Original Contributions |
From the Division of Nutrition, Centers for Disease Control and Prevention, Atlanta, Ga (D.S.F.); the Department of Biochemistry, North Carolina State University, Raleigh (J.D.O., E.J.J.); the Milwaukee Veterans Administration Medical Center, Milwaukee, Wis (J.J.B.); and St. Luke's Hospital, Milwaukee, Wis (A.J.A., J.A.W.).
Correspondence to David S. Freedman, CDC MSK26, 4770 Buford Hwy, Atlanta, GA 30341-3724. E-mail Dxf1{at}cdc.gov
| Abstract |
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Key Words: nuclear magnetic resonance spectroscopy coronary disease angiography lipoproteins lipoprotein subfractions
| Introduction |
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Although lipoprotein subclasses have been quantified by analytical and density gradient ultracentrifugation, GGE, and chromatography,8 10 11 12 13 the time-consuming and labor-intensive nature of these methods has limited their widespread use. Nevertheless, several cross-sectional14 15 16 17 18 and cohort19 20 21 studies have found that normocholesterolemic persons with high levels of small, dense LDL particles are at increased risk for CHD. Furthermore, the protective effect of HDL-C has been most consistently observed for the larger HDL2 (or HDL2b) subfraction,9 22 and some evidence suggests that levels of small HDL particles (HDL3b and HDL3c) may be positively related to the severity of CAD.12 23 24
We have developed a new procedure for quantifying plasma levels of lipoprotein subclasses by proton NMR spectroscopy.25 26 This method, which simultaneously provides the concentrations of VLDL, LDL, and HDL subspecies, does not require physical fractionation of the plasma and results in rapid and reproducible measurements. Furthermore, NMR-determined lipoprotein subclasses have been shown to correspond well with those obtained with established methods.26 27 28 The present study examines the relation of NMR-derived levels of lipoprotein subclasses to the severity of arteriographically documented CAD among 158 men.
| Methods |
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400* mg/dL were
also excluded. The 158 men included in the analyses ranged in age from 30 to 84 years (mean, 63 years), and Quetelet Index (weight in kilograms divided by the square of height in meters) was used as a measure of relative weight. Other characteristics, such as diabetes (n=31) or use of diuretics (n=32), were included as covariates in some analyses, but several men had missing information on the history of various medical conditions or use of antihypertensive medications. All analyses were limited to men because only 43 eligible women underwent coronary arteriography during the time frame of the study.
Chemical Analyses of Lipids and Lipoproteins
After a 12-hour fast, blood samples were drawn (prior to
arteriography) into tubes containing EDTA (final EDTA concentration, 1
g/L). After centrifugation at 4°C, the separated
plasma was analyzed for the concentrations of TC and TG by
automated procedures31 in a laboratory that was
standardized (and monitored) by the Centers for Disease Control and
Prevention. HDL-C levels were measured after selective precipitation of
apoB-containing lipoproteins with
heparin/MnCl2,32 and levels
of apoB and apoA-I were measured by rate immunonephelometry on an
automated system (Array, Beckman Instruments), with calibration
materials supplied by the manufacturer. Levels of lipids, lipoproteins,
and apolipoproteins based on these methods are referred to as
"chemical determinations" throughout the text.
NMR Spectroscopy
The basis for NMR analysis of lipoprotein subclasses is
that each lipoprotein particle in plasma within a given diameter range
"broadcasts" a distinctive lipid NMR signal, the intensity of which
is proportional to its bulk lipid mass
concentration.25 27 28 33 The methodology used in
this study to acquire and process the NMR data has been described in
detail26 and consisted of three steps: (1)
acquisition of 250-MHz proton NMR spectra of the plasma specimens (0.5
mL, stored at 4°C for up to 5 days) at 45°C, with a Bruker WM-250
spectrometer; (2) deconvolution of the lipid methyl group signal
envelope appearing in these spectra at
0.8 ppm, yielding the derived
signal amplitudes broadcast by 18 modeled lipoprotein subclasses; and
(3) conversion of these signal amplitudes to lipoprotein subclass
concentrations by using experimentally determined factors that relate
the signal amplitudes of isolated subfraction standards to their
chemically measured cholesterol and TG concentrations.
