© 1997 American Heart Association, Inc.
Articles |
Genetic Polymorphism of Paraoxonase and the Risk of Coronary Heart Disease
From the Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh (Pa).
Correspondence to M. Ilyas Kamboh, PhD, Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, 130 DeSoto St, Pittsburgh, PA 15261. E-mail ikamboh{at}helix.hgen.pitt.edu
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Abstract Recent studies have implicated paraoxonase, an HDL-associated enzyme, in providing protection against LDL oxidation, thus affecting the risk of coronary heart disease (CHD) in the general population. In this study, we evaluated the distribution of a biallelic PON polymorphism at codon 192 (A and B alleles) and its relationship with plasma lipids and CHD in two racial groups comprising Asian Indians and Chinese from Singapore. The frequency of the B allele was significantly higher in Chinese control subjects than in Indian control subjects (0.58 versus 0.33; P<.0001). With the exception of a marginal effect on apolipoprotein A-I levels in Indians, no other significant association was observed between the PON polymorphism and quantitative lipid traits in either racial group. However, there was a race-specific association of the B allele with CHD in Indians but not in Chinese. The Indian CHD patients had a significantly higher frequency of the B allele than control subjects (.43 versus .33; P=.014). The age- and sex-adjusted odds ratio for developing CHD with the B allele (BB+AB genotypes) was 2.01 (95% CI, 1.17 to 3.45; P=.011) compared with the A allele (AA genotype). When the Indian patients were stratified into subgroups, the association remained significant in nondiabetic patients (odds ratio, 2.29; P=.008), and it became stronger in patients with myocardial infarction (odds ratio, 2.94; P=.004) than in patients without myocardial infarction (odds ratio, 1.11; P=.76). These data indicate that a common polymorphism in the PON gene is an independent risk factor for CHD in populations with white ancestry.
Key Words: genetic polymorphism • high-density lipoprotein • paraoxonase • Asian Indians • Chinese • coronary heart disease
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Introduction |
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The role of HDL in impeding the process of atherosclerosis is well recognized. A strong inverse correlation exists between HDL cholesterol and CHD.1 2 The most likely mechanism by which HDL protects against CHD and atherosclerosis is thought to be mediated by its involvement in reverse cholesterol transport, in which HDL prevents the buildup of excess cholesterol in peripheral tissues. Recent evidence, however, suggests another role of HDL by which it can prevent atherosclerosis by inhibiting the oxidative modification of LDL particles.3 4 5 In this process, the potential involvement of some HDL-associated enzymes, including PON, is considered to play an important role in preventing LDL oxidation.5 6
Human serum PON is a glycoprotein of 
44 kD, which is a constituent of HDL subfractions that also contain apo A-I and apo J.7 8 Although the natural substrate for PON is unknown, it has been studied largely because of its important role in providing protection against poisoning from organophosphate compounds, which are widely used as nerve gases and insecticides.5 There is a wide variation in serum PON activity within and between population groups.9 10 A common polymorphism due to an amino acid substitution (Gln
Arg) at either codon 191 or 192 is considered to be a major determinant of variation in serum PON activity: individuals with Gln (A allele) have lower activity than individuals with Arg (B allele).11 12 13 The discrepancy in the numbering of the polymorphic amino acid position depends on the exclusion (codon 191)11 or inclusion (codon 192)12 of the initiator methionine residue on the N-terminal.
There is now growing evidence that PON plays an important role in lipoprotein metabolism and thus may affect the risk of CHD and atherosclerosis in the general population. PON has been colocalized with apo A-I– and apo J–containing HDL subfractions7 8 and raises the possibility that PON may be involved in reverse cholesterol transport. In vitro studies indicate that PON can significantly reduce lipid peroxide generation during LDL oxidation and thus may be involved with in vivo protection by HDL against atherosclerosis.5 6 Furthermore, serum PON activity has been found to be lower in patients with MI14 or familial hypercholesterolemia15 ; in the analphalipoproteinemias, including fish eye disease and Tangier disease16 17 ; and in diabetic patients.15 18 19 PON activity also has been shown to correlate with serum lipid and apolipoprotein levels.19 20 Recently, a PON polymorphism at codon 192 has been implicated in the risk of CHD.21 22 In view of its potential involvement in determining the risk of CHD, we have evaluated the racial distribution of the PON polymorphism and its relationship with plasma lipids and CHD in two large samples comprising Asian Indians and Chinese from Singapore.
