Arteriosclerosis, Thrombosis, and Vascular Biology. 2001;21:971-978
(Arteriosclerosis, Thrombosis, and Vascular Biology. 2001;21:971.)
© 2001 American Heart Association, Inc.
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Atherosclerosis and Lipoproteins |
Genome-Wide Linkage Analysis Reveals Evidence of Multiple Regions That Influence Variation in Plasma Lipid and Apolipoprotein Levels Associated With Risk of Coronary Heart Disease
Kathy L. Klos;
Sharon L. R. Kardia;
Robert E. Ferrell;
Stephen T. Turner;
Eric Boerwinkle;
Charles F. Sing
From the Department of Human Genetics (K.L.K., C.F.S.) and the Department
of Epidemiology (S.L.R.K.), University of Michigan, Ann Arbor; the Department
of Human Genetics (R.E.F.), University of Pittsburgh, Pittsburgh, Pa; the
Division of Hypertension, Department of Medicine, Mayo Clinic (S.T.T.),
Rochester, Minn; and the Human Genetics Center, University of Texas Health
Science Center (E.B.), Houston.
Correspondence to Dr Charles F. Sing, University of Michigan, Department of Human Genetics, 5928 Buhl Building, 1241 E. Catherine St, Ann Arbor, MI 48109-0618. E-mail csing{at}umich.edu
 |
Abstract
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|---|
AbstractResults
of genome-wide linkage analyses to identify
chromosomal regions
that influence interindividual variation
in plasma lipid and
apolipoprotein levels in the Rochester,
Minn, population are reported.
Analyses were conducted for total
cholesterol
(total-C), triglycerides (TGs), high density lipoprotein
cholesterol
(HDL-C), apolipoprotein A-I, apolipoprotein
A-II, apolipoprotein
B, apolipoprotein C-II, apolipoprotein C-III,
apolipoprotein
E, the total-C/HDL-C ratio, and the TG/HDL-C ratio.
Genotypes
were measured for 373 genome-wide marker loci on 1484
individuals
distributed among 232 multigeneration pedigrees sampled
without
regard to health status. LOD scores and estimates of additive
genetic
variance associated with map locations were obtained by using
the
variance-component method of linkage analysis. No evidence
of
linkage with genes influencing variation in age served as a
negative
control. Plasma apolipoprotein E levels and the
apolipoprotein E gene served as
a positive control (LOD score 4.20). Evidence
(LOD score >2.00) was
provided that was suggestive of a gene
or genes on chromosomes 4 and 5
influencing variation in the
apolipoprotein A-II level, on chromosome
12 influencing variation
in the apolipoprotein A-I level, and on
chromosome 17 influencing
variation of total-C/HDL-C. These
analyses provide new information
about genomic regions in
humans that influence interindividual
variation in plasma lipid and
apolipoprotein levels and serve
as a basis for further fine-mapping
studies to identify new
genes involved in lipid
metabolism.
Key Words: genetic linkage apolipoprotein E apolipoprotein A-I apolipoprotein A-II total cholesterol high density lipoproteins
 |
Introduction
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One of the
greatest challenges that the medical and public health
communities face
is to identify and characterize the genes that
influence the risk of
coronary artery disease (CAD). Only a
small fraction of the
genes that are expected to be involved
in determining the risk of CAD
are known. Measures of lipid
metabolism are
well-established intermediate traits that translate
genetic variation
into variation in the risk of CAD. Increased
risk of developing CAD has
been associated with elevated triglyceride
(TG),
1 2 total
cholesterol
(total-C),
3 4 5
and LDL
cholesterol
6 7
levels and with decreased levels of HDL cholesterol
(HDL-C).
6 8 CAD has
also been associated with low levels of plasma apoA-I
and apoA-II and
high levels of apoB and
apoE.
9 10 11 12 13 14
Only a fraction of the genetic variation in intermediate measures
of
lipid metabolism is explained by variation in known
candidate
genes. For example, the total genetic contribution to
variation
in total-C, HDL-C, and other lipid traits is estimated to be
between
40% and
80%.
15 16 However,
single polymorphisms typically explain
only 5% to 15% of that
variation.
