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(Stroke. 2003;34:1176.)
© 2003 American Heart Association, Inc.

Original Contributions

Lipoprotein Lipase (LPL) Gene Variation and Progression of Carotid Artery Plaque

J. David Spence, MD; Matthew R. Ban, BSc Robert A. Hegele, MD

From the Stroke Prevention and Atherosclerosis Research Centre (J.D.S.) and Blackburn Cardiovascular Genetics Laboratory (M.R.B., R.A.H.), Robarts Research Institute, London, Ontario, Canada.

Correspondence to Dr David Spence, Stroke Prevention and Atherosclerosis Research Centre, 1400 Western Rd, London, Ontario, Canada N6G 2V2. E-mail dspence{at}robarts.ca

	Abstract

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Background and Purpose— Coding single nucleotide polymorphisms (cSNPs) in the lipoprotein lipase (LPL) gene have been associated with lipoprotein phenotypes and vascular disease risk. We studied the association between LPL cSNPs and a novel noninvasive measure of disease, namely, cross-sectional carotid plaque area (CPA) on B-mode ultrasound.

Methods— Four hundred fifty-two patients from an atherosclerosis prevention clinic had determinations of baseline and total CPA. Traditional atherosclerosis risk factors were recorded, and the LPL D9N, N291S, and S447X cSNPs were genotyped. Multiple regression analysis was used to identify determinants of CPA.

Results— Minor allele frequencies for LPL D9N, N291S, and S447X were 2.8%, 0.9%, and 4.4%, respectively. There were no significant between-genotype differences in treated fasting lipids. The LPL D9N genotype was a significant predictor of both baseline CPA (P=0.008) and plaque progression from baseline to 1 year later (P=0.001). Heterozygotes for the N9 allele had higher mean baseline CPA and plaque progression than did LPL D9/D9 homozygotes.

Conclusions— LPL D9N genotype may be a determinant of atherosclerosis as estimated by static baseline CPA and by progression of CPA.

Key Words: atherosclerosis • carotid artery plaque • genetics • lipoprotein lipase

	Introduction

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Lipoprotein lipase (LPL) plays a key role in the hydrolysis of circulating triglyceride-rich lipoproteins, such as chylomicrons and VLDL, which appear to be determinants of vascular disease risk.¹ LPL is the predominant plasma triglyceride lipase and is bound to vascular endothelium through interaction with membrane-anchored proteoglycans.¹ While the main catalytic activity of LPL is within the capillary beds of skeletal muscle and adipose tissue, it also has a nonenzymatic molecular bridging function, which mediates the cellular uptake of lipoproteins.¹ Thus, the catalytic function of LPL is probably antiatherogenic, while the noncatalytic bridging function may be proatherogenic.

Over the last decade, several DNA polymorphisms in the LPL gene have been evaluated for their association with clinical traits.^2–7 LPL coding sequence single nucleotide polymorphisms (cSNPs) that alter the protein sequence have been associated with variation in fasting lipoproteins,^2–7 postprandial lipoproteins,^8,9 coronary artery disease,^10–19 and cerebrovascular disease,^20,21 although there are some important disparities.¹³ The relationship between LPL variation and the progression of vascular disease has not yet been examined. We previously demonstrated that the total cross-sectional area of all plaques determined by B-mode ultrasonography of common, internal, and external carotid arteries (carotid plaque area [CPA]) was associated with traditional and nontraditional atherosclerosis risk factors.^22–25 In addition, both baseline CPA and the rate of progression of CPA were strong independent predictors of vascular disease risk.²⁶ Patients in the top quartile of baseline plaque have a 3.5-fold increase in risk of stroke, death, or myocardial infarction over 5 years compared with the lowest quartile, and patients with progression have a 2-fold increase in risk compared with those with regression or stable plaque.²⁶ Thus, CPA may represent a useful adjunctive noninvasive measure for assessment and prediction of vascular disease risk. In the present report we tested for association between genetic variation in LPL marked by nonsynonymous cSNPs and interindividual variation in both baseline CPA and the progression of CPA.

	Subjects and Methods

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Study Sample
Study participants each attended the Atherosclerosis Prevention Clinic of the London Health Sciences Centre, London, Canada. Each subject had measurement of CPA at baseline and at 1 year, together with baseline medical history, physical examination, and fasting plasma lipoprotein profile. Genotypes were based on the nonsynonymous cSNPs at LPL codons 9, 291, and 447, namely, D9N, N291S, and S447X. Briefly, from genomic DNA that was extracted from peripheral blood leukocytes, a thermostable DNA polymerase was used to amplify the coding region surrounding the polymorphic sites at codons 9, 291, and 447 in 3 different amplification reactions for each DNA sample. The amplified fragments were then exposed to the appropriate restriction endonucleases.¹⁷ Electrophoresis in 2% agarose gels was used to identify size polymorphism of the digested fragments.¹⁷ Polymorphism in the length of the restriction fragment was used to score the genotype for the specific SNP, as described.¹⁷ Sequence-proven control samples were used for each genotyping reaction.

