Purpose
To describe the relationships of selected candidate genes to the prevalence of early age-related macular degeneration (AMD) in a cohort of whites, blacks, Hispanics, and Chinese Americans.
Design
Cross-sectional study.
Methods
setting : Multicenter study. study population : A total of 2456 persons aged 45-84 years with genotype information and fundus photographs. procedures : Twelve of 2862 single nucleotide polymorphisms (SNPs) from 11 of 233 candidate genes for cardiovascular disease were selected for analysis based on screening with marginal unadjusted P value <.001 within 1 or more racial/ethnic groups. Logistic regression models tested for association in case-control samples. main outcome measure : Prevalence of early AMD.
Results
Early AMD was present in 4.0% of the cohort and varied from 2.4% in blacks to 6.0% in whites. The odds ratio increased from 2.3 for 1 to 10.0 for 4 risk alleles in a joint effect analysis of Age-Related Maculopathy Susceptibility 2 rs10490924 and Complement Factor H Y402H ( P for trend = 4.2×10 −7 ). Frequencies of each SNP varied among the racial/ethnic groups. Adjusting for age and other factors, few statistically significant associations of the 12 SNPs with AMD were consistent across all groups. In a multivariate model, most candidate genes did not attenuate the comparatively higher odds of AMD in whites. The higher frequency of risk alleles for several SNPs in Chinese Americans may partially explain their AMD frequency’s approaching that of whites.
Conclusions
The relationships of 11 candidate genes to early AMD varied among 4 racial/ethnic groups, and partially explained the observed variations in early AMD prevalence among them.
Age-related macular degeneration (AMD) is an important cause of visual impairment in older persons in the United States and is more prevalent in whites compared with blacks and Hispanics. Such differences may be attributable to variation in environmental exposures (eg, smoking, physical activity, diet), variation in the frequencies of protective and deleterious genetic alleles for risk of AMD among the different racial/ethnic groups, or both. In the Multi-Ethnic Study of Atherosclerosis (MESA), we previously observed that racial/ethnic differences in the prevalence of AMD could not be explained by smoking status, levels of inflammatory factors, cardiovascular disease (CVD), or by the Complement Factor H ( CFH ) Y402H polymorphism, a major AMD risk allele.
Additional genes for AMD susceptibility have been identified by association studies in whites, but there is less information regarding the frequencies of protective and risk alleles in nonwhite populations of the United States. In this report, we examine the relationships of candidate genes and AMD in a cohort of whites, blacks, Hispanics, and Chinese Americans participating in the MESA. A candidate gene study across all of MESA afforded the opportunity to test the association of AMD with AMD candidate genes as well as genes selected for association with CVD and cardiovascular phenotypes, including cholesterol metabolism, innate immunity, and atherosclerosis. We aimed to examine the association of these candidate genes with AMD in 4 racial/ethnic groups (whites, blacks, Hispanics, and Chinese Americans) in the MESA and to test the hypothesis that differences in the frequencies of protective and risk alleles in these candidate genes may account, at least in part, for our previous observations of differences in the frequency of AMD signs among the 4 racial/ethnic groups represented in the MESA.
Methods
Study Sample
The MESA is a prospective cohort study of men and women aged 45-85 years without a history of clinical CVD living in 6 United States communities. The study objectives of the MESA are to identify risk factors for subclinical CVD, progression of subclinical CVD, and transition from subclinical to clinical CVD. Selection of the study population has been reported in detail elsewhere. At the first examination, carried out between July 17, 2000 and August 29, 2002, there were 6814 participants: 1086 from Baltimore, Maryland; 1164 from Chicago, Illinois; 1077 from Forsyth County, North Carolina; 1319 from Los Angeles County, California; 1102 from New York, New York; and 1066 from St. Paul, Minnesota. Tenets of the Declaration of Helsinki were followed, the work was compliant with the Health Insurance Portability and Accountability Act, and institutional review board approval was granted at each study site prior to examining any participants. Written informed consent was obtained from every participant before examination.
Retinal Photography and Grading of Age-Related Macular Degeneration
Fundus photography using a 45-degree 6.3-megapixel digital nonmydriatic camera was performed at each site at the second examination, conducted between September 9, 2002 and February 7, 2004 (immediately after the baseline examination) using a standardized protocol. Two photographic fields were taken of each eye, the first centered on the optic disc (Early Treatment Diabetic Retinopathy Study field 1) and the second centered on the fovea (Early Treatment Diabetic Retinopathy Study field 2). Images were obtained from 6176 participants.
