© 1995 American Heart Association, Inc.
Articles |
Segregation Analysis of HDL3-C Levels in Families of Patients Undergoing Coronary Arteriography at an Early Age
From the Department of Epidemiology (J.C., T.H.B., J.X.), The Johns Hopkins School of Hygiene and Public Health, and the Departments of Medicine (J.C.) and Pediatrics (P.O.K.), The Johns Hopkins School of Medicine, and the Division of Human Genetics (V.L.P.), University of Maryland, Baltimore, Md.
Correspondence to Josef Coresh, MD, PhD, Welch Center for Prevention, Epidemiology and Clinical Research, 2024 E Monument, Baltimore, MD 21205-2223. E-mail coresh@welchlink.welch.jhu.edu.
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Abstract HDL cholesterol (HDL-C) level is a risk factor for coronary heart disease. Studies have shown a strong genetic influence on HDL-C levels in addition to environmental influences, but no definite major gene control has been demonstrated. Since HDL subfractions may better reflect the actions of distinct metabolic alterations than total HDL, we tested the hypothesis that the amount of cholesterol in the denser HDL3 subfraction (HDL3-C) is under the control of a major gene. The study population included 676 family members of 116 probands who underwent coronary arteriography at an early age (men
50 and women 60 years). HDL3-C level was
measured by using enzymatic methods after preparative
ultracentrifugation at a density of 1.125 g/mL.
HDL3-C was adjusted for age, gender, alcohol consumption,
and smoking, which combined accounted for 3% of its variance.
Segregation analysis was conducted on adjusted
HDL3-C by using regressive models. The familial
correlations for HDL3-C levels were spouse .03±.08,
parent-offspring .14±.05, and sibling .24±.05. The data strongly
supported a codominant mendelian model, with the common allele
coding for lower HDL3-C levels and the rarer allele
(frequency, 25%) coding for higher HDL3-C levels. This
major gene explained 34% of the variation in HDL3-C levels
and 9% of the variation in total HDL-C levels. These results suggest
that HDL3-C levels exhibit clearer genetic control than
total HDL-C and may therefore be a useful target for further genetic
studies.
Key Words: HDL3 • HDL • segregation analysis • major gene • population genetics
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Introduction |
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Strong evidence suggests that HDL cholesterol (HDL-C) has an inverse association with the risk of coronary heart disease.1 2 HDL particles are heterogeneous in their composition and size,3 and a great deal of attention has been devoted to studying the metabolism, association with environmental factors, and implications for coronary risk of the different HDL subfractions.4 Only a few studies have examined genetic factors influencing HDL subfractions, and none have specifically modeled major gene control. This article presents a segregation analysis to test the hypothesis that among 676 participants of a family study HDL3-C levels are under the control of a major gene, ie, a gene with common genetic variants (alleles) that code for substantially different levels of HDL3-C. Once segregation analysis establishes the presence of a major gene, the identity of this gene and the mutation or mutations leading to the various alleles remain to be established by molecular studies.
Lipoprotein levels in general, and HDL-C levels in particular, show strong familial correlations that are compatible with a high level of genetic control.5 The higher correlations among siblings and parent-offspring pairs compared with spouses suggest a genetic basis for this aggregation. Although segregation analysis allows for a more detailed modeling of the sources of familial aggregation and testing for the presence of a major gene,6 segregation analyses of total HDL-C level have yielded mixed results. Hasstedt et al7 studied a single large pedigree ascertained through multiple cases of early myocardial infarction and found no evidence of a major locus determining HDL-C levels. Borecki et al8 found evidence of a major gene controlling abnormally low levels of HDL-C in 14 families ascertained through hypoalphalipoproteinemic probands. However, the mode of transmission could not be determined. By using data from the Lipid Research Clinics Program Family Study, Bucher et al9 found evidence for a factor that was transmitted from parent to offspring, but the transmission of this factor was not mendelian. Amos et al10 found evidence for a major gene determining HDL-C levels in a single large high-risk pedigree from the Bogalusa Heart Study. In a previous analysis of the present study population, Prenger et al11 found no evidence for major gene control of HDL-C levels.