Levels of chylomicrons and VLDL subclasses are expressed in units of TG
(mg/dL), and those of LDL and HDL subclasses in units of
cholesterol (mg/dL). Close agreement has previously been
demonstrated between NMR- and chemically determined LDL-C
(r=0.91) and HDL-C (r=0.93) levels with this
methodology.26 LDL and HDL subclass distributions
determined by GGE and NMR have also been shown to be closely
related.26
Because detailed information on the exact line shapes and chemical
shifts of the lipid methyl signals of homogeneous subclass
standards was not yet available at the time the NMR data from this
study were acquired and processed (1989 to 1990), the deconvolution
procedure employed 18 digitally shifted reference spectra to simulate
the spectral characteristics of isolated
subclasses.26 To simplify
presentation and analysis of the NMR data, the 18
modeled subclasses were combined into a smaller number (10) of
particle-size groupings; classification was based on recently
determined relations between isolated-subclass chemical shifts and
particle-size estimates from GGE or electron microscopy
measurements.27 28 The 10 lipoprotein subclass
categories used were the following: chylomicrons (diameter >100 nm),
large VLDL and remnants (60 to 100 nm), intermediate VLDL (40 to 60
nm), small VLDL (30 to 40 nm), large LDL (23 to 30
nm), intermediate
LDL (20.5 to 23 nm), small LDL (18 to 20.5 nm), large HDL (10 to 13 nm,
similar to HDL2b), intermediate HDL (8.2 to 10
nm, similar to HDL2a and
HDL3a), and small HDL (7.3 to 8.2 nm, similar to
HDL3b and
HDL3c).
A "particle size index," describing the mass-weighted average size of particles within each lipoprotein class, was calculated by weighting each subclass concentration by a numerical size designation (1 to 4 for VLDL, 1 to 3 for LDL and HDL) with larger values representing larger particle subclasses. For example, a person with an LDL-C level of 124 mg/dL, distributed as 18 mg/dL in small LDL, 56 mg/dL in intermediate LDL, and 50 mg/dL in large LDL, would have an LDL particle size index of 2.26 [(1x18)+(2x56)+ (3x50)÷124], a value slightly above the mean.
Extent of CAD
Coronary arteriograms were evaluated by a radiologist
and cardiologist (without knowledge of risk factor data) to determine
the extent of occlusive disease. Reductions in lumen diameter due to
the most serious stenosis in the left anterior descending,
circumflex, and right coronary arteries were incorporated into
a global occlusion score representing the severity of CAD,
as suggested by Rowe et al.34 We inverted the
scale so that a score of 0 indicates no observed occlusion, and a score
of 300 represents total occlusion of all vessels. The mean
occlusion score was 162 (SD=97), the interquartile range was from 82 to
247, and 11% (n=17) of the men had no detectable occlusive
disease.
Statistical Analyses
Because the distributions of several lipoprotein subclasses were
skewed toward higher values, analyses included the use of
logarithmically transformed values, Spearman correlations, and robust
regression techniques (such as minimizing the absolute rather than the
squared deviations).35 (In general, the exclusion
or downweighting of influential observations generally strengthened the
relation of subclass levels to CAD severity.) After the age-adjusted
associations between the NMR parameters and CAD severity
were examined, linear and logistic regression models focussed on which,
if any, NMR determinations could provide information, beyond that
obtained with chemically determined lipoprotein levels, on CAD
severity. In addition to hypotheses generated from the literature, we
used various stepwise regression procedures (forward selection with a
P value <0.05, maximum R2, and
the Cp statistic)36 to
determine the set of NMR parameters most predictive of
occlusive disease. In all regression models, we used quadratic terms
and natural splines to assess nonlinearity37 and
product terms to assess interactions.
