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Keywords:

  • apolipoprotein A-I;
  • apolipoprotein A-II;
  • apolipoprotein B;
  • cardiovascular risk;
  • C-reactive protein;
  • HDL cholesterol;
  • microalbuminuria;
  • non-HDL cholesterol

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Conflict of interest statement
  8. Acknowledgements
  9. References
  10. Supporting Information

Kappelle PJWH, Gansevoort RT, Hillege JL, Wolffenbuttel BHR, Dullaart RPF on behalf of the PREVEND study group (University Medical Center Groningen and University of Groningen, Groningen, The Netherlands). Apolipoprotein B/A-I and total cholesterol/high-density lipoprotein cholesterol ratios both predict cardiovascular events in the general population independently of nonlipid risk factors, albuminuria and C-reactive protein. J Intern Med 2011; 269: 232–242.

Abstract.  Background.  The total cholesterol/high-density lipoprotein cholesterol (TC/HDL-C) and apolipoprotein (apo) B/A-I ratios predict major adverse cardiovascular events (MACEs). The extent to which these associations are modified by high-sensitivity C-reactive protein (hs-CRP) and albuminuria is largely unknown. We compared the strength of these ratios with first MACE in the general population and determined whether these associations remain when taking account of these risk markers.

Subjects and methods.  A prospective case–cohort study was performed among 6948 subjects (PREVEND cohort) without previous cardiovascular disease and who did not use lipid-lowering drugs initially. Fasting serum TC, low-density lipoprotein cholesterol (LDL-C), HDL-C, non-HDL-C, apoB, apoA-I, triglycerides, hs-CRP and albuminuria were measured at baseline. The composite endpoint was incident MACE.

Results.  A total of 362 first cardiovascular events occurred during 7.9 years of follow-up. All pro- and anti-atherogenic measures of lipoproteins and apos predicted MACEs in age- and sex-adjusted Cox proportional hazard analyses (P = 0.018 to P < 0.001). The age- and sex-adjusted hazard ratio (HR) was 1.37 [95% confidence interval (CI), 1.26–1.48] for the apoB/apoA-I ratio and 1.24 (95% CI, 1.18–1.29) for the TC/HDL-C ratio (both < 0.001). These relationships were essentially unaltered after additional adjustment for triglyceride levels. Pair-wise comparison revealed that these ratios were of similar importance in age- and sex-adjusted analysis (= 0.397). The HRs of apoB/apoA-I (P < 0.001) and TC/HDL-C (P < 0.001) for risk of MACEs were only marginally attenuated by additional controlling for traditional risk factors (hypertension, diabetes, obesity and smoking), hs-CRP and albuminuria.

Conclusions.  First MACE is associated with both the fasting serum apoB/apoA-I ratio and the TC/HDL-C ratio in the general population, independently of triglycerides, hs-CRP and albuminuria.


Abbreviations
Apo

apolipoprotein

BMI

body mass index

CI

confidence interval

CV

coefficient of variation

HDL-C

high-density lipoprotein cholesterol

HR

hazard ratio

hs-CRP

high-sensitivity C-reactive protein

IDL

intermediate-density lipoprotein

LDL-C

low-density lipoprotein cholesterol

MACE

major adverse cardiovascular event

PREVEND

prevention of renal and vascular end-stage disease

TC

total cholesterol

VLDL

very low-density lipoprotein

Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Conflict of interest statement
  8. Acknowledgements
  9. References
  10. Supporting Information

Cardiovascular disease represents a major cause of morbidity and mortality worldwide [1], and lipoprotein abnormalities play a central role in its multifactorial pathogenesis [2]. Guidelines have traditionally advocated that the low-density lipoprotein cholesterol (LDL-C) concentration represents the primary target for lipid-lowering intervention [2]. However, there is growing awareness that all apolipoprotein B (apoB)-containing lipoproteins have atherogenic potential [3–6]. Thus, the cholesterol concentration in the combined LDL, intermediate-density lipoprotein (IDL) and very low-density lipoprotein (VLDL) fractions, collectively measured as non-high-density lipoprotein cholesterol (non-HDL-C), as well as the serum apoB concentration, are now considered of equivalent importance to LDL-C rather than secondary targets to initiate lipid-lowering treatment [7–9]. In addition, it is well known that the risk of cardiovascular disease is inversely related to the level of high-density lipoprotein cholesterol (HDL-C) of which apolipoprotein A-I (apoA-I) is the most abundant apolipoprotein [2, 10].

Several cross-sectional and prospective studies have evaluated the strength of the relationships between prevalent or incident cardiovascular disease and single pro-atherogenic (apo)lipoprotein measures or ratios of lipoprotein cholesterol, such as the non-HDL-C/HDL-C ratio [equivalent to the total cholesterol (TC)/HDL-C ratio] and the apoB/apoA-I ratio [1, 3–6, 11–16]. The ratios of pro-atherogenic to anti-atherogenic (apo)lipoproteins are likely to be more effective than single measures of atherogenic lipoprotein cholesterol [1, 3, 4, 12–14, 16], but it is uncertain whether the apoB/apoA-I ratio is better than lipoprotein cholesterol ratios for cardiovascular disease prediction in the general population. A recent meta-analysis by the Emerging Risk Factors Collaboration showed a similar hazard of cardiac and cerebral vascular events attributable to the non-HDL-C/HDL-C ratio compared to the apoB/apoA-I ratio [17], in apparent contrast with other studies [3, 14]. Both of these studies accounted for traditional risk factors and serum triglyceride levels, whereas high-sensitivity C-reactive protein (hs-CRP) was also taken into consideration in the EPIC-Norfolk study [14]. Of importance, it is unknown whether the relationships between incident cardiovascular disease and lipoprotein cholesterol or apolipoprotein ratios are affected by other novel risk markers, such as elevated urinary albumin excretion [18, 19].

The present study was initiated to determine the strength of any associations between major adverse cardiovascular events (MACEs) and fasting levels of serum lipoprotein cholesterol and apolipoproteins as well as their ratios in the population-based prevention of renal and vascular end-stage disease (PREVEND) cohort. The focus of PREVEND on the role of elevated urinary albumin excretion and inflammation for progression of renal and cardiovascular disease gave us the opportunity to examine the extent to which the relationship between MACEs and (apo)lipoprotein measures is modified by serum hs-CRP and albuminuria.

