Non-HDL cholesterol is strongly associated with coronary artery calcification in asymptomatic individuals

Atherosclerosis 202 (2009) 289–295

Non-HDL cholesterol is strongly associated with coronary artery calcification in asymptomatic individuals Sarwar H. Orakzai a , Khurram Nasir b , Michael Blaha c , Roger S. Blumenthal c , Paolo Raggi d,∗ a b

Department of Cardiology, Baylor College of Medicine, St. Luke’s Episcopal Hospital/Texas Heart Institute, Houston, TX, United States Cardiac PET CT MRI Program, Massachusetts General Hospital, Boston, MA, Harvard School of Medicine, Boston, MA, United States c The Ciccarone Preventive Cardiology Center, Johns Hopkins University School of Medicine, Baltimore, MD, United States d Division of Cardiology, Department of Medicine-Cardiology, Emory University School of Medicine, 1365 Clifton Road, AT-504, Atlanta, GA 30322, United States Received 26 December 2007; received in revised form 12 March 2008; accepted 13 March 2008 Available online 25 March 2008

Abstract Background: Growing evidence shows that non-high-density lipoprotein cholesterol (Non-HDL-C) is a strong and independent predictor of cardiovascular disease (CVD). Few studies have assessed the association between traditional lipid measures and subclinical end points. In this study we analyzed the association of Non-HDL-C, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and triglycerides (TG) with coronary artery calcium (CAC), a marker of subclinical atherosclerosis. Methods: The study population consisted of 1611 consecutive asymptomatic individuals (67% men, mean age: 53 ± 10 years) referred to a single electron beam tomography (EBT) facility for CAC screening. Multivariate logistic regression was used to test the association between increasing quartiles of lipid levels and presence of CAC score (CACS) > 0 and CACS ≥ 100, with the lowest levels (first quartile) of lipid values as reference. Results: Overall CACS of 0, 1–99, 100–399 and ≥400, were observed in 35%, 44%, 12% and 9% of the study subjects, respectively. The prevalence of CAC increased significantly across increasing quartiles of LDL-C, TG and Non-HDL-C (all p < 0.0001), whereas CACS was significantly lower across increasing quartiles of HDL-C (p < 0.001). In a multivariate model controlling for age, gender, race, cigarette smoking, hypertension, family history of coronary artery disease and obesity, there was a significant increase in the prevalence of CAC with increasing values of each lipid variable. In a multivariate model simultaneously controlling for increasing quartiles of the remaining lipid variables, only the association of Non-HDL-C with CACS > 0 remained statistically significant (p = 0.002). Similar results were observed with CACS ≥ 100 (p = 0.038). Conclusion: In this study Non-HDL-C was more strongly associated with subclinical atherosclerosis than all other conventional lipid values. These data suggests that Non-HDL-C may be an important treatment target in primary prevention. © 2008 Elsevier Ireland Ltd. All rights reserved. Keywords: Coronary artery calcium; Atherosclerosis; Lipoproteins; Cholesterol; Non-high-density lipoprotein cholesterol

1. Introduction Low-density lipoprotein cholesterol (LDL-C) has long been considered a major determinant of atherosclerosis and the primary target of lipid-lowering therapy for prevention of cardiovascular disease (CVD) [1]. In subjects with ∗

Corresponding author. Tel.: +1 404 778 5414; fax: +1 404 778 3540. E-mail address: [email protected] (P. Raggi).

0021-9150/$ – see front matter © 2008 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.atherosclerosis.2008.03.014

low triglyceride (TG) levels, LDL-C contains the bulk of atherogenic cholesterol. However triglyceride-rich lipoproteins, very-low-density lipoprotein cholesterol (VLDL-C) and intermediate-density lipoprotein cholesterol (IDL-C), carry a large amount of atherogenic cholesterol in subjects with elevated TG. The National Cholesterol Education Program (NCEP) Adult Treatment Panel III (NCEP ATPIII) guidelines thus recommend that Non-high-density lipoprotein cholesterol (Non-HDL-C) be considered as a secondary