Grading of digital images and quality control are described in detail elsewhere. Each image was graded twice (a preliminary and a detail grade) using a modification of the Wisconsin Age-Related Maculopathy Grading Scheme. Of all participants photographed, 5887 (95.3%) had at least 1 eye that could be evaluated for AMD (right eye only, n = 211; left eye only, n = 200; both eyes, n = 5476) and were included in the analyses for the purposes of this report. There were no statistically significant differences in gradability for AMD among the 4 racial/ethnic groups (data not shown).
Definitions of Age-Related Macular Degeneration Endpoints
Among the AMD features evaluated were drusen size, type, and area; increased retinal pigment; retinal pigment epithelial (RPE) depigmentation; pure geographic atrophy; and signs of exudative macular degeneration (subretinal hemorrhage, subretinal fibrous scar, RPE detachment, and/or serous detachment of the sensory retina or laser or photodynamic treatment scar for neovascular AMD). Soft distinct drusen were defined by size (between 63 and 300 μm in diameter) and appearance (sharp margins and a round nodular appearance with a uniform density). When 2 eyes of a participant were discrepant for the severity of a lesion, the grade assigned for the participant was that of the more severely involved eye. For example, in assigning the prevalence of soft drusen, if soft drusen were present in 1 eye but not in the other eye, the participant was considered to have soft drusen. When drusen or signs of AMD could not be graded in an eye, the participant was assigned a grade based on severity of the lesion in the other eye.
Assessment of Risk Factors
Participants underwent an interview and assessment of cardiovascular risk factors during the course of the study. Variables for this analysis were based on data collected at the baseline examination when most of the systemic hematologic tests were conducted. Resting blood pressure was measured 3 times with participants in the seated position using the Dinamap model Pro 100 automated oscillometric sphygmomanometer (Critikon, Tampa, Florida, USA). The average of the last 2 measurements was used in analyses. Hypertension was defined as systolic blood pressure ≥140 mm Hg and/or diastolic blood pressure ≥90 mm Hg and/or current use of antihypertensive medications. Height and weight were measured with participants wearing light clothing and no shoes; body mass index (BMI) was calculated as the weight in kg divided by the square of height in m. A detailed questionnaire was used to obtain information about past medical history such as hypertension, cigarette smoking, alcohol consumption, and medication use, including antihypertensive and hypoglycemic agents and lipid-lowering agents.
C-Reactive Protein
Fasting (≥8 hours) venous blood samples were drawn from participants and aliquots were prepared for central analysis and storage at the University of Vermont and the University of Minnesota. A standardized protocol was used to measure serum high-sensitivity C-reactive protein.
Genotyping and the Multi-Ethnic Study of Atherosclerosis Candidate Gene Study
DNA was extracted from whole blood and quantified using standard methods (DNA isolation by Puregene kits, Gentra Systems, Minneapolis, Minnesota, USA; PicoGreen kits, Molecular Probes, Inc, Eugene, Oregon, USA).
The details of the MESA Candidate Gene Study have been published previously. In brief, a subgroup of 2880 MESA subjects were selected from all subjects who participated in the third MESA examination, supplemented by random selection from the remaining cohort to give approximately equal numbers across the 4 MESA ethnic/racial groups and between sexes. A complete data set of 2456 participants with AMD grading and gene polymorphisms was available for this study.
Candidate genes were selected by the MESA Genetics Committee after considering suggestions by all MESA investigators. For each candidate gene, single nucleotide polymorphisms (SNPs) were selected for compatibility with the Illumina GoldenGate technology as determined by the Assay Design Tool (TechSupport; Illumina, San Diego, California, USA) and ability to tag white and Yoruban haplotypes in the HapMap Release 2 data set using “Tagger.” In total, 2862 SNPs from 233 genes were completed by the Illumina genotyping service. An additional 199 previously identified ancestry-informative markers selected from HapMap data for 4 racial/ethnic groups were also genotyped and used for estimating principal component variables. Details of the genotyping quality have been published elsewhere.
Analyses of Association
All statistical analyses were performed with SAS version 9.1 (SAS Institute, Cary, North Carolina, USA) and PLINK version 1.07. Logistic regression was used to estimate the odds ratio (OR) and 95% confidence interval (95% CI) for risk factors and AMD as a discrete variable (early AMD vs none). SNP association tests were performed by 2-stage design: initial screening of 2862 SNPs and follow-up analysis of 12 SNPs identified by screening. Although only 12 SNPs were selected for further analysis in detail, a Bonferroni corrected P value adjusted for 2862 SNPs (1.7 × 10 −5 ) was considered statistically significant for the SNP association. P values before and after Bonferroni correction are presented in the Results.
