Article

A pleiotropic QTL on 2p influences serum Lp-PLA2 activity and LDL cholesterol concentration in a baboon model for the genetics of atherosclerosis risk factors

Department of Genetics, Southwest Foundation for Biomedical Research, San Antonio, TX 78245, United States.
Atherosclerosis (Impact Factor: 3.99). 03/2008; 196(2):667-73. DOI: 10.1016/j.atherosclerosis.2007.07.014
Source: PubMed

ABSTRACT

Lipoprotein-associated phospholipase A(2) (Lp-PLA(2)), the major portion of which is bound to low-density lipoprotein, is an independent biomarker of cardiovascular disease risk. To search for common genetic determinants of variation in both Lp-PLA(2) activity and LDL cholesterol (LDL-C) concentration, we assayed these substances in serum from 679 pedigreed baboons. Using a maximum likelihood-based variance components approach, we detected significant evidence for a QTL affecting Lp-PLA(2) activity (LOD=2.79, genome-wide P=0.039) and suggestive evidence for a QTL affecting LDL-C levels (LOD=2.16) at the same location on the baboon ortholog of human chromosome 2p. Because we also found a significant genetic correlation between the two traits (rho(G)=0.50, P<0.00001), we conducted bivariate linkage analyses of Lp-PLA(2) activity and LDL-C concentration. These bivariate analyses improved the evidence (LOD=3.19, genome-wide P=0.015) for a QTL at the same location on 2p, corresponding to the human cytogenetic region 2p24.3-p23.2. The QTL-specific correlation between the traits (rho(Q)=0.62) was significantly different from both zero and 1 (P[rho(Q)=0]=0.047; P[rho(Q)=1]=0.022), rejecting the hypothesis of co-incident linkage and consistent with incomplete pleiotropy at this locus. We conclude that polymorphisms at the QTL described in this study exert some genetic effects that are shared between Lp-PLA(2) activity and LDL-C concentration.

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Atherosclerosis 196 (2008) 667–673
A pleiotropic QTL on 2p influences serum Lp-PLA
2
activity and LDL
cholesterol concentration in a baboon model for the genetics of
atherosclerosis risk factors
A. Vinson
a,
, M.C. Mahaney
a,b
, L.A. Cox
a,b
, J. Rogers
a,b
,
J.L. VandeBerg
a,b
, D.L. Rainwater
a
a
Department of Genetics, Southwest Foundation for Biomedical Research, San Antonio, TX, United States
b
Southwest National Primate Research Center, San Antonio, TX, United States
Received 2 February 2007; received in revised form 22 June 2007; accepted 16 July 2007
Available online 4 September 2007
Abstract
Lipoprotein-associated phospholipase A
2
(Lp-PLA
2
), the major portion of which is bound to low-density lipoprotein, is an independent
biomarker of cardiovascular disease risk. To search for common genetic determinants of variation in both Lp-PLA
2
activity and LDL cholesterol
(LDL-C) concentration, we assayed these substances in serum from 679 pedigreed baboons. Using a maximum likelihood-based variance
components approach, we detected significant evidence for a QTL affecting Lp-PLA
2
activity (LOD = 2.79, genome-wide P = 0.039) and
suggestive evidence for a QTL affecting LDL-C levels (LOD = 2.16) at the same location on the baboon ortholog of human chromosome 2p.
Because we also found a significant genetic correlation between the two traits (ρ
G
= 0.50, P < 0.00001), we conducted bivariate linkage analyses
of Lp-PLA
2
activity and LDL-C concentration. These bivariate analyses improved the evidence (LOD = 3.19, genome-wide P = 0.015) for a
QTL at the same location on 2p, corresponding to the human cytogenetic region 2p24.3–p23.2. The QTL-specific correlation between the
traits (ρ
Q
= 0.62) was significantly different from both zero and 1 (P[ρ
Q
= 0] = 0.047; P[ρ
Q
= 1] = 0.022), rejecting the hypothesis of co-incident
linkage and consistent with incomplete pleiotropy at this locus. We conclude that polymorphisms at the QTL described in this study exert
some genetic effects that are shared between Lp-PLA
2
activity and LDL-C concentration.
© 2007 Elsevier Ireland Ltd. All rights reserved.
Keywords: Lp-PLA
2
; LDL cholesterol; Genome scan; Bivariate; Pleiotropy; Baboon
1. Introduction
Lp-PLA
2
, or lipoprotein-associated phospholipase A
2
,is
increasingly implicated as a reliable biomarker of cardio-
vascular disease that is independent of other biomarkers
of inflammation [1]. The major portion of circulating
Lp-PLA
2
is bound to low-density lipoprotein (LDL) par-
ticles [2], and the amino acid residues that determine this
binding have been identified and described [3]. Consis-
tent with evidence showing that Lp-PLA
2
is responsible
Corresponding author at: Department of Genetics, Southwest Foundation
for Biomedical Research, P.O. Box 760549, San Antonio, TX 78245, United
States. Tel.: +1 210 258 9886.
