Diabetes & Metabolic Syndrome: Clinical Research & Reviews (2007) 1, 29—36

http://diabetesindia.com/

ORIGINAL PAPER

Non-HDL cholesterol versus Apolipoprotein B in theidentification of dyslipidemic phenotypesassociated with cardiovascular risk in type2 diabetic dyslipoproteinemia

Jamal Ahmad *, Abdur Rahman Khan, Faiz Ahmed, Sabah Siddiqui

Department of Medicine, Jawaharlal Nehru Medical College and Hospital, Aligarh Muslim University,Aligarh 202002, India

KEYWORDSNon-HDL cholesterol;Apolipoprotein B;Carotid intima—mediathickness;Type 2 diabetesmellitus

Summary

Objective: Few studies have compared non-HDL cholesterol (non-HDLc) and Apoli-poprotein B (apoB) as markers of atherosclerotic risk. No such study has yet beenundertaken in Asian-Indians who have a different lipid—lipoprotein profile than theirWestern counterparts. Our aim, therefore, was to evaluate the role of non-HDLc andapoB, as markers of all potentially atherogenic species, and to further assess as towhich is the better index of the risk of cardiovascular disease (CVD) in type 2 diabeticsubjects.Research design and methods: Lipidic parameters, apoB and carotid mean intima—media thickness (IMT) were determined in the 95 diabetic subjects included in thestudy. Subjects were classified on the basis of apoB and triglyceride as well as non-HDLc and triglyceride levels. Agreement of the resultant phenotypes with IMT wasassessed (correlation and concordance (k) analysis), and the major contributor to thevariance of IMT was determined using multistep linear regression.Results: HyperapoB was the most prevalent lipoproteic abnormality. The correlationbetween apoB and non-HDLc was strong in the whole cohort (r = 0.60, p < 0.01) andbetter in the hypertriglyceridemic subgroup (r = 0.67, p < 0.01). There was significantconcordance between IMT and apoB and non-HDLc in the whole cohort (k = 0.490,p < 0.0001; k = 0.403, p < 0.000); while the concordance between the apoB and non-HDLc dependent phenotypes and IMTwas better in the hypertriglyceridemic subgroup(HtgHapob-k = 0.598, p < 0.0001; HtgHnonhdl-k = 0.481, p < 0.0001) as opposed tothe normotriglyceridemic subgroup (NtgHapob-k = 0.387, p < 0.0001; NtgHnonhdl-k = 0.043, p = NS). Further apoB was a better predictor of IMT in all the subgroups aswell as the whole cohort (R2 = 0.378, b-coefficient = 0.002) as compared to non-HDLc(R2 change = 0.030, b-coefficient = 0.0017).

* Corresponding author. Tel.: +91 571 2721173; fax: +91 571 2721173.E-mail address: jamalahmad11@rediffmail.com (J. Ahmad).

1871-4021/$ — see front matter # 2006 Diabetes India. Published by Elsevier Ltd. All rights reserved.doi:10.1016/j.dsx.2006.11.002

30 J. Ahmad et al.

Conclusions: Non-HDLc and apoB are equivalent atherogenic markers of cardiovas-cular risk in hypertriglyceridemic diabetic subjects, but apoB is a better index of therisk of cardiovascular disease in normotriglyceridemic subjects. Thus, measurementof apoB might be helpful in identification of a subgroup of apparently normolipidemicsubjects who have hyperapoB and thus stand increased cardiovascular risk.# 2006 Diabetes India. Published by Elsevier Ltd. All rights reserved.

Introduction

In type 2 diabetes, dyslipoproteinemia is an impor-tant and common risk factor for CHD [1,2] and also amajor contributor to the proatherogenic profile ofthe disease. The present diagnostic and therapeuticalgorithms are built on LDLc [3]. As a consequence ofthe technical weaknesses inherent in the measure-ment of LDLc [4] and the physiological limitations ofLDLc as a measure of atherogenic risk [5], majordisadvantages are automatically built into thesealgorithms and should no longer be ignored. Otherindices like, plasma Apolipoprotein B (apoB) andnon-HDL cholesterol (non-HDLc) have been sug-gested that may be better predictors of cardiovas-cular risk, both on initial diagnosis and at follow-up[6]. Non-HDLc has, in fact, been included as atherapeutic target for hypertriglyceridemicpatients in the most recent NCEP recommendations[3]. As there is a good correlation between non-HDLcand apoB [7], measurement of non-HDLc has beenargued to be a substitute for measurement of apoB[3]; but, some studies have reported to the contrary[6,8]. Whether total apoB could be a better measurethan non-HDLc in predicting cardiovascular disease(CVD) risk in diabetic subjects, or vice versa is amatter of considerable debate.

