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ABSTRACT: BACKGROUND: Prior studies reported conflicting findings on the association between metabolic syndrome and inflammatory biomarkers. We tested the cross-sectional association between metabolic syndrome, its components, and 9 inflammatory markers. METHODS: We measured C-reactive protein, CD40 ligand, interleukin-6, intercellular adhesion molecule-1, monocyte chemoattractant protein-1, osteoprotegerin, P-selectin, tumor necrosis factor-alpha, and tumor necrosis factor receptor-2 in 2570 Framingham Offspring Study participants free of diabetes and cardiovascular disease at exam 7. Metabolic syndrome was defined by criteria of the National Cholesterol Education Program. We performed multivariable linear regressions for each biomarker with metabolic syndrome as the exposure adjusting for age, sex, smoking, aspirin use, and hormone replacement. We subsequently added each component of the metabolic syndrome as a continuous trait to the models, adjusting for age, sex, smoking, aspirin use, hormone replacement, lipid lowering treatment and hypertension therapy. We considered P < 0.05 as statistically significant. RESULTS: Metabolic syndrome was present in 984 participants, and statistically significantly associated with each biomarker (all P<0.0001) except osteoprotegerin. After adjusting for its components, the metabolic syndrome was only associated with P-selectin (beta=0.16, 95% CI (0.05, 0.27)). CONCLUSIONS: Metabolic syndrome was associated with multiple inflammatory biomarkers. However, adjusting for each of its components eliminated the association with most inflammatory markers, except P-selectin. Our results support the hypothesis that the relation between metabolic syndrome and inflammation is largely accounted for by its components.
Diabetology and Metabolic Syndrome 06/2012; 4(1):28. · 1.53 Impact Factor
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Amidou N'diaye,
Gary K Chen,
Cameron D Palmer,
Bing Ge,
Bamidele Tayo,
Rasika A Mathias,
Jingzhong Ding,
Michael A Nalls,
Adebowale Adeyemo,
Véronique Adoue, [......],
Alan B Zonderman,
Michele K Evans,
Yongmei Liu,
Diane M Becker,
Richard S Cooper,
Tomi Pastinen,
Brian E Henderson,
Joel N Hirschhorn,
Guillaume Lettre,
Christopher A Haiman
PLoS Genetics 11/2011; 7(11). · 8.69 Impact Factor
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Amidou N'Diaye,
Gary K Chen,
Cameron D Palmer,
Bing Ge,
Bamidele Tayo,
Rasika A Mathias,
Jingzhong Ding,
Michael A Nalls,
Adebowale Adeyemo,
Véronique Adoue, [......],
Alan B Zonderman,
Michele K Evans,
Yongmei Liu,
Diane M Becker,
Richard S Cooper,
Tomi Pastinen,
Brian E Henderson,
Joel N Hirschhorn,
Guillaume Lettre,
Christopher A Haiman
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ABSTRACT: Adult height is a classic polygenic trait of high heritability (h(2) approximately 0.8). More than 180 single nucleotide polymorphisms (SNPs), identified mostly in populations of European descent, are associated with height. These variants convey modest effects and explain approximately10% of the variance in height. Discovery efforts in other populations, while limited, have revealed loci for height not previously implicated in individuals of European ancestry. Here, we performed a meta-analysis of genome-wide association (GWA) results for adult height in 20,427 individuals of African ancestry with replication in up to 16,436 African Americans. We found two novel height loci (Xp22-rs12393627, P = 3.4×10(-12) and 2p14-rs4315565, P = 1.2×10(-8)). As a group, height associations discovered in European-ancestry samples replicate in individuals of African ancestry (P = 1.7×10(-4) for overall replication). Fine-mapping of the European height loci in African-ancestry individuals showed an enrichment of SNPs that are associated with expression of nearby genes when compared to the index European height SNPs (P<0.01). Our results highlight the utility of genetic studies in non-European populations to understand the etiology of complex human diseases and traits.
PLoS Genetics 10/2011; 7(10):e1002298. · 8.69 Impact Factor
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ABSTRACT: Abstract
Background
Genome-wide association (GWA) studies that use population-based association approaches may identify spurious associations in the presence of population admixture. In this paper, we propose a novel three-stage approach that is computationally efficient and robust to population admixture and more powerful than the family-based association test (FBAT) for GWA studies with family data.