E-mail address: avinson@sfbrgenetics.org (A. Vinson).
for over 95% of LDL-associated phospholipase activity
[4], positive correlations between Lp-PLA
2
activity and
LDL-C concentration have been described both in nor-
molipidemic [5] and in hypercholesterolemic individuals
[5,6].
While variation in both Lp-PLA
2
activity and LDL-C con-
centration is known to be influenced by genes, the latter has
been the subject of more extensive genetic analysis. In studies
of humans and animals, genes have been shown to account
for a moderate proportion of the variance – 36% to 59% – in
LDL-C levels [7,8]. Published genome scans have mapped
quantitative trait loci (QTLs) affecting LDL-C concentration
in humans to multiple chromosomal regions that harbor can-
didate genes affecting the regulation of LDL metabolism,
processing, and transport [7,9,10]. A number of these find-
0021-9150/$ – see front matter © 2007 Elsevier Ireland Ltd. All rights reserved.
doi:10.1016/j.atherosclerosis.2007.07.014
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668 A. Vinson et al. / Atherosclerosis 196 (2008) 667–673
ings in humans correspond well with those reported in studies
of mice [11] and non-human primates [12].
In contrast, comparatively little is known about the genet-
ics of quantitative variation in Lp-PLA
2
activity. Only two
studies report heritability estimates for this trait in humans:
one, a study of 240 individuals from 60 nuclear families from
Dallas, Texas [5], and the other, a study of 1341 Mexican
Americans from 42 extended pedigrees from San Antonio,
Texas [13]. Both studies found that approximately 60% of
the variance in Lp-PLA
2
activity is due to the additive effects
of genes. The latter study [13] also reported significant evi-
dence for a QTL on chromosome 1q when accounting for
interaction with adiposity.
In the present study, we hypothesized that some of the
well-documented biological correlation between Lp-PLA
2
activity and LDL-C concentration is due to pleiotropy, or
the shared effects of the same gene or genes. To test this
hypothesis, we conducted analyses to detect, characterize,
and localize to specific chromosomal regions the effects
of genes contributing pleiotropically to variation in both
phenotypes in pedigreed baboons, a model species with doc-
umented utility for studies of the genetics of lipoproteins and
other risk factors for cardiovascular disease [8,14,15].
2. Methods
2.1. Subject description
We obtained data for this study from a sample of 679 pedi-
greed baboons (Papio hamadryas) comprising 440 females
and 239 males maintained at the Southwest National Primate
Research Center (SNPRC), located at the Southwest Foun-
dation for Biomedical Research in San Antonio, Texas. The
age of baboons in this sample ranged from 2 to 29 years,
corresponding approximately to a human developmental age
range of 6–85 years. All animals are housed outdoors in social
groups and are maintained on a low-cholesterol, low-fat
commercial monkey diet (7% fat from plant oils, 0.02 mg/g
cholesterol) to which they have ad libitum access. Animal
care personnel and staff veterinarians provided routine and
emergency health care to all animals in accordance with the
Guide for the Care and Use of Laboratory Animals. The
SFBR facility is certified by the Association for Assessment
and Accreditation of Laboratory Animal Care International,
and all procedures were approved by the Institutional Animal
Care and Use Committee.
For the purposes of this study, these baboons were
organized into 11 distinct pedigrees, yielding a diverse array
of relative pair classes: 671 parent–offspring; 598 sibling;
73 grandparent–grandchild; 96 avuncular; 6732 half-sibling;
1794 half-avuncular; 6 first cousin; 47 half-first cousin; 5
half-first cousin, once removed; 27 half-sibling and first
cousin; 633 half-sibling and half first cousin; 7 half-sibling
and half avuncular, and 37 double half-avuncular. These 11
baboon pedigrees may be viewed at the SNPRC website:
http://www.snprc.org/baboon/map/BPPpedigrees/bpppeds.
htm.
2.2. Phenotyping
Lp-PLA
2
activity and LDL-C concentration were assayed
in serum samples, obtained as part of a large, ongoing study of
the effects of diet and genotype on variation in atherosclero-
sis risk factors. Blood samples were drawn in the morning
from a femoral vein of animals on basal diet following
an overnight fast (prior to blood collection, sedatives were
administered to ensure relaxation). Serum samples were sep-
arated from whole blood by low-speed centrifugation and
stored in individual, single-use aliquots at 80
C, protected
from oxidation and desiccation [16].