16 17 18 19 20
The present
study is part of an effort to find new genes that
influence
the genetic architecture of CAD by carrying out genetic
studies
of intermediate measures of lipid metabolism that
translate
genetic variation into variation in risk of CAD. The genetic
architecture
of a trait is defined by the number of genes, the number
of
alleles per gene and their relative frequencies, and the
gene-gene
and gene-environment interactions that combine to influence
interindividual
variation within a
population.
21 Genome-wide
linkage scans
have the potential for identifying regions of the genome
not
previously recognized as sources of interindividual variation
in
intermediate traits that influence variation in the risk
of
CAD.
22 23 24 25 26
To identify regions of the genome predictive of
interindividual variation in plasma lipid levels for the purpose of
identifying new candidate genes, we have applied a variance
componentbased linkage method to phenotypic data in pedigrees
ascertained without regard to health status. Evidence of the linkage of
marker loci with a gene(s) influencing interindividual variation in
plasma apoE level was observed in the region of chromosome 19
containing the apoE gene. LOD
scores provided suggestive evidence of the linkage of marker loci with
previously unknown genes on chromosomes 4 and 5 influencing apoA-II, on
chromosome 12 influencing apoA-I, and on chromosome 17 influencing the
total-C/HDL-C ratio.
 |
Methods
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Sample and Laboratory Methods
As part of the Rochester Family Heart Study,
multigeneration
pedigrees were ascertained without regard for health
through
households with

2 children enrolled in the primary and
secondary
schools of Rochester, Minn. Sampling details, the clinic
examination
protocol, and baseline characteristics have been described
by
Moll et al
27 and Turner et
al.
28 Marker genotype
data were
obtained for 1484 individuals (779 females and 705 males) of
the
4486 individuals identified with 232 pedigrees (see
Table 1

).
There was an average of 2.94 children per
pedigree. Individuals
were genotyped for 373 highly
polymorphic microsatellite marker
loci located on the 22 human
autosomes. The median distance
between adjacent markers was 8.3 cM
(range 0 to 40.2 cM). Genotyping
was performed by standard methods with
use of an Applied Biosystems/Perkin
Elmer 377 automatic DNA sequencer.
The genotype data were analyzed
for typings
inconsistent with the pedigree structure by use
of the Lange
and Goradia
29 algorithm as
implemented by Ped
Check.
30
Observed discrepancies were evaluated for typing errors
in the
laboratory. Instances that could not be resolved were
treated as
missing data.
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Table 1. Characteristics of 232 Multigeneration Pedigrees
Containing 1484 Individuals From Rochester, Minn., Who Were
Genotyped for the Linkage Analysis
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Plasma total-C and TG levels were measured by standard
enzymatic
methods.31 32 LDL
particles were precipitated with polyethylene glycol 6000, and an
aliquot of the supernatant was used for determination of HDL-C by an
enzymatic method as described by Kaprio et
al.33 Plasma apoA-I, apoA-II,
apoC-II, apoC-III, and apoE were measured by
radioimmunoassay.34 Plasma
apoB was measured by ELISA.33
Complete lipid and apolipoprotein measurements were available for 778
females and 704 males.
Linkage Analysis
The lipid levels were adjusted for gender-specific
age, height, and weight to the third order, as well as body mass index
(BMI), before carrying out the linkage analysis. Marker
relative allele frequencies were estimated as the sample relative
allele frequencies. Genetic map location estimates were taken from
the maps prepared by the Center for Medical Genetics at the Marshfield
Medical Research
Foundation.35 Locations for
markers not contained in the Marshfield map were inferred from their
map locations in the Genetic Location
Database.36
Linkage analyses were conducted by the
variance-components method37
with use of the SOLAR computer program. In this method, a linear mixed
model was fit to the trait data so that the phenotypic variance about
the trait mean is partitioned into a monogenic component
(
2QTL)
representing the contribution of a quantitative trait locus
(QTL) linked to the marker locus, a residual familial component
(
2R) attributable
to familial genetic and shared environmental effects, and a component
(
2E) attributable
to environmental effects unique to the individual. With the assumption
of no recombination between trait and marker loci, the phenotypic
variance-covariance matrix (
) for individuals in a pedigree
may be written as
=
2QTL+II
2R+I
2E,
where
is a matrix of the proportion of alleles shared identical
by descent (IBD) at a point in the genome estimated from the genotypic
data, II is a matrix of the expected proportion of alleles shared
IBD for pairs of relatives, and I is an identity matrix. Multipoint
estimates of IBD were obtained as a weighted average of the IBD at each
individual marker.38 The
estimates of IBD for individual markers were obtained by the computer
program SOLAR37 by using the
relationship information from the 4486 individuals making up the 232
pedigrees and the genotype data for the subset of 1484
individuals who were genotyped for the present study.
