Relationship between a Weighted Multi-Gene Algorithm and Blood Pressure Controlin Hypertension

Autor: Danielle M. Walla, Eric M. Snyder, Monica K. Akre, Thomas P. Olson, Pamela Phelps, Emma K. Bulock, Eli F. Kelley, Ryan Sprissler, Jerad J. Simmons, Audrie Ayres, Jennifer K Ross
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Journal of Clinical Medicine
Volume 8
Issue 3
Journal of Clinical Medicine, Vol 8, Iss 3, p 289 (2019)
ISSN: 2077-0383
DOI: 10.3390/jcm8030289
Popis: Hypertension (HTN) is a complex disease with interactions among multiple organ systems, including the heart, vasculature, and kidney with a strong heritable component. Despite the multifactorial nature of HTN, no clinical guidelines utilize a multi-gene approach to guide blood pressure (BP) therapy. Non-smokers with a family history of HTN were included in the analysis (n = 384
age = 61.0 ±
0.9, 11% non-white). A total of 17 functional genotypes were weighted according to the previous effect size in the literature and entered into an algorithm. Pharmacotherapy was ranked from 1&ndash
4 as most to least likely to respond based on the algorithmic assessment of individual patient&rsquo
s genotypes. Three-years of data were assessed at six-month intervals for BP and medication history. There was no difference in BP at diagnosis between groups matching the top drug recommendation using the multi-gene weighted algorithm (n = 92) vs. those who did not match (n = 292). However, from diagnosis to nadir, patients who matched the primary recommendation had a significantly greater drop in BP when compared to patients who did not. Further, the difference between diagnosis to current 1-year average BP was lower in the group that matched the top recommendation. These data suggest an association between a weighted multi-gene algorithm on the BP response to pharmacotherapy.
Databáze: OpenAIRE
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