© 1999 American Heart Association, Inc.
Atherosclerosis and Lipoproteins |
Peroxisome Proliferator–Activated Receptor 
Gene Locus Is Related to Body Mass Index and Lipid Values in Healthy Nonobese Subjects
From the Franz Volhard Clinic and Max Delbrück Center for Molecular Medicine (H.K., A.B., H.-D.F., H.S., R.U., F.C.L.), Charité, Medical Faculty of the Humboldt University of Berlin, Berlin; and Bernhard Nocht Institute for Tropical Medicine (B.M.-M.), Department of Molecular Medicine, Hamburg, Germany.
Correspondence to Friedrich C. Luft, Franz Volhard Clinic, Wiltbergstrasse 50, 13122 Berlin, Germany. E-mail: luft{at}fvk-berlin.de
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Abstract |
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Abstract—The peroxisome proliferator–activated receptor
(PPAR)
gene has been implicated in morbid obesity and is important to lipid
and carbohydrate metabolism. However, the relevance of gene
variations in healthy nonobese subjects has not been defined. We
recruited monozygotic and dizygotic healthy nonobese twin subjects to
test the hypothesis that the PPAR gene is important
to body mass index and lipid concentrations in healthy nonobese
subjects. Both linkage and association strategies were used in the same
dizygotic twins. The PPAR gene locus was linked
(P<0.01) to high-density lipoprotein
cholesterol, low-density lipoprotein
cholesterol, and body mass index as quantitative traits. A
biallelic variant in the PPAR gene was associated
with high-density lipoprotein cholesterol and body mass
index (P<0.05). We also looked for linkage between the
same variables and the retinoic X receptor gene locus. This locus
was linked to total and low-density lipoprotein cholesterol
as well as triglycerides. We conclude that the
PPAR gene is highly relevant to lipid
metabolism and body mass index, not only in the morbidly
obese but also in healthy nonobese subjects. The same appears to be
true for its binding partner. Sequencing these genes in twins would
serve to identify gene variations contributing to body mass index and
lipid concentrations in healthy nonobese subjects.
Key Words: genetics • PPAR • quantitative trait loci • body mass index • cholesterol, HDL • cholesterol, LDL • twins
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Introduction |
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Peroxisome proliferator–activated receptor
(PPAR) is a member of the nuclear hormone receptor superfamily that
heterodimerizes with the retinoid X receptor and functions as a
transcriptional regulator of genes linked to lipid
metabolism and energy balance. The thiazolidine class of
antidiabetic drugs and 15-deoxy-
12,14-prostaglandin J2
are ligands for this receptor.1 2 3 PPAR expression is
highest in adipose tissue but is detectable at lower levels in other
tissues (eg, kidney and liver).4 5 Tontonoz et
al6 recently reported that PPAR promotes
monocyte/macrophage differentiation and uptake of oxidized LDL
cholesterol. Ristow et al7 recently reported a
PPAR mutation in 4 patients with massive obesity. When
expressed in fibroblasts, the mutated gene accelerated lipid uptake of
the cells and caused them to differentiate into adipocytes. These
observations prompted us to test the hypothesis that the
PPAR locus is linked to lipid values and body mass index
(BMI) in healthy nonobese dizygotic (DZ) twin subjects in terms of a
quantitative trait locus (QTL). We then took advantage of a biallelic
marker in the PPAR gene and were able to associate the
genotypes with BMI and HDL cholesterol. We also
searched for linkage between the retinoic X receptor gene locus and the
same phenotypes and showed that this locus is a QTL for total
and LDL cholesterol. Our data support the notion that
PPAR and its binding partner are relevant to BMI and lipid levels in
healthy nonobese persons. |
Methods |
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Study Population
We recruited 222 pairs of monozygotic (MZ; 122 pairs) and DZ (100 pairs) twins by advertisement to participate in studies involving blood pressure regulation and cardiovascular phenotypes.8 9 We also recruited the parents of the DZ twins to permit identity by descent linkage analysis. Twin zygosity was verified with use of 5 polymerase chain reaction–amplified microsatellite markers as described in detail elsewhere.10 The subjects were all healthy, normotensive whites recruited from various parts of Germany. The protocol was approved by the university’s committee on the protection of human subjects, and written informed consent was obtained from all participants. Persons with histories of familial lipid disorders were excluded.
Phenotypic Characterization
Blood was obtained from the twins after a 12-hour fast. Total
cholesterol, HDL cholesterol, and
triglycerides were determined by automated
methods.11 LDL cholesterol concentrations were
calculated by the Friedewald equation.12 Blood was also
obtained for determination of zygosity and other molecular genetic
studies.
