Literature DB >> 33168928

Rapid response to the alpha-1 adrenergic agent phenylephrine in the perioperative period is impacted by genomics and ancestry.

Stephane Wenric1, Janina M Jeff1, Thomas Joseph2, Muh-Ching Yee3,4, Gillian M Belbin1,5, Aniwaa Owusu Obeng5,6,7,8, Stephen B Ellis6, Erwin P Bottinger5,9, Omri Gottesman6, Matthew A Levin8,10, Eimear E Kenny11,12,13.   

Abstract

The emergence of genomic data in biobanks and health systems offers new ways to derive medically important phenotypes, including acute phenotypes occurring during inpatient clinical care. Here we study the genetic underpinnings of the rapid response to phenylephrine, an α1-adrenergic receptor agonist commonly used to treat hypotension during anesthesia and surgery. We quantified this response by extracting blood pressure (BP) measurements 5 min before and after the administration of phenylephrine. Based on this derived phenotype, we show that systematic differences exist between self-reported ancestry groups: European-Americans (EA; n = 1387) have a significantly higher systolic response to phenylephrine than African-Americans (AA; n = 1217) and Hispanic/Latinos (HA; n = 1713) (31.3% increase, p value < 6e-08 and 22.9% increase, p value < 5e-05 respectively), after adjusting for genetic ancestry, demographics, and relevant clinical covariates. We performed a genome-wide association study to investigate genetic factors underlying individual differences in this derived phenotype. We discovered genome-wide significant association signals in loci and genes previously associated with BP measured in ambulatory settings, and a general enrichment of association in these genes. Finally, we discovered two low frequency variants, present at ~1% in EAs and AAs, respectively, where patients carrying one copy of these variants show no phenylephrine response. This work demonstrates our ability to derive a quantitative phenotype suited for comparative statistics and genome-wide association studies from dense clinical and physiological measures captured for managing patients during surgery. We identify genetic variants underlying non response to phenylephrine, with implications for preemptive pharmacogenomic screening to improve safety during surgery.

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Year:  2020        PMID: 33168928      PMCID: PMC7997806          DOI: 10.1038/s41397-020-00194-5

Source DB:  PubMed          Journal:  Pharmacogenomics J        ISSN: 1470-269X            Impact factor:   3.245


  51 in total

1.  Hospital stay and mortality are increased in patients having a "triple low" of low blood pressure, low bispectral index, and low minimum alveolar concentration of volatile anesthesia.

Authors:  Daniel I Sessler; Jeffrey C Sigl; Scott D Kelley; Nassib G Chamoun; Paul J Manberg; Leif Saager; Andrea Kurz; Scott Greenwald
Journal:  Anesthesiology       Date:  2012-06       Impact factor: 7.892

2.  Anesthetic management and one-year mortality after noncardiac surgery.

Authors:  Terri G Monk; Vikas Saini; B Craig Weldon; Jeffrey C Sigl
Journal:  Anesth Analg       Date:  2005-01       Impact factor: 5.108

3.  Relationship between intraoperative mean arterial pressure and clinical outcomes after noncardiac surgery: toward an empirical definition of hypotension.

Authors:  Michael Walsh; Philip J Devereaux; Amit X Garg; Andrea Kurz; Alparslan Turan; Reitze N Rodseth; Jacek Cywinski; Lehana Thabane; Daniel I Sessler
Journal:  Anesthesiology       Date:  2013-09       Impact factor: 7.892

4.  Intraoperative hypotension and 1-year mortality after noncardiac surgery.

Authors:  Jilles B Bijker; Wilton A van Klei; Yvonne Vergouwe; Douglas J Eleveld; Leo van Wolfswinkel; Karel G M Moons; Cor J Kalkman
Journal:  Anesthesiology       Date:  2009-12       Impact factor: 7.892

Review 5.  Using electronic health records to drive discovery in disease genomics.

Authors:  Isaac S Kohane
Journal:  Nat Rev Genet       Date:  2011-05-18       Impact factor: 53.242

6.  Intraoperative arterial blood pressure lability is associated with improved 30 day survival.

Authors:  M A Levin; G W Fischer; H-M Lin; P J McCormick; M Krol; D L Reich
Journal:  Br J Anaesth       Date:  2015-09-22       Impact factor: 9.166

7.  Intraoperative blood pressure. What patterns identify patients at risk for postoperative complications?

Authors:  M E Charlson; C R MacKenzie; J P Gold; K L Ales; M Topkins; G T Shires
Journal:  Ann Surg       Date:  1990-11       Impact factor: 12.969

8.  Different methods of modelling intraoperative hypotension and their association with postoperative complications in patients undergoing non-cardiac surgery.

Authors:  L M Vernooij; W A van Klei; M Machina; W Pasma; W S Beattie; L M Peelen
Journal:  Br J Anaesth       Date:  2018-03-21       Impact factor: 9.166

Review 9.  Personalized Medicine and the Power of Electronic Health Records.

Authors:  Noura S Abul-Husn; Eimear E Kenny
Journal:  Cell       Date:  2019-03-21       Impact factor: 41.582

10.  Biobanks and electronic medical records: enabling cost-effective research.

Authors:  Erica Bowton; Julie R Field; Sunny Wang; Jonathan S Schildcrout; Sara L Van Driest; Jessica T Delaney; James Cowan; Peter Weeke; Jonathan D Mosley; Quinn S Wells; Jason H Karnes; Christian Shaffer; Josh F Peterson; Joshua C Denny; Dan M Roden; Jill M Pulley
Journal:  Sci Transl Med       Date:  2014-04-30       Impact factor: 17.956

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