macular degeneration

There are currently no treatments for geographic atrophy, the advanced form of age-related macular degeneration. Hence, innovative studies are needed to model this condition and prevent or delay its progression. Induced pluripotent stem cells generated from patients with geographic atrophy and healthy individuals were differentiated to retinal pigment epithelium. Integrating transcriptional profiles of 127,659 retinal pigment epithelium cells generated from 43 individuals with geographic atrophy and 36 controls with genotype data, we identify 445 expression quantitative trait loci in cis that are asssociated with disease status and specific to retinal pigment epithelium subpopulations. Transcriptomics and proteomics approaches identify molecular pathways significantly upregulated in geographic atrophy, including in mitochondrial functions, metabolic pathways and extracellular cellular matrix reorganization. Five significant protein quantitative trait loci that regulate protein expression in the retinal pigment epithelium and in geographic atrophy are identified - two of which share variants with cis- expression quantitative trait loci, including proteins involved in mitochondrial biology and neurodegeneration. Investigation of mitochondrial metabolism confirms mitochondrial dysfunction as a core constitutive difference of the retinal pigment epithelium from patients with geographic atrophy. This study uncovers important differences in retinal pigment epithelium homeostasis associated with geographic atrophy.

Vitronectin and Its Interaction with PAI-1 Suggests a Functional Link to Vascular Changes in AMD Pathobiology

The pathogenesis of age-related macular degeneration (AMD), a frequent disorder of the central retina, is incompletely understood. Genome-wide association studies (GWAS) suggest a strong contribution of genomic variation in AMD susceptibility. Nevertheless, little is known about biological mechanisms of the disease. We reported previously that the AMD-associated polymorphism rs704C > T in the vitronectin (VTN) gene influences protein expression and functional aspects of encoded vitronectin, a human blood and extracellular matrix (ECM) protein. Here, we refined the association of rs704 with AMD in 16,144 cases and 17,832 controls and noted that rs704 is carried exclusively by the neovascular AMD subtype. Interaction studies demonstrate that rs704 affects the ability of vitronectin to bind the angiogenic regulator plasminogen activator inhibitor 1 (PAI-1) but has no influence on stabilizing its active state. Western blot analysis and confocal imaging reveal a strong enrichment of PAI-1 in the ECM of cultured endothelial cells and RPE cell line ARPE-19 exposed to vitronectin. Large-scale gene expression of VTN and PAI-1 showed positive correlations and a statistically significant increase in human retinal and blood tissues aged 60 years and older. Our results suggest a mechanism by which the AMD-associated rs704 variant in combination with ageing may contribute to the vascular complications in AMD.

Machine Learning Prediction of Non-Coding Variant Impact in Human Retinal cis-Regulatory Elements

Purpose

Prior studies have demonstrated the significance of specific cis-regulatory variants in retinal disease; however, determining the functional impact of regulatory variants remains a major challenge. In this study, we utilized a machine learning approach, trained on epigenomic data from the adult human retina, to systematically quantify the predicted impact of cis-regulatory variants.

Methods

We used human retinal DNA accessibility data (ATAC-seq) to determine a set of 18.9k high-confidence, putative cis-regulatory elements. Eighty percent of these elements were used to train a machine learning model utilizing a gapped k-mer support vector machine-based approach. In silico saturation mutagenesis and variant scoring was applied to predict the functional impact of all potential single nucleotide variants within cis-regulatory elements. Impact scores were tested in a 20% hold-out dataset and compared to allele population frequency, phylogenetic conservation, transcription factor (TF) binding motifs, and existing massively parallel reporter assay data.

Results

We generated a model that distinguishes between human retinal regulatory elements and negative test sequences with 95% accuracy. Among a hold-out test set of 3.7k human retinal CREs, all possible single nucleotide variants were scored. Variants with negative impact scores correlated with higher phylogenetic conservation of the reference allele, disruption of predicted TF binding motifs, and massively parallel reporter expression.

Conclusions

We demonstrated the utility of human retinal epigenomic data to train a machine learning model for the purpose of predicting the impact of non-coding regulatory sequence variants. Our model accurately scored sequences and predicted putative transcription factor binding motifs. This approach has the potential to expedite the characterization of pathogenic non-coding sequence variants in the context of unexplained retinal disease.

Translational Relevance

This workflow and resulting dataset serve as a promising genomic tool to facilitate the clinical prioritization of functionally disruptive non-coding mutations in the retina.

Secondary analyses for genome-wide association studies using expression quantitative trait loci

Genome-wide association studies (GWAS) have successfully identified thousands of single nucleotide polymorphisms (SNPs) associated with complex traits; however, the identified SNPs account for a fraction of trait heritability, and identifying the functional elements through which genetic variants exert their effects remains a challenge. Recent evidence suggests that SNPs associated with complex traits are more likely to be expression quantitative trait loci (eQTL). Thus, incorporating eQTL information can potentially improve power to detect causal variants missed by traditional GWAS approaches. Using genomic, transcriptomic, and platelet phenotype data from the Genetic Study of Atherosclerosis Risk family-based study, we investigated the potential to detect novel genomic risk loci by incorporating information from eQTL in the relevant target tissues (i.e., platelets and megakaryocytes) using established statistical principles in a novel way. Permutation analyses were performed to obtain family-wise error rates for eQTL associations, substantially lowering the genome-wide significance threshold for SNP-phenotype associations. In addition to confirming the well known association between PEAR1 and platelet aggregation, our eQTL-focused approach identified a novel locus (rs1354034) and gene (ARHGEF3) not previously identified in a GWAS of platelet aggregation phenotypes. A colocalization analysis showed strong evidence for a functional role of this eQTL.

