Volume 8 Supplement 1

The Framingham Heart Study 100,000 single nucleotide polymorphisms resource

Open Access

Genome-wide association and linkage analyses of hemostatic factors and hematological phenotypes in the Framingham Heart Study

  • Qiong Yang1, 2,
  • Sekar Kathiresan1, 3, 6,
  • Jing-Ping Lin4,
  • Geoffrey H Tofler5 and
  • Christopher J O'Donnell1, 6Email author
BMC Medical Genetics20078(Suppl 1):S12

DOI: 10.1186/1471-2350-8-S1-S12

Published: 19 September 2007

Abstract

Background

Increased circulating levels of hemostatic factors as well as anemia have been associated with increased risk of cardiovascular disease (CVD). Known associations between hemostatic factors and sequence variants at genes encoding these factors explain only a small proportion of total phenotypic variation. We sought to confirm known putative loci and identify novel loci that may influence either trait in genome-wide association and linkage analyses using the Affymetrix GeneChip 100K single nucleotide polymorphism (SNP) set.

Methods

Plasma levels of circulating hemostatic factors (fibrinogen, factor VII, plasminogen activator inhibitor-1, von Willebrand factor, tissue plasminogen activator, D-dimer) and hematological phenotypes (platelet aggregation, viscosity, hemoglobin, red blood cell count, mean corpuscular volume, mean corpuscular hemoglobin concentration) were obtained in approximately 1000 Framingham Heart Study (FHS) participants from 310 families. Population-based association analyses using the generalized estimating equations (GEE), family-based association test (FBAT), and multipoint variance components linkage analyses were performed on the multivariable adjusted residuals of hemostatic and hematological phenotypes.

Results

In association analysis, the lowest GEE p-value for hemostatic factors was p = 4.5*10-16 for factor VII at SNP rs561241, a variant located near the F7 gene and in complete linkage disequilibrium (LD) (r2 = 1) with the Arg353Gln F7 SNP previously shown to account for 9% of total phenotypic variance. The lowest GEE p-value for hematological phenotypes was 7*10-8 at SNP rs2412522 on chromosome 4 for mean corpuscular hemoglobin concentration. We presented top 25 most significant GEE results with p-values in the range of 10-6 to 10-5 for hemostatic or hematological phenotypes. In relating 100K SNPs to known candidate genes, we identified two SNPs (rs1582055, rs4897475) in erythrocyte membrane protein band 4.1-like 2 (EPB41L2) associated with hematological phenotypes (GEE p < 10-3). In linkage analyses, the highest linkage LOD score for hemostatic factors was 3.3 for factor VII on chromosome 10 around 15 Mb, and for hematological phenotypes, LOD 3.4 for hemoglobin on chromosome 4 around 55 Mb. All GEE and FBAT association and variance components linkage results can be found at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007

Conclusion

Using genome-wide association methodology, we have successfully identified a SNP in complete LD with a sequence variant previously shown to be strongly associated with factor VII, providing proof of principle for this approach. Further study of additional strongly associated SNPs and linked regions may identify novel variants that influence the inter-individual variability in hemostatic factors and hematological phenotypes.

Background

The relationship of hemostasis and thrombosis with atherothrombotic cardiovascular disease has been extensively studied in the past decades. Elevated circulating levels of hemostatic factors, such as fibrinogen [13], plasminogen activator inhibitor (PAI-1) [4, 5], von Willebrand factor (vWF) [6], tissue plasminogen activator (tPA) [4, 5, 7], factor VII (FVII) [8], and D-dimer [9, 10] are linked to the development of atherothrombosis and are risk markers for coronary heart disease (CHD), stroke and other cardiovascular disease (CVD) events.

In addition to coagulation proteins, the cellular and rheological components of circulating blood have been implicated in CHD, stroke and peripheral arterial disease, including hematological phenotypes such as hematocrit (HCT), hemoglobin (Hgb), red blood cell count (RBCC) and size, mean corpuscular volume (MCV) and mean corpuscular hemoglobin (MCH) [11, 12], as well as measures of platelet aggregation (induced by adenosine 5'-diphosphate (ADP), epinephrine (Epi) and collagen respectively) [12, 13], and viscosity [14, 15].

Cis-acting sequence variants in the following genes – fibrinogen-β (FGB), fibrinogen-α (FGA), fibrinogen-γ (FGG), FVII (F7), and PAI-1 (SERPINE1) – have been associated with corresponding levels of circulating hemostatic factor. By comprehensively characterizing common genetic variation at each of these loci, we have recently clarified that cis-acting variants, in sum, explain a modest proportion of phenotypic variation, ranging from 1% – 10% [16, 17]. For hematological variables such as hematocrit and hemoglobin, sequence variation in the major hemoglobin genes is well described to be associated with anemias, such as beta- and alpha-thalassemia, and sickle cell anemia [1820].

Systematic searches for novel genes beyond the known genetic determinants influencing these phenotypes have been carried out using genome-wide linkage analyses with microsatellite markers: Chromosome regions that may harbor novel loci influencing fibrinogen, PAI-1 [21, 22], hematocrit, Hgb, RBCC, MCV and MCH [23, 24], have been identified. However, linkage scans with microsatellite markers generally had low power to detect loci with small effects, and lacked precision in localizing the loci; thus, few novel loci have been identified.

The recent completion of a genome-wide scan using the Affymetrix GeneChip Human Mapping 100K single nucleotide polymorphism (SNP) set on participants in the Framingham Heart Study offered the opportunity to conduct a genome-wide association study (GWAS) and linkage scan for variants that influence hemostatic factors and hematological phenotypes.

Methods

Study participants and genotyping methods

The Framingham Heart Study design and the genotyping of the Affymetrix GeneChip Human Mapping 100K SNP set on Framingham Heart Study participants are detailed in the overview of this project [25]. To avoid potential bias due to genotyping artifacts, we limited the association analyses to 70987 SNPs on autosomes with minor allele frequency (MAF) ≥ 10%, genotyping call rate ≥ 80%, and Hardy-Weinberg equilibrium test p-value ≥ 0.001.