Screen
We first performed a screen of all 2862 SNPs that passed quality control to find those SNPs associated with AMD. An arbitrary cut point with an unadjusted marginal P value of less than .001 in 1 or more racial/ethnic groups was used as an initial approach to identify the best SNP associations in the data and to identify those SNPs for a combined analysis. For multiple SNPs identified in strong linkage disequilibrium (r 2 > 0.8) in the same region, we used the most significant SNP (the lead SNP) to represent the region. Based on this screening analysis, a total of 12 SNPs from 11 genes were selected for a more complete analysis of the association with AMD.
Association of individual single nucleotide polymorphisms
The association of the 12 SNPs with AMD was evaluated by logistic regression initially within each racial/ethnic group separately, and then combined by meta-analysis using the inverse variance method. Age, sex, study site, 2 principal component variables, and smoking status were selected as covariates. The 2 most statistically significant principal component variables representing global continental ancestry were obtained using the ancestry-informative markers.
Association of multiple single nucleotide polymorphisms
In order to test the association of multiple SNPs together, we performed the association analyses by combining the significant SNPs from the single gene analyses into a single model. First, the joint additive effect was tested for 2 interesting SNPs ( Age-Related Maculopathy Susceptibility 2 [ ARMS2 ] rs10490924, the most significant SNP associated with early AMD in our data; and Complement Factor H [ CFH ] Y402H, the most reported SNP associated with AMD in the literature). To test the association of combinations of these 2 SNPs, we grouped the combination by the number of risk alleles. For example, 2 risk alleles in ARMS2 ( AA ) and 2 risk alleles in CFH ( CC ) were grouped as the highest risk, and 2 protective alleles each in ARMS2 ( CC ) and CFH ( TT ) were grouped as the lowest risk. For the additive effect (ie, using a combination of significant SNPs together), we performed the association test by logistic regression among all combinations of groups with AMD.
Second, to identify the interaction effect among all tested SNPs, the multiplicative term of genotypes between 2 significant SNPs was included and evaluated in the model as an interaction term. A total of 144 SNP-SNP pair interactions by 3 genotype groups, ie, 9 genotype combinations for each SNP-SNP pair interaction, were performed. Because of limited sample size, association tests for interactions and the combination of 2 SNPs were performed by using all samples together and adjusted for principal component variables. Logistic regression was performed to evaluate the significance level of the interaction by including both the main effects of SNPs and the interaction in the model. The Bonferroni corrected P value adjusted for 144 tests (3.0 × 10 −4 ) was considered statistically significant.
In addition, we conducted a logistic regression analysis to identify whether these SNPs contributed to the observed racial/ethnic differences of early AMD. Using whites as the reference group, we first performed the tests to check the overall AMD difference between whites and each of the other 3 racial/ethnic groups after controlling for age, sex, study site, and smoking status. We then conditioned on a particular SNP and re-ran the model to compare the difference between 2 racial/ethnic groups. If parameters of the model (eg, P value and OR) changed after conditioning on a particular SNP, then this particular SNP was considered to contribute to the variation in genetic susceptibilities between the 2 tested racial/ethnic groups. For example, if the overall significance between whites and blacks existed in the original model but became less significant after conditioning on a specific SNP, we concluded that this SNP might contribute to the overall racial difference in AMD between whites and blacks. Since more than 1 SNP was independently associated with the differences between whites and Chinese Americans, a combined analysis of all the SNPs was further tested in an independent model with only these 2 racial/ethnic groups.
Results
Complete genotyping and gradable images were available for 2456 MESA subjects. Age, sex, and smoking status for these subjects as a whole, as well as by racial/ethnic group, are shown in Table 1 . The cohort under analysis consisted of 634 whites (25.8%), 630 Chinese Americans (25.7%), 593 blacks (24.1%), and 599 Hispanics (24.4%). Early AMD was present in 4.0%, late AMD in 0.5%, large drusen in 9.8%, soft drusen in 16.3%, increased retinal pigment in 1.8%, RPE depigmentation in 0.9%, neovascular AMD in 0.3%, and pure geographic atrophy in 0.2% of the cohort. These features were most frequent in whites and least frequent in blacks ( Table 1 ). The distributions of the specific SNPs in the 11 candidate AMD genes in each racial/ethnic group and the whole cohort are also presented in Table 1 . The frequency of the effect variant (in parentheses) was lower in Chinese Americans for CFH ( C ), PPARG ( A ), and CAPN5 rs11237081 ( G ) SNPs compared to the other racial/ethnic groups, while the frequency of MRPL10 rs3209 ( G ) and ABCA4 rs548122 ( C ) SNPs was lower and frequency of the SOD3 rs2284659 ( A ) SNP was higher in blacks compared to the other racial/ethnic groups.
