Literature DB >> 23087401

Hypertension susceptibility loci and blood pressure response to antihypertensives: results from the pharmacogenomic evaluation of antihypertensive responses study.

Yan Gong1, Caitrin W McDonough, Zhiying Wang, Wei Hou, Rhonda M Cooper-DeHoff, Taimour Y Langaee, Amber L Beitelshees, Arlene B Chapman, John G Gums, Kent R Bailey, Eric Boerwinkle, Stephen T Turner, Julie A Johnson.   

Abstract

BACKGROUND: To date, 39 single nucleotide polymorphisms (SNPs) have been associated with blood pressure (BP) or hypertension in genome-wide association studies in whites. Our hypothesis is that the loci/SNPs associated with BP/hypertension are also associated with BP response to antihypertensive drugs. METHODS AND
RESULTS: We assessed the association of these loci with BP response to atenolol or hydrochlorothiazide monotherapy in 768 hypertensive participants in the Pharmacogenomics Responses of Antihypertensive Responses study. Linear regression analysis was performed on whites for each SNP in an additive model adjusting for baseline BP, age, sex, and principal components for ancestry. Genetic scores were constructed to include SNPs with nominal associations, and empirical P values were determined by permutation test. Genotypes of 37 loci were obtained from Illumina 50K cardiovascular or Omni1M genome-wide association study chips. In whites, no SNPs reached Bonferroni-corrected α of 0.0014, 6 reached nominal significance (P<0.05), and 3 were associated with atenolol BP response at P<0.01. The genetic score of the atenolol BP-lowering alleles was associated with response to atenolol (P=3.3 × 10(-6) for systolic BP; P=1.6 × 10(-6) for diastolic BP). The genetic score of the hydrochlorothiazide BP-lowering alleles was associated with response to hydrochlorothiazide (P=0.0006 for systolic BP; P=0.0003 for diastolic BP). Both risk score P values were <0.01 based on the empirical distribution from the permutation test.
CONCLUSIONS: These findings suggest that selected signals from hypertension genome-wide association studies may predict BP response to atenolol and hydrochlorothiazide when assessed through risk scoring. Clinical Trial Registration Information- clinicaltrials.gov; Identifier: NCT00246519.

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Year:  2012        PMID: 23087401      PMCID: PMC3529147          DOI: 10.1161/CIRCGENETICS.112.964080

Source DB:  PubMed          Journal:  Circ Cardiovasc Genet        ISSN: 1942-3268


  20 in total

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Authors:  S Ragot; N Genès; L Vaur; D Herpin
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2.  Cardiovascular protection and blood pressure reduction: a meta-analysis.

Authors:  J A Staessen; J G Wang; L Thijs
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3.  PLINK: a tool set for whole-genome association and population-based linkage analyses.

Authors:  Shaun Purcell; Benjamin Neale; Kathe Todd-Brown; Lori Thomas; Manuel A R Ferreira; David Bender; Julian Maller; Pamela Sklar; Paul I W de Bakker; Mark J Daly; Pak C Sham
Journal:  Am J Hum Genet       Date:  2007-07-25       Impact factor: 11.025

4.  Diagnosis ex juvantibus. Individual response patterns to drugs reveal hypertension mechanisms and simplify treatment.

Authors:  J H Laragh; B Lamport; J Sealey; M H Alderman
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5.  Reproducibility of home, ambulatory, and clinic blood pressure: implications for the design of trials for the assessment of antihypertensive drug efficacy.

Authors:  George S Stergiou; Nikolaos M Baibas; Alexandra P Gantzarou; Irini I Skeva; Chrysa B Kalkana; Leonidas G Roussias; Theodore D Mountokalakis
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6.  Optimisation of antihypertensive treatment by crossover rotation of four major classes.

Authors:  J E Dickerson; A D Hingorani; M J Ashby; C R Palmer; M J Brown
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7.  The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report.

Authors:  Aram V Chobanian; George L Bakris; Henry R Black; William C Cushman; Lee A Green; Joseph L Izzo; Daniel W Jones; Barry J Materson; Suzanne Oparil; Jackson T Wright; Edward J Roccella
Journal:  JAMA       Date:  2003-05-14       Impact factor: 56.272

8.  Single-drug therapy for hypertension in men. A comparison of six antihypertensive agents with placebo. The Department of Veterans Affairs Cooperative Study Group on Antihypertensive Agents.

Authors:  B J Materson; D J Reda; W C Cushman; B M Massie; E D Freis; M S Kochar; R J Hamburger; C Fye; R Lakshman; J Gottdiener
Journal:  N Engl J Med       Date:  1993-04-01       Impact factor: 91.245

9.  Response to a second single antihypertensive agent used as monotherapy for hypertension after failure of the initial drug. Department of Veterans Affairs Cooperative Study Group on Antihypertensive Agents.

Authors:  B J Materson; D J Reda; R A Preston; W C Cushman; B M Massie; E D Freis; M S Kochar; R J Hamburger; C Fye; R Lakshman
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Authors:  Jason H Karnes; Yan Gong; Michael A Pacanowski; Caitrin W McDonough; Meghan J Arwood; Taimour Y Langaee; Carl J Pepine; Julie A Johnson; Rhonda M Cooper-Dehoff
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Review 3.  Mechanisms of Vascular Smooth Muscle Contraction and the Basis for Pharmacologic Treatment of Smooth Muscle Disorders.

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4.  Increasing the Precision of Hypertension Treatment Through Personalized Trials: a Pilot Study.

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Review 5.  Genetics, ancestry, and hypertension: implications for targeted antihypertensive therapies.

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Review 7.  An update on the pharmacogenetics of treating hypertension.

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Review 8.  Genome-Wide and Gene-Based Meta-Analyses Identify Novel Loci Influencing Blood Pressure Response to Hydrochlorothiazide.

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Journal:  Hypertension       Date:  2016-10-31       Impact factor: 10.190

Review 9.  Genetics of resistant hypertension: a novel pharmacogenomics phenotype.

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10.  Analytical validity of a genotyping assay for use with personalized antihypertensive and chronic kidney disease therapy.

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