Measurements of hemostatic factors and hematological phenotypes

Venous blood samples of Framingham Heart Study Offspring Cohort taken at the first and second examination cycles (1971–1975, and 1979–1983) were used to measure Hgb, RBCC, MCV and MCH, and samples taken at the fifth examination cycle (1991–1995) were used to measure all the hemostatic factors, platelet aggregation, D-dimer, and viscosity. Fibrinogen was additionally measured at the sixth (1995–1998) and seventh (1998–2001) examination cycles, and PAI-I antigen levels at the sixth exam. Details of the assessment of hemostatic factor levels have been described previously [17, 26]. Plasma fibrinogen levels were measured using the Clauss method [27]. Plasma PAI-I antigen, tPA antigen, von Willebrand factor and FVII antigen were assessed using enzyme-linked immunosorbent assays.

The determination of hematological phenotypes has been detailed previously. Platelet aggregation was performed according to the method of Born [28]. The reagents used were epinephrine, ADP and collagen. The percent extent of aggregation in duplicate to epinephrine and ADP was determined in varying concentrations (0.01 to 15 mmol/L). For each subject, the aggregation response (yes/no) was also tested to a fixed concentration of arachidonic acid (5 mg/mL). The collagen lag time was measured in response to 1.9 mmol/L collagen. Participants who were taking aspirin were excluded from the analyses for platelet aggregation phenotypes as well as PAI-1 and tPA.

HCT was measured by the Wintrobe method [29]. Blood was collected and spun at 5000 rpm for 20 minutes in a balanced oxalate tube. The percent of total blood volume that was due to red blood cells was determined visually against a calibrated scale. MCV is the average volume of an individual's red blood cells determined as the ratio of HCT to RBCC. MCH is the average amount of hemoglobin of an individual's red cell determined as the ratio of Hgb to RBCC.

Statistical methods

Standardized multivariable adjusted residuals of the hemostatic and hematological phenotypes were computed and used in all the linkage and association analyses. Covariates used in the adjustments were determined based upon what has been reported in the literature as potential risk factors for hemostatic factors or hematological phenotypes. Hardy-Weinberg equilibrium was examined using an exact chi-square test statistic [30]. Association between each SNP and each hemostatic or hematological phenotype was examined using a population based association method via generalized estimating equations (GEE) [31] and family-based association test (FBAT) [32], assuming an additive genetic model. Variance components linkage analyses were conducted using a subset of SNPs with pairwise r2 < 0.5. Details of both association and linkage methods are described in the overview of this project [25].

In secondary analyses, we combined the GEE association tests results across multiple phenotypes that may share the common pathway to reduce the type I error rates, and possibly detect SNPs of smaller effect sizes. We ranked SNPs by the number of GEE test p-values less than 0.01, and then by the geometric mean of the GEE test p-values. We also examined the β coefficient from the GEE regression that is the change in the phenotype in one standardized deviation unit with an increment of a copy of the alphabetically second allele (for example, allele G for a SNP with alleles A and G). This analysis was conducted for a phenotype assessed using multiple measurement methods such as the platelet aggregation with ADP-, collagen-, and Epi-induced platelet aggregation; or for a phenotype with serial measurements such as fibrinogen level measured at examination cycles 5, 6 and 7.

We attempted to identify association of 100K SNPs in or within 60 kilo base pairs (kbp) of selected candidate genes previously reported to be associated with hemostatic factors or hematological phenotypes. For hemostatic factors and platelet aggregation phenotypes, we included the following candidate genes in the search: F7, fibrinogen gene cluster (FGB, FGA, FGG), SERPINE1, plasminogen activator-tissue (PLAT), vWF and integrin beta 3 (ITGB3). For hematological phenotypes excluding platelet aggregation, we included erythropoietin receptor (EPOR), erythropoietin (EPO), erythrocyte membrane protein band 4.1-like 2 (EPB41L2), Kruppel-like factor 1(KLF1), heme binding protein 2 (HEBP2), the hemoglobin gene clusters on chromosome 11: hemoglobin-β chain complex (HBB), hemoglobin-δ (HBD), hemoglobin-γ A (HBG1), hemoglobin-γ G (HBG2), hemoglobin-ε 1 (HBE1), and the hemoglobin gene clusters on chromosome 16: hemoglobin-α 1 (HBA1), hemoglobin-α 2 (HBA2), hemoglobin-μ (HBM).

Results

Table 1 displays the hemostatic and hematological phenotypes analyzed in this study, as well as the number of individuals, examination cycles, and covariates used in multivariable models. The sample size ranged from 702 to 1073. Traits measured at multiple examinations were analyzed using multivariable adjusted residuals from each examination measure, and also the average of all the multivariable adjusted residuals from individual examination cycles.
Table 1

Description of hemostatic factors, hematological phenotypes, and covariates adjustment

Phenotype

Number of adjusted phenotypes

Offsrping cohort exam cycles†

Sample size (min-max)

Covariates adjusted

Hemostatic factors:

    

fibrinogen

4

5, 6, 7 and average

986–1073

age (and its squared and cubic terms), sex, body mass index, prevalent cardiovascular disease, current cigarette smoking, hypertension treatment, systolic blood pressure, diastolic blood pressure, estrogen therapy (women only), alcohol intake, triglycerides, diabetes, total cholesterol, and the ratio of total cholesterol to high-density lipoprotein cholesterol.

PAI-1

3

5, 6 and average

788–1037

 

tPA

1

5

786

 

vWF

1

5

883

 

FVII

1

5

886

 

D-dimer

1

5

987

 

Hematological and rheological phenotypes

    

platelet aggregation (ADP-induced)

1

5

724

 

platelet aggregation (collagen-induced)

1

5

702

 

platelet aggregation (Epi-induced)

1

5

719

 

Viscosity

1

5

832

 

Hgb

3

1, 2, and average

903–1066

age, sex, height, weight, high-density lipoprotein cholesterol, total serum protein, alcohol intake, triglycerides, and current cigarette smoking

RBCC

3

1, 2, and average

903–1062

 

MCH

3

1, 2, and average

903–1062

 

Hematocrit*

3

1, 2, and average

903–1062

 

MCV

3

1, 2, and average

903–1062

 

WBC*

3

1, 2, and average

903–1062

 

*Results for these two phenotypes are not reported in this manuscript. The complete results of all the phenotypes listed above can be found at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007

Among individuals who were included in the genotyping and had at least one hemostatic factor or platelet aggregation phenotype measured at examination cycle five, 52% were women, mean age was 52 years, and 6% had prevalent CVD. Among individuals who were included in the genotyping and had at least one hematological phenotype measured at examination cycle one or two, 52% were women, with a mean age over the two examinations of 36 years, and 2% had prevalent CVD.

