title: Power to identify a genetic predictor of antihypertensive drug response using different methods to measure blood pressure response.
abstract: BACKGROUND
  To determine whether office, home, ambulatory daytime and nighttime blood pressure (BP) responses to antihypertensive drug therapy measure the same signal and which method provides greatest power to identify genetic predictors of BP response.
  
  
  METHODS
  We analyzed office, home, ambulatory daytime and nighttime BP responses in hypertensive adults randomized to atenolol (N = 242) or hydrochlorothiazide (N = 257) in the Pharmacogenomic Evaluation of Antihypertensive Responses Study. Since different measured BP responses may have different predictors, we tested the "same signal" model by using linear regression methods to determine whether known predictors of BP response depend on the method of BP measurement. We estimated signal-to-noise ratios and compared power to identify a genetic polymorphism predicting BP response measured by each method separately and by weighted averages of multiple methods.
  
  
  RESULTS
  After adjustment for pretreatment BP level, known predictors of BP response including plasma renin activity, race, and sex were independent of the method of BP measurement. Signal-to-noise ratios were more than 2-fold greater for home and ambulatory daytime BP responses than for office and ambulatory nighttime BP responses and up to 11-fold greater for weighted averages of all four methods. Power to identify a genetic polymorphism predicting BP response was directly related to the signal-to-noise ratio and, therefore, greatest with the weighted averages.
  
  
  CONCLUSIONS
  Since different methods of measuring BP response to antihypertensive drug therapy measure the same signal, weighted averages of the BP responses measured by multiple methods minimize measurement error and optimize power to identify genetic predictors of BP response.
authors.affiliation: Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA. sturner@mayo.edu
authors.forename: Stephen T
authors.initials: ST
authors.lastname: Turner
authors.forename: Gary L
authors.initials: GL
authors.lastname: Schwartz
authors.forename: Arlene B
authors.initials: AB
authors.lastname: Chapman
authors.forename: Amber L
authors.initials: AL
authors.lastname: Beitelshees
authors.forename: John G
authors.initials: JG
authors.lastname: Gums
authors.forename: Rhonda M
authors.initials: RM
authors.lastname: Cooper-Dehoff
authors.forename: Eric
authors.initials: E
authors.lastname: Boerwinkle
authors.forename: Julie A
authors.initials: JA
authors.lastname: Johnson
authors.forename: Kent R
authors.initials: KR
authors.lastname: Bailey
mesh_terms: D000328:Adult; D000959:Antihypertensive Agents / Q000494:pharmacology*; D001262:Atenolol / Q000494:pharmacology; D001794:Blood Pressure / Q000187:drug effects* / Q000235:genetics*; D001795:Blood Pressure Determination / Q000379:methods*; D018660:Blood Pressure Monitoring, Ambulatory; D005260:Female; D006801:Humans; D006852:Hydrochlorothiazide / Q000494:pharmacology; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D020641:Polymorphism, Single Nucleotide / Q000235:genetics; D018401:Sample Size; D059629:Signal-To-Noise Ratio; D016896:Treatment Outcome
chemical_list: D000959:Antihypertensive Agents; D006852:Hydrochlorothiazide; D001262:Atenolol