Materials and methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Conflict of interest statement
  8. Acknowledgements
  9. References
  10. Supporting Information

Study population

The study was carried out among participants of the PREVEND study. This prospective cohort study was initiated in 1997 to investigate the natural course of urinary albumin excretion and its relation to renal and cardiovascular disease in a predominantly Caucasian population. Details of the study protocol have been published previously [20]. Briefly, all inhabitants of the city of Groningen aged 28–75 years were sent a questionnaire and a vial to collect a first-morning-void urine sample (prescreening). Of these individuals, 40 856 responded (47.8%) and returned a vial to a central laboratory for urinary albumin and creatinine assessment. After exclusion of subjects with insulin-treated diabetes mellitus and pregnant women, all those with a urinary albumin concentration ≥10 mg L−1 (= 7768) were invited and 6000 agreed to participate. Furthermore, 3394 randomly selected subjects with a urinary albumin concentration <10 mg L−1 were invited and 2592 agreed to participate. These 8592 subjects took part in the baseline screening and constitute the PREVEND cohort. For the present study, we first excluded participants who were nonfasting at the time of first blood sampling (= 428), subjects with a prior history of cardiovascular disease (= 426) and those who used lipid-lowering drugs (= 238). We also excluded those remaining subjects with missing values of one of the following variables: cholesterol, triglycerides, HDL-C, apoA-I, apoA-II or apoB (= 552). Thus, 6948 subjects were included in the analysis. The PREVEND study was approved by the review board of our institution and was conducted in accordance with the guidelines of the Declaration of Helsinki. All participants provided written informed consent.

Baseline measurements and definitions

Participants visited the outpatient research unit twice for the baseline survey. They completed a questionnaire on demographics, cardiovascular disease history, smoking habits, alcohol consumption and medication use prior to their first visit. Height and weight were measured during the first visit; body mass index (BMI) was calculated as weight divided by height squared. Obesity was defined as BMI ≥ 30 kg m−2. During both visits, blood pressure was measured, in the supine position, every min for 10 min with an automatic device (Dinamap XL Model 9300; Johnson-Johnson Medical, Tampa, FL, USA). Blood pressure values are given as the mean of the last two recordings of both visits; hypertension was defined as systolic blood pressure of at least 140 mmHg or diastolic blood pressure of at least 90 mmHg, or the use of antihypertensive drugs [21]. Participants collected two 24-h urine samples for measurement of albumin excretion. Microalbuminuria and macroalbuminuria were defined as mean urinary albumin excretion of 30–300 mg 24 h−1 and >300 mg 24 h−1, respectively [22]. Participants were instructed to remain fasting for at least 8 h before blood was sampled at the second visit. Diabetes mellitus was diagnosed by fasting plasma glucose ≥7.0 mmol L−1, according to 1997 American Diabetes Association criteria [23] or use of glucose-lowering drugs. Furthermore, data on medication use were checked using pharmacy-dispensing information from all community pharmacies in the city of Groningen; this covers complete information on drug use in 80% of PREVEND participants.

Outcome

The primary endpoint of this analysis was first MACE, which was defined as the combined endpoint of incident cardiovascular morbidity and mortality during the follow-up of the study. Information (on hospitalization) for cardiovascular morbidity was obtained from PRISMANT, the Dutch national registry of hospital discharge diagnoses. Data on mortality were acquired from the municipal register, and cause of death was obtained by linking the number of the death certificate to the primary cause of death as coded by the Dutch Central Bureau of Statistics. Data were coded according to the International Classification of Diseases, 9th revision (ICD-9) and the classification of interventions. MACE was defined as acute myocardial infarction (ICD-code 410), acute and subacute ischaemic heart disease (ICD-code 411), occlusion or stenosis of the precerebral (ICD-code 433) or cerebral arteries (ICD-code 434) or the following procedures: coronary artery bypass grafting, percutaneous transluminal coronary angioplasty or other vascular interventions (i.e. percutaneous transluminal angioplasty or bypass grafting of the aorta and peripheral vessels). Survival time was defined as the period from the baseline survey to the date of a first MACE. Subjects who did not develop an MACE were censored on 31 December 2005. In case a person moved to an unknown destination (= 396, overall cohort), census date was date of removal from the municipal registry.

Laboratory methods

Blood samples were taken after a 15-min rest. Plasma glucose was measured shortly after blood sampling. Serum samples for lipid and apolipoprotein measurements were stored at −80 °C until analysis. Serum TC and plasma glucose were assessed using Kodak Ektachem dry chemistry (Eastman Kodak, Rochester, NY, USA). HDL-C was measured using a homogeneous method (direct HDL, no. 7D67, AEROSET System; Abbott Laboratories, Abbott Park, IL, USA) [24]. Serum triglycerides were measured enzymatically. LDL-C was calculated using the Friedewald formula [25]. Non-HDL-C was calculated as the difference between TC and HDL-C. Serum apoB, apoA-I and apoA-II were determined by nephelometry applying commercially available reagents for Dade Behring nephelometer systems (BN II; Dade Behring, Marburg, Germany; apo A-I test kit, code no. OUED; apo A-II test kit, code no. OQBA; apo B test kit, code no. OSAN) [26]. Reference preparations for apoB, apoA-I and apoA-II were IRP SP3-07, BCR-393 and BCR-394, respectively. Urinary albumin concentration was determined by nephelometry (Dade Behring Diagnostic). hs-CRP was measured by nephelometry with a threshold of 0.18 mg L−1 (BNII, Dade Behring). The inter- and intra-assay coefficients of variation (CVs) of all these assays were well below 5% except for the inter-assay CV of hs-CRP which was 5.7%.

Statistical methods

Analyses were performed using spss version 16.0.2 (SPSS Inc., Chicago, IL, USA) and Stata SE 11 (StataCorp, College Station, TX, USA). Normally, distributed values are presented as mean ± SD with between-group differences determined with Student’s t-tests. Variables with a skewed distribution are presented as median (inter-quartile range), and between-group differences were determined using the Mann–Whitney U-test. Differences between categorical variables were tested using the chi-square test.

