Volume 8 Supplement 1

The Framingham Heart Study 100,000 single nucleotide polymorphisms resource

Open Access

Genome-wide association of echocardiographic dimensions, brachial artery endothelial function and treadmill exercise responses in the Framingham Heart Study

  • Ramachandran S Vasan1, 2Email author,
  • Martin G Larson1, 3,
  • Jayashri Aragam4,
  • Thomas J Wang5,
  • Gary F Mitchell6,
  • Sekar Kathiresan5, 7,
  • Christopher Newton-Cheh5, 7,
  • Joseph A Vita2,
  • Michelle J Keyes1, 3,
  • Christopher J O'Donnell1, 8,
  • Daniel Levy1, 8 and
  • Emelia J Benjamin1, 2
BMC Medical Genetics20078(Suppl 1):S2

DOI: 10.1186/1471-2350-8-S1-S2

Published: 19 September 2007

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 blood pressure 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 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 suggesting pleiotropy. 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-sized community-based sample, we identified several SNPs that are candidates for replication attempts and we provide a web-based 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, with overt events being antedated by subclinical cardiovascular target organ damage [2, 3]. Current research indicates a fundamental role of left ventricular (LV) chamber size, wall thickness (LV remodeling) and mass (LVM) in the pathogenesis 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 brachial artery (BA) flow-mediated dilation (FMD), has emerged as a fundamental component of atherosclerosis and a precursor of overt CVD [1416]. Thus, traits obtained via echocardiography (Echo), testing for BA endothelial function and ETT can serve as intermediate phenotypes in the pathway from standard risk factor to overt CVD. Such intermediate phenotypes have been studied extensively to characterize their clinical and genetic correlates, have been reported to be heritable traits [14, 1728], and have been linked to select genetic loci in several reports [2931].

More recently, several investigators have proposed genome-wide association studies (GWAS) as a strategy to map 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 a unique opportunity to conduct both genome-wide association and linkage analyses to explore the genetic underpinnings of LV remodeling, endothelial function and exercise 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 polymorphism (SNP) set [34]. Participants were eligible for the present investigation if they had available genotypes and the echocardiographic, vascular and ETT traits of interest (as defined below). The Institutional Review Board at Boston University Medical Center approved the study and all participants gave written informed consent (including for genetic research).

Measurement of phenotypes

Echocardiography

All attendees underwent routine transthoracic two-dimensionally-guided M-mode echocardiography at the second (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 Aerotech transducer) 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 the posterior wall (PW) and interventricular septum (IVS), and the diameters of the aortic root (all measured at end-diastole) and left atrium (LA) at end-systole were obtained by using a 'leading edge' technique [38], averaging measurements in 3 cardiac cycles according to the American Society of Echocardiography guidelines. We calculated LV wall thickness (LVWT) as the sum of PW and IVS measurements. LV mass was calculated by using the formula 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), all attendees 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 the recovery period.

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 clinical examination 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 and 1 minute after reactive hyperemia induced by 5-minute forearm cuff occlusion. The coefficient of variation for baseline 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 with correction for the insonation angle [41]. Mean baseline and hyperemic flow velocities were analyzed from digitized audio data using semiautomated signal averaging (Cardiovascular Engineering, Waltham, MA). Baseline and 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 adjusting for the following covariates: for the echocardiographic phenotypes, age, sex, height, weight, smoking, systolic and diastolic blood pressure, hypertension treatment; for ETT measures, age, sex, body mass index, baseline heart rate, diabetes, smoking, ratio of total to high-density lipoprotein cholesterol, and treatment for hypertension (additional adjustments for select variables is detailed in Table 1); for BA function, a set of 15 covariates previously reported [14] to be associated with endothelial function in our sample (see Table 1). Covariates were from the same exam as the phenotype measures. Next, we used residuals for the phenotypes of interest to test for potential association with 100K SNPs using additive family-based 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%, 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 is less precise than other algorithms that have been introduced more recently. The association analyses were complemented by linkage analyses that used variance components methods and a subset of 100K markers and Marshfield STRs; the selection of markers and methods for calculating identity-by-descent are also described in the Overview [37].
Table 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

A. Echocardiographic Traits Averaged Across 4 Examinations

LV mass (LVM)

10

2,4,5,6

- age- and sex-

- multivariable-**

0.36

LV diastolic dimension (LVDD)

10

2,4,5,6

 

0.38

LV systolic dimension (LVDS)

10

2,4,5,6

 

