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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Vision Res. Author manuscript; available in PMC Mar 31, 2011.
Published in final edited form as:
PMCID: PMC2884392
NIHMSID: NIHMS150167

Convergence of linkage, gene expression and association data demonstrates the influence of the RAR-related orphan receptor alpha (RORA) gene on neovascular AMD: A systems biology based approach

Abstract

To identify novel genes and pathways associated with AMD, we performed microarray gene expression and linkage analysis which implicated the candidate gene, retinoic acid receptor-related orphan receptor alpha (RORA, 15q). Subsequent genotyping of 159 RORA single nucleotide polymorphisms (SNPs) in a family-based cohort, followed by replication in an unrelated case-control cohort, demonstrated that SNPs and haplotypes located in intron 1 were significantly associated with neovascular AMD risk in both cohorts. This is the first report demonstrating a possible role for RORA, a receptor for cholesterol, in the pathophysiology of AMD. Moreover, we found a significant interaction between RORA and the ARMS2/HTRA1 locus suggesting a novel pathway underlying AMD pathophysiology.

Keywords: Neovascularization, RORA, Single nucleotide polymorphisms, Haplotypes, Linkage, Microarray

1. Introduction

The etiology of age-related macular degeneration (AMD) has yet to be fully elucidated; nevertheless, it is clear that the development and progression of this complex, multifactorial disease may be influenced by several different pathways, including cholesterol and lipid metabolism. (for reviews, please see Javitt and Javitt 2009 and Ding 2009). Epidemiologic findings have indicated a role for lipid/cholesterol metabolism in the pathogenesis of AMD. (Klein et al. 1997; Baker et al. 2009; Tan et al. 2009) This is further supported by evidence that comes from studies showing that the use of cholesterol lowering drugs (statins) has a protective effect against the development of neovascular AMD and all types of AMD (Wilson et al. 2004; McGwin et al. 2005); however, others have found no significant association between use of these drugs and any AMD subtypes. (Klein et al. 2003b; van Leeuwen et al. 2003) Additionally, both in vivo and in vitro assays have implicated a role for cholesterol/lipid metabolism in the development of AMD. (Yamada et al. 2008; Sallo et al. 2009; Yu et al. 2009; for review please see Ding et al. 2009)

Genetic studies have similarly implicated several lipid/cholesterol metabolism and transport genes in the pathophysiology of early and/or advanced stages of AMD. For example, the genes toll-like receptor -3 and -4 (Zareparsi et al. 2005; Yang et al. 2008), apolipoprotein E (Klaver et al. 1998; Souied et al. 1998; Anderson et al. 2001; Schmidt et al. 2002; Baird et al. 2004; Zareparsi et al. 2004), ATP-binding cassette transporter (Allikmets et al. 1997; Allikmets 2000; Edwards et al. 2008) and the elongation of very long chain fatty acids-like 4 (Conley et al. 2005) have all been associated with risk of all AMD subtypes. However, these findings have not been replicated consistently. (Stone et al. 1998; De La Paz et al. 1999; Souied et al. 2000; Ayyagari et al. 2001; Guymer et al. 2001; Schultz et al. 2003; Haddad et al. 2006; DeAngelis et al. 2007; Despriet et al. 2008; Edwards et al. 2008; Allikmets et al., 2009; Cho et al., 2009; Edwards et al., 2009; Lewin 2009; Liew et al., 2009).

The variants most consistently associated with AMD are within the gene complement factor H (CFH) (1q32) and the locus containing the genes age-related maculopathy susceptibility 2 and HtrA serine peptidase 1 (ARMS2 and HTRA1) (10q26). (Edwards et al. 2005; Hageman et al. 2005; Haines et al. 2005; Jakobsdottir et al. 2005; Klein et al. 2005b; Rivera et al. 2005; Dewan et al. 2006; Li et al. 2006; Yang et al. 2006; DeAngelis et al. 2008) These genes have been shown to have large influences on AMD risk in populations of various ethnicities, with variants on 10q26 being the most strongly associated with the neovascular AMD subtype. (Fisher et al. 2005; Shuler, Jr. et al. 2007; Zhang et al. 2008) Despite their large influence on AMD risk, the combination of these genes alone is insufficient to correctly predict the development and progression of this disease (Jakobsdottir et al. 2009). While additional genes may be only minor players in terms of their contribution to the total genetic variance of AMD, effect size does not always correlate with the importance to pathogenesis of AMD. Additionally, because other loci do exist which have yet to be elucidated (Majewski et al. 2003; Seddon et al. 2003; Schick et al. 2003; Abecasis et al. 2004; Iyengar et al. 2004; Kenealy et al. 2004; Schmidt et al. 2004; Fisher et al. 2005; Jun et al. 2005), it is clear that the percent of genetic variance is not proportional to understanding the pathophysiology of disease or understanding gene-gene interactions. It may therefore be important to identify and characterize additional risk factors that may augment the value of known risk factors as prognostic tools in order to identify individuals that require closer follow-up and early intervention (Ware 2006; Jakobsdottir et al. 2009). Moreover, it is equally important to determine the mechanism of disease, not just risk factors, so that appropriate avenues for treatment may be identified and explored.

Retinoic acid receptor-related orphan receptor alpha (RORA) is one of three retinoid-related orphan receptors that compose a distinct subfamily of nuclear receptors (Hubbard et al. 2009). RORA is known to play a key role in the regulation of circadian rhythms, the development of cones, bone morphogenesis, angiogenesis, and pathways including immunity/inflammation, lipid metabolism, and cholesterol. (Besnard et al. 2001; Besnard et al. 2002; Boukhtouche et al. 2004; Boukhtouche et al. 2006; Zhu et al. 2006; Lau et al. 2008)

In vitro studies have identified cholesterol as a natural ligand of RORA (Kallen et al. 2002). In addition to binding cholesterol, RORA has also been shown to regulate lipoproteins, such as high density lipoprotein, serum amyloid A, and apolipoprotein A1. (Voyiaziakis et al. 1998; Migita et al. 2004; Lau et al. 2008) Further evidence for the role of RORA in cholesterol (“cholesteROR”) metabolism comes from phenotypic examination of the RORA deficient staggerer mouse (RORAsg) that displays an increased susceptibility to arteriosclerosis and dislipidemia. (Kopmels et al. 1991; Mamontova et al. 1998; Jetten and Ueda 2002; Boukhtouche et al. 2004; Lau et al. 2008)

If cholesterol/lipid transport and metabolism are involved in the pathophysiology of neovascular AMD, then genes that are intrinsic to these pathways may be differentially expressed between patients with neovascular AMD and their unaffected siblings. In order to identify novel candidate genes and pathways with biological relevance to AMD pathophysiology, we performed linkage analysis and gene expression microarray analysis on extremely discordant sibling pairs. An “extreme” sibling pair consists of one sibling with a trait value in the top 10% of disease severity and the other sibling with a trait value in the bottom 10% of disease severity. (Risch and Zhang 1995; Risch and Zhang 1996) Based on the results of these studies and biological plausibility in AMD etiology, the candidate gene RORA was chosen for further analysis. Any significant haplotypes identified in the family-based cohort of European descent were then tested in an unrelated case-control cohort from Central Greece.

