Abstract Background Despite strong evidence for a genetic component to variation in high-density lipoprotein cholesterol levels (HDL-C), specific polymorphisms associated with normal variation in HDL-C have not been identified. It is known, however, that HDL-C levels are influenced in complex ways by factors related to age and sex. In this paper, we examined the evidence for age- and sex-specific linkage of HDL-C in a longitudinal sample of participants from the Framingham Heart Study. To determine if aging could influence our ability to detect linkage, we explored the evidence for linkage of HDL-C at three time points, t1, t2, and t3, spaced approximately 8 years apart and corresponding respectively to visits 11, 15, and 20 for the original cohort and 1, 2, and 4 for the offspring and spouses. Additionally, to examine the effects of sex on linkage at each time point, we estimated the heritability and genetic correlation of HDL-C, performed linkage analysis of HDL-C, tested for genotype-by-sex interaction at a QTL, and performed linkage analysis of HDL-C in males and females separately. Results and Conclusion In women, we found evidence for a QTL on chromosome 2q influencing HDL-C variation. Although the QTL could be detected in the combined sample of males and females at the first time point, the linkage was not significant at subsequent time points

Comuzzie, Anthony G

Dyer, Tom

Martin, Lisa J

North, Kari

Williams, Jeff T

BMC Genetics

PubMed

Kari E North

Lisa J Martin

Tom Dyer

Anthony G Comuzzie

Jeff T Williams

Crossref

HDL cholesterol in females in the Framingham Heart Study is linked to a region of chromosome 2q

