Paraoxonase (PON1) Phenotype Is a Better Predictor of Vascular Disease Than Is PON1192 or PON155 Genotype
Arteriosclerosis, Thrombosis, and Vascular Biology
Abstract
Abstract—The paraoxonase (PON1) PON1-Q192R and PON1-L55M polymorphisms have been inconsistently associated with vascular disease. Plasma PON1 activity phenotypes vary markedly within genotypes and were, therefore, expected to add to the informativeness of genotype for predicting vascular disease. The case-control sample included 212 age- and race-matched men (mean age 66.4 years). The 106 carotid artery disease (CAAD) cases had >80% carotid stenosis, and the 106 controls had <15%. Two PON1 substrate hydrolysis rates (paraoxon [POase] and diazoxon [DZOase]) were significantly lower in cases than in controls and were significant predictors of CAAD by use of logistic regression (POase, P=0.005; DZOase, P=0.019). DZOase predicted vascular disease independently of lipoprotein profile, high density lipoprotein subfractions, apolipoprotein A-I, and smoking. PON1-192 and PON1-55 genotypes or haplotypes did not predict case-control status unless the activity phenotype was also included as a predictor by use of logistic regression. When phenotype was included as a predictor, PON1-192 and PON1-55 genotypes or combined haplotypes were significant predictors (P<0.05). In conclusion, examining PON1-192 and/or PON1-55 genotypes alone may mistakenly lead to the conclusion that there is no role of PON1 in CAAD. These results support the benefit of a “level crossing” approach that includes intervening phenotypes in the study of complexly inherited disease.
The paraoxonase (PON1) gene maps to human chromosome 7q21-22 and has 2 common coding region polymorphisms, PON1Q192R, the Gln (Q) to Arg (R) substitution at amino acid 192, and PON1L55M, the Leu (L) to Met (M) substitution at amino acid 55. The PON1192R allele or PON1192RR genotype have been found to be associated with cardiovascular disease (CVD) in many,1 2 3 4 5 6 7 but not all,8 9 10 11 12 13 studies. The PON155LL genotype predicted CVD in several studies,14 15 including an Australian sample in which PON1192 genotype did not predict disease,12 but not in an Asian Indian sample in which PON1192 genotype did predict CVD.4 15 The PON1R192 and PON1L55 alleles are in strong linkage disequilibrium in several ethnic groups.15 16 17
The cardioprotective role of HDL, the inhibition or reduction of atherogenic LDL oxidation, appears to be, in large part, a function of PON1, which is associated with HDL.18 19 20 21 22 PON1 metabolizes mildly oxidized phospholipids, presumably by eliminating hydroperoxy derivatives of unsaturated fatty acids.20 Thus, the PON1-CVD association is expected to result from the role of PON1 in the metabolism of bioactive lipid molecules and protection against damage due to oxidized LDL.
PON1 hydrolyzes a variety of substrates, including the toxic components of the pesticides parathion, chlorpyrifos, and diazinon; aryl esters, such as phenyl acetate; and the nerve agents soman and sarin. There is 10- to 40-fold interindividual variability in rates of paraoxon hydrolysis.23 The PON1192Q allele has the higher rate of in vitro hydrolysis of diazoxon, sarin, and soman,24 whereas the PON1192R allele has higher activity for the hydrolysis of paraoxon and chlorpyrifos oxon.24 25 These rates of substrate hydrolysis are quite variable within PON1 genotypes (at least 13-fold) and represent phenotypes that can add information about PON1 status beyond genotyping alone.24 Paraoxon hydrolysis activity is lost in the plasma of the PON1 knockout mouse, and these mice are more susceptible to atherosclerosis.26
We compared the PON1192 and PON155 genotypes with PON1 rates of hydrolysis of paraoxon (POase activity) and diazoxon (DZOase activity) for their predictiveness in vascular disease of the carotid arteries. These 2 substrates were chosen because, relative to the other isoform, the PON1192Q isoform has a higher DZOase activity and the PON1192R isoform has a higher POase activity in the in vitro assays. The resulting 2D plot (Figure 1) allows an accurate inference of PON1192 genotype, in addition to providing PON1 phenotype information.27
Methods
Sample
All subjects were collected through an Epidemiology Research and Information Center project at the Puget Sounds Veterans Affairs Health Care System (PSVAHCS). All cases had severe carotid artery disease (CAAD), ie, >80% internal carotid artery stenosis, unilaterally or bilaterally, on angiography with the use of standardized guidelines, or they had carotid endarterectomy without prior angiogram. All controls were drawn from patients without codes for vascular disease and subsequently were shown to have had <15% internal carotid artery stenosis, bilaterally, on carotid ultrasound with the use of standardized guidelines. Any subjects with total serum cholesterol >400 mg/dL or coagulopathy were excluded. Subjects were matched by race and censored age (within 12 months). Race was ascertained from PSVAHCS record and self-report. Censored age matching was based on the age at the time of the blood draw for controls and the age at the diagnosis of vascular disease for cases. The mean duration of documented vascular disease before the sampling of cases was 2.6 years. The present study was approved by the University of Washington and the PSVAHCS human subject review processes. Subjects gave written informed consent.
