Volume 8 Supplement 1

The Framingham Heart Study 100,000 single nucleotide polymorphisms resource

Open Access

Genome-wide association to body mass index and waist circumference: the Framingham Heart Study 100K project

  • Caroline S Fox1Email author,
  • Nancy Heard-Costa2,
  • L Adrienne Cupples2,
  • Josée Dupuis2,
  • Ramachandran S Vasan2 and
  • Larry D Atwood2
BMC Medical Genetics20078(Suppl 1):S18

DOI: 10.1186/1471-2350-8-S1-S18

Published: 19 September 2007

Abstract

Background

Obesity is related to multiple cardiovascular disease (CVD) risk factors as well as CVD and has a strong familial component. We tested for association between SNPs on the Affymetrix 100K SNP GeneChip and measures of adiposity in the Framingham Heart Study.

Methods

A total of 1341 Framingham Heart Study participants in 310 families genotyped with the Affymetrix 100K SNP GeneChip had adiposity traits measured over 30 years of follow up. Body mass index (BMI), waist circumference (WC), weight change, height, and radiographic measures of adiposity (subcutaneous adipose tissue, visceral adipose tissue, waist circumference, sagittal height) were measured at multiple examination cycles. Multivariable-adjusted residuals, adjusting for age, age-squared, sex, smoking, and menopausal status, were evaluated in association with the genotype data using additive Generalized Estimating Equations (GEE) and Family Based Association Test (FBAT) models. We prioritized mean BMI over offspring examinations (1–7) and cohort examinations (10, 16, 18, 20, 22, 24, 26) and mean WC over offspring examinations (4–7) for presentation. We evaluated associations with 70,987 SNPs on autosomes with minor allele frequencies of at least 0.10, Hardy-Weinberg equilibrium p ≥ 0.001, and call rates of at least 80%.

Results

The top SNPs to be associated with mean BMI and mean WC by GEE were rs110683 (p-value 1.22*10-7) and rs4471028 (p-values 1.96*10-7). Please see http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007 for the complete set of results. We were able to validate SNPs in known genes that have been related to BMI or other adiposity traits, including the ESR1 Xba1 SNP, PPARG, and ADIPOQ.

Conclusion

Adiposity traits are associated with SNPs on the Affymetrix 100K SNP GeneChip. Replication of these initial findings is necessary. These data will serve as a resource for replication as more genes become identified with BMI and WC.

Introduction

Cardiovascular disease (CVD) is the leading cause of morbidity and mortality in the United States, affecting roughly twelve million people and accounting for nearly one million deaths per year [1]. Although improvements in cardiovascular risk factor profiles have contributed to reductions in CVD mortality, an increasing prevalence of obesity may have slowed this rate of decline [2]. Obesity increases the risk of all-cause mortality [3], vascular disease [4], and non-vascular causes of death including certain cancers [5]. Genetic and environmental factors have been linked to obesity [6]. We have previously reported linkage to body mass index (BMI) on chromosomes 6q23 and 11q24 [7, 8], waist circumference (WC) on chromosome 6q23 [9], and weight change on chromosome 20q13 [10] in the Framingham Heart Study. Additionally, multiple quantitative trait loci and candidate genes have been mapped to adiposity-related traits, as recently reviewed [11].

As part of the Framingham Heart Study 100K Project, we sought to test the relation of multiple adiposity-related traits with the Affymetrix one hundred thousand single nucleotide polymorphisms (SNP) chip. A broad range of phenotypes were studied and include BMI, WC, height, and radiographic quantification of subcutaneous (SAT) and visceral (VAT) fat. In this manuscript we focus on mean BMI and mean WC. We tested the relation of these traits to 70,987 SNPs.

Methods

Participants from the Framingham Heart Study Original Cohort and Offspring Cohort underwent genotyping with the Affymetrix 100K GeneChip; details about the selection process and genotyping are provided in the Overview [12]. Participants (n = 1345) were genotyped for the Affymetrix GeneChip Human Mapping 100K SNP set. For the current analysis, phenotype data were available in 1341 participants for mean BMI and 1079 participants for mean WC. For this manuscript, we focused on mean BMI over offspring examinations (1–7) and cohort examinations (10, 16, 18, 20, 22, 24, 26) and mean WC over offspring examinations (4–7). We evaluated associations with 70,987 SNPs on autosomes with minor allele frequencies ≥ 0.10, Hardy-Weinberg equilibrium (HWE) p-value ≥ 0.001, and call rates ≥80%.