Most investigators have attempted to resolve the complicated genetic control of total HDL-C by examining concentrations of apoA-I, which is the major protein on HDL particles. Investigations of apoA-I levels have had mixed results as well, but several reports,7 10 12 13 including one from this study population,11 provide evidence for a major gene coding for high apoA-I levels. Other reports suggest that the effect of more than one major gene on apoA-I levels may be discernible in baboons14 as well as humans.13 ApoA-I is the direct product of a single gene, APOA1. However, once secreted, apoA-I is distributed across the full range of HDL particles and is found to a lesser extent in other lipoproteins as well. Therefore, apoA-I metabolism is complex and is likely to be influenced by a large number of factors, both genetic and environmental.
Another approach to obtaining a clearer understanding of the genetic determination of HDL-C levels is to restrict attention to a more homogeneous population of HDL particles that may exhibit simpler metabolic control. HDL particles have been separated by ultracentrifugation into the denser HDL3 particles (d>1.125 g/mL) and the less dense HDL2 particles (d=1.06 to 1.125 g/mL).3 Epidemiological studies have yielded mixed results as to whether coronary heart disease risk is largely determined by HDL3-C, HDL2-C, or both.15 16 Environmental factors such as exercise, alcohol, and hormone replacement therapy may affect HDL2-C to a greater extent than they influence HDL3-C.17 18 19 This suggests that in a study population with a wide range of environmental conditions, genetic influences on HDL3-C levels may be easier to detect than influences of a similar magnitude on HDL2-C levels, which would be diluted by environmental influences.
Gradient gel electrophoresis has allowed differentiation of three
subclasses within HDL3 (HDL3a,
HDL3b, and HDL3c) and two subclasses
within HDL2 (HDL2a and
HDL2b).20 These subclasses are also
divided on the basis of their apoA-I and apoA-II content, with
HDL2b and HDL3c containing only apoA-I
and HDL2a and HDL3b containing both
apoA-I and apoA-II.21 22 Williams et al23
have studied the familial correlations of HDL subclasses as determined
by gradient gel electrophoresis in 150 offspring in 47 nuclear
families. They show that the familial correlations varied across the
range of HDL particle sizes. Familial correlations were highest for
particle diameters 
8 nm in the HDL3 range and 10.5 nm
in the HDL2 range. Particles of intermediate sizes
showed lower familial correlations. These data provide additional
evidence for the argument that levels of a subfraction of HDL may
exhibit clearer evidence of genetic control than total HDL-C
levels.
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Methods |
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Study Population
The target study population was first-degree relatives of probands in the Johns Hopkins Coronary Artery Disease Study, which included 99 men aged 50 years or less and 104 women aged 60 years or less who underwent diagnostic coronary arteriography at The Johns Hopkins Hospital from April 1985 through April 1988. Of these, 176 patients (87%) were located and invited to participate in a family study of risk factors for heart disease; 152 (86%) of these agreed to participate. As of January 1991, data collection was complete for the families of 116 of these individuals. The study population included 558 (82%) of the 678 living first-degree relatives and 96 (94%) of the 102 current spouses of the index cases. In addition, 65 other family members of the index cases (grandchildren, stepchildren, and wives and children of first-degree relatives) were included in the study population. HDL3-C data were unavailable for 18.8% of the individuals. This was higher than for other lipoprotein measurements because measurement of HDL subfractions required precipitation followed by ultracentrifugation as described below. Questionnaire data were unavailable for another 4%, resulting in a final sample size of 676 individuals in 116 families with both HDL3-C and questionnaire data. The median number of individuals per family with complete data was 5 (5.8±2.7, mean±SD; range, 1 through 16). All subjects gave their informed consent to participate in the study, and the study was approved by the Johns Hopkins Joint Committee on Clinical Investigations.
Data Collection Protocols
Subjects enrolled in the study were instructed to fast for at
least 12 hours before blood was drawn. Blood was collected into tubes
containing EDTA (final concentration, 1.5 mg/mL blood). Age, gender,
cigarette smoking, alcohol consumption, medication use, and dietary
information were obtained by an interviewer-administered questionnaire.
Height and weight were measured, and body mass index (weight in
kilograms divided by height in meters squared) was calculated. Data
were collected in the Lipid Research Clinic for 41% of the subjects,
and in the subjects' homes for 39%. For 20% of the subjects direct
contact was not possible, and a telephone interview was administered. A
blood sample was drawn from these individuals at a local hospital,
processed according to the study protocol, and shipped on ice by
express mail to the Lipid Laboratory.
