Purpose
Age-related macular degeneration (AMD) is the leading cause of blindness among older adults, in which oxidative damage may play a pivotal role. Paraoxonase 1 (PON1) protects against oxidative damage and has been evaluated for its involvement in aging diseases including AMD. This study investigated whether PON1 gene polymorphisms associate with AMD.
Design
Case-control association study.
Methods
We studied 1037 individuals with AMD subcategorized using AREDS criteria and 370 control subjects without retinal disease. Participants were primarily Caucasian of European descent. All exons of PON1 were evaluated by single-strand conformation polymorphism and direct sequence analysis.
Results
Six missense changes (Leu55Met, Met127Arg, His155Arg, Gln192Arg, Gln192Glu, Ala252Gly) were identified in PON1 . We observed a weak association of Leu55Met with an increased risk of wet AMD ( P = .02), but not with dry AMD or when combining all patient categories. A significantly higher allele frequency for Gln192Arg was detected in controls than in the combined AMD patient population ( P < .0001), and when category 2, 3, and 4 patients were separately considered ( P = .004, P = .002, and P < .0001, respectively). For category 4 AMD, the Arg192 allele was significantly less prevalent in the wet form ( P < .0001), but not in the dry form ( P = .377).
Conclusion
We report a weak association of PON1 Leu55Met with an increased risk of wet AMD, replicating previous reports. Our findings indicate a protective role for Gln192Arg, particularly for patients with the wet form. Gln192Glu warrants consideration, as this variant alters the same amino acid as Gln192Arg and was identified only in category 4 AMD patients. We believe that Met127Arg, His155Arg, and Ala252Gly play minor roles in AMD susceptibility because of their limited frequency and/or location within the PON1 gene. The functional and biological mechanism by which Gln192Arg is acting to decrease AMD susceptibility remains to be determined.
Age-related macular degeneration (AMD) is the leading cause of irreversible visual impairment and blindness among older adults in the United States and throughout the developed world. The prevalence of AMD will increase even further, as the number of people aged 65 years or older will increase by approximately 80% in the next 25 years. AMD is a progressive disorder of the photoreceptor–retinal pigment epithelium (RPE)–Bruchs membrane–choriocapillaris complex. AMD typically starts with the formation of a few macular drusen, the lipoproteinaceous extracellular deposits localized between the RPE and Bruchs membrane. Drusen are considered to be a major risk factor for developing end-stage AMD associated with irreversible vision loss, attributable to geographic atrophy (GA, also known as dry, atrophic, or nonexudative AMD) or choroidal neovascularization (CNV, also known as wet or exudative AMD).
Although the clinical and histopathologic characteristics of AMD have been described, little is known about the etiology and pathogenesis of this disorder. It is clear, however, that AMD is a complex disease caused by actions and interactions between multiple genes and environmental factors. Familial aggregation studies, twin studies, association studies, and whole genome linkage scans provided clear evidence that AMD has a strong genetic component. The discoveries of AMD-associated single nucleotide polymorphisms (SNPs) in several genes involved in the regulation of the immune-mediated complement pathway, including complement factor H (CFH), complement factor B (BF), complement component 2 (C2), and complement component 3 (C3), provide an important opportunity to advance our understanding of AMD pathogenesis. The specific role of these variants in causing AMD remains, however, unknown.
In addition to inflammation, it has been postulated that oxidative damage plays a pivotal role in AMD progression. Epidemiologic studies show that cigarette smoking significantly increases the risk of AMD and that dietary supplementation with zinc and antioxidants can slow AMD progression. During the past several years, an enzyme that protects against oxidative damage, paraoxonase 1 (PON1), has been studied extensively for its involvement in several aging diseases including coronary artery disease, arthrosclerosis, Parkinson’s disease, Alzheimer’s disease, diabetes, cancer, and AMD.
PON1 belongs to the paraoxonase ( PON ) family of genes, which also includes PON2 and PON3 . All PON genes are highly conserved in mammalian evolution. Based on their respective cDNA structures and deduced amino acid sequences, there is over 80% identity between human, mouse, and rabbit PON1 proteins, and at least 60% identity between PON1 , PON2 , and PON3 genes of these species. The human PON genes lay in a tandem array on chromosome 7q21.3. Human PON1 is a high-density lipoprotein (HDL)-associated serum enzyme that is synthesized in the liver and protects lipoproteins from oxidative modifications via antioxidant activities and by hydrolyzing oxidized substrates including phospholipids, hydroperoxides, lactones, and carboxylic acid esters.