0.30

LV wall thickness (LVWT)

10

2,4,5,6

 

0.41

LV fractional shortening (LVFS)

10

2,4,5,6

 

0.20

Left atrial diameter (LAD)

10

2,4,5,6

 

0.25

Aortic root diameter (AOR)

10

2,4,5,6

 

0.52

B. Exercise Treadmill Test (ETT) Traits

Stage 2 Exercise systolic blood pressure (SBP)

2

2

- age- and sex-

- multivariable-**

0.28

Stage 2 Exercise diastolic blood pressure (DBP)

2

2

 

0.22

Stage 2 Exercise heart rate

2

2

 

0.25

Post-exercise 3 minute recovery SBP

2

2

 

0.20

Post-exercise 3 minute recovery DBP

2

2

 

0.16

Post-exercise 3 minute recovery heart rate

2

2

 

0.40

C. Brachial Artery (BA) Endothelial Function Traits

Baseline BA diameter

2

7

- age- and sex-

- multivariable-**

0.25

Baseline BA flow velocity

2

7

 

0.32

BA flow-mediated dilation (FMD) percent

2

7

 

0.19

BA hyperemic flow velocity

2

7

 

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, prevalent cardiovascular 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.

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 the larger 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 of values for traits averaged across the 4 examinations, as well as traits at individual examinations separately. In order to evaluate potential pleiotropic effects, we examined SNP associations across related sets of traits and listed the top 25 SNPs with the lowest geometric mean of p values for all echocardiographic traits (averaged across the 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 the four 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, 4251]. 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 three groups (Echo, ETT and BA endothelial function), the number of traits evaluated within each group, and the covariates included in regression models to create residuals. We observed moderate to high heritability of most of the traits evaluated (Table 1; estimates are multivariable-adjusted, for covariates noted above under methods, and listed in table footnote). Heritability estimates were 52% for aortic root dimension, 36–40% for LV mass, internal 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 (32 and 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 Information. Overall, nine SNPs yielded a p value <10-5 in either GEE or FBAT models for Echo traits. Eleven SNPs were associated with ETT traits with a p value <10-5, and one 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 an approximate 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 FBAT. The top SNPs associated with averaged Echo traits included: rs1379659 and rs666088 (both in SLIT2) with LV diastolic dimension, rs1935881 (FAM5C) and rs10493389 (PDE4B) with LA diameter, and rs10504543 (KCNB2) with LV systolic dimension. The top SNPs associated with ETT traits included: rs6847149 (NOLA1) and rs2056387 (RYR2) with stage 2 exercise heart rate, and rs2553268 (WRN) with stage 2 exercise systolic blood pressure. 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 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

4

20296952

1.17*10 -7

0.001

SLIT2

LV fractional shortening

rs366676

6

88774485

2.44*10 -6

0.059

SPACA1

LV diastolic dimension

rs666088

4

20171404

5.10*10 -6

0.008

SLIT2

LV systolic dimension

rs10504543

8

73941196

5.18*10 -6

0.247

KCNB2

Left atrial diameter

rs1935881

1

186798043

5.56*10 -6

0.003

FAM5C

LV mass

rs10498091

2

221724949

5.68*10 -6

0.162

 

Left atrial diameter

rs10493389

1

66022886

6.56*10 -6

0.119

PDE4B

LV diastolic dimension

rs4920799

5

84642284

6.84*10 -6

0.041

 

LV wall thickness

rs10519181

15

76076030

1.04*10 -5

0.027

TBC1D2B

LV diastolic dimension

rs6104740

20

11284809

1.15*10 -5

0.021

 

LV diastolic dimension

rs2900208

12

11769731

1.20*10 -5

0.021

ETV6

LV systolic dimension

rs3766377

1

157613632

1.25*10 -5

0.032

CD244

LV diastolic dimension

rs10511762

9

25621130

1.29*10 -5

0.002

TUSC1

LV mass

rs4936770

11

122434085

1.37*10 -5

0.019

HSPA8

LV diastolic dimension

rs4485619

20

11251676

1.57*10 -5

0.043

 

II. Top 5 SNPs associated with ETT Traits

Stage 2 Exercise heart rate

rs6847149

4

111157701

2.74*10 -6

0.014

NOLA1

Stage 2 Exercise heart rate

rs2819770

1

234237045

3.53*10 -6

0.010

RYR2

Post-exercise 3 minute recovery SBP

rs746463

11

109501154

4.88*10 -6

0.564

 

