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Automation and Analytical Techniques |
Departments of1
Biotechnical and Clinical Laboratory Sciences, 2
Social and Preventive Medicine, and 3
Biostatistics, State University of New York at Buffalo, Buffalo, NY.
4 Department of Epidemiology, Italian National Cancer Institute "Regina Elena", Rome, Italy.
aAddress correspondence to this author at: Department of Biotechnical and Clinical Laboratory Sciences, State University of New York at Buffalo, 26 Cary Hall, 3435 Main Street, Buffalo, NY 14214. Fax 716-829-3601; e-mail rwbrowne{at}buffalo.edu.
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Abstract |
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Methods: We have adapted 5 enzyme kinetic assays for high-throughput automated analysis of PON1 activity. Using different substrates and reaction conditions, we measured PON1 activity and used activity ratios to identify the PON1 Q192R genetic polymorphisms and assessed the accuracy of the genotype assignments in 79 adult study participants by comparing them with genotypes determined by AlwI restriction enzyme digestion of a 176-bp PCR amplification product from genomic DNA. Imprecision was determined using pooled serum and purified enzyme preparations. Biological variability was estimated by analysis of serial samples from 17 individuals. Variability parameters were compared with total cholesterol as a point of reference to a recognized biomarker of coronary heart disease risk.
Results: Salt stimulation and inhibition ratios were 97.4% and 94.7% correct in assigning Q192R genotype, respectively. Analytical imprecision (CV) was 1.0%–3.0% for phenylacetate and paraoxon substrate assays and 3.0%–8.0% for the para-nitrophenylacetate substrate assays. Combination of the 2 ratios into a double ratio resulted in 100% correct genotype classification.
Conclusion: The described methods for measurement of PON1 activity and accurate genotype assignment are rapid and have potential to facilitate the efficient investigation of PON1 status in clinical and epidemiological studies.
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Introduction |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
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PON1 has 2 exonic amino acid polymorphisms, 1 at position 192 [a glutamine (Q)/arginine (R) substitution], and 1 at position 55 [a methionine (M)/leucine (L) substitution] (7). The PON1-Q192R polymorphism has been the more extensively studied and has been shown to affect the activity of PON1 alloenzymes with respect to both organophosphate detoxification (8) and lipoprotein oxidation (5).
The PON1-Q192R (paraoxonase 1)2 genotype has been positively associated with coronary heart disease (CHD) in several case-control studies (9)(10)(11)(12)(13)(14)(15)(16), but not in all (17)(18)(19)(20), although a recent metaanalysis (21) indicates an increased frequency of the PON 192 R allele in CHD and that the R allele is associated with an increased risk of CHD. The discrepancy among studies is likely due to the high level of variation of gene expression coupled with the fact that the PON Q192R polymorphism is functional; meaning it affects PON1 activity. In this light, determination of PON1 activity in addition to genotype (referred to as PON1 status) has been advocated to be more important than PON1 genotype alone (21)(22). Larger, preferably prospective, studies are required to determine the relationship between PON1 status and CHD, and these studies will require high-throughput methods capable of measuring PON1 status.
PON1 phenotype can be determined by kinetic enzyme assays. The identification of PON1 phenotypes by their response to 1 mol/L NaCl (23) was refined into the paraoxonase:arylesterase ratio (24). A further modification of the salt-stimulation technique combined the salt-stimulation technique with the differential inhibition of the phenylacetate (PA) hydrolysis by 0.1 mmol/L chlorpromazine (25). Haagan and Brock(26) described the inhibited arylesterase:noninhibited arylesterase ratio, and Mueller (27) described an assay for PON1 phenotype that used the inhibitory effect of EDTA on paraoxonase activity (28). Paraoxon and diazoxon have been used as substrates with adaptation to a microtiter plate system (28). A semiautomated, microtiter plate-based assay has been described (29). These assays are not 100% accurate in assigning genotype and may not be amenable to high-throughput automation. The activity ratios used in these studies overlap, especially between QR and RR genotypes at low enzyme activity, and may introduce misclassification into population-based studies. In the present study, we have automated 5 assays of PON1 activity, used them to assign PON1 phenotype based on activity ratios, and compared these results with PCR–based genotyping.
