Version 1
: Received: 2 May 2019 / Approved: 6 May 2019 / Online: 6 May 2019 (08:31:53 CEST)
How to cite:
Cunningham, P.N.; Chapman, A.B. Pharmacogenomics in Hypertension: Where We Stand Today. Preprints2019, 2019050035. https://doi.org/10.20944/preprints201905.0035.v1
Cunningham, P.N.; Chapman, A.B. Pharmacogenomics in Hypertension: Where We Stand Today. Preprints 2019, 2019050035. https://doi.org/10.20944/preprints201905.0035.v1
Cunningham, P.N.; Chapman, A.B. Pharmacogenomics in Hypertension: Where We Stand Today. Preprints2019, 2019050035. https://doi.org/10.20944/preprints201905.0035.v1
APA Style
Cunningham, P.N., & Chapman, A.B. (2019). Pharmacogenomics in Hypertension: Where We Stand Today. Preprints. https://doi.org/10.20944/preprints201905.0035.v1
Chicago/Turabian Style
Cunningham, P.N. and Arlene B. Chapman. 2019 "Pharmacogenomics in Hypertension: Where We Stand Today" Preprints. https://doi.org/10.20944/preprints201905.0035.v1
Abstract
Hypertension is a common and growing medical problem that leads to enormous cardiovascular and kidney disease worldwide. While many drugs exist to treat hypertension, there is large individual variation in how a given individual responds to different agents, which contributes to dismal rates of hypertension control. While demographic factors predict which drugs may work better in certain individuals, a great degree of this variation has a genetic basis. In recent years, genome wide association studies have begun to identify specific gene variants that predict drug response to particular agents. This review identifies the major genetic variants influencing antihypertensive response that have emerged from this growing body of work. For novel genetic variants without a previously known biologic basis in blood pressure, it is crucial to validate initial findings in subsequent studies. This information may eventually lead to a more personalized approach to hypertension management that will improve blood pressure control and patient outcomes. The integration of this large amount of data and its real world application will be highly challenging, but strategies to accomplish this are discussed.
Medicine and Pharmacology, Pharmacology and Toxicology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