We propose a three-stage approach for GWA studies with family data. The first stage is to perform linear regression ignoring phenotypic correlations among family members. SNPs with a first stage p-value below a liberal cut-off (e.g. 0.1) are then analyzed in the second stage that employs a linear mixed effects (LME) model that accounts for within family correlations. Next, SNPs that reach genome-wide significance (e.g. 10<sup>-6 </sup>for 34,625 genotyped SNPs in this paper) are analyzed in the third stage using FBAT, with correction of multiple testing only for SNPs that enter the third stage. Simulations are performed to evaluate type I error and power of the proposed method compared to LME adjusting for 10 principal components (PC) of the genotype data. We also apply the three-stage approach to the GWA analyses of uric acid in Framingham Heart Study's SNP Health Association Resource (SHARe) project.
Results
Our simulations show that whether or not population admixture is present, the three-stage approach has no inflated type I error. In terms of power, using LME adjusting PC is only slightly more powerful than the three-stage approach. When applied to the GWA analyses of uric acid in the SHARe project of FHS, the three-stage approach successfully identified and confirmed three SNPs previously reported as genome-wide significant signals.
Conclusions
For GWA analyses of quantitative traits with family data, our three-stage approach provides another appealing solution to population admixture, in addition to LME adjusting for genetic PC.
BMC Genetics. 01/2010;
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ABSTRACT: The burden of cardiovascular risk associated with obesity disproportionately affects African Americans and little is known about ethnic/racial differences in the relationship of obesity to cardiometabolic risk. This report assesses whether obesity is similarly associated with cardiometabolic risk factors in African Americans and whites of European ancestry. Cross-sectional observational data from the Jackson Heart Study (JHS) and the Framingham Heart Study (FHS) were compared. This analysis uses participants aged 35-74 years with BMI >18.5 kg/m(2), and free of prevalent cardiovascular disease (CVD), from the initial JHS clinical examination (2000-2004) and the FHS Offspring (1998-2001) and Third Generation (2002-2005) cohorts. Participants were evaluated for the presence of lipid abnormalities, hypertension, and diabetes. Overall, 4,030 JHS (mean age 54 years, 64% women) and 5,245 FHS (mean age 51 years, 54% women) participants were available for analysis. The prevalence of all risk factors except high triglycerides and low high-density lipoprotein (HDL) was substantially higher in JHS (all P < 0.001) and BMI was associated with increasing prevalence of most CVD risk factors within each race. For diabetes mellitus, hypertension, and low HDL, steeper relationships to BMI were observed in FHS than in JHS (P values <0.001-0.016). There were larger proportional increases in risk factor prevalence with increasing BMI in whites than in African Americans. The higher prevalence rates of cardiometabolic risk factors at nearly all levels of BMI in African Americans, however, suggest that additional factors contribute to the burden of CVD risk in African Americans.
Obesity 11/2009; 18(8):1638-45. · 4.28 Impact Factor
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Anna Kottgen,
Wen Kao,
Shih-Jen Hwang,
Eric Boerwinkle,
Qiong Yang,
Daniel Levy,
Emelia Benjamin,
Martin Larson,
Brad Astor,
Josef Coresh, Caroline Fox
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ABSTRACT: Abstract
Background
The Framingham Heart Study (FHS) recently obtained initial results from the first genome-wide association scan for renal traits. The study of 70,987 single nucleotide polymorphisms (SNPs) in 1,010 FHS participants provides a list of SNPs showing the strongest associations with renal traits which need to be verified in independent study samples.
Methods
Sixteen SNPs were selected for replication based on the most promising associations with chronic kidney disease (CKD), estimated glomerular filtration rate (eGFR), and serum cystatin C in FHS. These SNPs were genotyped in 15,747 participants of the Atherosclerosis in Communities (ARIC) Study and evaluated for association using multivariable adjusted regression analyses. Primary outcomes in ARIC were CKD and eGFR. Secondary prospective analyses were conducted for association with kidney disease progression using multivariable adjusted Cox proportional hazards regression. The definition of the outcomes, all covariates, and the use of an additive genetic model was consistent with the original analyses in FHS.