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Materials and Methods |
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pcr genotyping
Recombinant Taq DNA polymerase, forward and reverse custom oligonucleotide primers, and dNTPs were purchased from Invitrogen, Inc. Restriction endonuclease AlwI was purchased from New England Biolabs. Primers for amplification of a 176-bp sequence coding for position 192 of human PON1 were: 5'-GGG ACC TGA GCA CTT TTA TGG C-3' and 5'-CAT CGG GTG AAA TGT TGA TTC C-3'. PCR product from each sample was restriction digested with AlwI for 2 h at 37 °C. The AlwI recognition site is not present in the PON1 192 A allele but is present in the B allele (7). One of 3 restriction fragment length polymorphism genotype patterns was possible: QQ 176-bp fragment, RR 118-bp and 58-bp fragments, and QR 176-bp, 118-bp, and 58-bp fragments.
kinetic enzyme assays
Instrumentation included the Cobas Fara II automated chemistry analyzers (Roche Diagnostic Systems Inc.), and a Model 160U ultraviolet-visible recording spectrophotometer (Shimadzu Corporation). Unless otherwise indicated all reagents were obtained from Sigma Chemical Company. Diethyl p-nitrophenyl phosphate (paraoxon), 98.0%, was obtained from Chem Service. For all assays water blanks were used to correct for nonenzymatic hydrolysis.
paraoxonase activity and salt-stimulated paraoxonase activity
The rate of formation of p-nitrophenol was measured on the Cobas Fara II analyzer using 1 mmol/L paraoxon in 50 mmol/L glycine buffer, pH 10.5, with 1.0 mmol/L CaCl2, with or without 1 mol/L NaCl. The reaction was initiated by 20 µL diluted sample (1:20 in 25 mmol/L triethanolamine-hydrochlorine, pH 7.4, 1.0 mmol/L CaCl2) to 360 µL working reagent. The rate of p-nitrophenol formation was measured at 405 nm over 200 s with a 25 s lag time. The activity was expressed as U/L based on the molar absorptivity (18 290) of p-nitrophenol at 405 nm, at pH 10.5. Paraoxon is a neurotoxic substance and safety measures included use of dedicated sample and reagent needles and treatment of the on-board wastewater receptacle with concentrated sodium hydroxide.
arylesterase activity with phenyl acetate as substrate
The working reagent consisted of 20 mmol/L Tris-HCl, 1 mmol/L PA, pH 8.0, with 1.0 mmol/L CaCl2. The reaction was initiated by 20 µL of diluted sample (1:3 in TRIS) to 3.0 mL of the working reagent at 25 °C. The change in absorbance at 270 nm was recorded for 60 s after a 20 s lag time on the 160-U spectrophotometer. The activity, expressed as kU/L, was based on the molar absorptivity (1310) of phenol at 270 nm, at pH 8.0 (24). For automated assay on the Cobas Fara, serum samples were automatically diluted 1:4 in TRIS buffer and the enzymatic reaction was initiated by addition of 5 µL of diluted sample to 0.3 mL of the working reagent at 25 °C. The activity, expressed as kU/L, was based on the molar absorptivity (188) of phenol at 285 nm, at pH 8.0 and determined on the 160U spectrophotometer.
arylesterase activity with p-nitrophenyl acetate as substrate and inhibition of p-nitrophenylacetate hydrolysis by phenyl acetate
The working reagent consisted of 25 mmol/L triethanolamine-hydrochlorine buffer, pH 7.4, with 1.0 mmol/L CaCl2 with or without 1 mmol/L phenyl acetate. The start reagent consisted of 2.5 mmol/L p-nitrophenyl acetate in water. The reaction was initiated by addition of 20 µL diluted sample (1:20 in triethanolamine-hydrochlorine buffer) to 288 µL working reagent followed by 72 µL of start reagent. The rate of formation of p-nitrophenol was determined at 405 nm at 25 °C over 225 s after a 100 s lag time. The activity, expressed in kU/L, was based on the molar absorptivity (14 000) of p-nitrophenol at 405 nm, at pH 7.4 (24).