Missing genotype values in the subset of 1484 were imputed by
using information from flanking markers before full multipoint
estimation.37
All LOD scores reported below are based on multipoint
analyses. The LOD scores were calculated as the difference
between the maximum of the log10 likelihood of
the full model, including estimates of
2QTL,
2R, and
2E, and the
maximum of the log10 likelihood of the reduced
model in which
2QTL was
constrained to equal 0. Twice the difference between the maximum of the
loge likelihood of these 2 models is a
likelihood ratio test statistic asymptotically distributed as a 1/2:1/2
mixture of a
2 with a point mass at 0 and
1 df. In 3 cases, the linkage
analysis yielded evidence of
1 QTL influencing
interindividual variation in a trait (multipoint LOD >2.00). In these
cases, a second linkage analysis was performed with the
contribution of the first QTL to trait variation fixed in the full and
reduced models.39 All linkage
analyses were carried out in SOLAR with use of the
t distribution function, which
provides a better fit to data that do not meet assumptions of
normality. We have used a LOD score of
3.00 to indicate adequate
evidence of linkage, a LOD threshold of
2.00 as suggestive, and a LOD
score of
1.30 as tentative evidence of
linkage.40
 |
Results
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The phenotypic characteristics of the 1482 individuals
in 232
pedigrees used in these linkage analyses are summarized
in
Table
2

. The average age of males was 36.3 years (range 5.2
to 89.3
years) and of females was 39.0 years (range 5.4 to 90.3 years).
The
average BMI was 23.4 kg/m
2 (range 13.7
to 50.8 kg/m
2) for females
and 23.7
kg/m
2 (range 13.8 to 43.3
kg/m
2) for males. On average,
1263 (range
819 to 1392) individuals were genotyped for a marker
locus. The
average individual was successfully genotyped for
320
markers.
The multipoint linkage analysis results of the
genome scan are presented in
Table 3
as the highest LOD score observed on each
chromosome for each of 11 plasma lipid and apolipoprotein
traits. LOD peaks >2.00 are indicated in boldface type; LOD scores
>3.00 were observed for the apoE level on chromosome 19 in the
region containing the apoE
gene. In the analysis of age, we observed no LOD score >0.00
(Table 3
).
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Table 3. Peak Multipoint LOD Scores and Positions on Each
Chromosome for 11 Plasma Lipid and Apolipoprotein Traits
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Figure 1
depicts the linkage results for 4 traits (apoA-I,
apoA-II, apoE, and total-C/HDL-C) for the chromosomes for which LOD
peaks >1.30 were observed. The highest LOD score observed was 4.20,
corresponding to a chromosomal region influencing the plasma apoE level
on 19q, near the marker D19S246. An interval 40 cM wide between markers
D19S245 and D19S254 had LOD scores >2.00. Tentative evidence for
linkage to a region influencing variation in apoE was also found on
chromosome 12p near the marker GATA91H06 (LOD score 1.50). To test
whether the multiple QTLs identified as influencing variation in apoE
levels formed a true multilocus system, we ran a multipoint linkage
scan of the genome by using full and reduced models, which both
included the contribution of the QTL on chromosome 19. A LOD score from
this analysis of 1.30 on chromosome 12 near the marker
GATA91H06 supports the initially observed evidence of linkage to a QTL
in this region that influences variation in apoE levels.

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Figure 1. Plot of multipoint LOD scores (calculated at 1-cM intervals) for linkage with regions on chromosomes 4, 5, and 18 influencing variation in plasma apoA-II level, on chromosomes 5 and 17 influencing variation in total-C/HDL-C, on chromosomes 12 and 19 influencing variation in plasma apoE level, and on chromosome 12 influencing variation in plasma apoA-I level.