Results
The intronic SNP rs6495446 in the gene MTHFS was significantly associated with CKD among white ARIC participants at visit 4: the odds ratio per each C allele was 1.24 (95% CI 1.09–1.41, p = 0.001). Borderline significant associations of rs6495446 were observed with CKD at study visit 1 (p = 0.024), eGFR at study visits 1 (p = 0.073) and 4 (lower mean eGFR per C allele by 0.6 ml/min/1.73 m<sup>2</sup>, p = 0.043) and kidney disease progression (hazard ratio 1.13 per each C allele, 95% CI 1.00–1.26, p = 0.041). Another SNP, rs3779748 in EYA1 , was significantly associated with CKD at ARIC visit 1 (odds ratio per each T allele 1.22, p = 0.01), but only with eGFR and cystatin C in FHS.
Conclusion
This genome-wide association study provides unbiased information implicating MTHFS as a candidate gene for kidney disease. Our findings highlight the importance of replication to identify common SNPs associated with renal traits.
BMC Medical Genetics. 01/2008;
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ABSTRACT: Red blood cell (RBC) count and size are major criteria for evaluating anemia and related hematology disease diagnoses. While environmental factors influence RBC count (RBCC) and size, mean corpuscular volume (MCV), and mean corpuscular hemoglobin (MCH), studies have indicated that each of these measures has a substantial genetic component. So far, no linkage analysis or genome scan has been reported. We carried out 10 cM genome-wide scans on RBCC, MCV, and MCH in a community-based Caucasian cohort, the Framingham Heart Study, using 325 pedigrees with 1,144 individuals genotyped and phenotyped. Using variance-component linkage methods, heritabilities were estimated as 56, 52, and 52% after covariate adjusted for RBCC, MCV, and MCH, respectively. For RBCC, we found a maximum LOD score of 3.2 on chromosome 19, 24 cM (7.0 Mbp). Near this region, there lie a few important candidate genes, including erythropoietin receptor and erythroid Krüppel-like factor. For linkage analyses for MCV and MCH, there were coinciding maximized LOD scores on chromosome 11, 9 cM (5.2 Mbp) with values of 3.8 and 3.6, respectively. Under the peak resides the hemoglobin beta cluster - several beta-like genes, which are important candidates for RBC size. In subsequent analyses, we excluded individuals with low MCV to assess the possible influence of beta-thalassemia carriers, and there continued to be evidence for linkage in the same region on chromosome 11p15 (LOD scores of 2.6 and 2.7 for MCV and MCH, respectively). For MCV, we also identified a new region on chromosome 6q24 with a LOD score of 2.9. These findings suggest that further studies are warranted to identify potential causal genetic variants for RBC size and count and related erythrocyte indices.
American Journal of Hematology 08/2007; 82(7):605-10. · 4.67 Impact Factor
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Cupples L Adrienne,
Heather Arruda,
Emelia Benjamin,
Ralph D'Agostino,
Serkalem Demissie,
Anita DeStefano,
Josée Dupuis,
Kathleen Falls, Caroline Fox,
Daniel Gottlieb, [......],
George O'Connor,
Christopher O'Donnell,
Mona Pandey,
Sudha Seshadri,
Ramachandran Vasan,
Zhen Wang,
Jemma Wilk,
Philip Wolf,
Qiong Yang,
Larry Atwood
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ABSTRACT: Abstract
Background
The Framingham Heart Study (FHS), founded in 1948 to examine the epidemiology of cardiovascular disease, is among the most comprehensively characterized multi-generational studies in the world. Many collected phenotypes have substantial genetic contributors; yet most genetic determinants remain to be identified. Using single nucleotide polymorphisms (SNPs) from a 100K genome-wide scan, we examine the associations of common polymorphisms with phenotypic variation in this community-based cohort and provide a full-disclosure, web-based resource of results for future replication studies.
Methods
Adult participants (n = 1345) of the largest 310 pedigrees in the FHS, many biologically related, were genotyped with the 100K Affymetrix GeneChip. These genotypes were used to assess their contribution to 987 phenotypes collected in FHS over 56 years of follow up, including: cardiovascular risk factors and biomarkers; subclinical and clinical cardiovascular disease; cancer and longevity traits; and traits in pulmonary, sleep, neurology, renal, and bone domains. We conducted genome-wide variance components linkage and population-based and family-based association tests.