2. Methods

2.1. Family patient population

The protocol was reviewed and approved by the Institutional Review Boards at Massachusetts Eye and Ear, Boston, Massachusetts and conforms to the tenets of the Declaration of Helsinki. Eligible patients were enrolled in this study after they gave informed consent, either in person, over the phone, or through the mail, before completing a standardized questionnaire and donating 10 to 50 ml of venous blood.

Details of the recruitment of the 196 sibling pairs, comprised mainly of individuals of European ancestry, are described elsewhere (DeAngelis et al. 2008) (Population characteristics are summarized in Supplementary Table 1). In brief, all index patients were aged 50 years or older, except where one individual was 49 years of age, and had the neovascular form of AMD in at least one eye, defined by subretinal hemorrhage, fibrosis, or fluorescein angiographic presence of neovascularization documented at the time of, or prior to, enrollment in the study. Patients whose only exudative finding was a retinal pigment epithelium detachment were excluded because this finding may not represent definite neovascular AMD. Patients with signs of pathologic myopia, presumed ocular histoplasmosis syndrome, angioid streaks, choroidal rupture, any hereditary retinal diseases other than AMD, and previous laser treatment due to retinal conditions other than AMD were also excluded.

Of the 196 sibling pairs, 150 were extremely phenotypically discordant. That is pairs where the unaffected siblings had normal maculae at an age older than that at which the index patient was first diagnosed with neovascular AMD. Normal maculae (defined as the zone centered at the foveola and extending 2 disc diameters, or 3000 microns, in radius) fulfilled the following criteria: 0–5 small drusen (all less than 63 microns in diameter), no pigment abnormalities, no geographic atrophy, and no neovascularization (as defined previously; AMD “category 1 or less” on the Age-Related Eye Disease Study (AREDS) scale). (AREDS Research Group 2000) Disease status of every participant was confirmed by at least two of the investigators by evaluation of fundus photographs or fluorescein angiograms except when one of the investigators directly examined an unaffected sibling during a home visit (n = 4 cases). Smoking data as measured in pack years was available for every participant.

An additional 46 discordant sibling pairs were analyzed where each pair was comprised of one sibling (the index sibling) with neovascular AMD and the other sibling (the control sibling) with mild or very early AMD [AREDS category 2 (AREDS Research Group 2000)] at 65 years of age or older in most cases. Siblings were categorized as early AMD only if they met the following criteria for the definition of AREDS category 2: small (<63 µm) drusen with total area ≥ 125 µm diameter circle, or at least 1 intermediate drusen (≥ 63 and < 125 µm) or presence of pigment. These criteria are based on published epidemiologic studies that indicate that elderly individuals with such maculae rarely go on to develop neovascular AMD during a 10-year follow-up. (Klein et al. 2002)

2.2. Unrelated case and control population

Replication of significant findings was performed on an unrelated case-control cohort from Central Greece that included patients without AMD, with early and intermediate dry AMD [AREDS category 2 (as described above) and AREDS category 3 (n = 84); intermediate drusen comprising total area ≥ 360 µm diameter circle in the presence of soft drusen or ≥656 µm diameter circle in absence of soft drusen, or at least 1 large druse (≥ 125μm), or non-Central geographic atrophy (AREDS Research Group 2000)] and with neovascular AMD (cases, n = 139) (Supplementary Table 1). These patients were recruited from the medical retina outpatient clinic at the University Hospital of Larissa, Greece. The diagnosis of macular degeneration was confirmed by optical coherence tomography and fluorescein angiography. Color fundus photographs and indocyanine green angiography were performed in some cases.

2.3. Microarray analysis

Total RNA isolates from transformed lymphocyte cell lines derived from 18 individuals (9 sibpairs) were prepared using RNAeasy kits (Qiagen, Valencia, CA). Each pair was matched for smoking history, age, sex, cardiovascular disease history, body mass index, hypertension, and hypercholesterolemia, factors that could influence gene expression levels. RNA quality was determined by analysis using agarose gel or an Agilent 2100 Bioanalyzer instrument (Agilent, Santa Clara, CA). Approximately 20 ug of RNA was submitted to amplification, labeled, and hybridized to human Affymetrix U133A 2.0 PLUS microarrays (Affymetrix, Santa Clara, CA) containing analytical elements corresponding to approximately 35,000+ genes.

For the gene expression microarray analysis, statistical analysis was performed using principal component analysis (PCA) to identify substantial differences between the affected and unaffected siblings. Further analysis was performed employing a statistical tool referred to as robust multichip analysis (RMA). This procedure entailed the following: 1) probe-specific correction of the probes using a model based on observed intensity being the sum of signal and (background) noise (Irizarry et al. 2003), 2) normalization of corrected perfect match probes using quantile normalization (Bolstad et al. 2003), 3) calculation of expression measures using median polish. Additional normalization was then applied to the summarized data. The local pooled error (LPE) test was then applied to search for differentially expressed genes. The LPE approach is similar to the Significance Analysis of Microarrays (SAM) method (Tusher et al. 2001) and the B-statistic (Lonnstedt and Speed 2001). To account for the multiple testing issue inherent to analysis of data from microarray experiments, Bonferroni correction was used to control for the family wise error rate equal to 0.05. Our results were further confirmed using a second summarizing method, which is a variation of the RMA called GCRMA. (Wu 2004) Analysis was completed using S+arrayanalyzer 2.0 from Insightful (http://www.insightful.com).

Ingenuity Pathway Software (Ingenuity Systems, Inc., Redwood City, CA) was used to analyze gene function and pathways/networks of significant microarray genes using probe names and fold differences between affected siblings compared to their unaffected siblings.