Although CAD severity was modeled primarily as a continuous
variable, some analyses treated disease status as extensive
(occlusion score
200, n=61) versus minimal (occlusion score <100,
n=48). In these analyses, which excluded men with occlusion
scores of 100 to 199, ORs were used to summarize the magnitudes of the
associations with lipoprotein subclass levels (dichotomized at
approximately the median). Some results from these analyses are
presented graphically, with the predicted logits transformed to
probabilities and covariates set to median
values.37 Although data on other characteristics,
such as use of diuretics, were missing for several men, these
adjustments (performed among the men with no missing data) did not
substantially alter the relation of the lipoprotein subclasses to
CAD.
| Results |
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After controlling for the association between CAD severity and age
(rs=0.33), the extent of CAD was most
strongly related to levels of apoB (Spearman partial
[rs] correlation=0.30), but statistically
significantly associations were seen with most of the chemically
determined lipid and lipoprotein levels (Table 2
). Although age-adjusted levels of the
LDL and HDL particle size indices were also inversely related to the
extent of occlusive disease (rs=-0.17 to
-0.19), these associations were not statistically significant after
further adjustment for the chemical determinations.
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Of the individual lipoprotein subclasses, levels of large VLDL, small
LDL, intermediate HDL, and small HDL particles were significantly
associated with CAD severity after adjustment for age (Table 3
). For example, as the number of
diseased vessels increased, the (geometric) mean level of large VLDL
increased from 5 to 12 mg/dL and of small LDL from 10 to 21 mg/dL.
Further adjustment for the chemical determinations (final column)
reduced the magnitude of the association with levels of small LDL by
50%, but other associations remained statistically significant.
Because of the differing associations of the HDL subclasses with CAD
severity (positive with small particles versus inverse with larger
particles), a derived variable (HDLdiff) was
calculated as [(large HDL+intermediate HDL)-small HDL]. Levels of
HDLdiff were strongly related to CAD severity,
and all 7 men with a negative value of HDLdiff
had an (age-adjusted) occlusion score that was equal to or above the
median occlusion score among the other 151 men (data not shown).
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Associations with extensive (versus minimal) disease were then examined
(Table 4
). Two thirds (40/60) of the men
with a level of large VLDL above the median had extensive CAD compared
with 43% of the other men. The resulting OR [(40:20)÷(21:28)]
indicates that men with a high level of this subspecies were 2.7 times
as likely to have extensive disease as were other men. As estimated
from a logistic regression model containing age and various chemical
determinations as covariates, adjusted ORs for large VLDL ranged from
3 to 5 (P<0.05 for each). Adjusted ORs with extensive
CAD were also statistically significant for levels of small HDL (ORs
>3) and HDLdiff (OR=0.3). Furthermore, 22 of the
27 men with high levels of both small HDL and large VLDL had extensive
CAD (versus 9 of the 26 men with low levels of both subclasses),
yielding an adjusted OR of 15. (Levels of small HDL and large VLDL
showed little correlation [rs=-0.05].)
In contrast to these associations with CAD, levels of small LDL-C were
not consistently related to disease after adjustment for lipid
and lipoprotein levels, and an adjusted OR of 0.6 (P>0.05)
was seen for chemically determined levels of HDL-C (final column).
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Several of these associations are shown in the
Figure
, in which the vertical distances
between the roughly parallel lines reflect the additional information
provided by the lipoprotein subclasses in predicting CAD. (Various
interactions between the NMR data and chemical determinations were
examined, and none were found to be statistically significant;
P>0.25 in all cases.) For example, at a TG level of 150
mg/dL (upper right panel), the probability of extensive CAD for a
63-year-old subject was estimated to be either 0.44 or 0.75, depending
on the level of large VLDL particles. In contrast, if the level of
large VLDL was known, the TG level provide little additional
information on CAD severity: the estimated probability of extensive CAD
varied from only 0.71 to 0.82 between the 10th and 90th percentiles of
TG among men with high levels of large VLDL. Furthermore, if
HDLdiff was relatively high (lower right panel),
even men with an HDL-C level <35 mg/dL were not at greatly increased
risk for occlusive disease. Knowledge of each subspecies in the Figure
significantly improved CAD prediction beyond that obtained with the
corresponding chemical determination, whereas if NMR-determined
subclass levels were known, the only chemical determination that was
significantly related to occlusive disease was the LDL-C level.