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target of therapy among individuals with TG > 2.26 mmol/l (200 mg/dl) [1]. Non-HDL-C is defined as the difference between total cholesterol (TC) and high-density lipoprotein cholesterol (HDL-C) and, thus, represents cholesterol carried on all proatherogenic apo-B-containing particles [VLDL-C, IDLC, LDL-C as well as chylomicron remnants and lipoprotein (a)]. The most common pattern of dyslipidemia in patients with type-2 diabetes is elevated TG levels and decreased HDL-C levels, with LDL-C levels being similar to that seen in patients without diabetes [2]. Therefore Non-HDL-C has been considered to be particularly valuable in patients with type-2 diabetes [3]. Non-HDL-C has been shown to be an effective predictor of outcome in patients with [4] and without established CVD [5], with end-stage renal failure [6] and diabetes mellitus [7]. Few studies have directly compared the relative usefulness of conventional lipid particles for prediction of subclinical atherosclerosis. Accordingly, in this study we aim to compare the association of Non-HDL-C, LDL-C, HDL-C and TG with coronary calcium, a marker of subclinical atherosclerosis.

2. Methods 2.1. Study population This is a cross-sectional study of 2046 consecutive physician-referred patients who presented to a single electron beam tomography (EBT) scanning facility for atherosclerosis risk assessment. We excluded 404 subjects who reported a history of prior myocardial infarction, coronary and/or peripheral arterial revascularization, current symptoms suggestive of angina and individuals with diabetes as these are considered coronary heart disease (CHD) risk equivalent patients. Additionally, 31 individuals reporting use of cholesterol lowering medications were also excluded from the analyses. The final study sample was thus composed of 1611 adult subjects. The study was approved by the local institutional review board and received a waiver of patient consent. 2.2. Risk factor assessment and calculation of 10-year CHD risk All individuals provided details of their demographics, medical history, medication usage, and current symptoms by means of questionnaires offered at the time of first coronary artery calcium (CAC) screening. Hypertension was defined as current or recommended use of antihypertensive medications for blood pressure control. Smoking was defined as current tobacco usage. Family history of premature CHD was defined as CHD in first-degree male relatives ≤ 55 years of age or female relatives ≤ 65-year-old. Body mass index was calculated as weight (kg)/height (m)2 .

Fasting TC and TG were determined using enzymatic methods on samples drawn on the same day as the screening CT scan. HDL-C was measured after precipitation of apoB containing particles with phosphotungstate. LDL-C was calculated using the Friedwald equation. Non-HDL-C was derived as TC minus HDL-C. The Framingham risk score was calculated to estimate 10-year risk of CHD events in all enrolled patients. 2.3. Electron beam tomography Each patient underwent EBT scanning using a GE Imatron C-150 scanner (GE/Imatron, South San Francisco, CA). Coronary arteries were imaged with rapid acquisition of 30–40 contiguous slices with a thickness of 3 mm (26cm2 field of view) during end-diastole. Image acquisition was ECG-triggered and occurred during a single 20–30 s breath hold. CAC score was quantified using the previously described Agatston scoring method [8]. Calcium was considered present in a coronary artery when a plaque including a minimum of three contiguous pixels (>1.03 mm3 ) with an attenuation > 130 Hounsfield units was found. The CAC score is calculated as the product of the area of calcification by an attenuation factor based on peak plaque density [8]. A total CAC score was computed as the sum of all individual lesion scores in each coronary artery. To facilitate data interpretation, the CAC score was classified into the following pre-specified categories: 0, 1.0–99, 100–399, and ≥400 (no identifiable plaque, mild, moderate, and severe atherosclerotic plaque burden, respectively). These categories of CAC score have been used to differentiate between very low, moderate, moderately high, and high cardiovascular risk [9]. 2.4. Statistical analysis Baseline patient characteristics are reported as frequencies and proportions for categorical variables, and as means and standard deviations for continuous variables. The distribution of values was assessed by the Kolmogorov–Smirnov test for homogeneity of variances. Association between increasing quartile of lipid values and coronary artery calcium was initially assessed with a chi-square analysis. Logistic regression was then employed to further quantify the association between lipid level quartiles and CAC score > 0 and CAC score ≥ 100, with the lowest quartile as reference. Two sets of multivariable models were examined in a hierarchical fashion. In model 1, we adjusted for age, gender, race, cigarette smoking, hypertension, family history of premature CHD and obesity. In model 2, we adjusted for all lipid variables in addition to risk factors in model 1 to assess the independent association of each lipid profile with CAC. Finally, to test the independence of the relationship between Non-HDL-C and CAC, another chi-square analysis was conducted stratifying by low (below the median value) and high (above the median value) levels of the other

