Genetic Architecture of Plasma T-PA and PAI-1
Information source: National Heart, Lung, and Blood Institute (NHLBI)
Information obtained from ClinicalTrials.gov on June 20, 2008
Link to the current ClinicalTrials.gov record.
Condition(s) targeted: Cardiovascular Diseases; Heart Diseases; Thrombosis; Atherosclerosis
Phase: N/A
Status: Completed
Sponsored by: National Heart, Lung, and Blood Institute (NHLBI) Official(s) and/or principal investigator(s):
Jason Moore, Affiliation: Vanderbilt University
Summary
To determine the effects of six genes on thrombotic risk factors known to be associated with
the development of heart disease.
Clinical Details
Study design: N/A
Detailed description:
BACKGROUND:
Abnormalities in the plasminogen activator system have been implicated in the pathogenesis of
arterial and cerebral thrombosis. In particular, elevated plasma levels of plasminogen
activator inhibitor-1 (PAI-1), tissue-type plasminogen activator (t-PA), and t-PA/PAI-1
complexes have been found to correlate with increased risk of myocardial infarction (MI)
and/or stroke. Vascular fibrinolytic balance is, to a large part, determined by the competing
effects of t-PA and PAI-1, and reflects a complex interplay between genetic and environmental
factors. The present collaboration focuses on the common hypothesis that the association
between activation of the renin-angiotensin-aldosterone system (RAAS) and atherothrombotic
events derives from an interaction between the RAAS and the fibrinolytic system.
The study is part of an initiative "Thrombosis of the Arterial and Cerebral Vasculature: New
Molecular Genetic Concepts for Prevention and Treatment" which was released in April 1999.
The objective of the initiative is to establish collaborative teams of closely interacting
investigators with diverse, complementary areas of expertise to elucidate the molecular
genetic mechanisms of thrombosis in the arterial and cerebral vasculature.
DESIGN NARRATIVE:
The investigators will use two population-based samples of unrelated individuals to address
their aims: 1) study subjects in the PREVEND study in Groningen, The Netherlands in whom DNA
and plasma samples and clinical data have already been collected and 2) an estimated 2000
unrelated study subjects from Ghana, Africa in whom data need to be collected. The
collaborative study focuses on the common hypothesis that the association between activation
of the renin-angiotensin-aldosterone system (RAAS) and atherothrombotic events derives from
an interaction between the RAAS and the fibrinolytic system.
Eligibility
Minimum age: N/A.
Maximum age: N/A.
Gender(s): Both.
Criteria:
No eligibility criteria
Locations and Contacts
Additional Information
Related publications: Moore JH, Williams SM. New strategies for identifying gene-gene interactions in hypertension. Ann Med. 2002;34(2):88-95. Review. Hahn LW, Ritchie MD, Moore JH. Multifactor dimensionality reduction software for detecting gene-gene and gene-environment interactions. Bioinformatics. 2003 Feb 12;19(3):376-82. Ritchie MD, Hahn LW, Moore JH. Power of multifactor dimensionality reduction for detecting gene-gene interactions in the presence of genotyping error, missing data, phenocopy, and genetic heterogeneity. Genet Epidemiol. 2003 Feb;24(2):150-7. Moore JH, Smolkin ME, Lamb JM, Brown NJ, Vaughan DE. The relationship between plasma t-PA and PAI-1 levels is dependent on epistatic effects of the ACE I/D and PAI-1 4G/5G polymorphisms. Clin Genet. 2002 Jul;62(1):53-9. Coffey CS, Hebert PR, Krumholz HM, Morgan TM, Williams SM, Moore JH. Reporting of model validation procedures in human studies of genetic interactions. Nutrition. 2004 Jan;20(1):69-73. No abstract available. Moore JH, Hahn LW. Petri net modeling of high-order genetic systems using grammatical evolution. Biosystems. 2003 Nov;72(1-2):177-86. Moore JH. The ubiquitous nature of epistasis in determining susceptibility to common human diseases. Hum Hered. 2003;56(1-3):73-82. Ritchie MD, White BC, Parker JS, Hahn LW, Moore JH. Optimization of neural network architecture using genetic programming improves detection and modeling of gene-gene interactions in studies of human diseases. BMC Bioinformatics. 2003 Jul 07;4(1):28. Williams SM, Ritchie MD, Phillips JA 3rd, Dawson E, Prince M, Dzhura E, Willis A, Semenya A, Summar M, White BC, Addy JH, Kpodonu J, Wong LJ, Felder RA, Jose PA, Moore JH. Multilocus analysis of hypertension: a hierarchical approach. Hum Hered. 2004;57(1):28-38. Smith MW, Patterson N, Lautenberger JA, Truelove AL, McDonald GJ, Waliszewska A, Kessing BD, Malasky MJ, Scafe C, Le E, De Jager PL, Mignault AA, Yi Z, De The G, Essex M, Sankale JL, Moore JH, Poku K, Phair JP, Goedert JJ, Vlahov D, Williams SM, Tishkoff SA, Winkler CA, De La Vega FM, Woodage T, Sninsky JJ, Hafler DA, Altshuler D, Gilbert DA, O'Brien SJ, Reich D. A high-density admixture map for disease gene discovery in african americans. Am J Hum Genet. 2004 May;74(5):1001-13. Epub 2004 Apr 14. Moore JH, Ritchie MD. STUDENTJAMA. The challenges of whole-genome approaches to common diseases. JAMA. 2004 Apr 7;291(13):1642-3. No abstract available. Tsai CT, Lai LP, Lin JL, Chiang FT, Hwang JJ, Ritchie MD, Moore JH, Hsu KL, Tseng CD, Liau CS, Tseng YZ. Renin-angiotensin system gene polymorphisms and atrial fibrillation. Circulation. 2004 Apr 6;109(13):1640-6. Epub 2004 Mar 15. Zeng C, Sanada H, Watanabe H, Eisner GM, Felder RA, Jose PA. Functional genomics of the dopaminergic system in hypertension. Physiol Genomics. 2004 Nov 17;19(3):233-46. Moore JH. Computational analysis of gene-gene interactions using multifactor dimensionality reduction. Expert Rev Mol Diagn. 2004 Nov;4(6):795-803. Review. Thornton-Wells TA, Moore JH, Haines JL. Genetics, statistics and human disease: analytical retooling for complexity. Trends Genet. 2004 Dec;20(12):640-7. Robinson M, Williams SM. Role of two angiotensinogen polymorphisms in blood pressure variation. J Hum Hypertens. 2004 Dec;18(12):865-9. Hahn LW, Moore JH. Ideal discrimination of discrete clinical endpoints using multilocus genotypes. In Silico Biol. 2004;4(2):183-94. Moore JH, Ritchie MD. STUDENTJAMA. The challenges of whole-genome approaches to common diseases. JAMA. 2004 Apr 7;291(13):1642-3. No abstract available. Moore JH, Boczko EM, Summar ML. Connecting the dots between genes, biochemistry, and disease susceptibility: systems biology modeling in human genetics. Mol Genet Metab. 2005 Feb;84(2):104-11. Epub 2004 Dec 19.
Starting date: September 2000
Ending date: July 2006
Last updated: January 18, 2008
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