Event-free survival time for participants was defined as the period between inclusion in the study and an MACE. The associations between incidence of MACEs and (apo)lipoprotein(s) (ratios) were analysed by Cox proportional hazard analyses. The proportional hazard assumption was assessed for every predictor using graphical approaches. A proportional hazard was assumed when the log–log survival curve was constant over time. The proportional hazards assumption was not violated in any model. Hazard ratios (HRs) were reported per SD change for each variable with 95% confidence intervals (95% CIs). Additional models were also made by further controlling for triglycerides, conventional risk factors (hypertension, diabetes, obesity and smoking), hs-CRP and albuminuria. Interactions between (apo)lipoprotein ratios, hs-CRP and albuminuria on cardiovascular risk were also determined. To this end, the mean value was subtracted from the measured value in order to obtain a distribution centred on the mean, and product terms were calculated. These product terms were then included in the models. Logarithmically transformed values were used if a variable had a skewed distribution, as in the case of triglycerides, hs-CRP and albuminuria. We tested the crude and age- and sex-adjusted contributions of different sets of (apo)lipoprotein parameters on MACEs. Variables were entered pair-wise in the models in order to directly compare differences in HRs by means of Wald statistics.

Because of the design of the PREVEND study with preferential inclusion of subjects with elevated urinary albumin excretion, sensitivity analyses were performed. Analyses were performed again using a complex sample design procedure. In addition, sensitivity analyses were performed on the data-set of subjects derived from the random sample making part of the PREVEND cohort ([20] and http://www.PREVEND.org). A two-sided P < 0.05 indicated statistical significance.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Conflict of interest statement
  8. Acknowledgements
  9. References
  10. Supporting Information

This study included 52 112 person-years of follow-up. During a median follow-up of 7.9 (interquartile range, 7.5–8.1) years, 362 first cases of an MACE were documented (6.9 per 1000 person-years). Table 1 shows the number of first MACEs with respect to the composite endpoint, and the separate cardiovascular domains in the whole cohort and stratified by sex.

Table 1. Major adverse cardiovascular events by cardiovascular domain and sex
 AllMenWomen
  1. Cardiac events include fatal/nonfatal myocardial infarction, ischaemic heart disease, coronary artery bypass grafting and percutaneous transluminal coronary angioplasty. Cerebrovascular events include fatal/nonfatal occlusion of cerebral arteries, occlusion or stenosis of precerebral arteries, subarachnoidal haemorrhage, intracranial haemorrhage, other intracranial haemorrhages and carotic artery desobstruction. Peripheral vascular events include aortic peripheral bypass surgery and percutaneous transluminal femoral angioplasty (see Materials and methods).

Total events362255107
Cardiac event253 (69.9%)185 (72.5%)68 (63.6%)
Cerebrovascular event85 (23.5%)51 (20.0%)34 (31.7%)
Peripheral vascular event24 (6.6%)19 (7.5%)5 (4.8%)

Subjects who experienced an event (cases) were older, more likely to be male and smoked more frequently compared with subjects who did not experience an event during follow-up (controls) (Table 2). Obesity, diabetes mellitus, hypertension and micro- and macroalbuminuria were more prevalent among cases. Serum levels of TC, LDL-C, non-HDL-C, and apoB, the TC/HDL-C and the apoB/apoA-I ratios, and triglycerides and hs-CRP levels were higher, whereas levels of HDL-C, apoA-I and apoA-II were lower in cases than in controls (Table 2). When cases and controls were classified according to gender, similar differences in clinical features and levels of lipids and apolipoproteins and their ratios were found, except for smoking, apoA-I and apoA-II which did not differ significantly between female cases and controls (Table S1).

Table 2. Baseline clinical and laboratory characteristics of study participants
 Whole cohort (= 6948)Cases (= 362)Controls (= 6586)P-value
  1. Values are given as mean ± SD, except for triglycerides and hs-CRP which are given as median (interquartile range).

  2. TC, total cholesterol; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; non-HDL-C, non-HDL cholesterol; apo, apolipoprotein; hs-CRP, high-sensitivity C-reactive protein.

Men (%)47.870.446.6<0.001
Age (years)48 ± 1260 ± 1148 ± 12<0.001
Obesity (%)15.225.014.7<0.001
Hypertension (%)29.964.628.0<0.001
Microalbuminuria (%)12.026.511.1<0.001
Macroalbuminuria (%)1.44.41.2<0.001
Diabetes (%)2.85.32.1<0.001
Alcohol use (%)25.726.725.60.657
Smoking status (%)
 Never30.316.031.0<0.001
 Former smoker35.839.035.5 
 Current33.945.033.2 
TC (mmol L−1)5.64 ± 1.136.18 ± 1.115.62 ± 1.12<0.001
LDL-C (mmol L−1)3.69 ± 1.064.23 ± 1.073.66 ± 1.05<0.001
Non-HDL-C (mmol L−1)4.31 ± 1.225.01 ± 1.184.27 ± 1.21<0.001
HDL-C (mmol L−1)1.34 ± 0.401.18 ± 0.381.34 ± 0.40<0.001
ApoA-I (g L−1)1.39 ± 0.281.33 ± 0.271.40 ± 0.28<0.001
ApoB (g L−1)1.04 ± 0.301.20 ± 0.311.03 ± 0.30<0.001
ApoA-II (g L−1)0.34 ± 0.060.33 ± 0.060.34 ± 0.06<0.001
TC/HDL-C4.64 ± 1.845.78 ± 2.124.57 ± 1.81<0.001
ApoB/apoA-I0.77 ± 0.270.94 ± 0.310.76 ± 0.27<0.001
Triglycerides (mmol L−1)1.12 (0.82–1.64)1.47 (1.02–2.06)1.11 (0.81–1.61)<0.001
hs-CRP (mg L−1)1.24 (0.55–2.86)2.46 (1.12–5.34)1.20 (0.53–2.77)<0.001