Results
The participants were white of European descent and from the FHS Original and Offspring Cohorts (examination 1 Offspring mean age 32 ± 9 years, 54% women). This overview summarizes the methods, selected findings and limitations of the results presented in the accompanying series of 17 manuscripts. The presented association results are based on 70,897 autosomal SNPs meeting the following criteria: minor allele frequency ≥ 10%, genotype call rate ≥ 80%, Hardy-Weinberg equilibrium p-value ≥ 0.001, and satisfying Mendelian consistency. Linkage analyses are based on 11,200 SNPs and short-tandem repeats. Results of phenotype-genotype linkages and associations for all autosomal SNPs are posted on the NCBI dbGaP website at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007 .
Conclusion
We have created a full-disclosure resource of results, posted on the dbGaP website, from a genome-wide association study in the FHS. Because we used three analytical approaches to examine the association and linkage of 987 phenotypes with thousands of SNPs, our results must be considered hypothesis-generating and need to be replicated. Results from the FHS 100K project with NCBI web posting provides a resource for investigators to identify high priority findings for replication.
BMC Medical Genetics. 01/2007;
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ABSTRACT: Abstract
Background
Glomerular filtration rate (GFR) and urinary albumin excretion (UAE) are markers of kidney function that are known to be heritable. Many endocrine conditions have strong familial components. We tested for association between the Affymetrix GeneChip Human Mapping 100K single nucleotide polymorphism (SNP) set and measures of kidney function and endocrine traits.
Methods
Genotype information on the Affymetrix GeneChip Human Mapping 100K SNP set was available on 1345 participants. Serum creatinine and cystatin-C (cysC; n = 981) were measured at the seventh examination cycle (1998–2001); GFR (n = 1010) was estimated via the Modification of Diet in Renal Disease (MDRD) equation; UAE was measured on spot urine samples during the sixth examination cycle (1995–1998) and was indexed to urinary creatinine (n = 822). Thyroid stimulating hormone (TSH) was measured at the third and fourth examination cycles (1981–1984; 1984–1987) and mean value of the measurements were used (n = 810). Age-sex-adjusted and multivariable-adjusted residuals for these measurements were used in association with genotype data using generalized estimating equations (GEE) and family-based association tests (FBAT) models. We presented the results for association tests using additive allele model. We evaluated associations with 70,987 SNPs on autosomes with minor allele frequencies of at least 0.10, Hardy-Weinberg Equilibrium p-value ≥ 0.001, and call rates of at least 80%.
Results
The top SNPs associated with these traits using the GEE method were rs2839235 with GFR (p-value 1.6*10<sup>-05</sup>), rs1158167 with cysC (p-value 8.5*10<sup>-09</sup>), rs1712790 with UAE (p-value 1.9*10<sup>-06</sup>), and rs6977660 with TSH (p-value 3.7*10<sup>-06</sup>), respectively. The top SNPs associated with these traits using the FBAT method were rs6434804 with GFR(p-value 2.4*10<sup>-5</sup>), rs563754 with cysC (p-value 4.7*10<sup>-5</sup>), rs1243400 with UAE (p-value 4.8*10<sup>-6</sup>), and rs4128956 with TSH (p-value 3.6*10<sup>-5</sup>), respectively. Detailed association test results can be found at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007 . Four SNPs in or near the CST 3 gene were highly associated with cysC levels (p-value 8.5*10<sup>-09 </sup>to 0.007).
Conclusion
Kidney function traits and TSH are associated with SNPs on the Affymetrix GeneChip Human Mapping 100K SNP set. These data will serve as a valuable resource for replication as more SNPs associated with kidney function and endocrine traits are identified.
BMC Medical Genetics. 01/2007;
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ABSTRACT: Abstract
Background
Susceptibility to type 2 diabetes may be conferred by genetic variants having modest effects on risk. Genome-wide fixed marker arrays offer a novel approach to detect these variants.
Methods
We used the Affymetrix 100K SNP array in 1,087 Framingham Offspring Study family members to examine genetic associations with three diabetes-related quantitative glucose traits (fasting plasma glucose (FPG), hemoglobin A1c, 28-yr time-averaged FPG (tFPG)), three insulin traits (fasting insulin, HOMA-insulin resistance, and 0–120 min insulin sensitivity index); and with risk for diabetes. We used additive generalized estimating equations (GEE) and family-based association test (FBAT) models to test associations of SNP genotypes with sex-age-age<sup>2</sup>-adjusted residual trait values, and Cox survival models to test incident diabetes.