Association between SNPs and hemostatic and hematological phenotypes

We report the 25 SNPs with lowest GEE association test p-values in Table 2 for hemostatic factors, and in Table 3 for hematological phenotypes. The lowest GEE p-value (4.5*10-16) for hemostatic factors was obtained from the test of association between circulating levels of FVII and rs561241; this SNP resides near the F7 gene on chromosome 13 and is in complete linkage disequilibrium (LD) (r2 = 1) with the Arg353Gln F7 SNP (rs6046) we previously reported to account for 9% of total phenotypic variance [16]. The lowest GEE p-value (6.9*10-8) for hematological phenotypes was obtained in the test of association between MCH and rs1397048 on chromosome 11 near the olfactory receptors, olfactory receptor, family 5, subfamily AP, member 2 (OR5AP2), olfactory receptor, family 5, subfamily AR, member 1 (OR5AR1), olfactory receptor, family 9, subfamily G, member 1(OR9G1) and olfactory receptor, family 9, subfamily G, member 4 (OR9G4). The 25 SNPs with lowest FBAT association test p-values are presented in Additional file 1, Table A1 and Table A2, respectively.
Table 2

The 25 SNPs with lowest GEE association test p-values with hemostatic factors measured at exam 5

Phenotype*

SNP

MAF

CHR

Physical Position (bp)

GEE p-val (Rank)††

FBAT p-val†††

Genes within 60 kb

Fibrinogen

rs6683832

0.41

1

62,988,925

5.6 × 10 -5 (4)

3.4 × 10-2

APG4C

Fibrinogen

rs4861952

0.11

4

182,696,179

3.5 × 10 -5 (24)

8.2 × 10-3

 

Fibrinogen

rs10506540

0.12

12

65,699,364

2.2 × 10 -5 (16)

3.3 × 10-2

 

Fibrinogen

rs974673

0.15

14

33,550,265

3.1 × 10 -5 (19)

1.3 × 10-3

 

FVII

rs966321

0.47

1

4,225,577

7.6 × 10 -6 (6)

4.5 × 10-2

 

FVII

rs1245072

0.17

1

69,827,777

1.8 × 10 -5 (13)

7.5 × 10-3

LRRC7

FVII

rs2362932

0.24

1

242,240,325

2.4 × 10 -5 (17)

1.5 × 10-2

SMYD3

FVII

rs10496112

0.30

2

64,535,384

3.3 × 10 -5 (23)

7.4 × 10-3

HSPC159

FVII

rs1001254

0.13

3

7,909,333

2.0 × 10 -5 (14)

2.0 × 10-2

 

FVII

rs4591494

0.19

3

7,957,827

9.2 × 10 -6 (7)

1.2 × 10-4

 

FVII

rs10488360

0.30

7

4,184,450

7.2 × 10 -6 (5)

9.3 × 10-3

 

FVII

rs727435

0.13

9

80,809,022

9.6 × 10 -6 (8)

2.8 × 10-2

 

FVII

rs7938734

0.31

11

49,834,857

3.2 × 10 -5 (21)

7.0 × 10-2

 

FVII

rs561241

0.12

13

112,808,035

4.5 × 10 -16 (1)

3.4 × 10-4

MCF2L; AB116074; AK092739; AK123267; AB002360; F7; CR603372; F10; PROZ

PAI1

rs10490733

0.14

2

137,872,229

3.2 × 10 -5 (22)

2.4 × 10-2

 

PAI1

rs4460176

0.29

5

109,524,859

3.1 × 10 -6 (3)

7.6 × 10-2

 

tPA

rs10493485

0.29

1

71,783,150

1.6 × 10 -6 (2)

1.1 × 10-3

BC036771; NEGR1

tPA

rs10494076

0.32

1

108,050,369

3.1 × 10 -5 (20)

2.3 × 10-2

VAV3

tPA

rs2029637

0.25

3

113,404,510

1.3 × 10 -5 (10)

6.1 × 10-2

SLC9A10

tPA

rs953377

0.28

6

23,998,670

1.5 × 10 -5 (11)

3.4 × 10-2

 

vWF

rs9295740

0.14

6

27,797,481

2.8 × 10 -5 (18)

5.7 × 10-3

 

vWF

rs202906

0.12

6

28,119,631

2.1 × 10 -5 (15)

1.1 × 10-1

ZNF165

vWF

rs708356

0.35

12

128,998,794

1.5 × 10 -5 (12)

2.4 × 10-2

AK127723

vWF

rs1954971

0.38

18

26,633,241

1.0 × 10 -5 (9)

1.6 × 10-2

 

vWF

rs7319671

0.30

13

36,923,224

3.6 × 10 -5 (25)

1.1 × 10-2

 

* All the phenotypes reported here were multivariable adjusted residuals from the measurements obtained at exam cycle 5.

Physical position is in base pair (bp) and based on the May 2004 human reference sequence (NCBI Build 35).

††P-value from GEE genotype association test and rank of the GEE p-values in ascending order.

†††P-value from family-based association test using the FBAT program.