Serum Lp-PLA
2
enzyme activity was measured at 30
C
using a kit provided by Cayman Chemical Company (Ann
Arbor, MI). Hydrolysis of the substrate, 2-thio platelet-
activating factor, produced a free thiol which was quantified
using 5,5
-dithio-bis-(2-nitrobenzoic acid). The reaction was
monitored at 405 nm using a BioTek ELx808 microplate
reader running in kinetic data acquisition mode. Rates were
calculated from at least 15 min of readings in the linear phase
and converted to nmol/min/mL plasma using an extinction
coefficient value of 13.6/mM-cm. Each sample was run
in duplicate, and the average coefficient of variation was
1.7% (n = 2542). The across-plate coefficient of variation,
based on a control sample run on each plate, was 4.3%
(n = 59).
Cholesterol concentrations were measured enzymatically
[17] with a reagent supplied by Boehringer Mannheim
Diagnostics and using a Ciba-Corning Express Plus clin-
ical chemistry analyzer. Cholesterol carried by HDL
was estimated following precipitation of apoB-containing
lipoproteins with heparin-Mn
2+
as described [18] and LDL
cholesterol was calculated as the difference between total and
HDL cholesterol. Ninety percent (90%) of non-HDL choles-
terol on basal diet is associated with particles in the LDL size
range [15]; for convenience, we refer to it as LDL-C. Average
between-assay coefficients of variation for these determina-
tions were 2.2% and 4.6% for total and HDL cholesterol,
respectively. ApoB concentrations were determined using an
immunoturbidometric assay [15].
2.3. Baboon genotyping and whole genome linkage map
Statistical genetic analyses of these two traits took advan-
tage of a baboon whole genome linkage map based on
genotype data at nearly 300 microsatellite marker loci
(mean inter-marker interval = 8.9 cM) from 984 pedigreed
baboons in these same 11 extended pedigrees. The phys-
ical locations in the human genome for nearly all marker
loci in the baboon map are known, thus facilitating the
identification of likely orthologous chromosomal regions
in the two species. Construction of the current baboon
linkage map is described in detail elsewhere [19], and addi-
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A. Vinson et al. / Atherosclerosis 196 (2008) 667–673 669
tional information can be found at the SNPRC website:
http://www.snprc.org/baboon/genome/index.html.
2.4. Statistical genetic methods
Accounting for random and measured environmental con-
tributions to the phenotypic variance can improve power to
detect genetic effects. Prior to all analyses, we used like-
lihood ratio tests to screen each of the following variables
for significant mean effects on Lp-PLA
2
and LDL-C levels:
age, sex, age
2
, age × sex, and age
2
× sex. After regressing
out the mean effects of all nominally significant (P 0.10)
covariates, we applied an inverse Gaussian transformation to
the residuals to correct for departures from multivariate nor-
mality that might inflate evidence for linkage. All polygenic
and linkage analyses were conducted using these normalized
residual data.
2.4.1. Univariate analyses
All statistical genetic analyses were conducted using
a maximum likelihood-based variance decomposition
approach implemented in the computer package Sequen-
tial Oligogenic Linkage Analysis Routines (SOLAR [20]).
We used this approach to partition the phenotypic vari-
ance in a trait (σ
2
P
) into components corresponding to
additive genetic effects (σ
2
G
), estimated as a function of
relatedness among pedigreed baboons, and environmental
effects (σ
2
E
). We define residual heritability (h
2
)asthe
proportion of residual phenotypic variance unexplained by
covariates that can be attributed to additive genetic effects
(h
2
= σ
2
G
2
P
).
To identify regions of the baboon genome harboring
QTLs affecting either Lp-PLA
2
activity or LDL-C concen-
tration, we used an extension to this variance decomposition
method to conduct univariate multipoint linkage analyses for
each phenotype. In these analyses, we modeled the pheno-
typic covariance among relatives as the sum of the additive
genetic covariance attributable to a specified marker locus,
the additive genetic covariance due to the effects of other
loci, and the variance due to unmeasured environmental
factors.
We estimated probabilities of identity-by-descent (IBD)
among relatives at marker loci in the baboon linkage map
using Markov Chain Monte Carlo routines implemented in
the computer package Loki [21]. We tested linkage hypothe-
ses at 1 cM intervals along each chromosome using likelihood
ratio tests, and converted the resulting likelihood ratio statistic
to the LOD score of classic linkage analysis [22].