2.4. Real-time quantitative polymerase chain reaction (qRT-PCR)

Total RNA was isolated from 32 index patients and 35 unaffected control samples that were part of the extremely discordant sibpair cohort analyzed in both the gene expression and linkage studies, using Trizol (Invitrogen, Carlsbad, CA). Eighty ng of total RNA was reverse transcribed using SuperScript III First-Strand Synthesis SuperMix (Invitrogen). One µl of cDNA sample, and 0.5 µl probe were used in a 10 µl PCR reaction, and five replicates were performed for each probe using Taqman Gene Expression Master Mix (Applied Biosystems, Foster City, CA). Premade Applied Biosystems (ABI) probes labeled with FAM were used to amplify RORA (ABI, hs00933986_m1, hs01387931_m1, hs01387932_m1) and β-actin (ABI, hs99999903_m1). Reactions were quantified using an ABI 7500 Real Time PCR instrument and analyzed with accompanying software. Relative expression levels were determined by normalizing cycle threshold values for each primer to the amount of β-actin expressed (1000/2^(Ct-gene-Ct-: β-actin). Relative fold change was calculated from normalized values. Significant expression differences were assessed by the student’s paired T-Test.

2.5. Genotyping of microsatellite markers

For the genotyping of microsatellite markers, the Sequenom iPLEX system technology, and direct sequencing protocols, leukocyte DNA was either purified by using standard phenol-chloroform or DNAzol (Invitrogen Corporation, Carlsbad, California) extraction protocols. Using 133 extremely discordant sibling pairs, we analyzed 18 highly heterozygous microsatellite markers spanning 34 megabases of the 15q21-22 region (Supplementary Table 2). These markers included several that were in the vicinity of RORA. All markers were fluorescently labeled with either 5-carboxyfluorescein or 6-carboxyfluorescein on the 5’ end of the reverse primer and an additional sequence of CTGTCTT was added to the 5’ end of the forward primer. PCR was used to amplify genomic DNA fragments from 20 ng of leukocyte DNA in a solution of 10X PCR buffer containing 25 mmol/L of MgCl2; 0.2 mmol/L each of deoxyadenosine triphosphate, deoxythymidine triphosphate, deoxyguanosine triphosphate, and deoxycytidine triphosphate; and 0.5 U of Taq DNA polymerase (USB, Cleveland, OH). PCR cycling conditions were as follows, 95°C for 5 minutes, followed by 35 cycles of 54°C to 60°C (specific to primer pair) for 30 seconds, 72°C for 30 seconds, and 95°C for 30 seconds, with a final annealing at 54°C to 60°C (specific to primer pair) for 1.5 minutes and extension of 72°C for 5 minutes. Polymerase chain reaction products were diluted 1:20 for markers labeled with FAM and 1:10 for markers labeled with HEX. Samples were pooled according to product size and denatured before being genotyped on the ABI 3730xl DNA Analyzer (Applied Biosystems). Data were then analyzed using ABI’s Genemapper 3.7 software, which interrogates the quality of the size standard and makes the appropriate genotype calls based on size. For quality control purposes, all genotypes were then evaluated manually.

For linkage analysis of the 18 microsatellite markers, identity-by-state (IBS) scores were calculated from the number of alleles (0, 1 or 2) shared between each pair, the index and the discordant sibling, for each of the 18 markers. Using heterozygosities for each marker obtained from Map-O-Mat (http://compgen.rutgers.edu/mapomat/), the expected IBS (null hypothesis of no linkage) was calculated and then compared with the observed IBS values. A goodness of fit test was applied to assess the significance of the difference between the observed and expected distribution. This method has been used previously for linkage analysis in sibling pairs (DeAngelis et al. 2008)

2.5. Genotyping analysis

RORA is located on chromosome 15q and spans approximately 730 kilobases. We analyzed SNP location in terms of the largest of 4 transcripts, which encodes 12 exons as shown in ENSEMBL (RORA-001: ENST00000335670) (http://www.ensembl.org/index.html). Single nucleotide polymorphisms (SNPs) were chosen for analysis at approximately every 5,000 base pairs (when variation information was available) in an effort to represent the entire variation within the gene (Supplementary Table 2). Based on the location of SNPs and haplotypes found to be significantly associated with neovascular AMD, 11 TagSNPs were chosen for genotyping using the HapMap (http://www.hapmap.org/) and meeting the following criteria: 1) a minor allele frequency greater than 10% and 2) an r2 value that was at least 0.8. (Supplementary Table 2).

Multiplex PCR assays were designed using Sequenom SpectroDESIGNER software (version 3.0.0.3) (Sequenom, San Diego, CA) by inputting sequence containing the SNP site and 100 base pairs of flanking sequence on either side of the SNP. Briefly, 10 ng genomic DNA was amplified in a 5 ul reaction containing 1X HotStar Taq PCR buffer (Qiagen, Valencia, CA), 1.625 mM MgCl2, 500 uM each dNTP, 100 nM each PCR primer, 0.5 U HotStar Taq (Qiagen). The reaction was incubated at 94°C for 15 minutes followed by 45 cycles of 94°C for 20 seconds, 56°C for 30 seconds, 72°C for 1 minute, followed by 3 minutes at 72°C. Excess dNTPs were removed from the reaction by incubation with 0.3 U shrimp alkaline phosphatase (USB, Cleveland, OH) at 37°C for 40 minutes followed by a 5 minute incubation at 85°C to deactivate the enzyme. Single primer extension over the SNP was carried out in a final concentration of between 0.625 uM and 1.5 uM for each extension primer (depending on the mass of the probe), iPLEX termination mix (Sequenom), and 1.35 U iPLEX enzyme (Sequenom), and cycled using a two-step 200 short cycles program; 94°C for 30 seconds followed by 40 cycles of 94°C for 5 seconds, 5 cycles of 52°C for 5 seconds, and 80°C for 5 seconds, then 72°C for 3 minutes. The reaction was then desalted by addition of 6 mg cation exchange resin followed by mixing and centrifugation to settle the contents of the tube. The extension product was then spotted onto a 384 well SpectroCHIP (Sequenom) before being flown in the MALDI-TOF mass spectrometer. Data was collected, real time, using SpectroTYPER Analyzer 3.3.0.15, SpectraAQUIRE 3.3.1.1 and SpectroCALLER 3.3.0.14 (Sequenom). To ensure data quality, genotypes for each subject were also checked manually.

