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Genome-wide association of echocardiographic dimensions,brachial artery endothelial function and treadmill exercise
responses in the Framingham Heart Study
Ramachandran S Vasan*1,2, Martin G Larson1,3, Jayashri Aragam4,
Thomas J Wang5, Gary F Mitchell6, Sekar Kathiresan5,7, Christopher NewtonCheh5,7, Joseph A Vita2, Michelle J Keyes1,3, Christopher J O'Donnell1,8,Daniel Levy1,8 and Emelia J Benjamin1,2
Address: 1The National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, USA, 2Evans Department of Medicine andWhitaker Cardiovascular Institute, Boston University School of Medicine, Boston, MA, USA, 3Department of Mathematics and Statistics, Boston
University, Boston, MA, USA, 4Veterans Administration Hospital, West Roxbury, MA, USA, 5Cardiology Division, Massachusetts General Hospital,
Harvard Medical School, Boston, MA, USA, 6Cardiovascular Engineering, Inc., Waltham, MA, USA, 7Program in Medical and Population Genetics,
Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA and 8National Heart, Lung, and Blood
Institute, National Institutes of Health, Bethesda, MD, USA
Email: Ramachandran S Vasan* - vasan@bu.edu; Martin G Larson - mlarson@bu.edu; Jayashri Aragam - Jayashri.Aragam@va.gov;
Thomas J Wang - tjwang@partners.org; Gary F Mitchell - GaryFMitchell@mindspring.com; Sekar Kathiresan - skathiresan1@partners.org;
Christopher Newton-Cheh - cnewtoncheh@partners.org; Joseph A Vita - jvita@bu.edu; Michelle J Keyes - mjkeyes@bu.edu;
Christopher J O'Donnell - codonnell@nih.gov; Daniel Levy - levyd@nih.gov; Emelia J Benjamin - emelia@bu.edu* Corresponding author

Published: 19 September 2007
<supplement>
S Vasan</editor><title><note>Research</note><p>The Framingham <url>http://www.biomedcentral.com/content/pdf/1471-2350-8-S1-info.pdf</url>
Heart Study 100,000 single nucleotide polymorphisms resource</p> </title> <editor>Emelia</supplement>
J Benjamin, Caroline S Fox, Daniel J Gottlieb, Cashell E Jaquish, Daniel Levy, James B Meigs, Christopher Newton-Cheh, Christopher J O'Donnell and Ramachandran

BMC Medical Genetics 2007, 8(Suppl 1):S2

doi:10.1186/1471-2350-8-S1-S2This article is available from: http://www.biomedcentral.com/1471-2350/8/S1/S2© 2007 Vasan et al; licensee BioMed Central Ltd.
This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0),
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract
Background: Echocardiographic left ventricular (LV) measurements, exercise responses to standardized treadmill test
(ETT) and brachial artery (BA) vascular function are heritable traits that are associated with cardiovascular disease risk.
We conducted a genome-wide association study (GWAS) in the community-based Framingham Heart Study.
Methods: We estimated multivariable-adjusted residuals for quantitative echocardiography, ETT and BA function traits.
Echocardiography residuals were averaged across 4 examinations and included LV mass, diastolic and systolic dimensions,wall thickness, fractional shortening, left atrial and aortic root size. ETT measures (single exam) included systolic bloodpressure and heart rate responses during exercise stage 2, and at 3 minutes post-exercise. BA measures (single exam)included vessel diameter, flow-mediated dilation (FMD), and baseline and hyperemic flow responses. Generalized
estimating equations (GEE), family-based association tests (FBAT) and variance-components linkage were used to relate
multivariable-adjusted trait residuals to 70,987 SNPs (Human 100K GeneChip, Affymetrix) restricted to autosomal SNPs
with minor allele frequency ≥0.10, genotype call rate ≥0.80, and Hardy-Weinberg equilibrium p ≥ 0.001.
Results: We summarize results from 17 traits in up to 1238 related middle-aged to elderly men and women. Results of
all association and linkage analyses are web-posted at http://ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007.
We confirmed modest-to-strong heritabilities (estimates 0.30–0.52) for several Echo, ETT and BA function traits.
Overall, p < 10-5 in either GEE or FBAT models were observed for 21 SNPs (nine for echocardiography, eleven for ETT
and one for BA function). The top SNPs associated were (GEE results): LV diastolic dimension, rs1379659 (SLIT2, p =1.17*10-7); LV systolic dimension, rs10504543 (KCNB2, p = 5.18*10-6); LV mass, rs10498091 (p = 5.68*10-6); Left atrial
size, rs1935881 (FAM5C, p = 6.56*10-6); exercise heart rate, rs6847149 (NOLA1, p = 2.74*10-6); exercise systolic blood

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pressure, rs2553268 (WRN, p = 6.3*10-6); BA baseline flow, rs3814219 (OBFC1, 9.48*10-7), and FMD, rs4148686 (CFTR,
p = 1.13*10-5). Several SNPs are reasonable biological candidates, with some being related to multiple traits suggestingpleiotropy. The peak LOD score was for LV mass (4.38; chromosome 5); the 1.5 LOD support interval included NRG2.
Conclusion: In hypothesis-generating GWAS of echocardiography, ETT and BA vascular function in a moderate-sizedcommunity-based sample, we identified several SNPs that are candidates for replication attempts and we provide a webbased GWAS resource for the research community.

Background
Cardiovascular disease (CVD) is a leading cause of morbidity and mortality in the United States [1]. It is increasingly recognized that CVD is a life-course disease, withovert events being antedated by subclinical cardiovasculartarget organ damage [2,3]. Current research indicates afundamental role of left ventricular (LV) chamber size,
wall thickness (LV remodeling) and mass (LVM) in thepathogenesis of high blood pressure [4,5], and clinical
CVD [6,7], including stroke [8,9] and heart failure [1012]. On a parallel note, exercise treadmill stress testing(ETT) is used routinely to evaluate patients with chest
pain suggestive of ischemic etiology and for identifying
individuals at intermediate pre-test probability of CVD
who are more likely to develop clinical events [13]. Likewise, endothelial dysfunction, as assessed via brachialartery (BA) flow-mediated dilation (FMD), has emerged
as a fundamental component of atherosclerosis and a precursor of overt CVD [14-16]. Thus, traits obtained via
echocardiography (Echo), testing for BA endothelial function and ETT can serve as intermediate phenotypes in thepathway from standard risk factor to overt CVD. Suchintermediate phenotypes have been studied extensively tocharacterize their clinical and genetic correlates, havebeen reported to be heritable traits [14,17-28], and havebeen linked to select genetic loci in several reports [2931].
More recently, several investigators have proposed
genome-wide association studies (GWAS) as a strategy tomap causal genes with modest influences on traits associated with complex diseases such as CVD [32,33]. The
availability of 100K genotype data on a subset of related
Framingham Heart Study participants [34] provides aunique opportunity to conduct both genome-wide association and linkage analyses to explore the genetic underpinnings of LV remodeling, endothelial function andexercise performance in a community-based sample.