S.H. Orakzai et al. / Atherosclerosis 202 (2009) 289–295 Table 1 Clinical characteristics of study population (n = 1611) Variables Age (years) Men Hypertension Current smoker Body mass index (kg/m2 ) TC (mg/dl) LDL-C (mg/dl) HDL-C (mg/dl) TG (mg/dl) Non-HDL-C (mg/dl) Framingham risk score (10-year risk %)

53 ± 10 1080 (67%) 193 (12%) 242 (15%) 28 ± 5 215 ± 41 136 ± 35 51 ± 26 142 ± 88 164 ± 46 5±5

TC: total cholesterol, LDL-C: low-density lipoprotein cholesterol, HDL-C: high-density lipoprotein cholesterol, TG: triglycerides, Non-HDL-C: nonhigh-density lipoprotein cholesterol.

lipid variables. All statistical analyses were performed using Stata Version 8.0 (Austin, TX). The level of significance was set at p < 0.05 (two-tailed).

3. Results The final study population consisted of 1611 asymptomatic men and women free of known coronary artery disease. Demographic and clinical characteristics of the study population are shown in Table 1. The mean age of the study population (67% men) was 53 ± 10 years and the majority of individuals were young (men < 55-year-old and women < 65year-old). Over half (54%) of the participants had ≥2 CHD risk factors. The mean 10-year risk of CHD was 5 ± 5% according to Framingham risk score calculations. The majority of individuals (78%) had a 10-year risk of CHD lower than 10% (low risk), with only 20% and 2% classified as intermediate (10-year risk: 10–20%) and high risk (10-year risk > 20%), respectively.

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The mean lipid values were well within the recommended range by NCEP ATPIII guidelines (Table 1). The majority of the study population (n = 1034, 63%) had LDL-C levels ranging from 100 to 159 mg/dl, whereas 14% had an LDL-C < 100 mg/dl. Only 7% of participants had LDLC ≥ 190 mg/dl. Low HDL-C (<40 mg/dl) was observed in a quarter (25%) of the study population. The median (IQ range) CAC score was 6 (0–67). Overall CAC scores of 0, 1–99, 100–399 and ≥400, were observed in 35%, 44%, 12% and 9% of the study subjects, respectively. Fig. 1 shows the prevalence of any CAC according to increasing quartiles of lipid levels. The presence of CAC increased significantly across increasing quartiles of LDLC, TG and Non-HDL-C levels (all p < 0.0001), whereas prevalence of CAC was significantly lower across increasing quartiles of HDL-C (p < 0.001). These relationships persisted for CAC ≥ 100 except for HDL-C that was no longer significant (p = 0.56) (Fig. 2). The highest chi-square value was observed for the relationship of Non-HDL-C levels with both prevalence of CAC score > 0 (chi-square = 66.8) as well as for CAC score ≥ 100 (chi-square = 21.7). In a multivariate model adjusting for age, gender, race, cigarette smoking, hypertension, family history of premature CHD and obesity, each lipid variable was a significant predictor of the presence of CAC (Table 2, Model 1). After simultaneously controlling for increasing quartiles of all lipid levels (Table 2, Model 2), only the association of Non-HDL-C with CAC remained statistically significant (p = 0.002). Similar results were observed with CAC score ≥ 100 (p = 0.038) (Table 3). When the analyses were repeated according to gender in the fully adjusted model (model 2), increasing quartiles of Non-HDL-C remained significantly associated with CAC in both men (p = 0.027) and women (p = 0.024). On the other hand, no such association existed with LDL-C, HDLC and TG (all p values > 0.3). Furthermore, when we added the Framingham risk score to the final fully adjusted model,

Fig. 1. Prevalence of coronary artery calcium score > 0 (%) across quartile of lipid levels.