Springer - Publisher Connector

BioMed CentralBMC Genetics
ssOpen AcceProceedings
HDL cholesterol in females in the Framingham Heart Study is 
linked to a region of chromosome 2q
Kari E North*1, Lisa J Martin2, Tom Dyer3, Anthony G Comuzzie3 and 
Jeff T Williams3
Address: 1Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, 27514 USA, 2Center for Epidemiology and 
Biostatistics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, 45229 USA and 3Department of Genetics, Southwest Foundation 
for Biomedical Research, San Antonio, Texas, 78245 USA
Email: Kari E North* - kari_north@unc.edu; Lisa J Martin - lisa.martin@cchmc.org; Tom Dyer - tdyer@darwin.sfbr.org; 
Anthony G Comuzzie - agcom@darwin.sfbr.org; Jeff T Williams - jeffw@darwin.sfbr.org
* Corresponding author    
Abstract
Background: Despite strong evidence for a genetic component to variation in high-density
lipoprotein cholesterol levels (HDL-C), specific polymorphisms associated with normal variation in
HDL-C have not been identified. It is known, however, that HDL-C levels are influenced in complex
ways by factors related to age and sex. In this paper, we examined the evidence for age- and sex-
specific linkage of HDL-C in a longitudinal sample of participants from the Framingham Heart Study.
To determine if aging could influence our ability to detect linkage, we explored the evidence for
linkage of HDL-C at three time points, t1, t2, and t3, spaced approximately 8 years apart and
corresponding respectively to visits 11, 15, and 20 for the original cohort and 1, 2, and 4 for the
offspring and spouses. Additionally, to examine the effects of sex on linkage at each time point, we
estimated the heritability and genetic correlation of HDL-C, performed linkage analysis of HDL-C,
tested for genotype-by-sex interaction at a QTL, and performed linkage analysis of HDL-C in males
and females separately.
Results and Conclusion: In women, we found evidence for a QTL on chromosome 2q
influencing HDL-C variation. Although the QTL could be detected in the combined sample of males
and females at the first time point, the linkage was not significant at subsequent time points.
Background
Despite strong evidence for an additive genetic compo-
nent to variation in high-density lipoprotein cholesterol
(HDL-C) levels, specific polymorphisms associated with
normal variation in HDL-C have not been identified. It is
known, however, that HDL-C levels are influenced in
complex ways by factors related to age and sex [1]. With
specific reference to the Framingham Heart Study, Son-
nenberg et al. [2] found that dietary fat and alcohol
showed different relationships to HDL-C in pre- and post-
menopausal women, and Wilson et al. [3] showed that
HDL-C levels declined with advancing age and increasing
obesity. In light of these indications of age and sex differ-
ences in HDL-C variability, we elected to examine the evi-
dence for sex- and age-specific linkage of HDL-C in a
longitudinal sample of participants from the Framingham
Heart Study.
from Genetic Analysis Workshop 13: Analysis of Longitudinal Family Data for Complex Diseases and Related Risk Factors
New Orleans Marriott Hotel, New Orleans, LA, USA, November 11–14, 2002
Published: 31 December 2003
BMC Genetics 2003, 4(Suppl 1):S98
<supplement> <title> <p>Genetic Analysis Workshop 13: Analysis of Longitudinal Family Data for Complex Diseases and Related Risk Factors</p> </title> <editor>Laura Almasy, Christopher I Amos, Joan E Bailey-Wilson, Rita M Cantor, Cashell E Jaquish, Maria Martinez, Rosalind J Neuman, Jane M Olson, Lyle J Palmer, Stephen S Rich, M Anne Spence, Jean W MacCluer</editor> </supplement>
This article is available from: http://www.biomedcentral.com/1471-2156/4/s1/S98Page 1 of 5
(page number not for citation purposes)
BMC Genetics 2003, 4 http://www.biomedcentral.com/1471-2156/4/s1/S98Methods
Data
The study design and methods of the Framingham Heart
Study have been detailed elsewhere [4,5]. Beginning in
1948, 5209 subjects between the ages of 28 and 62 years
were enrolled in the original cohort study and, starting in
1971, 5124 of their offspring and spouses were enrolled.
Participants were invited to attend regular follow-up visits
every 2 to 4 years, for the cohort and offspring groups,
respectively.
We examined fasting HDL-C at time points t1, t2, and t3,
spaced approximately 8 years apart and corresponding
respectively to visits 11, 15, and 20 in the cohort and visits
1, 2, and 4 for the offspring and spouses. We chose the ear-
liest observations to maximize our sample size, and con-
sidered only those individuals for whom complete data
were available for age, sex, and cohort, various age-by-sex
interactions, and cohort effects. Data were also cleaned for