A non-invasive and quantitative investigation foridentifying atheroslcerosis, even in an asympto-matic subject, is by measuring intima—media thick-ness (IMT) in carotid artery [9]. It has beensuggested that the carotid IMT may be the mostsensitive marker for the earliest stages of athero-sclerosis [10] An increase in carotid IMT is associatedwith an increased risk of CVD or CHD [11].

Ethnic differences have been reported by variousstudies in CHD morbidity and mortality [12,13], theprevalence and course of type 2 diabetes [14] and inIMT [15,16]. These differences emphasize the needfor studies on IMTand its determinants in differentpopulations. Asian-Indians are of particular interestas they have high prevalence rates of diabetes[14,17], premature CHD [12,13], as well as a dif-ferent lipid—lipoprotein profile as compared totheir Western counterparts [18]. Because of thesefactors the need for early CVD risk factor assess-ment and modification is greatly increased in thispopulation.

To the best of our knowledge, there has been nostudy till date to compare apoB and non-HDLc asindices of cardiovascular risk in Asian-Indian type 2diabetic subjects known to have a high prevalence ofdiabetes [14,17] as well as premature CHD [12,13].With this background, this study focused on therelation between lipids and early signs of athero-sclerosis, especially in diabetic subjects. This studypresents data on carotid IMT in Asian-Indian type 2diabetic subjects with reference to the atherogenicindices namely non-HDLc and apoB. It further tries tocompare the classification of the diabetic subjects onthe basis of apoB and non-HDLc and aims to establishas to which of these two atherogenic indices is abetter predictor of carotid intima media thicknessand hence atherosclerotic risk.

Methods

Patients

A total of 102 newly detected (duration of disease1—12 months) type 2 diabetic subjects (54 males; 48females) were recruited at the outpatient clinic ofEndocrine and Metabolic Division, Department ofMedicine, JN Medical College Hospital, AMU, Ali-garh, India, from January 2003 to June 2004. Ofthese, 7 were excluded from the study on the basisof the exclusion criteria given below and 95 newlydetected type 2 diabetic subjects (51 males; 44females) were chosen for the study. All subjectsgave informed consent and the ethical committeeapproved the study. The diagnosis of diabetes mel-litus was made as per criteria laid down by WHO[19].

Exclusion criteria

� A cute metabolic complications of diabetes melli-

tus.

� E vidence of CHD. Patients were diagnosed as

having cardiovascular disease on the basis ofacute MI, history of angina, previous MI, post-CABG or balloon angioplasty, ECG changes andechocardiography.

� C

erebrovascular accidents. � I nherited/acquired/family history of disorders of

lipid/lipoprotein metabolism.

Non-HDL versus apoB in identification of dyslipidemic phenotypes 31

� D

eranged liver function. � M edications known to affect lipid metabolism

(other than a sulfonylurea).

Procedures

A detailed history and physical examination wascarried out for every subject who entered in thestudy as per a pre-designed questionnaire. Examina-tion comprised of a thorough physical examination,assessment of vital parameters, anthropometry andsystemic examination. The subjects were requestedto report to the endocrinology laboratory after anovernight fast of 10—12 h; screening investigationincluded fasting and post-prandial plasma glucose,glycohaemoglobin (HbA1), serum creatinine, liverfunction test, fasting lipid profile, apoB, chestX-ray, routine urine analysis, electrocardiogramand fundus examination. Other investigationsincluded colour Doppler study of carotid arteriesand echocardiography wherever indicated.

Laboratory determinations

Total cholesterol and triglycerides were estimatedby enzymatic methods (Pointe Scientific Inc., MI,USA). HDL cholesterol was estimated by Ranbaxy-HDL-cholesterol precipitation method. LDLc wascalculated using Friedewald formula [20]. Non-HDLcwas calculated by subtracting HDL cholesterol fromtotal cholesterol. The cut-offs were taken as definedby the NCEP (total cholesterol � 200 mg/dl, trigly-ceride � 150 mg/dl, LDLc � 130 mg/dl and non-HDLc was taken as �160 mg/dl {defined as thecut-off equivalent to an LDL level when pharmaco-logical therapy is warranted in type 2 diabetes}) [3].