In vivo, there is a wide individual variation in serum PON1 concentration and enzymatic activity. This variability is attributed to genetic polymorphisms in the PON1 gene and also by environmental factors such as smoking, alcohol consumption, and diet. The 2 most prevalent PON1 polymorphisms, Leu55Met and Gln192Arg, involve residues that are thought to influence enzymatic activity and concentration. Four additional SNPs in the promoter region of the PON1 gene (-107C→T, -162A→G, -824G→A,-907G→C) have also been reported to affect the expression and thus the serum concentration of the enzyme. Among them, the -107C→T polymorphism has been indicated as the most important genetic determinant of PON1 levels. Leu55Met is in linkage with the promoter region SNPs, including -107C→T, and consequently it is associated with variations of the enzyme concentration. Specifically, Leu55 is associated with higher concentrations of the enzyme, irrespective of the amino acid present at position 192. The Gln192Arg polymorphism is responsible for a striking difference in the substrate specificity and activity of the enzyme. Interestingly, several studies indicate that individuals with a specific genetic background, such as those carrying the Arg192 allele and having a high PON1 enzymatic activity, appear to have a survival advantage and seem to age more successfully. These individuals have been defined as centenarians who have avoided or delayed major age-related diseases because of a superior ability to counteract oxidative stress.
Two PON1 SNPs (Leu55Met and Gln192Arg) have been reported to be associated with wet AMD in a study of 72 individuals of Japanese descent. In that study, significant differences in the distributions of both SNPs were found between cases and controls, suggesting that these PON1 gene polymorphisms represent a genetic risk factor for AMD. When the same 2 SNPs were evaluated in separate cohorts of 62 or 94 Caucasian patients primarily from Northern Ireland and Melbourne, Australia, with United Kingdom ancestry with end-stage AMD (dry or wet), no significant association with AMD was found. Given the conflicting PON1 genetic data, we reasoned that investigating a much larger number of patients will help to clarify whether PON1 is associated in AMD pathogenesis. Therefore, we evaluated 1037 patients with AMD for Leu55Met and Gln192Arg, as well as other novel sequence variations.
Materials and Methods
Ascertainment of Patients
Blood samples were collected at the Cole Eye Institute (CEI), Cleveland Clinic and the VA Eye Clinic. We collected a total of 1037 index cases with AMD, each diagnosed through ophthalmologic examination by a clinician in the Clinical Study Group and subcategorized into 1 of 4 experimental groups using the criteria defined by the Age-Related Eye Disease Study. AMD disease progression was categorized based on fundus examination. Briefly, AMD category 1 subjects have 5 or fewer small (<63 μm) drusen/eye and visual acuity of 20/30 or better in both eyes. AMD category 2 patients exhibited early-stage disease with multiple small drusen, single or nonextensive intermediate (63–124 μm) drusen, RPE pigmentary abnormalities, or any combination of these, in 1 or both eyes and visual acuity of 20/30 or better in both eyes. AMD category 3 patients exhibited mid-stage disease with at least 1 eye having visual acuity 20/30 or better, 1 or more large (125 μm) drusen, and extensive intermediate drusen and/or geographic atrophy that did not involve the macula. Category 3 patients lacked advanced AMD in either eye. AMD category 4 patients exhibited advanced AMD with substantial CNV or GA involving the macula in 1 or both eyes. Patients with a diagnosis of exudative or neovascular AMD in at least 1 eye were classified as wet. Control donors lacked macular drusen and exhibited no clinical evidence of any retinal disorder. Of the total, 661 patients were obtained from CEI and 376 patients were obtained from the VA. Of the 1037 patients recruited, 132 were defined as category 1 AMD, 191 were category 2, 127 were category 3, and 587 were category 4. Of the 587 category 4 patients, 76 had dry or atrophic AMD, 493 had wet or exudative AMD, and we were unable to categorize 18 unequivocally as dry or wet AMD. Approximately 95% of our patient population were Caucasian of European descent while about 5% were African-American and less than 1% were Asian. The age range was 53 to 105 years, with a mean age of 77.0 years. A total of 370 unrelated individuals without retinal disease or a family history of retinal disease was used as normal control subjects; 84 were obtained from CEI and 286 were obtained from the VA. Approximately 97% of normal controls were Caucasian of European descent, approximately 3% were African-American, and less than 1% were Asian. The age range was 54 to 94 years, with a mean age of 76.3 years. Study population characteristics including mean age, gender, and health history are summarized for each AMD category in Table 1 . Information was obtained by questionnaire administered at the time of consent. Leukocyte nuclei were prepared from the blood samples followed by DNA purification using standard protocols.