The subjects were US military veterans (mean censored age 66.4 years, range 49 to 82 years). Of the 212 subjects, all were male, 95% were white, 26% were on lipid-lowering medications, and 66% were current or former smokers (Table 1). Smoking history was by self-report. The presence of treatment with antihypertensive drugs or lipid-lowering medications was abstracted by a physician from the patient’s pharmacy medication history. Type 2 diabetes was considered present if the subject took oral hypoglycemics or insulin or if he had a hemoglobin A1C >7.0.
PON1 Genotype and Activity Phenotype Methods
DNA was prepared from buffy coat preparations by a modification of the procedure of Miller et al28 with the use of Puregene reagents (Gentra). PON1192 and PON155 genotypes were determined by polymerase chain reaction techniques and AlwI and NlaIII restriction enzyme analysis.25 Genotype distributions did not significantly differ from Hardy-Weinberg equilibrium expectations.
POase activity and DZOase activity were measured spectrophotometrically with lithium heparin plasma, as described.27 All samples were run in duplicate; the averaged value was used for analysis. PON1192 genotype can be predicted with high accuracy from examination of the 2D plot of paraoxon and diazoxon hydrolysis rates.27 When assignments did not match, both genotyping and phenotyping studies were repeated. All 212 subjects had genotype-phenotype agreement (Figure 1), resulting in an expected nearly 100% genotype accuracy.
Lipid Measurements
Lipid measurements were performed on fasting whole plasma. Standard enzymatic methods were used to determine levels of total cholesterol, triglycerides, and HDL cholesterol on an Abbott Spectrum analyzer.29 30 31 LDL cholesterol was calculated.32 HDL subfractions 2 and 3 were determined by precipitation of HDL2 from total HDL and measurement of the HDL3 remaining in the supernatant. ApoA-I measurement methods were as previously reported.33
Statistical Methods
Logistic regression was used to test for POase and DZOase activity effect in the prediction of CAAD cases (coded as 1) versus controls (coded as 0). Current age was included as a covariate. A Wald statistic was used to test for significance of the effect at the 0.05 level. Separate logistic regressions were tested for a PON1192 and PON155 genotype or combined haplotype effect on the prediction of CAAD status. Another logistic regression tested whether the addition of genotype or combined haplotype information altered the significance of POase and/or DZOase in the prediction of CAAD status. POase, DZOase, and lipid-related measures were transformed by natural logarithm (ln) because of positive skew. Combined haplotype was considered as an alternative to genotype, to allow for joint PON1192 and PON1155 effects or to allow for the possibility that any genotypic effects observed may be due to linkage disequilibrium of the genotype with another etiologic polymorphism. Combined haplotypes (both haplotypes, per subject) were constructed for the PON1 polymorphisms (Table 2), assuming that all PON1192QR-PON155LM subjects had haplotypes MQ and LR; this assumption was based on the rarity of the MR haplotype. The combined haplotypes MQ/MR and LR/MR each had only 1 occurrence and were dropped from haplotype analyses, except for the computation of genetic variance. Genotype or combined haplotype were evaluated as grouped dummy variables, with PON1192QQ, PON155LL, and combined haplotype LQ/LQ as the reference groups. Backward stepwise logistic regression (with use of the likelihood ratio criterion) was used to determine whether the predictive power of POase and DZOase was independent of other factors, with age held as a covariate in the model. There was no statistically significant (at P≤0.05) relationship of POase or DZOase with age in the cases or controls. All analyses used SPSS 8.0 for Windows,34 except for computation of the portion of the total variance (Vt) due to genetic variance (VG), which was computed as VG/Vt.