To control for the genome-wide false positive rate, we
calculated genome-wide P-values for each LOD score using
a method suggested by Feingold et al. [23] that takes into
account pedigree complexity and the finite marker density
of the linkage map. Accordingly, our threshold for signifi-
cant evidence of linkage was LOD = 2.69, and for suggestive
evidence of linkage was LOD = 1.46.
Because variation in LDL-C concentration is known to
be influenced by multiple genes and we expect variation
in Lp-PLA
2
activity to be determined in a similar manner,
we performed sequential multipoint whole genome linkage
screens to facilitate detection of multiple QTLs for each trait
[20]. That is, after a first genome screen detected a puta-
tive QTL, we repeated the linkage screen using a model that
accounted for the effect(s) of the previously detected, sig-
nificant QTL(s). This was done sequentially until a genome
screen failed to detect a QTL for which there was at least
suggestive evidence at the genome-wide level.
2.4.2. Multivariate analyses
To determine the extent to which phenotypic variation
in serum Lp-PLA
2
activity and LDL-C concentration may
be affected by shared genes and shared non-genetic fac-
tors, we conducted bivariate analyses in which both traits are
considered simultaneously. In comparison to the univariate
polygenic model, the bivariate polygenic model additionally
estimates the additive genetic and environmental correla-
tions between both traits. The genetic correlation (ρ
G
)is
an estimate of pleiotropy between the two traits, and ρ
2
G
thus estimates the portion of the additive genetic variance
in each trait due to shared genetic effects. The random
environmental correlation (ρ
E
) is an estimate of the shared
effects of non-additive genetic factors and unmeasured envi-
ronmental variables. Using these estimates, we calculated
the phenotypic correlation between the trait pair as ρ
P
=
ρ
G
h
2
1
h
2
2
+ ρ
E
1 h
2
1
1 h
2
2
[24]. We assessed the
significance of ρ
G
and ρ
E
by means of likelihood ratio tests
comparing the likelihoods of models in which the correlation
was estimated to those in which it was constrained to zero
(rejection of ρ
G
= 0 indicates pleiotropy) or to 1 (failure to
reject |ρ
G
| = 1 indicates complete pleiotropy).
To search for pleiotropic QTLs affecting phenotypic vari-
ation in both Lp-PLA
2
activity and LDL-C concentration,
we conducted bivariate multipoint linkage analyses, lim-
iting these analyses to chromosomes exhibiting at least
suggestive evidence for QTLs in the univariate screens.
To facilitate comparison with univariate linkage results,
we adjusted bivariate LOD scores to be equivalent to
univariate LOD scores in terms of degrees of freedom
[25].
An additional parameter estimated in the bivariate link-
age model is ρ
Q
, the additive genetic correlation between
the traits due to the effects of the QTL. In a bivariate
linkage analysis, QTLs may be found that appear to influ-
ence phenotypic variation in both traits. To distinguish the
event where two traits may each be independently influ-
enced by closely linked genes (“co-incident linkage”) from
QTL pleiotropy, we conducted a likelihood ratio test of the
hypothesis ρ
Q
= 0. In accordance with Almasy et al. [26],
failure to reject this hypothesis supports the co-incident
linkage of two QTLs over pleiotropic effects at the same
locus.
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670 A. Vinson et al. / Atherosclerosis 196 (2008) 667–673
3. Results
3.1. A priori analysis of apoB concentration
Given that “LDL-C” refers to all the apoB-containing
lipoproteins in the LDL size interval in baboons, we con-
ducted initial analyses to confirm that our focus on LDL-C
concentration did not ignore genetic information contained
in measures of apoB. Like LDL-C concentration, a signifi-
cant proportion of the variance in apoB concentration in these
baboons was due to the additive effects of genes (h
2
= 0.48).
Further, the additive genetic correlation between these two
traits was not significantly different from 1 (ρ
G
= 0.97,
P[ρ
G
= 1] = 0.20), indicating that all, or nearly all, the additive
genetic variance in LDL-C and apoB concentrations mea-
sured in this study is due to the effects of the same gene or
genes.
3.2. Univariate analyses: genetic effects on Lp-PLA
2
activity and LDL-C levels
Maximum likelihood estimates of heritability, mean
covariate effects, and the proportion of total phenotypic vari-
ation due to significant covariates for both Lp-PLA
2
activity
and LDL-C concentration are provided in Table 1. The pro-
portion of phenotypic variance due to significant age and sex
terms was moderate for both traits, accounting for approxi-
mately 29% of the phenotypic variance in Lp-PLA
2
activity
and 18% for LDL-C concentration. The additive effects
of genes accounted for statistically significant and similar
proportions of the residual phenotypic variance in the two
traits: h
2
= 0.67 for Lp-PLA
2
activity and h
2
= 0.63 for LDL-
C concentration. When considered on a scale describing
total phenotypic variance, the additive effects of genes were
responsible for approximately half the variation in each trait
(i.e., 48% for Lp-PLA
2
and 52% for LDL-C).