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Suggestive evidence of a QTL near the marker D4S2368 on
chromosome 4q (LOD score 2.35) and a QTL on 5p (LOD score 2.13) near
the marker D5S2500, which influence variation in apoA-II levels, was
detected. Tentative evidence was observed for a third QTL influencing
apoA-II variation on chromosome 18 near the marker D18S976 (LOD score
1.53). Linkage analysis in which the full and reduced models
included the contribution of the chromosome 4 QTL resulted in a LOD
score of 1.55 for a second QTL on chromosome 5 near D5S2500. Suggestive
evidence was found of linkage near marker D12S2070 on chromosome 12
(LOD score 2.02) with a QTL influencing plasma apoA-I levels. Evidence
suggestive of a QTL near marker D17S928 at the end of the long arm of
chromosome 17 (LOD score 2.48) that influences plasma total-C/HDL-C
variation was observed. Additional tentative evidence of a QTL
influencing variation in total-C/HDL-C was found on chromosome 5q near
the marker D5S408 (LOD score 1.57). Linkage analysis with the
contribution of the chromosome 17 QTL included in the full and reduced
models resulted in a LOD score of 1.26 for a second QTL at the
chromosome 5 location.
 |
Discussion
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The purpose of the present study was to identify
genomic regions
containing genes influencing interindividual variation
in plasma
lipid and apolipoprotein levels in nonhispanic white
families
from Rochester, Minn, selected without regard to health
status.
The results of our linkage scan provide evidence of regions
of
the genome that may contain previously unknown genes that
influence
normal interindividual variation in apoA-I, apoA-II,
apoE, and
total-C/HDL-C. Positional candidate genes in regions
identified by
multipoint linkage analyses are summarized in
Table
4

.
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Table 4. Positional Candidate Genes for Plasma ApoA-I,
ApoA-II, ApoE, and Total-C/HDL-C in Genomic Regions Identified by
Multipoint Linkage Analyses
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The genome-wide linkage scan for loci influencing age serves
as a negative control for the variance-components linkage method in
this population.
Figure 2
contrasts the multipoint linkage results for age
with those for plasma apoE on chromosome 19. The fact that no LOD score
>0.00 was observed for age on any chromosome is in accord with the low
type I error rate (0.0025) estimated for this method in the GAW10
problem set of simulated nuclear
families.41

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Figure 2. Plot of multipoint LOD scores (calculated at 1-cM intervals) for linkage on chromosome 19 with regions influencing variation in plasma apoE level, apoE adjusted for apoE genotype (apoE/E type), and age.
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The apoE gene region
on chromosome 19q serves as a positive control for the
variance-components linkage method. There is a large body of evidence
supporting the major contribution of the
apoE gene to variation in
plasma apoE level and to the risk of developing
CAD.11 14 42 43 44 45
The 3 major apoE isoforms (E2, E3, and E4) account for between 11% and
19% of the interindividual variation in levels of apoE in this and
other
populations.16 33 46
The highest LOD score observed in the present study (LOD score
4.20, near the marker D19S246) identifies a region of chromosome 19
that includes the apoE/C-I/C-II
gene cluster. The width of this peak, covering more than one third of
chromosome 19 (LOD score >2.00), may be due to the major effect of the
apoE gene on interindividual
variation in the apoE level. Alternately, the width of the region with
LOD scores suggestive of linkage may indicate overlapping peaks that
are due to genes other than
apoE within this region with
effects on lipid metabolism. To test whether variation in
the apoE gene was responsible
for the multipoint LOD peak observed on chromosome 19, we adjusted
plasma apoE levels for apoE
genotype means (after gender-specific adjustment for variation
in age, height, and weight to the third order and BMI). The resulting
peak multipoint LOD, 1.10 at 78 cM
(Figure 2
), is below our threshold for tentative evidence of
linkage but may still reflect variation in the
apoE gene not measured by the
2,
3, and
4
alleles47 (J.H.
Stengård, personal communication, 2000).
The ability to detect linkage of markers with the
apoE gene region, when the
plasma apoE level is considered, documents the utility of this method
to localize genes influencing interindividual variation in plasma lipid
traits of complex inheritance. Simulations by Blangero et
al39 indicate that a
variance-components linkage analysis of 1000 individuals in
randomly ascertained extended pedigrees has a power of 80% to detect a
QTL that accounts for as little as 20% of trait variation with a LOD
score of
3.0. However, the pedigrees used in the study of Blangero et
al were much larger than the pedigrees used in the present study,
and the power of the variance-components method to detect linkage
decreases with declining QTL-specific
heritability.48 Thus, the
many QTLs that are each expected to have considerably smaller effects
on genetic variance may not be detected by a linkage analysis
performed with this simple model on small randomly ascertained
pedigrees.