Results
Preliminary Analyses: Relationship of PON1 Genotypes and Phenotypes
As expected, POase and DZOase are highly correlated within the PON1192 genotype or combined haplotypes (Table 2, Figure 1). The POase and DZOase activity levels are not correlated within the PON155LL or PON155LM genotype. They were correlated within the PON155MM genotype; however, this is likely secondary to the preponderance of PON1192QQ genotypes in that group, which is due to linkage disequilibrium between PON1192Q and PON155M. PON1192 and PON155 genotypes or combined haplotypes predicted significant variation in ln POase and ln DZOase for both cases and controls (ANOVA, all P<0.01), except that the PON155 genotype did not predict significant variation within ln DZOase in the controls. The portion of the total variance in POase and DZOase attributable to genotype or combined haplotype effects is shown in Table 2. The 2 singly occurring combined haplotypes were included in these calculations.
Activity Phenotypes Predicted Vascular Disease
The ln DZOase activity phenotype significantly predicted severe CAAD (CAAD case, coded as 1) versus control (coded as 0) status (P=0.005), by use of logistic regression with age at blood draw (current age) as a covariate. The exponential logistic regression coefficient (Exp-β) was 0.32, with a 95% CI of 0.14 to 0.70. The ln POase activity phenotype also significantly predicted CAAD case versus control status (P=0.019), by use of logistic regression with age (current age) as a covariate. For ln POase, Exp-β was 0.63 (95% CI 0.43 to 0.93). By use of a likelihood ratio test (LRT) to compare nested models, ln DZOase (P=0.006) and ln POase (P=0.023) added to the prediction of CAAD status. In the model including age, ln DZOase, and ln POase as predictors, the exponential coefficients were 0.31 (95% CI 0.14 to 0.71) for ln DZOase and 0.63 (95% CI 0.42 to 0.94) for ln POase.
CAAD cases had significantly lower levels of POase activity (25% reduced) and DZOase activity (16% reduced), see Table 2. The plot of POase versus DZOase activity demonstrated that the cases had lower joint activities without loss of the PON1192 genotype–specific ratios of rates of substrate hydrolysis (Figure 1). This was particularly notable for the PON1192QQ genotype.
Genotype Did Not Predict Vascular Disease Unless Activity Phenotype Is Considered
PON1192 and PON155 genotype distributions and combined haplotype distributions for cases and controls are shown in Table 3. Marginal analysis of PON1192 genotype did not predict CAAD case status, by use of logistic regression with current age included in the model (P=0.75 for the 2 df test). Similarly, PON155 genotype (P=0.83) or combined haplotype (P=0.70 for the 5 df test) individually did not predict CAAD status, with age included as a covariate in the logistic regression model.
When PON1192 genotype, PON155 genotype, or combined haplotype was added to ln DZOase and ln POase (and age) in the CAAD prediction model, the effects of ln DZOase were no longer significant (P=0.93 for the nested LRT), but the effect of genotype or combined haplotype became significant (at P=0.05). Because ln POase and ln DZOase are highly correlated in PON1192 genotype, one would not expect all 3 to be significant predictors in a joint model. When ln POase, PON1192 genotype, and PON155 genotype are entered, with age, as covariates in a logistic regression (ln POase, P<0.0001; PON1192 genotype, P=0.002; and PON155 genotype, P=0.053), 61% of CAAD status is correctly predicted. When combined haplotype is used instead of PON1192 and PON155 genotype, 65.7% of the subjects have their CAAD status correctly predicted. Because these are not nested models, they cannot be compared by LRT. For the model considering ln POase, combined haplotypes, and age, Exp-β was 0.10 (95% CI 0.03 to 0.29) for ln POase, 0.06 (95% CI 0.01 to 0.45) for LQ/LQ (versus LR/LR), 0.02 (95% CI 0.003 to 0.19) for LQ/MQ, 0.008 (95% CI 0.001 to 0.11) for MQ/MQ, 0.27 (95% CI 0.07 to 1.01) for LQ/LR, and 0.31 (95% CI 0.08 to 1.19) for LQ/LR. No evidence of an ln POase genotype or an ln POase combined haplotype multiplicative interaction term was detected at the 0.05 level of significance, although power to detect interactions was expected to be low (data not shown). The same pattern of decreased PON1 hydrolysis rates was seen within each PON1192 genotype, except for the PON1192RR genotype (Figure 2, Table 2). The trend of lower activity phenotypes in the cases was also seen within each PON155 genotype (Table 2). This trend is also noted in the combined haplotypes, except for the MQ/LR and LR/LR combined haplotypes.