Measurement of Atherosclerosis
CPA was measured as described previously^22–26 with the use of a high-resolution duplex ultrasound scanner (initially an ATL Mark 9, more recently an ATL 5000 HDI; Advanced Technology Laboratories). Plaque was defined as a local thickening of the intima >1 mm. Measurements were made in magnified longitudinal views of each plaque seen in the right and left common, internal, and external carotid artery. The plane for measurement of each plaque was chosen by scanning to find the largest extent of plaque. The image was then frozen and magnified, and the plaque was measured by tracing around the perimeter with a cursor on the screen. The microprocessor in the scanner then displayed the cross-sectional area of the plaque. The operator then moved on to the next plaque and repeated the process until all observed plaques were measured. The sum of cross-sectional areas of all plaques between the clavicle and the angle of the jaw was taken as total plaque area. Intraobserver reliability was 0.94 for repeated measurements; interobserver reliability was 0.85.^22,26 All measurements used in this study were made by the same certified vascular ultrasound technologist.

Statistical Methods
Data were entered and analyzed with the use of SPSS PC+ 10.0 (SPSS). Deviation from Hardy-Weinberg equilibrium was determined by ² analysis. Multiple regression analysis was performed with a cube root transformation of CPA, which resulted in a variable with a distribution not significantly different from normal, and a linear probability plot. Independent variables included in the regression model were those traditional risk factors that we previously identified as being significant predictors of CPA, including age, sex, systolic blood pressure, plasma total cholesterol, pack-years of smoking, treatment of hyperlipidemia, and treatment of hypertension.^23–25 We used ² analysis to test for differences among genotypes with respect to baseline history of myocardial infarction, stroke, or transient ischemic attack, assuming a dominant model for the minor allele in each instance.

	Results

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Clinical Attributes
Baseline clinical features of the study population are shown in Table 1. The patients were typical of a sample drawn from an atherosclerosis prevention clinic: middle-aged, overweight as indicated by body mass index (BMI), and having several risk factors.

View this table: [in this window] [in a new window]   TABLE 1. Clinical Attributes of Study Sample

LPL Genotypes
Allele and genotype frequencies among the study subjects of the 3 LPL cSNPs are shown in Table 2. Genotype frequencies did not deviate from Hardy-Weinberg expectations.

View this table: [in this window] [in a new window]   TABLE 2. Genetic Attributes of Sample

Genotype-Phenotype Associations
There were no significant associations between any LPL genotype and any clinical or biochemical trait (data not shown). The multiple regression analysis of determinants of baseline CPA is shown in Table 3. Variables entered were based on our previous work, in which the proportion of explained plaque area (r²) was 0.513; all variables were significant predictors of baseline plaque with a probability value <0.007, in a sample of >1600 patients.²⁶ For the present study of 452 cases, in the overall regression model before LPL genotypes were entered, the proportion of baseline CPA that was explained by the risk factors (r²) was 0.394.

View this table: [in this window] [in a new window]   TABLE 3. Multiple Regression Model for Baseline CPA

When BMI and the genotypes were entered singly into the complete regression model (Table 4), only D9N was a significant predictor of baseline plaque (ß=0.144, P=0.003). Among the subjects who had been genotyped for LPL D9N, the baseline CPA (mean±SD) was 0.94±0.32 cm² in the N9/D9 heterozygotes compared with 0.53±0.06 cm² in the D9/D9 homozygotes (P<0.05). The effect of N291S genotype approached significance (ß=-0.087, P=0.06) but that of S447X genotype did not (ß=-0.028, P=0.47). The effect of BMI was not significant (ß=-0.028, P=0.13). With pairwise entry of BMI and each LPL genotype, the standardized ß for D9N increased to 0.157 (P=0.006), whereas the ß for BMI decreased to -0.023 (P=0.68), suggesting an interaction between genotype and BMI. This interaction was specifically tested with the use of an interaction term in the multivariate analysis (general linear model) and was found to be significant (P=0.007). There was no interaction of BMI with the other LPL cSNPs.

View this table: [in this window] [in a new window]   TABLE 4. Multiple Regression Model of Baseline CPA With LPL Genotype

In the multiple regression model for prediction of progression of plaque area from baseline to 1 year later (Table 5), only LPL D9N genotype predicted progression of plaque from baseline to 1 year later (ß=0.241, P=0.001). None of the traditional risk factors was a significant predictor of progression. Among the subjects who had been genotyped for LPL D9N, the progression in CPA was 0.53±0.41 cm²/y in the N9/D9 heterozygotes compared with 0.077±0.023 cm²/y in the D9/D9 homozygotes (P<0.001).