Table 3

The 25 SNPs with lowest GEE association tests p-values with hematological phenotypes

Phenotype*

SNP

MAF

CHR

Physical Position (bp)

GEE Pval (Rank)††

FBAT Pval†††

Genes within 60 Kb

Hgb

rs4133289

0.19

1

156,267,010

1.6 × 10 -7 (2)

6.0 × 10-4

OR10J1; OR10J5

Hgb

rs1510107

0.41

2

53,071,788

1.0 × 10 -5 (17)

2.2 × 10-3

 

Hgb

rs1160297

0.43

2

53,148,971

1.0 × 10 -6 (4)

8.3 × 10-4

 

Hgb

rs2357013

0.45

2

53,177,780

6.1 × 10 -6 (14)

1.3 × 10-3

 

Hgb

rs7844723

0.45

8

122,977,684

2.1 × 10 -6 (5)

2.6 × 10-3

 

MCH

rs1829883

0.41

5

98,809,002

5.8 × 10 -6 (11)

1.4 × 10-2

 

MCH

rs1200821

0.47

10

37,599,586

5.9 × 10 -6 (13)

1.0 × 10-1

ANKRD30A

MCH

rs1397048

0.40

11

56,222,675

6.9 × 10 -8 (1)

1.0 × 10-2

OR5AP2; OR5AR1; OR9G1; OR9G4

platelet aggregation (ADP-induced)

rs10493895

0.19

1

97,983,247

1.6 × 10 -5 (23)

4.5 × 10-2

BC064027; DPYD

platelet aggregation (ADP-induced)

rs10484128

0.15

14

97,712,325

5.8 × 10 -6 (12)

1.3 × 10-3

 

platelet aggregation (collagen-induced)

rs848523

0.42

2

36,659,307

2.1 × 10 -5 (24)

4.3 × 10-1

CRIM1

platelet aggregation (collagen-induced)

rs565229

0.10

11

121,694,675

3.7 × 10 -6 (6)

2.6 × 10-2

 

platelet aggregation (collagen-induced)

rs10506458

0.13

12

61,731,359

4.5 × 10 -6 (9)

1.1 × 10-4

 

platelet aggregation (Epi-induced)

rs6811964

0.11

4

158,143,059

1.3 × 10 -5 (20)

5.5 × 10-2

PDGFC

platelet aggregation (Epi-induced)

rs1958208

0.32

14

81,194,793

1.1 × 10 -5 (18)

7.0 × 10-1

 

platelet aggregation (Epi-induced)

rs10502583

0.17

18

28,011,131

1.1 × 10 -5 (19)

1.1 × 10-2

RNF138; MEP1B

RBCC

rs9253

0.18

1

37,627,906

4.2 × 10 -6 (7)

1.1 × 10-5

FLJ11730; BC016328

RBCC

rs10489087

0.13

4

13,470,685

4.5 × 10 -6 (8)

9.6 × 10-4

 

RBCC

rs636864

0.21

6

149,567,299

6.3 × 10 -6 (15)

1.3 × 10-4

 

RBCC

rs727979

0.14

6

149,635,613

7.5 × 10 -6 (16)

2.6 × 10-5

MAP3K7IP2

RBCC

rs6108011

0.28

20

7,500,504

5.8 × 10 -6 (10)

7.0 × 10-2

 

Viscosity

rs10490258

0.11

2

40,717,605

1.5 × 10 -5 (21)

2.9 × 10-2

 

Viscosity

rs1359339

0.18

6

18,606,507

2.2 × 10 -5 (25)

2.3 × 10-2

IBRDC2

Viscosity

rs10485968

0.20

7

81,108,037

1.6 × 10 -5 (22)

3.0 × 10-3

 

Viscosity

rs7159841

0.21

14

46,933,585

2.1 × 10 -7 (3)

2.0 × 10-1

MAMDC1

* For Hgb, MCH and RBCC reported here, multivariable adjusted residuals from average of measurements over exam cycles 1 and 2 were used; for all platelet aggregation phenotypes, and viscosity reported here, multivariable adjusted residuals from measurements at examination cycle 5 were used.

Physical position is in base pair (bp) and based on the May 2004 human reference sequence (NCBI Build 35).

††P-value from GEE genotype association test and rank of the GEE p-values in ascending order.

†††P-value from family-based association test using the FBAT program.

Linkage results

Maximum multipoint LOD scores greater than 2 and the 1.5-LOD support intervals around the maximum LOD scores are presented in Table 4. The highest LOD score for hemostatic factors was 3.3 for factor VII at approximately 15 Mb on chromosome 10. The highest LOD for hematological phenotypes was 3.4 for Hgb at approximately 55 Mb on chromosome 4.
Table 4

Maximum LOD scores (≥2) on each chromosomes for hemostatic factors and hematological phenotypes

Phenotype*

SNP

CHR

Physical Position (bp)

LOD

1.5 LOD Support Interval

Fibrinogen

rs1273819

2

227,307,918

2.4

221,455,139

234,213,322

FVII

rs1542535

3

138,548,560

2.8

128,478,856

147,720,726

FVII

rs2400107

10

15,113,999

3.3

13,834,912

21,013,729

PAI1

143xd8

8

2,117,752

2.3

181,076

5,519,520

vWF

rs10514670

3

18,544,296

2.1

9,261,438

25,964,778

platelet aggregation (ADP-induced)

rs4148751

7

86,787,804

2.0

81,841,699

94,233,832

platelet aggregation (collagen-induced)

rs17310225

X

41,973,417

2.1

30,937,095

81,367,217

Hgb

rs2412522

4

54,779,471

3.4

41,552,790

57,899,713

Hgb

rs10514838

9

120,826,350

2.5

113,537,965

133,903,932

MCVavg12

rs38993

7

153,013,905

2.2

149,613,755

154,729,817

MCVavg12

rs9299952

11

19,075,037

3.3

12,241,666

21,560,867

MCVavg12

rs10522006

X

32,347,187

2.3

27,553,388

40,183,712

RBCC

rs956275

4

57,108,334

2.5

44,437,719

74,935,678

RBCC

rs2023048

6

162,441,307

2.9

156,253,205

165,513,097

RBCC

rs10500769

11

12,975,794

3.2

9,335,581

15,231,734

RBCC

rs10500770

11

13,053,050

3.2

9,335,581

15,231,734

RBCC

rs2178692

12

6,706,312

2.8

4,817,859

9,212,944

RBCC

rs10498633

14

91,996,705

2.6

74,270,406

93,717,052

RBCC

GATA27A03

15

100,152,332

2.3

98,566,644

100,152,332

RBCC

rs2271090

17

76,861,200

2.3

73,915,579

78,166,561

RBCC

rs486633

18

555,760

3.3

156,277

4,009,209

RBCC

rs20037

22

27,802,395

2.2

25,095,430

42,711,182

* For Hgb, MCH and RBCC reported here, multivariable adjusted residuals from average of measurements over exam cycles 1 and 2 were used; for all platelet aggregation phenotypes, fibrinogen, FVII, PAI1, vWF reported here, multivariable adjusted residuals from measurements at examination cycle 5 were used.