Results
We found 415 SNPs associated (at p < 0.001) with at least one of the six quantitative traits in GEE, 242 in FBAT (18 overlapped with GEE for 639 non-overlapping SNPs), and 128 associated with incident diabetes (31 overlapped with the 639) giving 736 non-overlapping SNPs. Of these 736 SNPs, 439 were within 60 kb of a known gene. Additionally, 53 SNPs (of which 42 had r<sup>2 </sup>< 0.80 with each other) had p < 0.01 for incident diabetes AND (all 3 glucose traits OR all 3 insulin traits, OR 2 glucose traits and 2 insulin traits); of these, 36 overlapped with the 736 other SNPs. Of 100K SNPs, one (rs7100927) was in moderate LD (r<sup>2 </sup>= 0.50) with TCF7L2 (rs7903146), and was associated with risk of diabetes (Cox p-value 0.007, additive hazard ratio for diabetes = 1.56) and with tFPG (GEE p-value 0.03). There were no common (MAF > 1%) 100K SNPs in LD (r<sup>2 </sup>> 0.05) with ABCC8 A1369S (rs757110), KCNJ11 E23K (rs5219), or SNPs in CAPN10 or HNFa . PPARG P12A (rs1801282) was not significantly associated with diabetes or related traits.
Conclusion
Framingham 100K SNP data is a resource for association tests of known and novel genes with diabetes and related traits posted at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007 . Framingham 100K data replicate the TCF7L2 association with diabetes.
BMC Medical Genetics. 01/2007;
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ABSTRACT: 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<sup>-7</sup>) and rs4471028 (p-values 1.96*10<sup>-7</sup>). 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.
BMC Medical Genetics. 01/2007;
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Christopher O'Donnell,
Cupples L Adrienne,
Ralph D'Agostino, Caroline Fox,
Udo Hoffmann,
Shih-Jen Hwang,
Erik Ingellson,
Chunyu Liu,
Joanne Murabito,
Joseph Polak,
Philip Wolf,
Serkalem Demissie
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ABSTRACT: Abstract
Introduction
Subclinical atherosclerosis (SCA) measures in multiple arterial beds are heritable phenotypes that are associated with increased incidence of cardiovascular disease. We conducted a genome-wide association study (GWAS) for SCA measurements in the community-based Framingham Heart Study.
Methods
Over 100,000 single nucleotide polymorphisms (SNPs) were genotyped (Human 100K GeneChip, Affymetrix) in 1345 subjects from 310 families. We calculated sex-specific age-adjusted and multivariable-adjusted residuals in subjects tested for quantitative SCA phenotypes, including ankle-brachial index, coronary artery calcification and abdominal aortic calcification using multi-detector computed tomography, and carotid intimal medial thickness (IMT) using carotid ultrasonography. We evaluated associations of these phenotypes with 70,987 autosomal SNPs with minor allele frequency ≥ 0.10, call rate ≥ 80%, and Hardy-Weinberg p-value ≥ 0.001 in samples ranging from 673 to 984 subjects, using linear regression with generalized estimating equations (GEE) methodology and family-based association testing (FBAT). Variance components LOD scores were also calculated.
Results
There was no association result meeting criteria for genome-wide significance, but our methods identified 11 SNPs with p < 10<sup>-5 </sup>by GEE and five SNPs with p < 10<sup>-5 </sup>by FBAT for multivariable-adjusted phenotypes. Among the associated variants were SNPs in or near genes that may be considered candidates for further study, such as rs1376877 (GEE p < 0.000001, located in ABI2 ) for maximum internal carotid artery IMT and rs4814615 (FBAT p = 0.000003, located in PCSK2 ) for maximum common carotid artery IMT. Modest significant associations were noted with various SCA phenotypes for variants in previously reported atherosclerosis candidate genes, including NOS3 and ESR1 . Associations were also noted of a region on chromosome 9p21 with CAC phenotypes that confirm associations with coronary heart disease and CAC in two recently reported genome-wide association studies. In linkage analyses, several regions of genome-wide linkage were noted, confirming previously reported linkage of internal carotid artery IMT on chromosome 12. All GEE, FBAT and linkage results are provided as an open-access results resource at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007 .
Conclusion
The results from this GWAS generate hypotheses regarding several SNPs that may be associated with SCA phenotypes in multiple arterial beds. Given the number of tests conducted, subsequent independent replication in a staged approach is essential to identify genetic variants that may be implicated in atherosclerosis.