In Singapore, the Indians and Chinese are descendants of immigrants who migrated to Singapore in the early 19th century from the Indian subcontinent and the southern provinces of China, respectively. Indians and Chinese are of Dravidian and Han ancestry, respectively, determined by parental ethnic origin and language spoken. No subject with mixed ancestry was encountered, as expected from the very low incidence of interracial marriages in Singapore. They have lived together for several generations in a shared socioeconomic environment while maintaining part of their cultural and dietary habits. There are significant differences in mortality rates from CHD in these two racial groups: the age-standardized relative risk in Indians is about three times that in Chinese.23 24 The higher prevalence of CHD in Asian Indians cannot be explained by traditional risk factors like cigarette smoking, blood pressure, and serum cholesterol, because these risk factors are similar or more favorable in Asian Indians than in Chinese. However, Asian Indians have consistently lower HDL cholesterol, higher triglycerides, and higher prevalence of diabetes.24 25 These data strongly suggest that Asian Indians have unique genetic elements that put them at higher risk of developing CHD even in the presence of favorable traditional factors. The identification of genetic factors that explain the interracial differences in CHD rates is critical to understanding the pathogenesis of this disease. The present study indicates that a common PON polymorphism is a significant risk factor for CHD in Asian Indians but not in Chinese.
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Patients
The study samples comprised 122 unrelated Asian Indian CHD patients (109 men and 13 women) 32 to 83 years old (mean age, 54.9±0.8 years) and 246 Chinese CHD patients (206 men and 40 women) 35 to 81 years old (mean age, 57.8±0.5 years). All CHD patients were admitted to the Cardiothoracic Surgery Unit at Singapore General Hospital for coronary artery bypass graft surgery between August 1989 and December 1992. Blood samples from patients were collected during preoperative review or at least 3 months after full recovery from those with a history of MI. Patients with a positive stress test (Bruce method) were evaluated for the presence of CHD by coronary angiography. Inclusion criteria were >50% stenosis of at least one of the major coronary arteries. Patients with less obstruction or valvular disease were excluded. MI had occurred in 48% of the Chinese and 57% of the Indian patients, as judged by typical ECG changes (Minnesota code 1.1 or 1.2 in the ECG) and changes in serum enzymes (aspartate aminotransferase, lactate dehydrogenase, and creatine kinase). A detailed family history of CHD, hypertension, diabetes, and smoking status was obtained from each patient.
Control Subjects
Control subjects were recruited from factories and the community as voluntary participants in the "Healthy Lifestyle Promotion Exercise" sponsored by factory authorities and community centers in Singapore. These include 225 Indians (168 men and 57 women) 19 to 81 years old (mean age, 43.0±0.8 years) and 441 Chinese (229 men and 212 women) 18 to 74 years old (mean age, 37.8±0.6 years). For the case-control comparisons (Tables 1
through 4), only those Indian control subjects 
32 years old (n=165; mean age, 48.3±0.8 years) and Chinese control subjects 35 years old (n=244; mean age, 45.9±0.6 years) were included in the analyses to match the age range of control subjects with that of patients. However, in genotype-lipid association studies (Table 5), all control subjects were included. All control subjects were healthy and had no family history of any cardiovascular disease, diabetes, or infection. Individuals were selected after careful physical examination, chest radiograph, ECG, urine, and blood tests, including hemoglobin and glucose.
