RESULTS Meta- analysis suggested that statin therapy is associated with a significant elevation of PON1 paraoxonase and arylesterase activities , but not PON1 protein concentration .
The PON1-enhancing effects of statins were robust in the sensitivity analyses and were independent of statin dose , treatment duration and changes in plasma low-density lipoprotein cholesterol concentration .
CONCLUSION The increase of paraoxonase and arylesterase activities with statins is a pleiotropic lipid-independent clinical benefit that may partly explain the putative effects of statins in preventing cardiovascular outcomes
BACKGROUND Decreased activity of the enzyme paraoxonase-1 ( PON1 ) has been demonstrated in cardiovascular diseases .
Statins , the forefront of pharmacotherapy for dyslipidemia , have been shown to enhance PON1 activity but clinical findings have not been conclusive .
OBJECTIVE To systematic ally review the clinical findings on the impact of statin therapy on PON1 status ( protein concentrations and activities of paraoxonase and arylesterase ) and calculate an effect size for the mentioned effects through meta- analysis of available data .
Paraoxonase genotype modifies the effect of pravastatin on high-density lipoprotein cholesterol.
Paraoxonase ( PON ) is an enzyme carried by high-density lipoprotein cholesterol ( HDL-C ) . Two gene polymorphisms leading to amino acid substitutions of methionine for leucine at position 55 ( M/L55 ) and arginine for glutamine at position 192 ( R/Q192 ) modulate the activity of the enzyme and possibly also lipid and apolipoprotein concentrations . Our purpose was to examine the effect of the PON genotype on HDL-C and apolipoprotein AI ( apo AI ) responses to pravastatin treatment . Fifty-one mildly hypercholesterolemic male subjects ( mean age 35 + /- 4 years ) were enrolled by this prospect i ve , r and omized , double-blind study . Lipid concentrations were measured at baseline and after 6 months of pravastatin ( n = 25 ) or placebo ( n = 26 ) therapy . Low active ( MM , ML or QQ ) and high active ( LL or RQ , RR ) PON genotype groups were related to lipid and apolipoprotein concentration changes . Pravastatin increased the apo AI concentration 12 % ( P = 0.017 , RANOVA ) and tended to increase the HDL-C concentration ( P = 0.095 , RANOVA ) in R allele carriers but not in QQ homozygotes . Significant predictors of the change in apo AI concentration during pravastatin treatment were R/Q192 genotype ( P = 0.002 ) , apo AI concentration at baseline ( P = 0.002 ) and M/L55 genotype ( P = 0.042 ) . Correspondingly , R/Q192 ( P = 0.009 ) and M/L55 ( P = 0.050 ) genotypes were the statistically significant determinants of HDL-C concentration change . The PON genotype thus modifies the effect of pravastatin on serum HDL-C and apo AI concentrations . This could partly explain the contradictory results obtained from previous studies on the effects of statins on the serum HDL-C concentration
RESULTS Meta- analysis suggested that statin therapy is associated with a significant elevation of PON1 paraoxonase and arylesterase activities , but not PON1 protein concentration .
The PON1-enhancing effects of statins were robust in the sensitivity analyses and were independent of statin dose , treatment duration and changes in plasma low-density lipoprotein cholesterol concentration .
CONCLUSION The increase of paraoxonase and arylesterase activities with statins is a pleiotropic lipid-independent clinical benefit that may partly explain the putative effects of statins in preventing cardiovascular outcomes
BACKGROUND Decreased activity of the enzyme paraoxonase-1 ( PON1 ) has been demonstrated in cardiovascular diseases .
Statins , the forefront of pharmacotherapy for dyslipidemia , have been shown to enhance PON1 activity but clinical findings have not been conclusive .
OBJECTIVE To systematic ally review the clinical findings on the impact of statin therapy on PON1 status ( protein concentrations and activities of paraoxonase and arylesterase ) and calculate an effect size for the mentioned effects through meta- analysis of available data .