Age- and sex-adjusted HRs for individual (apo)lipoprotein measures (TC, LDL-C, non-HDL-C, HDL-C and apos) and their ratios with incident MACEs are given in Table 3. MACEs were associated with all pro- and anti-atherogenic lipoprotein variables, apos and their ratios (P = 0.018 to P < 0.001). Among the pro-atherogenic variables, the highest age- and sex-adjusted HR point estimates were found for non-HDL-C and the apoB/apoA-I ratio. Among the anti-atherogenic measures, the highest point estimate was found for HDL-C. All HRs for an MACE were only marginally altered after additional adjustment for triglycerides (Table 3). The relationship between incident MACE and the apoB/apoA-I and TC/HDL-C ratios according to quartiles is illustrated in Fig. 1. The HRs for risk of first MACE for the apoB/apoA- and the TC/HDL-C ratios in the upper quartile compared with the combined three lower quartiles were 1.95 (95% CI, 1.58–2.40, < 0.001) and 2.13 (95% CI, 1.72–2.63, < 0.001), respectively. Furthermore, risk was associated with hypertension (HR: 1.88; 95% CI, 1.48–2.38, < 0.001), obesity (HR: 1.48; 95% CI, 1.16–1.88, = 0.002), diabetes (HR: 1.54; 95% CI, 1.04–2.27, = 0.03), smoking (former smoker HR: 1.29; 95% CI 0.95–1.77, = 0.108; current smoker HR: 2.44; 95% CI, 1.80–3.31, < 0.001), hs-CRP (HR: 1.40; 95% CI, 1.27–1.54, < 0.001) and urinary albumin excretion (HR: 1.25; 95% CI, 1.15–1.35, < 0.001) in age- and sex-adjusted analyses.

Table 3. Hazard ratios (HRs) of serum total cholesterol, lipoprotein cholesterol, apolipoproteins and their ratios for major adverse cardiovascular events
 Age- and sex-adjustedAge-, sex- and triglyceride-adjusted
HR (95% CI)P-valueHR (95% CI)P-value
  1. HRs are given per 1-SD increase for all variables.

  2. TC, total cholesterol; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; non-HDL-C, non-HDL cholesterol; apo, apolipoprotein.

TC1.27 (1.15–1.41)<0.0011.16 (1.04–1.30)0.007
LDL-C1.30 (1.17–1.45)<0.0011.24 (1.12–1.38)<0.001
Non-HDL-C1.36 (1.23–1.50)<0.0011.25 (1.11–1.41)<0.001
HDL-C0.69 (0.60–0.79)<0.0010.77 (0.66–0.90)0.001
ApoB1.24 (1.13–1.35)<0.0011.13 (1.01–1.26)0.028
ApoA-I0.78 (0.70–0.88)<0.0010.82 (0.73–0.92)<0.001
ApoA-II0.88 (0.78–0.98)0.0180.86 (0.77–0.95)0.005
TC/HDL-C ratio1.24 (1.18–1.29)<0.0011.19 (1.11–1.27)<0.001
ApoB/apoA-I ratio1.37 (1.26–1.48)<0.0011.30 (1.18–1.43)<0.001
image

Figure 1. Unadjusted and age- and sex-adjusted relationships between first major adverse cardiovascular event and the total cholesterol/HDL cholesterol (TC/HDL-C) ratio or the apolipoprotein B/apolipoprotein A-I (apoB/apoA-I) ratio. Ratios are presented in quartiles with the first quartile as reference. The vertical bars represent the point estimate of the hazard ratio (HR) and the 95% confidence interval. *P < 0.001, **P for trend <0.001.

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Direct pair-wise comparisons between the various pro- and anti-atherogenic lipoproteins, apos and their ratios were made in order to compare the strength of their associations with MACEs (Table 4). Of the single pro-atherogenic measures, non-HDL-C was the strongest single predictor of an MACE in age- and sex-adjusted analyses. Of the anti-atherogenic measures, the strongest relationship was found between MACE and HDL-C. ApoA-I performed better than apoA-II in age- and sex-adjusted analyses. When ratios were compared with single measures, the apoB/apoA-I ratio was better than apo B and LDL-C. The TC/HDL-C ratio was not significantly better than LDL-C, whereas both the TC/HDL-C ratio and the apoB/apoA-I ratio were not significantly better than non-HDL-C in age- and sex-adjusted analyses. The relationship between incident MACE and the apoB/apoA-I ratio was stronger than between MACE and the TC/HDL-C ratio in unadjusted analysis (HR: 1.43; 95% CI, 1.31–1.56 and HR: 1.12; 95% CI, 1.05–1.18, < 0.001, respectively), but the apoB/apoA-I ratio was not statistically better in age- and sex-adjusted analysis (Table 4).

Table 4. Direct pair-wise comparisons of the relationships between lipoprotein cholesterol, apolipoproteins and their ratios, and major adverse cardiovascular events
 Age- and sex-adjusted
HR (95% CI)P-value
  1. HRs are given per 1-SD increase for all variables.

  2. HR, hazard ratio; TC, total cholesterol; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; non-HDL-C, non-HDL cholesterol; apo, apolipoprotein.

Comparison of single variables
Non-HDL-C1.43 (1.21–1.70)0.016
LDL-C0.94 (0.77–1.13) 
Non-HDL-C1.39 (1.20–1.63)0.015
ApoB0.97 (0.83–1.13) 
LDL-C1.22 (1.04–1.43)0.418
ApoB1.08 (0.94–1.26) 
ApoA-I0.95 (0.81–1.12)0.069
HDL-C0.72 (0.60–0.86) 
ApoA-II0.98 (0.87–1.11)0.002
HDL-C0.70 (0.60–0.81) 
ApoA-I0.74 (0.62–0.87)0.015
ApoA-II1.08 (0.92–1.27) 
Comparison of single variables with ratios
Non-HDL-C1.13 (0.97–1.32)0.832
TC/HDL-C ratio1.16 (1.06–1.27) 
ApoB0.85 (0.73–0.99)<0.001
ApoB/ApoA-I ratio1.57 (1.34–1.83) 
ApoB1.09 (0.98–1.22)0.147
TC/HDL-C ratio1.21 (1.15–1.28) 
Non-HDL-C1.13 (0.98–1.30)0.299
ApoB/ApoA-I ratio1.28 (1.14–1.44) 
LDL-C1.15 (1.03–1.29)0.476
TC/HDL-C ratio1.21 (1.15–1.28) 
LDL-C1.07 (0.94–1.22)0.047
ApoB/ApoA-I ratio1.32 (1.20–1.47) 
Comparison of ratios
TC/HDL-C ratio1.15 (1.07–1.24)0.397
ApoB/ApoA-I ratio1.24 (1.11–1.38) 