For some replicate samples, direct sequencing was performed. For these reactions, oligonucleotide primers were selected using the Primer3 program (http://primer3.sourceforge.net/) to encompass the SNP and flanking intronic sequences.

All PCR assays were performed using genomic DNA fragments from 20 ng of leukocyte DNA in a solution of 10X PCR buffer containing 25 mM of MgCl2, 0.2 mM each of dATP, dTTP, dGTP, and dCTP, and 0.5 U of Taq DNA polymerase (USB Corporation, Cleveland, OH). Five molar betaine was added to the reaction mix for rs2414687 (Sigma-Aldrich, St. Louis, MO). The temperatures used during the polymerase chain reaction were as follows: 95°C for 5 minutes followed by 35 cycles of 58°C for 30 seconds, 72°C for 30 seconds and 95°C for 30 seconds, with a final annealing at 58°C for 1.5 minutes and extension of 72°C for 5 minutes. For sequencing reactions, PCR products were digested according to manufacturer's protocol with ExoSAP-IT (USB Corporation, Cleveland, OH) then were subjected to a cycle sequencing reaction using the Big Dye Terminator v3.1 Cycle Sequencing kit (Applied Biosystems, Foster City, CA) according to manufacturer's protocol. Products were purified with Performa DTR Ultra 96-well plates (Edge Biosystems, Gaithersburg, MD) in order to remove excess dye terminators. Samples were sequenced on an ABI Prism 3100 DNA sequencer (Applied Biosystems). Electropherograms generated from the ABI Prism 3100 were analyzed using the Lasergene DNA and protein analysis software (DNASTAR, Inc., Madison, WI). Electropherograms were read by two independent evaluators without knowledge of the subject's disease status. All patients were sequenced in the forward direction (5' to 3'), unless variants or polymorphisms were identified, in which case confirmation was obtained in some cases by sequencing in the reverse direction.

Testing of association between SNPs and AMD in the 196 sibling pairs was done using the family-based association test (FBAT) (http://biosun1.harvard.edu/~fbat/fbat.htm). SNPs were tested for association using the minor allele, as defined by the allele occurring less frequently in the unaffected siblings. Alleles were tested under three genetic models: additive, dominant and recessive. SNPs were only included for analysis in FBAT if the minor allele frequency (MAF) in the affected and unaffected siblings combined was greater than or equal to 5% and the number of informative families was at least 4. Linkage disequilibrium (LD) (both r2 and D’) between each of the SNPs was determined using the program Haploview (http://www.broad.mit.edu/mpg/haploview/). Haplotype blocks were constructed in Haploview using the method proposed by Gabriel et al. (Gabriel et al. 2002) Individual haplotypes were inferred and tested for association with AMD using the program FBAT. In order to correct for multiple testing in FBAT, the permutation test was used to examine each of the resulting haplotypes.

Genotype and allele frequencies for all SNPs identified as significant, either individually or as part of a haplotype, were calculated in affected and separately in unaffected individuals. Deviation from Hardy-Weinberg Equilibrium was tested on each SNP using the chi square test.

Risk factors were controlled for using conditional logistic regression performed using SAS (SAS, version 9.1; SAS Institute Inc, Cary, NC). Included in this analysis were those SNPs identified as significantly associated with neovascular AMD and known risk factors. Known risk factors for the extremely discordant sibling pair cohort included smoking history and the genetic variants CFH rs1061170 (Y402H) and ARMS2/HTRA1 rs10490924/rs11200638 (DeAngelis et al. 2008; Zhang et al. 2008). Conditional logistic regression was also used to test gene-gene interaction between RORA SNPs identified as significantly associated with AMD and the CFH and the ARMS2/HTRA1 loci individually. Similarly, conditional logistic regression was used to test gene-environment interaction between RORA and smoking.

For replication in the unrelated case-control cohort from Central Greece, single SNP analysis and haplotype analysis was performed using unconditional logistic regression (UCLR) in SAS (SAS, version 9.1; SAS Institute Inc, Cary, NC) under the same three genetic models: additive, dominant, and recessive. Linkage disequilibrium was also tested using Haploview.

2.6. Expression quantitative trait loci analysis

Using the publicly available expression quantitative trait loci (eQTL) database mRNA by SNP Browser v 1.0.1 (Dixon et al. 2007; Moffatt et al. 2007), we investigated the association between eQTLs and the RORA SNPs that were identified as significant either individually or as part of a haplotype.

3. Results

3.1. Patient population

We recruited a total of 196 sibling pairs, 150 of which were extremely discordant sibling pairs (one sibling with neovascular AMD and one normal sibling - AREDS category 1 or less) and the remaining 46 were discordant, meaning one sibling had neovascular AMD and the other sibling had early dry, AMD (AREDS category 2) (Supplementary Table 1). The mean ± SD age of the affected siblings (neovascular AMD) was 72.1 ± 8.0 years (age range, 49.0–92.0 years), the age of the mildly affected siblings (dry AMD) was 77.4 ± 7.0 years (age range, 58.2–89.1 years), and the age of the unaffected siblings was 76.4 ± 7.8 years (age range, 50.3–94.3 years). Forty-one percent of the unaffected siblings, 30% of the dry AMD siblings and 43% of the matching affected siblings were male. All participants were white and mostly of European descent.

The cohort from Central Greece consisted of a total of 344 patients: 121 normal controls, 84 early dry patients (AREDS category 2 and 3), and 139 neovascular patients (Supplementary Table 1). The mean ± SD age of the affected subjects (neovascular AMD) was 76.2 ± 7.4 years (age range, 49.0–94.0 years), the age of the mildly affected subjects (dry AMD) was 74.5 ± 7.8 years (age range, 52.0–91.0 years), and the age of the unaffected subjects was 73.5 ± 7.3 years (age range, 48.0–88.0 years). Fifty-one percent of the unaffected subjects, 44% of the AREDS category 2 and AREDS category 3 AMD subjects and 45% of the neovascular subjects were male. All participants were white and from Central Greece.