enzyme activity ratios
To differentiate between PON1 phenotypes we calculated activity ratios (24)(26). The salt-stimulation ratio (SALT/PA) was defined as the salt-stimulated paraoxonase activity (SALT) over arylesterase activity, with PA as substrate (24). The inhibition ratio [(IA-IAO)/NIA] was defined as the PA-inhibited arylesterase activity (IA) with p-nitrophenyl acetate as substrate minus the estimate of influence of nonspecific arylesterase activity of other carboxylic ester hydrolases (IAO) divided by the noninhibited arylesterase activity (NIA) with p-nitrophenylacetate alone as substrate (26). Finally, a double ratio, dubbed the PON salt-stimulation/similar-substrate inhibition (PON 4SI) ratio, was defined as (SALT/PA)/[(IA-IAO)/NIA]. The activity of PON to hydrolyze paraoxon in the absence of 1 mol/L NaCl (PXON) was not used in the calculation of ratios but was measured nonetheless as a further indicator of PON1 activity.
partial purification of pon 1 from human serum
PON1Q and PON1R alloenzymes were partially purified from 200 mL of pooled human serum according to the methods described by Gan et al. (32). The final DEAE anion exchange fractions were screened for total protein and arylesterase activity and the highest specific activity fractions were used as a QC material.
total cholesterol measurement
Total serum cholesterol was determined by cholesterol oxidase methodology with reagents, calibrators, and controls from Wako Diagnostics, Inc.
method performance characteristics
QC materials consisted of 3 human serum pools (QQ, QR, and RR) and 2 preparations (QQ and RR) of partially purified PON1. Within-run imprecision was calculated on 20 replicates of each material. Between-run imprecision was estimated by analysis of 5 replicates per day on 5 consecutive days. Imprecision was expressed as the CV and the percentage of total sum of squares (SS) attributed to each component, where within-run SS + between-run SS = Total SS. Correlation among PON1 activity assays was calculated by Pearson regression. Agreement between manual and automated arylesterase activity measurements was calculated as the interclass correlation coefficient.
method accuracy
PCR/AlwI genotype analysis was use as the standard to compare the efficiency [correctly classified phenotypes/(correctly classified phenotypes + incorrectly classified phenotypes)] of activity ratios to classify QQ homozygotes vs QR heterozygotes and for QR heterozygotes vs RR homozygotes. Cutoff points for classifying genotype by activity ratio(s) were determined by plotting the distribution of ratio values for each genotype and identifying the point of overlap between adjacent distributions.
biological variability
To describe the observed variability we used an unconditional hierarchical nested random effects model. The model assumes the total variance in the population is represented by 
T2 = G2 + I2 + A2, and variance within an individual is represented by A+I2 = I2 + A2, where the subscript G = among group, I = within individual, and A= analytical or within replicate. IA and NIA were log transformed to meet statistical assumptions. Estimates of the variance obtained from the fitted model (SG2, SI2 and SA2) and the percentage each component represents in terms of the total were computed, as were the CVs (CVG, CVI and CVA). The index of individuality (I) was defined as I = SA+I/SG, where SA+I = (SA2 + SI2)1/2. To determine the number of measurements (k) needed to be taken on an individual so that I was at least as small as the cholesterol index of individuality, IChol, we used the formula, k>(IChol–1IMean)2. In this context cholesterol was used as a point of reference to a well-established biomarker of CHD risk. We also calculated the analytical acceptability index, defined as CVA/CVI = SA/SI, an index of analytical error. The standard criterion states that the maximum allowable error should be less than or equal to half the intraindividual biological variation (33). SAS version 9.0 statistical software was used for all analyses.