Measurement of Lipid and Lipoprotein Levels
The plasma levels of total cholesterol,
triglycerides, and the concentration of VLDL
cholesterol, LDL cholesterol, and HDL-C were
determined by using the methods of the Lipid Research Clinics
Program24 as modified by Kwiterovich et al25
and described previously.26 Total HDL-C was determined
after precipitation of the apoB-containing lipoproteins with heparin
and manganese chloride. Four milliliters of heparin–manganese chloride
supernate was adjusted to a density of 1.125 g/mL27 and
centrifuged at 105 000g for 40 hours. The bottom
fraction containing HDL3-C was recovered by tube slicing,
and its cholesterol concentration was determined by using
enzymatic methods.25 HDL2-C
concentration was calculated as the difference between total HDL-C and
HDL3-C.
HDL3-C measurements were not available for 18.8% of the study participants who had blood drawn. The most common reason for this was incomplete precipitation of apoB-containing lipoproteins, which occurred in 11.1% of samples and prevented ultracentrifugation. Measurement of the HDL subfractions was also impossible if an insufficient amount of plasma remained after the plasma was divided into aliquots for the measurement of LDL and VLDL by ultracentrifugation; this occurred in 4.6% of the samples. Incomplete yield resulted in missing data only 0.7% of the time; for 1.7% of the samples, the reason was unknown. Incomplete precipitation of the apoB-containing lipoproteins typically occurred in samples with high serum triglyceride levels. This was confirmed by a stepwise logistic regression that identified higher plasma triglyceride level as the strongest predictor of missing HDL3-C data. In the same model lower HDL and higher apoA-I levels were significantly associated with increased risk of missing data. In individuals with missing data we attempted to explore the effect of the missing values by using linear regression to impute HDL3-C. The linear regression model used included total HDL-C, plasma apoA-I and apoB, log of triglycerides, sex, and diabetes (R2=.33). The segregation analysis was then repeated with all study participants by using both measured and imputed values.
Statistical Analyses
Multiple linear regression was used to examine the association
between HDL3-C and covariates. HDL3-C levels
were adjusted for age, age2, sex, age*sex,
age2*sex, alcohol consumption, and current cigarette
smoking. Age was centered by subtracting 45 years from the age
variable. The residuals from the regression were scaled back by
adding 33.6 mg/dL (0.869 mmol/L), the mean HDL3-C level of
the total study population. Familial correlations were calculated by
using the FCOR program as implemented in
SAGE release 2.1.28 The role of genetic and
environmental influences in determining interindividual variability in
HDL3-C levels was examined by fitting a series of class D
regressive models as proposed by Bonney29 and implemented
in SAGE release 2.1.28 These models assume
that variation among individuals for a quantitative trait is the result
of a major gene effect and residual variation that may reflect both
familial correlations and individual variation. The class D models
presented in this article assume that, given a common
parentage, additional sibling effects are equal among all sibs. The
parent-offspring correlation was held equal to the sibling correlation
in this study (ie, 
po=ss) because these
models have been shown to be mathematically and numerically equivalent
to the conventional mixed model of inheritance in nuclear
families.30 This parent-offspring correlation provides an
estimate of the polygenic heritability, ie,
h2=2*po*
2/T< ARRANGE="STAGGER">2,
where T< ARRANGE="STAGGER">2 is the total variance, and
2 is the variance conditional on the major
"type." Hypotheses were tested by fitting a general model and
comparing its likelihood to that of reduced models
representing specific models of inheritance.
The general model used allows for two alleles at a single locus
(denoted L and H) resulting in three "types" of individuals (LL,
HL, and HH), termed "ousiotypes" by Cannings et
al.31 The mean HDL3-C level associated with
each type is denoted µLL,
µHL, or µHH, respectively. The
within-type variance, 2, is assumed to be equal
among all three types. The frequency of allele L is denoted
qL; 1-qL denotes the frequency of the
alternative allele H. The distribution of types in the population
is assumed to be in Hardy-Weinberg equilibrium. Individuals of type LL,
HL, and HH are assumed to transmit the L allele with probabilities
LL, HL, and
HH, and the H allele with probabilities
(1-LL), (1-HL), and
(1-HH), respectively. These transmission probabilities
are used to calculate the probability of all three types for each
individual whose parents are in the pedigree. In addition, the
parameters sp,
po, and ss denote the spouse,
parent-offspring, and sibling-sibling correlations, respectively.