Methods
The design and selection criteria of the Original Framingham Study [35] and the Offspring Study [36] have been
described elsewhere. As detailed in the Overview [37],1345 participants (1087 Offspring and 258 Original
Cohort) underwent genotyping using the Affymetrix
GeneChip Human Mapping 100K single nucleotide poly-morphism (SNP) set [34]. Participants were eligible forthe present investigation if they had available genotypes
and the echocardiographic, vascular and ETT traits ofinterest (as defined below). The Institutional Review
Board at Boston University Medical Center approved thestudy and all participants gave written informed consent(including for genetic research).
Measurement of phenotypes
Echocardiography
All attendees underwent routine transthoracic twodimensionally-guided M-mode echocardiography at thesecond (1979–1982), fourth (1987–1990), fifth (1991–
1995) and sixth (1996–1998) Offspring cohort examinations. Echocardiographic equipment for image acquisition varied across these examinations: at examination
cycle 2, a Hoffrel 201 ultrasound receiver (and Aerotechtransducer) was used; at examinations 4 and 5, a Hewlett
Packard (model 77020AC) ultrasound machine was used;
at examination 6 images were acquired using a Sonos
1000 Hewlett-Packard machine. At all four examinations,however, measurements of LV internal dimension in diastole (LVDD) and systole (LVDS), the thicknesses of theposterior wall (PW) and interventricular septum (IVS),
and the diameters of the aortic root (all measured at enddiastole) and left atrium (LA) at end-systole wereobtained by using a 'leading edge' technique [38], averaging measurements in 3 cardiac cycles according to theAmerican Society of Echocardiography guidelines. We calculated LV wall thickness (LVWT) as the sum of PW andIVS measurements. LV mass was calculated by using theformula 0.8[1.04(LVDD+IVS+PW)3 - (LVDD)3] + 0.6 [39].
The reproducibility of Echo measurements was systematically assessed at the sixth examination [40].
ETT measures
At the second Offspring examination (1978–1981), allattendees underwent submaximal exercise test according
to the standard Bruce protocol for up to five incremental
3-minute stages. The test was terminated (without a cool
down period) when participants reached their target heart
rate (85% age-predicted peak heart rate). Blood pressure
measurements and electrocardiograms were recorded during exercise at the midpoint of each 3-minute exercise
stage, and for each minute for up to 4 minutes into therecovery period.
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BA endothelial function
As described previously [14], BA flow-mediated dilation(FMD; percent change in diameter from baseline; i.e. 100* [hyperemic diameter at 1 minute - baseline diameter]/baseline diameter) and mean hyperemic flow velocity(cm/sec) were determined during the seventh clinicalexamination cycle (1998–2001). A Toshiba SSH-140A
ultrasound system with a 7.5 MHz linear array transducer
and commercially available software (Brachial Analyzer
version 3.2.3, Medical Imaging Applications) were used.
Investigators, blinded to participant clinical and genetic
data, determined brachial artery diameter at baseline and1 minute after reactive hyperemia induced by 5-minuteforearm cuff occlusion. The coefficient of variation forbaseline and hyperemic diameters were 0.5% and 0.7%,
respectively.

Doppler flow was assessed at baseline and during reactive
hyperemia using a 3.75 MHz carrier frequency and withcorrection for the insonation angle [41]. Mean baselineand hyperemic flow velocities were analyzed from digitized audio data using semiautomated signal averaging(Cardiovascular Engineering, Waltham, MA). Baselineand deflation flow measurements were reproducible on
repeated analysis of 30 subjects with correlations of >0.98.
Genotyping methods
The Overview [37] details the genotyping performed with
the Affymetrix 100K SNP GeneChip http://gmed.bu.edu/
about/genotyping.html[34] and with the Marshfield STR
marker set at the Mammalian Genotyping Service http://
research.marshfieldclinic.org/genetics.
Statistical methods
We generated normalized sex-specific residuals adjustingfor the following covariates: for the echocardiographic
phenotypes, age, sex, height, weight, smoking, systolicand diastolic blood pressure, hypertension treatment; for
ETT measures, age, sex, body mass index, baseline heartrate, diabetes, smoking, ratio of total to high-density lipoprotein cholesterol, and treatment for hypertension (additional adjustments for select variables is detailed in Table1); for BA function, a set of 15 covariates previously
reported [14] to be associated with endothelial functionin our sample (see Table 1). Covariates were from thesame exam as the phenotype measures. Next, we used
residuals for the phenotypes of interest to test for potential association with 100K SNPs using additive familybased association tests (FBAT) and linear regression models with general estimating equations (GEE; additive
genetic models) to account for correlation among related
individuals from nuclear families, as detailed in the Overview [37]. We chose 70,987 SNPS for association analysis
that met the following criteria: autosomal SNPs with genotypic call rate ≥80%, minor allele frequency ≥10%,