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Results |
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pon1 enzyme assays
The descriptive statistics, stratified by PON1 genotype, are listed in Table 1
. These values agree closely with previous reports of PON1 activity against the substrates and reaction conditions selected for this study (24)(26). The correlations for all pairs of analyses (with different substrates and reaction conditions) were >0.64, with most >0.90 (Table 2
). The automated and manual PA methods were highly correlated (Pearson r = 0.96, interclass correlation coefficient = 0.929), but imprecision of the automated method was higher (Table 3
). A Bland–Altman plot indicated that results for the automated method were slightly higher than expected at high activity and slightly lower than expected at low activity (data not shown). Phenotypes assigned by the SALT/PA ratio, however, were identical for the 2 PA methods, and the automated PA values were used for all subsequent data analyses.
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The distribution of the IA-IAO/NIA ratio was trimodal (Fig. 1A
). We used the Kolmogorov–Smirnov test to test for gaussian distribution of the ratio values for each genotype. A log transform was applied to nongaussian data, the transformed mean and SD were calculated, and the inverse log was taken to plot a distribution for each genotype (as determined by PCR). The cutoff points for assigning phenotype based on activity ratio are shown in Fig. 1A
and 1B
. Similar plots for the SALT/PA ratio are shown in Fig. 2
.
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The SALT/PA method correctly classified 78 of 79 genotypes, and the IA-IAO/NIA method correctly classified 77 of 79. Both ratios are able to completely distinguish between QQ and QR phenotypes, and the efficiency for each method was 100% with respect to these 2 genotypes. There was misclassification, however, between QR and RR genotypes. The SALT/PA method misclassified one RR genotype as a QR phenotype. The IA-IAO/NIA method misclassified one RR genotype as a QR genotype and one QR genotype as a RR genotype. The area of overlap between QR and RR distributions appeared to be less in the SALT/PA method than in the IA-IAO/NIA method, and the correct classification rates of the 2 methods were 97.4% and 94.7%, respectively. Combination of these ratios into the PON 4SI ratio completely separated QR and RR phenotypes (Fig. 3
).
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The QC materials reflected the activity found in serum in that the QQ material had the lowest activity, the RR material had the highest activity, and the QR activities were intermediate. All assays demonstrated CV <5% except the IA method, which had imprecision that increased from 3% to 8% as the enzyme activity decreased. The NIA method also demonstrated an increase in imprecision at lower enzyme activity. We attribute this observation to both nonenzymatic hydrolysis of the p-nitrophenylacetate substrate during the reaction and non–paraoxonase-specific hydrolysis. Although water blanks were used to account for this nonenzymatic hydrolysis, we found these blank measurements to be highly variable as well. The imprecision of the blank contributed more to the total change in absorbance per minute at lower enzyme activity, which was reflected in increased imprecision in the QQ control material relative to the QR and RR control material. We further noted a decrease in imprecision in the partially purified PON1 preparations relative to frozen serum samples for the para-nitrophenylacetate assays, which we attributed to removal of non–paraoxonase-specific hydrolysis by the purification steps. ANOVA of the QC data showed that the within-run sum of squares comprised >90% of the total sum of squares when within-run and between-run measurements were combined, indicating that nearly all the analytical variation was due to within-run imprecision.
Results of ANOVA separating the sources of variation into analytical variance (SA2), intraindividual variance (SI2), and interindividual or group variance (SG2) are shown in Table 3
. For assays using PA and paraoxonase, <10% of the total variance was attributed to analytical and intraindividual variability combined, indicating that the majority of difference within our study population was due to differences among individuals. The assays using p-nitrophenyl acetate as substrate had higher analytical variability than did paraoxon and PA assays. We hypothesize that the nonenzymatic and non–paraoxonase-specific hydrolysis of p-nitrophenylacetate in the reaction is the major contributor to this variability. Before modification of the NIA and IA assays (i.e., removing the substrate from the working reagent into a separate start reagent and thus minimizing the nonspecific hydrolysis of the substrate), the estimates of analytical imprecision (within-run and between-run CVs) and the estimated percentage of variance attributable to analytical variation (%SA2) were 50% to 60%higher (data not shown).