Physical position is in base pair (bp) and based on the May 2004 human reference sequence (NCBI Build 35).

Combining association tests across multiple phenotypes

The top 10 SNPs with most number of p-values < 0.01 and lowest mean p-values are reported in Tables 5 and 6 for platelet aggregation phenotypes and fibrinogen levels respectively. The top ranked SNP for platelet aggregation was rs10500631 on chromosome 11 located near an olfactory gene cluster. The p-values of the GEE association test for ADP-, collagen- and epinephrine-induced platelet aggregation levels with this SNP were all less than 0.01, with average p-value 0.007 over the three tests. The range of the regression coefficients was 0.19–0.24, indicating the effect size was consistently estimated across the three phenotypes.
Table 5

Top 10 ranked SNPs in combining GEE association tests of ADP-induced, Collagen-induced and Epi-induced platelet aggregation levels

         

GEE P-value of individual phenotypes

SNP

MAF

CHR

Physical Position (bp)*

Mean GEE p-value

Range of Beta Coefficient (min, max)

Number of Phenotypes with GEE P-value < 0.01

Gene within 60 Kb

ADP

Collagen

Epi

rs10500631

0.13

11

4,882,639

6.6 × 10-3

0.19

0.24

3

OR51S1; OR51T1; OR51A7; OR51G2; OR51G1; OR51A4; OR51A2

9.7 × 10-3

7.8 × 10-3

3.8 × 10-3

rs930323

0.18

1

221,172,525

1.9 × 10-3

-0.26

-0.16

2

CNIH3

3.8 × 10-2

1.6 × 10-3

1.2 × 10-4

rs7033457

0.25

9

7,383,934

2.6 × 10-3

0.15

0.24

2

 

2.5 × 10-3

3.7 × 10-2

2.0 × 10-4

rs2974490

0.11

5

113,433,775

2.7 × 10-3

0.07

0.28

2

 

4.2 × 10-1

8.7 × 10-5

5.2 × 10-4

rs10517543

0.13

4

40,332,115

3.2 × 10-3

0.13

0.27

2

AF262323; FLJ20273

5.8 × 10-3

1.0 × 10-1

5.2 × 10-5

rs2916601

0.13

5

89,556,637

3.5 × 10-3

0.11

0.29

2

 

9.7 × 10-2

3.2 × 10-4

1.4 × 10-3

rs4350297

0.18

10

106,463,038

3.9 × 10-3

-0.24

-0.10

2

SORCS3

3.5 × 10-4

1.0 × 10-1

1.7 × 10-3

rs7956194

0.42

12

108,340,545

4.3 × 10-3

0.09

0.20

2

FLJ37587; KCTD10; BC040062; AK056912; BC051266; UBE3B

3.6 × 10-3

1.1 × 10-1

2.0 × 10-4

* Physical position is in base pair (bp) and based on the May 2004 human reference sequence (NCBI Build 35).

β coefficient is the change in the phenotype in one standardized deviation unit with an increment of a copy of the alphabetically higher allele.

Table 6

Top 10 ranked SNPs in combining GEE association tests of fibrinogen levels measured at examination cycles 5, 6 and 7

SNP

MAF

CHR

Physical Position (bp)*

mean GEE P-value

Range of β Coefficients (min, max)

Number of Phenotypes with GEE P-value < 0.01

Gene within 60 Kb

GEE P-value of individual phenotypes

         

Exam 5

Exam 6

Exam 7

rs4861952

0.11

4

182,696,179.00

4.9 × 10-4

-0.28

-0.17

3

 

3.5 × 10-5

9.2 × 10-3

3.6 × 10-4

rs1869733

0.15

8

63,970,954.00

5.5 × 10-4

-0.23

-0.16

3

FLJ39630

6.7 × 10-5

4.1 × 10-3

6.1 × 10-4

rs9317390

0.47

13

63,625,531.00

6.5 × 10-4

0.13

0.17

3

 

3.8 × 10-3

1.9 × 10-4

3.8 × 10-4

rs1561478

0.15

4

61,317,252.00

7.3 × 10-4

0.15

0.22

3

 

3.0 × 10-4

1.6 × 10-4

8.6 × 10-3

rs277330

0.16

5

53,489,351.00

1.1 × 10-3

-0.22

-0.16

3

ARFRP2

1.5 × 10-3

1.9 × 10-4

4.1 × 10-3

rs1649053

0.41

10

59,991,493.00

1.2 × 10-3

0.13

0.18

3

 

2.8 × 10-3

5.8 × 10-3

1.0 × 10-4

rs2175271

0.09

15

34,097,057.00

1.5 × 10-3

-0.26

-0.20

3

 

6.5 × 10-3

3.1 × 10-4

1.8 × 10-3

rs9323656

0.06

14

77,394,323.00

1.5 × 10-3

-0.31

-0.27

3

ADCK1; AK096919

1.2 × 10-3

2.5 × 10-3

1.3 × 10-3

rs1423741

0.42

16

59,874,592.00

1.8 × 10-3

-0.17

-0.11

3

 

7.6 × 10-4

9.4 × 10-3

7.6 × 10-4

rs10497881

0.32

2

205,818,470.00

2.2 × 10-3

0.14

0.17

3

ALS2CR19

4.8 × 10-4

5.0 × 10-3

4.5 × 10-3

* Physical position is in base pair (bp) and based on the May 2004 human reference sequence (NCBI Build 35).

β coefficient is the change in the phenotype in one standardized deviation unit with an increment of a copy of the alphabetically higher allele.

For fibrinogen, the top ranked SNP was rs4861952 on chromosome 4, which was also listed in the Table 2 as one of the 25 most significantly associated SNPs with hemostatic factors. This SNP was consistently associated with fibrinogen levels across three examination cycles with effect size ranging from -0.28 to -0.17.