ApoB assay was done by immunoturbidimetrictest. Serumwas separated by centrifugation at roomtemperature and stored in sterile tubes at �80 8Ctill the test was performed. Endpoint determinationof the concentration of apoB was through photo-metric measurement of antigen antibody reactionbetween antibodies to apoB and apoB present in theplasma (Diasys Diagnostic Systems; Germany). Thecut-off for apoB was taken to be 1.2 g/l according tothe Framingham Offspring Study [21].

Measurement of carotid IMT

The IMTof the carotid arteries was determined usinga high resolution B-mode Ultrasonography system(Logic 500 Proseries; Wipro GE). Extra cranial car-otid arteries (common and internal carotid arteriesand the carotid bulb) were examined on both sidesThe longitudinal view demonstrated two nearlyparallel echogenic lines, the inner line is the

intima—lumen interface and the outer line is themedia—adventitia interface. The distance betweenthese two lines is the intima—media thickness mea-sured in mm. An IMT more than 0.8 mm representsearly changes of atherosclerosis. A mean of sixmeasurements on either side were taken. In addi-tion to IMT measurement, presence of atherosclero-tic plaques or stenosis was noted.

Statistical analysis

Analysis was performed using SPSS version 11.0statistical package for Windows (SPSS, Chicago,IL). Continuous variables were expressed asmean � S.D., and qualitative data are expressedin percentages. For continuous variables, indepen-dent sample t test was used. The associationbetween continuous variables was tested by Pear-son’s correlation. Despite the skewed distribution oftriglycerides we did not transform the variable, as itwas an independent variable and not the dependentvariable of interest. All tests were two-tailed, and ap value of �0.05 was considered significant. Con-cordance between classifications according to tri-glycerides, as well as apoB and non-HDLc wasassessed using the k (Cohen’s kappa) index. Valuesbetween 0.21 and 0.40, 0.41 and 0.60, 0.61 and0.80, and 0.81 and 1.0 showed fair, moderate, goodand very good concordance, respectively [22]. Step-wise multiple linear regression model was used withcarotid IMT as the dependent variable and withindependent variables of interest namely, age, gen-der, weight, height, BMI, waist and hip circumfer-ences, waist to hip ratio, systolic and diastolic bloodpressure, fasting and post-prandial plasma glucose,glycated haemoglobin, serum cholesterol, triglycer-ides, LDLc, HDLc, VLDLc, non-HDLc, apoB and theratio of urinary albumin to creatinine.

Results

The clinical and biological features of the 95 type 2diabetic subjects included in the study are shown inTable 1. The majority of subjects were above 40years of age. Sixteen (17%) were controlled on dietalone while the remaining 79 (83%) were on sulfo-nylureas. None of the patients were ever treatedwith insulin while 40 (42%) patients were hyperten-sive and were on medications (ACE inhibitor; ARB orboth). Smoking, either currently or in the past wasreported by approximately 41% of the diabetic sub-jects. None of the patients had any evidence ofcoronary artery disease.

Diabetic subjects were classified into varioussubgroups on the basis of the concentrations of