| Cat 1 N = 132 | Cat 2 N = 191 | Cat 3 N = 127 | Cat 4 N = 587 | All N = 1037 | |
|---|---|---|---|---|---|
| Female | 19/132 (14.4%) | 38/191 (19.9%) | 54/127 (42.5%) | 303/587 (51.6%) | 414/1037 (39.9%) |
| Male | 113/132 (85.6%) | 153/191 (80.1%) | 73/127 (57.5%) | 284/587 (48.4%) | 623/1037 (60.1%) |
| Mean age | 72.6 | 75.3 | 77.0 | 79.0 | 77.0 |
| Smoker | 91/111 (82.0%) | 139/178 (78.1%) | 55/88 (62.5%) | 258/477 (54.1%) | 543/854 (63.6%) |
| Diabetic | 23/36 (63.9%) | 35/121 (28.9%) | 10/71 (14.1%) | 56/442 (12.7%) | 124/670 (18.5%) |
| Hypertensive | 62/67 (92.5%) | 100/146 (68.5%) | 51/77 (66.2%) | 267/462 (57.8%) | 480/752 (63.8%) |
| Hyperlipidemic | 44/52 (84.6%) | 50/128 (39.1%) | 35/80 (43.7%) | 170/447 (38.0%) | 299/707 (42.3%) |
| Cardiovascular disease | 86/89 (96.6%) | 90/150 (60.0%) | 61/84 (72.6%) | 176/465 (37.8%) | 413/788 (52.4%) |
| Neurologic disease | 2/16 (12.5%) | 10/106 (9.4%) | 6/69 (8.7%) | 16/433 (3.7%) | 34/624 (5.4%) |
a All numbers are presented as % of total reported for each category.
Mutation Screening
For mutation detection, PCR products corresponding to the PON1 coding sequence (GenBank RefSeq NM_000446) were amplified from genomic DNA and analyzed by the single-strand conformation polymorphism (SSCP) technique. Twelve primer pairs were designed to cover the 9 coding exons as well as the immediately flanking intron sequences and are listed in Table 2 along with the PCR conditions. Two primer pairs were designed for exons 4, 6, and 9 in order to split the exons into 2 fragments to yield smaller-sized amplicons for SSCP. The buffer pH, Mg ++ concentration, annealing temperature, and presence or absence of 10% dimethyl sulfoxide were tailored to each primer pair to yield optimal amplification.
| Exon | Sense Primer | Antisense Primer | Anneal Temp. C | Buffer pH | MgCl 2 mM | % DMSO | Fragment (bp) |
|---|---|---|---|---|---|---|---|
| 1 | tcctagcccgtcggtgtctgcgcc | ggctcgtggagctggcagggagtg | 64 | 8.4 | 1.5 | 10 | 190 |
| 2 | aacttttgtggactgcctaccttt | ggcacattaatcacacaaagagca | 52 | 8.6 | 1.5 | 0 | 228 |
| 3 | ggatccacatcctgcaataatatg | aaagacttaaactgccagtcctag | 50 | 8.6 | 1.5 | 0 | 180 |
| 4.1 | agcgcctctattagcatttgaagt | tcaaatttacttccagtgatcccc | 52 | 8.6 | 1.5 | 0 | 187 |
| 4.2 | gaagaagatccaacagtgttggaa | agagggtaagtttaaaacccagag | 50 | 8.6 | 1.5 | 0 | 242 |
| 5 | gtgagagcttagttaatgtttcat | actaaaagtggattaactatccgc | 46 | 8.4 | 1.5 | 10 | 238 |
| 6.1 | cctgtaatgttcaataccttcacc | ctatagtagacaacatacgaccac | 54 | 8.6 | 1.5 | 0 | 185 |
| 6.2 | gatcactattttcttgacccctac | ctcctgagaatctgagtaaatcca | 52 | 8.4 | 1.5 | 0 | 200 |
| 7 | cttaatctctcaagttgtgttact | attaagcagtccttttttcttcac | 50 | 8.4 | 1.5 | 0 | 233 |
| 8 | ctctgatatattttgctccatcac | aacagtagctgggaataaagtcac | 54 | 8.4 | 1.5 | 0 | 254 |
| 9.1 | gaccctattatgcataaggttgtt | actgtgccattttctgcataaacc | 52 | 8.6 | 1.5 | 0 | 142 |
| 9.2 | tccacaggtgcttcgaatccagaa | ctaagaacactgggtcctcggaat | 56 | 8.4 | 1.5 | 10 | 248 |
SSCP was performed as previously described. Variant bands detected by SSCP were analyzed by sequencing the corresponding PCR-amplified DNA segments using the Quick Start sequencing kit (Beckman-Coulter, Fullerton, California, USA) following the manufacturer’s protocol. A CEQ-2000 automated sequencer (Beckman-Coulter) was used to resolve sequences.