outliers (defined here as any observation greater than 4
standard deviations from the global mean) to reduce the
effect of trait non-normality (kurtosis) on the analysis [6].
The kurtosis of the trimmed dataset for HDL-C is 0.3, 0.5,
and 0.4, at t1, t2, and t3, respectively.
Our final sample size was 1562 participants, including in
total 663 parent-offspring, 1273 sibling, 445 avuncular,
which are aunt/uncle-niece/nephew pairs, and 717 pairs
of first cousins. In all, the sample included information
on nearly 3300 relative pairs.
Analytic methods
Univariate quantitative genetic analysis was done to parti-
tion the phenotypic variance of HDL-C into its additive
genetic and environmental variance components using
maximum likelihood variance decomposition methods.
The initial analysis screened for the following covariates:
sex, age, age-by-sex interaction, cohort, body mass index
(derived from height and weight), drinking status, and
hypertensive status. Any covariates whose effects were sig-
nificant at the p = 0.10 level in the initial analysis were
retained in subsequent analyses, even if the significance
levels decreased after inclusion of other covariates. After
the initial covariate screening, maximum likelihood
methods were used to estimate the effects of covariates
and additive effects of genes.
Next, we generated genome-wide LOD scores for HDL-C
at three time points, implemented in the program package
SOLAR, using the methods detailed by Almasy and Blang-
ero [7]. A pair-wise maximum likelihood-based procedure
was used to estimate multi-point IBD probabilities. To
permit multi-point analysis for QTL mapping, an exten-
sion of the technique of Fulker and colleagues [8] was
employed.
The basic variance components approach can then be
extended to a multivariate framework [9,10]. In the mul-
tivariate linkage model, the phenotype covariance is fur-
ther decomposed to include the genetic correlation
between traits due to additive genetic effects and the
shared effects of the QTL, such that the covariation
between two individuals for two traits is given by:
where a and b can be trait 1 or 2 and ρg is the additive
genetic correlation between the two traits. This approach
has been implemented in SOLAR version 2.0.
We next tested for linkage to HDL-C using a variance-com-
ponents linkage model extended to include genotype-by-
sex interaction at a QTL [11-13]. The expected genetic cov-
ariance between a male and female relative pair i,j is
defined as:
σg ij = 2φij ρg ij σgM σgF + πij ρq ij σqM σqF,
where φij is the coefficient of kinship between the two
individuals, ρg ij is the additive genetic component of the
correlation between the expressions of the trait in the two
sexes, and σgM and σgF are the genetic standard deviations
for males and females, respectively; πij is the probability
that individuals i and j are IBD at a quantitative trait locus
tightly linked to a marker locus; ρq ijis the marker-specific
component of the trait correlation between the sexes; and
σqM and σqF are, respectively, the marker-specific genetic
standard deviations for males and females. Under the null
hypothesis of no genotype-by-sex interaction at the QTL,
the male and female marker-specific variances are equal
(σ2qM = σ2qF).
Lastly, because a significant genotype-by-sex interaction
was found, we generated genome-wide LOD scores for
HDL-C at three time points in males and females sepa-
rately in the program package SOLAR using the methods
detailed by Almasy and Blangero [7].
Results
At t1, t2, and t3, the mean ages of the sample members
from the longitudinal sample were 38.3, 46.5, and 54.8
years, respectively. The residual heritability of HDL-C was
estimated as 0.42 ± 0.05 across all three time points (sexes
combined). Age, sex, and age-by-sex interactions were sig-
nificant between time points, where as cohort effects were
significant only at the last observation, t3. The variance
explained by covariate effects was nearly constant, varying
from 18% at t1 to 20% at t3. In preliminary analyses we
Ω
Ω Ω
Ω Ω
Ω Π Φ
=
= + +
11 12
12 22
2ab q qa qb g ga gb ea ebIˆ ,σ σ ρ σ σ σ σPage 2 of 5
(page number not for citation purposes)
BMC Genetics 2003, 4 http://www.biomedcentral.com/1471-2156/4/s1/S98also considered body mass index (derived from height
and weight), drinking status, and hypertensive status as
covariates (n = 1506; data not shown). The results were
not significantly different from those presented below,
and we did not interpret these analyses further.
The genetic correlations of HDL-C between time points,
for males and females separately, are shown in Table 1.
Measures were highly correlated across all time points,
and the correlations for males and females were not sig-
nificantly different.
