Literature DB >> 11849460

Predictors of antihypertensive response to a standard dose of hydrochlorothiazide for essential hypertension.

Arlene B Chapman1, Gary L Schwartz, Eric Boerwinkle, Stephen T Turner.   

Abstract

BACKGROUND: Determinants of inter-individual variation in blood pressure (BP) response to antihypertensive therapy remain largely unknown. Although differences in race, age and measures of the renin-angiotensin-aldosterone system (RAAS) have been associated with variation in blood pressure response to hydrochlorothiazide, whether these characteristics make additive contributions to predicting response has not been established. We conducted a comprehensive search for predictors of BP response to a standard dose of hydrochlorothiazide in a biracial sample to estimate how much inter-individual variation in BP response could be explained by all of the identified predictors.
METHODS: After withdrawal of antihypertensive medications for at least four weeks (baseline) and stabilization on a diet approximating 150 mmol sodium per day, 225 African American and 280 Caucasian subjects with diagnosed essential hypertension were treated for four weeks with hydrochlorothiazide 25 mg per day. At baseline and the end of treatment, subjects were admitted to the General Clinical Research Center for measurement of activity of the RAAS and other regulators of BP. Characteristics measured at study enrollment, at baseline, and in response to drug treatment were incorporated stepwise into linear regression models in order to quantify their additive contributions to predicting BP responses to hydrochlorothiazide.
RESULTS: Black race and female gender were both associated with significantly greater systolic (SBP) and diastolic (DBP) blood pressure responses to hydrochlorothiazide. Together the combined effects of race and gender accounted for 11% inter-individual variation in SBP response (P < 0.0001) and 4% of inter-individual variation in DBP response (P < 0.0001). Additional statistically significant predictors of greater systolic and diastolic responses to hydrochlorothiazide included, shorter duration of diagnosed or treated hypertension (P < 0.001), higher baseline BP level (P < 0.0001), lower baseline plasma renin activity (P < 0.05), lower baseline urinary aldosterone excretion (P < 0.002), and greater decrease in urinary sodium excretion (P < or = 0.004). Greater decrease in weight was an additional statistically significant predictor of SBP but not DBP response, and older age was a predictor of diastolic but not SBP response. The combined effects of all identified predictors accounted for 38% of inter-individual variation in SBP response (P < 0.0001) and 20% of inter-individual variation in DBP response (P < 0.0001).
CONCLUSIONS: A systematic search reveals numerous predictors of BP response to a standard antihypertensive dose of hydrochlorothiazide. However, because the majority of inter-individual variation in SBP and DBP responses remains unexplained, there is considerable opportunity for future investigations to improve the ability to predict individual BP responses to antihypertensive drug therapy.

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Year:  2002        PMID: 11849460     DOI: 10.1046/j.1523-1755.2002.00200.x

Source DB:  PubMed          Journal:  Kidney Int        ISSN: 0085-2538            Impact factor:   10.612


  46 in total

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Journal:  Drugs       Date:  2004       Impact factor: 9.546

Review 2.  Pharmacogenetics of antihypertensive drug response.

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Journal:  Curr Hypertens Rep       Date:  2004-02       Impact factor: 5.369

3.  Plasma renin activity predicts blood pressure responses to beta-blocker and thiazide diuretic as monotherapy and add-on therapy for hypertension.

Authors:  Stephen T Turner; Gary L Schwartz; Arlene B Chapman; Amber L Beitelshees; John G Gums; Rhonda M Cooper-DeHoff; Eric Boerwinkle; Julie A Johnson; Kent R Bailey
Journal:  Am J Hypertens       Date:  2010-08-19       Impact factor: 2.689

Review 4.  Do thiazides worsen metabolic syndrome and renal disease? The pivotal roles for hyperuricemia and hypokalemia.

Authors:  Sirirat Reungjui; Thongchai Pratipanawatr; Richard J Johnson; Takahiko Nakagawa
Journal:  Curr Opin Nephrol Hypertens       Date:  2008-09       Impact factor: 2.894

5.  Genetic Variants Influencing Plasma Renin Activity in Hypertensive Patients From the PEAR Study (Pharmacogenomic Evaluation of Antihypertensive Responses).

Authors:  Caitrin W McDonough; Oyunbileg Magvanjav; Ana C C Sá; Nihal M El Rouby; Chintan Dave; Amelia N Deitchman; Marina Kawaguchi-Suzuki; Wenbin Mei; Yong Shen; Ravi Shankar Prasad Singh; Mohamed Solayman; Kent R Bailey; Eric Boerwinkle; Arlene B Chapman; John G Gums; Amy Webb; Steven E Scherer; Wolfgang Sadee; Stephen T Turner; Rhonda M Cooper-DeHoff; Yan Gong; Julie A Johnson
Journal:  Circ Genom Precis Med       Date:  2018-04

Review 6.  Thiazide effects and adverse effects: insights from molecular genetics.

Authors:  David H Ellison; Johannes Loffing
Journal:  Hypertension       Date:  2009-06-29       Impact factor: 10.190

7.  Kininogen gene (KNG) variation has a consistent effect on aldosterone response to antihypertensive drug therapy: the GERA study.

Authors:  Maja Barbalic; Gary L Schwartz; Arlene B Chapman; Stephen T Turner; Eric Boerwinkle
Journal:  Physiol Genomics       Date:  2009-07-07       Impact factor: 3.107

Review 8.  Salt sensitivity: a review with a focus on non-Hispanic blacks and Hispanics.

Authors:  Safiya I Richardson; Barry I Freedman; David H Ellison; Carlos J Rodriguez
Journal:  J Am Soc Hypertens       Date:  2013-02-19

9.  Risk of hypercalcemia in blacks taking hydrochlorothiazide and vitamin D.

Authors:  Paulette D Chandler; Jamil B Scott; Bettina F Drake; Kimmie Ng; John P Forman; Andrew T Chan; Gary G Bennett; Bruce W Hollis; Edward L Giovannucci; Karen M Emmons; Charles S Fuchs
Journal:  Am J Med       Date:  2014-03-20       Impact factor: 4.965

10.  GLOSSI: a method to assess the association of genetic loci-sets with complex diseases.

Authors:  High-Seng Chai; Hugues Sicotte; Kent R Bailey; Stephen T Turner; Yan W Asmann; Jean-Pierre A Kocher
Journal:  BMC Bioinformatics       Date:  2009-04-03       Impact factor: 3.169

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