32 J. Ahmad et al.

Table 1 Study group–—demographic profile and clinical features

Male, 51 (54%) Female, 44 (46%) Mean t p

Mean age (years) 50.9 � 9.5 50.2 � 9.9 57.1 � 8.1 0.401 NSWeight (kg) 66.7 � 10.9 74.9 � 7.8 70.5 � 5.0 0.743 NSHeight (cm) 172.4 � 40.1 149.6 � 9.8 161.9 � 32.1 3.67 0.0001BMI (kg/m2) 23.8 � 03 27.6 � 4.9 25.6 � 4.4 4.632 0.001Waist circumference (cm) 90.8 � 9.7 94.3 � 10.1 92.4 � 10.0 1.687 0.01Hip circumference (cm) 93.9 � 8.9 99.9 � 9.7 96.7 � 9.7 3.122 0.002Waist to hip ratio 0.95 � 0.1 0.95 � 0.1 0.95 � 0.1 0.195 NSSystolic BP (mmHg) 134.4 � 17.4 141.7 � 21.9 137.8 � 19.9 1.816 NSDiastolic BP (mmHg) 85.4 � 11.0 88.5 � 11.4 86.8 � 11.3 1.355 NSFasting glucose (mg/dl) 125.3 � 42.6 136.2 � 44.5 130.3 � 43.6 1.216 NSPP blood glucose (mg/dl) 181.8 � 52.5 191.8 � 67.1 186.4 � 59.6 0.815 NSHbA1 (%) 8.7 � 0.7 8.6 � 0.5 8.7 � 0.6 0.460 NSCreatinine (mg/dl) 1.0 � 0.2 0.9 � 0.2 0.9 � 0.2 2.009 NSSerum cholesterol (mg/dl) 179.9 � 34.2 184.9 � 29.7 182.2 � 32.1 0.749 NSHDL cholesterol (mg/dl) 43.1 � 6.5 42.1 � 6.9 42.6 � 6.7 0.750 NSLDL cholesterol (mg/dl) 105.7 � 26.7 110.7 � 25.1 108.1 � 25.9 0.956 NSVLDL cholesterol (mg/dl) 31.6 � 13.2 33.6 � 10.8 32.6 � 12.1 0.956 NSSerum triglycerides (mg/dl) 149.9 � 60.9 157.2 � 52.2 153.3 � 56.8 0.620 NSNon-HDL cholesterol (mg/dl) 136.2 � 31.8 143.5 � 28.7 145.7 � 37.9 1.16 NSApolipoprotein B (mg/dl) 1.6 � 0.9 1.3 � 0.6 1.4 � 0.7 0.015 NSTotal cholesterol/HDL cholesterol 4.3 � 0.9 4.5 � 0.9 4.4 � 0.9 0.985 NSMean IMT (mm) 0.7 � 0.1 0.7 � 0.1 0.7 � 0.1 0.15 NS

Values are mean � S.D.; t is value of Student’s t test; p value indicates difference (independent sample t-test; NS: not significant).

triglycerides and non-HDLc as well as triglyceridesand apoB. The number of subjects allocated to eachsubgroup is given below.

Apolipoprotein B and triglyceride

NormoTriglyceridemic-NormoApoB! (NtgNa-(NtgNapob), n = 30 (32%);NormoTriglyceridemic-HyperApoB! (NtgHa-(NtgHapob), n = 45 (47%);HyperTriglyceridemic-NormoApoB! (HtgNa-(HtgNapob), n = 1 (1%);HyperTriglyceridemic-HyperApoB! (HtgHapob),n = 19 (20%).

Non-HDL cholesterol and triglyceride

NormoTriglyceridemic-Normo-nonHDLc! (NtgNnhdl), n = 60 (63%);NormoTriglyceridemic-Hyper-NonHDLc! (NtgHnhdl), n = 15 (16%);HyperTriglyceridemic-Normo-nonHDLc! (HtgNnhdl), n = 3 (3%);HyperTriglyceridemic-Hyper-nonHDLc! (HtgHnhdl), n = 17 (18%).

Hypercholesterolemia, hypertriglyceridemia andlow HDLc were present in 23 (24%), 20 (21%) and 32(33%) diabetic subjects, respectively. HyperapoBwas the most prevalent phenotype with 64 (67%)

subjects (45 normotriglyceridemic and 19 hypertri-glyceridemic). Increased levels of non-HDLc were in32 (34%) subjects (15 normotriglyceridemic and 17hypertriglyceridemic). Thus, the number of athero-genic particles as measured by non-HDLc was 32(34%) as compared to 64 (67%) by apoB. Thus, abouttwo-third of our patients had elevated apoB andtherefore elevated LDL particle number.

Agreement between IMTwith age, components ofinsulin resistance and the various atherogenicindices was assessed via Pearson’s linear correlationand concordance analysis in each subgroup as well asthe whole cohort. IMT does not show a significantcorrelation with the glycemic parameters andcomponents of insulin resistance but was signifi-cantly correlated with the all the indices of athero-genic risk except HDLc. ApoB had a strongercorrelation with carotid mean IMT than non-HDLcin the whole cohort as well as the subgroups(Table 2).