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Fig. 2. Prevalence of coronary artery calcium score ≥ 100 (%) across quartile of lipid levels.

the association of CAC with increasing levels of Non-HDLC remained robust (p = 0.001), whereas no such association was seen with LDL-C (p = 0.45), HDL-C (p = 0.32) and TG (p = 0.41). In a stratified analysis, we divided the population according to low (below the median) and high (above the median) levels of each lipid variable. A Non-HDL-C level above the median was significantly associated with the presence of any CAC (Fig. 3) as well CAC score ≥ 100 (Fig. 4) across low and high levels of LDL-C, HDL-C and TG.

4. Discussion Our study shows that among the conventional lipids, Non-HDL-C was more strongly associated with subclinical atherosclerosis. Several studies have shown that Non-HDL-

C is a strong and independent predictor of cardiovascular events [4–7]. Recent studies comparing various lipoproteins have shown Non-HDL-C to be equivalent to, or even better than, LDL-C at predicting CHD risk. Cui et al. [5] analyzed the relationship between cardiovascular death and various lipoproteins over 19 years of follow-up in the Lipid Research Clinics Program Follow-up Study. Both LDL-C and Non-HDL-C predicted cardiovascular death in women and men, but non-HDL-C was a stronger predictor than LDL-C in both sexes; a 30-mg/dl increase in Non-HDL-C translated into a 19% increase in cardiovascular mortality risk among men and 15% among women. The corresponding risks for a 30-mg/dl increase in LDL-C were 11% among men and 8% among women, respectively. In the Strong Heart Study, Lu et al. [7] found Non-HDL-C to be a better predictor of cardiovascular events in patients with diabetes compared to LDL-C [Hazard Ratio (HR) 2.23

Table 2 Adjusted odd ratios for CAC > 0 according to lipid levels 1

2

3

4

Trend across quartiles

LDL-C Model 1 Model 2

1 (ref) 1 (ref)

0.99 (0.72–1.36) 0.68 (0.45–1.02)

1.14 (0.82–1.57) 0.55 (0.32–0.94)

1.92 (1.37–2.69) 0.73 (0.37–1.45)

<0.0001 0.27

HDL-C Model 1 Model 2

1 (ref) 1 (ref)

0.80 (0.57–1.08) 0.84 (0.59–1.18)

0.76 (0.53–1.10) 0.86 (0.59–1.18)

0.66 (0.45–0.95) 0.85 (0.57–1.29)

<0.0001 0.032

Triglycerides Model 1 Model 2

1 (ref) 1 (ref)

1.20 (0.87–1.66) 1.02 (0.73–1.43)

1.70 (1.22–1.66) 1.21 (0.84–1.75)

1.89 (1.36–2.62) 1.08 (0.69–1.68)

<0.0001 0.46

Non-HDL-C Model 1 Model 2

1 (ref) 1 (ref)

1.46 (1.06–2.00) 1.90 (1.23–2.93)

1.81 (1.31–2.52) 2.53 (1.41–4.53)

2.65 (1.89–3.70) 3.29 (1.53–7.04)

<0.0001 0.002

LDL-C: low-density lipoprotein cholesterol, HDL-C: High density lipoprotein cholesterol, Non-HDL-C: Non-high density lipoprotein cholesterol, Model 1 adjusted for age, gender, race, cigarette smoking, hypertension, family history of premature coronary heart disease and obesity, Model 2 adjusted for increasing quartiles of all lipid levels in addition to the risk factors adjusted in Model 1.