Association of SNPs in known candidate genes

100K SNPs residing in or near known candidate genes for hemostatic factors are presented in Table 7. Among the candidate genes for hemostatic factors, no 100K SNP was in or within 60 kb of PLAT. Only SNPs in or near the rest of the candidate genes (F7, FGG, FGA, FGB, ITGB3, SERPINE1 and vWF) are presented. Among all these associations, three reached nominal significance (p-value < 0.05): rs561241 for factor VII, and rs6950982 and rs6956010 for PAI-1.
Table 7

Association between SNPs in/near known hemostatic candidate genes, and the corresponding phenotypes

Candidate Gene

SNP

CHR

Physical Position (bp)*

MAF

Position to Gene

Function

Phenotype

GEE Association Pvalue

F7

rs561241

13

112,808,035

0.12

NEAR

unknown

FVII, exam 5

4.5 × 10-16

FGG

rs2066864

4

155,883,300

0.19

IN

intron

Fibrinogen, average

0.239

FGG

rs2066864

4

155,883,300

0.19

IN

intron

Fibrinogen, exam 5

0.711

FGG

rs2066864

4

155,883,300

0.19

IN

intron

Fibrinogen, exam 6

0.095

FGG

rs2066864

4

155,883,300

0.19

IN

intron

Fibrinogen, exam 7

0.586

FGG

rs1074801

4

155,933,889

0.49

NEAR

unknown

Fibrinogen, average

0.667

FGG

rs1074801

4

155,933,889

0.49

NEAR

unknown

Fibrinogen, exam 5

0.898

FGG

rs1074801

4

155,933,889

0.49

NEAR

unknown

Fibrinogen, exam 6

0.521

FGG

rs1074801

4

155,933,889

0.49

NEAR

unknown

Fibrinogen, exam 7

0.608

ITGB3

rs4525555

17

42,692,948

0.31

IN

intron

Platelet Aggregation, ADP, exam 5

0.231

ITGB3

rs4525555

17

42,692,948

0.31

IN

intron

Platelet Aggregation, Collagen, exam 5

0.375

ITGB3

rs4525555

17

42,692,948

0.31

IN

intron

Platelet Aggregation, epinephrine, exam 5

0.292

ITGB3

rs10514919

17

42,697,128

0.24

IN

intron

Platelet Aggregation, ADP, exam 5

0.495

ITGB3

rs10514919

17

42,697,128

0.24

IN

intron

Platelet Aggregation, Collagen, exam 5

0.331

ITGB3

rs10514919

17

42,697,128

0.24

IN

intron

Platelet Aggregation, epinephrine, exam 5

0.302

ITGB3

rs2015729

17

42,709,492

0.36

IN

intron

Platelet Aggregation, ADP, exam 5

0.326

ITGB3

rs2015729

17

42,709,492

0.36

IN

intron

Platelet Aggregation, Collagen, exam 5

0.919

ITGB3

rs2015729

17

42,709,492

0.36

IN

intron

Platelet Aggregation, epinephrine, exam 5

0.963

SERPINE1

rs6950982

7

100,360,038

0.18

NEAR

unknown

PAI1, average

0.187

SERPINE1

rs6950982

7

100,360,038

0.18

NEAR

unknown

PAI1, exam 5

0.035

SERPINE1

rs6950982

7

100,360,038

0.18

NEAR

unknown

PAI1, exam 6

0.688

SERPINE1

rs6956010

7

100,360,470

0.19

NEAR

unknown

PAI1, average

0.218

SERPINE1

rs6956010

7

100,360,470

0.19

NEAR

unknown

PAI1, exam 5

0.053

SERPINE1

rs6956010

7

100,360,470

0.19

NEAR

unknown

PAI1, exam 6

0.740

VWF

rs917858

12

5,952,199

0.32

IN

intron

wVW, exam 5

0.398

VWF

rs917859

12

5,952,374

0.32

IN

intron

wVW, exam 5

0.413

VWF

rs2239138

12

5,952,819

0.32

IN

intron

wVW, exam 5

0.487

VWF

rs216901

12

5,975,129

0.48

IN

intron

wVW, exam 5

0.297

VWF

rs216903

12

5,975,760

0.48

IN

intron

wVW, exam 5

0.316

VWF

rs216904

12

5,976,279

0.34

IN

intron

wVW, exam 5

0.584

* Physical position is in base pair (bp) and based on the May 2004 human reference sequence (NCBI Build 35).

'NEAR' means within 60 kb to a gene; 'IN' means within a gene.

††Phenotypes are multivariate adjusted residuals.

Among the candidate genes for hematological traits, no 100K SNP was in or within 60 Kb of EPOR, EPO, KLF1, HBA1, HBA2, HBM. For the rest of the candidate genes, associations between hematological phenotypes and 100K SNPs in/near EPB41L2, the beta hemoglobin gene cluster on chromosome 11 (HBB, HBD, HBG1, HBG2, HBE1), and HEBP2 are presented in Table 8. The most significant associations were SNP rs1582055 near EPB41L2 with hematocrit (p = 7.7 × 10-5), Hgb (p = 2.9 × 10-4), and RBCC (p = 3.9 × 10-4); SNP rs4897475 with hematocrit (p = 1.6 × 10-4) and Hgb (p = 6.0 × 10-4).
Table 8

Association between hematological phenotypes and SNPs in/near known candidate genes

       

