Literature DB >> 25171760

Pharmacogenetic effects of 'candidate gene complexes' on stroke in the GenHAT study.

Izel F Sørensen1, Ana I Vazquez, Marguerite R Irvin, Peter Sørensen, Barry R Davis, Charles E Ford, Eric Boerwinkle, John H Eckfeldt, Donna K Arnett.   

Abstract

OBJECTIVE: The aim of this study was to investigate whether there is a genotype-by-treatment interaction in patients experiencing stroke and treated with one of three antihypertensive drugs, that is chlorthalidone, amlodipine, or lisinopril. PARTICIPANTS AND METHODS: A population of 436 African Americans and 539 whites who had experienced stroke in the GenHAT study were genotyped for 768 single nucleotide polymorphisms (SNPs) in 280 candidate genes. To detect a genotype-by-treatment interaction, we used the Pearson's χ-test to assess whether the genotype frequencies differed at the single SNP level for the three drug treatment groups. From these single SNP analyses, we derived a summary statistic for the degree of association at the gene and gene complex levels. This was done by grouping SNPs using information on gene locations and defining gene complexes on the basis of protein-protein interactions. To assess the statistical significance of the observed test statistic, we derived an empirical P-value by simulating data under the null hypothesis.
RESULTS: We found that, in patients who have experienced stroke, there is a significant genetic difference between hypertension drug treatment groups. In African Americans, SNP rs12143842 showed a significant association (P<0.001) with drug treatment. At the gene level, HNRNPA1P4 and NOS1AP in African Americans and PRICKLE1 and NINJ2 in non-Hispanic whites were significantly associated (P<0.01) with drug treatment, whereas none of the gene complexes tested showed significance.
CONCLUSION: On the basis of the genetic differences between drug treatment groups, we conclude that there may be an interaction between certain genotypes and antihypertensive treatment in stroke patients. This needs to be replicated in other studies.

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Year:  2014        PMID: 25171760      PMCID: PMC4189974          DOI: 10.1097/FPC.0000000000000088

Source DB:  PubMed          Journal:  Pharmacogenet Genomics        ISSN: 1744-6872            Impact factor:   2.089


  41 in total

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Authors:  Alexander G Bassuk; Robyn H Wallace; Aimee Buhr; Andrew R Buller; Zaid Afawi; Masahito Shimojo; Shingo Miyata; Shan Chen; Pedro Gonzalez-Alegre; Hilary L Griesbach; Shu Wu; Marcus Nashelsky; Eszter K Vladar; Dragana Antic; Polly J Ferguson; Sebahattin Cirak; Thomas Voit; Matthew P Scott; Jeffrey D Axelrod; Christina Gurnett; Azhar S Daoud; Sara Kivity; Miriam Y Neufeld; Aziz Mazarib; Rachel Straussberg; Simri Walid; Amos D Korczyn; Diane C Slusarski; Samuel F Berkovic; Hatem I El-Shanti
Journal:  Am J Hum Genet       Date:  2008-10-30       Impact factor: 11.025

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