Univariate multipoint linkage analysis for Lp-PLA
2
(Table 2) revealed significant evidence in the first genome
Table 1
Univariate polygenic analysis of variation in serum Lp-PLA
2
activity
(nmol/min/mL, N = 657) and LDL-C concentration (SIU*10, N = 670) in
pedigreed baboons: maximum likelihood parameter estimates
Parameter Lp-PLA
2
LDL-C
μ 5.49 (0.14) 6.94 (0.46)
σ 1.18 (0.04) 3.73 (0.12)
h
2
residual
*
0.67 (0.08) 0.63 (0.07)
β age 0.13 (0.01) 0.37 (0.04)
β sex 0.22 (0.13) 3.20 (0.42)
β age × sex ns
0.27 (0.05)
β age
2
0.02 (0.00) 0.04 (0.01)
β age
2
× sex 0.01 (0.00) 0.03 (0.01)
c
2**
0.29 0.18
Parentheses enclose S.E.M.
*
P 0.000001.
ns: not significant at P 0.10.
**
Proportion of total phenotypic variance due to significant covariates.
Table 2
Evidence for QTLs influencing variation in Lp-PLA
2
activity and LDL-
C concentration in pedigreed baboons (univariate whole genome linkage
screen results)
Lp-PLA
2
LDL-C
Maximum LOD 2.79 2.16
Genome-wide P 0.0394 ns
Baboon chromosome (PHA) 13 13
Genetic location (cM from pter-most marker) 26 cM 26 cM
QTL-specific h
2
0.13 0.16
Residual h
2
at QTL 0.52 0.46
scan for a QTL located at position 26 cM from the pter-
most marker locus on baboon chromosome 13 (PHA13,
LOD = 2.79, genome-wide P = 0.0394). A second genome
scan, conditioned on the significant QTL found on PHA13,
found suggestive evidence for a second QTL on PHA20
(LOD = 2.03, results not shown). Estimates of heritability
specific to the QTLs found on PHA13 and PHA20 are 0.13
and 0.11, respectively. When we consider these QTL-specific
heritabilities as a proportion of the total residual heritability
in Lp-PLA
2
activity, each QTL accounts for approximately
19% and 16% of the total additive genetic effect on variation
in Lp-PLA
2
activity, respectively
(h
2
Q
/h
2
) × 100
.
Univariate linkage analysis for LDL-C concentration
(Table 2) also revealed suggestive evidence for a QTL at the
same region on PHA13 (26 cM, LOD = 2.16) as that for Lp-
PLA
2
. Estimated heritability specific to this QTL was 0.16,
and accounts for approximately 25% of the total additive
genetic effect on LDL-C concentration.
3.3. Multivariate analyses: pleiotropy between Lp-PLA
2
activity and LDL-C levels
Because the detected QTLs for both traits mapped to
PHA13, we conducted bivariate analyses to further charac-
terize the gene(s) responsible. The results of the bivariate
polygenic analysis for Lp-PLA
2
activity and LDL-C concen-
tration are summarized in Table 3. The estimated additive
genetic correlation between Lp-PLA
2
and LDL-C concen-
tration was 0.50 (P[ρ
G
= 0] < 0.00001), indicating that both
traits are influenced by shared additive genetic effects and
that an estimated 25% of the additive genetic variance in
each of the two traits is due to the effects of the same gene or
genes. The hypothesis of complete pleiotropy between these
Table 3
Bivariate polygenic analysis of variation in Lp-PLA
2
activity and LDL-
C concentration in pedigreed baboons: maximum likelihood parameter
estimates
Parameter Lp-PLA
2
LDL-C
h
2
residual
*
0.66 (0.08) 0.63 (0.07)
ρ
G
0.50 (0.09)
ρ
E
0.40 (0.11)
ρ
P
0.47
Parentheses enclose S.E.M.
*
P 0.000001.