GEE Association Test P-values††

Candidate Gene

SNP

CHR

Physical Position (bp)*

MAF

Position to Gene

Function

Hematocrit

Hgb

MCH

MCV

RBCC

EPB41L2

rs7741731

6

131,152,063

0.17

NEAR

unknown

0.488

0.326

0.847

0.549

0.163

EPB41L2

rs1582055

6

131,186,056

0.3

NEAR

unknown

7.7 × 10-5

2.9 × 10-4

0.427

0.762

3.9 × 10-4

EPB41L2

rs1413753

6

131,192,197

0.34

NEAR

intron

0.003

0.007

0.691

0.730

0.007

EPB41L2

rs1413754

6

131,192,319

0.3

NEAR

intron

0.242

0.158

0.561

0.039

0.016

EPB41L2

rs4075265

6

131,208,150

0.33

IN

untranslated

0.001

0.004

0.470

0.506

0.002

EPB41L2

rs915171

6

131,226,607

0.26

IN

intron

0.712

0.486

0.355

0.232

0.273

EPB41L2

rs9285468

6

131,233,823

0.33

IN

intron

0.003

0.005

0.437

0.921

0.022

EPB41L2

rs6938586

6

131,251,097

0.18

IN

intron

0.878

0.511

0.578

0.661

0.951

EPB41L2

rs3777442

6

131,251,481

0.48

IN

intron

0.017

0.124

0.834

0.568

0.044

EPB41L2

rs4897472

6

131,254,831

0.49

IN

intron

0.002

0.022

0.972

0.551

0.009

EPB41L2

rs4897475

6

131,274,643

0.28

IN

intron

1.6 × 10-4

6.0 × 10-4

0.633

0.485

0.011

EPB41L2

rs1334689

6

131,275,701

0.31

IN

intron

0.001

0.005

0.703

0.639

0.020

EPB41L2

rs7748468

6

131,297,742

0.3

IN

intron

0.002

0.005

0.616

0.956

0.009

EPB41L2

rs2105250

6

131,325,875

0.28

IN

unknown

0.013

0.002

0.050

0.696

0.076

EPB41L2

rs9321263

6

131,340,606

0.33

IN

unknown

0.461

0.137

0.188

0.095

0.056

EPB41L2

rs1811949

6

131,340,872

0.32

IN

unknown

0.511

0.210

0.176

0.119

0.076

EPB41L2

rs9321265

6

131,345,926

0.14

IN

unknown

0.985

0.909

0.734

0.941

0.896

EPB41L2

rs7761311

6

131,352,801

0.37

IN

unknown

0.986

0.553

0.202

0.066

0.143

EPB41L2

rs1412540

6

131,368,085

0.24

IN

unknown

0.006

0.006

0.356

0.725

0.008

EPB41L2

rs6907809

6

131,374,355

0.21

IN

unknown

0.739

0.928

0.153

0.049

0.281

EPB41L2

rs951251

6

131,432,905

0.15

NEAR

unknown

0.851

0.789

0.419

0.009

0.075

HBB, HBD

rs4128714

11

5,151,240

0.25

NEAR

unknown

0.557

0.402

0.345

0.175

0.431

HBB, HBD, HBG1, HBG2, HBE1

rs2105819

11

5,216,303

0.46

NEAR

unknown

0.007

0.039

0.128

0.027

0.463

HBB, HBD, HBG1, HBG2, HBE1

rs968856

11

5,217,152

0.47

NEAR

unknown

0.013

0.049

0.202

0.016

0.576

HBB, HBD, HBG1, HBG2, HBE1

rs10488676

11

5,225,373

0.48

NEAR

unknown

0.051

0.134

0.174

0.047

0.735

HBB, HBD, HBG1, HBG2, HBE1

rs10488675

11

5,254,606

0.27

NEAR

unknown

0.050

0.180

0.798

0.077

0.920

HBG1, HBG2, HBE1

rs3898916

11

5,284,996

0.38

NEAR

unknown

0.089

0.165

0.353

0.260

0.367

HEBP2

rs10499199

6

138,811,539

0.16

NEAR

intron

0.503

0.585

0.557

0.412

0.972

HEBP2

rs10499200

6

138,813,645

0.16

NEAR

intron

0.706

0.742

0.535

0.382

0.793

HEBP2

rs10499201

6

138,818,107

0.16

NEAR

intron

0.633

0.725

0.487

0.414

0.897

HEBP2

rs6902919

6

138,819,479

0.21

NEAR

intron

0.789

0.977

0.225

0.148

0.541

HEBP2

rs6926204

6

138,820,053

0.16

NEAR

intron

0.887

0.979

0.429

0.381

0.660

* Physical position is in base pair (bp) and based on the May 2004 human reference sequence (NCBI Build 35).

'NEAR' means within 60 kb to a gene; 'IN' means within a gene.

†† The p-values are from the GEE association test on multivariable adjusted phenotypes listed below.

Discussion

We conducted a GWAS and a genome-wide linkage analyses for hemostatic factors and hematological phenotypes measured in Framingham Heart Study Offspring participants. We identified a highly significant association between factor VII level and SNP rs561241 in complete LD with the F7 SNP rs6046 (Arg353Gln) previously demonstrated to explain about 9% of total phenotypic variation. This association is significant after Bonferroni correction for multiple testing (we used a conservative α = 5 × 10-8), and confirms the strong association at this locus that has previously been reported by us and others. This SNP was also significant (p-value = 3.4 × 10-4) at a nominal α level 0.05 for FBAT and linkage test (LOD = 1.8, p-value = 0.002), but not after Bonferroni correction. That may be explained by the well known fact that FBAT and linkage test are less powerful than population-based association tests.

FBAT lacks power to detect variants that explain small proportion of variance for this study. It is difficult to distinguish true positives from false ones among FBAT results because it was evident that few 100K SNPs explain a large proportion of variance for hemostatic factors or hematological phenotypes. Given that there is no evidence for major population substructure in FHS [33] and there is greater power from use of GEE testing, we emphasize our population-based GEE analysis results in this report. Linkage analyses have the same problem of low power to detect small effects. However, a linkage peak can be caused by loci in linkage but not in LD with the SNPs, or by several loci of small effects in the region. Thus linkage peaks deserve additional attention. For example, we identified a linkage peak on chromosome 10 for multivariate adjusted factor VII. The SNP underneath the peak is rs2400107. However, the GEE association p-value was 0.52. This could occur because rs2400107 was linked but not in LD with the disease locus (loci) under the peak, or because this linkage peak was caused by several loci of small effects, or this peak was a false positive. Therefore, a more careful examination of the association results of SNPs under the linkage peak along with potentially additional genotyping may be needed to confirm the linkage results.