Several initial estimates were used to guard against the presence of
multiple maxima in the likelihood surface.
The likelihood of a restricted model was compared with the general
model by using the likelihood-ratio test. Under the null hypothesis,
the difference between the -2ln(L) of the restricted and general model
approximates a 
2 distribution with degrees of
freedom equal to the difference in the number of parameters
estimated in the two models. Models that do not fit the data as well as
the general model will have a large 2 and a small
probability value. Pleiotropic effects of this major gene on other
lipoprotein and apolipoprotein characteristics were described by using
genotypic probability estimators as described by Hasstedt and
Moll.32
Correction for ascertainment was not made in this study for three reasons. First, ascertainment was not based on HDL3-C levels directly; second, the HDL3-C levels of probands did not markedly differ from those of their relatives; and third, the method of case identification in this study should allow for inferences to the larger population of families of patients suspected of having early coronary artery disease. No normalizing transformation was performed since evaluation of the environmental model with nontransmitted "types" reduces the possibility that skewness alone will lead to false detection of a major gene33 without incurring the loss of power associated with normalizing transformations.34 In addition, the analysis of untransformed data leads to results that are easier to interpret.
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Results |
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Study Population
The characteristics of the study population are shown in Table 1
. The mean age was 42.8 years with a unimodal
distribution but a wide range (4 through 88 years). On average, the
population did not have markedly abnormal lipoprotein levels, with a
mean LDL cholesterol of 116 mg/dL (3.00 mmol/L) and a mean
HDL-C of 57 mg/dL (1.47 mmol/L). However, as the large SDs indicate,
the distribution of these variables was relatively wide. The mean
HDL3-C level was within the normal range at 34 mg/dL (0.879
mmol/L).
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Familial Correlations
Table 2 shows the pattern of familial correlations
for HDL3-C as well as total HDL, apoA-I, and
HDL2-C. Both HDL3-C and apoA-I display a
correlation pattern consistent with a strong genetic effect,
ie, a low spouse (mother-father) correlation and higher
parent-offspring and sibling correlations. In contrast,
HDL2-C and total HDL-C levels show higher spouse and
lower parent-offspring correlations, indicating a stronger influence of
environment on these measures.
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HDL3-C Adjustment
HDL3-C levels were only weakly associated with most
covariates measured. Alcohol consumption was the only variable that
was significantly associated with higher HDL3-C levels.
This was in marked contrast to the stronger association of
HDL2-C levels with gender, alcohol consumption, and
physical activity (r2=.14, data not
shown). Table 3 shows the regression model that was used
to adjust HDL3-C levels. Age and gender as well as their
interaction and quadratic terms were used to avoid any possibility of
residual confounding by these important subject characteristics. For
the same reason, smoking was retained in the model despite having only
borderline significance (P=.07). A histogram of adjusted
HDL3-C levels is shown in the Figure.
Adjusted HDL3-C levels were mildly skewed toward higher
values (coefficient of skewness, .40; P<.05) and were
somewhat more concentrated at the center of the distribution (kurtosis,
0.62; P<.05).
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Segregation Analysis
Table 4 shows the parameter estimates
and likelihood of five models of inheritance that were fit to the data.
Model 2, which allows for familial correlations, fit the data much
better than model 1, in which all familial correlations were zero. The
pattern of familial correlation in model 2 showed an insignificant
spouse correlation (-.02; 95% confidence interval, -.18 to .14). The
residual sibling correlation, ss=.15, was similar to the
parent-offspring correlation, po=.16. Therefore all
subsequent models assumed the parent-offspring and sibling correlations
to be equal. Model 2, including familial correlations but no major gene
effect (only one mean), did not fit the data nearly as well as the
general model (model 5) and had three means, arbitrary transmission
parameters, and residual familial correlations
(2=30.6 with 6 df,
P<.001). A codominant mendelian model (model 3), on the
other hand, was the only model that fit the data as well as the general
model (2=1.4 with 3 df,
P=.71). This model is graphically described in the Figure
.