Phenotype assessment

Body weight and height were measured at all 7 Offspring examination cycles, from 1971 to 2001 and chronologically corresponding to 7 Original cohort examinations (10, 16, 18, 20, 22, 24, 26); WC was measured at the level of the umbilicus at 4 Offspring examinations (4, 5, 6, and 7). BMI was calculated by taking the weight (in kilograms) over the height (in meters-squared). Mean BMI across 7 offspring examinations (1–7) and 7 cohort examinations (10, 16, 18, 20, 22, 24, 26) was obtained by taking the average of all available measurements; mean WC across 4 examinations was obtained by taking the average of all available offspring measurements. Covariates were also averaged over the exams at which the adiposity measures were available.

Subcutaneous and visceral fat volumes (SAT and VAT, respectively) were measured on a subset of individuals who took part in the Framingham Offspring Multi-Detector Computed Tomography Study between 2002 and 2005. Briefly, subjects underwent eight-slice multi-detector computed tomography imaging of the chest and abdomen in a supine position as previously described (LightSpeed Ultra, General Electric, Milwaukee, WI) [13]. SAT and VAT volumes were assessed (Aquarius 3D Workstation, TeraRecon Inc., San Mateo, CA) via manual tracing of the abdominal muscular wall that separates the visceral from the subcutaneous compartment, with excellent inter-reader variability of 0.99 for VAT and SAT, as previously reported [13].

Genotyping

Genotyping was performed using the 100K Affymetrix GeneChip. Please see the Overview [12] for details.

Statistical methods

In total, a maximum of 1341 genotyped participants with phenotype information were available for analysis. Residuals were created from multiple linear regression models to adjust traits for covariates; these residuals were created separately in the Original Cohort and Offspring, and in women and men separately. The standardized residuals from these regression models were used to create ranked normalized deviates, which were in turn used for genetic analyses. Adiposity traits were age-adjusted (age and age-squared) and then multivariable adjusted; details of multivariable adjustment for each trait are presented in Table 1. Only multivariable-adjusted results are presented in this manuscript. All association analyses were performed using generalized estimating equations (GEE) and family-based association testing (FBAT); variance component methods were used for linkage; details are provided in the Overview [12]. To consider concordance of results among correlated adiposity traits (see the third table in this article), we selected SNPs with significant association (p < 0.01 in GEE or FBAT analyses) for at least 6 out of 8 following weight-related traits: BMI at Offspring exams 1–7 and chronologically corresponding Cohort exams 10, 16, 18, 20, 22, 24, 26 and mean BMI from these exams, and computed a geometric mean GEE p-values across all 8 traits for FBAT and GEE separately. We evaluated associations with 70,987 SNPs on autosomes with minor allele frequencies of at least 0.10, HWE p ≥ 0.001, and call rates of at least 80%. Linkage analysis was performed using variance components methods on a subset of 100K markers in linkage equilibrium and Marshfield short tandem repeats; please see the Overview [12] for more details, including power calculations.
Table 1

Phenotype master trait table: exam cycle, and numbers of participants in family plates with phenotype

   

Exam cycle/s

 

Phenotype

Number of traits§

Sample Size

Offspring

Cohort

Adjustment

Body Mass Index; men and women combined and separate

46

529–1341

1–7; mean 1–7; change from 1–7

10, 16, 18, 20, 22, 24, 26; mean 10, 16, 18, 20, 22, 24, 26

*

Weight change

11

468–1115

Change from 1–7

 

*

Weight; men and women combined and separate

43

498–1342

1–7

10, 16, 18, 20, 22, 24, 26

*

Height; men and women combined and separate

25

529–1341

1–7

10, 16, 18, 20, 22, 24, 26

*

Waist circumference; men and women combined and separate

24

479–1252

4–7; mean 4–7; change from 4–7

20, 22, 23; change from 20–23;

**

Subcutaneous fat by computed tomography

2

654

7

-

*

Visceral fat by computed tomography

2

653

7

-

*

Waist circumference by computed tomography

2

664

7

-

*

Sagittal diameter by computed tomography

2

665

7

-

*

§Refers to number of traits within each group actually analyzed

*All models included age, age-squared, sex, smoking, menopause

**Models additionally adjusted for body mass index

Results

All traits (n = 157), including relevant examination cycles and multivariable-adjustments, are presented in Table 1. Table 2a presents the top 25 p-values obtained via GEE for mean BMI and mean WC. The top SNPs to be associated with mean BMI and mean WC by GEE were rs110683 (p-value 1.22*10-7) and rs4471028 (p-values 1.9*10-7); Table 2b presents the top SNPs for the FBAT procedure. Additional results can be found on the following website: http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007. Table 2c presents all LOD scores of at least 2.0. For mean BMI, we observed a peak LOD score of 2.3 on chromosome 2p16, whereas for mean WC, we observed a peak LOD score of 2.3 on chromosome 2q14.
Table 2