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The prediction of occlusive disease, treated as a continuous
variable, by various combinations of the chemical and NMR
determinations was then examined (Table 5
). Whereas levels of TC and TG (in
addition to age) accounted for 22% of the variability in the occlusion
score (model 1), information on levels of LDL-C and HDL-C significantly
improved disease prediction, with a multiple
R2 of 0.25 (model 2). (No further
improvements were achieved by adding apolipoprotein levels to model 2.)
Further increases in the multiple R2
(P=0.002) were obtained by using information on levels of
large VLDL and HDLdiff (model 3), and the
predictive ability was similar (R2=0.30,
model 4) if levels of HDL-C and TG were not considered. (None of the
other 11 other NMR parameters, described in Tables 1 through 3![]()
![]()
, further improved disease prediction.) Furthermore, adding
information on diabetes, previous myocardial infarction, and use of
diuretics did not alter the relation of large VLDL and
HDLdiff levels to CAD. Interestingly, although
the improvement in disease prediction obtained by using NMR-determined
subclasses was relatively small
(
R2=0.06, model 3 versus 2), it was
larger than that achieved by using levels of LDL-C and HDL-C rather
than TC (
R2=0.03, model 2 versus 1).
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| Discussion |
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The principal advantage of NMR lipoprotein analysis is the
elimination of the lengthy, labor-intensive step(s) needed to
physically separate the subclasses of interest. Because the lipids in
each lipoprotein subclass broadcast a distinguishable signal with an
intensity proportional to particle concentration and lipid
mass,27 28 quantification proceeds directly from
a short (
1 minute) acquisition time of the proton NMR spectrum of
unfractionated plasma. Rather than arising from differences in chemical
composition, the distinct properties of lipid NMR signals of various
subspecies are based on particle sizedependent differences in
magnetic susceptibility; these differences are induced by the
orientation order of the phospholipids in the shell of lipoprotein
particles that surround the neutral lipid core.33
Because NMR lipoprotein analysis is based on differences in
particle size (specifically, the phospholipid shell diameter), it
cannot distinguish between VLDL particles and chylomicron remnants of
similar size or between LDL and Lp(a) particles; furthermore, IDLs are
included in the quantification of large LDL. However, NMR lipoprotein
analysis can simultaneously quantify VLDL, LDL, and
HDL subclasses and thus provide information that would otherwise be
very difficult and time consuming to obtain.
Despite the differences between NMR and other methods used to quantify
lipoprotein subspecies, studies of split samples have shown close
agreement between LDL and HDL particle sizes measured by NMR and
GGE.26 Several of the cross-sectional findings in
the current study (Table 1
) provide additional evidence concerning the
validity of NMR lipoprotein analysis. In agreement with
previous reports based on GGE or
ultracentrifugation,39 40 41 42 we
found that men with a preponderance of small LDL particles also had
relatively high levels of TG, large VLDL, and small HDL particles,
along with low levels of HDL-C and the LDL-C/apoB ratio. We also found,
as have others,13 43 that there is a relative
excess of small HDL particles among men who are overweight or who have
high TG levels.