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Hardy-Weinberg equilibrium test p ≥0.001, and ≥10
informative families for FBAT. The choice of an 80% genotyping call rate threshold may appear unusually liberal.
We chose this threshold to be more inclusive in terms of
associations reported. Also, the algorithm for the genotype calls was the Dynamic Modeling algorithm, which isless precise than other algorithms that have been introduced more recently. The association analyses were complemented by linkage analyses that used variancecomponents methods and a subset of 100K markers andMarshfield STRs; the selection of markers and methods forcalculating identity-by-descent are also described in the
Overview [37].
We used an unfiltered approach and report the top 25
SNPs associated with echocardiographic traits, ETT measures and BA phenotypes (15, 5 and 5 SNPs, respectively;
relative proportions chosen empirically because of thelarger number of echocardiographic traits analyzed)
according to their degree of statistical significance (lowest
p values) in GEE and FBAT models separately. For
echocardiographic phenotypes, we analyzed the mean ofvalues for traits averaged across the 4 examinations, aswell as traits at individual examinations separately. In
order to evaluate potential pleiotropic effects, we examined SNP associations across related sets of traits andlisted the top 25 SNPs with the lowest geometric mean ofp values for all echocardiographic traits (averaged acrossthe four examinations), for all ETT measures and for all
BA traits (15, 5 and 5 SNPs, respectively, for the 3 groups).
Because we analyzed individual echocardiographic traits
at each of the four examinations, we also listed the top
SNP associations based on the geometric mean of p values
for these individual echocardiographic traits across thefour examinations. Thus, we use the term 'pleiotropic
effects' to refer to whether there were SNPs that were associated with multiple traits within the 3 subgroups. Additionally, we examined associations of SNPs in or within
200 Kb of the start or terminus of six selected genes (ACE,
AGT, AGTR1, ADRB1, VEGF, NOS3) that have been previously reported to be associated with Echo, ETT and BA
function phenotypes [30,42-51]. We view these analyses
as exploratory because the coverage of the Affymetrix
100K GeneChip for these genes was quite limited.

Results
Table 1 lists the phenotypes analyzed from the threegroups (Echo, ETT and BA endothelial function), thenumber of traits evaluated within each group, and thecovariates included in regression models to create residuals. We observed moderate to high heritability of most of
the traits evaluated (Table 1; estimates are multivariableadjusted, for covariates noted above under methods, andlisted in table footnote). Heritability estimates were 52%
for aortic root dimension, 36–40% for LV mass, internal

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http://www.biomedcentral.com/1471-2350/8/S1/S2Table 1: Echocardiographic, exercise testing and brachial artery function traits analyzed in participants with 100K genotype data

Trait

Number of Traits*

Offspring Exam cycles

Adjustment†

Heritability- age- and sex- multivariable-**0.36

A. Echocardiographic Traits Averaged Across 4 Examinations
LV mass (LVM)

10

2,4,5,6

LV diastolic dimension (LVDD)
LV systolic dimension (LVDS)
LV wall thickness (LVWT)
LV fractional shortening (LVFS)
Left atrial diameter (LAD)
Aortic root diameter (AOR)

10
10
10
10
10
10

2,4,5,6
2,4,5,6
2,4,5,6
2,4,5,6
2,4,5,6
2,4,5,6Stage 2 Exercise systolic blood pressure (SBP)22Stage 2 Exercise diastolic blood pressure (DBP)
Stage 2 Exercise heart rate
Post-exercise 3 minute recovery SBP
Post-exercise 3 minute recovery DBP
Post-exercise 3 minute recovery heart rate

2
2
2
2
2

2
2
2
2
2

Baseline BA diameter2

7

Baseline BA flow velocity
BA flow-mediated dilation (FMD) percent
BA hyperemic flow velocity

2
2
2

7
7
7

0.38
0.30
0.41
0.20
0.25
0.52

B. Exercise Treadmill Test (ETT) Traits- age- and sex- multivariable-**

0.28
0.22
0.25
0.20
0.16
0.40

C. Brachial Artery (BA) Endothelial Function Traits- age- and sex- multivariable-**

0.25
0.32
0.19
0.06

BA = brachial artery. LV = left ventricular. SBP = systolic blood pressure. DBP = diastolic blood pressure.
* For Echo traits, the phenotypes listed include those based on averaged values across 4 examinations. Overall, the number of Echo phenotypes
includes individual traits at each exam (× 2 for two levels of adjustment in models) plus the averaged traits across 4 exams (× 2 for two levels of
adjustment in models) listed above. For ETT and BA traits, the number of individual traits includes traits at single exams (× 2 for two levels of
adjustment in models).
**covariates in multivariable models include:
For Echo phenotypes: age, sex, height, weight, smoking, systolic blood pressure, diastolic blood pressure, hypertension treatment.
For ETT phenotypes: age, sex, BMI, diabetes, current smoking, baseline heart rate, hypertension treatment, total/HDL cholesterol. Additional
adjustments were ETT phenotype-specific: Exercise SBP was also adjusted for systolic BP at rest; exercise DBP for diastolic BP at rest; exercise
heart rate for heart rate at rest; Recovery SBP for systolic BP at rest, systolic BP during second stage of exercise, and peak systolic BP during
exercise; Recovery DBP for diastolic BP at rest, diastolic BP during second stage of exercise, and peak diastolic BP during exercise; and recovery
heart rate for heart rate at rest, during second stage of exercise, and peak heart rate during exercise.
For BA phenotypes: age, sex, mean arterial pressure, pulse pressure, heart rate, diabetes, body mass index, fasting blood glucose, prevalentcardiovascular disease, hormone replacement therapy use, walk test before and after BA test, Total/HDL cholesterol, smoking within 6 hrs of BA
test, hypertension, lipid-lowering treatment use.

dimensions and LVWT, and 25% for LA size. Estimates for
ETT measures varied from 41% for post-exercise recovery
heart rate, 28% for exercise systolic blood pressure, and
16–25% for other phenotypes. For BA function, baseline
flow velocity and vessel diameter were most heritable (32and 25%, respectively) and hyperemic flow the least(6%), with intermediate values for FMD (19%).
Results of all association analyses and detailed linkage
results are web-posted at http://ncbi.nlm.nih.gov/
projects/gap/cgi-bin/study.cgi?id=phs000007, the database of genotype and phenotype public repository(dbGaP) at the National Center for Biotechnology Infor-

mation. Overall, nine SNPs yielded a p value <10-5 ineither GEE or FBAT models for Echo traits. Eleven SNPs
were associated with ETT traits with a p value <10-5, andone SNP yielded a p value below this threshold for BA
function traits. A conservative Bonferroni correction for
the number of statistical tests (0.05/1,000,000) yields anapproximate threshold of genome-wide significance of
5*10-8.
Table 2A displays the 25 most significantly associated
SNPs in GEE analyses (15 for echo phenotypes; 5 each for
ETT and BA phenotypes; additive genetic models) sorted
by p values along with the corresponding p value using