Genotyping
Microsatellite markers spanning 
45 cM around the
PPAR gene on chromosome 313 (D3S1297,
D3S1304, D3S3726, D3S3589, D3S1263, D3S3608, D3S2338, and D3S1266), as
well as markers spanning 5 cM around the retinoic X receptor
gene on chromosome 1 (D1S2768, D1S2844, D1S426, and D1S194), were
analyzed using the PE Applied Biosystems genotyping
system. A polymorphism corresponding to a silent C-to-T
substitution in exon 6 of PPAR was analyzed
according to a published protocol.14
Statistical Analysis
For linkage analysis, only DZ pairs and their parents
were included. Data were analyzed by using a structural
equation modeling (SEM) approach15 as implemented in the
Mx statistical package.16 This approach is based on
variance-covariance matrices of sibs weighted by the
probability of sharing 0, 1, or 2 alleles identical by descent. The
higher power of the variance-covariance–based
analysis, compared with the squared trait differences–based
approach by the Haseman-Elston regression method,17 was
shown in a recent simulation study.18 Because we used a
candidate gene approach, we accepted P<0.01 to test for
significant linkage in accordance with the criteria defined by Lander
and Kruglyak.19 To increase the power for the
association analysis, mean scores of pairs of MZ twins were
included together with scores of DZ pairs.20 Statistical
analysis was conducted by using ANOVA (SPSS).
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Results |
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Table 1
shows the demographic and
lipid-related variables for the twin subjects. Female sex was twice
as common as male sex. Subjects were young adults of normal height,
weight, and BMI. Total, HDL, and LDL cholesterol and
triglyceride values were all within normal limits. Table 2 shows the results of the heritability
analysis. A major genetic effect was demonstrated on all lipid
parameters, although strong environmental effects were also
shown. Table 3 gives the results of the
structural equation modeling multipoint linkage analysis for
markers spanning the PPAR and retinoic X receptor gene
loci and body size as well as for serum lipid concentrations. Only the
peak value for each locus is given. Significant linkage was found
between the PPAR locus and BMI, body weight, and serum
HDL and LDL cholesterol levels. For the retinoic X receptor
locus, linkage was found for total and LDL cholesterol
levels, as well as triglycerides. Figure 1 shows the results of the linkage
analysis for PPAR and HDL
cholesterol. The location of the markers and the
PPAR gene is indicated in the figure. BMI and LDL
cholesterol reached their peak significance in the same
chromosomal region as HDL cholesterol. Table 4 gives the results of an association
analysis using the biallelic marker in the PPAR
gene. Persons with the TT variant had decidedly higher HDL
cholesterol values, as shown in Figure 2, and tended to have lower LDL
cholesterol values and the lowest BMI compared with persons
with the CC or CT variant.
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We next examined within-pair differences in MZ twins, biallelic
marker–concordant DZ twins, and biallelic marker–discordant DZ twins.
For HDL cholesterol, MZ twins had the least pair
difference, DZ concordant twins were intermediate, and DZ discordant
twins had the greatest within-pair HDL cholesterol
concentration difference (P<0.01). These results are shown
in Figure 3. Similar results were
obtained for LDL cholesterol (data not shown). For BMI, the
results of the analysis were not significant.
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Discussion |
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Because cardiovascular disease is the most common cause of death worldwide, more than half of the population can expect to develop cardiovascular disease during their lifetime.21 Thus, identifying QTL for cardiovascular disease–relevant phenotypes in healthy nonobese persons, and subsequently demonstrating variations in the corresponding candidate genes, is important to cardiovascular disease genetics. We believe that our study exemplifies the utility of this combined linkage and association approach. MZ and DZ twins permit quantification of genetic and environmental variance. As reported earlier,22 the body size parameters and serum lipid concentrations were all influenced by genetic variance. DZ twins, who are perfectly matched for age and who are generally exposed to very similar environmental conditions, are ideal subjects for efficient sib-pair analyses. Thus, far fewer subjects are needed to gain insight into QTL.
We showed that the PPAR gene locus is a QTL for BMI, LDL,
and HDL cholesterol concentrations in healthy non-obese
subjects and that a biallelic polymorphism in the
PPAR gene is associated with BMI and lipid
concentrations. The relationship between LDL cholesterol
and PPAR, as well as the relationship between HDL
cholesterol and PPAR achieved significance,
whereas that for total cholesterol and PPAR
did not. We interpret this finding as suggesting that the effects on
LDL and HDL cholesterol may be opposite in nature. Our
association results would support that point of view. Furthermore, the
retinoic X receptor gene locus is a QTL for LDL and total
cholesterol. Our results are in concordance with data from
a total genome scan conducted in 92 nuclear families using several
measures of obesity.23 In this study, a marker on
chromosome 3 (D3S1286) was significantly linked to the percentage of
body fat. This marker is located within the chromosomal region linked
to BMI in our study. A second genomic scan conducted in Pima Indians,
which pointed toward a QTL for BMI on chromosome 11, showed no
significant linkage.24 That lack of confirmation may have
been due to population specifics or power restrictions.