Statistical Analysis
The χ 2 test was used for comparisons of genotype frequencies and to analyze Hardy-Weinberg equilibrium. A 2-tailed Fisher exact test was used for comparisons of allele frequencies. Logistic regression analysis was used to estimate odds ratios and 95% confidence intervals. P values <.05 were defined as nominally significant and were further subjected to Bonferroni correction to account for multiple-comparisons testing. Following correction for the 6 SNPs examined, the significance level for single SNP tests was 0.008 (0.05/6).
Computational Assessment of Missense Mutations
Two sequence homology–based programs were used to predict the functional impact of missense changes identified in this study: PolyPhen (Polymorphism Phenotyping, http://genetics. bwh.harvard.edu/pph/ ) and PMut ( http://mmb2.pcb.ub.es:8080/PMut/ ). PolyPhen analyzes the impact of an amino acid polymorphism on protein structure, and predicts whether that amino acid change is likely to be deleterious to protein function. The prediction is based on the position-specific independent counts (PSIC) score derived from multiple sequence alignments of observations. PolyPhen scores of >2.0 indicate the polymorphism is probably damaging to protein function; scores of 1.5 to 2.0, possibly damaging; and scores of <1.5, likely benign. PMut allows the accurate pathologic prediction of single amino acid mutations based on the use of neural networks. Following the input of a reference sequence and the amino acid substitution of interest, the algorithm provides an answer and a reliability index. An output value >0.5 is predicted to be a pathologic mutation and a value <0.5 is neutral. The reliability is considered good with a score of 6 or greater and is highly reliable at the maximum score of 9.
Results
We initially evaluated a cohort of 377 unrelated patients with AMD. In these patients, all 9 PON1 coding exons were screened by SSCP analysis. Six missense changes (Leu55Met, Met127Arg, His155Arg, Gln192Arg, Gln192Glu, Ala252Gly) were identified ( Table 3 ). An example of each DNA sequence change and its location on a schematic representation of PON1 are shown in the Figure . The Leu55Met and Gln192Arg sequence changes have been previously reported and influence the concentration and/or activity of PON1. The other 4 missense changes (Met127Arg, His155Arg, Gln192Glu, Ala252Gly) are novel.
| Exon | Sequence Change | Protein Change | Allele Frequency AMD Patients | Allele Frequency Normals |
|---|---|---|---|---|
| 3 | T TG → A TG | Leu55Met | 693/1838 = 37.70% | 250/736 = 33.97% |
| 5 | A T G → A G G | Met127Arg | 3/1774 = 0.17% | 1/714 = 0.14% |
| 5 | C A T → C G T | His155Arg | 1/1774 = 0.06% | 0/714 = 0.0% |
| 6 | C A A → C G A | Gln192Arg | 565/1918 = 29.45% | 284/740 = 38.38% |
| 6 | C AA → G AA | Gln192Glu | 7/1932 = 0.36% | 0/740 = 0.0% |
| 7 | G C T → G G T | Ala252Gly | 1/1894 = 0.05% | 0/730 = 0.0% |
We next expanded our evaluation of these 6 variations by screening an additional 660 patients with AMD. Table 3 summarizes the frequency for each of these variants in our AMD and age-matched control cohorts. All 6 variants were identified in Caucasians.
Leu55Met Polymorphism
The Leu55Met polymorphism is a common variant present in the NCBI SNP database (rs854560). In our samples, this SNP had an allele frequency of 37.7% in patients (N = 919) and 34.0% in controls (N = 368) ( P = .078). Allele and genotype data for the Leu55Met polymorphism are given in Table 4 . There was no significant difference between the observed genotype frequencies for both the patient and control populations with those expected under Hardy-Weinberg equilibrium (χ 2 = 0.20, P = .91 in patients; χ 2 = 0.01, P = .99 in controls). Compared with controls, the frequency of the A allele was not significantly higher in all AMD cases (categories 1-4) or in phenotypic subgroups defined by AREDS as categories 1, 2, 3, and 4. However, if category 1 patients are not included in the AMD cohort, this allele was significantly higher in patients than controls ( P = .030). This association does not remain significant following a conservative Bonferroni correction of P < .008. The frequency of the AA genotype was also not significantly higher in all AMD cases when combining categories 1 through 4 or categories 2 through 4 or in the 4 phenotypic subgroups as compared with controls. Table 5 shows that when the category 4 wet and dry AMD patients were separately compared to controls, the minor allele frequency of this variant was significantly more prevalent for wet AMD patients (N = 436; P = .020) but not for dry AMD patients (N = 70; P = .328). Similarly, the genotypic frequency of the AA genotype was significantly more prevalent than controls for wet AMD patients ( P = .040) but not for dry AMD patients ( P = .341). However, neither of these associations remains significant following a conservative Bonferroni correction of P < .008.