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FBAT. The top SNPs associated with averaged Echo traits
included: rs1379659 and rs666088 (both in SLIT2) with
LV diastolic dimension, rs1935881 (FAM5C) andrs10493389 (PDE4B) with LA diameter, and rs10504543(KCNB2) with LV systolic dimension. The top SNPs associated with ETT traits included: rs6847149 (NOLA1) andrs2056387 (RYR2) with stage 2 exercise heart rate, andrs2553268 (WRN) with stage 2 exercise systolic bloodpressure. The top 5 SNPs associated with BA traits
included rs3814219 (OBFC1) and rs10515508 (NRG2)
with BA baseline flow, and rs4148686 (CFTR) with FMD.
Only one of these SNPs (SLIT2) had a p value < 10-3 in
FBAT.
Table 2B lists the top 25 SNPs associated with phenotypes
in FBAT along with corresponding p values in GEE models. Only one of these SNPs (rs1959290 associated with
LV systolic dimension) had a p value < 10-3 in GEE models. The top 5 SNPs associated with ETT traits included
rs1029947 and rs1029946 (both in PRKAG2) with heart
rate at 3 minutes of post-exercise recovery. The top 5 SNPs
associated with BA traits included rs2389866 (PDE5A).
Table 2C lists the magnitude and the location of loci with
LOD scores that exceeded 2.0. The peak LOD scores were:for Echo traits, 4.38 (chromosome 5) for LV mass and4.23 (chromosome 3) for aortic root size; for ETT traits,
2.93 (chromosome 5), 2.46 (chromosome 1), and 2.43
(chromosome 22) for heart rate during stage 2 of exercise;for BA traits, 2.14 (chromosome 8) for baseline flow
velocity.
Table 3 evaluates the potential pleiotropic effect of SNPs
by evaluating the geometric mean of p values for associations across averaged echo, and single-exam ETT and BA
traits, and by relating them to the individual Echo traits
across 4 examinations. SNPs associated with 4 genes(SLIT2, WDR72, UBE2L3 and KCNB2) were related toindividual echo traits across examinations, as well as associated with the averaged Echo traits. Likewise, RYR2 wasassociated with a low geometric p value when related to
all ETT traits across the examination.
Table 4A–C displays results of association of Echo, ETT
and BA function traits with SNPs in proximity to 6 genes(within 200 Kb of the start or terminus) chosen from thepublished literature; as noted earlier, the Affymetrix 100K
GeneChip does not cover SNPs within these genes adequately. We observed weak associations of several SNPs in
proximity to the genes of interest and Echo, ETT and BA
function traits, none of which had a p value < 10-3). It isnoteworthy, though, that several SNPs in proximity to
ADRB1, AGT, and AGTR1 were associated weakly (p valueof 0.05 to 10-3) with several Echo, ETT and BA function
phenotypes.

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Discussion
Principal findings
We report results of GWAS of Echo, ETT and BA function
traits in a moderate-size community-based sample using
several complementary analytical approaches. Our principal findings are five-fold. First, we observed modest to
strong evidence of heritability for several Echo, ETT and
BA function traits, underscoring the contribution of additive genetic effects to interindividual variation in these
traits. Our heritability findings confirm prior reports forsome of the traits [18,20,22,23,27,28,52], including fromour group [14,24]. Second, notwithstanding the modestto-high heritability, none of the SNP-trait associations weobserved achieved genome-wide significance (conservative Bonferroni correction p of 5*10-8). Therefore, any
associations presented should be viewed as hypothesisgenerating, with need for replication in additional samples. Third, our investigation highlights some of the challenges inherent in the interpretation of GWAS results. We
did not observe any overlap between the top SNPs noted
in GEE-based versus FBAT-based analyses, in part due tothe inherent differences in the two analytical methods(see Overview for details [37]). Fourth, notwithstanding
the lack of genome-wide statistical significance, our data
do suggest several interesting biological candidates
among the SNPs most strongly associated with different
traits in the various analytical approaches (see discussion
below). Fifth, we were quite limited in our ability to replicate findings for genetic variants previously associatedwith the traits that we investigated because specific coverage of such genetic variation in these candidates was limited in the Affymetrix 100K GeneChip. Therefore, the lackof replication of SNPs in proximity to 6 genes previously
reported to be associated with Echo, ETT and BA traits
should be interpreted with great caution. It is interestingthat several weak associations (p between 0.05 and 10-3)
were observed between traits in the three groups and SNPs
in proximity to selected candidate genes evaluated(ADRB1, AGT and AGTR1).
Potential biological candidates among observed
associations
In our GWAS of Echo traits, a SNP in SLIT2 was associatedwith Echo LV diastolic dimension in several analyses.
SLIT2 is an evolutionarily highly conserved gene that
encodes a putative secreted protein, which contains conserved protein-protein interaction domains including leucine-rich repeats and epidermal growth factor-like motifs[53]. The gene has multiple effects but has been recently
identified to have a novel role in vascular function by contributing to migratory mechanisms in vascular smoothmuscle cells [54]. Likewise, the associations of LV mass
with HSPA8, and of LA size with PDE4B are consistent
with the key role of heat shock protein expression [55]and T-cell mediated immune responses [56], respectively,

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http://www.biomedcentral.com/1471-2350/8/S1/S2Table 2: Top associations for Echo, ETT and BA function traits based on lowest p value for GEE test (2a), FBAT (2b), and Linkage(2c)*

2A. Top Associations based on lowest GEE p values
Trait

SNP

Chromosome

Physical position

GEE p-value

FBAT p-value

In/near Gene (within 60 kb)