3.2. Gene expression analysis

We compared microarray data from 9 extremely discordant sibling pairs that had been matched for smoking history, age, sex, cardiovascular disease history, body mass index, hypertension, and hypercholesterolemia. To create a short list of candidate genes for further study, we used Ingenuity Pathway Analysis (IPA) software to investigate known functions and pathways of statistically significant genes that were identified by either LPE or GCRMA and had at least a 2 fold difference in expression levels. To focus our studies, we concentrated on the IPA-generated network that encompassed the greatest number of genes (Fig. 1 and Supplementary Table 3). Within this network, the individual genes that were identified by LPE and GCRMA are chemokine (C-X-C motif) ligand 13 (CXCL13), interleukin 1 alpha (IL1A), matrix metallopeptidase 7 (MMP7), plakophilin 2 (PKP2), phospholipase A2 group IVA (PLA2G4A), NLR family, pyrin domain containing 2 (NLRP2), regulator of G-protein signaling 13 (RGS13), roundabout, axon guidance receptor, homolog 1 (Drosophila) (ROBO1), RAR-related orphan receptor A (RORA), ribosomal protein S6 kinase, 90kDa, polypeptide 2 (RPS6KA2) (Table 1). This set of genes was simultaneously analyzed with linkage data previously obtained from our laboratory to investigate genomic convergence (Table 1).

Fig. 1
IPA-generated network containing microarray genes that were identified as significant and that showed a greater than two fold difference when comparing neovascular AMD patients and their unaffected siblings. The molecules which are colored are those that ...
Table 1
Convergence of gene expression and genomic data.

Of these genes, RORA was selected for further study due to its anti-angiogenic properties (Boukhtouche et al. 2004; Chauvet et al., 2004; Chauvet et al., 2005), the statistically different expression between affected patients compared to their unaffected siblings, and linkage data (see section 3.3.) demonstrating an association of the 15q region with neovascular AMD. Specifically, 4 RORA probes were identified as significantly altered in AMD versus control samples. Three of these probes showed decreased expression in AMD patients (p-value ranged from 10−3 to 10−9 after Bonferonni correction) while 1 probe showed increased expression in affected patients (p = 10−4 after Bonferonni correction).

In order to confirm the results of the microarray studies, qRT-PCR analysis was performed on RNA from neovascular AMD patients (n = 32) and their unaffected control siblings (n = 35), which included RNA from 7 of the 9 original pairs used for the gene expression microarray analysis. The 3 RNA probes used showed a trend of decreased RORA expression in this cohort (> 1.5 fold; data not shown). Specifically, 5 of the families showed statistically significant reduction in RORA gene expression ranging from 2-fold reduction to as high as 16-fold reduction in an AMD patient compared to their respective sib pair, p < 0.04 (Fig. 2).

Fig 2
Quantitative real time-PCR analysis reveals reduction of RORA expression in AMD patients of the extremely discordant sibling pairs. The graph represents data from 5 families depicting reduction of RORA expression in AMD patients relative to their respective ...

3.3. Linkage analysis using microsatellite markers

Calculation of identity-by-state scores from the genotyping results of 18 highly heterozygous microsatellite markers in the 15q region identified 3 markers, D15S1015, D15S209, and D15S214, that were modestly associated with neovascular AMD (p < 0.05) (Table 2). The most significantly associated marker, D15S117 (p = 0.01), is located approximately 2 megabases from the gene end (RORA: ENSG00000069667) (Supplementary Table 2).

Table 2
Chromosome 15 microsatellite markers.

3.4. Analysis of RORA SNPs and haplotypes in the extremely discordant sibling pair cohort

In total, we identified 92 SNPs in the RORA gene demonstrating variation in our extremely discordant sibling pair cohort (discovery cohort) (n = 150 pairs; 300 subjects) (for SNPs and location refer to Supplementary Table 2). No significant deviations from Hardy-Weinberg equilibrium for any of the variants studied were observed in either affected or unaffected siblings, suggesting unlikely contamination of our dataset. Single SNP analysis using FBAT in our discovery cohort identified rs12591914 and rs4335725, variants located within intron 1 of the RORA-001 transcript (ENST00000335670), as modestly (p = 0.029) and significantly (p = 0.0029) associated under a recessive model respectively (Table 3). The RORA SNP rs4335725 remained significant (p ≤ 0.007) after controlling for the following factors: CFH rs1061170 (Y402H), ARMS2/HTRA1 rs10490924/rs11200638, and smoking history in a multiple logistic regression model; however, the rs12591914 SNP did not remain significant (data not shown).

Table 3
FBAT analysis of RORA SNPs in the extremely discordant sibling pair cohort (n = 150).

Haploview, using haplotype blocks defined by the Gabriel rule (Gabriel et al. 2002), demonstrated that there were 13 haplotype blocks spanning the more than 700,000 base pairs covered by genotyping (Supplementary Figs. 1 and 2, Supplementary Table 2). Of the 13 haplotype blocks, 2 blocks, both located in intron 1 and comprising 3 haplotypes, were shown to be significantly associated with neovascular AMD risk in FBAT [h3 in block 1 (GCG) under both additive (p = 0.0128) and dominant (p = 0.0062) genetic models, as well as h2 in block 4 (AA) under a recessive (p = 0.0008) genetic model (Fig. 3 and Table 3)]. The overall permutations for the first haplotype in block 1 under both an additive and a dominant model was p = 0.03 and p = 0.02, respectively. The overall permutation for the second haplotype block was p = 0.0018 under a recessive model. Conservation analysis showed that the SNPs comprising these 2 haplotypes blocks (rs730754, rs8034864, rs12900948, rs17237514 and rs4335725) (Fig. 3) are all well conserved in both rat and mouse. Genotype and allele frequencies for these 5 SNPs are given in Table 5. Based on these findings, we chose 11 tagging SNPs within intron 1 to further capture variation and refine this region, which is approximately 550 kilobases, for further study. Statistical analysis using FBAT showed that none of the RORA intron 1 tagging SNPs were informative individually or as part of a haplotype as they did not remain significantly associated with neovascular AMD after correction for multiple testing.

Fig. 3
Linkage disequilibrium plots for the extremely discordant sibling cohort (n = 150 sibling pairs). Haplotype blocks were constructed in Haploview using the method proposed by Gabriel et al. (Gabriel et al. 2002) Boxes were shaded increasingly darker to ...
Table 5
Genotype and allele frequencies.

3.5. Analysis of RORA SNPs and haplotypes in the AREDS category 2 discordant sibling pair cohort

The 5 SNPs that comprised the 2 haplotype blocks containing significant haplotypes in the discovery cohort (rs730754, rs8034864, rs12900948, for block 1 and rs17237514 and rs4335725 for block 4) were tested for association in the AREDS category 2 discordant sibling pair cohort where the index patient had the neovascular form of AMD and the matched sibling had the early/dry form of AMD (AREDS category 2). Single SNP analysis of these 5 SNPs using FBAT showed that one SNP, rs12900948, was modestly associated with decreased risk of developing neovascular AMD under a recessive genetic model (p = 0.034) (Table 6). This SNP, like rs4335725, is also located in intron 1 of the RORA-001 transcript (ENST00000335670) and is also well conserved.