BMC Medical Genetics. 01/2007;
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Martin Larson,
Larry Atwood,
Emelia Benjamin,
Cupples L Adrienne,
Ralph D'Agostino, Caroline Fox,
Diddahally Govindaraju,
Chao-Yu Guo,
Nancy Heard-Costa,
Shih-Jen Hwang,
Joanne Murabito,
Christopher Newton-Cheh,
Christopher O'Donnell,
Sudha Seshadri,
Ramachandran Vasan,
Thomas Wang,
Philip Wolf,
Daniel Levy
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ABSTRACT: Abstract
Background
Cardiovascular disease (CVD) and its most common manifestations – including coronary heart disease (CHD), stroke, heart failure (HF), and atrial fibrillation (AF) – are major causes of morbidity and mortality. In many industrialized countries, cardiovascular disease (CVD) claims more lives each year than any other disease. Heart disease and stroke are the first and third leading causes of death in the United States. Prior investigations have reported several single gene variants associated with CHD, stroke, HF, and AF. We report a community-based genome-wide association study of major CVD outcomes.
Methods
In 1345 Framingham Heart Study participants from the largest 310 pedigrees (54% women, mean age 33 years at entry), we analyzed associations of 70,987 qualifying SNPs (Affymetrix 100K GeneChip) to four major CVD outcomes: major atherosclerotic CVD (n = 142; myocardial infarction, stroke, CHD death), major CHD (n = 118; myocardial infarction, CHD death), AF (n = 151), and HF (n = 73). Participants free of the condition at entry were included in proportional hazards models. We analyzed model-based deviance residuals using generalized estimating equations to test associations between SNP genotypes and traits in additive genetic models restricted to autosomal SNPs with minor allele frequency ≥0.10, genotype call rate ≥0.80, and Hardy-Weinberg equilibrium p-value ≥ 0.001.
Results
Six associations yielded p < 10<sup>-5</sup>. The lowest p-values for each CVD trait were as follows: major CVD, rs499818, p = 6.6 × 10<sup>-6</sup>; major CHD, rs2549513, p = 9.7 × 10<sup>-6</sup>; AF, rs958546, p = 4.8 × 10<sup>-6</sup>; HF: rs740363, p = 8.8 × 10<sup>-6</sup>. Of note, we found associations of a 13 Kb region on chromosome 9p21 with major CVD (p 1.7 – 1.9 × 10<sup>-5</sup>) and major CHD (p 2.5 – 3.5 × 10<sup>-4</sup>) that confirm associations with CHD in two recently reported genome-wide association studies. Also, rs10501920 in CNTN5 was associated with AF (p = 9.4 × 10<sup>-6</sup>) and HF (p = 1.2 × 10<sup>-4</sup>). Complete results for these phenotypes can be found at the dbgap website http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007 .
Conclusion
No association attained genome-wide significance, but several intriguing findings emerged. Notably, we replicated associations of chromosome 9p21 with major CVD. Additional studies are needed to validate these results. Finding genetic variants associated with CVD may point to novel disease pathways and identify potential targeted preventive therapies.
BMC Medical Genetics. 01/2007;
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ABSTRACT: Abstract
Background
Previously, we reported significant linkage of body mass index (BMI) to chromosomes 6 and 11 across six examinations, covering 28 years, of the Framingham Heart Study. These results were on all individuals available at each exam, thus the sample size varied from exam to exam. To remove any effect of sample size variation we have now constructed six subsets; for each exam individuals were only included if they were measured at every exam , i.e. for each exam, included individuals comprise the intersection of the original six exams. This strategy preferentially removed older individuals who died before reaching the sixth exam, thus the intersection datasets are smaller (n = 1114) and significantly younger than the full datasets. We performed variance components linkage analysis on these intersection datasets and on their sex-specific subsets.
Results
Results from the sex-specific genome scans revealed 11 regions in which a sex-specific maximum lodscore was at least 2.0 for at least one dataset. Randomization tests indicated that all 11 regions had significant (p < 0.05) differences in sex-specific maximum lodscores for at least three datasets. The strongest sex-specific linkage was for men on chromosome 16 with maximum lodscores 2.70, 3.00, 3.42, 3.61, 2.56 and 1.93 for datasets 1–6 respectively.