I. Top 15 SNPs associated with Echocardiographic Traits (Averaged across exams)
LV diastolic dimension

rs1379659

420296952

1.17*10-7

0.001

SLIT2

LV fractional shortening

rs366676

688774485

2.44*10-6

0.059

SPACA1

LV diastolic dimension

rs666088

420171404

5.10*10-6

0.008

SLIT2

LV systolic dimension

rs10504543

873941196

5.18*10-6

0.247

KCNB2

Left atrial diameter

rs1935881

1186798043

5.56*10-6

0.003

FAM5C

LV mass

rs10498091

2221724949

5.68*10-6

0.162

Left atrial diameterrs10493389

166022886

6.56*10-6

0.119

LV diastolic dimension

rs4920799

584642284

6.84*10-6

0.041

LV wall thickness

rs10519181

1576076030

1.04*10-5

0.027

LV diastolic dimension

rs6104740

2011284809

1.15*10-5

0.021

LV diastolic dimension

rs2900208

1211769731

1.20*10-5

0.021

ETV6

LV systolic dimension

rs3766377

1157613632

1.25*10-5

0.032

CD244

PDE4B
TBC1D2B

LV diastolic dimension

rs10511762

925621130

1.29*10-5

0.002

TUSC1

LV mass

rs4936770

11122434085

1.37*10-5

0.019

HSPA8

LV diastolic dimension

rs4485619

2011251676

1.57*10-5

0.043

II. Top 5 SNPs associated with ETT Traits
Stage 2 Exercise heart rate

rs6847149

4111157701

2.74*10-6

0.014

NOLA1

Stage 2 Exercise heart rate

rs2819770

1234237045

3.53*10-6

0.010

RYR2

Post-exercise 3 minute recovery SBP

rs746463

11109501154

4.88*10-6

0.564

Stage 2 Exercise heart rate

rs2056387

1234250153

5.17*10-6

0.002

RYR2

Stage 2 Exercise SBP

rs2553268

831055898

6.32*10-6

0.001

WRN

III. Top 5 SNPs associated with BA endothelial function Traits
Baseline BA flow velocity

rs3814219

10105637085

9.48*10-7

0.325

OBFC1

BA FMD percent

rs4148686

7116728468

1.13*10-5

0.025

CFTR

Baseline BA flow velocity

rs1471639

1433552277

1.26*10-5

0.001

Baseline BA diameterrs1045182

6116705168

1.44*10-5

0.058

TSPYL1Baseline BA flow velocity

rs10515508

5139355254

1.71*10-5

0.016

NRG2

Chromosome

Physical position

GEE p-value

FBAT p-value

In/near Gene (within 60 kb)

WDR52

2B. Top associations based on lowest FBAT p value
Trait

SNP

I. Top 15 SNPs associated with Echocardiographic Traits (Averaged across exams)
LV systolic dimension

rs1392284

3114584100

0.139

6.39*10-6

LV fractional shortening

rs10515040

1748859319

0.211

1.29*10-5

LV fractional shortening

rs9312006

38234491

0.002

1.64*10-5

LV systolic dimension

rs10504591

876199715

0.046

1.95*10-5

LV fractional shortening

rs448458

1560591780

0.206

2.26*10-5

LV diastolic dimension

rs580859

1368030441

0.046

2.68*10-5
6.42*10-5

LV systolic dimension

rs1959290

1486208482

2.07*10-5

Aortic root diameterrs2468680

8140590402

0.690

6.12*10-5

LV systolic dimension

rs448458

1560591780

0.019

5.60*10-5

LV systolic dimension

rs2918268

5148586949

0.574

4.82*10-5

LV mass

rs965036

6

20099022

0.033

3.69*10-5

Left atrial diameter

rs1701821

7112544622

0.137

3.66*10-5

ABLIM3

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BMC Medical Genetics 2007, 8(Suppl 1):S2

http://www.biomedcentral.com/1471-2350/8/S1/S2Table 2: Top associations for Echo, ETT and BA function traits based on lowest p value for GEE test (2a), FBAT (2b), and Linkage (2c)*(Continued)
Aortic root diameter

rs7544568

138308301

0.194

3.21*10-5

LV fractional shortening

rs10504591

876199715

0.112

2.92*10-5

LV diastolic dimension

rs1488745

3

19768020.141

2.72*10-5

II. Top 5 SNPs associated with ETT Traits
Post-exercise 3 minute recovery SBP

rs2016718

896813381

0.006

2.20*10-7

Post-exercise 3 minute recovery heartrate

rs1029947

7150713400

0.013

9.20*10-7

PRKAG2

Post-exercise 3 minute recovery heartrate

rs1029946

7150713454

0.022

3.89*10-6

PRKAG2

Stage 2 Exercise heart rate

rs1958055

1433254537

0.040

8.55*10-6

NPAS3

Post-exercise 3 minute recovery SBP

rs7828552

871862761

0.057

9.34*10-6

XRG9III. Top 5 SNPs associated with BA endothelial function Traits
BA hyperemic flow velocity

rs1859634

7100758808

0.030

1.21*10-5

AK124120

BA FMD percent

rs1106494

1462201734

0.003

1.61*10-5

KCNH5

BA hyperemic flow velocity

rs2389866

4120872866

0.423

2.12*10-5

PDE5A

Baseline BA diameterrs774227

991273496

0.002

2.34*10-5

NFIL3Baseline BA diameterrs10502887

1843433881

0.002

2.79*10-5

Maximum
LOD score

LOD-1.5
interval

2C. Magnitude and location of peak LOD scores ≥2.0 for Echo, ETT and BA function traits
Trait

SNP or
STR

Chromosome

Physical position

LOD+1.5 interval

I. Echocardiographic Traits (Averaged across examinations)
LV mass

rs10515509

5139270238

4.37

133816612

150634674

Aortic root diameterrs10513442

3

154474088

4.22

150552924

161813142

LV wall thickness

rs3813713

1051241137

3.16

32818116

58684005

LV wall thickness

rs10511550

910638555

3.1110220368

15384347

LV fractional shortening

AFM254ve1

3198506417

2.78

195278503

199138789

LV wall thickness

rs2438085

2105339005

2.59103478258

106924695

Left atrial diameter

rs7327514

13783341002.5568655834

90511230

LV wall thickness

rs17191583149176

2.45

64238853

86738287

LV mass

rs10489725

1

181172198

2.41

176249023

201595809

LV mass

rs1989051

8129363300

2.38127811630

133926399

LV wall thickness

GATA164B
08

385600162.25

218383220875136

Stage 2 Exercise heart rate

rs190982

588259176

2.93

71236666

96112374

Stage 2 Exercise heart rate

GATA165C
03

1

60383884

2.4643070922

67006164

Stage 2 Exercise heart rate

rs7286558

2220504737

2.43

15786453

25685518

Stage 2 Exercise heart rate

rs10483844

1471902088

2.3953240301

74937294

32261074

II. ETT Traits

III. BA Endothelial Function Traits
Baseline BA flow velocity

rs1425727

825642697

2.14

19459783

BA FMD percent

D21S11

21

19476134

2.13

10000969

27037800

Baseline BA flow velocity

rs3007456

942925816

2.1236878975

76736108*SNPs are ordered by GEE p values. dbSNP positions are from NCBI Build 35 (hg17).
Abbreviations as in Table 1. The number of informative families for FBAT analyses ranged from a minimum of 80 to a maximum of 210.