For optimal test interpretation, the analytical acceptability index specifies having CVA 
CVI or CVA/CVI 0.5 (33). None of the described assays had an analytical acceptability index <0.5 except for total cholesterol. The paraoxon- and PA-based assays had indices of 0.58–0.68, and the 4 nitrophenol-based assays had indices of 1.79–3.69. The intraindividual ranges for assay results were narrow compared with group ranges, and the values of the index of individuality were lower than those of cholesterol for all assays except the IA assay.
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Discussion |
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We modified the molecular methods (7) by using different forward and reverse primers to lengthen the PCR product from a 99-bp to a 176-bp amplimer. We had difficulty resolving the 99-bp amplimer cut and uncut fragments from the 22 and 23mer PCR primers on 3% agarose, and the 176-bp product was more easily resolved, as was the 118-bp digestion product. Thermocycler parameters were adjusted to 35 cycles to increase the PCR product without having to do a secondary amplification, decreasing the number of steps and the potential for contamination.
Five kinetic enzyme methods were adapted to the Cobas Fara II autoanalyzer. Manual PON 1 arylesterase activity with PA as substrate at 270 nm was compared with the Cobas Fara II, which has a lower wavelength limit of 285 nm. The suboptimal wavelength on the Cobas Fara II caused an increase in assay CVs but did not change the genotype assignment by activity ratios. Paraoxonase assay parameters were only minimally modified, and our results closely parallel other reports (24). The PON1-inhibition technique(26) was modified more substantially. Para-nitrophenylacetate is subject to significant spontaneous hydrolysis in the reagent buffer system originally described. This hydrolysis was grossly apparent in the yellow color of the reagent. We removed this substrate from the working reagent buffer and prepared it in water as a separate starting reagent, which remained colorless. The starting reagent was added to initiate the kinetic reaction, and this modification reduced the CV of both sample and sample blank readings and improved the reproducibility of the assay.
In addition to using QC material to generate estimates of analytical imprecision and describing the proportion of total variance attributed to analytical variance, we calculated an index of analytical acceptability defined as CVA CVI. The rationale for selecting the fraction has been previously described (33). This index has been used to judge the ability of analytical methods to detect individual variations that indicate a disease state or significant changes over time. Based on this criterion, the assays described here are not analytically acceptable to detect small changes within an individual over the 1-month time frame studied.
The index of individuality is a means to assess the usefulness of conventional population-based reference intervals. If the index is >1.4, the test results from an individual can be compared usefully to the reference interval. If the index is <0.6, reference intervals are of limited value because of limited day-to-day variation and/or a large variation between individuals in the population (35). The low index of individuality found in this study reflects a large variation in serum PON1 activity between individuals and indicates that although these assays (except for the measurement of IA) can detect differences between individuals in a population, the use of population-based reference intervals based solely on PON1 activity will have limited utility. Because each genotype is associated with significant differences in activity it may be more useful to consider PON1 status or genotype-specific reference intervals with regard to PON1 activity in epidemiological studies.
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Acknowledgments |
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Footnotes |
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1 Nonstandard abbreviations: PON1, human serum paraoxonase 1; PA, phenylacetate; CHD, coronary heart disease; SALT, salt-stimulated paraxonase activity; IA, phenylacetate-inhibited arylesterase activity; IAO, estimate of influence of nonspecific arylesterase activity of other carboxylic ester hydrolases; NIA, noninhibited arylesterase activity; PON 4SI ratio, PON salt-stimulation/similar-substrate inhibition, or (SALT/PA)/[(IA-IAO)/NIA]; PXON, the activity of PON to hydrolyze paraoxon in the absence of 1 mol/L NaCl; SS, total sum of squares; I, index of individuality; SA2, analytical variance; SI2, intraindividual variance; SG2, interindividual or group variance; %SA2, estimated percentage of variance attributable to analytical variation.
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References |
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The following articles in journals at HighWire Press have cited this article:
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