(a) Top association results for mean BMI and mean WC based on GEE p-value; (b) Top 25 association results for mean BMI and mean WC based on FBAT p-value; (c) LOD scores of at least 2.0 with accompanying LOD score 1.5 support interval for mean BMI and mean WC

Trait

SNP

Chromosome

Physical Position (Mb)

GEE p-value

FBAT p-value

Gene

2a. Top association results for mean BMI and mean WC based on GEE p-value

Mean BMI

rs1106683

7

130910780

1.2*10-07

3.2*10-04

 

Mean WC

rs4471028

8

75457530

2.0*10-07

3.2*10-04

GDAP1

Mean WC

rs4469448

8

75457665

2.6*10-07

0.003

GDAP1

Mean WC

rs6996971

8

75455047

4.9*10-07

0.002

GDAP1

Mean WC

rs10504576

8

75429234

7.1*10-07

0.005

GDAP1

Mean WC

rs1875517

3

118790257

1.5*10-06

0.002

 

Mean BMI

rs1106684

7

130910920

1.6*10-06

0.002

 

Mean BMI

rs1333026

13

65018785

8.1*10-06

0.209

 

Mean BMI

rs2296465

10

3299647

1.5*10-05

0.262

 

Mean BMI

rs1374489

5

19658900

1.6*10-05

0.348

CDH18

Mean WC

rs1466113

17

68676913

2.7*10-05

0.004

SSTR2

Mean BMI

rs10486301

7

18183021

2.7*10-05

0.016

 

Mean BMI

rs2221880

5

19420500

3.0*10-05

0.072

 

Mean WC

rs1456873

4

62130929

3.1*10-05

0.005

 

Mean BMI

rs10513097

5

11406101

4.4*10-05

0.022

CTNND2

Mean BMI

rs2361128

19

62431059

4.4*10-05

0.004

ZNF264

Mean BMI

rs2942329

5

19429660

4.5*10-05

0.089

 

Mean WC

rs4129319

4

88752564

4.7*10-05

0.003

SPARCL1

Mean BMI

rs10509361

10

77223192

5.2*10-05

0.044

C10orf11

Mean BMI

rs2967001

5

19422000

6.0*10-05

0.074

 

Mean BMI

rs464766

3

162570294

6.1*10-05

0.072

ADMP

Mean BMI

rs10487263

7

123603987

7.0*10-05

0.036

 

Mean BMI

rs4922571

11

31643025

7.0*10-05

0.062

ELP4

Mean BMI

rs7013836

8

5666540

8.2*10-05

0.103

 

Mean BMI

rs7202384

16

13658225

8.2*10-05

0.002

 

2b. Top 25 association results for mean BMI and mean WC based on FBAT p-value

Trait

SNP

Chromosome

Physical Location (Mb)

GEE p-value

FBAT p-value

Gene

Mean WC

rs10488165

7

132594899

0.011

2.6*10-06

SEC8L1

Mean WC

rs2206682

6

56001938

0.011

4.2*10-06

COL21A1

Mean WC

rs2223662

6

56001756

0.013

5.1*10-06

COL21A1

Mean WC

rs953536

9

111569442

0.007

8.2*10-06

C9orf84

Mean WC

rs10517461

4

37789743

2.3*10-04

2.9*10-05

TBC1D1

Mean WC

rs7941883

11

123262095

0.084

3.0*10-05

OR8D4|OR4D5|OR6T1

Mean BMI

rs10503776

8

25765786

0.009

3.8*10-05

EBF2

Mean BMI

rs711702

3

22956280

0.143

4.0*10-05

 

Mean WC

rs4312989

6

55918441

0.075

4.2*10-05

 

Mean WC

rs10519381

5

113700141

0.01

4.4*10-05

KCNN2

Mean WC

rs10483872

14

75239061

0.018

4.5*10-05

KIAA0998

Mean WC

rs315711

9

111628006

0.008

5.4*10-05

C9orf84

Mean WC

rs4715571

6

55917006

0.03

5.9*10-05

 