Activity Phenotype Effects Were Independent of Other Risk Factors in CAAD Prediction
When ln total cholesterol, ln LDL cholesterol, ln triglycerides, ln apoA-I, ln HDL cholesterol, ln HDL2, ln HDL3, and ln pack-years of smoking were considered in the logistic regression model in addition to ln POase and ln DZOase (and age), ln DZOase remained a statistically significant predictor (P=0.04) of CAAD, but ln POase did not (P=0.31). By use of backward stepwise logistic regression, only ln DZOase, ln HDL, and ln HDL2 contributed to CAAD case-control prediction at the P=0.05 level. This suggests that the effect of DZOase in CAAD prediction is significant independent of the usual lipid risk factors. DZOase activity was negatively correlated with pack-years of smoking (Pearson correlation −0.155, P=0.02); however, DZOase activity significantly predicted vascular disease even when it and ln pack-years were included in a predictive model. When PON1192 and PON155 genotype are added in addition to all the above-listed effects, backward stepwise logistic regression retains the ln POase, ln apoA-I, ln pack-years, PON1192, and PON155 genotype effects as having P≤0.05 in the prediction of CAAD status by LRT. Exp-β for each term was 0.06 (95% CI 0.02 to 0.24) for ln POase, 0.05 (95% CI 0.005 to 0.62) for ln apoA-I, 1.51 (95% CI 1.07 to 2.12) for ln pack-years, 0.017 (95% CI 0.002 to 0.21) for the PON1192QQ versus PON1192RR genotype, 0.28 (95% CI 0.06 to 1.37) for the PON1192QR versus the PON1192RR genotype, 12.4 (95% CI 2.4 to 63.6) for the PON155LL versus the PON155MM genotype, and 9.6 (95% CI 2.15 to 43.0) for the PON155LM versus the PON155MM genotype. This is consistent with prior reports of the PON1192R allele as a risk for vascular disease. These data do not demonstrate a significant risk difference for the PON1192QR genotype versus the PON1192RR genotype. The statistical significance of the PON155 terms, given the inclusion of PON1192 effects in the model, suggests that that the PON155MM genotype is a risk factor for CAAD, separate from any effect of the PON1192 genotype, although this may be due to linkage disequilibrium with another polymorphism.
When PON1 combined haplotypes were considered with ln total cholesterol, ln LDL cholesterol, ln triglycerides, ln apoA-I, ln HDL cholesterol, ln HDL2, ln HDL3, ln pack-years, ln POase, and ln DZOase (and age) and when all variables except age were subjected to backward stepwise logistic regression, only ln POase (P<0.0001), combined haplotypes (P=0.004), ln apoA-I (0.007), ln total cholesterol (P=0.047), and ln pack-years (0.012) significantly predicted CAAD status at the P=0.05 level. Exp-β for each term was 0.04 (95% CI 0.01 to 0.20) for ln POase, 0.03 (95% CI 0.002 to 0.38) for ln apoA-I, 12.2 (95% CI 1.03 to 143) for ln total cholesterol, 1.57 (95% CI 1.10 to 2.22) for ln pack-years, 0.015 (95% CI 0.001 to 0.22) for the PON1 LQ/LQ (versus MR/MR) combined haplotype, 0.008 (95% CI 0.001 to 0.12) for the LQ/MQ combined haplotype, 0.001 (95% CI 0.0001 to 0.03) for the MQ/MQ combined haplotype, 0.24 (95% CI 0.04 to 1.38) for the LQ/LR combined haplotype, and 0.25 (95% CI 0.05 to 1.35) for the MQ/LR combined haplotypes. Thus, subjects with the LR/LR combined haplotypes are estimated to have the highest risk of CAAD, although this risk estimate overlaps with the CIs of any subject with at least 1 LR haplotype. The MQ/MQ combined haplotype subjects are at the least risk, followed by the MQ/LQ subjects, and then the LQ/LQ subjects, although, again, these CIs overlap. When subjects on lipid-lowering medications or those with diabetes were separately excluded, ln POase and combined haplotype remained significant predictors of CAAD at the 0.05 level. PON1192 and PON155 genotypes or combined haplotype were never significant predictors of CAAD status unless PON1 activity phenotype was in the model.