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BMC Medical Genetics 2007, 8(Suppl 1):S2

http://www.biomedcentral.com/1471-2350/8/S1/S2Table 3: Top associations ordered by geometric mean of GEE p-values across traits (3 groups) and across examinations (echo traits)

Trait

SNP

Chromosome

Physical position GEE p-value

In/near Gene (within 60 kb)

IA. Top 15 SNPs associated with Echocardiographic Traits across individual exams
LV diastolic dimension
LV diastolic dimension
Aortic root diameter
LV mass
Aortic root diameter
LV mass
LV diastolic dimension
LV diastolic dimension
LV systolic dimension
LV diastolic dimension
LV mass
LV systolic dimension
LV systolic dimension
Aortic root diameter
LV diastolic dimension

rs4920799
rs1379659
rs26438
rs473664
rs10488825
rs10498091
rs10514431
rs10505599
rs10504543
rs2900208
rs861857
rs10501940
rs707025
rs1395204
rs10513272

5
4
5
15
11
2
16
8
8
12
22
11
2
18
9

84642284
20296952
165221499
51598287
81688520
221724949
76498035
133812159
73941196
11769731
20306894
99440078
155014031
4477509116143601

0.001
0.001
0.001
0.00160.00170.00170.00180.00190.00190.00190.00220.00230.00230.00250.0026

SLIT2
WDR72

KIAA1576
FLJ33069
KCNB2
ETV6
UBE2L3CNTN5GALNT13
PAPPA

IB. Top 15 SNPs associated with Averaged Echocardiographic Traits (across LV traits)
Across LV phenotypes

rs1379659
rs10498091
rs861857
rs473664
rs3766377
rs10504543
rs10518462
rs1959289
rs667269
rs1959290
rs1959291
rs10485104
rs10491574
rs707025
rs525960

4
2
22
15
1
8
4
14
3
14
14
6
9
2
1

20296952
221724949
20306894
51598287
157613632
73941196
126562521
86208319
175822307
86208482
86208525
165966351
116701992
155014031
149310939

0.00070.00090.001
0.00120.00160.00170.00180.00260.00270.00270.00270.00300.00300.00320.003328973892
137712255
76835140
234250153
2363105

0.01010.01060.01120.01150.0132SLIT2UBE2L3
WDR72
CD244
KCNB2

PDE10AASTN2GALNT13
LCE5A

II. Top 5 SNPs associated with ETT Traits (across traits)
Across phenotypes

rs1560916
rs1432214
rs10512056
rs2056387
rs6560812

17
2
9
1
10

ACCN1
LOC442425
RYR2

III. Top 5 SNPs associated with BA endothelial Traits (across traits)
Across phenotypes

rs2912991
rs10510677
rs10493052
rs7155941
rs1954627

7
3
1
14
14

52684247
36168070
33614778
41681710
41689011

0.0029
0.007
0.007
0.008
0.009

ZNF31

dbSNP positions are from NCBI Build 35 (hg17).
Abbreviations as in Table 1.

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BMC Medical Genetics 2007, 8(Suppl 1):S2

http://www.biomedcentral.com/1471-2350/8/S1/S2Table 4: Associations of traits with SNPs in or near (up to 200 kb away) 6 well-replicated genes in the published literature with a pvalue < 0.05 in either FBAT or GEE.
4A. Associations of averaged echo traits

Candidate GeneFHS 100K SNP

ACE

ADRB1

AGT

AGTR1

VEGF

NOS3

Physical Position

Trait

GEE p-value

FBAT p-value

0.0002

no SNP was associated with a p value < 0.05 for any LV trait studies

rs10510001

115962372

LV diastolic dimension

0.004

rs10510001

115962372

LV systolic dimension

0.001

0.001

rs10510000

115961985

LV diastolic dimension

0.052

0.001
0.001

rs10510000

115961985

LV systolic dimension

0.059

rs7902873

115884949

LV diastolic dimension

0.467

0.002

rs10509999

115917269

LV diastolic dimension

0.136

0.003

rs180940

115712401

LV wall thickness

0.003

0.072

rs180934

115720720

LV wall thickness

0.005

0.090

rs180935

115720249

LV wall thickness

0.005

0.160

rs998334

115957002

LV diastolic dimension

0.289

0.005

rs7902873

115884949

LV systolic dimension

0.249

0.006

rs10509999

115917269

LV systolic dimension

0.036

0.008

rs180935

115720249

LV mass

0.011

0.409

rs180934

115720720

LV mass

0.015

0.411

rs7902873

115884949

LV mass

0.646

0.016

rs998334

115957002

LV systolic dimension

0.110

0.018

rs10510001

115962372

LV fractional shortening

0.021

0.056

rs10510000

115961985

LV fractional shortening

0.382

0.027

rs180940

115712401

LV mass

0.029

0.303

rs10510001

115962372

LV mass

0.393

0.040

rs6585258

115739125

LV mass

0.047

0.481

rs10510000

115961985

LV mass

0.335

0.048

rs10495300

227188497

Left atrial diameter

0.095

0.001

rs2478518

227174605

LV fractional shortening

0.028

0.238

rs1202585

227309949

LV wall thickness

0.030

0.028

rs2180478

227295655

LV diastolic dimension

0.800

0.030

rs758216

227005969

Aortic root diameter

0.031

0.341

rs1202524

227257907

LV diastolic dimension

0.323

0.037

rs2478518

227174605

LV systolic dimension

0.038

0.467
0.399

rs731824

227329806

Left atrial diameter

0.043

rs1202585

227309949

LV mass

0.044

0.117

rs1059502

150045008

Aortic root diameter

0.598

0.005

rs1357424

149801524

LV fractional shortening

0.075

0.006

rs1357424

149801524

LV systolic dimension

0.241

0.030

rs1059502

150045008

LV diastolic dimension

0.142

0.030

rs2331406

150048180

Aortic root diameter

0.589

0.032

rs10513333

149786557

Left atrial diameter

0.437

0.039

rs729761

43912549

LV fractional shortening

0.012

0.200

rs729761

43912549

Left atrial diameter

0.573

0.018

rs729761

43912549

LV systolic dimension

0.018

0.249

rs2396083

43912786

LV fractional shortening

0.026

0.250

rs2396083

43912786

Left atrial diameter

0.489

0.031

rs2396083

43912786

LV systolic dimension

0.040

0.224

No SNP was associated with a p value < 0.05 for any LV trait studied

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BMC Medical Genetics 2007, 8(Suppl 1):S2