Stage 2 Exercise heart rate

rs2056387

1

234250153

5.17*10 -6

0.002

RYR2

Stage 2 Exercise SBP

rs2553268

8

31055898

6.32*10 -6

0.001

WRN

III. Top 5 SNPs associated with BA endothelial function Traits

Baseline BA flow velocity

rs3814219

10

105637085

9.48*10 -7

0.325

OBFC1

BA FMD percent

rs4148686

7

116728468

1.13*10 -5

0.025

CFTR

Baseline BA flow velocity

rs1471639

14

33552277

1.26*10 -5

0.001

 

Baseline BA diameter

rs1045182

6

116705168

1.44*10 -5

0.058

TSPYL1

Baseline BA flow velocity

rs10515508

5

139355254

1.71*10 -5

0.016

NRG2

2B. Top associations based on lowest FBAT p value

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 systolic dimension

rs1392284

3

114584100

0.139

6.39*10 -6

WDR52

LV fractional shortening

rs10515040

17

48859319

0.211

1.29*10 -5

 

LV fractional shortening

rs9312006

3

8234491

0.002

1.64*10 -5

 

LV systolic dimension

rs10504591

8

76199715

0.046

1.95*10 -5

 

LV fractional shortening

rs448458

15

60591780

0.206

2.26*10 -5

 

LV diastolic dimension

rs580859

13

68030441

0.046

2.68*10 -5

 

LV systolic dimension

rs1959290

14

86208482

2.07*10-5

6.42*10 -5

 

Aortic root diameter

rs2468680

8

140590402

0.690

6.12*10 -5

 

LV systolic dimension

rs448458

15

60591780

0.019

5.60*10 -5

 

LV systolic dimension

rs2918268

5

148586949

0.574

4.82*10 -5

ABLIM3

LV mass

rs965036

6

20099022

0.033

3.69*10 -5

 

Left atrial diameter

rs1701821

7

112544622

0.137

3.66*10 -5

 

Aortic root diameter

rs7544568

1

38308301

0.194

3.21*10 -5

 

LV fractional shortening

rs10504591

8

76199715

0.112

2.92*10 -5

 

LV diastolic dimension

rs1488745

3

1976802

0.141

2.72*10 -5

 

II. Top 5 SNPs associated with ETT Traits

Post-exercise 3 minute recovery SBP

rs2016718

8

96813381

0.006

2.20*10 -7

 

Post-exercise 3 minute recovery heart rate

rs1029947

7

150713400

0.013

9.20*10 -7

PRKAG2

Post-exercise 3 minute recovery heart rate

rs1029946

7

150713454

0.022

3.89*10 -6

PRKAG2

Stage 2 Exercise heart rate

rs1958055

14

33254537

0.040

8.55*10 -6

NPAS3

Post-exercise 3 minute recovery SBP

rs7828552

8

71862761

0.057

9.34*10 -6

XRG9

III. Top 5 SNPs associated with BA endothelial function Traits

BA hyperemic flow velocity

rs1859634

7

100758808

0.030

1.21*10 -5

AK124120

BA FMD percent

rs1106494

14

62201734

0.003

1.61*10 -5

KCNH5

BA hyperemic flow velocity

rs2389866

4

120872866

0.423

2.12*10 -5

PDE5A

Baseline BA diameter

rs774227

9

91273496

0.002

2.34*10 -5

NFIL3

Baseline BA diameter

rs10502887

18

43433881

0.002

2.79*10 -5

 