Table 6
FBAT analysis of RORA SNPs in the AREDS category 2 discordant sibling pair cohort (n = 46 pairs).

Haploview was used to create LD plots for this cohort (Fig. 4). Like the extremely discordant sibling pairs, applying the Gabriel rule demonstrated that block 1 containing SNPs rs730754, rs8034864 and rs12900948 was the same between both sibling pair cohorts studied (Fig. 3 and Fig. 4). However, the second haplotype block identified in the initial discovery cohort of extremely discordant sibling pairs was not found in the AREDS category 2 discordant sibling pair cohort. This may be due to the much smaller sample size analyzed (n = 46 discordant sibling pairs). FBAT analysis of these 2 haplotype blocks in the AREDS category 2 discordant sibling pair cohort demonstrated that 1 haplotype (ACA) within this block was modestly associated with neovascular AMD risk (p = 0.0492). However, after permutation testing this finding was no longer significant (p = 0.114). (Supplementary Table 4).

Fig. 4
Linkage disequilibrium plots for the AREDS 2 discordant sibling cohort (n = 46 sibling pairs). Haplotype blocks were constructed in Haploview using the method proposed by Gabriel et al. (Gabriel et al. 2002) Boxes were shaded increasingly darker to represent ...

3.6. Analysis of RORA SNPs and haplotypes in the Greek cohort

The SNPs that comprised the significant haplotypes (rs730754, rs8034864, rs12900948, for block 1 and rs17237514 and rs4335725 for block 4) in the discovery cohort were genotyped and tested for association in the Greek population (n = 344) using unconditional logistic regression. This analysis showed that only rs12900948 was significantly associated with neovascular AMD when comparing neovascular AMD patients to normal patients and separately to patients with early and intermediate dry AMD (AREDS category 2 and category 3) under either a dominant or recessive model (Table 7). Specifically, the G allele (which is the minor allele for both family-based cohorts but the major allele for the Greek cohort) of rs12900948 increased risk of neovascular AMD in the unrelated case-control cohort by 4-fold and 3.8-fold when compared to normal patients and separately to patients with dry AMD respectively (OR: 4.028; 95% C.I.: 1.924, 8.433; p = 0.0002 and OR: 3.802; 95% C.I.: 1.725, 8.379; p = 0.0009). When we compared the G allele of rs12900948 in normal controls (AREDS category 1 or less) to all subtypes of AMD in this unrelated case-control cohort, this finding was much more modestly associated (OR: 2.020; 95% C.I.: 1.172, 3.480; p = 0.0113).

Table 7
UCLR analysis of RORA SNPs in the Greek cohort.

Haploview analysis using the Gabriel rule showed that there was a single haplotype block in the Greek unrelated case-control cohort (Fig. 5). This haplotype block, containing SNPs rs730754, rs8034864, rs12900948, was common to the cohort from Central Greece and both family-based cohorts studied (Fig. 3, Fig. 4, and Fig. 5). While SNPs rs17237514 and rs4335725 comprised a haplotype block for the initial discovery family-based cohort of extremely discordant sibling pairs, these SNPs did not comprise a second block (block 4) in the unrelated case-control cohort from Central Greece. Nonetheless, both blocks initially identified in the discovery cohort were tested in unconditional logistic regression in the unrelated case-control cohort. In the Greek population, the single haplotype block identified by the Gabriel rule in Haploview was significantly associated with AMD risk. Specifically, when either comparing neovascular patients to unaffected patients or separately, to dry patients, the h2 (GAG) haplotype was significantly associated with AMD risk under a dominant model (OR: 1.470; 95% C.I.: 1.148,1.882; p = 0.0022 and OR: 1.584; 95% C.I.:1.204,2.085; p = 0.0010, respectively ) (Table 7). A second, more modestly associated haplotype, h3 (GCG), in this same block (block 1), was also identified under a dominant model for both the comparison of neovascular patients to normal subjects and separately for neovascular patients compared to subjects with dry AMD (AREDS category 2 and category 3) (OR: 1.639; 95% C.I.: 1.032,2.603; p = 0.0363 and OR: 1.718; 95% C.I.:1.01,2.905; p = 0.0432, respectively)

Fig. 5
Linkage disequilibrium plots for unrelated case-control cohort from Central Greece. Haplotype blocks were constructed in Haploview using the method proposed by Gabriel et al. (Gabriel et al. 2002) Boxes were shaded increasingly darker to represent higher ...

3.7. Interaction of RORA SNPs with CFH and ARMS2/HTRA1

Using conditional logistic regression, interaction was tested between RORA and CFH, ARMS2/HTRA1 and smoking in the discovery cohort of 150 extremely discordant sibling pairs. No significant interaction was found between RORA and CFH and separately between RORA and smoking history. A significant interaction was found between the RORA SNP rs12900948 and the ARMS2/HTRA1 SNPs rs10490924, rs11200638, and rs1049331 (p = 0.0044, 0.0044 and 0.0038 respectively). Based on this data, we incorporated HTRA1 into the network pathway analysis that included RORA using IPA’s “Path Designer” function to explore a hypothetical molecular means of interaction (Fig. 6). The addition of HTRA1 introduced the following genes: bone morphogenetic protein 4 (BMP4), family with sequence similarity 46, member A (FAM46A), fibronectin 1 (FN1), growth differentiation factor 5 (GDF5), interleukin 13 (IL13), matrix metallopeptidase 3 (MMP3), matrix metallopeptidase 1 (MMP1), serpin peptidase inhibitor, clade A, member 1 (SERPINA1), transforming growth factor, beta 2 (TGFβ2), transforming growth factor, beta 3 (TGFβ3) into the analysis (Supplementary Table 5). ARMS2 was not included in network analysis as it was not available by IPA’s database.

Fig. 6
IPA-generated network containing microarray genes that were identified as significant and that showed a greater than two fold difference when comparing neovascular AMD patients and their unaffected siblings with the addition of HTRA1 and HTRA1 interacting ...