Polymorphism in the
apoE gene has been identified
as a predictor of variation in intermediate risk factors for CAD, apart
from apoE level, including total-C, TGs, apoB, and
HDL-C.33 45 49
For example, the traditional
apoE genotypes explain
3% and 23% of variation in TGs in men and women, respectively, in
Rochester, Minn.33 Peak
multipoint LOD scores on chromosome 19 for TGs did not exceed 2.00, nor
did the peak correspond to the position of the
apoE gene
(Table 3
). However, the effect of
apoE on TG level varies in
contexts such as age and measures of body
size.50 51 52 53
The context-dependent effects of
apoE genotype on other
measures of lipid metabolism, and on the correlations among
them, are also well
known.52 53 Much of
the complexity of the genetic architecture of apoE and other plasma
lipid and apolipoprotein traits is ignored by the simple additive
variance-components model of linkage used in the present study. We
chose to initially examine the first-order effects to maximize the
power to detect a QTL by using the full sample in this first genome
scan. We expect that QTLs with large marginal effects will be detected
by this model but that QTLs whose effects are confined to particular
strata of the population may be associated with LOD scores below our
threshold for linkage.
Despite the limitations of the simple model used in the
present study, several regions suggestive of linkage with lipid and
apolipoprotein traits within which lie candidate genes for lipid
metabolism were identified
(Table 4
). In addition to the evidence for linkage with a
QTL influencing variation in apoE level on chromosome 19, tentative
evidence for linkage was observed on chromosome 12. This region
contains the gene encoding the catalytic polypeptide of the apoB
mRNAediting enzyme (APOBEC1),
which is involved in the metabolism of apoE. In LDL
receptor knockout mice, inactivation of
APOBEC1 resulted in a 60%
increase in plasma apoE.54
Thus, variation in the APOBEC1
gene may affect the risk of CAD by influencing variation in the apoE
level in particular contexts indexed by the level of LDL receptor
expression. Additionally, evidence of a locus on chromosome 12
influencing the risk of Alzheimers disease is stronger in
families without the apoE
4
allele,55 56 57
a risk factor for CAD and Alzheimers disease.
Regions on chromosomes 4 and 5 showed suggestive evidence of
the influence of QTL on apoA-II variation (LOD score >2.00)
(Figure 1
). ApoA-II is the second most abundant
apolipoprotein in HDL (after apoA-I) and may affect the risk of CAD by
influencing the rate of cholesterol efflux from
peripheral
tissues.58 A gene on
chromosome 4 that codes for carboxypeptidase E is a positional
candidate gene for influencing apoA-II level. Carboxypeptidase E is an
enzyme responsible for prohormone sorting and processing, influencing
such signaling molecules as pro-opiomelanocortin and insulin, both of
which are involved in energy
homeostasis.59 60 61
Also near the position of the multipoint LOD peak for apoA-II on
chromosome 4 is the gene coding for the fibrinogen-ß polypeptide,
which has been associated with increased risk of peripheral
atherosclerosis.62
On chromosome 5, positional candidate genes include
cholesterologenesis enzymes
3-hydroxy-3-methylglutaryl-coenzyme A reductase
(HMGCR) and 3-hydroxy-3-methylglutaryl coenzyme A
synthase 1 (HMGCS1). Inhibition of
HMGCR in humans alters the plasma lipid profile,
including a significant reduction in the ratio of
cholesterol to
HDL-C.63 In rats,
administration of tetradecylthioacetic acid decreases apoA-II while
increasing HMGCS1 mRNA levels, evidence of a link
between HMGCS1 expression and the level of liver
apolipoproteins.64 Neither of
the 2 regions influencing variation in apoA-II that were identified in
this population included the structural gene for
apoA-II on chromosome 1q21-q23.
Variation in the apoA-II gene
can account for 10% to 11% of interindividual variation in the
apoA-II level.65 However, in
the sample considered here, variation in the
apoA-II gene does not
contribute to variation in apoA-II at a level detectable by linkage
analysis (LOD score <0.50,
Table 2
).