Concordance revealed significant agreementbetween IMT and apoB (k = 0.490, p < 0.0001) aswell as between IMT and non-HDLc (k = 0.403,p < 0.0001) in the cohort as a whole; while theconcordance of IMT was better in the hypertrigly-ceridemic subgroup (HtgHapob-k = 0.598, p <0.0001; HtgHnonhdl-k = 0.481, p < 0.0001) than inthe normotriglyceridemic subgroup (NtgHapob-k = 0.387, p < 0.0001; NtgHnonhdl-k = 0.043;p = non-significant) where apoB showed a better

Non-HDL versus apoB in identification of dyslipidemic phenotypes 33

Table 2 Pearson’s correlation of IMT with apoB andnon-HDLc in the whole cohort and subgroups

Non-HDLc ApoB

r p r p

Whole cohort 0.560 0.01 0.623 0.01

Hypertriglyceridemic subgroupHtgHapob 0.619 0.005 0.776 0.0001HtgNapob — — — —HtgHnhdl 0.634 0.007 0.649 0.008HtgNnhdl 0.032 NS 0.384 0.01

Normotriglyceridemic subgroupNtgNapob 0.271 NS 0.295 NSNtgHapob 0.361 0.01 0.658 0.005NtgNnhdl 0.256 NS 0.321 NSNtgHnhdl 0.277 0.05 0.526 0.03

r is the Pearson’s correlation coefficient; p value indicatessignificant correlation; NS is non-significant.

agreement with mean IMT than non-HDLc. In fact inthe normotriglyceridemic subgroup; NtgHapob hada better concordance than NtgHnonhdl which had apoor concordance (Table 3).

The correlation between apoB and non-HDLc wasstrong in the cohort as a whole (r = 0.60, p < 0.01)and better in the hypertriglyceridemic subgroup(r = 0.67, p < 0.01) than in the normotriglyceri-demic subgroup (r = 0.30, p < 0.05) while the con-cordance between the two was moderate in the inhypertriglyceridemic subgroup and slight in the nor-motriglyceridemic subgroup. In fact the majority ofthe subjects classified as normolipidemic on thebasis of non-HDLc and triglycerides (n = 60) hadincreased apoB (n = 45).

Multistep linear regression analysis using IMT asthe dependent variable revealed that apoB was themajor contributor towards the variance of IMT in thewhole cohort and the subgroups as well, as com-pared to non-HDLc (Table 4).

Table 3 Concordance analysis between carotid IMT and va

k a S.E. of k a

Hypertriglyceridemic subgroupHtgHapob 0.598 0.087HtgHnhdl 0.481 0.091HtgNnhdl 0.140 0.075

Normotriglyceridemic subgroupNtgNapob 0.217 0.066NtgHapob 0.387 0.097NtgHnhdl 0.120 0.093NtgNnhdl 0.043 0.078

a The k statistic, on a scale from 0 to 1, reflects the degree of ab The levels of agreement range from slight (k 0.0—0.20), fair (0.21

(0.81—1.00), according to Landis and Koch [22].

Discussion

The present study reveals that [1] hyperapoB is themost prevalent lipoproteic abnormality [2]. BothApoB and non-HDLc are good predictors of carotidIMT, but apoB is a better predictor in the diabeticcohort as a whole as well as the dyslipidemic sub-groups [3]. Both apoB and non-HDLc are more or lessequivalent markers of atherosclerotic risk in hyper-triglyceridemic subjects, in normotriglyceridemicsubjects; apoB is a better marker of subjects at riskthan non-HDLc.

The result of the present study shows a majordifference regarding the number of atherogenicspecies determined, on the basis of a differentclassification resulting in a major difference in diag-nostic and therapeutic outcome. ApoB is present inlipoproteins that are potentially atherogenic andabsent from those that are antiatherogenic.Because each VLDL, IDL and LDL particle containsonly a single apoB molecule [23], measuring plasmaapoB is roughly equivalent to quantifying the num-ber of apoB containing lipoprotein particles. Exceptin the most severe hypertriglyceridemia, >90% ofthe apoB containing lipoproteins are LDL particles[24]. Cardiovascular risk increases six-fold [25]when increased number of small dense LDL particlesis present; this is the combination that is common insubjects with CHD [26]. Measurement of apoB is thekey because particle for particle, the smaller, den-ser LDL appears to be more atherogenic than thelarge buoyant LDL particles [27]. Many studies havereported that hyperapoB is the most prevalentabnormality in subjects with CAD [28—30] and dia-betes [31]. They further elaborated that, hyperapoB(with or without elevated plasma cholesterol ortriglyceride concentrations) characterized almosthalf of the men who developed an ischemic heartevent.