Discussion
The previously examined determinants of POase activity include PON1192 genotype,25 PON155 genotype,35 and the serum concentration of PON1.35 Variation within genotypes, it has been suggested, is primarily due to the variability in PON1 concentration,36 37 hence the correlation of POase and DZOase activities within, but not among, PON1192 genotypes (Figure 1). One study reported that POase activity was determined 46% by PON1192 genotype, 16% by PON155 genotype, and 13% by PON1 concentration.35 Cigarette smoke extract has been shown to inhibit POase activity in vitro,38 and lipid, lipoprotein, or apolipoprotein levels have been weakly associated with PON1 activity or genotype in some,11 17 39 40 but not all,3 35 studies. PON155 genotype was predictive of PON1 concentration in a study of diabetics,37 but this was not found in a study of nondiabetics.35 The lowered POase and DZOase activity seen in cases in the present study may be best attributed to lowered PON1 serum concentration.
Given the large variation in PON1 activities within PON1192 and PON155 genotypes seen in the present study and elsewhere,24 27 41 it is not surprising that the PON1 activity phenotypes provided additional information about risk of vascular disease that was not provided by genotype alone. However, no genotype effect was detectable unless activity phenotype was also considered, even though the PON1192 and/or PON155 genotypes account for a large portion of the variation in POase and DZOase activity. Interestingly, we found that DZOase activity, which is substantially less affected by the PON1192 and PON155 polymorphisms, was more predictive of disease status than was POase activity in a marginal analysis. Smoking did depress DZOase activity, but increased smoking in cases accounted for only 1% of the case-control DZOase activity difference (data not shown). We have shown that the predictive power of PON1 activity for CAAD is not due to any correlations with smoking and lipid levels. The dramatically lowered phenotype activities observed in a subset of the vascular disease subjects may represent phenomena such as promoter mutations. However, most of the cases are shifted toward lower activities, relative to the control subjects. This suggests that the factor(s) responsible for lowering the activities is not rare.
Our results are consistent with a recent study that found that reduced POase activity, but not marginal PON1192 or PON155 genotype, predicted retinopathy and proteinuria in non–insulin-dependent diabetics.42 Our results also suggest that the lowered POase activity reported in myocardial infarction survivors, also without a genotype effect,43 was a risk factor rather than the result of the infarction. The current cohort was older and had a high proportion of smokers. Although this is representative of vascular disease patients, this demographic may differ from some studies that have detected PON1 genotype effects on vascular disease without consideration of PON1 phenotypes.1 2 3 4 5 6 7 12 14 15
The POase and DZOase enzyme activity phenotypes clearly add information about CAAD risk in this cohort and should help clarify the relation of genetic polymorphisms to disease risk. This result should encourage investigators to reevaluate the currently common polymerase chain reaction–only technology when exploring the role of PON1 in vascular disease and other diseases. It raises the broader question of whether it is efficient to study genetic associations without also examining expression. One or more important modifiers of PON1 exist, play a role in atherogenesis, and are not reflected by the PON1192 and PON155 polymorphisms. This may contribute to the conflicting results found when evaluating the association of these polymorphisms with vascular disease risk.
| Characteristic | CAAD Cases | Controls |
|---|---|---|
| n | 106 | 106 |
| Males, % | 100 | 100 |
| White, % | 95 | 95 |
| Type 2 diabetes, % | 24 | 21 |
| On lipid-lowering medication, % | 38 | 18 |
| On antihypertensives, % | 62 | 61 |
| Ever smoked, % | 77 | 57 |
| Smoking, mean pack-years | 37.5 | 22.7 |
| Total cholesterol, mean mmol/L (mg/dL) | 5.100 (197.2) | 5.061 (195.7) |
| Calculated LDL-C, mean mmol/L (mg/dL) | 2.671 (103.3) | 2.640 (102.1) |
| Triglycerides, mean mmol/L (mg/dL) | 1.789 (158.5) | 1.890 (167.4) |
| VLDL-C, mean mmol/L (mg/dL) | 0.817 (31.6) | 0.817 (31.6) |
| ApoA-I, mean mg/dL | 123.8 | 132.4 |
| HDL-C, mean mmol/L (mg/dL) | 1.071 (41.4) | 1.161 (44.9) |
LDL-C, VLDL-C, and HDL-C indicate LDL, VLDL, and HDL cholesterol, respectively.