| % or Mean ± SD | |||||
|---|---|---|---|---|---|
| All (N = 2456) | White (N = 634) | Chinese (N = 630) | Black (N = 593) | Hispanic (N = 599) | |
| Characteristic | |||||
| Age, y | 60.9 ± 10.0 | 61.0 ± 10.3 | 61.5 ± 10.1 | 60.6 ± 9.5 | 60.3 ± 9.8 |
| Sex, male | 47.2 | 48.0 | 49.1 | 45.4 | 46.2 |
| Current smoker | 13.6 | 15.1 | 5.6 | 18.7 | 15.4 |
| Early AMD | 4.0 | 6.0 | 3.8 | 2.4 | 3.8 |
| Large drusen | 9.8 | 9.9 | 12.9 | 6.2 | 10.0 |
| Soft drusen | 16.3 | 14.0 | 23.3 | 11.3 | 16.4 |
| Increased retinal pigment | 1.8 | 3.9 | 1.3 | 0.7 | 1.0 |
| RPE depigmentation | 0.9 | 1.7 | 1.3 | 0.3 | 0.3 |
| Late AMD | 0.5 | 0.5 | 1.1 | 0.2 | 0.0 |
| Pure GA | 0.2 | 0.3 | 0.2 | 0.2 | 0.0 |
| Neovascular AMD | 0.3 | 0.2 | 1.0 | 0.0 | 0.0 |
| Risk alleles | |||||
| CFH Y402H | |||||
| CT genotype | 33.3 | 45.6 | 9.8 | 45.1 | 33.1 |
| CC genotype | 8.1 | 12.8 | 0.3 | 12.0 | 7.2 |
| ARMS2 rs10490924 | |||||
| AC genotype | 39.7 | 36.0 | 49.7 | 36.6 | 37.8 |
| CC genotype | 51.8 | 60.1 | 30.0 | 57.5 | 57.2 |
| PPARG rs2972164 | |||||
| AG genotype | 34.8 | 49.4 | 10.9 | 38.2 | 40.7 |
| AA genotype | 24.7 | 26.0 | 0.3 | 53.7 | 20.0 |
| PLEKHA1 rs4311997 | |||||
| AG genotype | 47.4 | 51.3 | 44.4 | 45.7 | 47.5 |
| AA genotype | 28.0 | 23.1 | 43.5 | 14.9 | 31.9 |
| PLEKHA1 rs2421018 | |||||
| AG genotype | 38.0 | 48.0 | 31.7 | 31.5 | 39.8 |
| AA genotype | 54.2 | 36.3 | 64.5 | 64.5 | 53.7 |
| MRPL10 rs3209 | |||||
| AG genotype | 25.0 | 47.2 | 2.7 | 20.4 | 29.4 |
| AA genotype | 70.4 | 41.0 | 97.3 | 78.6 | 65.3 |
| ABCA4 rs1237081 | |||||
| CG genotype | 48.0 | 53.1 | 49.9 | 42.1 | 46.5 |
| CC genotype | 19.9 | 14.9 | 31.9 | 8.8 | 25.3 |
| CAPN5 rs 11237081 | |||||
| CG genotype | 38.8 | 49.1 | 29.8 | 35.5 | 39.3 |
| GG genotype | 11.5 | 23.9 | 4.2 | 4.0 | 12.4 |
| IL1B rs1143629 | |||||
| AG genotype | 48.8 | 45.5 | 51.8 | 51.0 | 46.7 |
| AA genotype | 31.8 | 43.7 | 26.8 | 28.9 | 27.4 |
| FOXO1 rs12583418 | |||||
| AG genotype | 42.5 | 39.6 | 38.3 | 49.2 | 42.7 |
| AA genotype | 28.2 | 11.4 | 53.2 | 29.8 | 21.8 |
| SOD3 rs2284659 | |||||
| AC genotype | 41.2 | 46.9 | 42.7 | 28.9 | 45.9 |
| AA genotype | 38.5 | 13.0 | 44.8 | 67.1 | 30.7 |
| MTR rs3754255 | |||||
| AG genotype | 50.6 | 52.1 | 46.4 | 52.9 | 51.2 |
| GG genotype | 30.0 | 32.3 | 28.6 | 29.4 | 29.6 |
Associations
Associations of the selected SNPs with early AMD in the initial screen are presented in Table 2 . Statistically significant associations of early AMD with PLEKHA1 rs4311197, MRPL10 , ABCA4 , and CAPN5 were found in whites only, PLEKHA1 rs2421018 in whites and Chinese Americans only, CFH in whites and Hispanics only, and IL1B rs114629 in blacks only ( Table 2 ). However, after controlling for multiple tests by Bonferroni correction (1.7 × 10 −5 ), only the association of ARMS2 remained significant in the combined sample. All SNPs met Hardy-Weinberg equilibrium in each racial/ethnic group (all P ≥ .01; data not shown).