Among the SNPs with top GEE p-values in single phenotype or multiple phenotypes analyses, only a few resided near genes that were known for a likely role in hemostasis and thrombosis and hematological biology. For hemostatic factors, the cis-acting SNP rs561241 near F7 gene was associated with factor. For hematological phenotypes, we identified rs6811964 near PDGFC, platelet derived growth factor-C. It has been shown that PDGFC highly expressed in vascular smooth muscle cells, renal mesangial cells and platelets, and was likely involved in platelet biology [34]. This SNP was found associated with Epi-induced platelet aggregation (P = 10-5, Table 3), with ADP-induced platelet aggregation at nominal significance (P = 0.02), and with collagen-induced platelet aggregation at borderline nominal significance (P = 0.08). Other associations were found with SNPs in genes not clearly related to the phenotypes, or with SNPs that are not in known genes. These associations, together with other findings from this GWAS, must be viewed as hypotheses that warrant further testing in other cohorts.

Although we only summarized results for multivariable adjusted phenotype, we have also conducted linkage and association analyses for age-sex adjusted phenotypes. It is possible that the effects of some loci may be mediated through the covariates included in multivariable adjustment, and thus only associated with age and sex adjusted phenotypes. Among the 52 SNPs that were associated with age and sex adjusted hemostatic factors or hematological phenotypes with a GEE p-value equal or less than 10-5, 28 SNPs had a GEE p-value greater than 10-5 with multivariable adjusted phenotypes. However, no age and sex adjusted GEE p-value for the 28 SNPs reached genome-wide significance (p-value < 5 × 10-8), and no new highly plausible candidate genes resided within 60 Kb of these SNPs. The full disclosure results of all analyses, including the age-sex adjusted analyses, can be viewed at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007.

There are some limitations to this study. The participants are Caucasian and thus the results may not be generalizable to other racial groups. The study sample size was relatively small, and as such, we may have insufficient power to detect small effects. To avoid worsening the multiple testing problem, we performed only sex-pooled and not sex-specific analyses. There may be some SNPs that are associated with some phenotypes only in female or male undetected in the current study. The advantages of this study are that we had family data, which enabled us to also apply family-based association tests that are robust to population admixture, and linkage analyses that can detect loci not in LD but in linkage with any 100K SNP. The study subjects were recruited without regarding to their phenotypic values, which makes the analyses of multiple phenotypes possible without the need to correct ascertainment bias.

Finally, compared with studies focused only on SNPs within candidate genes, GWAS approaches are unbiased and as such they have the advantage of detecting novel genes or confirming genes that are not well-known to have an influence on a phenotype. However, since the current GWAS uses only a subset of all the SNPs in HapMap [35], it may miss some genes due to lack of coverage. For the same reason, GWAS data usually are not enough to study a candidate gene comprehensively. To understand the roles played by each SNP in a candidate gene, additional genotyping, and single-SNP and haplotype analyses are needed. A large GWAS involving more than 550,000 SNPs in more than 9000 participants of FHS will be available for analysis later in 2007, providing increased power for detection of smaller effects for the hemostatic and hematological phenotypes.

Conclusion

In summary, we have tested for association and linkage using the Affymetrix 100K SNPs and a set of hemostatic factor and hematological phenotypes. We have confirmed a previously reported association, providing proof of principle (a "positive control") for the GWAS approach. Our results provide a set of hypotheses that warrant testing in additional studies.

Abbreviations

ADP: 

adenosine 5'-diphosphate

bp: 

base pair(s)

CHD: 

coronary heart disease

CVD: 

cardiovascular disease

CHR: 

chromosome

EPB41L2: 

erythrocyte membrane protein band 4.1-like 2

EPO: 

erythropoietin

EPOR: 

erythropoietin receptor

FBAT: 

family-based association test

FGB: 

fibrinogen-β

FGA: 

fibrinogen-α

FGG: 

fibrinogen-γ

FHS: 

Framingham Heart Study

FVII: 

factor VII

GAW: 

Genetic Analysis Workshop

GEE: 

generalized estimating equations

GWAS: 

genome-wide association study

HBA1: 

hemoglobin-α 1

HBA2: 

hemoglobin-α 2

HBB: 

hemoglobin-β chain complex

HBD: 

hemoglobin-δ

HBE1: 

hemoglobin-ε 1

HBG1: 

hemoglobin-γ A

HBG2: 

hemoglobin-γ G

HBM: 

hemoglobin-μ

HCT: 

hematocrit

HEBP2: 

heme binding protein 2

Hgb: 

hemoglobin

ITGB3: 

integrin beta 3 (platelet glycoprotein IIIa, antigen CD61)

kb: 

kilo base pairs (=1000 bp)

KLF1: 

Kruppel-like factor 1

LD: 

linkage disequilibrium

MAF: 

minor allele frequency

MCV: 

mean corpuscular volume

MCH: 

mean corpuscular hemoglobin

Mb: 

mega base pairs (=1000,000 bp)

OR5AP2: 

olfactory receptor family 5, subfamily AP, member 2

OR5AR1: 

olfactory receptor family 5, subfamily AR, member 1

OR9G1: 

olfactory receptor family 9, subfamily G, member 1

OR9G4: 

olfactory receptor family 9, subfamily G, member 4

PAI-1: 

plasminogen activator inhibitor

PDGFC: 

platelet derived growth factor-C

RBCC: 

red blood cell count

SERPINE1: 

serpin peptidase inhibitor clade E, member 1

SNP: 

single nucleotide polymorphism

tPA: 

tissue plasminogen activator

vWF: 

von Willebrand factor

WBC: 

white blood cell.

Declarations

Acknowledgements

This work is supported by National Institute of Health/National Heart, Lung & Blood Institute (NHLBI) Contract N01-HC-25195. A portion of the research was conducted using the BU Linux Cluster for Genetic Analysis (LinGA) funded by the NIH NCRR (National Center for Research Resources) Shared Instrumentation grant (1S10RR163736-01A1). We express out gratitude to the Framinghan Heart Study participants, and helpful input from the collaborators: Emelia Benjamin and Martin G. Larson.

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)
Department of Biostatistics, Boston University School of Public Health
(3)
Broad Institute of Harvard University and Massachusetts Institute of Technology
(4)
Office of Biostatistics Research, NHLBI, National Institute of Health
(5)
Royal North Shore Hospital Sydney
(6)
Cardiology Division, Massachusetts General Hospital, Harvard Medical School

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