http://www.biomedcentral.com/1471-2350/8/S1/S2Table 4: Associations of traits with SNPs in or near (up to 200 kb away) 6 well-replicated genes in the published literature with a pvalue < 0.05 in either FBAT or GEE. (Continued)
4B. Associations of ETT traits

Candidate Gene

ACE

ADRB1

AGT

AGTR1

FHS 100K SNP

Physical Position

Trait

GEE p-value

FBAT p-value

rs10491167

58780430

Stage 2 Exercise systolic blood pressure

0.046

0.137

rs10491168

58795195

Stage 2 Exercise systolic blood pressure

0.030

0.124

rs721575

59136652

Post-exercise 3 minute recovery heart rate

0.024

0.025

rs2419857

115607366

Stage 2 Exercise heart rate

0.852

0.030

rs4345919

115651155

Post-exercise 3 minute recovery heart rate

0.048

0.740

rs1752189

227000046

Post-exercise 3 minute recovery SBP

0.145

0.021

rs758216

227005969

Post-exercise 3 minute recovery SBP

0.184

0.050

rs10495298

227120049

Stage 2 Exercise systolic blood pressure

0.288

0.050

rs2478516

227175387

Stage 2 Exercise systolic blood pressure

0.021

0.486

rs275678

149851039

Post-exercise 3 minute recovery SBP

0.216

0.049

rs427832

149949061

Post-exercise 3 minute recovery SBP

0.014

0.171

rs1949350

150089423

Stage 2 Exercise heart rate

0.010

0.335

VEGF

rs729761

43912549

Stage 2 Exercise heart rate

0.041

0.035

NOS3

rs2303928

150176978

Stage 2 Exercise heart rate

0.012

0.056

GEE p-value

FBAT p-value

4C. Associations of BA function traits

Candidate GeneFHS 100K SNP

Physical Position

ACE

ADRB1

AGT

AGTR1

VEGF

NOS3

Trait

no SNP was associated with a p value < 0.05

rs180940

115712401

BA hyperemic flow velocity

0.581

0.015

rs180935

115720249

BA hyperemic flow velocity

0.953

0.030

rs180934

115720720

BA hyperemic flow velocity

0.662

0.029

rs10509999

115917269

BA hyperemic flow velocity

0.001

0.137

rs10510000

115961985

BA hyperemic flow velocity

0.007

0.014

rs10510001

115962372

BA hyperemic flow velocity

0.017

0.239

rs758216

227005969

Baseline BA flow velocity

0.049

0.488

rs1202585

227309949

Baseline BA diameter

0.002

0.080

rs1202585

227309949

BA hyperemic flow velocity

0.049

0.080

rs1492090

149884751

BA hyperemic flow velocity

0.026

0.293

rs427832

149949061

Baseline BA flow velocity

0.509

0.043

rs833048

43762514

BA hyperemic flow velocity

0.860

0.036

rs10498756

44046909

BA hyperemic flow velocity

0.312

0.008

rs741067

149938103

Baseline BA diameter

0.043

0.024

rs1006581

149949571

Baseline BA diameter

0.009

0.097

rs2215564

150001612

BA hyperemic flow velocity

0.028

0.104

dbSNP positions are from NCBI Build 35 (hg17).

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BMC Medical Genetics 2007, 8(Suppl 1):S2

in myocardial hypertrophic responses to insults or hemodynamic overload.
Analyses of ETT traits provided some interesting results.
The association of a SNP in RYR2 with exercise heart rate
responses in multiple analyses is quite consistent with thefundamental role of the ryanodine receptor on the sarcoplasmic reticulum in calcium trafficking during cardiac
muscle excitation-contraction coupling [57]. Furthermore, RYR2 has been implicated in exercise-induced polymorphic ventricular tachyarrhythmias [58]. Using FBAT,
SNPs in PRKAG2 were associated with heart rate during
the recovery period post-exercise. Mutations in PRKAG2,an enzyme that modulates glucose uptake and glycolysis[59], are associated with glycogen-filled vacuoles in cardiomyocytes. The phenotypic manifestations include cardiac hypertrophy, ventricular pre-excitation andconduction system disturbances, encompassed together
in the Wolff-Parkinson-White syndrome [60].
Genetic linkage analyses of ETT traits identified peaks on
chromosomes 5 and 22 for exercise heart rate. The 1.5
LOD support intervals for these peaks included MEF2C
and MAPK1, respectively. MEF2C is a critical regulator of
cardiac morphogenesis [61]. Additionally, overexpressionof MEF2C in experimental studies is associated with disturbances in extracellular matrix remodeling, ion handling, and metabolism of cardiomyocytes [62]. The peakon MAPK1 is of interest because a recent investigations
highlighted the role of MAPK signaling in mediating the
responses of skeletal muscles to exercise training [63].
A SNP in NRG2 was associated with BA flow velocity atrest, and also was in proximity to the top LOD peak for LV
mass, raising the possibility of pleiotropic effects of thisgene on ventricular and vascular remodeling and function. NRG2, which encodes neuregulin-2, is a member ofthe epidermal growth factor (EGF) family and binds to
ErbB receptors. ErbB signaling has been implicated in angiogenesis and endothelial cell proliferation [64]. Of interest, a SNP in CFTR was associated with FMD. It isnoteworthy that CFTR is expressed in vascular smoothmuscle cells and activation of CFTR chloride channels regulates contraction and relaxation of smooth muscle cells;
disruption of the CFTR gene prevents cAMP-dependentvasorelaxation in experimental studies [65]. CFTR is also
expressed in endothelial cells where it functions as a cyclic
nucleotide-regulated chloride channel [66]. Of interest, a
SNP in PDE5A was associated with BA hyperemic flow
velocity in FBAT analyses. Phosphodiesterase 5 (PDE5)hydrolyzes cyclic guanosine monophosphate (cGMP) andcyclic adenosine monophosphate (cAMP), is widely
expressed in the vasculature, and is best known as the target of sildenafil, a drug used to treat erectile dysfunction[67]. PDE5 degrades cGMP in smooth muscle cells so as