The extent to which the relationships between MACE and the apoB/apoA-I and TC/HDL-ratios were modified by traditional cardiovascular risk factors (hypertension, diabetes, obesity and smoking), albuminuria and hs-CRP was determined next. In age-, sex- and triglyceride-adjusted analyses, further controlling for traditional risk factors (model 1), albuminuria and hs-CRP (model 2) or both sets of variables (model 3) only marginally diminished the relationship between MACE and the apoB/apoA-I ratio (Table 5). Likewise, the relationship between MACE and the TC/HDL-C ratio remained essentially unaltered after adjustment for traditional risk factors, albuminuria and hs-CRP. When the apoB/apoA-I and TC/HDL-C ratios were included together in the same model (model 3), both ratios were related to risk (HR: 1.16; 95% CI, 1.02–1.31, = 0.020 and HR: 1.13; 95% CI, 1.03–1.24, = 0.011, respectively). No significant interactions between the apoB/apoA-I and TC/HDL-C ratios and albuminuria and hs-CRP on incident MACE were observed (> 0.10 for all, data not shown). In the subgroup of subjects with elevated urinary albumin excretion (>30 mg 24 h−1; = 918), both the apoB/apoA-I ratio (HR: 1.28; 95% CI, 1.08–1.50, P = 0.003) and the TC/HDL-C ratio predicted an MACE (HR: 1.28; 95% CI, 1.08–1.51, = 0.004).

Table 5. Hazard ratios (HRs) for apolipoprotein (apo) B/A-I ratio (A) and total cholesterol/high-density lipoprotein cholesterol (TC/HDL-C) ratio (B) for major adverse cardiovascular events after adjustment for traditional risk factors and nontraditional risk markers
 Model 1Model 2Model 3
HR (95% CI)P-valueHR (95% CI)P-valueHR (95% CI)P-value
  1. All models are adjusted for age and sex.

  2. Model 1: additional adjustment for traditional risk factors (hypertension, diabetes, obesity and smoking).

  3. Model 2: additional adjustment for nontraditional risk markers [urinary albumin excretion (UAE) and high-sensitivity C-reactive protein (hs-CRP)].

  4. Model 3: additional adjustment for both traditional risk factors and nontraditional risk markers.

  5. Hypertension is defined as blood pressure >140/90 mmHg and/or use of antihypertensive drugs; diabetes is defined as fasting plasma glucose ≥7.0 mmol L−1; obesity is defined as body mass index ≥30 kg m−2; HRs for apoB/apoA-I ratio, TC/HDL-C, UAE and hs-CRP are given per 1-SD increase.

A
 ApoB/apoA-I1.26 (1.14–1.40)<0.0011.27 (1.14–1.41)<0.0011.24 (1.12–1.38)<0.001
 Hypertension1.76 (1.38–2.24)<0.0011.59 (1.24–2.04)<0.001
 Diabetes1.08 (0.85–1.37)0.5361.03 (0.83–1.27)0.807
 Obesity1.26 (0.98–1.62)0.0711.14 (0.88–1.47)0.320
 Smoking
  Never1 1 
  Former1.27 (0.93–1.71)0.136  1.21 (0.83–1.65)0.237
  Current2.45 (1.80–3.33)<0.0012.15 (1.57–2.94)<0.001
 UAE1.16 (1.07–1.26)<0.0011.12 (1.03–1.22)0.008
 hs-CRP1.35 (1.20–1.52)<0.0011.21 (1.07–1.38)0.003
B
 TC/HDL-C ratio1.19 (1.11–1.28)<0.0011.20 (1.12–1.30)<0.0011.19 (1.11–1.29)<0.001
 Hypertension1.79 (1.41–2.29)<0.0011.61 (1.25–2.07)<0.001
 Diabetes1.09 (0.86–1.38)0.4681.04 (0.84–1.28)0.726
 Obesity1.26 (0.98–1.62)0.0661.13 (0.88–1.46)0.334
 Smoking
  Never1 1 
  Former1.27 (0.93–1.730.138  1.20 (0.88–1.65)0.248
  Current2.46 (1.81–3.34)<0.001  2.14 (1.56–2.92)<0.001
 UAE1.17 (1.08–1.27)<0.0011.12 (1.03–1.22)0.007
 hs-CRP1.37 (1.22–1.54)<0.0011.23 (1.09–1.39)0.001

Because of the design of the PREVEND study with enrichment of subjects with urinary albumin excretion >10 mg L−1, the analyses were repeated using a complex sample design procedure. These analyses yielded essentially similar results. The age- and sex-adjusted HRs for MACEs for the apoB/apoA-I and TC/HDL-C ratios were 1.37 (95% CI, 1.21–1.56, P < 0.001) and 1.19 (95% CI, 1.09–1.29, P < 0.001), respectively. Finally, sensitivity analyses were carried out on the data-set of subjects recruited from the random sample of the PREVEND cohort (= 2819) [20]. The age- and sex-adjusted relationship between MACEs and the apoB/apoA-I ratio (HR: 1.37; 95% CI, 1.17–1.63, P < 0.001) was similar to that observed in the whole study population (Table 3), whereas the HR for the TC/HDL-C ratio was 1.13 (95% CI, 0.96–1.24, P = 0.19).

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Conflict of interest statement
  8. Acknowledgements
  9. References
  10. Supporting Information

The results of this prospective case–cohort study show that the association between a first MACE and the serum TC/HDL-C and apoB/apoA-I ratios is at least as strong as that between a first MACE and the single pro-atherogenic (apo)lipoprotein measures. Direct pair-wise comparison of the strength of the relationship between MACEs and these ratios showed a higher hazard attributable to the apoB/apoA-I ratio, but this difference was not statistically significant after adjustment for sex and age. Of relevance, both ratios predicted a first MACE after additional adjustment for triglycerides, as well as for nonlipid risk factors and hs-CRP and albuminuria. The results of the present study, therefore, suggest that incident cardiovascular risk is determined by both the TC/HDL-C and the apoB/apoA-I ratios in the general population even when taking account of novel risk markers.

