Analyzing How Genetics May Affect Response to High Blood Pressure Medications

March 2, 2014 updated by: University of Alabama at Birmingham

GenHAT - Genetics of Hypertension Associated Treatments - Ancillary to ALLHAT

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.

Study Overview

Detailed Description

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.

Study Type

Observational

Enrollment (Actual)

37939

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

    • Minnesota
      • Minneapolis, Minnesota, United States, 55455
        • University of Minnesota
    • Texas
      • Houston, Texas, United States, 77030
        • University of Texas Houston

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

55 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

Yes

Genders Eligible for Study

All

Sampling Method

Non-Probability Sample

Study Population

The study population samples will be taken from adults who are high risk for high blood pressure in the ALLHAT study, which included a randomized trial of the four high blood pressure drugs chlorthalidone, amlodipine, lisinopril, and doxazosin.

Description

Inclusion Criteria:

  • Participant in the ALLHAT study

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
1
Adults with a high risk for high blood pressure from the ALLHAT study

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Time Frame
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
Measured at completion of genetic analysis

Secondary Outcome Measures

Outcome Measure
Time Frame
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
Measured at completion of genetic analysis

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Investigators

  • Principal Investigator: Donna K. Arnett, PhD, University of Alabama at Birmingham

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start

September 1, 2000

Primary Completion (Actual)

May 1, 2004

Study Completion (Actual)

May 1, 2004

Study Registration Dates

First Submitted

November 21, 2007

First Submitted That Met QC Criteria

November 21, 2007

First Posted (Estimate)

November 26, 2007

Study Record Updates

Last Update Posted (Estimate)

March 4, 2014

Last Update Submitted That Met QC Criteria

March 2, 2014

Last Verified

January 1, 2008

More Information

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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