Possible differences in the atherogenicity of lipoprotein subspecies have focussed primarily on LDL subclasses. Results of several case-control studies, including two nested within a cohort design,19 20 have suggested that persons with small, dense LDL particles ("pattern B") are more likely to have CAD or its clinical complications.14 15 16 17 18 However, because of the association of pattern B with adverse levels of TG and HDL-C, it is difficult to determine whether the size of LDL particles per se is responsible for the increased risk. We found, as have other investigators,14 15 16 17 that the importance of small LDL particles is substantially reduced if comparisons are made at similar levels of TG and HDL-C. However, some reports have indicated that levels of small LDL may provide some independent information concerning disease risk,18 21 particularly among normotriglyceridemic men.44 Knowledge of the LDL particle-size distribution may also be useful in the choice of lipid-lowering medications.45
Cross-sectional studies that have examined HDL subfractions have
typically found that CAD was most strongly related (inversely) to
levels of the larger HDL2a and
HDL2b subclasses.12 22 24
In further agreement with our results, elevated levels of small HDL
particles have been found among persons with
CAD23 24 46 and among myocardial infarction
survivors.12 Although several cohort
studies20 47 48 49 found that information on levels
of HDL2 and HDL3 did not
improve disease prediction, the laboratory methodology used may be
important, because the proportion of HDL-C in the
HDL2 subfraction has been reported to range from
10%20 to
66%.47
(The coefficient of variation for HDL subfraction determinations is
frequently >10%.49 ) It has also been
suggested13 that levels of
HDL3, as determined by differential
precipitation, are more strongly correlated with levels of
HDL2a and HDL3a than with
smaller HDL particles. Our finding that HDLdiff
is related to CAD severity, independently of the HDL-C level,
emphasizes the importance of considering differences in the
atherogenicity of HDL subspecies when assessing CAD risk.
Because several reports have found that smaller TG-rich lipoproteins may be particularly atherogenic,4 5 50 51 it is interesting that we found levels of large VLDL particles (and/or chylomicron remnants) to be positively related to CAD severity. However, the lack of evidence concerning the atherogenicity of large VLDL subclasses may in part be methodological: no simple analytical procedures are available for VLDL subfractionation. It has been speculated51 52 that large VLDL particles may play a role in the development of CHD through either their enhanced uptake by macrophages or induction of a procoagulant state promoting thrombosis. Because fasting levels of large VLDL (Sf 60 to 400) are also correlated with delayed chylomicron clearance,53 which is related to CAD severity,2 3 the observed association may reflect the atherogenicity of postprandial lipemia.
Several limitations of the current study should be considered. Although coronary arteriography is useful for studying factors associated with atherosclerosis, the cross-sectional design precluded the study of men who died from an initial myocardial infarction and those with asymptomatic disease. Furthermore, lipoprotein (and subclass) levels measured at arteriography may not reflect levels present during lesion development,54 and there can also be substantial misclassification of coronary arteriograms. These biases, however, would be expected to decrease the magnitudes of the associations with both the chemical and the NMR determinations. Several statistical considerations, including our limited ability in this small study to assesses whether the relation of subclass levels to CAD varied by age or level of the corresponding chemical determination, should also be considered. It is also very difficult to select a single "best" regression model when independent variables are correlated, but we found that NMR-determined levels of VLDL and HDL subclasses were consistently included in regression models that fit the data well. It should also be emphasized that the methodology for NMR lipoprotein analysis has evolved considerably since the current study was conducted, and it is now possible to reliably quantify 6 VLDL, 3 LDL, and 5 HDL subclasses as well as IDLs.27 28
Despite these limitations, our results suggest that levels of lipoprotein subfractions provide information on CHD that cannot be obtained with the routine clinical measurement of lipid and lipoprotein levels. Because the current guidelines from the National Cholesterol Education Program have relatively low sensitivity and positive predictive value,7 this additional information may lead to improved diagnostic accuracy. For example, our results suggest that if the HDL size distribution is weighted toward larger particles, an HDL-C level <35 mg/dL may confer little, if any, increased risk; in contrast, a high level of large VLDL particles, irrespective of the TG level, may be of concern. The advantages of lipoprotein subclass analyses through NMR, particularly its rapid and simultaneous measurement of VLDL, LDL, and HDL subspecies, make it feasible to examine the importance of various subspecies in large cohort studies.
| Selected Abbreviations and Acronyms |
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| Acknowledgments |
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Received September 23, 1997; accepted January 13, 1998.
| References |
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