It has an L allele frequency, qL, of 75%, which
implies that 56% (75%*75%) of the subjects have the LL
genotype and a mean HDL3-C of 30.5 mg/dL (0.879
mmol/L); 38% (2*75%*25%) have the HL genotype and a mean
HDL3-C of 36.6 mg/dL (0.946 mmol/L); and the last 6%
(25%*25%) of the subjects have the HH genotype with mean
HDL3-C levels of 49.3 mg/dL (1.27 mmol/L). The major gene
effect detected here reduces the residual unexplained variance from
65.2 mg2/dL2 to 43.2
mg2/dL2, thus explaining 34% of the variance
in adjusted HDL3-C levels. Further tests of the
transmission parameters allow for rejection of the
environmental model (model 4, 2=20 with 3
df, P<.0002), which allows for familial
correlations as well as three arbitrary means but no transmission of
the different types from parents to offspring. Once the major gene is
accounted for (model 3), the residual parent-offspring correlation is
markedly decreased to .06 (95% confidence interval, .00 to .12). This
suggests that this major gene accounts for the majority of the familial
correlations in HDL3-C levels.
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Neither a dominant nor a recessive model of transmission fit the data
as well as the codominant model 3 (-2lnL=4690.6 and 4689.6,
respectively, P<.01). In addition, a model with equal
transmission parameters that were not held equal to
qL was rejected when compared with the general model
(2=13.7 with 2 df,
P<.001). All the segregation models discussed were also run
allowing for unequal parent-offspring and sibling correlations and
yielded identical inferences favoring the major gene model.
Because HDL3-C levels were missing for a substantial
proportion of the subjects, we assessed whether the major gene effect
detected was caused by these missing data. After missing
HDL3-C values were imputed by using linear regression
analysis and adjusted as described in "Methods," the
segregation analysis was repeated using all subjects. In this
analysis the mendelian model gave a good fit to the data
compared with the general model (2=4.8 with
3 df, P>.1), while the
environmental model yielded a substantially poorer fit
(2=9.1 with 3 df,
P=.02). The main effect of adding the imputed data appeared
in the familial correlations. In the mendelian model the spouse
correlation remained insignificant, but the parent-offspring
correlation was .05, and the residual sibling correlation was larger at
.22.
Pleiotropic Effects
Table 5 shows the effect of this major gene on
other lipoprotein and apolipoprotein characteristics. The major gene
accounts for 32.7% of the variation in unadjusted HDL3-C
levels and 9.3% of the variation in HDL-C levels. This is mainly due
to the fact that individuals with the HH genotype had a mean
HDL-C level of 72.1 mg/dL (1.86 mmol/L), 13.2 mg/dL (0.341 mmol/L)
higher than individuals with an HL genotype. This major gene
also explains 7.5% of the variation in distribution of HDL particle
size, as measured by the percentage of the total HDL-C that was in the
HDL3-C subfraction. This suggests that the gene accounts
for both a higher level of HDL3-C and a distribution of HDL
particles that is predominantly denser (d>1.125 g/mL). As
expected, this putative gene also affected apoA-I levels but accounted
for only 4.7% of the variance in apoA-I levels. This was mainly due to
a very high predicted mean apoA-I level of 185 mg/dL (6.60 µmol/L)
among individuals with the HH genotype.
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Discussion |
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The data from this family study provide strong evidence for a codominant major locus controlling HDL3-C levels. These findings are the first report, to our knowledge, of a major gene effect for a specific HDL subclass; they suggest that genetic analysis of HDL subclasses may provide a clearer picture than analysis of total HDL-C. Analysis of the pleiotropic effects of this gene indicates that homozygous carriers of the H allele have substantially elevated apoA-I levels.
Evidence exists for a major locus resulting in elevated apoA-I levels. Prenger et al11 found evidence for a dominant major gene influencing apoA-I levels in a subset of 390 members of the present study population. The major gene model for apoA-I in that report predicted 80% of the subjects to have normal apoA-I levels (mean, 144 mg/dL [5.14 µmol/L]) and the other 20% to have a genotype coding for higher apoA-I levels (mean, 197 mg/dL [7.03 µmol/L]). The apoA-I locus explained over 37% of the variation in apoA-I levels compared with only 4.7% of the variation explained by the locus reported here. This suggests the two loci may be different. The latter hypothesis is consistent with a report by Xu et al13 that found evidence for a second locus controlling apoA-I levels among Mormon families. Preliminary results from a similar analysis on the present study population indicate evidence for a second locus as well (J.X., unpublished data, 1995). However, it is unclear whether the major gene for elevated HDL3-C levels described here is the same as the major gene postulated to elevate apoA-I levels. Regardless of the answer to this question, the present results have several implications about the genes influencing HDL metabolism.
