Literature DB >> 15133310

Multilocus analysis of hypertension: a hierarchical approach.

Scott M Williams1, Marylyn D Ritchie, John A Phillips, Elliot Dawson, Melissa Prince, Elvira Dzhura, Alecia Willis, Amma Semenya, Marshall Summar, Bill C White, Jonathan H Addy, John Kpodonu, Lee-Jun Wong, Robin A Felder, Pedro A Jose, Jason H Moore.   

Abstract

While hypertension is a complex disease with a well-documented genetic component, genetic studies often fail to replicate findings. One possibility for such inconsistency is that the underlying genetics of hypertension is not based on single genes of major effect, but on interactions among genes. To test this hypothesis, we studied both single locus and multilocus effects, using a case-control design of subjects from Ghana. Thirteen polymorphisms in eight candidate genes were studied. Each candidate gene has been shown to play a physiological role in blood pressure regulation and affects one of four pathways that modulate blood pressure: vasoconstriction (angiotensinogen, angiotensin converting enzyme - ACE, angiotensin II receptor), nitric oxide (NO) dependent and NO independent vasodilation pathways and sodium balance (G protein-coupled receptor kinase, GRK4). We evaluated single site allelic and genotypic associations, multilocus genotype equilibrium and multilocus genotype associations, using multifactor dimensionality reduction (MDR). For MDR, we performed systematic reanalysis of the data to address the role of various physiological pathways. We found no significant single site associations, but the hypertensive class deviated significantly from genotype equilibrium in more than 25% of all multilocus comparisons (2,162 of 8,178), whereas the normotensive class rarely did (11 of 8,178). The MDR analysis identified a two-locus model including ACE and GRK4 that successfully predicted blood pressure phenotype 70.5% of the time. Thus, our data indicate epistatic interactions play a major role in hypertension susceptibility. Our data also support a model where multiple pathways need to be affected in order to predispose to hypertension. Copyright 2004 S. Karger AG, Basel

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Year:  2004        PMID: 15133310     DOI: 10.1159/000077387

Source DB:  PubMed          Journal:  Hum Hered        ISSN: 0001-5652            Impact factor:   0.444


  54 in total

Review 1.  Between candidate genes and whole genomes: time for alternative approaches in blood pressure genetics.

Authors:  Jacob Basson; Jeannette Simino; D C Rao
Journal:  Curr Hypertens Rep       Date:  2012-02       Impact factor: 5.369

Review 2.  Dopamine, the kidney, and hypertension.

Authors:  Raymond C Harris; Ming-Zhi Zhang
Journal:  Curr Hypertens Rep       Date:  2012-04       Impact factor: 5.369

3.  Identification of fetal and maternal single nucleotide polymorphisms in candidate genes that predispose to spontaneous preterm labor with intact membranes.

Authors:  Roberto Romero; Digna R Velez Edwards; Juan Pedro Kusanovic; Sonia S Hassan; Shali Mazaki-Tovi; Edi Vaisbuch; Chong Jai Kim; Tinnakorn Chaiworapongsa; Brad D Pearce; Lara A Friel; Jacquelaine Bartlett; Madan Kumar Anant; Benjamin A Salisbury; Gerald F Vovis; Min Seob Lee; Ricardo Gomez; Ernesto Behnke; Enrique Oyarzun; Gerard Tromp; Scott M Williams; Ramkumar Menon
Journal:  Am J Obstet Gynecol       Date:  2010-05       Impact factor: 8.661

4.  Bayesian epistasis association mapping via SNP imputation.

Authors:  Yu Zhang
Journal:  Biostatistics       Date:  2010-10-05       Impact factor: 5.899

5.  Interaction between the C(-344)T polymorphism of CYP11B2 and alcohol consumption on the risk of essential hypertension in a Chinese Mongolian population.

Authors:  Xing-Qiang Pan; Yong-Hong Zhang; Yong-Yue Liu; Wei-Jun Tong
Journal:  Eur J Epidemiol       Date:  2010-09-29       Impact factor: 8.082

6.  Machine learning for detecting gene-gene interactions: a review.

Authors:  Brett A McKinney; David M Reif; Marylyn D Ritchie; Jason H Moore
Journal:  Appl Bioinformatics       Date:  2006

7.  Test for interaction between two unlinked loci.

Authors:  Jinying Zhao; Li Jin; Momiao Xiong
Journal:  Am J Hum Genet       Date:  2006-09-21       Impact factor: 11.025

8.  Building global health through a center-without-walls: the Vanderbilt Institute for Global Health.

Authors:  Sten H Vermund; Vikrant V Sahasrabuddhe; Sheetal Khedkar; Yujiang Jia; Carol Etherington; Alfredo Vergara
Journal:  Acad Med       Date:  2008-02       Impact factor: 6.893

9.  Role of GRK4 in the regulation of arterial AT1 receptor in hypertension.

Authors:  Ken Chen; Chunjiang Fu; Caiyu Chen; Li Liu; Hongmei Ren; Yu Han; Jian Yang; Duofen He; Lin Zhou; Zhiwei Yang; Lianfeng Zhang; Pedro A Jose; Chunyu Zeng
Journal:  Hypertension       Date:  2013-11-11       Impact factor: 10.190

10.  Effects of decreased renal cortical expression of G protein-coupled receptor kinase 4 and angiotensin type 1 receptors in rats.

Authors:  Junichi Yatabe; Hironobu Sanada; Sanae Midorikawa; Shigeatsu Hashimoto; Tsuyoshi Watanabe; Peter M Andrews; Ines Armando; Xiaoyan Wang; Robin A Felder; Pedro A Jose
Journal:  Hypertens Res       Date:  2008-07       Impact factor: 3.872

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