In a preliminary genome scan of HDL-C we obtained a
maximum LOD score of 3.4 on chromosome 2 at 150 cM
for the t1 observation. At t2 the maximum LOD score was
0.6 at 120 cM, and at t3 the maximum LOD was 1.1 at 122
cM. Based on these results we chose to restrict further
analysis to chromosome 2 and to examine males and
females separately at each time point. The results of sepa-
rate linkage analyses in males and females are summa-
rized in Figure 1 and Table 2 and suggest that, although
the total additive genetic effect on HDL-C is not signifi-
cantly different in males and females, sex does exert a
strong effect on the QTL-specific variance of HDL-C.
We also considered the possibility of genotype-by-cohort
and genotype-by-sex interactions on the HDL-C linkage,
by formally modeling an interaction between sex and
Table 1: Genetic correlation between HDL-C at three time points for males (upper triangle) and females (lower triangle).
t1 t2 t3
t1 - 1.0 1.0
t2 0.96 ± 0.07 - 0.98 ± 0.06
t3 0.91 ± 0.07 0.88 ± 0.08 -
Table 2: Maximum LOD scores on chromosome 2 in separate linkage analyses of male and female subjects.
HeritabilityA Chromosome 2
Maximum LOD
Centimorgans (cM)
Females
t1 0.48 ± 0.10 3.2200 133.0000
t2 0.42 ± 0.10 1.8600 126.0000
t3 0.38 ± 0.09 2.3600 132.0000
Males
t1 0.62 ± 0.10 0.5200 140.0000
t2 0.50 ± 0.10 0.1600 140.0000
t3 0.51 ± 0.09 0.2900 150.0000
AAll heritabilities significant at p = 0.0001.
Table 3: Genotype×sex linkage results from chromosome 2 at 135 cM.
Mean σg σe σq h2g h2q
Females
t1 58.38 ± 0.89 2.20 ± 2.19 10.16 ± 0.73 9.75 ± 0.93A 0.0200 0.4700
t2 57.70 ± 0.82 5.96 ± 1.86 9.50 ± 0.77 6.51 ± 1.63 0.2100 0.2500
t3 52.48 ± 0.87 5.86 ± 1.81 10.19 ± 0.77 6.94 ± 1.61 0.1800 0.2600
Males
t1 44.64 ± 1.37 7.66 ± 1.25 7.25 ± 0.88 4.25 ± 1.48A 0.4500 0.1400
t2 45.87 ± 1.28 7.56 ± 0.93 7.34 ± 0.72 1.11 ± 2.22 0.5100 0.0100
t3 39.69 ± 1.51 7.78 ± 1.16 8.19 ± 0.70 2.56 ± 2.21 0.4500 0.0500
AAt t1 σq,F ≠ σq,M p = 0.01.Page 3 of 5
(page number not for citation purposes)
BMC Genetics 2003, 4 http://www.biomedcentral.com/1471-2156/4/s1/S98cohort in the linkage analysis (Table 3). All estimates of
genotype-by-cohort interaction were nonsignificant
(results not shown); at t1, however, males and females
showed significantly different genetic variances (p = 0.01).
Discussion
In a longitudinal sample of women from the Framingham
Heart Study we found evidence for a QTL on chromosome
2q influencing HDL-C variation. Although the QTL could
be detected in the combined sample of males and females
at the first time point, the linkage was not significant at
subsequent time points.
In sex-specific analyses, the QTL was detected consistently
in females but not in males. Apart from the interaction
with sex, our results are similar to those of Almasy et al.
[14], who reported a LOD score of 2.3 at 140 cM on chro-
mosome 2 for unesterified HDL-C.
Unfortunately, we did not have the desired covariate data
to evaluate fully other possible sources of change across
the time points, such as the influence of menopause, hor-
mone therapy, oral contraceptive use, and nutrition. We
therefore propose to examine further the evidence for sex-
specific linkage of HDL-C in future studies of the Framing-
ham Heart Study.
A search of genome databases revealed two plausible can-
didate genes located on chromosome 2q near marker
D2S1326; these are the phospholipase A2 receptor 1
(PLA2R1) at 2q23–2q24 and the oxysterol binding pro-
tein-like 6 receptor (OSBPL6) at 2q32.1. Studies have
demonstrated that estradiol affects PLA2R1 activity [15]
and a relationship between secretory phospholipase A2
and HDL-C levels [16,17]. Oxysterol binding protein-like
6 is an intracellular lipid receptor that may have a regula-
tory role in the synthesis of cholesterol [18,19].
Authors' contributions
KEN and LJM performed statistical analyses and inter-
preted results. JW assisted in the interpretation of the
results. TD calculated the mIBDs. AGC participated in the
design of the study. All authors read and approved the
final manuscript.
Acknowledgments
This research was supported in part by National Institutes of Health grants 
HL 45522, HL 28972, GM 31575, MH 59490. The program package SOLAR 
is available at http://www.sfbr.org/sfbr/public/software/solar/index.html.
References
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Genome-wide LOD score plots for HDL-C on chromosome 2 in fe ales (left) and males (right) across all time points, t1 (blue), t2 (gre n), and t3Figure 1
Genome-wide LOD score plots for HDL-C on chromosome 
2 in females (left) and males (right) across all time points, t1 
(blue), t2 (green), and t3Page 4 of 5
(page number not for citation purposes)
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Carolina Digital Repository