rious subgroups

t p Agreementb

5.993 0.0001 Moderate4.824 0.0001 Moderate2.510 0.012 Slight

2.863 0.001 Fair3.241 0.0001 Slight1.401 NS Slight0.569 NS Slight

greement between two variables.—0.40), moderate (0.41—0.60), good (0.61—0.80) and very good

34 J. Ahmad et al.

Table 4 Multistep linear regression comparing the contribution of Apolipoprotein B and non-HDL cholesterol to thevariance of carotid IMT

R 2 R2 change b-Coefficient t Significance

Whole cohortApoB 0.378 0.378 0.002 13.980 0.0001Non-HDLc 0.030 0.0017 3.084 0.003

NtgHapobApoB 0.433 0.433 0.0018 6.060 0.0001Non-HDLc 0.018 0.0007 2.206 0.03

HtgHapobApoB 0.502 0.502 0.0014 5.067 0.0001Non-HDLca — — — —

NtgHnhdlApoB 0.327 0.327 0.0016 3.654 0.003Non-HDLc 0.028 0.0019 3.868 0.003

HtgHnhdlApoB 0.421 0.421 0.0011 3.192 0.007Non-HDLc 0.254 0.0013 3.194 0.007

b denotes regression coefficient; R2 change is the change in R2 after each independent variable was entered into the model. Only thevariables significantly contributing to the model are shown.a No significant contribution to the variance of carotid IMT.

In the present study, non-HDLc seems to be a goodalternative to apoB in hypertriglyceridemicpatients, since a strong correlation and good con-cordance were found between both parameters inthe various classes of patients. Nevertheless, thecorrelation was weaker in the normotriglyceridemicgroup. It has previously [32] been reported thatthere is high concordance of apoB with non-HDLcas compared to LDLc, although more than one-thirdof all subjects had discordant levels. This consider-able difference is based on the fact that correlationis not a precise measure of the overall relationbetween two parameters, as it does not conveyinformation to the dispersion of values at any pointin the relation. Therefore, our study raises doubtover the decision to consider non-HDLc as a surro-gate for the measurement of apoB.

Further, we found out that apoB was a betterpredictor of IMT and hence, atherosclerotic risk inthe diabetic cohort as a whole as well as the sub-groups. It was also seen that non-HDLc and apoBwere equivalent markers of atherosclerotic risk inthe hypertriglyceridemic subgroup while apoB alonewas useful in normotriglyceridemic subgroup asassessed by carotid IMT. Almost one-third of thenormotriglyceridemic patients, who account formost of the subjects with fair glycemic control[33,34], were misclassified into a low risk categorywhen non-HDLc level was used as the parameter.Similar findings have been reported previously thathave revealed that hyperapoB identifies high riskdyslipidemic phenotypes not identified by otheratherogenic indices [31,35]. Intervention studies

comparing apoB and non-HDLc have also shown apoBas a better predictor of IMT and cardiovascularevents than non-HDLc [13].

Thus, measurement of apoB facilitates the iden-tification of a subgroup of apparently normolipi-demic and hypertriglyceridemic patients who hadhyperapoB, and thus stand increased cardiovascularrisk [36]. Interestingly, these patients showed a highproportion of low HDLc. Slightly raised triglyceride,low HDLc and high apoB are metabolically intercon-nected. ApoB is required for the hepatic secretion ofVLDL, and remains linked to the particle until itsclearance from the circulation as IDL or LDLc [34].When the catabolism of triglyceride-rich lipopro-teins is impaired, as happens in type 2 diabetes,several lipoproteic disorders associated with hyper-triglyceridemia occur, such as increased VLDL rem-nants, low HDLc and preponderance of small denseLDL particles [37]. Hypertriglyceridemia and lowHDLc are detected by routine biochemical methods,whereas increased VLDL remnants and the propor-tion of small dense LDL particles are not. The mea-surement of plasma apoB, therefore, may be usefulin identifying these phenotypes [38]. Because thereis only one apoB molecule per atherogenic particle[31], measuring plasma apoB is roughly equivalentto quantifying the number of apoB containing lipo-protein particles. Thus, for a given cholesterol con-centration, a high concentration of apoB reflects thepresence of an elevated number of apoB containinglipoprotein particles [23].

The measurement of apoB therefore might behelpful in the identification of a subgroup of appar-

Non-HDL versus apoB in identification of dyslipidemic phenotypes 35

ently normolipidemic patients who have hyperapoB,and thus stand increased cardiovascular risk.

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