PPAR has been shown to be an important disease gene for
morbid obesity.7 In a segregation analysis,
evidence was found for at least 2 major loci influencing
BMI.25 Together, these loci are expected to account for
64% of the variance in BMI.
Although obesity is common, most persons do not have morbid obesity.
Our data suggest that more subtle variations in PPAR are
important to BMI and lipid values in healthy nonobese subjects as well.
We believe that these observations are particularly relevant for
several reasons. Obesity is reported as the most common health problem
in developed countries.26 Low HDL
cholesterol values are a recognized risk for
coronary heart disease.27 PPAR is pivotal to a
variety of serious obesity-related medical conditions, including type 2
diabetes mellitus and cardiovascular disease. Although
adipose tissue has been recognized as a principal site of
PPAR gene expression, the gene is expressed at lower
levels in many nonadipose tissues and cell types, where it may also
play an important role. Several classes of ligands have been
found.28 29 30 31 The thiazolidinediones are specific
synthetic agonists for PPAR.
15-deoxy-12,14-prostaglandin J2 is a natural ligand.
Certain polyunsaturated fatty acids, such as linoleic acid, also
activate PPAR. Nonsteroidal antiinflammatory drugs, such as
ibuprofen, can activate the receptor as well. PPAR also
functions as an obligate heterodimer with the retinoic X receptor,
which, among other things, is involved in triglyceride
metabolism.32
PPAR may actively participate in the pathogenesis of
atherosclerosis. Monocytes and macrophages are
pivotal to inflammation and the development of
arteriosclerosis. Ricote et al33 were
able to show that PPAR is markedly upregulated in activated
macrophages. They found that PPAR inhibits the expression of
inducible nitric oxide synthase, gelatinase B, and the scavenger
receptor A genes in response to synthetic ligands, probably by
antagonizing the transcription factors AT-1, STAT, and NF-
B.
Tontonoz et al5 found that PPAR is induced in human
monocytes after exposure to oxidized LDL and is expressed at high
levels in atherosclerotic lesions. Ligand activation of PPAR induced
monocyte differentiation and promoted the transcriptional induction of
the scavenger receptor. Nagy et al34 further elucidated
this issue by showing that oxidized LDL components acted as
endogenous PPAR ligands. They demonstrated a novel
signaling pathway coordinated by the macrophage scavenger
receptor on the cell surface internalizing the particle and PPAR in
the nucleus, which is transcriptionally activated by its
component lipids. Thus, PPAR appears to be a key regulator of foam
cell gene expression.
Our data suggest that PPAR gene variants in healthy
nonobese, nonhyperlipidemic subjects may have
significant influence on BMI and plasma lipids. Such variants may have
a great effect on the propensity to obesity, type 2 diabetes, and
cardiovascular disease in later life. We can only
speculate on the interrelationships among BMI, HDL
cholesterol concentrations, and PPAR. However, in
epidemiological studies, a higher BMI is associated with lower HDL
cholesterol concentrations,35
consistent with our findings. Furthermore, Meirhaeghe et
al14 have described an interaction between the C-to-T
substitution in the PPAR gene and BMI for plasma leptin
levels. They found that persons bearing at least one T allele had a
lower BMI for a given leptin level, compared with CC homozygous
individuals. Their results are consistent with our
findings.
Deeb et al36 recently demonstrated that the Pro12/Ala
substitution in the PPAR gene is associated with lower
BMI and improved insulin sensitivity. The investigators were also able
to show that the Pro12/Ala substitution is associated with decreased
receptor activity. Yen et al37 first reported this
missense PPAR mutation, which involves a C-to-G
substitution at nucleotide 34. They also found an
association between this mutation and type 2 diabetes mellitus in a
small number of white patients. Ringel et al38 were
unable to confirm these findings in a large association study involving
522 type 1 diabetic and 503 type 2 diabetic patients, compared with 310
nondiabetic control subjects. Discrepancies in association studies are
common. We believe our twin model may be more stable because we relied
on both linkage and association approaches. Furthermore, our DZ sib
pairs have half of their genes in common and therefore provide a much
more homogeneous sample. For example, if 30 genes are
responsible for obesity, the DZ twin would have concordant alleles
for half of these genes. If we then examine discordancy in a candidate
gene, the number of confounders in our study would be decidedly less
compared with that in association studies in randomly selected
people.
The variant we examined is silent but apparently in linkage
disequilibrium with a functional polymorphism in the
PPAR gene or possibly in a nearby gene. We suggest that
much of the genetic variance on BMI and HDL cholesterol
levels in healthy nonobese persons is attributable to the
PPAR gene locus. Multiplex sequencing of the
PPAR gene in all of our DZ twin subjects and their
parents may provide insight into the functional variants involved.
These findings highlight the broad, encompassing role of
PPAR in processes involving BMI and lipid
metabolism not only in persons with disease but also in
healthy, healthy nonobese persons.
Received March 8, 1999; accepted April 9, 1999.
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