BioMed CentralBMC GeneticsssOpen AcceProceedingsHDL cholesterol in females in the Framingham Heart Study is linked to a region of chromosome 2qKari E North*1, Lisa J Martin2, Tom Dyer3, Anthony G Comuzzie3 and Jeff T Williams3Address: 1Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, 27514 USA, 2Center for Epidemiology and Biostatistics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, 45229 USA and 3Department of Genetics, Southwest Foundation for Biomedical Research, San Antonio, Texas, 78245 USAEmail: Kari E North* - kari_north@unc.edu; Lisa J Martin - lisa.martin@cchmc.org; Tom Dyer - tdyer@darwin.sfbr.org; Anthony G Comuzzie - agcom@darwin.sfbr.org; Jeff T Williams - jeffw@darwin.sfbr.org* Corresponding author    AbstractBackground: Despite strong evidence for a genetic component to variation in high-densitylipoprotein cholesterol levels (HDL-C), specific polymorphisms associated with normal variation inHDL-C have not been identified. It is known, however, that HDL-C levels are influenced in complexways by factors related to age and sex. In this paper, we examined the evidence for age- and sex-specific linkage of HDL-C in a longitudinal sample of participants from the Framingham Heart Study.To determine if aging could influence our ability to detect linkage, we explored the evidence forlinkage of HDL-C at three time points, t1, t2, and t3, spaced approximately 8 years apart andcorresponding respectively to visits 11, 15, and 20 for the original cohort and 1, 2, and 4 for theoffspring and spouses. Additionally, to examine the effects of sex on linkage at each time point, weestimated the heritability and genetic correlation of HDL-C, performed linkage analysis of HDL-C,tested for genotype-by-sex interaction at a QTL, and performed linkage analysis of HDL-C in malesand females separately.Results and Conclusion: In women, we found evidence for a QTL on chromosome 2qinfluencing HDL-C variation. Although the QTL could be detected in the combined sample of malesand females at the first time point, the linkage was not significant at subsequent time points.BackgroundDespite strong evidence for an additive genetic compo-nent to variation in high-density lipoprotein cholesterol(HDL-C) levels, specific polymorphisms associated withnormal variation in HDL-C have not been identified. It isknown, however, that HDL-C levels are influenced incomplex ways by factors related to age and sex [1]. Withspecific reference to the Framingham Heart Study, Son-nenberg et al. [2] found that dietary fat and alcoholshowed different relationships to HDL-C in pre- and post-menopausal women, and Wilson et al. [3] showed thatHDL-C levels declined with advancing age and increasingobesity. In light of these indications of age and sex differ-ences in HDL-C variability, we elected to examine the evi-dence for sex- and age-specific linkage of HDL-C in alongitudinal sample of participants from the FraminghamHeart Study.from Genetic Analysis Workshop 13: Analysis of Longitudinal Family Data for Complex Diseases and Related Risk FactorsNew Orleans Marriott Hotel, New Orleans, LA, USA, November 11–14, 2002Published: 31 December 2003BMC Genetics 2003, 4(Suppl 1):S98<supplement> <title> <p>Genetic Analysis Workshop 13: Analysis of Longitudinal Family Data for Complex Diseases and Related Risk Factors</p> </title> <editor>Laura Almasy, Christopher I Amos, Joan E Bailey-Wilson, Rita M Cantor, Cashell E Jaquish, Maria Martinez, Rosalind J Neuman, Jane M Olson, Lyle J Palmer, Stephen S Rich, M Anne Spence, Jean W MacCluer</editor> </supplement>This article is available from: http://www.biomedcentral.com/1471-2156/4/s1/S98Page 1 of 5(page number not for citation purposes)BMC Genetics 2003, 4 http://www.biomedcentral.com/1471-2156/4/s1/S98MethodsDataThe study design and methods of the Framingham HeartStudy have been detailed elsewhere [4,5]. Beginning in1948, 5209 subjects between the ages of 28 and 62 yearswere enrolled in the original cohort study and, starting in1971, 5124 of their offspring and spouses were enrolled.Participants were invited to attend regular follow-up visitsevery 2 to 4 years, for the cohort and offspring groups,respectively.We examined fasting HDL-C at time points t1, t2, and t3,spaced approximately 8 years apart and correspondingrespectively to visits 11, 15, and 20 in the cohort and visits1, 2, and 4 for the offspring and spouses. We chose the ear-liest observations to maximize our sample size, and con-sidered only those individuals for whom complete datawere available for age, sex, and cohort, various age-by-sexinteractions, and cohort effects. Data were also cleaned foroutliers (defined here as any observation greater than 4standard deviations from the global mean) to reduce theeffect of trait non-normality (kurtosis) on the analysis [6].The kurtosis of the trimmed dataset for HDL-C is 0.3, 0.5,and 0.4, at t1, t2, and t3, respectively.Our final sample size was 1562 participants, including intotal 663 parent-offspring, 1273 sibling, 445 avuncular,which are aunt/uncle-niece/nephew pairs, and 717 pairsof first cousins. In all, the sample included informationon nearly 3300 relative pairs.Analytic methodsUnivariate quantitative genetic analysis was done to parti-tion the phenotypic variance of HDL-C into its additivegenetic and environmental variance components usingmaximum likelihood variance decomposition methods.The initial analysis screened for the following covariates:sex, age, age-by-sex interaction, cohort, body mass index(derived from height and weight), drinking status, andhypertensive status. Any covariates whose effects were sig-nificant at the p = 0.10 level in the initial analysis wereretained in subsequent analyses, even if the significancelevels decreased after inclusion of other covariates. Afterthe initial covariate screening, maximum likelihoodmethods were used to estimate the effects of covariatesand additive effects of genes.Next, we