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

Trait

SNP or STR

Chromosome

Physical position

Maximum LOD score

LOD-1.5 interval

LOD+1.5 interval

I. Echocardiographic Traits (Averaged across examinations)

LV mass

rs10515509

5

139270238

4.37

133816612

150634674

Aortic root diameter

rs10513442

3

154474088

4.22

150552924

161813142

LV wall thickness

rs3813713

10

51241137

3.16

32818116

58684005

LV wall thickness

rs10511550

9

10638555

3.11

10220368

15384347

LV fractional shortening

AFM254ve1

3

198506417

2.78

195278503

199138789

LV wall thickness

rs2438085

2

105339005

2.59

103478258

106924695

Left atrial diameter

rs7327514

13

78334100

2.55

68655834

90511230

LV wall thickness

rs1719

15

83149176

2.45

64238853

86738287

LV mass

rs10489725

1

181172198

2.41

176249023

201595809

LV mass

rs1989051

8

129363300

2.38

127811630

133926399

LV wall thickness

GATA164B08

3

8560016

2.25

2183832

20875136

II. ETT Traits

Stage 2 Exercise heart rate

rs190982

5

88259176

2.93

71236666

96112374

Stage 2 Exercise heart rate

GATA165C03

1

60383884

2.46

43070922

67006164

Stage 2 Exercise heart rate

rs7286558

22

20504737

2.43

15786453

25685518

Stage 2 Exercise heart rate

rs10483844

14

71902088

2.39

53240301

74937294

III. BA Endothelial Function Traits

Baseline BA flow velocity

rs1425727

8

25642697

2.14

19459783

32261074

BA FMD percent

D21S11

21

19476134

2.13

10000969

27037800

Baseline BA flow velocity

rs3007456

9

42925816

2.12

36878975

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.

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 and 4.23 (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 to individual echo traits across examinations, as well as associated with the averaged Echo traits. Likewise, RYR2 was associated with a low geometric p value when related to all ETT traits across the examination.
Table 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

rs4920799

5

84642284

0.001

 

LV diastolic dimension

rs1379659

4

20296952

0.001

SLIT2

Aortic root diameter

rs26438

5

165221499

0.001

 

LV mass

rs473664

15

51598287

0.0016

WDR72

Aortic root diameter

rs10488825

11

81688520

0.0017

 

LV mass

rs10498091

2

221724949

0.0017

 

LV diastolic dimension

rs10514431

16

76498035

0.0018

KIAA1576

LV diastolic dimension

rs10505599

8

133812159

0.0019

FLJ33069

LV systolic dimension

rs10504543

8

73941196

0.0019

KCNB2

LV diastolic dimension

rs2900208

12

11769731

0.0019

ETV6

LV mass

rs861857

22

20306894

0.0022

UBE2L3

LV systolic dimension

rs10501940

11

99440078

0.0023

CNTN5

LV systolic dimension

rs707025

2

155014031

0.0023

GALNT13

Aortic root diameter

rs1395204

18

4477509

0.0025

 

LV diastolic dimension

rs10513272

9

116143601

0.0026

PAPPA

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

Across LV phenotypes

rs1379659

4

20296952

0.0007

SLIT2

 

rs10498091

2

221724949

0.0009

 
 

rs861857

22

20306894

0.001

UBE2L3

 

rs473664

15

51598287

0.0012

WDR72

 

rs3766377

1

157613632

0.0016

CD244

 

rs10504543

8

73941196

0.0017

KCNB2

 

rs10518462

4

126562521

0.0018

 
 

rs1959289

14

86208319

0.0026

 
 

rs667269

3

175822307

0.0027

 
 

rs1959290

14

86208482

0.0027

 
 

rs1959291

14

86208525

0.0027

 
 

rs10485104

6

165966351

0.0030

PDE10A

 

rs10491574

9

116701992

0.0030

ASTN2

 

rs707025

2

155014031

0.0032

GALNT13

 

rs525960

1

149310939

0.0033

LCE5A

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

Across phenotypes

rs1560916

17

28973892

0.0101

ACCN1

 

rs1432214

2

137712255

0.0106

 
 

rs10512056

9

76835140

0.0112

LOC442425

 

rs2056387

1

234250153

0.0115

RYR2

 

rs6560812

10

2363105

0.0132

 

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

Across phenotypes

rs2912991

7

52684247

0.0029

 
 

rs10510677

3

36168070

0.007

 
 

rs10493052

1

33614778

0.007

ZNF31

 

rs7155941

14

41681710

0.008

 
 

rs1954627

14

41689011

0.009

 

dbSNP positions are from NCBI Build 35 (hg17).

Abbreviations as in Table 1.

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 the published 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 is noteworthy, though, that several SNPs in proximity to ADRB1, AGT, and AGTR1 were associated weakly (p value of 0.05 to 10-3) with several Echo, ETT and BA function phenotypes.
Table 4

Associations of traits with SNPs in or near (up to 200 kb away) 6 well-replicated genes in the published literature with a p-value < 0.05 in either FBAT or GEE.

