The Effect of Genetically Guided Mathematical Prediction and the Blood Pressure Response to Pharmacotherapy in Hypertension Patients.

IF 2.3 Q2 CARDIAC & CARDIOVASCULAR SYSTEMS
Clinical Medicine Insights. Cardiology Pub Date : 2019-05-03 eCollection Date: 2019-01-01 DOI:10.1177/1179546819845883
Eli F Kelley, Thomas P Olson, Timothy B Curry, Ryan Sprissler, Eric M Snyder
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引用次数: 1

Abstract

Purpose: The purpose of this study was to determine the effectiveness of a simple algorithm to mathematically predict a patients' response to blood pressure (BP) therapy using functional genes in the 3 major organ systems involved in hypertension.

Methods: Eighty-six patients with controlled hypertension completed 1 study visit consisting of a buccal swab collection, measurement of office BP, and a medical chart review for BP history. Genes in the analysis included 14 functional alleles in 11 genes. These genotypes were mathematically summed per organ system to determine whether a patient would likely respond to target therapy.

Results: Patients recommended to and taking a diuretic had significantly higher rates of control (<120/<80) than patients recommended but not taking this drug class (0.2 ± 0.1 and 0.03 ± 0.03, respectively). Furthermore, there was a difference between patients genetically recommended and taking an angiotensin receptor blocker (ARB) vs patients recommended but not taking an ARB for the lowest diastolic blood pressure (DBP) and mean arterial pressure (MAP) recorded in the past 2 years (DBP = 66.2 ± 2.9 and 75.3 ± 1.7, MAP = 82.3 ± 2.8 and 89.3 ± 1.5, respectively). In addition, there was a nonsignificant trend for greater reductions in ΔSBP, ΔDBP, and ΔMAP in patients on recommended drug class for beta-blockers, diuretics, and angiotensin II receptor blockers vs patients not on these classes.

Conclusion: The present study suggests that simple mathematical weighting of functional genotypes known to control BP may be ineffective in predicting control. This study demonstrates the need for a more complex, weighted, multigene algorithm to more accurately predict BP therapy response.

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遗传指导数学预测对高血压患者药物治疗血压反应的影响。
目的:本研究的目的是确定一种简单算法的有效性,该算法利用与高血压有关的3个主要器官系统的功能基因,从数学上预测患者对血压治疗的反应。方法:86例高血压患者完成了1次研究访视,包括口腔拭子采集、办公室血压测量和血压病史的病历回顾。分析的基因包括11个基因中的14个功能等位基因。这些基因型被数学地总结为每个器官系统,以确定患者是否可能对靶向治疗有反应。结果:推荐和服用利尿剂的患者控制率明显更高(结论:本研究表明,已知控制血压的功能基因型的简单数学加权可能无法预测控制。这项研究表明,需要一个更复杂的、加权的、多基因的算法来更准确地预测BP治疗的反应。
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来源期刊
Clinical Medicine Insights. Cardiology
Clinical Medicine Insights. Cardiology CARDIAC & CARDIOVASCULAR SYSTEMS-
CiteScore
5.20
自引率
3.30%
发文量
16
审稿时长
8 weeks
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