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Metabolic Estimations
Recumbent blood pressure and 12-lead ECG were recorded on each subject after a 30-minute rest on a couch. Height and weight were recorded, and blood samples were collected by venipuncture after overnight fasting. Plasma samples were separated into three aliquots within 1 hour of blood collection. One aliquot was precipitated with phosphotungstic acid/magnesium chloride, and the supernatant was used for estimating HDL cholesterol on the same day. The second aliquot was used for estimation of glucose, total cholesterol, and triglycerides on the same day. The third aliquot was stored at -20°C for estimation of apo A-I and apo B. Buffy coats were separated and stored at -20°C until DNA was extracted. Plasma levels for total cholesterol, HDL cholesterol, and triglycerides were measured by enzymatic methods with an autoanalyzer (Cobas Mira, Roche) and manufacturer's reagent kits; apo A-I and apo B levels were estimated by a turbidimetric assay with reagent kits (Roche) as described previously.26 LDL cholesterol was estimated by Friedewald's equation27 on samples with triglyceride values <400 mg/dL. BMI was calculated by dividing weight (in kilograms) by the square of height (in meters).
PON Polymorphism Screening
DNA was extracted from buffy coats as described28 and was used to amplify the target region in the PON gene by PCR using forward 5'-TAT TGT TGC TGT GGG ACC TGA G-3' and reverse 5'-CAC GCT AAA CCC AAA TAC ATC TC-3' primers.13 Genomic DNA (1 µg) was amplified in 50 µL of reaction mixture containing 0.3 µmol/L of each primer, 200 µmol/L of each dNTP (Pharmacia), 5 µL of 10x reaction buffer [100 mmol/L Tris HCl (pH 9.0), 500 mmol/L KCl, and 1% Triton X-100]; 5% DMSO, and 1.25 U Taq DNA polymerase. After the DNA was denatured for 8 minutes at 95°C, the reaction mixture was subjected to 30 cycles of denaturation for 1 minute at 95°C, 1.5 minutes of annealing at 58°C, and 2 minutes of extension at 72°C. The PON polymorphism was detected by digestion of the PCR-amplified product with the Alw I restriction enzyme followed by size fractionation in 3% Nusieve (FMC Corp) agarose gel.
Statistical Analyses
Allele frequencies were calculated by allele counting. Concordance of genotype frequencies with Hardy-Weinberg equilibrium was tested with a 
2 goodness-of-fit test. Comparison of the genotype frequency distribution between case patients and control subjects and between control samples was made with a 2 test for a 2xk contingency table. The difference in allele frequencies between the two racial groups and between case patients and control subjects within a group was calculated with a standard test of two binomial proportions.29
Approximate normality of the sampling distribution of each dependent variable was tested with the Lilliefors test for normality (a modified Kolmogorov-Smirnov test) separately for each racial group. The distribution of triglycerides was not normal; therefore, they were log-transformed. Means and SEM were calculated with the SPSS for Windows statistical package. Significant covariates for each dependent trait were identified by Spearman's correlation and stepwise multiple linear regression with an overall 5% level of significance. The covariates considered were the linear effects of age, BMI, waist-to-hip ratio, and triglyceride levels. Age and BMI were the significant covariates in all quantitative traits. Each dependent quantitative variable was then adjusted to remove the effects of the significant covariates, and these adjusted variables were used in the one-way ANOVAs to determine the contribution of the PON polymorphism to variation in the lipid measures. The proportion of the total phenotypic variability attributable to the PON polymorphism was estimated by R2 as described by Boerwinkle and Sing.30 These were calculated with the statistical software package SAS and a FORTRAN program written by C.E. Aston and A.E. McAllister. ANOVAs were performed on the combined sample of men and women after adjustment for sex in both racial groups. Analyses were done including and excluding individuals with triglycerides >300 mg/dL to examine the effect of hypertriglyceridemia on the genotype-specific means of lipid traits.
The contribution of the PON polymorphism to CHD risk was estimated by logistic regression for unmatched data to obtain odds ratios for the PON polymorphism adjusted for the effects of age, sex, race, medical history, and their interactions (eg, racexPON genotype). Logistic regressions were calculated with the statistical package GLIM (version 3.77, NAG Inc, 1987), which allows nested models. Included odds ratios were tested for significance by Wald's test, whereas overall significance for the difference between the logistic regression models was tested, with the deviance used as an approximate 2 statistic.31
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Table 1
shows the distribution of mean quantitative lipid and apolipoprotein levels along with mean age, BMI, and smoking status in control subjects and CHD patients. Both Chinese and Indian patients were older and more commonly smokers or ex-smokers than the respective control samples. There was no significant difference in plasma total or LDL cholesterol levels between patients and control subjects. However, plasma HDL cholesterol and apo A-I levels were significantly lower in patient groups than control subjects. Although plasma apo B levels were similar among Chinese patients and control subjects, they were significantly lower in Indian patients than control subjects (P<.001). The latter is an unexpected finding compared with what is known about apo B and risk of CHD. Additional studies are needed in Indians to determine whether apo B is a risk factor in this group.