Our findings are in agreement with those of a recent meta-analysis showing similar age- and sex-adjusted hazards for incident coronary heart disease for the apoB/apoA-I compared with the TC/HDL-C ratio [17]. By comparison, the INTERHEART case–control study [1], as well as the prospective Amoris and EPIC-Norfolk studies, showed that the apoB/apoA-I ratio was more important than the TC/HDL-C ratio with respect to their relation with incident cardiovascular events [3, 14]. The present observation that non-HDL-C rather than apoB is the strongest single pro-atherogenic measure is also in keeping with the meta-analysis [17], but not with the Amoris study [3]. However, HDL-C was not directly measured in the latter study [3]. Instead, both HDL-C and LDL-C were estimated using a mathematical formula based on apoA-I, triglycerides and TC. A potentially important difference between the EPIC-Norfolk study [14] and the current study is that we only included fasting individuals. The serum apoB/apoA-I ratio is thought to be unaffected by the nonfasting state [11], but the interpretation of nonfasting non-HDL-C may be confounded by cholesterol contained in chylomicrons [11, 27]. The Friedewald formula was originally reported to be inaccurate when using nonfasting samples [25]. Therefore, it is possible that nonfasting conditions of the participants may to some extent have affected the interpretation of the EPIC-Norfolk study [14] and the meta-analysis [17]. Although the relationship between incident coronary heart disease and serum triglyceride levels was found to be unaffected by the nonfasting state [17], it is clear that collecting fasting serum samples is likely to reduce the potential bias owing to postprandial triglyceride variations. Thus, the present study, in which we directly compared cardiovascular hazard attributable to the fasting serum apoB/apoA-I ratio with that of the TC/HDL-C ratio, is complementary to these reports [14, 17]. Of further interest, lower apoA-II was found in cases compared with controls, but did not predict MACEs independently of apoA-I and HDL-C levels. By comparison, coronary risk was inversely related to apoA-II even after controlling for HDL-C, apoA-I and conventional risk factors [28], although no difference in apoA-II levels between cases and controls was observed in another prospective study [29]. Collectively, these findings suggest that the value of additional apoA-II measurement is limited.

Microalbuminuria is an independent predictor of cardiovascular disease [18, 30] and diabetes mellitus [31] and is associated with endothelial dysfunction and chronic inflammation [30, 32–34]. Microalbuminuria is also associated with unfavourable lipoprotein changes, as evidenced by lower levels of HDL-C and higher concentrations of triglycerides and small LDL particles [35]. Furthermore, hs-CRP is associated positively with obesity and insulin resistance and negatively with HDL-C [16, 36–38]. In view of these interrelationships, we consider our finding that the association between incident MACE and the apoB/apoAI and TC/HDL-C ratios was not significantly attenuated by the degree of urinary albumin excretion and the level of hs-CRP to be of clinical interest. This result supports the hypothesis that lipid factors, microalbuminuria and enhanced chronic inflammation are at least in part independent predictors of clinically manifest atherosclerosis. Of further relevance, both ratios also significantly predicted events in subjects with elevated urinary albumin excretion, supporting the validity of these (apo)lipoprotein measures in these high-risk subjects.

Comparison of the strength of the relationships between the apoB/apoA-I and the TC/HDL-C ratios and incident cardiovascular disease needs to be interpreted from a pathophysiological perspective. The pro-atherogenic potential of apoB-containing lipoproteins is neither fully reflected by their cholesterol concentration as such, nor by the serum apoB level, but there is general agreement that all apoB-containing lipoprotein particles are implicated in the atherosclerotic process [39]. In this respect, it is of interest that non-HDL-C was also a better predictor of first MACE than LDL-C in the current study. Of further relevance, evidence is accumulating that not all HDLs are equally atheroprotective and that these particles can become dysfunctional [40–44]. It has been suggested that this problem can at least in part be circumvented by apoA-I measurement [40]. Nonetheless, modification of apoA-I (e.g. by oxidation and chlorination of amino acid residues) may attenuate its anti-atherogenic properties [45]. This could possibly explain why the inverse relationship between incident MACE and apoA-I was weaker than between incident MACE and HDL-C. Taken together, these results clearly demonstrate that routinely available lipoprotein cholesterol and apolipoprotein measures are still suboptimal for cardiovascular risk prediction.

Several methodological aspects of our study need to be considered. First, we carried out a prospective analysis in a population-based cohort. Consequently, the number of events in women and in each separate cardiovascular domain was not large enough to allow for meaningful sex- and domain-specific analyses. Secondly, as in other studies [4–6, 12, 14, 15, 17], we only included subjects without clinically manifest cardiovascular disease at baseline. Thirdly, we reliably excluded prescription of lipid-lowering drugs at baseline, but did not include information regarding use of these agents during follow-up in the present analyses. However, statin treatment shifts the relation of LDL-C and non-HDL-C with apoB towards lower concentrations of LDL-C and non-HDL-C that correspond to similar apoB levels [46, 47]. Thus, if statin treatment was started during follow-up, this may have underestimated the superiority of the apoB/apoA-I ratio. It has indeed been suggested that the apoB/apoA-I ratio is better than the TC/HDL-C ratio for predicting recurrent events during statin treatment [13]. Additionally, it should be noted that relevant bias due to over-representation of subjects with microalbuminuria because of the design of the PREVEND study is very unlikely, as both a complex design procedure and a sensitivity analysis yielded similar results. Therefore, we consider our findings to be representative of the general population.

Of note, it should be appreciated that we did not aim to address the discriminative power of the various (apo)lipoprotein variables in predicting risk. The magnitude of HRs of the (apo)lipoprotein measures as documented in our study is in keeping with those reported previously [17]. Of importance, much higher hazards are required to be able to demonstrate significant improvement in risk prediction upon addition of the risk factor/marker under study to a set of established risk factors [14, 48, 49]. Finally, continued effort is still needed to further optimize standardization of HDL-C and apolipoprotein measurement worldwide. Assay availability and cost remain relevant issues that determine preference for use in clinical practice. The results of our study suggest that calculated LDL-C does not add to TC and HDL-C measurement.