Mean WC

rs667463

9

111647315

0.004

7.0*10-05

C9orf84

Mean BMI

rs7320523

13

67552774

0.193

7.4*10-05

 

Mean WC

rs3752591

22

40664016

0.001

8.5*10-05

C22orf18

Mean WC

rs1496389

5

113753570

0.018

9.8*10-05

KCNN2

Mean WC

rs1619682

7

133453958

0.14

1.0*10-04

SLC35B4

Mean BMI

rs10492197

12

66871874

0.038

1.0*10-04

IFNG|IL26|IL22

Mean WC

rs10501467

11

79913437

0.037

1.1*10-04

 

Mean WC

SNP_A-1731932

1

24035982

0.152

1.1*10-04

 

Mean BMI

rs10512326

9

103934100

0.063

1.2*10-04

SMC2L1

Mean BMI

rs7533902

1

97791249

0.029

1.2*10-04

DPYD

Mean BMI

rs2870950

12

66870973

0.034

1.2*10-04

IFNG|IL26|IL22

Mean WC

rs2226351

21

25259810

1.8*10-04

1.3*10-04

 

2c. LOD scores of at least 2.0 with accompanying LOD score 1.5 support interval for mean BMI and mean WC

Trait

SNP

Chromosome

Physical Position (bp)

LOD

LOD1.5 Lower Bound (bp)

LOD1.5 Upper Bound (bp)

Mean BMI

rs9309153

2

48856798

2.3125

44048379

64579948

Mean WC

rs1992901

2

121386899

2.2721

116579748

132195205

Mean BMI

rs10518418

1

89149134

2.0053

51727132

99668198

Table 3 presents the top 25 SNPs for our multiple traits analysis, summarizing concordance of results in related BMI traits. The SNP with the lowest p-value was rs1106683 (p-value 3.8*10-6). We also evaluated 4 well-replicated genes in the obesity field (ADIPOQ [14], ESR1 [15], LEP [16], and PPARG [17]), as well as the recently identified INSIG2 gene [18]; Table 4a displays the associated validated SNPs from the literature that are either present in the Affymetrix 100K or that are in linkage disequilibrium (LD) with these SNPs. We found significant results for a SNP in LD with the ESR1 Xba1 SNP (rs3853250; FBAT p-value for mean BMI = 0.047). We also confirmed the association between a SNP in the INSIG2 gene (rs7566605; GEE p-value 0.001 for mean BMI) previously identified in this sample using a different analytic method [18]. We further explored associations with all SNPs in the Affymetrix 100K either within these genes or within 200 kb of these genes (Table 4b); only associations with p < 0.05 are presented. We identified 3 additional associated SNPs in the INSIG2 gene, 5 SNPs in the PPARG gene, 1 SNP in the ADIPOQ gene, and 5 SNPs in the ESR1 gene. Of the 4 SNPs present in the LEP gene, there were no associations with a p-value < 0.05.
Table 3

Results informed by combination of GEE and FBAT based on p-value of ≤0.01 for GEE or FBAT for 6 out of 8 BMI traits

SNP

Chromosome

Physical Position (bp)

Gene name

Mean GEE geometric p-value

rs1106683

7

130910780

 

3.8*10-6

rs2296465

10

3299647

 

5.9*10-5

rs10513097

5

11406101

CTNND2

6.8*10-5

rs2361128

19

62431059

ZNF264|AURKC

7.9*10-5

rs1374489

5

19658900

CDH18

1.1*10-4

rs10486301

7

18183021

 

1.3*10-4

rs1333026

13

65018785

 

1.3*10-4

rs10509361

10

77223192

C10orf11

1.7*10-4

rs10504368

8

64947097

 

2.7*10-4

rs947599

10

95256673

C10orf3

3.6*10-4

rs2012187

5

11375037

CTNND2

3.6*10-4

rs6480902

10

80157318

 

3.9*10-4

rs336583

3

162564683

ADMP

3.9*10-4

rs9290065

3

162259666

PPMIL

4.1*10-4

rs10494810

1

196868239

NR5A2

4.3*10-4

rs2012064

7

18220564

 

4.5*10-4

rs1869731

8

63972241

FLJ39630

4.7*10-4

rs775748

3

77679150

ROBO2

4.8*10-4

rs10499068

6

113189197

 

4.9*10-4

rs10236525

7

18184912

 

5.5*10-4

rs9309770

3

77647000

ROBO2

5.5*10-4

rs1504294

3

68831828

FAM19A4

5.5*10-4

rs7142517

14

54376554

SAMD4|GCH1

5.5*10-4

rs2051545

16

13680100

 