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Table 4
A pleiotropic QTL on baboon chromosome 13 (HSA2p) influencing varia-
tion in Lp-PLA
2
activity and LDL-C concentration in pedigreed baboons:
summary of bivariate linkage analysis results
Lp-PLA
2
, LDL-C
LOD 3.19
Genome-wide P 0.0148
Baboon chromosome (PHA) 13
Genetic location (cM from pter-most marker locus) 26
Flanking microsatellite marker loci (pter, qter) D2S131, D2S146
Human chromosome (HSA) 2p
Corresponding HSA cytogenetic region p24.3–p23.2
QTL-specific h
2
(Lp-PLA
2
, LDL-C) 0.13, 0.15
ρ
Q
0.62
two traits, ρ
G
= 1, was rejected (P 0.000001). The genetic
effects common to both traits account for approximately 17%
and 16% of the residual phenotypic variance in Lp-PLA
2
activity and LDL-C concentration, respectively. The magni-
tude of these shared genetic effects accounted for much of
the residual phenotypic variance shared between Lp-PLA
2
activity and LDL-C concentration (i.e., ρ
2
P
= 0.22).
Results from bivariate multipoint linkage analysis of Lp-
PLA
2
activity and LDL-C concentration for PHA13 are
summarized in Table 4, and Fig. 1 presents the multipoint
LOD plots on PHA13 for each trait from the univariate anal-
yses, and for both traits from the bivariate analysis. While the
maximum LOD score in all analyses was obtained at 26 cM
from the pter-most marker on this chromosome, the evidence
for a QTL influencing variation in the Lp-PLA
2
\LDL-C
bivariate phenotype was improved over that obtained in
the analyses of individual traits (LOD = 3.19, genome-wide
P = 0.0148).
We defined a support interval surrounding the bivariate
QTL as the interval bounded by the locations on the baboon
genetic map at which the LOD score was 1-LOD unit lower
Fig. 1. Univariate linkage results for Lp-PLA2 (dashed line) and LDL-
C (dotted line), and bivariate linkage results for the combined phenotype
Lp-PLA
2
/LDL-C (solid line) on PHA13, the baboon ortholog of human
chromosome 2p.
than the peak LOD score (“1-LOD drop” method). We then
used the markers flanking this support interval to ascertain a
likely orthologous region of interest in the human genome.
Thus, the region likely to harbor the bivariate QTL is a 16 Mb
interval mapping to HSA2p24.3–p23.2, a region narrower
than either region identified in the same manner by the uni-
variate linkage analyses (results not shown).
The estimated additive genetic correlation between Lp-
PLA
2
activity and LDL-C concentration at this QTL was sig-
nificantly greater than zero (ρ
Q
= 0.62; P[ρ
Q
= 0] = 0.0465),
rejecting the hypothesis of co-incident linkage (no shared
genetic effects) and consistent with the hypothesis that this
QTL exerts pleiotropic effects on both traits. However, the
hypothesis of complete QTL pleiotropy between both traits
was also rejected (P[ρ
Q
= 1] = 0.0217). These results indicate
the existence at this QTL of incomplete, or partial, pleiotropic
effects on variation in both traits.
3.4. A posteriori analysis of APOB RFLP polymorphism
Prominent among identified genes mapping to the region
of HSA2p24.3–p23.2 is APOB, the structural locus for the
apoB isoform associated primarily with circulating LDL-
C. We took advantage of APOB genotype data previously
collected for a small subset of these animals [27] to test
for a possible effect of this locus on the two phenotypes
in this study. We performed a measured genotype analysis
[28] in which we included additive and dominance effects of
PvuII restriction fragment length polymorphisms in APOB
as covariates in our genetic models for LDL-C concentra-
tion and Lp-PLA
2
activity. Results of these analyses provided
marginal support for additive effects of this polymorphism on
Lp-PLA
2
activity (P = 0.07, n = 323) and significant support
for dominance effects of the same polymorphism on LDL-C
concentration (P = 0.04, n = 315).
4. Discussion
Genes contribute substantively to the variance in both
Lp-PLA
2
activity and LDL-C concentration in pedigreed
baboons, accounting for approximately one-half of the total
phenotypic variation in each trait. Our estimates of residual
heritability are consistent with previous findings from differ-
ent researchers also describing the substantial effect of genes
on Lp-PLA
2
[5,13] and LDL-C concentration [7,8].
The magnitude of the genetic contributions to phenotypic
variation in both Lp-PLA
2
activity and LDL-C concentra-
tion facilitated the detection of a QTL for each trait, both of
which mapped to a location on PHA13 that corresponds to
HSA2p24.3–p23.2. Both QTLs appear to account for only a
moderate proportion of the individual additive genetic varia-
tion in each trait. Thus, it is likely that other QTLs (undetected
in this analysis) also affect phenotypic variation in each trait,
a conclusion consistent with a complex genetic architecture
for both traits.