The PON polymorphism displayed three genotypes (AA, AB, and BB) because of the presence of two common alleles, designated A (glutamine) and B (arginine) for the amino acids at codon 192. The genotypic distribution of the PON polymorphism was in Hardy-Weinberg equilibrium in both Chinese and Indian control and patient groups (Table 2). The allelic distribution of the PON polymorphism was significantly different between Indian and Chinese control subjects: Indians had a significantly lower frequency of the B allele than Chinese (0.33 versus 0.58; P<.0001). The genotypic distribution of the PON polymorphism was comparable between Chinese case patients and control subjects, but it varied significantly between Indian case patients and control subjects. Indian patients had a significantly higher frequency of the AB genotype (59% versus 40%; P<.001) and lower frequency of the AA genotype (27% versus 47%; P<.001). The race-specific age- and sex-adjusted odds ratio of developing CHD with the B allele (AB+BB genotypes) versus the A allele (AA genotype) was 2.01 (95% CI, 1.17 to 3.45; P=.011) in Indians and 1.35 (95% CI, 0.76 to 2.41; P=.31) in Chinese, suggesting a possible difference between these races and CHD risk attributable to the PON polymorphism.
To determine whether the difference between the race-specific odds ratio constituted a significant difference in CHD risk between these races, a logistic regression analysis of the entire sample was done (Table 3). For brevity, the simplest model presented (model 1) includes the significant covariates, which were determined to be race, sex, and age within each race (ie, a race-specific age coefficient for Chinese and for Indians). Model 2 estimates a coefficient for the PON polymorphism, whereas model 3 estimates separate race-specific coefficients for the PON polymorphism. Comparison of model 1 with model 2 (2=7.7; df=1; P=.0055) shows that the PON polymorphism accounts for a significant proportion of CHD risk in the entire sample. Comparison of model 2 with model 3 (2=1.7; df=1; P=.19) shows that there is no significant evidence of a race-specific difference in CHD risk attributable to the PON polymorphism, although we continue to observe that the odds ratio in the Indians is significant (odds ratio, 2.20; P=.0037), whereas the odds ratio in the Chinese is not (odds ratio, 1.30; P=.37). For the above analyses, the PON polymorphism was parameterized as a dominant system (BB+AB versus AA). An additive model for the PON polymorphism was also considered, as was a recessive model. In all cases, however, the dominant model provided a better fit to the data.
In view of a previous finding that the B allele is a risk factor for CHD in diabetic patients,21 we compared the distribution of the PON polymorphism between nondiabetic and diabetic patients (Table 4). As reflected in the odds ratio, the B allele was significantly associated with CHD risk in Indian nondiabetic (odds ratio, 2.29) patients but not in Indian diabetic and Chinese patients. We also analyzed the data by stratifying patients having MI (MI+) and those without MI (MI-) to further refine the CHD association to CHD subgroups (Table 4). The positive association of the B allele was stronger in the MI+ subgroup (odds ratio, 2.94) than the MI- subgroup (odds ratio, 1.11) among Indian patients. Although the latter trend was also observed in Chinese patients (odds ratio: MI+, 1.84; MI-, 0.93), it was not statistically significant. Overall, these data suggest that the CHD risk associated with the B allele is stronger in MI+ patients.