5.6*10-4

rs910623

1

115336446

TSPAN2

5.8*10-4

Table 4

(a) Comparison of mean BMI and mean WC Results with prior literature for SNPs that are either present in the 100K or in LD with a SNP in the 100K; (b) Associations of mean BMI and mean WC with all SNPs in or near genes (up to 200 kb away) for 5 well-replicated genes in the published literature (INSIG, PPARG, ADIPOQ, ESR1, LEP)* with a p-value < 0.05 in either FBAT or GEE**

4a. Comparison of mean BMI and mean WC Results with prior literature for SNPs that are either present in the 100K or in LD with a SNP in the 100K

       

Mean BMI p-value

Mean WC p-value

Gene

Candidate SNP

100K SNP

Location Candidate SNP (bp)

Location 100K SNP (bp)

D. prime

r2

FBAT

GEE

FBAT

GEE

INSIG2

rs7566605

Rs7566605

118552255

118552255

1

1

0.449

0.001

0.975

0.480

ESR1-Xba1

rs9340799

rs3853250

152255495

152252014

1

0.62

0.047

0.350

0.980

0.105

 

rs9340799

rs3853251

152255495

152252870

1

0.96

0.309

0.963

0.333

0.336

LEP

rs1349419

rs10487506

127471164

127472106

1

0.69

0.422

0.583

0.788

0.848

 

rs12535747

rs10487505

127472286

127454114

0.83

0.34

0.188

0.286

0.420

0.975

 

rs12535747

rs10487506

127472286

127472106

1

0.48

0.422

0.583

0.788

0.848

PPARG

rs1801282

rs1801282

12368125

12368125

1

1

0.556

0.178

0.290

0.406

4b. Associations of mean BMI and mean WC with all SNPs in or near genes (up to 200 kb away) for 5 well-replicated genes in the published literature (INSIG, PPARG, ADIPOQ, ESR1, LEP)* with a p-value < 0.05 in either FBAT or GEE**

   

Mean BMI p-value

Mean WC p-value

    

Gene

SNP

Physical Position (bp)

FBAT

GEE

FBAT

GEE

    

INSIG

rs9284719

118395025

0.148

0.035

0.510

0.925

    
 

rs3771942

118425080

0.766

0.005

0.812

0.984

    
 

rs10490628

118446520

0.464

0.021

0.765

0.238

    
 

rs7566605

118552255

0.449

0.001

0.975

0.480

    

PPARG

rs2938392

12409608

0.158

0.003

0.644

0.244

    
 

rs709157

12437024

0.602

0.106

0.091

0.023

    
 

rs10510422

12505413

0.806

0.546

0.044

0.720

    
 

rs10510423

12526881

0.986

0.753

0.038

0.787

    
 

rs2454431

12558068

0.806

0.034

0.268

0.882

    
 

rs963163

12632067

0.997

0.047

0.749

0.036

    

ADIPOQ

rs1042464

187878274

0.962

0.231

0.024

0.722

    

ESR1

rs851982

152117099

0.880

0.538

0.119

0.043

    
 

rs10484922

152224431

0.318

0.012

0.067

0.528

    
 

rs3853250

152252014

0.047

0.350

0.980

0.105

    
 

rs3778099

152510689

0.033

0.367

0.513

0.689

    
 

rs9322361

152551257

0.020

0.096

0.122

0.522

    

*No SNPs in the LEP gene had a p-value < 0.05

**The following number of SNPs were evaluated in the INSIG, PPARG, ADIPOQ, ESR1, and LEP genes: 19, 28, 16, 37, 4

Additional Findings

We also identified several additional SNPs in genes in relation to mean BMI or mean WC among our list of the top 500 SNPs http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007. The LRP1B gene (SNP rs3923350, GEE p-value 0.0005) was associated with both mean BMI and mean WC. We also found association with the VIP gene (SNP rs620598, GEE p = 0.001), the LEPR gene (SNP rs2025804, GEE p-value = 0.003), the ADRB1 gene (SNP rs6585258, FBAT p-value 0.004), the NPY2R gene (SNP rs2880411, p-value = 0.006), the HSD3B1 gene (rs 4659200, FBAT p-value 0.0007), the ADRA1B gene (SNP rs952037, GEE p-value = 0.002), IL6R (SNP rs4129267, FBAT p-value = 0.003), AGTR1 (SNP rs275678, FBAT p-value = 0.006), and FSHR (SNP rs1504155; GEE p-value = 0.0004).