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Table 3 Adjusted odd ratios for CAC ≥ 100 according to lipid levels 1

2

3

4

Trend across quartiles

LDL-C Model 1 Model 2

1 (ref) 1 (ref)

1.10 (0.73–1.69) 0.82 (0.48–1.38)

1.48 (0.98–2.23) 0.84 (0.43–1.57)

1.53 (1.02–2.30) 0.69 (0.32–1.53)

0.016 0.45

HDL-C Model 1 Model 2

1 (ref) 1 (ref)

0.87 (0.59–1.27) 1.01 (0.66–1.57)

0.89 (0.59–1.35) 0.98 (0.60–1.59)

0.74 (0.47–1.16) 0.93 (0.62–1.38)

0.24 0.96

Triglycerides Model 1 Model 2

1 (ref) 1 (ref)

1.00 (0.66–1.55) 0.86 (0.55–1.35)

1.56 (1.03–2.36) 1.20 (0.75–1.92)

1.67 (1.10–2.53) 1.11 (0.63–1.92)

0.003 0.44

Non-HDL-C Model 1 Model 2

1 (ref) 1 (ref)

1.54 (1.00–2.39) 1.70 (0.97–2.98)

1.90 (1.23–2.94) 2.15 (1.05–4.44)

2.26 (1.48–3.46) 2.77 (1.12–6.80)

<0.0001 0.038

LDL-C: low-density lipoprotein cholesterol, HDL-C: high-density lipoprotein cholesterol, Non-HDL-C: non-high-density lipoprotein cholesterol, Model 1 adjusted for age, gender, race, cigarette smoking, hypertension, family history of premature coronary heart disease and obesity, Model 2 adjusted for increasing quartiles of all lipid levels in addition to the risk factors adjusted in Model 1.

and 1.80 for the highest tertile of Non-HDL-C among men and women, respectively]. Analysis of the Bypass Angioplasty Revascularization Investigation (BARI) [4] population showed Non-HDL-C to be a strong and independent predictor of non-fatal myocardial infarction and angina among patients with coronary artery disease at 5 years, while LDL-C and HDL-C were not associated with either outcome in that study. Non-HDL-C levels correlate with apo-B concentrations more accurately than LDL-C levels, especially at higher TG levels [10]. Apo-B has been shown to be superior to “traditional” lipid risk factors for predicting CHD in sev-

eral large databases [11,12]. Despite the strong association between apo-B and CHD, its measurement in clinical practice is limited by the availability of standard assays. Therefore Non-HDL-C, through its close correlation with apo-B, may be as good if not better a predictor of CHD risk as LDL-C [5,13]. Very few studies have assessed the association of various lipoproteins with subclinical endpoints. Simon et al. [14] analyzed the association of various lipoproteins with CAC assessed by EBT and extracoronary plaque assessed by ultrasound in 723 asymptomatic men. Non-HDL-C was more strongly associated with CAC [Odds Ratio (OR) 1.33, 95% CI

Fig. 3. Prevalence of coronary artery calcium score > 0 (%) with increasing Non-HDL-C levels across LDL-C, HDL-C and TG levels.

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Fig. 4. Prevalence of coronary artery calcium score ≥ 100 (%) with increasing Non-HDL-C levels across LDL-C, HDL-C and TG levels.