http://www.biomedcentral.com/1471-2350/8/S1/S2

to maintain the contracted state of blood vessels [67].
PDE5A may also play a critical role in the growth promoting effects of Angiotensin II on vascular smooth muscle
cells [68].
Strengths and limitations
The moderate-sized community-based sample, availability of longitudinal Echo measurements, routine ascertainment of standardized and reproducibly-measured traits,
and evaluation of multiple complementary analyticalmethods including assessment of potential pleiotropic
genetic effects strengthen our investigation. By web-posting unfiltered aggregate data we provide a resource for thescientific community to conduct in silico replication.
Nonetheless, several limitations must be emphasized. As
noted previously, the lack of genome-wide significance forany association observed given the extent of multiple statistical testing does not exclude a potential role of genetic
influences on the traits studied. We had limited statisticalpower to detect modest genetic effects, given the sample
size and the extent of multiple testing. As detailed in the
Overview paper [37], for a conservative alpha level such as
10-8, we have more than 90% power to detect an association with a SNP explaining 4% or more total phenotypicvariation when 80% or more individuals are phenotyped.
We also had limited ability to replicate previously
reported findings, in view of the partial coverage ofgenetic variation in select candidates with the Affymetrix
100K gene chip. Additionally, genetic variants may influence phenotypes in a context-specific manner [69], being
modulated by environmental influences. For instance, theassociations of ACE and AGTR2 with LV mass werereported to vary according to dietary salt intake in one
investigation [48]. We did not undertake an investigationof gene-environmental interactions in the present study.
Likewise, some of the moderately strong associations may
represent false-positive results, notwithstanding the evidence suggesting that some of the associated SNPs may bereasonable biological candidates. We averaged echocardiographic traits across multiple examinations, with a viewto characterizing the phenotype better over a period oftime using several observations. Such a strategy could
limit regression dilution bias, if the examinations arerepeated over a short period of time. In our study, however, these examinations spanned a time period of twenty
years, and the examinations used different echocardiographic equipment that may introduce misclassification.
Further, such averaging assumes that similar sets of genes
and environmental factors influence traits over a wide age
range. Such an assumption may not be true, i.e., agedependent gene effects may be masked by averaging ofobservations across ages in participants. Lastly, our sample was white and of European descent. The generalizability of our findings to other ethnicities is unknown.

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BMC Medical Genetics 2007, 8(Suppl 1):S2

http://www.biomedcentral.com/1471-2350/8/S1/S2

Conclusion

Acknowledgements

In hypothesis-generating GWAS of Echo, ETT response
and BA vascular function in a moderate size communitybased sample, we identified several SNPs that are potential candidates for replication. Overall, our investigation
provides a scientific framework for analyzing and interpreting GWAS of phenotypes fundamental to our understanding of cardiac and vascular remodeling andhemodynamic responses to exercise testing. We expect the
Framingham 100K SNP data to serve as a valuable scientific resource by virtue of the web-posting of unfilteredaggregate data

This work was supported by the National Heart, Lung and Blood Institute's
Framingham Heart Study (contract No. N01-HC-25195), the Boston University Linux Cluster for Genetic Analysis (LinGA) funded by the NIH
NCRR (National Center for Research Resources) Shared Instrumentation
grant 1S10RR163736-01A1, and NIH grants K23-HL-074077 (TJW), K23HL080025 (Dr. Newton-Cheh), 6R01-NS 17950; 1R01 HL60040 (EJB);
RO1 HL70100 (EJB), HL080124 (RSV) and K24-HL04334 (RSV).

Abbreviations
BA = brachial artery. CVD = cardiovascular disease. ETT =exercise treadmill test. FBAT = family-based association
test. FHS = Framingham Heart Study. FMD = flow-mediated dilation. GEE = generalized estimating equations.
GWAS = genome-wide association. IVS = interventricular
septum. LA = left atrium. LOD = logarithm of odds. LV =left ventricular. LVM = LV mass. LVWT = LV wall thickness.
LVDD = LV diastolic diameter. LVSD = LV systolic diameter. PW = posterior wall. SNP= single nucleotide polymorphism.

This article has been published as part of BMC Medical Genetics Volume 8
Supplement 1, 2007: The Framingham Heart Study 100,000 single nucleotide polymorphisms resource. The full contents of the supplement areavailable online at http://www.biomedcentral.com/1471-2350/8?issue=S1.

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Competing interests
None of the authors have a competing interest relevant tothe subject of this manuscript. GFM is the owner of Cardiovascular Engineering, Inc, a company that designs andmanufactures devices that measure vascular stiffness. The
company uses these devices in clinical trials that evaluate
the effects of diseases and interventions on vascular stiffness.

Authors' contributions
RSV conceived the study design, planned the analyses,
drafted and critically revised the manuscript. MGL
planned the study, assisted in securing funding for BA
function, planned and conducted the analyses, and critically revised the manuscript. JA critically revised the manuscript. TJW contributed to the analysis and interpretationof data, revising of the manuscript for important intellectual content. GFM assisted in obtaining funding for BA
function measures, contributed to data acquisition, andcritically revised the manuscript. SK and CNC participatedin the study design, interpretation of data, and reviewed
the manuscript. JAV assisted in securing funding for BA
function measures and revising the manuscript. MJK contributed to collecting the BA function data base andreviewing the manuscript. COD and DL participated in
the study conception and design, interpretation of data
and reviewed the manuscript. EJB provided critical input
designing the study, securing funding for BA function andecho measures, acquiring measurements, planning theanalyses and critically revising the manuscript.

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