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OpenTrials
Completed

NCT Number: NCT00563901

Analyzing How Genetics May Affect Response to High Blood Pressure Medications

High blood pressure is one of the most common health problems in the United States. There are many medications to treat high blood pressure, but there is a large variance in how people respond to these medications. It is believed that genetic variations may contribute to the inconsistent treatment response. This study will use genetic analysis to determine whether particular genes interact with high blood pressure medications to modify the risk of certain cardiovascular diseases.

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Key information

About this study

High blood pressure affects nearly one in three individuals in the Unites States. There are many factors that can cause high blood pressure, including family history and genetic traits, kidney disease, stress, diabetes, and diet. If left untreated, high blood pressure can increase one's risk for coronary heart disease (CHD), stroke, heart attack, and heart failure. While high blood pressure can be managed with medication, people receiving medication treatment for high blood pressure are still variably at risk for CHD and other cardiovascular conditions. This risk variation may stem from varying drug reactions that are likely due to genetics. This study will use genetic analysis to determine whether particular genes interact with high blood pressure medications to modify the risk of certain cardiovascular diseases.

This is a continuation study to the antihypertensive and lipid-lowering treatment to prevent heart attack trial (ALLHAT), which included a randomized trial of the four high blood pressure drugs chlorthalidone, amlodipine, lisinopril, and doxazosin. Using samples from ALLHAT participants, this study will analyze the interactions of candidate gene pathways of relevance with medications from the ALLHAT study. Researchers will examine both single DNA building blocks and multiple genes in the candidate gene pathways and determine whether their interaction with the ALLHAT drugs modifies the risk of cardiovascular outcomes. Researchers will perform genetic analysis on 96 genetic markers using structured association testing (SAT) and false discovery rate (FDR) methods. These methods will control for population stratification and multiple testing. Finally, the study will establish a mechanism for other researchers to continue further analysis of the genetic variants examined in this study.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Participant in the ALLHAT study

Treatment and study plan

Primary outcomes

  1. Candidate genes that interact with ALLHAT high blood pressure medications to modify risk of other cardiovascular conditions

    Time frame: Measured at completion of genetic analysis

Secondary outcomes

  1. Within selected candidate genes, effect of multiple gene interactions with high blood pressure medications in modifying risk of other cardiovascular conditions

    Time frame: Measured at completion of genetic analysis

Sponsors and collaborators

Lead sponsor

University of Alabama at Birmingham

Other

Collaborators

  • National Heart, Lung, and Blood Institute (NHLBI)
  • University of Minnesota
  • University of Texas

Registry information

Official study title

GenHAT - Genetics of Hypertension Associated Treatments - Ancillary to ALLHAT

Important dates

Study start
2000
Primary completion
2004
Study completion
2004
First posted
Nov 26, 2007
Registry last updated
Mar 4, 2014

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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