View this table: [in this window] [in a new window]   TABLE 5. Stepwise Multiple Regression for CPA Progression Over 1 Year

	Discussion

Top Abstract Introduction Subjects and Methods Results Discussion References

 
There is still no uniform consensus regarding the relationship between candidate gene variation and plasma triglyceride concentrations. Common variants, in particular LPL D9N and N291S, appear to be fairly consistently associated with variation in plasma lipoprotein concentrations.¹³ Common variants of some other candidate genes, such as hepatic lipase, have not been shown to have consistent associations with plasma triglycerides. Studies of newer candidates such as the mitochondrial genome, nuclear lamin A/C, and interleukin-6 indicate that many different genes may contribute importantly to plasma triglyceride in different populations.³

The mechanistic basis for the observed association between LPL D9N and both CPA at baseline and plaque progression is not clear. The product of the D9N allele has been associated with low enzyme activity,⁵ although LPL activity as an intermediate trait was not assessed in this study sample. Furthermore, the relationship between the LPL D9N marker and carotid plaque was independent of such established risk factors as plasma lipids. Talmud and Humphries⁵ recently speculated that LPL D9N polymorphism may be associated with an increased bridging function, resulting in increased uptake of lipoprotein particles into cells of the vascular wall. While this has yet to be tested in vitro, if such a mechanism were correct, then LPL D9N could be associated with variation in atherosclerosis end points but not have any relationship with variation in lipase activity and/or plasma lipoprotein concentrations. The reason why the LPL genotype was related to plaque progression while traditional risk factors were not could have been due to the fact that the traditional risk factors were being treated over the period between the baseline and follow-up measurements.

The literature is inconsistent with respect to associations between LPL SNP genotypes and vascular disease end points.^3–21 For instance, in the Framingham Offspring Study,⁷ both D9N and N291S were associated with lipoprotein changes compatible with increased atherosclerosis risk, while in the Atherosclerosis Risk in Communities Study,²¹ S447X was associated with MRI-detected strokes but not with changes in plasma lipoproteins. A more extensive review of all LPL gene association studies performed to the present is beyond the scope of this article. However, disparities may not be that surprising when it is considered that LPL has several functions in vivo, some of which are mechanistically opposed. Thus, any particular associations found in one specific population may not translate to others. Another point that may contribute to discrepancies may be intersample differences with respect to linkage disequilibrium between a measured marker and an unmeasured functional allele at or near the LPL locus.

Like the D9N allele, the product of the less common LPL N291S allele has been associated with low enzyme activity. In contrast, the product of the less common S447X allele has been associated with increased enzyme activity.²⁷ LPL activity has been associated with angina severity in a study of statin drugs and angiographic progression of coronary disease.²⁸ In that study 47% of patients in the lowest quartile of LPL activity had severe angina compared with only 29% of subjects in the highest quartile of LPL activity.²⁸ There has been some indication that the LPL S447X variant may protect against elevated triglycerides, depressed HDL cholesterol, and coronary heart disease in men.¹⁴ We found no association of this variant with reduced or increased CPA at baseline or with CPA progression.

There is increasing evidence that postprandial lipids are as important as fasting lipids as determinants of disease states.^29–31 Even dietary cholesterol, which has traditionally not been thought to be important, is emerging as a significant contributor to fasting lipids and oxidized LDL and as a risk factor for vascular disease.^32–34 A high-fat meal impairs endothelial function for approximately 4 hours, an effect that can be reduced by antioxidant vitamins.^35,36 A Mediterranean diet has been shown to improve endothelial function.³⁷ These observations suggest that oxidative stress may be an important mechanism underlying the adverse effect of diets high in animal fat.

Postprandial lipemia appears to be related both to fat intake and to variations in postprandial lipid metabolism.³⁸ Polymorphisms of some genes, including LPL, have been reported to alter the relationship between visceral obesity and plasma lipoproteins.³⁹ LPL polymorphism has also been shown to be associated with greater response of lipid levels to caloric restriction in obese patients.⁴⁰ There are several genetic factors that can affect responsiveness of plasma lipoproteins to dietary intervention.⁴¹ Some studies have shown that LPL genotypes are important determinants of postprandial lipids^8,9 and response of plasma lipids to diet.⁴² Our observation that the interaction between LPL variation and BMI was associated with CPA mirrors a similar interaction reported in association with plasma triglycerides.⁴³ LPL activity has been shown to be upregulated in response to caloric restriction,⁴⁴ and therefore it is possible that an interaction between LPL genotype and BMI could also affect clinical phenotypes, such as plasma lipoproteins or vascular disease.

In summary, we found that the LPL D9N genotype was a significant predictor of baseline CPA and that this association might have been modulated by BMI. In addition, the LPL D9N genotype was strongly associated with plaque progression over a 1-year period. The findings suggest that LPL D9N genotype may be an important determinant of atherosclerosis as estimated by progression of CPA.

	Acknowledgments

 
This work was supported by grants T4772 (Dr Hegele) and T5017 (Dr Spence) from the Heart and Stroke Foundation of Ontario. Dr Hegele holds a Canada Research Chair (Tier I) in Human Genetics and a Career Investigator Award from the Heart and Stroke Foundation of Ontario. We wish to thank Maria DiCicco, RVT, for her meticulous measurements of carotid plaque area.

	Footnotes

 
This article was guest-edited by Dr John W. Norris, Associate Editor, Toronto.

Received August 27, 2002; revision received December 3, 2002; accepted December 10, 2002.

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