Literature DB >> 28408189

Genetic Effects on the Correlation Structure of CVD Risk Factors: Exome-Wide Data From a Ghanaian Population.

Nuri Kodaman1, Rafal S Sobota2, Folkert W Asselbergs3, Matthew T Oetjens4, Jason H Moore5, Nancy J Brown6, Melinda C Aldrich7, Scott M Williams8.   

Abstract

Plasma concentration of plasminogen activator inhibitor-1 (PAI-1) is highly correlated with several cardiovascular disease (CVD) risk factors. It also plays a direct role in CVD, including myocardial infarction and stroke, by impeding the dissolution of thrombi in the blood. Insofar as PAI-1 links CVD's risk factors to its endpoints, genetic variants modulating the relationship between PAI-1 and risk factors may be of particular clinical and biological interest. The high heritability of PAI-1, which has not been explained by genetic association studies, may also, in large part, be due to this relationship with CVD risk factors. Using exome-wide data from 1,032 Ghanaian study participants, we tested for heterogeneity of correlation by genotype between PAI-1 and 4 CVD risk factors (body mass index, triglycerides, mean arterial pressure, and fasting glucose) under the hypothesis that loci involved in the relationship between PAI-1 and other risk factors will also modify their correlational structure. We found more significant heterogeneities of correlation by genotype than we found marginal effects, with no evidence of type I inflation. The most significant result among all univariate and multivariate tests performed in this study was the heterogeneity of correlation between PAI-1 and mean arterial pressure at rs10738554, near SLC24A2, a gene previously associated with high blood pressure in African Americans.
Copyright © 2017 World Heart Federation (Geneva). Published by Elsevier B.V. All rights reserved.

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Year:  2017        PMID: 28408189      PMCID: PMC5642993          DOI: 10.1016/j.gheart.2017.01.013

Source DB:  PubMed          Journal:  Glob Heart


  41 in total

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Journal:  J Immunol       Date:  2010-10-06       Impact factor: 5.422

2.  Addressing population-specific multiple testing burdens in genetic association studies.

Authors:  Rafal S Sobota; Daniel Shriner; Nuri Kodaman; Robert Goodloe; Wei Zheng; Yu-Tang Gao; Todd L Edwards; Christopher I Amos; Scott M Williams
Journal:  Ann Hum Genet       Date:  2015-01-22       Impact factor: 1.670

3.  Genetics of dietary habits and obesity - a twin study.

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Journal:  Dan Med Bull       Date:  2010-09

4.  Common SNPs explain a large proportion of the heritability for human height.

Authors:  Jian Yang; Beben Benyamin; Brian P McEvoy; Scott Gordon; Anjali K Henders; Dale R Nyholt; Pamela A Madden; Andrew C Heath; Nicholas G Martin; Grant W Montgomery; Michael E Goddard; Peter M Visscher
Journal:  Nat Genet       Date:  2010-06-20       Impact factor: 38.330

5.  PAI-1 in human hypertension: relation to hypertensive groups.

Authors:  Nadarajah Srikumar; Nancy J Brown; Paul N Hopkins; Xavier Jeunemaitre; Steven C Hunt; Douglas E Vaughan; Gordon H Williams
Journal:  Am J Hypertens       Date:  2002-08       Impact factor: 2.689

Review 6.  Genetic architecture of tissue-type plasminogen activator and plasminogen activator inhibitor-1.

Authors:  Folkert W Asselbergs; Kristine Pattin; Harold Snieder; Hans L Hillege; Wiek H van Gilst; Jason H Moore
Journal:  Semin Thromb Hemost       Date:  2008-11-28       Impact factor: 4.180

7.  Prevention of obesity and insulin resistance in mice lacking plasminogen activator inhibitor 1.

Authors:  Li-Jun Ma; Su-Li Mao; Kevin L Taylor; Talerngsak Kanjanabuch; YouFei Guan; YaHua Zhang; Nancy J Brown; Larry L Swift; Owen P McGuinness; David H Wasserman; Douglas E Vaughan; Agnes B Fogo
Journal:  Diabetes       Date:  2004-02       Impact factor: 9.461

8.  Association between the plasminogen activator inhibitor-1 4G/5G polymorphism and venous thrombosis. A meta-analysis.

Authors:  Argirios E Tsantes; Georgios K Nikolopoulos; Pantelis G Bagos; Evdoxia Rapti; Georgios Mantzios; Violeta Kapsimali; Anthi Travlou
Journal:  Thromb Haemost       Date:  2007-06       Impact factor: 5.249

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Journal:  Nature       Date:  2012-02-08       Impact factor: 49.962

10.  MultiPhen: joint model of multiple phenotypes can increase discovery in GWAS.

Authors:  Paul F O'Reilly; Clive J Hoggart; Yotsawat Pomyen; Federico C F Calboli; Paul Elliott; Marjo-Riitta Jarvelin; Lachlan J M Coin
Journal:  PLoS One       Date:  2012-05-02       Impact factor: 3.240

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  1 in total

1.  Risk factors for Keshan disease: a prospective cohort study protocol of gut flora.

Authors:  Zhenzhen Li; Jin Wei; Yanping Zhang; Gaopeng Li; Huange Zhu; Na Lei; Qian He; Yan Geng; Jianhong Zhu
Journal:  BMC Cardiovasc Disord       Date:  2020-11-11       Impact factor: 2.298

  1 in total

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