3.8. eQTL analysis

Increasingly, data from GWAS and microarray studies have been analyzed in combination to uncover expression quantitative trait loci (eQTL) that relate specific SNPs to global or tissue specific expression of gene transcripts. (Cookson et al. 2009) Using the publicly available eQTL database mRNA by SNP Browser v 1.0.1 (Dixon et al. 2007; Moffatt et al. 2007), we investigated the association of the RORA SNPs that comprised our significant haplotypes with eQTLs. Of our 5 SNPs, rs8034864, rs730754, and rs4335725 were present in the database but none were significantly associated with transcript expression according to the method for calculating significance defined by Dixon et. al. (Supplementary Table 6). The interaction between the RORA SNP rs12900948 and the ARMS2/HTRA1 SNPs led us to investigate the association of these SNPs, rs10490924, rs11200638, and rs1049331, with transcript expression. Of the ARMS2/HTRA1 SNPs, only rs10490924 was present in the database but was not significantly associated with the expression of any transcripts (Supplementary Table 6).

4. Discussion

In this study, we demonstrate an association between RORA and AMD. Using a family based cohort comprised of extremely discordant sibling pairs, we identified a single RORA SNP, rs4335725, and 2 haplotypes which were significantly associated with neovascular AMD in FBAT. Study of a smaller discordant sibling population [where the index patient had neovascular AMD and the “control sibling” had a mild dry form of AMD (AREDS category 2)] identified a second SNP, rs12900948, as being modestly associated with neovascular AMD. The rs12900948 SNP was part of a haplotype (GCG) that was identified as significantly associated with neovascular AMD risk in the initial discovery cohort of extremely discordant sibling pairs in FBAT. In a separate unrelated case-control cohort from Central Greece, we also identified rs12900948 and two haplotypes containing this SNP (GAG and GCG) as associated with neovascular AMD when compared to either unrelated controls or to unrelated subjects with dry AMD (ARED category 2 and 3). Moreover both the rs12900948 and the significant haplotype (rs730754, rs8034864 and rs12900948) that contained this SNP were validated prospectively in nested case-control cohorts from the Nurses’ Health Study and the Health Professionals Follow-up Study (D. Schaumberg et al., personal communication).

It is interesting to note that rs12900948 was significant when comparing neovascular patients to patients with the dry form of AMD in both the family-based cohort and in the unrelated case-control cohorts from Central Greece. This may indicate that the risk associated with rs129000948, or as yet to be discovered variants in LD with rs129000948, may specifically relate to the development of neovascular/advanced AMD.

The significant RORA variants and haplotypes associated with neovascular AMD in both the family-based and unrelated case-control cohorts occur within the first intron of the RORA-001 transcript (ENST00000335670), a region that is well conserved across species, including mouse and rat. Although there is no apparent functional change, it is interesting to speculate that these or other undiscovered variations in intron 1, such as an insertion or deletion resulting in a change in copy number, may change the structure of the transcript and/or the sequence of unidentified modifying elements (eg. silencers or enhancers). (Lupski, 2007; Hastings et al., 2009) In turn, these variations could theoretically influence gene expression by altering modifying elements, increasing/decreasing RNA transcript stability, or affecting splicing with a resultant change in isoform expression. (Hollams et al. 2002; Maddox et al. 2008; Margulies and Birney 2008)

However, it is most likely that the causal sequence change(s) in this region has yet to be identified as suggested by analysis of the significant haplotypes. For example, the haplotype containing SNP rs4335725 was more significantly associated with risk of neovascular AMD than rs4335725 alone, suggesting that the causal variant(s) is likely in LD with this region. Additionally, SNP rs12900948 was significantly associated with neovascular AMD risk in the discovery cohort as part of a haplotype but not individually. To begin to resolve these questions, further sequencing of the exons and the acceptor/donor splice sites adjacent to this region as well as functionally evaluating each sequence variant for its influence on gene expression is currently being conducted.

Included in our study is expression analysis of RORA in lymphoblastoid cell lines. Initial microarray data showed significant changes in both directions, with the majority of probes indicating decreased expression in affected patients. When evaluating an expanded population (n = 67) with qRT-PCR to clarify and validate the finding of the gene expression microarray analysis, we observed an overall trend of decreased RORA expression in affected patients compared to their unaffected siblings, with statistically significant reduction in RORA gene expression in 5 of these families. A limitation of these expression studies is that they did not assay the individual expression of each of the four RORA isoforms, which have been shown to have both temporal- and tissue-specific expression in mouse. (Chauvet et al. 2002; Zhu et al. 2006; Liu et al. 2008) Similarly, a limitation of using mRNA derived from lymphoblastoid cell lines is that while it may be possible to gain information that reflects systemic changes in RORA expression, these results may be tissue specific and therefore, may not be fully reflective of expression changes in the retina or retinal pigment epithelium (RPE) (Nica et al. 2008) Therefore, in order to determine whether or not RORA expression is truly correlated with neovascular AMD, further studies need to be conducted on a greater number of patient samples examining not only the levels of RORA but also the specific transcripts of RORA expressed in the various cell types of the retina and cells involved in the process of neovascularization (including for example endothelial cells and immune infiltrates). In addition, evaluating the functional consequence of lack of RORA gene expression in a model system such as mouse may provide further insight into its role in retinal diseases such as AMD.

Rora has been shown to be ubiquitously expressed but with tissue specific isoform expression. (Chauvet et al. 2002; Zhu et al. 2006; Liu et al. 2008) Immunohistochemical analysis of normal mouse retina showed Rora expression in the ganglion cell layer and inner nuclear layer (Steinmayr et al. 1998; Ino 2004; Fujieda et al. 2009). Ganglion cell layer neurons have been shown by Medeiros and Curcio to be reduced by nearly 50% in eyes of patients with neovascular AMD compared to eyes from individuals with no AMD (Medeiros and Curcio, 2001). Further, Rora has been co-localized with cone specific markers and demonstrated to play an important role in the development of photoreceptors by synergistically regulating the expression of several cone genes, including S- and M-opsin, along with Crx in the mouse. (Fujieda et al. 2009) Studies using the Rora deficient staggerer mouse show that Rora is important but not essential for cone development, as the retina of the staggerer mouse does not exhibit a difference in cone density nor a difference in other cell types compared to wild-type mice (Steinmayr et al. 1998; Fujieda et al. 2009). The role of Rora in the aging retina of the adult staggerer mouse has yet to be established due to lethality in early life. (Fujieda et al. 2009)