| Gene and Genotype | All | White | Chinese | Black | Hispanic | |||||
|---|---|---|---|---|---|---|---|---|---|---|
| N | % | N | % | N | % | N | % | N | % | |
| CFH Y402H | ||||||||||
| TT | 1434 | 3.2 | 262 | 3.8 | 560 | 3.9 | 254 | 2.8 | 358 | 2.0 |
| CT | 814 | 4.9 | 288 | 7.3 | 61 | 3.3 | 267 | 1.5 | 198 | 6.6 |
| CC | 197 | 6.6 | 81 | 8.6 | 2 | 0.0 | 71 | 4.3 | 43 | 7.0 |
| OR ( C ) | 1.61 | 1.60 | 0.48 | 1.03 | 2.59 | |||||
| P value a | .007 | .07 | .35 | .94 | .003 | |||||
| ARMS2 rs10490924 | ||||||||||
| AA | 200 | 10.0 | 25 | 16.0 | 110 | 6.4 | 35 | 2.9 | 30 | 26.7 |
| AC | 939 | 3.9 | 227 | 7.1 | 270 | 3.7 | 216 | 3.2 | 226 | 1.8 |
| CC | 1224 | 3.0 | 379 | 4.8 | 163 | 1.2 | 340 | 1.8 | 342 | 3.2 |
| OR ( A ) | 2.12 | 1.77 | 2.46 | 1.61 | 2.84 | |||||
| P value a | 1.1 × 10 −5 b | .05 | .01 | .26 | .002 | |||||
| PPARG rs2972164 | ||||||||||
| AA | 604 | 5.3 | 164 | 6.7 | 2 | 0.0 | 318 | 2.8 | 120 | 10.0 |
| AG | 850 | 4.4 | 312 | 6.7 | 68 | 2.9 | 226 | 2.2 | 244 | 3.7 |
| GG | 991 | 3.0 | 155 | 3.9 | 553 | 4.0 | 48 | 0.0 | 235 | 0.9 |
| OR ( A ) | 1.69 | 1.14 | 0.58 | 1.89 | 4.35 | |||||
| P value a | .004 | .60 | .48 | .21 | 1.0 × 10 −5 c | |||||
| PLEKHA1 rs4311997 d | ||||||||||
| AA | 661 | 5.9 | 146 | 10.3 | 236 | 5.1 | 88 | 1.1 | 191 | 5.8 |
| AG | 1119 | 3.2 | 324 | 4.6 | 241 | 2.1 | 270 | 3.0 | 284 | 2.8 |
| GG | 583 | 3.3 | 161 | 5.0 | 66 | 3.0 | 233 | 2.2 | 123 | 3.3 |
| OR ( A ) | 1.54 | 1.89 | 1.75 | 0.80 | 1.61 | |||||
| P value a | .01 | .02 | .16 | .58 | .14 | |||||
| PLEKHA1 rs2421018 e | ||||||||||
| AA | 1281 | 4.8 | 229 | 9.6 | 350 | 4.9 | 381 | 2.1 | 321 | 4.4 |
| AG | 899 | 2.7 | 303 | 4.0 | 172 | 1.2 | 186 | 2.7 | 238 | 2.1 |
| GG | 183 | 4.9 | 99 | 4.0 | 21 | 0.0 | 24 | 4.2 | 39 | 13.0 |
| OR ( A ) | 1.49 | 2.22 | 5.00 | 0.76 | 0.97 | |||||
| P value a | .04 | .007 | .03 | .56 | .93 | |||||
| MRPL10 rs3209 | ||||||||||
| AA | 1721 | 4.4 | 259 | 9.7 | 606 | 3.8 | 465 | 2.8 | 391 | 3.6 |
| AG | 612 | 3.6 | 298 | 4.0 | 17 | 5.9 | 121 | 0.8 | 176 | 4.6 |
| GG | 112 | 1.8 | 74 | 1.4 | 0 | 0.0 | 6 | 0.0 | 32 | 3.1 |
| OR ( A ) | 1.69 | 2.86 | 0.47 | 4.35 | 0.93 | |||||