Seed sequence polymorphism rs2168518 and allele-specific target gene regulation of hsa-miR-4513

MicroRNAs (miRNAs) are small post-transcriptional regulators that offer promising targets for treating complex diseases. To this end, hsa-miR-4513 is an excellent candidate as this gene harbors within its conserved heptametrical seed sequence a frequent polymorphism (rs2168518), which has previously been associated with several complex phenotypes. So far, little is known about the biological mechanism(s) underlying these associations. In an initial step, we now aimed to identify allele-specific target genes of hsa-miR-4513. We performed RNA sequencing in a miRNA overexpression model in human umbilical vein endothelial cells transfected with separated hsa-miR-4513 alleles at rs2168518, namely hsa-miR-4513-G and hsa-miR-4513-A. Genes specifically regulated by the rs2168518 alleles were independently verified by quantitative reverse transcription PCR (qRT-PCR), western blot analysis and allele-specific miRNA binding via a luciferase reporter assay. By a text-based search publicly available databases such as Online Mendelian Inheritance in Man and Mouse Genome Informatics were utilized to link target genes of hsa-miR-4513 to previously described phenotypes. Overall, we identified 23 allele-specific hsa-miR-4513 target genes and replicated 19 of those independently via qRT-PCR. Western blot analysis and luciferase reporter assays conducted for an exemplary subsample further confirmed the allele-specific regulation of these genes by hsa-miR-4513. Remarkably, multiple allele-specific target genes identified are linked via text retrieval to several phenotypes previously reported to be associated with hsa-miR-4513. These genes offer promising candidates for ongoing research on the functional pathobiological impact of hsa-miR-4513 and its seed polymorphism rs2168518. This could give rise to therapeutic applications targeting this miRNA.

Assigning Co-Regulated Human Genes and Regulatory Gene Clusters

Elucidating the role of genetic variation in the regulation of gene expression is key to understanding the pathobiology of complex diseases which, in consequence, is crucial in devising targeted treatment options. Expression quantitative trait locus (eQTL) analysis correlates a genetic variant with the strength of gene expression, thus defining thousands of regulated genes in a multitude of human cell types and tissues. Some eQTL may not act independently of each other but instead may be regulated in a coordinated fashion by seemingly independent genetic variants. To address this issue, we combined the approaches of eQTL analysis and colocalization studies. Gene expression was determined in datasets comprising 49 tissues from the Genotype-Tissue Expression (GTEx) project. From about 33,000 regulated genes, over 14,000 were found to be co-regulated in pairs and were assembled across all tissues to almost 15,000 unique clusters containing up to nine regulated genes affected by the same eQTL signal. The distance of co-regulated eGenes was, on average, 112 kilobase pairs. Of 713 genes known to express clinical symptoms upon haploinsufficiency, 231 (32.4%) are part of at least one of the identified clusters. This calls for caution should treatment approaches aim at an upregulation of a haploinsufficient gene. In conclusion, we present an unbiased approach to identifying co-regulated genes in and across multiple tissues. Knowledge of such common effects is crucial to appreciate implications on biological pathways involved, specifically when a treatment option targets a co-regulated disease gene.

Learning from Fifteen Years of Genome-Wide Association Studies in Age-Related Macular Degeneration

Over the last 15 years, genome-wide association studies (GWAS) have greatly advanced our understanding of the genetic landscape of complex phenotypes. Nevertheless, causal interpretations of GWAS data are challenging but crucial to understand underlying mechanisms and pathologies. In this review, we explore to what extend the research community follows up on GWAS data. We have traced the scientific activities responding to the two largest GWAS conducted on age-related macular degeneration (AMD) so far. Altogether 703 articles were manually categorized according to their study type. This demonstrates that follow-up studies mainly involve "Review articles" (33%) or "Genetic association studies" (33%), while 19% of publications report on findings from experimental work. It is striking to note that only three of 16 AMD-associated loci described de novo in 2016 were examined in the four-year follow-up period after publication. A comparative analysis of five studies on gene expression regulation in AMD-associated loci revealed consistent gene candidates for 15 of these loci. Our random survey highlights the fact that functional follow-up studies on GWAS results are still in its early stages hampering a significant refinement of the vast association data and thus a more accurate insight into mechanisms and pathways.

Pleiotropic Locus 15q24.1 Reveals a Gender-Specific Association with Neovascular but Not Atrophic Age-Related Macular Degeneration (AMD)

Genome-wide association studies (GWAS) have identified an abundance of genetic loci associated with complex traits and diseases. In contrast, in-depth characterization of an individual genetic signal is rarely available. Here, we focus on the genetic variant rs2168518 in 15q24.1 previously associated with age-related macular degeneration (AMD), but only with suggestive evidence. In a two-step procedure, we initially conducted a series of association analyses to further delineate the association of rs2168518 with AMD but also with other complex phenotypes by using large independent datasets from the International AMD Genomics Consortium (IAMDGC) and the UK Biobank. We then performed a functional annotation with reference to gene expression regulation based on data from the Genotype-Tissue Expression (GTEx) project and RegulomeDB. Association analysis revealed a gender-specific association with male AMD patients and an association predominantly with choroidal neovascularization. Further, the AMD association colocalizes with an association signal of several blood pressure-related phenotypes and with the gene expression regulation of CYP1A1, a member of the cytochrome P450 superfamily of monooxygenases. Functional annotation revealed altered transcription factor (TF) binding sites for gender-specific TFs, including SOX9 and SRY. In conclusion, the pleiotropic 15q24.1 association signal suggests a shared mechanism between blood pressure regulation and choroidal neovascularization with a potential involvement of CYP1A1.