1.07–1.64] than LDL-C (OR 1.26, 95% CI 1.01–1.39). NonHDL-C was also a better predictor of extracoronary plaque compared to LDL-C [OR for Non-HDL-C 1.31 (1.11–1.56), OR for LDL-C 1.19 (1.01–1.39)]. Similarly Kawamoto et al. [15] estimated the association of various lipoproteins with carotid intima–media thickness in the elderly. Non-HDL-C was more strongly associated with carotid atherosclerosis than LDL-C. Non-HDL-C includes all of the potentially atherogenic lipid fractions [LDL-C, lipoprotein (a) [16,17], IDL-C [18,19] and VLDL-C remnants [18,20]]. Although the Friedwald formula and ␤ quantification include IDL-C and lipoprotein (a) in the LDL-C level measurement, they do not include remnant cholesterol particles. The inclusion of remnant particles in the Non-HDL-C level calculation may then provide an improved assessment of risk. When TG levels are <200 mg/dl, VLDL-C is not markedly elevated and NonHDL-C corresponds closely to LDL-C concentration [21,22]. Therefore, in this situation the sum of VLDL-C and LDL-C adds little information on levels of atherogenic lipoproteins, compared with the measurement of LDL-C alone. However, when TG levels are high, VLDL-C levels increase [23]. In this setting, LDL-C concentration alone does not capture the full extent of lipoprotein-associated risk, and Non-HDL-C is a superior marker of the total level of atherogenic lipoproteins. This relationship likely does not hold for very high TG levels (>500 mg/dl and >5.7 mmol/l), since a portion of the cholesterol in the TG-rich lipoprotein occurs in less atherogenic, larger VLDL-C and chylomicrons. Remnant TG-rich lipoprotein can be taken up by macrophages, leading to

increased foam cell formation and accelerated atherosclerosis [24]. In addition, numerous studies indicate that elevated TG level (>150 mg/dl and >1.7 mmol/l) is associated with small, dense LDL-C, which is thought to be more easily oxidized and, thus, more atherogenic [5]. An elevation of VLDL-C is also associated with increases in prothrombotic and procoagulant factors [25]. The Third Adult Treatment Panel (ATPIII) of the National Cholesterol Education Program (NCEP) thus recommended the use of Non-HDL-C as a secondary target of lipid lowering, after achieving adequate control of LDL-C and if TG are elevated (≥200 mg/dl and ≥2.3 mmol/l), especially in patients with diabetes or the metabolic syndrome [1]. When TG levels exceed 200 mg/dl (2.3 mmol/l), the ATPIII guidelines recommend Non-HDL-C of ≤30 mg/dl above the appropriate LDL-C target (this number is used because a normal VLDL-C level is ≤30 mg/dl). Non-HDL-C measurement offers several potential advantages for routine clinical practice. First, it can be calculated in the non-fasting state simply by subtracting HDL-C from the TC. Second, it can be calculated in the setting of hypertriglyceridemia (TG > 400 mg/dl and >4.5 mmol/l) where the estimation of LDL-C levels with the Friedwald formula is less accurate [13]. Additionally, estimations of Non-HDL-C levels are not limited by assumptions about the relationship between VLDL-C and TG. In patients with diabetes, this relationship can be altered, leading to falsely low LDL-C values as calculated by the Friedwald formula, especially in conjunction with elevated TG levels. Finally, Non-HDL-C level might also identify a group of individuals who have a genetically

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determined atherogenic lipoprotein phenotype, characterized by high VLDL-C and IDL-C levels, a low HDL-C level, and an LDL-C level within the reference range. Approximately 20% of the American population are estimated to have this phenotype [24,26]. Our study presents several limitations. The study population was somewhat pre-selected and thus may differ from the general population in its use of screening procedures and other preventive measures. We enrolled a majority of Caucasians and the findings may not apply to other ethnic groups [27]. Finally, we did not measure waist circumference that may be a better indicator of obesity than BMI and did not measure LDL levels. Indeed, using the Friedwald formula there in an inherent risk of miscalculating the actual LDL levels, especially in the presence of elevated triglycerides. In our cohort there were only 13 patients with triglycerides > 400 mg/dl and even excluding these patients, the results of our analyses did not change (data not shown). In conclusion, our study shows that among the traditional lipid measures, Non-HDL-C was more strongly associated with subclinical atherosclerosis as estimated by measurement of coronary artery calcium. The NCEP has recommended LDL-C as the primary target of therapy. However, many individuals are at increased risk of CHD due to elevated concentrations of atherogenic lipoproteins not reflected in LDL-C measurement, especially patients with dyslipidemia associated with the metabolic syndrome and diabetes. The use of Non-HDL-C instead of LDL-C as a primary target for cholesterol lowering therapy deserves further investigation. Use of Non-HDL-C as target for therapy in individuals with mild to moderate TG elevation may improve risk stratification and help guide treatment decisions.

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