| Controls N = 368 | Cat 1 N = 117 | Cat 2 N = 175 | Cat 3 N = 105 | Cat 4 N = 522 | All AMD (Cat 2–4) N = 802 | All AMD (Cat 1–4) N = 919 | |
|---|---|---|---|---|---|---|---|
| Alleles | |||||||
| T | 486 (66.0) | 161 (68.8) | 212 (60.6) | 125 (59.5) | 647 (62.0) | 984 (61.3) | 1145 (62.3) |
| A | 250 (34.0) | 73 (31.2) | 138 (39.4) | 85 (40.5) | 397 (38.0) | 620 (38.7) | 693 (37.7) |
| Significance b | P = .474 | P = .090 | P = .086 | P = .080 | P = .030 | P = .078 | |
| Genotypes | |||||||
| TT | 161 (43.7) | 56 (47.8) | 64 (36.6) | 34 (32.4) | 198 (37.9) | 296 (36.9) | 352 (38.3) |
| TA | 164 (44.6) | 49 (41.9) | 84 (48.0) | 57 (54.3) | 251 (48.1) | 392 (48.9) | 441 (48.0) |
| AA | 43 (11.7) | 12 (10.3) | 27 (15.4) | 14 (13.3) | 73 (14.0) | 114 (14.2) | 126 (13.7) |
| Significance b | P = .726 | P = .215 | P = .111 | P = .196 | P = .074 | P = .179 |
a Data expressed as the number of subjects (% of entire group).
b Comparison with control frequencies, Fisher exact (alleles) and χ 2 test (genotypes).
| Controls N = 368 | Cat 4 – Dry N = 70 | Cat 4 – Wet N = 436 | |
|---|---|---|---|
| Alleles | |||
| T | 486 (66.0) | 99 (70.7) | 526 (60.3) |
| A | 250 (34.0) | 41 (29.3) | 346 (39.7) |
| Significance b | P = .328 | P = .020 | |
| Genotypes | |||
| TT | 161 (43.7) | 37 (52.9) | 153 (35.1) |
| TA | 164 (44.6) | 25 (35.7) | 220 (50.5) |
| AA | 43 (11.7) | 8 (11.4) | 63 (14.4) |
| Significance b | P = .341 | P = .040 |
a Data expressed as the number of subjects (% of entire group).
b Comparison with control frequencies, Fisher exact (alleles) and χ 2 test (genotypes).
Gln192Arg Polymorphism
The Gln192Arg polymorphism is also present in the NCBI SNP database (rs662). Allele and genotype data for the Gln192Arg polymorphism are shown in Table 6 . In our study population, this SNP had a significantly different ( P < .0001) allele frequency of 38.4% in controls (N = 370) and 29.5% in patients (N = 959). For both the patient and control populations, there was no significant difference between the observed genotype frequencies with those expected under Hardy-Weinberg equilibrium (χ 2 = 4.57, P = .10 in patients; χ 2 = 5.21, P = .07 in controls). The frequency of the G allele was significantly higher in controls than in all AMD patients when combining categories 1 through 4 or categories 2 through 4 ( P < .0001, P < .0001, respectively). This difference is significant for AMD categories 2, 3, and 4 as compared to controls ( P = .004, P = .002, P < .0001, respectively) but not for AMD category 1 patients ( P = .197). The frequency of the GG genotype was also significantly higher in controls as compared with all AMD cases, both categories 1 through 4 and categories 2 through 4, and in the 3 more severe AMD subgroups individually. Similarly, category 1 did not appear different than controls. Table 7 shows that when only the category 4 wet AMD patients were considered (N = 457), the minor allele frequency of this variant was significantly higher in controls as compared to patients ( P < .0001); whereas controls did not show a statistical difference when compared to category 4 dry AMD patients (N = 65) ( P = .377). The associations observed with Gln192Arg remain significant after Bonferroni correction. These results indicate that the Gln192Arg SNP in PON1 is associated with a decreased susceptibility to AMD.