In conclusion, the results of this case–cohort study support the contention that the fasting serum apoB/apoA-I ratio and the TC/HDL-C ratio are both important determinants of a first MACE in the general population. The relationships between events and these ratios are only slightly affected by triglyceride levels, nonlipid risk factors, hs-CRP and albuminuria.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Conflict of interest statement
  8. Acknowledgements
  9. References
  10. Supporting Information

This study was supported by grants from the Netherlands Heart Foundation (grant 2001.005) and the Jan Kornelis de Cock Foundation Groningen, the Netherlands. The technical assistance of J.J. Duker and J. van der Wal–Haneveld is appreciated. We thank Dade Behring (Marburg, Germany) for supplying equipment (Behring Nephelometer II) and analytes for the determination of apolipoproteins and other metabolites.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Conflict of interest statement
  8. Acknowledgements
  9. References
  10. Supporting Information
  • 1
    McQueen MJ, Hawken S, Wang X et al. Lipids, lipoproteins, and apolipoproteins as risk markers of myocardial infarction in 52 countries (the INTERHEART study): a case–control study. Lancet 2008; 372: 22433.
  • 2
    National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). Third report of the National Cholesterol Education Program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (Adult Treatment Panel III) final report. Circulation 2002; 106: 3143421.
  • 3
    Walldius G, Jungner I, Holme I, Aastveit AH, Kolar W, Steiner E. High apolipoprotein B, low apolipoprotein A-I, and improvement in the prediction of fatal myocardial infarction (AMORIS study): a prospective study. Lancet 2001; 358: 202633.
  • 4
    Talmud PJ, Hawe E, Miller GJ, Humphries SE. Nonfasting apolipoprotein B and triglyceride levels as a useful predictor of coronary heart disease risk in middle-aged UK men. Arterioscler Thromb Vasc Biol 2002; 22: 191823.
  • 5
    Lamarche B, Moorjani S, Lupien PJ et al. Apolipoprotein A-I and B levels and the risk of ischaemic heart disease during a five year follow up of men in the Quebec cardiovascular study. Circulation 1996; 94: 2738.
  • 6
    Benn M, Nordestgaard BG, Jensen GB, Tybjaerg-Hansen A. Improving prediction of ischemic cardiovascular disease in the general population using apolipoprotein B The Copenhagen City Heart Study. Arterioscler Thromb Vasc Biol 2007; 27: 66170.
  • 7
    Contois JH, McConnell JP, Sethi AA et al. Apolipoprotein B and cardiovascular disease risk: position statement from the AACC Lipoproteins and Vascular Diseases Division Working Group on Best Practices. Clin Chem 2009; 55: 40719.
  • 8
    Brunzell JD, Davidson M, Furberg CD et al. Lipoprotein management in patients with cardiometabolic risk: consensus conference report from the American Diabetes Association and the American College of Cardiology Foundation. J Am Coll Cardiol 2008; 51: 151224.
  • 9
    Sniderman A. Targets for LDL-lowering therapy. Curr Opin Lipidol 2009; 20: 2827.
  • 10
    Walldius G, Jungner I. Apolipoprotein B and apolipoprotein A-I: risk indicators of coronary heart disease and targets for lipid-modifying therapy. J Intern Med 2004; 255: 188205.
  • 11
    Barter PJ, Ballantyne CM, Carmena R et al. Apo B versus cholesterol in estimating cardiovascular risk and in guiding therapy: report of the thirty-person/ten-country panel. J Intern Med 2006; 259: 24758.
  • 12
    Ridker PM, Rifai N, Cook NR, Bradwin G, Buring JE. Non-HDL cholesterol, apolipoproteins A-I and B100, standard lipid measures, lipid ratios, and CRP as risk factors for cardiovascular disease in women. JAMA 2005; 294: 32633.
  • 13
    Kastelein JJ, van der Steeg WA, Holme I et al. Lipids, apolipoproteins, and their ratios in relation to cardiovascular events with statin treatment. Circulation 2008; 117: 30029.
  • 14
    van der Steeg WA, Boekholdt SM, Stein EA et al. Role of the apolipoprotein B-apolipoprotein A-I ratio in cardiovascular risk assessment: a case–control analysis in EPIC-Norfolk. Ann Intern Med 2007; 146: 6408.
  • 15
    Pischon T, Girman CJ, Sacks FM et al. Non-high-density lipoprotein cholesterol and apolipoprotein B in the prediction of coronary heart disease in men. Circulation 2005; 112: 337583.
  • 16
    Parish S, Peto R, Palmer A et al. The joint effects of apolipoprotein B, apolipoprotein A1, LDL cholesterol, and HDL cholesterol on risk: 3510 cases of acute myocardial infarction and 9805 controls. Eur Heart J 2009; 30: 213746.
  • 17
    The Emerging Risk Factors Collaboration. Major lipids, apolipoproteins, and risk of vascular disease. JAMA 2009; 302: 19932000.
  • 18
    Hillege HL, Fidler V, Diercks GF et al. Urinary albumin excretion predicts cardiovascular and noncardiovascular mortality in general population. Circulation 2002; 106: 177782.
  • 19
    Arnlöv J, Evans JC, Meigs JB et al. Low-grade albuminuria and incidence of cardiovascular disease events in nonhypertensive and nondiabetic individuals: the Framingham Heart Study. Circulation 2005; 112: 96975.
  • 20
    Lambers Heerspink HJ, Brantsma AH, de Zeeuw D et al. Albuminuria assessed from first-morning-void urine samples versus 24-hour urine collections as a predictor of cardiovascular morbidity and mortality. Am J Epidemiol 2008; 168: 897905.
  • 21
    Chobanian AV, Bakris GL, Black HR et al. The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. JAMA 2003; 289: 256072.
  • 22
    Borggreve SE, Hillege HL, Wolffenbuttel BHR et al. An increased coronary risk is paradoxically associated with common cholesteryl ester transfer protein gene variations that relate to higher high-density lipoprotein cholesterol: a population-based study. J Clin Endocrinol Metab 2006; 91: 33828.
  • 23
    Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Report of the Expert Committee on the Diagnosis and Classification of diabetes mellitus. Diabetes Care 1997; 20: 118397.
  • 24
    Warnick GR, Nauck M, Rifai N. Evolution of methods for measurement of HDL-cholesterol: from ultracentrifugation to homogeneous assays. Clin Chem 2001; 47: 157996.
  • 25
    Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem 1972; 18: 499502.
  • 26
    Steinmetz J, Tarallo P, Fournier B, Caces E, Siest G. Reference limits of apolipoprotein A-I and apolipoprotein B using an IFCC standardized immunonephelometric method. Eur J Clin Chem Clin Biochem 1995; 33: 33742.
  • 27
    Dullaart RPF, Groener JE, van Wijk H, Sluiter WJ, Erkelens DW. Alimentary lipemia-induced redistribution of cholesteryl ester between lipoproteins. Studies in normolipidemic, combined hyperlipidemic, and hypercholesterolemic men. Arteriosclerosis 1989; 9: 61422.
  • 28
    Birjmohun RS, Dallinga-Thie GM, Kuivenhoven JA et al. Apolipoprotein A-II is inversely associated with risk of future coronary artery disease. Circulation 2007; 116: 202935.
  • 29
    Sweetnam PM, Bolton CH, Downs LG et al. Apolipoproteins A-I, A-II and B, lipoprotein(a) and the risk of ischaemic heart disease: the Caerphilly study. Eur J Clin Invest 2000; 30: 94756.
  • 30
    Stehouwer CD, Smulders YM. Microalbuminuria and risk for cardiovascular disease: analysis of potential mechanisms. J Am Soc Nephrol 2006; 17: 210611.
  • 31
    Brantsma AH, Bakker SJ, Hillege HL et al. Urinary albumin excretion and its relation with C-reactive protein and the metabolic syndrome in the prediction of type 2 diabetes. Diabetes Care 2005; 28: 252530.
  • 32
    Deckert T, Feldt-Rasmussen B, Borch-Johnsen K, Jensen T, Kofoed-Enevoldsen A. Albuminuria reflects widespread vascular damage. The Steno hypothesis. Diabetologia 1989; 32: 21926.
  • 33
    Stuveling EM, Bakker SJ, Hillege HL et al. C-reactive protein modifies the relationship between blood pressure and microalbuminuria. Hypertension 2004; 43: 7916.
  • 34
    Kshirsagar AV, Bomback AS, Bang H et al. Association of C-reactive protein and microalbuminuria (from the National Health and Nutrition Examination Surveys, 1999 to 2004). Am J Cardiol 2008; 101: 4016.
  • 35
    de Boer IH, Astor BC, Kramer H et al. Mild elevations of urine albumin excretion are associated with atherogenic lipoprotein abnormalities in the Multi-Ethnic Study of Atherosclerosis (MESA). Atherosclerosis 2008; 197: 40714.
  • 36
    Schmidt MI, Duncan BB. Diabesity: an inflammatory metabolic condition. Clin Chem Lab Med 2003; 41: 112030.
  • 37
    Dullaart RPF, de Vries R, Sluiter WJ, Voorbij HA. High plasma C-reactive protein (CRP) is related to low paraoxonase-I (PON-I) activity independently of high leptin and low adiponectin in type 2 diabetes mellitus. Clin Endocrinol (Oxf) 2009; 70: 2216.
  • 38
    Dullaart RPF, de Vries R, Dikkeschei LD, Sluiter WJ. Higher plasma leptin largely explains increased C-reactive protein levels in women. Eur J Clin Invest 2007; 37: 2313.
  • 39
    Williams KJ, Tabas I. The response-to-retention hypothesis of atherogenesis reinforced. Curr Opin Lipidol 1998; 9: 4714.
  • 40
    van der Steeg WA, Holme I, Boekholdt SM et al. High-density lipoprotein cholesterol, high-density lipoprotein particle size, and apolipoprotein A-I: significance for cardiovascular risk: the IDEAL and EPIC-Norfolk studies. J Am Coll Cardiol 2008; 51: 63442.
  • 41
    Dullaart RPF, Perton F, van der Klauw MM, Hillege HL, Sluiter WJ; on behalf of the PREVEND Study Group. High plasma lecithin:cholesterol acyltransferase activity does not predict low incidence of cardiovascular events: possible attenuation of cardioprotection associated with high HDL cholesterol. Atherosclerosis 2010; 208: 53742.
  • 42
    Kontush A, Chapman MJ. Functionally defective high-density lipoprotein: a new therapeutic target at the crossroads of dyslipidemia, inflammation, and atherosclerosis. Pharmacol Rev 2006; 58: 34274.
  • 43
    Corsetti JP, Gansevoort RT, Sparks CE, Dullaart RPF. Inflammation reduces HDL protection against primary cardiac risk. Eur J Clin Invest 2010; 40: 4839.
  • 44
    Dullaart RPF. Increased coronary heart disease risk determined by high high-density lipoprotein cholesterol and C-reactive protein: modulation by variation in the CETP gene. Arterioscler Thromb Vasc Biol 2010; 30: 15023.
  • 45
    Shao B, Oda MN, Oram JF, Heinecke JW. Myeloperoxidase: an inflammatory enzyme for generating dysfunctional high density lipoprotein. Curr Opin Cardiol 2006; 21: 3228.
  • 46
    Ballantyne CM, Raichlen JS, Cain VA. Statin therapy alters the relationship between apolipoprotein B and low-density lipoprotein cholesterol and non-high-density lipoprotein cholesterol targets in high-risk patients: the MERCURY II (Measuring Effective Reductions in Cholesterol Using Rosuvastatin) trial. J Am Coll Cardiol 2008; 52: 62632.
  • 47
    Kappelle PJWH, Zwang L, Huisman MV et al. Atorvastatin affects low density lipoprotein and non-high density lipoprotein cholesterol relations with apolipoprotein B in type 2 diabetes mellitus: modification by triglycerides and cholesteryl ester transfer protein. Expert Opin Ther Targets 2009; 13: 74351.
  • 48
    Berkwits M, Guallar E. Risk factors, risk prediction, and the apolipoprotein B-apolipoprotein A-I ratio. Ann Intern Med 2007; 146: 6779.
  • 49
    Ware JH. The limitations of risk factors as prognostic tools. N Engl J Med 2006; 355: 26157.

Supporting Information

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Conflict of interest statement
  8. Acknowledgements
  9. References
  10. Supporting Information

Table S1. Baseline clinical and laboratory characteristics of study participants according to gender.

FilenameFormatSizeDescription
JOIM_2323_sm_Supplementarytable.doc69KSupporting info item

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