ApoA-I is the most abundant apolipoprotein in HDL-C and is a
better predictor of CAD risk than is HDL-C
alone.10 13 Studies
of the genetic determination of apoA-I have found evidence of 1 major
locus,66 2 major
loci,67 or polygenes
alone68 69
influencing the variation in different populations. The LOD score of
2.02 at 128 cM in the present study suggests that variation in
plasma apoA-I may be influenced by a gene on chromosome 12q. A
positional candidate gene, scavenger receptor class B type 1
(SRB1), is located near the
position of this LOD peak. SRB1, with a binding affinity for multiple
apolipoproteins including apoA-I, apoA-II, and apoC-III, acts as a
receptor for the selective uptake of HDL cholesteryl ester in the liver
and steroidogenic tissues and for the efflux of cholesterol
from peripheral
cells.70 The overexpression
of SRB1 in mice is accompanied
by a substantial, but transitory, decrease in HDL-C and apoA-I
levels.71 It is possible that
changes in SRB1 expression may
also influence apoA-I levels in humans.
Evidence suggestive of the influence of a QTL on variation
in total-C/HDL-C was observed from the analyses of chromosomes
5 and 17. Regulation of microsomal transfer protein
(MTP) expression and activity may influence plasma
cholesterol level. There are no obvious candidate genes
near this location of the LOD peak on chromosome 5. A positional
candidate gene located in the region of the peak LOD score on
chromosome 17 is the procollagen proline 2-oxoglutarate
4-dioxygenase cellular thyroid hormone binding protein, a
multifunctional protein that is the small subunit of the MTP
heterodimer. MTP catalyzes the transport of TGs, cholesteryl esters,
and phospholipids between phospholipid surfaces. Defects in the larger
subunit of MTP have been previously associated with
abetalipoproteinemia.72
Three regions identified in our genome-wide linkage scan,
although associated with LOD scores <2.00, are worthy of further
mention as supporting evidence for previously published reports of
linkage. Aouizerat et al23
found suggestive evidence of linkage on chromosome 11p with a gene
contributing to familial combined hyperlipidemia in
Dutch pedigrees. The region, near the marker D11S1324 (35 cM), was
associated with a combined lipid phenotype that included
elevated total-C (>90th percentile). Tentative evidence for linkage
(LOD score 1.84 at 34 cM) with a gene(s) on chromosome 11p (34 cM)
influencing plasma total-C level was observed in the present study.
Knoblauch et al25 observed
strong evidence of linkage with a region of chromosome 13q near the
markers D13S1241 and D13S786 (76 to 77 cM) influencing HDL-C, LDL,
total-C, and BMI in an Arab family from Israel ascertained for familial
hypercholesterolemia and in an independent
sample of healthy white monozygotic and dizygotic twins from
Germany. This region of 13q is very near the QLTs identified in the
present study, which may influence TG (LOD score 1.64 at 86 cM) and
TG/HDL-C (LOD score 1.37 at 64 cM) levels.
The results of our genome-wide linkage analyses of
11 lipid and apolipoprotein traits provide a focus for future genetic
studies. This scan has identified chromosomal regions hypothesized to
contain new genes influencing interindividual variation in apoA-I,
apoA-II, and total-C/HDL-C and has provided supporting evidence of
regions that may contain genes influencing variation in apoE, total-C,
TGs, and TG/HDL-C. These results suggest a list of positional candidate
genes for detailed DNA sequence analysis aimed at identifying
functional mutations that affect variation in the plasma lipid
profile. Identification of genes that influence lipid
metabolism will lead to a better understanding of the
etiology of CAD and provide suggestions for the development of new
therapies for the treatment and prevention of disease. Finally, a
comparison of our results with the findings of other studies suggests
to us the importance of gene-environment interactions and the need for
context-dependent linkage analyses to identify regions of the
genome that contain genes that influence interindividual variation in
plasma lipid and apolipoprotein levels only in particular subdivisions
of the population at
large.
 |
Acknowledgments
|
|---|
Funding for this research was provided by
National Institutes
of Health grants HL-39107, HL-51021, and HD-32197.
We would
like to thank Paul Kopec, Ken Weiss, and Sara Hamon at the
University
of Michigan and Terry Bertin and Kim Lawson at the
University
of Texas for their technical assistance and critical
input.
Received February 9, 2001;
accepted February 26, 2001.
 |
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