| Genotype | Activity, U/L | POase-DZOase Correlation | ||||||
|---|---|---|---|---|---|---|---|---|
| Mean POase | Mean DZOase | |||||||
| Case | Control | Case | Control | All | ||||
| PON1 192 | ||||||||
| All | 546.6 | 685.4 | 8 493.1 | 10 009.1 | −0.02 | |||
| 249.5 | 302.7 | 9 345.1 | 11 536.9 | 0.933 | ||||
| QR | 767.1 | 966.7 | 7 872.1 | 9 107.0 | 0.813 | |||
| RR | 1403.9 | 1389.4 | 5 973.0 | 5 872.6 | 0.953 | |||
| VG/VT1 | 0.76 | 0.73 | 0.12 | 0.25 | ||||
| PON1 55 | ||||||||
| LL | 714.0 | 976.5 | 9 185.8 | 10 540.8 | −0.13 | |||
| LM | 503.7 | 555.2 | 8 431.1 | 9 670.7 | −0.203 | |||
| MM | 152.6 | 255.6 | 6 283.9 | 9 618.6 | 0.553 | |||
| VG/VT | 0.17 | 0.33 | 0.08 | 0.02 | ||||
| Combined haplotype | ||||||||
| LQ/LQ | 314.2 | 364.5 | 10 949.6 | 13 059.0 | 0.953 | |||
| LQ/MQ | 250.6 | 278.3 | 9 630.9 | 11 552.8 | 0.913 | |||
| MQ/MQ | 152.6 | 231.4 | 6 283.9 | 9999.9 | 0.953 | |||
| LQ/LR | 777.6 | 1093.9 | 8 730.8 | 11 047.6 | 0.883 | |||
| MQ/LR2 | 760.2 | 828.0 | 7 310.7 | 7 161.5 | 0.733 | |||
| LR/LR | 1473.4 | 1389.4 | 6 259.4 | 5 872.6 | 0.943 | |||
| VG/VT | 0.79 | 0.81 | 0.32 | 0.45 | ||||
1
Portion of total variance due to genotype or combined haplotype effect.
2
Presumed combined haplotype, based on infrequency of MR haplotype.
3
Pearson correlation significant at P=0.05 level.
| Genotype | Cases, n (%) | Controls, n (%) |
|---|---|---|
| PON1 192 | ||
| 55 (51.9) | 50 (47.2) | |
| QR | 43 (40.5) | 48 (45.3) |
| RR | 8 (7.5) | 8 (7.5) |
| PON1 55 | ||
| LL | 40 (37.7) | 42 (39.6) |
| LM | 55 (51.9) | 51 (48.1) |
| MM | 11 (10.4) | 13 (12.3) |
| Combined haplotype | ||
| LQ/LQ | 16 (15.1) | 10 (9.4) |
| LQ/MQ | 28 (26.4) | 28 (26.4) |
| MQ/MQ | 11 (10.4) | 12 (11.3) |
| LQ/LR | 17 (16.0) | 24 (22.6) |
| MQ/LR1 | 26 (24.5) | 23 (21.7) |
| LR/LR | 7 (6.6) | 8 (7.5) |
| MQ/MR | 0 (0) | 1 (0.9) |
| LR/MR | 1 (0.9) | 0 (0) |
1
Assumed (see Methods).
Acknowledgments
This work was funded by the Veteran Affairs Epidemiology Research and Information Center Program (award CSP 701S, G.P.J) and an American Heart Association Physician Scientist Award (G.P.J.), with additional funding from National Institutes of Health grants T32 AG-00057 and RO1 ES-09883. The authors would like to thank the subjects for their participation and thank the following people for their technical assistance: Laura McKinstry, Jeff Rodenbaugh, Dr Nancy Tsai, and Tianji Yu.
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© 2000.
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Received: 13 June 2000
Accepted: 26 July 2000
Published online: 1 November 2000
Published in print: November 2000
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