generated genome-wide LOD scores for HDL-Cat three time points, implemented in the program packageSOLAR, using the methods detailed by Almasy and Blang-ero [7]. A pair-wise maximum likelihood-based procedurewas used to estimate multi-point IBD probabilities. Topermit multi-point analysis for QTL mapping, an exten-sion of the technique of Fulker and colleagues [8] wasemployed.The basic variance components approach can then beextended to a multivariate framework [9,10]. In the mul-tivariate linkage model, the phenotype covariance is fur-ther decomposed to include the genetic correlationbetween traits due to additive genetic effects and theshared effects of the QTL, such that the covariationbetween two individuals for two traits is given by:where a and b can be trait 1 or 2 and ρg is the additivegenetic correlation between the two traits. This approachhas been implemented in SOLAR version 2.0.We next tested for linkage to HDL-C using a variance-com-ponents linkage model extended to include genotype-by-sex interaction at a QTL [11-13]. The expected genetic cov-ariance between a male and female relative pair i,j isdefined as:σg ij = 2φij ρg ij σgM σgF + πij ρq ij σqM σqF,where φij is the coefficient of kinship between the twoindividuals, ρg ij is the additive genetic component of thecorrelation between the expressions of the trait in the twosexes, and σgM and σgF are the genetic standard deviationsfor males and females, respectively; πij is the probabilitythat individuals i and j are IBD at a quantitative trait locustightly linked to a marker locus; ρq ijis the marker-specificcomponent of the trait correlation between the sexes; andσqM and σqF are, respectively, the marker-specific geneticstandard deviations for males and females. Under the nullhypothesis of no genotype-by-sex interaction at the QTL,the male and female marker-specific variances are equal(σ2qM = σ2qF).Lastly, because a significant genotype-by-sex interactionwas found, we generated genome-wide LOD scores forHDL-C at three time points in males and females sepa-rately in the program package SOLAR using the methodsdetailed by Almasy and Blangero [7].ResultsAt t1, t2, and t3, the mean ages of the sample membersfrom the longitudinal sample were 38.3, 46.5, and 54.8years, respectively. The residual heritability of HDL-C wasestimated as 0.42 ± 0.05 across all three time points (sexescombined). Age, sex, and age-by-sex interactions were sig-nificant between time points, where as cohort effects weresignificant only at the last observation, t3. The varianceexplained by covariate effects was nearly constant, varyingfrom 18% at t1 to 20% at t3. In preliminary analyses weΩΩ ΩΩ ΩΩ Π Φ== + +11 1212 222ab q qa qb g ga gb ea ebIˆ ,σ σ ρ σ σ σ σPage 2 of 5(page number not for citation purposes)BMC Genetics 2003, 4 http://www.biomedcentral.com/1471-2156/4/s1/S98also considered body mass index (derived from heightand weight), drinking status, and hypertensive status ascovariates (n = 1506; data not shown). The results werenot significantly different from those presented below,and we did not interpret these analyses further.The genetic correlations of HDL-C between time points,for males and females separately, are shown in Table 1.Measures were highly correlated across all time points,and the correlations for males and females were not sig-nificantly different.In a preliminary genome scan of HDL-C we obtained amaximum LOD score of 3.4 on chromosome 2 at 150 cMfor the t1 observation. At t2 the maximum LOD score was0.6 at 120 cM, and at t3 the maximum LOD was 1.1 at 122cM. Based on these results we chose to restrict furtheranalysis to chromosome 2 and to examine males andfemales separately at each time point. The results of sepa-rate linkage analyses in males and females are summa-rized in Figure 1 and Table 2 and suggest that, althoughthe total additive genetic effect on HDL-C is not signifi-cantly different in males and females, sex does exert astrong effect on the QTL-specific variance of HDL-C.We also considered the possibility of genotype-by-cohortand genotype-by-sex interactions on the HDL-C linkage,by formally modeling an interaction between sex andTable 1: Genetic correlation between HDL-C at three time points for males (upper triangle) and females (lower triangle).t1 t2 t3t1 - 1.0 1.0t2 0.96 ± 0.07 - 0.98 ± 0.06t3 0.91 ± 0.07 0.88 ± 0.08 -Table 2: Maximum LOD scores on chromosome 2 in separate linkage analyses of male and female subjects.HeritabilityA Chromosome 2Maximum LODCentimorgans (cM)Femalest1 0.48 ± 0.10 3.2200 133.0000t2 0.42 ± 0.10 1.8600 126.0000t3 0.38 ± 0.09 2.3600 132.0000Malest1 0.62 ± 0.10 0.5200 140.0000t2 0.50 ± 0.10 0.1600 140.0000t3 0.51 ± 0.09 0.2900 150.0000AAll heritabilities significant at p = 0.0001.Table 3: Genotype×sex linkage results from chromosome 2 at 135 cM.Mean σg σe σq h2g h2qFemalest1 58.38 ± 0.89 2.20 ± 2.19 10.16 ± 0.73 9.75 ± 0.93A 0.0200 0.4700t2 57.70 ± 0.82 5.96 ± 1.86 9.50 ± 0.77 6.51 ± 1.63 0.2100 0.2500t3 52.48 ± 0.87 5.86 ± 1.81 10.19 ± 0.77 6.94 ± 1.61 0.1800 0.2600Malest1 44.64 ± 1.37 7.66 ± 1.25 7.25 ± 0.88 4.25 ± 1.48A 0.4500 0.1400t2 45.87 ± 1.28 7.56 ± 0.93 7.34 ± 0.72 1.11 ± 2.22 0.5100 0.0100t3 39.69 ± 1.51 7.78 ± 1.16 8.19 ± 0.70 2.56 ± 2.21 0.4500 0.0500AAt t1 σq,F ≠ σq,M p = 0.01.Page 3 of 5(page number not for citation purposes)BMC Genetics 2003, 4 http://www.biomedcentral.com/1471-2156/4/s1/S98cohort in the linkage analysis (Table 3). All estimates ofgenotype-by-cohort interaction were nonsignificant(results not shown); at t1, however, males and femalesshowed significantly different genetic variances (p = 0.01).DiscussionIn a longitudinal sample of women from the FraminghamHeart Study we found evidence for a QTL on chromosome2q influencing HDL-C variation. Although the QTL couldbe detected in the combined sample of males and femalesat the first time point, the linkage was not significant atsubsequent time points.In sex-specific analyses, the QTL was detected consistentlyin females but not in males. Apart from the interactionwith sex, our results are similar to those of Almasy et al.