| P value a | .02 | .001 | .51 | .15 | .85 | |||||
| ABCA4 rs548122 | ||||||||||
| CC | 470 | 6.4 | 94 | 13.8 | 173 | 4.6 | 52 | 3.9 | 151 | 4.6 |
| CG | 1133 | 3.5 | 335 | 5.4 | 271 | 3.3 | 249 | 2.8 | 278 | 2.2 |
| GG | 760 | 3.2 | 202 | 3.5 | 99 | 2.0 | 290 | 1.7 | 169 | 5.9 |
| OR ( C ) | 1.48 | 2.37 | 1.59 | 1.49 | 0.76 | |||||
| P value a | .02 | .002 | .20 | .34 | .36 | |||||
| CAPN5 rs11237081 | ||||||||||
| CC | 1175 | 2.9 | 170 | 2.9 | 358 | 3.4 | 358 | 2.0 | 289 | 3.5 |
| CG | 917 | 4.3 | 310 | 7.1 | 162 | 3.1 | 210 | 1.9 | 235 | 3.4 |
| GG | 271 | 7.8 | 151 | 7.3 | 23 | 8.7 | 23 | 13.0 | 74 | 6.8 |
| OR ( G ) | 1.50 | 1.68 | 1.31 | 1.84 | 1.20 | |||||
| P value a | .01 | .04 | .51 | .16 | .58 | |||||
| IL1B rs1143629 | ||||||||||
| AA | 778 | 5.8 | 276 | 8.3 | 167 | 3.6 | 171 | 4.7 | 164 | 4.9 |
| AG | 1192 | 3.6 | 287 | 3.8 | 323 | 5.0 | 302 | 2.0 | 280 | 3.6 |
| GG | 475 | 2.3 | 68 | 5.9 | 133 | 1.5 | 119 | 0.0 | 155 | 3.2 |
| OR ( A ) | 1.52 | 1.59 | 1.35 | 3.57 | 1.16 | |||||
| P value a | .01 | .11 | .35 | .009 | .61 | |||||
| FOXO1 rs12583418 | ||||||||||
| GG | 691 | 4.6 | 309 | 4.9 | 46 | 2.2 | 124 | 6.5 | 212 | 3.8 |
| AG | 1003 | 3.9 | 250 | 7.6 | 207 | 2.4 | 291 | 2.1 | 255 | 3.5 |
| AA | 666 | 3.5 | 72 | 5.6 | 288 | 4.5 | 176 | 0.0 | 130 | 4.6 |
| OR ( G ) | 1.03 | 0.90 | 0.62 | 3.91 | 0.94 | |||||
| P value a | .85 | .67 | .26 | .004 | .82 | |||||
| SOD3 rs2284659 | ||||||||||
| CC | 495 | 5.1 | 253 | 6.3 | 78 | 0.0 | 24 | 0.0 | 140 | 6.4 |
| AC | 1008 | 3.4 | 296 | 5.1 | 266 | 2.3 | 171 | 2.3 | 275 | 3.3 |
| AA | 942 | 4.3 | 82 | 8.5 | 279 | 6.5 | 397 | 2.5 | 184 | 2.7 |
| OR ( A ) | 1.12 | 0.94 | 4.17 | 2.13 | 0.66 | |||||
| P value a | .52 | .83 | .002 | .23 | .18 | |||||
| MTR rs3754255 | ||||||||||
| AA | 475 | 3.0 | 98 | 5.1 | 156 | 4.5 | 105 | 1.9 | 116 | 0.0 |
| AG | 1237 | 3.6 | 329 | 5.8 | 289 | 3.1 | 313 | 1.6 | 306 | 3.6 |
| GG | 733 | 5.6 | 204 | 6.9 | 178 | 4.5 | 174 | 4.0 | 177 | 6.8 |
| OR ( G ) | 1.49 | 1.23 | 1.09 | 1.82 | 2.94 | |||||
| P value a | .01 | .43 | .79 | .15 | .003 | |||||
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