Results from the full genome scans revealed that linked regions on chromosomes 6 and 11 remained significantly and consistently linked in the intersection datasets. Surprisingly, the maximum lodscore on chromosome 10 for dataset 1 increased from 0.97 in the older original dataset to 4.23 in the younger smaller intersection dataset. This difference in maximum lodscores was highly significant (p < 0.0001), implying that the effect of this chromosome may vary with age. Age effects may also exist for the linked regions on chromosomes 6 and 11.
Conclusion
Sex specific effects of chromosomal regions on BMI are common in the Framingham study. Some evidence also exists for age-specific effects of chromosomal regions.
BMC Genetics. 01/2006;
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ABSTRACT: Twin registries and family history studies provide evidence that genetic factors contribute to the onset of menopause, but heritability estimates in population-based samples are limited. We sought to estimate heritability of age at natural menopause in women participating in the multigenerational Framingham Heart Study, a community-based epidemiological study.
A total of 1500 original cohort and 932 offspring cohort women from 1296 extended families reported a natural menopause defined as the natural cessation of menses for 1 yr or more. Correlation coefficients were calculated using family correlations in Statistical Applications for Genetic Epidemiology for mother-daughter, sister-sister, and aunt-niece pairs. Heritability was estimated using variance-components methods in the Sequential Oligogenic Linkage Analysis Routines (SOLAR) computer package. Covariates in the multivariable models included generation, number of cigarettes smoked, body mass index, and parity.
The mean age at natural menopause was 49.1 and 49.4 yr in original cohort and offspring women, respectively. The multivariable-adjusted correlation coefficients for mother-daughter, sister-sister, and aunt-niece pairs were 0.21, 0.22, and 0.12, respectively. The crude and multivariable-adjusted heritability estimates for age at natural menopause were 0.49 (0.37, 0.61) and 0.52 (0.35, 0.69).
Our data suggest that at least 50% of the interindividual variability in menopausal age appears to be attributable to genetic effects.
Journal of Clinical Endocrinology & Metabolism 07/2005; 90(6):3427-30. · 6.50 Impact Factor
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ABSTRACT: Atherosclerosis is a systemic disease that underlies clinical cardiovascular disease. The radiographic finding of abdominal aortic calcific deposits is an indicator of the presence of aortic atherosclerosis and an independent predictor of cardiovascular disease events. Little is known about the heritability of aortic calcification.
Original Framingham Heart Study cohort participants (2151) in 1109 extended pedigrees had a lateral lumbar radiograph. The presence and severity of abdominal aortic calcific (AAC) deposits at the levels of the first through fourth lumbar vertebrae was graded by a previously validated rating scale. Correlation coefficients were calculated in pairs of siblings, parent-offspring, and spouses. Age-, sex-, and multivariable-adjusted correlation coefficients for AAC were 0.52 for parent-offspring pairs and 0.20 for sibling pairs. In contrast, the multivariable-adjusted correlation for AAC in spouse pairs was -0.02. Using variance component methods implemented in SOLAR, the estimated heritability for age-, sex-, and multivariable-adjusted AAC was 0.49 (P<0.001). Thirty-one percent of the overall variance in AAC deposits was due to measured covariates, and 49% to heritable factors.
In our large, population-based sample, heritable factors play a role in the presence and extent of abdominal aortic calcification. Thus, a substantial proportion of the variation in AAC is due to additive effects of genes, which have yet to be characterized. Measures of aortic atherosclerosis may provide heritable quantitative phenotypes for the genetic dissection of the complex condition of atherosclerosis in human populations.