Discussion

In our analysis of adiposity-related traits, we found strong and significant results to SNPs on the Affymetrix 100K GeneChip. Further, we have confirmed or replicated several well-validated genes that have been reported to be related to adiposity.

One of the top SNPs that we identified via the GEE method is located in the SSTR2 gene, the somatostatin receptor 2 gene, which has been reported to suppress growth hormone secretion. We also identified several additional SNPs in genes in relation to mean BMI or mean WC among our list of the top 500 SNPs. The LRP1B gene is a member of the LDL receptor gene family, and represents a potentially attractive candidate gene. The VIP gene (SNP rs620598, GEE p = 0.001) is a member of the glucagon family that plays a role in multiple physiologic and metabolic pathways, including myocardial contractility, smooth muscle relaxation, blood pressure lowering and vasodilation, and glycogenolysis. We also found significant associations with multiple genes that have been previously associated with adiposity-related traits [11].

Using our clustered traits analysis, we identified the CTNND2 gene, a gene that is part of the catenin family that may be involved in nutrient absorption in the intestine and signaling with nuclear receptors including PPAR [19]. We also identified the NR5A2 gene, a gene that is part of the nuclear receptor subfamily, a family of orphan receptors. NR5A2 is a key regulator of CYP7A expression in the liver, and PPM1L (protein phosphatase 1), a gene that is a suppressor of the SAPK pathway and may be involved in oxidative stress and apotosis.

Well-replicated candidate genes

We were able to confirm association (i.e. validate) with the INSIG2 gene (SNP rs7566605, GEE p-value = 0.001). This same SNP was previously identified in association with BMI in this same sample using a different analytic method [18]. We also had nominal significance with a SNP in LD with the ESR1 Xba1 SNP, and multiple other SNPs in well-replicated obesity genes, suggesting that the Affymetrix 100K GeneChip provides a valid tool for uncovering candidate gene associations with adiposity-related traits. Of note, some of our SNPs did overlap with results reported for BMI using different analytic methods (Herbert et al, http://gmed.bu.edu/about/index.html[20]).

Comparison with prior linkage results

We have previously identified a locus for BMI on chromosome 1 (D1S1665, LOD score 1.85) [7]. This peak falls within the 1.5 LOD score interval for our current finding on chromosome 1. We also have previously identified a LOD score of 2.0 for waist circumference on chromosome 2q14 [9], nearby to our current LOD score of 2.27 for mean WC. Differences with previously reported results may stem from our use of different phenotypes.

Strengths and limitations

Strengths of our study lie in our assessment of multiple measures of BMI and WC in a sample unselected for these traits, thus improving precision. We also have excellent assessment of potential confounders that we are able to adjust for in our residual creation. Because the Framingham Heart Study has measured multiple traits, we are able to examine trait clustering, which may be more likely to identify SNPs in coding regions. Limitations exist as well. Our sample is neither ethnically diverse nor nationally representative, and it is uncertain how our results would apply to other ethnic groups. However, in genetics studies, sample homogeneity is beneficial in order to reduce population stratification. Further, none of these results reached genome-wide significance; please see the Overview [12] for details regarding this threshold. These results should be considered preliminary, and are likely to contain false negatives and false positives. Therefore, replication in independent samples is critical. For limitations pertaining to our genotyping or statistical methods, including multiple testing, please see the Overview [12].

Conclusion

Adiposity-related traits are associated with SNPs on the Affymetrix 100K SNP GeneChip. Further work to replicate some of these SNPs in other samples is necessary. These data will serve as a resource for replication as more genes become identified with BMI and WC.

Abbreviations

BMI: 

body mass index

CVD: 

cardiovascular disease

FBAT: 

Family Based Association Test

GEE: 

Generalized Estimating Equations

HWE: 

Hardy-Weinberg equilibrium

LD: 

linkage disequilibrium

SAT: 

subcutaneous fat

SNP: 

single nucleotide polymorphisms

VAT: 

visceral fat

WC: 

waist circumference.

Declarations

Acknowledgements

We gratefully acknowledge the continued commitment and dedication of the Framingham Study participants. This work was supported by the National Heart, Lung and Blood Institute's Framingham Heart Study (Contract No. N01-HC-25195) and by Atwood R01 DK066241. 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).

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)
Boston University Schools of Medicine and Public Health

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© Fox et al; licensee BioMed Central Ltd. 2007

This article is published under license to 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.

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