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672 A. Vinson et al. / Atherosclerosis 196 (2008) 667–673
Localization of QTLs at the same genetic region for both
Lp-PLA
2
activity and LDL-C concentration is not sufficient
to support the conclusion that the same gene(s) at this QTL
are exerting pleiotropic effects on the two traits, as the cyto-
genetic interval implicated at the QTL may contain many
hundreds of genes. Rather, finding a moderate but statisti-
cally significant QTL-associated genetic correlation between
the traits leads us to propose that the same gene(s) exert a
measurable, pleiotropic influence on coordinated changes in
phenotypic variation in Lp-PLA
2
activity and LDL-C con-
centration reported by others in previous studies of these two
traits [5,6]. Although previous studies of Lp-PLA
2
activity
and LDL-C concentration in humans have reported corre-
lations between both phenotypes, this is the first study to
demonstrate a genetic basis for this phenotypic correlation.
Consistent with our experience in the analysis of com-
plex traits [29], because a substantial proportion of the shared
genetic variance between the two traits was attributable to the
QTL, our bivariate analyses of Lp-PLA
2
activity and LDL-C
levels increased both our confidence in localization of a QTL
and substantially narrowed its support interval in the baboon
genome, and the orthologous region of interest on human
chromosome 2p. However, pleiotropic effects on variation
in Lp-PLA
2
activity and LDL-C concentration at this QTL,
though considerable, are not complete (i.e., the correlation
between the traits due to the QTL is less than one). This
is consistent with sharing by Lp-PLA
2
activity and LDL-C
levels of some, but not all, genetic effects at the QTL. Incom-
plete QTL-specific pleiotropy between Lp-PLA
2
activity and
LDL-C levels could be explained by genes or regulatory ele-
ments with variably correlated effects on the two traits. Such a
set of functional elements may be part of a metabolic or regu-
latory pathway shared by the two phenotypes, e.g., cis-acting
transcription elements such as promoters or enhancers, or
trans-acting phenomena, such as factors affecting transcrip-
tion initiation or regulation.
APOB, a positional candidate gene from the human chro-
mosomal region implicated by our linkage analyses, codes
for the apoB100 isoform, known to be involved in molecular
cascades affecting risk of atherosclerosis. ApoB100 plays a
critical role in the binding of Lp-PLA
2
to the LDL particle [3],
and is the defining protein of LDLs. Genome screens using
data from human populations have localized QTLs to adja-
cent regions of HSA2p for apoB [10,30], total cholesterol
[10,31], and familial combined hyperlipidemia [10,30,32].
Additionally, Austin et al. [33] reported APOB effects on
multiple lipoprotein traits comprising an atherogenic phe-
notype: peak particle diameter of LDL, triglycerides, and
HDL cholesterol levels. Although not conclusive, the results
of our measured genotype analyses in a subset of these
pedigreed baboons lend additional support to APOB as a
positional candidate gene for the pleiotropic QTL detected
in this study. Additional analyses of DNA-level variation in
APOB and other genes within the support interval for this
QTL will be necessary to confirm and expand on our current
results.
In summary, we have localized a QTL with pleiotropic
effects on phenotypic variation in serum Lp-PLA
2
activity
and LDL-C concentration, and provided evidence nominat-
ing APOB as a positional candidate for this QTL, in a baboon
model for studies of the genetics of atherosclerosis risk fac-
tors. To the best of our knowledge, this is the first report
of a QTL affecting both serum Lp-PLA
2
activity and the
concentration of its biological partner, LDL. Because vari-
ation in both phenotypes is associated with cardiovascular
disease risk in humans, we anticipate that subsequent studies
to identify and characterize the genetic variants responsi-
ble for this pleiotropic QTL in these pedigreed baboons
will have tangible implications for our understanding of the
human condition. While genetically and physiologically sim-
ilar to our own species [34], the non-inbred baboons used
in this study belong to pedigrees characterized by relatively
greater size and complexity than those in most human family
studies. Consequently, the study design, analytical methods,
and results from this study can be extrapolated readily to
genetic analyses of Lp-PLA
2
activity and LDL-C concentra-
tion in humans. While experimental control of environmental
contributors to phenotypic variation certainly is greater for
captive animals, currently available analytical methodologies
can accommodate potential environmental covariates in stud-
ies of these traits in humans, particularly when informed by
results from a closely related nonhuman primate species.
Acknowledgements
This study was made possible by research grants from
the National Institutes of Health (P01 HL028972, R01
HL068922, R24 RR008781); a base grant from the National
Center of Research Resources (NCRR) to the South-
west National Primate Research Center (SNPRC; P51
RR013986); and was conducted in facilities constructed with
support from NCRR Research Facilities Improvement Pro-
gram grants (C06 RR014578, C06 RR13556, C06 RR15456,
C06 RR017515). For technical contributions and support we
thank: Ms. T. Baker, Ms. S. Birnbaum, Mr. J. Bridges, Ms.