Circulation 08/2002; 106(3):337-41. · 14.74 Impact Factor
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ABSTRACT: OBJECTIVE— Variants in ADIPOQ have been inconsistently associated with adiponectin levels or diabetes. Using comprehensive linkage disequilibrium mapping, we genotyped single nucleotide polymorphisms (SNPs) in ADIPOQ to evaluate the association of common variants with adiponectin levels and risk of diabetes. RESEARCH DESIGN AND METHODS— Participants in the Framingham Offspring Study (n = 2,543, 53% women) were measured for glycemic phenotypes and incident diabetes over 28 years of follow-up; adiponectin levels were quantified at exam 7. We genotyped 22 tag SNPs that captured common (minor allele frequency >0.05) variation at r[sup]2 > 0.8 across ADIPOQ plus 20 kb 5′ and 10 kb 3′ of the gene. We used linear mixed effects models to test additive associations of each SNP with adiponectin levels and glycemic phenotypes. Hazard ratios (HRs) for incident diabetes were estimated using an adjusted Cox proportional hazards model. RESULTS— Two promoter SNPs in strong linkage disequilibrium with each other (r[sup]2 = 0.80) were associated with adiponectin levels (rs17300539; Pnominal [Pn] = 2.6 × 10−8; Pempiric [Pe] = 0.0005 and rs822387; Pn = 3.8 × 10−5; Pe = 0.001). A 3′-untranslated region (3′UTR) SNP (rs6773957) was associated with adiponectin levels (Pn = 4.4 × 10−4; Pe = 0.005). A nonsynonymous coding SNP (rs17366743, Y111H) was confirmed to be associated with diabetes incidence (HR 1.94 [95% CI 1.16–3.25] for the minor C allele; Pn = 0.01) and with higher mean fasting glucose over 28 years of follow-up (Pn = 0.0004; Pe = 0.004). No other significant associations were found with other adiposity and metabolic phenotypes. CONCLUSIONS— Adiponectin levels are associated with SNPs in two different regulatory regions (5′ promoter and 3′UTR), whereas diabetes incidence and time-averaged fasting glucose are associated with a missense SNP of ADIPOQ.
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ABSTRACT: OBJECTIVE—The prevalence of abdominal obesity exceeds that of general obesity. We sought to determine the prevalence of abdominal subcutaneous and visceral obesity and to characterize the different patterns of fat distribution in a community-based sample. RESEARCH DESIGN AND METHODS—Participants from the Framingham Heart Study (n = 3,348, 48% women, mean age 52 years) underwent multidetector computed tomography; subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) volumes were assessed. Sex-specific high SAT and VAT definitions were based on 90th percentile cut points from a healthy referent sample. Metabolic risk factors were examined in subgroups with elevated SAT and VAT. RESULTS—The prevalence of high SAT was 30% (women) and 31% (men) and that for high VAT was 44% (women) and 42% (men). Overall, 27.8% of the sample was discordant for high SAT and high VAT: 19.9% had SAT less than but VAT equal to or greater than the 90th percentile, and 7.9% had SAT greater than but VAT less than the 90th percentile. The prevalence of metabolic syndrome was higher among women and men with SAT less than the 90th percentile and high VAT than in those with high SAT but VAT less than the 90th percentile, despite lower BMI and waist circumference. Findings were similar for hypertension, elevated triglycerides, and low HDL cholesterol. CONCLUSIONS—Nearly one-third of our sample has abdominal subcutaneous obesity, and <40% have visceral obesity. Clinical measures of BMI and waist circumference may misclassify individuals in terms of VAT and metabolic risk.
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ABSTRACT: OBJECTIVE—Obesity is associated with an increased risk for cardiovascular disease (CVD). We sought to determine rates of treatment and control of CVD risk factors among normal weight, overweight, and obese individuals in a community-based cohort. RESEARCH DESIGN AND METHODS—Participants free of CVD (n = 6,801; mean age 49 years; 54% women) from the Framingham Offspring and Third Generation cohorts who attended the seventh Offspring examination (1998–2001) or first Third Generation (2002–2005) examination were studied. RESULTS—Obese participants with hypertension were more likely to receive antihypertensive treatment (62.3%) than normal weight (58.7%) or overweight (59.0%) individuals (P = 0.002), but no differences in hypertension control across BMI subgroups among participants with hypertension were observed (36.7% [normal weight], 37.3% [overweight], and 39.4% [obese]; P = 0.48). Rates of lipid-lowering treatment were higher among obese participants with elevated LDL cholesterol (39.5%) compared with normal weight (34.2%) or overweight (36.4%) participants (P = 0.02), but control rates among those with elevated LDL cholesterol did not differ across BMI categories (26.7% [normal weight], 26.0% [overweight], and 29.2% [obese]; P = 0.11). There were no differences in diabetes treatment among participants with diabetes across BMI groups (69.2% [normal weight], 50.0% [overweight], 55.0% [obese]; P = 0.54), but obese participants with diabetes were less likely to have fasting blood glucose <126 mg/dl (15.7%) compared with normal weight (30.4%) or overweight (20.7%) participants (P = 0.02). CONCLUSIONS—These findings emphasize the suboptimal rates of treatment and control of CVD risk factors among overweight and obese individuals.