Because of the observed association between the PON polymorphism and CHD, we investigated the relationship of PON genotypes with lipid-related variables in control samples (Table 5) to try to understand the mechanism behind this association. We chose only the control group for analysis to avoid a potential bias occurring in lipid levels in the CHD group. With the exception of apo A-I levels, which varied significantly among the three PON genotypes in Indians (P=.031), no other positive association was seen between the PON polymorphism and lipid levels in either racial group. The effect of the PON polymorphism on apo A-I levels was gene dosage related: the levels were highest in the AA genotype, intermediate in the AB genotype, and lowest in the BB genotype. However, when we further stratified the Indian sample into men (n=168) and women (n=57), the observed association was found to be restricted to women (P=.01). A similar sex-stratified analysis in Chinese did not yield any positive association (data not shown). Furthermore, no significant association between the PON polymorphism and lipid levels was observed in either the Indian or the Chinese patient samples (data not shown).
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Several lines of evidence indicate that PON plays an important role in lipid metabolism and thus may affect the risk of CHD and atherosclerosis in the general population. In view of this, a comprehensive population-based study was performed in Asian Indians and Chinese, who experience mortality rates different from CHD, to address three questions: (1) the race-specific distribution of the codon 192 PON polymorphism, (2) the association of the PON polymorphism with plasma lipid levels, and (3) the relationship between the PON polymorphism and CHD.
The distribution of the PON polymorphism was significantly different between the two racial groups, with Chinese having a significantly higher frequency of the B allele than Indians (0.58 versus 0.33; P<.0001). Previously, we have also reported the frequency of the B allele based on PON activity assay in these two populations,10 but it was found to be significantly lower than observed in this study. Because the samples used in our previous study10 and this study are genetically similar, this difference perhaps reflects the inherent problems associated with biochemical assays in distinguishing unequivocally between the heterozygote and homozygote classes. PON activity in the present series of Chinese and Indian samples was not available for direct comparison between the functional (activity) and structural (DNA) polymorphisms.
Our analyses of the relationship between the PON polymorphism and quantitative traits indicate that the codon 192 polymorphism does not have a substantial effect on plasma lipid profile. With the exception of a sex-specific effect on plasma apo A-I levels in the Indian sample, no other statistically significant effect was seen on any lipid variable in either racial group. Considering that multiple comparisons were performed and the Indian female sample was small, even this sex-specific positive association could be due to chance. Recently, Hegele et al32 reported some positive associations between the PON polymorphism and plasma lipid variables, but they accounted for only 1% of the total variation in these traits, suggesting a relatively small contribution of this polymorphism to the total phenotypic variation of quantitative risk factors.
The principal finding of this study is that despite its negative association with the conventional risk factors, the PON polymorphism, specifically the B allele, is a significant risk factor for CHD in Asian Indians but not in Chinese. These observations raise two interesting questions: (1) Is the race-specific association true or spurious? and (2) If true, what is the mechanism behind this association? The positive association in the Indian sample could be a chance observation, because the number of patients in this population was one half that of the Chinese patients. However, we believe that this is not the case, because, as this study was in progress, two groups reported a positive association of the B allele with CHD in French and US white patients.21 22 Interestingly, the frequency of the B allele in all three populations showing a positive association with CHD is similar (Indians, 0.33; US whites, 0.31; French, 0.26), but together they have a significantly lower frequency of this allele than Chinese (0.58), in whom the association was not apparent. Comparable PON frequencies observed in Asian Indians and the other two white populations are consistent with other genetic data showing that overall, Indians have a higher degree of genetic affinity with whites than other racial groups.33 Possibly the common occurrence of the B allele in Chinese may have diluted its association with CHD. Conceivably, because the Chinese control group was younger than the patient groups, certain control individuals with the B allele might have had silent CHD. However, when we restricted the analyses to a subset of 103 Chinese control subjects (age range, 45 to 74 years; mean age, 54.9±0.8 years) to avoid the possible confounding effect of the younger age by matching the mean age of the case and control samples, the outcome was not different from that using either the 244 control subjects (Table 2) or the entire sample of 441 control subjects. However, pooling the entire sample across both races and examining the race-specific genotype term in the logistic regression, we did not find this to be significant, although the trend showed a definite increased genotype risk in Indians, as suggested by the race-stratified analyses (Table 3).
