Received on June 7, 2006
Accepted on November 20, 2006

Automation and Analytical Techniques

Accuracy and Biological Variation of Human Serum Paraoxonase 1 Activity and Polymorphism (Q192R) by Kinetic Enzyme Assay

¹ Department of Biotechnical and Clinical Laboratory Sciences, State University of New York at Buffalo, Buffalo, NY
² Department of Biostatistics, State University of New York at Buffalo, Buffalo, NY
³ Department of Epidemiology, Italian National Cancer Institute "Regina Elena", Rome, Italy
⁴ Department of Social and Preventive Medicine, State University of New York at Buffalo, Buffalo, NY

^* To whom correspondence should be addressed. E-mail: e-mail rwbrowne{at}buffalo.edu.

Background: Paraoxonase 1 (PON1) phenotype is a better predictor of atherosclerosis risk than are PON1 genetic polymorphisms alone. Larger studies are required to determine the role of PON1 and there is a need for standardized PON1 assays between laboratories.

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.