[14], who reported a LOD score of 2.3 at 140 cM on chro-mosome 2 for unesterified HDL-C.Unfortunately, we did not have the desired covariate datato evaluate fully other possible sources of change acrossthe time points, such as the influence of menopause, hor-mone therapy, oral contraceptive use, and nutrition. Wetherefore propose to examine further the evidence for sex-specific linkage of HDL-C in future studies of the Framing-ham Heart Study.A search of genome databases revealed two plausible can-didate genes located on chromosome 2q near markerD2S1326; these are the phospholipase A2 receptor 1(PLA2R1) at 2q23–2q24 and the oxysterol binding pro-tein-like 6 receptor (OSBPL6) at 2q32.1. Studies havedemonstrated that estradiol affects PLA2R1 activity [15]and a relationship between secretory phospholipase A2and HDL-C levels [16,17]. Oxysterol binding protein-like6 is an intracellular lipid receptor that may have a regula-tory role in the synthesis of cholesterol [18,19].Authors' contributionsKEN and LJM performed statistical analyses and inter-preted results. JW assisted in the interpretation of theresults. TD calculated the mIBDs. AGC participated in thedesign of the study. All authors read and approved thefinal manuscript.AcknowledgmentsThis research was supported in part by National Institutes of Health grants HL 45522, HL 28972, GM 31575, MH 59490. The program package SOLAR is available at http://www.sfbr.org/sfbr/public/software/solar/index.html.References1. Emond MJ, Zareba W: Prognostic value of cholesterol inwomen of different ages. J Womens Health 1997, 6:295-307.2. Sonnenberg LM, Quatromoni PA, Gagnon DR, Cupples LA, FranzMM, Ordovas JM, Wilson PW, Schaefer EJ, Millen BE: Diet andplasma lipids in women. II. Macronutrients and plasma trig-lycerides, high-density lipoprotein, and the ratio of total tohigh-density lipoprotein cholesterol in women: the Framing-ham nutrition studies. J Clin Epidemiol 1996, 49:665-672.3. Wilson PW, Anderson KM, Harris T, Kannel WB, Castelli WP:Determinants of change in total cholesterol and HDL-C withage: the Framingham Study. J Gerontol 1994, 49:M252-M257.Genome-wide LOD score plots for HDL-C on chromosome 2 in fe ales (left) and males (right) across all time points, t1 (blue), t2 (gre n), and t3Figure 1Genome-wide LOD score plots for HDL-C on chromosome 2 in females (left) and males (right) across all time points, t1 (blue), t2 (green), and t3Page 4 of 5(page number not for citation purposes)BMC Genetics 2003, 4 http://www.biomedcentral.com/1471-2156/4/s1/S98Publish with BioMed Central   and  every scientist can read your work free of charge"BioMed Central will be the most significant development for disseminating the results of biomedical research in our lifetime."Sir Paul Nurse, Cancer Research UKYour research papers will be:available free of charge to the entire biomedical communitypeer reviewed and published immediately upon acceptancecited in PubMed and archived on PubMed Central yours — you keep the copyrightSubmit your manuscript here:http://www.biomedcentral.com/info/publishing_adv.aspBioMedcentral4. Dawber TR, Meadors G, Moore F: Epidemiological approachesto heart disease: the Framingham Study. Am J Public Health1951, 41:279-286.5. Kannel WB, Feinleib M, McNamara PM, Garrison RJ, Castelli WP: Aninvestigation of coronary heart disease in families. TheFramingham offspring study. Am J Epidemiol 1979, 110:281-290.6. Blangero J, Williams JT, Almasy L: Variance component methodsfor detecting complex trait loci. Adv Genet 2001, 42:151-181.7. Almasy L, Blangero J: Multipoint quantitative-trait linkage anal-ysis in general pedigrees. Am J Hum Genet 1998, 62:1198-1211.8. Fulker DW, Cherny SS, Cardon LR: Multipoint interval mappingof quantitative trait loci, using sib pairs. Am J Hum Genet 1995,56:1224-1233.9. Hopper JL, Mathews JD: Extensions to multivariate normalmodels for pedigree analysis. Ann Hum Genet 1982, 46:373-383.10. Blangero J, Williams-Blangero S, Kammerer CM, Towne B, Konigs-berg LW: Multivariate genetic analysis of nevus measure-ments and melanoma. Cytogenet Cell Genet 1992, 59:179-181.11. Robertson A: The sampling variance of the genetic correlationcoefficient. Biometrics 1959, 15:469-485.12. Eisen EJ, Legates JE: Genotype-sex interaction and the geneticcorrelation between the sexes for body weight in Musmusculus. Genetics 1966, 54:611-623.13. Towne B, Blangero J, Siervogel RM: Genotype by sex interactionin measures of lipids, lipoproteins, and apolipoproteins. GenetEpidemiol 1993, 10:611-616.14. Almasy L, Hixson JE, Rainwater DL, Cole S, Williams JT, Mahaney MC,VandeBerg JL, Stern MP, MacCluer JW, Blangero J: Human pedi-gree-based quantitative-trait-locus mapping: localization oftwo genes influencing HDL-cholesterol metabolism. Am JHum Genet 1999, 64:1686-1693.15. Periwal SB, Farooq A, Bhargava VL, Bhatla N, Vij U, Murugesan K:Effect of hormones and antihormones on phospholipase A2activity in human endometrial stromal cells. Prostaglandins1996, 51:191-201.16. Petrovic N, Grove C, Langton PE, Misso NL, Thompson PJ: A simpleassay for a human serum phospholipase A2 that is associatedwith high-density lipoproteins. J Lipid Res 2001, 42:1706-1713.17. Tietge UJ, Maugeais C, Lund-Katz S, Grass D, deBeer FC, Rader DJ:Human secretory phospholipase A2 mediates decreasedplasma levels of HDL cholesterol and apoA-I in response toinflammation in human apoA-I transgenic mice. ArteriosclerThromb Vasc Biol 2002, 22:1213-1218.18. Patel NT, Thompson EB: Human oxysterol-binding protein. I.Identification and characterization in liver. J Clin EndocrinolMetab 1990, 71:1637-1645.19. Schroepfer GJ Jr: Oxysterols: modulators of cholesterolmetabolism and other processes. Physiol Rev 2000, 80:361-554.Page 5 of 5(page number not for citation purposes)