These observations suggest, therefore, that the B allele is a significant risk factor for CHD in Asian Indians but not in Chinese. This race-specific association also implies that the B allele by itself is not causally related to CHD. Other possible causes underlying a genetic association include admixture, linkage disequilibrium, genexgene interaction, and genexenvironment interaction. If the sampled population is derived from the admixture of two or more parental populations having different frequencies of the disease and the marker allele, then the associated allele may merely act as a marker of one of the ancestral populations rather than having a direct role in the pathogenesis of the disease. In this case, this possibility could be ruled out because, paradoxically, the frequency of the disease-associated allele is higher in nondiseased Chinese than in affected Indians or in the reported French21 and US white22 CHD patients, indicating that admixture cannot explain this association. The race-specific association of the B allele with CHD in this study can also be explained if we assume that the B allele is in linkage disequilibrium with a functional mutation that is commonly present in white populations but is absent or present sporadically in Chinese. Alternatively, specific genexgene interaction present in populations of white ancestry only may also explain this race-specific association. In addition to the known human PON gene, two additional genes, designated PON 2 and PON 3, have recently been identified that are structurally homologous to the PON 1 gene.34 Although the role of the two new PON genes in relation to the known PON 1 gene has yet to be characterized, they can interact at the gene level to affect the risk of CHD. PON, which is associated with HDL, can also interact metabolically on the HDL particles with other genes whose products are also present on HDL, including apo J7 8 and platelet activating factor–acetylhydrolase.35
Alternatively, specific genotypexdiet interaction may possibly affect differential expression of CHD and ethnicity is merely a marker of dietary differences. Recently, Shih et al36 showed in mice that the PON gene expression is determined by both dietary and genetic factors and found interindividual variation in the response of PON-related phenotypes to dietary stimuli. There are significant differences in the intakes of macronutrients and micronutrients between Singapore Indians and Chinese.37 Surprisingly, the high-risk Indians consume less animal protein, total fat, and cholesterol than the low-risk Chinese. Conversely, the intakes of polyunsaturated and monounsaturated fats, thiamin, and nicotinic acids are significantly higher in Chinese, whereas Indians consume more calcium and less magnesium in their diets. The animal proteins in Chinese food contain mainly pork, chicken, pig's liver, duck, and shellfish, whereas Indians consume mutton. Chinese food also contains more fresh fruits and vegetables. The most striking differences are in the cooking media and style: Indians use coconut oil, ghee, and fried items, whereas Chinese prefer corn oil and lard in mostly steamed items.37 38 An interesting negative correlation between the intakes of nicotinic acid and thiamin with serum cholesterol and triglycerides is present in these populations.37 Whether these dietary differences can modulate the expression of the PON gene is a matter of conjecture at present but remains a possibility in light of reported population differences in serum PON concentrations39 and experimental findings of differential expression of the PON gene in mice.36
In summary, our findings, in conjunction with recently reported data, strongly indicate that the B allele of the PON polymorphism at codon 192 is an independent risk factor for CHD in populations of white ancestry. Our race-specific association data may also explain, at least in part, the higher prevalence and mortality from CHD in Asian Indians than Chinese in Singapore.23 24 Once the exact cause of this genetic association is known, then the underlying physiological mechanism could be elucidated. A possible mechanism by which the PON polymorphism can exert its effect on the risk of CHD may be mediated by its involvement in the hydrolysis of lipid peroxides.5 6 The oxidation of LDL and its involvement in the development of foam cell–laden fatty streaks in the arterial wall are believed to initiate the atherosclerotic process.40 41 In vitro studies indicate that PON prevents LDL oxidation5 6 and can destroy biologically active lipids in mildly oxidized LDL42 43 and may therefore affect the process of atherosclerosis. If the functional mutation marking the B allele acts differentially to inhibit LDL oxidation, then its association with CHD can be explained by its default action in preventing LDL oxidation. Obviously, additional genetic and functional studies are required to address the question of genotype-specific inhibition of LDL oxidation.
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Acknowledgments |
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This study was supported in part by NIH grants HL-44672, HL-49074, and HL-52611. The technical assistance of Wei Si is gratefully acknowledged.
Received May 21, 1996; accepted August 20, 1996.
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