C. Jett, Mr. P.H. Moore, Jr., Ms. D.E. Newman, Dr. K.S. Rice
and the SNPRC veterinary and animal care staff, Ms. M.L.
Sparks, and Ms. J.F. VandeBerg.
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    • "Here, we describe an important first step toward identifying genetic determinants of atherosclerosis in the rhesus macaque by characterizing the contribution of genes (i.e., heritability) to spontaneous variation in circulating lipids. We elected to study lipid levels first because lipids are well-established risk factors for human atherosclerosis, and because heritability for lipid levels has been demonstrated previously in both humans and in other NHP species [15,16]. Additionally, because significant gender differences in the genetic architecture of lipid levels and lipid metabolism have been demonstrated recently in humans [17-19], and implicated in rhesus macaques [20], we also wanted to investigate potential differences in heritability between male and female macaques for all lipids measured in this study. "
    [Show abstract] [Hide abstract] ABSTRACT: The rhesus macaque is an important model for human atherosclerosis but genetic determinants of relevant phenotypes have not yet been investigated in this species. Because lipid levels are well-established and heritable risk factors for human atherosclerosis, our goal was to assess the heritability of lipoprotein cholesterol and triglyceride levels in a single, extended pedigree of 1,289 Indian-origin rhesus macaques. Additionally, because increasing evidence supports sex differences in the genetic architecture of lipid levels and lipid metabolism in humans and macaques, we also explored sex-specific heritability for all lipid measures investigated in this study. Using standard methods, we measured lipoprotein cholesterol and triglyceride levels from fasted plasma in a sample of 193 pedigreed rhesus macaques selected for membership in large, paternal half-sib cohorts, and maintained on a low-fat, low cholesterol chow diet. Employing a variance components approach, we found moderate heritability for total cholesterol (h2=0.257, P=0.032), LDL cholesterol (h2=0.252, P=0.030), and triglyceride levels (h2=0.197, P=0.034) in the full sample. However, stratification by sex (N=68 males, N=125 females) revealed substantial sex-specific heritability for total cholesterol (0.644, P=0.004, females only), HDL cholesterol (0.843, P=0.0008, females only), VLDL cholesterol (0.482, P=0.018, males only), and triglyceride levels (0.705, P=0.001, males only) that was obscured or absent when sexes were combined in the full sample. We conclude that genes contribute to spontaneous variation in circulating lipid levels in the Indian-origin rhesus macaque in a sex-specific manner, and that the rhesus macaque is likely to be a valuable model for sex-specific genetic effects on lipid risk factors for human atherosclerosis. These findings are a first-ever report of heritability for cholesterol levels in this species, and support the need for expanded analysis of these traits in this population.
    Full-text · Article · Aug 2013 · PLoS ONE
  • Source
    • "The first-generation linkage map was published in 2000 [35] and later improved in 2006 by the addition of more loci in chromosomal regions with insufficient marker density in the initial map [36]. This map has allowed scientists to localize and identify functionally significant genes that influence phenotypic variation related to human health or disease [11,14,373839404142. To further enhance the baboon as a model for biomedical research, we used high-throughput cDNA sequencing (RNA-Seq) to analyze the baboon kidney transcriptome. "
    [Show abstract] [Hide abstract] ABSTRACT: The baboon is an invaluable model for the study of human health and disease, including many complex diseases of the kidney. Although scientists have made great progress in developing this animal as a model for numerous areas of biomedical research, genomic resources for the baboon, such as a quality annotated genome, are still lacking. To this end, we characterized the baboon kidney transcriptome using high-throughput cDNA sequencing (RNA-Seq) to identify genes, gene variants, single nucleotide polymorphisms (SNPs), insertion-deletion polymorphisms (InDels), cellular functions, and key pathways in the baboon kidney to provide a genomic resource for the baboon. Analysis of our sequencing data revealed 45,499 high-confidence SNPs and 29,813 InDels comparing baboon cDNA sequences with the human hg18 reference assembly and identified 35,900 cDNAs in the baboon kidney, including 35,150 transcripts representing 15,369 genic genes that are novel for the baboon. Gene ontology analysis of our sequencing dataset also identified numerous biological functions and canonical pathways that were significant in the baboon kidney, including a large number of metabolic pathways that support known functions of the kidney. The results presented in this study catalogues the transcribed mRNAs, noncoding RNAs, and hypothetical proteins in the baboon kidney and establishes a genomic resource for scientists using the baboon as an experimental model.
    Full-text · Article · Apr 2013 · PLoS ONE
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    [Show abstract] [Hide abstract] ABSTRACT: First Page of the Article
    Preview · Conference Paper · Jan 2005
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