Almasy L: Variance component methods for detecting complex trait loci. Adv Genet

Diet and plasma lipids in women. II. Macronutrients and plasma triglycerides, high-density lipoprotein, and the ratio of total to high-density lipoprotein cholesterol in women: the Framingham nutrition studies.

F: Epidemiological approaches to heart disease: the Framingham Study.

Human oxysterol-binding protein. I. Identification and characterization in liver.

Human pedigree-based quantitative-trait-locus mapping: localization of two genes influencing HDL-cholesterol metabolism.

Human secretory phospholipase A2 mediates decreased plasma levels of HDL cholesterol and apoA-I in response to inflammation in human apoA-I transgenic mice. Arterioscler Thromb Vasc Biol

Jr: Oxysterols: modulators of cholesterol metabolism and other processes. Physiol Rev

Konigsberg LW: Multivariate genetic analysis of nevus measurements and melanoma. Cytogenet Cell Genet

Legates JE: Genotype-sex interaction and the genetic correlation between the sexes for body weight in Mus musculus. Genetics

LR: Multipoint interval mapping of quantitative trait loci, using sib pairs.

Mathews JD: Extensions to multivariate normal models for pedigree analysis. Ann Hum Genet

Multipoint quantitative-trait linkage analysis in general pedigrees.

Murugesan K: Effect of hormones and antihormones on phospholipase A2 activity in human endometrial stromal cells. Prostaglandins

PJ: A simple assay for a human serum phospholipase A2 that is associated with high-density lipoproteins.

Siervogel RM: Genotype by sex interaction in measures of lipids, lipoproteins, and apolipoproteins. Genet Epidemiol

The sampling variance of the genetic correlation coefficient. Biometrics

WP: An investigation of coronary heart disease in families. The Framingham offspring study.

Zareba W: Prognostic value of cholesterol in women of different ages.

http://cdr.lib.unc.edu/downloads/73666692w

HDL cholesterol in females in the Framingham Heart Study is linked to a region of chromosome 2q

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