4A. Associations of averaged echo traits

Candidate Gene

FHS 100K SNP

Physical Position

Trait

GEE p-value

FBAT p-value

ACE

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

ADRB1

rs10510001

115962372

LV diastolic dimension

0.004

0.0002

 

rs10510001

115962372

LV systolic dimension

0.001

0.001

 

rs10510000

115961985

LV diastolic dimension

0.052

0.001

 

rs10510000

115961985

LV systolic dimension

0.059

0.001

 

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

AGT

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

 

rs731824

227329806

Left atrial diameter

0.043

0.399

 

rs1202585

227309949

LV mass

0.044

0.117

AGTR1

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

VEGF

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

NOS3

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

4B. Associations of ETT traits

Candidate Gene

FHS 100K SNP

Physical Position

Trait

GEE p-value

FBAT p-value

ACE

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

ADRB1

rs2419857

115607366

Stage 2 Exercise heart rate

0.852

0.030

 

rs4345919

115651155

Post-exercise 3 minute recovery heart rate

0.048

0.740

AGT

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

AGTR1

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

4C. Associations of BA function traits

Candidate Gene

FHS 100K SNP

Physical Position

Trait

GEE p-value

FBAT p-value

ACE

no SNP was associated with a p value < 0.05

ADRB1

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

AGT

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

AGTR1

rs1492090

149884751

BA hyperemic flow velocity

0.026

0.293

 

rs427832

149949061

Baseline BA flow velocity

0.509

0.043

VEGF

rs833048

43762514

BA hyperemic flow velocity

0.860

0.036

 

rs10498756

44046909

BA hyperemic flow velocity

0.312

0.008

NOS3

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).

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 for some of the traits [18, 20, 22, 23, 27, 28, 52], including from our group [14, 24]. Second, notwithstanding the modest-to-high heritability, none of the SNP-trait associations we observed achieved genome-wide significance (conservative Bonferroni correction p of 5*10-8). Therefore, any associations presented should be viewed as hypothesis-generating, 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 to the 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 associated with the traits that we investigated because specific coverage of such genetic variation in these candidates was limited in the Affymetrix 100K GeneChip. Therefore, the lack of 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 interesting that 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 associated with 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 smooth muscle 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, 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 the fundamental 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 and conduction 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, overexpression of MEF2C in experimental studies is associated with disturbances in extracellular matrix remodeling, ion handling, and metabolism of cardiomyocytes [62]. The peak on 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 at rest, and also was in proximity to the top LOD peak for LV mass, raising the possibility of pleiotropic effects of this gene on ventricular and vascular remodeling and function. NRG2, which encodes neuregulin-2, is a member of the 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 is noteworthy that CFTR is expressed in vascular smooth muscle cells and activation of CFTR chloride channels regulates contraction and relaxation of smooth muscle cells; disruption of the CFTR gene prevents cAMP-dependent vasorelaxation 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) and cyclic 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 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 analytical methods including assessment of potential pleiotropic genetic effects strengthen our investigation. By web-posting unfiltered aggregate data we provide a resource for the scientific community to conduct in silico replication. Nonetheless, several limitations must be emphasized. As noted previously, the lack of genome-wide significance for any 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 statistical power 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 phenotypic variation when 80% or more individuals are phenotyped. We also had limited ability to replicate previously reported findings, in view of the partial coverage of genetic 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, the associations of ACE and AGTR2 with LV mass were reported to vary according to dietary salt intake in one investigation [48]. We did not undertake an investigation of 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 be reasonable biological candidates. We averaged echocardiographic traits across multiple examinations, with a view to characterizing the phenotype better over a period of time using several observations. Such a strategy could limit regression dilution bias, if the examinations are repeated 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., age-dependent gene effects may be masked by averaging of observations across ages in participants. Lastly, our sample was white and of European descent. The generalizability of our findings to other ethnicities is unknown.

Conclusion

In hypothesis-generating GWAS of Echo, ETT response and BA vascular function in a moderate size community-based 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 and hemodynamic 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 unfiltered aggregate data

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.

Declarations

Acknowledgements

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), K23-HL080025 (Dr. Newton-Cheh), 6R01-NS 17950; 1R01 HL60040 (EJB); RO1 HL70100 (EJB), HL080124 (RSV) and K24-HL04334 (RSV).

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 are available online at http://www.biomedcentral.com/1471-2350/8?issue=S1.

Authors’ Affiliations

(1)
The National Heart, Lung, and Blood Institute's Framingham Heart Study
(2)
Evans Department of Medicine and Whitaker Cardiovascular Institute, Boston University School of Medicine
(3)
Department of Mathematics and Statistics, Boston University
(4)
Veterans Administration Hospital
(5)
Cardiology Division, Massachusetts General Hospital, Harvard Medical School
(6)
Cardiovascular Engineering, Inc.
(7)
Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard University
(8)
National Heart, Lung, and Blood Institute, National Institutes of Health

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