In addition to the regulation of cholesterol/lipid metabolism, data suggest an inhibitory role for RORA in inflammation and angiogenesis, cellular processes that have also been implicated in the development and progression of neovascular AMD. (Besnard et al. 2001; Hageman et al. 2001; Anderson et al. 2002; Besnard et al. 2002; Klein et al. 2003b; Boukhtouche et al. 2004; Conley et al. 2005; Johnson 2005; Boukhtouche et al. 2006; Zhu et al. 2006; Lau et al. 2008) Macrophages isolated from the staggerer mouse were shown to have increased mRNA expression of the inflammatory cytokines interleukin-1 alpha, interleukin-1 beta, interleukin-6, and tumor necrosis factor-alpha (TNF-α). (Kopmels et al. 1990; Kopmels et al. 1991; Kopmels et al. 1992) This phenotype has been linked to Rora-mediated transcriptional inhibition of the pro-inflammatory transcription factor nuclear factor kappa B (NFκB). (Delerive et al. 2001) Moreover, RORA isoforms 1 and 4 have been shown to suppress the activation of NFκB by TNF-α and to suppress TNF-α induced expression of the cell adhesion molecules vascular cell adhesion molecule and the intracellular adhesion molecule in human endothelial cells. (Migita et al. 2004) Staggerer mice also exhibited decreased angiogenesis in response to ischemia induced by femoral artery ligation. (Besnard et al. 2001) It is therefore plausible that genetic variants of RORA might affect AMD risk through a combination of multiple pathways in addition to the regulation of cholesterol.

Given the number of processes/pathways in which RORA functions and the significance of association between RORA and neovascular AMD, it is unlikely that RORA alone contributes to the sequelae of events in neovascular AMD but rather that genes regulated by RORA, or those that regulate RORA, may influence the disease. Therefore, although one gene may be modestly associated with AMD risk, it may be the combination of variants within sets of genes that can lead to small changes in the way the genes/proteins interact, which, when combined with environmental effects, can have a huge impact on biological systems culminating in disease with age. (Chen et al. 2008) As a result, the investigation of RORA related pathways and gene networks may lead to a better understanding of the pathophysiology of AMD (Figure 1 and Figure 6).

In this study, we observed a statistically significant interaction between RORA and the ARMS2/HTRA1 locus. This finding was prospectively validated in 2 nested case-control cohorts (D. Schaumberg et al., paper under review). To date, the ARMS2/HTRA1 locus is the region most significantly associated with neovascular AMD (Fisher et al. 2005; Shuler, Jr. et al. 2007; Zhang et al. 2008), however, the pathway in which it functions has yet to be elucidated. This interaction suggests that RORA may be functioning in a similar, overlapping or the same pathway as ARMS2/HTRA1 and opens up new avenues of investigation based upon the known roles of RORA.

Similarly, network investigation of RORA, in combination with HTRA1 and the putative AMD-associated genes discovered by microarray gene expression analysis, provides further areas of study interest, some of which have been corroborated independently by different experimental means. For example, network analysis of our significant microarray genes (Fig. 1) implicated a role for transforming growth factor β (TGF β) family members in AMD. TGFβ has been suggested to play a role in AMD by controlling secretion of vascular endothelial growth factor by RPE cells (Nagineni et al., 2003). The addition of HTRA1 to our network analysis further suggested specific members of the TGFβ family, TGFβ2 and TGFβ3, that may be involved in AMD pathophysiology (Fig. 6). This example underscores the importance of examining gene-gene interaction along with network analysis data as tools in the investigation of mechanisms underlying AMD.

Another potential result of genetic variation(s) in RORA is the cis or trans regulation of a nearby locus, a distant gene, or the indirect regulation of a gene by means of influencing a regulatory locus. (for review please see Ioannidis et al. 2009) In any of these scenarios one can hypothesize that variation within RORA could affect transcription of another gene(s) that in turn would influence the development and progression of AMD. Therefore, we investigated the association of the RORA SNPs found to be significant in our study (either directly or those within a significant haplotype) with eQTLs. Of our 5 SNPs, rs8034864, rs730754, and rs4335725 were present in the database but none were significantly associated with transcript expression (Supplementary Table 6). However this is not surprising based on our haplotype analysis demonstrating that these SNPs are likely not individually causal.

A caveat in the investigation of RORA linked eQTLs is that current studies are limited by the available genome wide association and gene expression microarray platforms, thus limiting the amount of genetic variation and genes that are assayed. For example, the most significant SNP in the unrelated case-control Greek population, rs12900948, was not included in the database. As increasing data becomes available, the study of RORA linked eQTLs may yield interesting information regarding proteins and pathways involved in AMD.

In summary, this is the first report of a genetic association between RORA and neovascular AMD. The identification of RORA alleles and haplotypes significantly associated with neovascular AMD, coupled with linkage and gene expression data, suggests an important role for RORA in the aging retina. Additionally, the overlap between pathways in which RORA plays a role and those believed to underlie AMD pathophysiology suggests that RORA and the pathways in which it functions merit further investigation.

Table 4
FBAT haplotype analysis of RORA in the extremely discordant sibling pair cohort (n = 150 pairs).
Table 8
Haplotype analysis of RORA in the Greek cohort.

Supplementary Material

05

09

Supplementary Fig. 1:

Linkage disequilibrium plot for the extremely discordant sibling cohort (n = 150 sibling pairs). Haplotype blocks were constructed in Haploview using the method proposed by Gabriel et al. (Gabriel et al. 2002) Boxes were shaded increasingly darker to represent higher percentage of LD and the numbers listed in each square represent the D’ unless the box is completely shaded in representing complete LD. Thirteen haplotype blocks were generated for this cohort.

10

Supplementary Fig. 2:

Linkage disequilibrium plot for the extremely discordant sibling cohort (n = 150 sibling pairs). Haplotype blocks were constructed in Haploview using the method proposed by Gabriel et al. (Gabriel et al. 2002) Boxes were shaded increasingly darker to represent higher percentage of LD and the numbers listed in each square represent the r2 unless the box is completely shaded in representing complete LD. Thirteen haplotype blocks were generated for this cohort.

Acknowledgements

We thank all the families and subjects described in this study for their willing participation. We would like to thank the generous support from the Lincy Fund, the Marion W. and Edward F. Knight Age-Related Macular Degeneration Fund, the Massachusetts Lions, Friends of the Massachusetts Eye and Ear Infirmary, Genetics of Age-Related Macular Degeneration Fund, Eannelli for Macular Degeneration Fund, Research to Prevent Blindness, NIH grants EY014458, EY14104, and EY017362 and Hope for Vision.

Footnotes

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The authors have no conflict of interest in any materials presented in the article.

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