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Articles by J. B Meigs
Total Records ( 3 ) for J. B Meigs
  N. L Smith , M. H Chen , A Dehghan , D. P Strachan , S Basu , N Soranzo , C Hayward , I Rudan , M Sabater Lleal , J. C Bis , M. P. M de Maat , A Rumley , X Kong , Q Yang , F. M. K Williams , V Vitart , H Campbell , A Malarstig , K. L Wiggins , C. M Van Duijn , W. L McArdle , J. S Pankow , A. D Johnson , A Silveira , B McKnight , A. G Uitterlinden , Aleksic Wellcome Trust Case Control Consortium; , J. B Meigs , A Peters , W Koenig , M Cushman , S Kathiresan , J. I Rotter , E. G Bovill , A Hofman , E Boerwinkle , G. H Tofler , J. F Peden , B. M Psaty , F Leebeek , A. R Folsom , M. G Larson , T. D Spector , A. F Wright , J. F Wilson , A Hamsten , T Lumley , J. C. M Witteman , W Tang and C. J. O'Donnell

Background— Plasma levels of coagulation factors VII (FVII), VIII (FVIII), and von Willebrand factor (vWF) influence risk of hemorrhage and thrombosis. We conducted genome-wide association studies to identify new loci associated with plasma levels.

Methods and Results— The setting of the study included 5 community-based studies for discovery comprising 23 608 European-ancestry participants: Atherosclerosis Risk In Communities Study, Cardiovascular Health Study, British 1958 Birth Cohort, Framingham Heart Study, and Rotterdam Study. All subjects had genome-wide single-nucleotide polymorphism (SNP) scans and at least 1 phenotype measured: FVII activity/antigen, FVIII activity, and vWF antigen. Each study used its genotype data to impute to HapMap SNPs and independently conducted association analyses of hemostasis measures using an additive genetic model. Study findings were combined by meta-analysis. Replication was conducted in 7604 participants not in the discovery cohort. For FVII, 305 SNPs exceeded the genome-wide significance threshold of 5.0x10–8 and comprised 5 loci on 5 chromosomes: 2p23 (smallest P value 6.2x10–24), 4q25 (3.6x10–12), 11q12 (2.0x10–10), 13q34 (9.0x10–259), and 20q11.2 (5.7x10–37). Loci were within or near genes, including 4 new candidate genes and F7 (13q34). For vWF, 400 SNPs exceeded the threshold and marked 8 loci on 6 chromosomes: 6q24 (1.2x10–22), 8p21 (1.3x10–16), 9q34 (<5.0x10–324), 12p13 (1.7x10–32), 12q23 (7.3x10–10), 12q24.3 (3.8x10–11), 14q32 (2.3x10–10), and 19p13.2 (1.3x10–9). All loci were within genes, including 6 new candidate genes, as well as ABO (9q34) and VWF (12p13). For FVIII, 5 loci were identified and overlapped vWF findings. Nine of the 10 new findings were replicated.

Conclusions— New genetic associations were discovered outside previously known biological pathways and may point to novel prevention and treatment targets of hemostasis disorders.

  R. B Schnabel , K. L Lunetta , M. G Larson , J Dupuis , I Lipinska , J Rong , M. H Chen , Z Zhao , J. F Yamamoto , J. B Meigs , V Nicaud , C Perret , T Zeller , S Blankenberg , L Tiret , J. F Keaney , R. S Vasan and E. J. Benjamin

Background— Environmental and genetic correlates of inflammatory marker variability are incompletely understood. In the family-based Framingham Heart Study, we investigated heritability and candidate gene associations of systemic inflammatory biomarkers.

Methods and Results— In offspring participants (n=3710), we examined 11 inflammatory biomarkers (CD40 ligand, C-reactive protein, intercellular adhesion molecule-1, interleukin-6, urinary isoprostanes, monocyte chemoattractant protein-1, myeloperoxidase, P-selectin, tumor necrosis factor-, tumor necrosis factor receptor II, fibrinogen). Heritability and bivariate genetic and environmental correlations were assessed by Sequential Oligogenic Linkage Analysis routines in 1012 family members. We examined 1943 tagging single-nucleotide polymorphisms in 233 inflammatory pathway genes with ≥5 minor allele carriers using a general genetic linear model. Clinical correlates explained 2.4% (CD40 ligand) to 28.5% (C-reactive protein) of the variability in inflammatory biomarkers. Estimated heritability ranged from 10.9% (isoprostanes) to 44.8% (P-selectin). Most correlations between biomarkers were weak although statistically significant. A total of 45 single-nucleotide polymorphism-biomarker associations met the q-value threshold of 0.25. Novel top single-nucleotide polymorphisms were observed in ICAM1 gene in relation to intercellular adhesion molecule-1 concentrations (rs1799969, P=1.32x10–8) and MPO in relation to myeloperoxidase (rs28730837, P=1.9x10–5). Lowest P values for trans-acting single-nucleotide polymorphisms were observed for APCS with monocyte chemoattractant protein-1 concentrations (rs1374486, P=1.01x10–7) and confirmed for IL6R with interleukin-6 concentrations (rs8192284, P=3.36x10–5). Novel potential candidates (APCS, MPO) need to be replicated.

Conclusions— Our community-based data support the relevance of clinical and genetic factors for explaining variation in inflammatory biomarker traits.

  C. S Fox , J. M Massaro , C. L Schlett , S. J Lehman , J. B Meigs , C. J O'Donnell , U Hoffmann and J. M. Murabito

Central obesity is associated with peripheral arterial disease, suggesting that ectopic fat depots may be associated with localized diseases of the aorta and lower-extremity arteries. We hypothesized that persons with greater amounts of periaortic fat are more likely to have clinical PAD and a low ankle-brachial index.

Methods and Results—

We quantified periaortic fat surrounding the thoracic aorta using a novel volumetric quantitative approach in 1205 participants from the Framingham Heart Study Offspring cohort (mean age, 65.9 years; women, 54%); visceral abdominal fat also was measured. Clinical peripheral arterial disease was defined as a history of intermittent claudication, and ankle-brachial index was dichotomized as low (≤0.9) or lower-extremity revascularization versus normal (>0.9 to <1.4). Regression models were created to examine the association between periaortic fat and intermittent claudication or low ankle-brachial index (n=66). In multivariable logistic regression, per 1 SD increase in periaortic fat, the odds ratio for the combined end point was 1.52 (P=0.004); these results were strengthened with additional adjustment for body mass index (odds ratio, 1.69; P=0.002) or visceral abdominal fat (odds ratio, 1.67; P=0.009), whereas no association was observed for visceral abdominal fat (P=0.16). Similarly, per SD increase in body mass index or waist circumference, no association was observed after accounting for visceral abdominal fat (body mass index, P=0.35; waist circumference, P=0.49).


Periaortic fat is associated with low ABI and intermittent claudication.

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