The major gene locus described here resulted in increased levels of HDL3-C but not HDL2-C. In fact, a segregation analysis of HDL2-C (not shown) found evidence for nonnormality; this was indicated by multiple means fitting better than one mean, but an environmental model fit the data substantially better than a mendelian model. Our results suggest that the gene's action must influence the metabolism of denser HDL particles. HDL3-C levels can be increased by increased synthesis or decreased catabolism of HDL3 particles. The current understanding is that HDL3-C particles are produced either as nascent HDL particles or through the lipolysis of HDL2 by hepatic triglyceride lipase. Catabolism of HDL3-C particles is either by removal from the circulation or metabolism to less dense, more cholesterol ester–rich lipoproteins by lecithin:cholesterol acyltransferase.21 Studies of HDL metabolism indicate that the rate of HDL catabolism is highly variable among individuals and is correlated with HDL levels.35 This suggests that the higher levels of HDL3-C among HH genotype individuals may be due to increased activity of hepatic triglyceride lipase or decreased activity of lecithin:cholesterol acyltransferase. In addition, the flux of free cholesterol from the apoB-containing lipoproteins to apoA-containing lipoproteins may be important in determining the rate of HDL maturation.36 Thus, lipoprotein lipase, which is thought to play a role in HDL metabolism through its effect on lipolysis of apoB-containing lipoproteins, may also be a candidate for the major gene described here.
The major gene model presented has a complication that is
commonly found in genetic models of complex traits. Despite the fact
that the mean HDL3-C level in HH individuals is 62% higher
than the corresponding mean for LL individuals, the HDL3-C
distributions in the three genotypes (Figure) overlap
substantially. This overlap is due to substantial residual variation in
HDL3-C within each genotype as a result of
environmental influences and genetic factors other than the major gene.
The presence of this overlap limits the certainty with which the
genotype of specific individuals can be determined by the
genetic model presented. Such a genetic model with overlapping
distributions is a poor candidate for a genome-wide search for linkage.
However, studies of candidate genes have been productive even when
the genetic effect is much smaller.
The design of the current study resulted in several limitations. The ascertainment of the study population allowed for inferences to families of probands undergoing diagnostic cardiac catheterization. However, the frequency of the HDL3-C–elevating allele estimated in this study cannot be directly generalized to the population at large. Measurement of HDL3-C by ultracentrifugation did not allow for estimation of HDL3 subfractions. Therefore, it is unknown whether some or all of the HDL3 subfractions are elevated by the major gene described. Clarifying this point is important in view of evidence that the two major HDL3 subfractions, HDL3a and HDL3b, have markedly different correlations with coronary heart disease risk factors37 and associations with coronary disease38 39 40 in cross-sectional studies. It cannot be assumed that individuals carrying the allele for higher HDL3-C levels will have a lower risk of coronary disease. The high rate of incomplete precipitation of apoB-containing lipoproteins that caused missing HDL3-C values for 11% of the sample is a concern. These missing values led to an underrepresentation in the final study population of individuals with high triglyceride and low HDL-C levels. However, the fact that the main result of the present study persisted even with the imputation of HDL3-C values for these individuals, which would certainly have introduced more noise into the data, is reassuring. Whether the action of this major gene is modified by other genes or environmental factors (eg, age, sex, or diet) is unclear, but the presence of such interactions is entirely plausible. While it is possible to examine some of these issues by using statistical methods alone, characterization of the molecular defect responsible for the observed effect will greatly increase our understanding of such interactions.
The major gene described suggests that genetic influences on HDL-C may be mediated through genes acting preferentially on specific HDL subfractions. These results may provide guidance for further study of the molecular basis for elevated levels of HDL-C. Linkage studies with hepatic lipase, lecithin:cholesterol acyltransferase, lipoprotein lipase, and other candidate genes for HDL3-C should provide promising avenues for understanding the molecular basis for the results of this investigation.
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Acknowledgments |
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This work was supported by the following grants from the National Institutes of Health: HL 31497-08; I-P50-HL 47212-03 (Specialized Center of Research in Arteriosclerosis); Cardiovascular Epidemiology Institutional Training grant No. 5T32 HL07024; outpatient Clinical Research grant No. 5M01 RR00722; and RR 00035 (for computational assistance). We thank Hazel Smith for patient recruitment and Jeff Jenkins for data management.
Received December 28, 1994; accepted June 8, 1995.
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