Evidence map›Paper›PMID 31090079›Full record

Trial reportJournal of clinical pharmacology2019

β

Mohamed H Shahin, Nihal El Rouby, Daniela J Conrado, Daniel Gonzalez, Yan Gong, Maximilian T Lobmeyer, Amber L Beitelshees, Eric Boerwinkle, John G Gums, Arlene Chapman and 4 more

Open access · greenAbstract readClinical Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Journal of clinical pharmacology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.8field-weighted citation impact, top 25% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 11 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors at 8 institutions in 1 country.

Mohamed H ShahinDepartment of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, FL, USA.
Nihal El RoubyDepartment of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, FL, USA.
Daniela J ConradoDepartment of Pharmaceutics, College of Pharmacy, University of Florida, Gainesville, FL, USA.
Daniel GonzalezDivision of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, USA.
Yan GongDepartment of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, FL, USA.
Maximilian T LobmeyerDepartment of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, FL, USA.
Amber L BeitelsheesDepartment of Medicine, University of Maryland, Baltimore, MD, USA.
Eric BoerwinkleHuman Genetics Center and Institute of Molecular Medicine, University of Texas Health Science Center, Houston, TX, USA.
John G GumsDepartment of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, FL, USA.
Arlene ChapmanDepartment of Medicine, The University of Chicago, Chicago, IL, USA.
Stephen T TurnerDivision of Nephrology and Hypertension, Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA.
Carl J PepineDivision of Cardiovascular Medicine, Department of Medicine, University of Florida, College of Medicine, Gainesville, FL, USA.
Rhonda M Cooper-DeHoffDepartment of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, FL, USA.
Julie A JohnsonDepartment of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, FL, USA.
University of Florida · USAmerican Association of Colleges of Pharmacy · USFlorida College · USMayo Clinic in Arizona · USThe University of Texas Health Science Center at Houston · USUniversity of Chicago · USUniversity of Maryland, Baltimore · USUniversity of North Carolina at Chapel Hill · US

Funding

Mayo Clinic Center for Translational Science ActivitiesUL1TR000135 · NCATS · MAYO CLINIC ROCHESTER · PI KHOSLA, SUNDEEP · 2012 to 2015
$41.2M
Atlanta Clinical and Translational Science Institute (ACTSI) RenewalUL1TR000454 · NCATS · EMORY UNIVERSITY · PI STEPHENS, DAVID S · 2012 to 2016
$25.8M
Pharmacogenomic Evaluation of Antihypertensive ResponsesU01GM074492 · NIGMS · UNIVERSITY OF FLORIDA · PI JOHNSON, JULIE A. · 2005 to 2014
$20.7M
UF Clinical and Translational Science AwardUL1TR000064 · NCATS · UNIVERSITY OF FLORIDA · PI NELSON, DAVID R · 2012 to 2014
$12.2M
Hypertension PharmacogeneticsR01HL074730 · NHLBI · UNIVERSITY OF FLORIDA · PI JOHNSON, JULIE A. · 2003 to 2006
$3.4M
Use of Physiologically-Based PK/PD Models to Streamline Drug ApprovalsK23HD083465 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI GONZALEZ, DANIEL · 2015 to 2019
$727k
NCATS NIH HHS UL1 TR000064NCATS NIH HHS UL1 TR000135NCATS NIH HHS UL1 TR000454NHLBI NIH HHS R01 HL074730NICHD NIH HHS K23 HD083465NIGMS NIH HHS U01 GM074492
6 · The paper itself

Abstract

β-Blockers' heart rate (HR)-lowering effect is an important determinant of the effectiveness for this class of drugs, yet it is variable among β-blocker-treated patients. To date, genetic studies have revealed several genetic signals associated with HR response to β-blockers. However, these genetic signals have not been consistently replicated across multiple independent cohorts. Here we sought to use data from 3 hypertension clinical trials to validate single-nucleotide polymorphisms (SNPs) previously associated with the HR response to β-blockers. Using linear regression analysis, we investigated the effects of 6 SNPs in 3 genes, including ADRB1, ADRB2, and GNB3, relative to the HR response following β-blocker used in the PEAR (n = 757), PEAR-2 (n = 368), and INVEST (n = 1401) trials, adjusting for baseline HR, age, sex, and ancestry. Atenolol was used in PEAR and INVEST, and metoprolol was used in PEAR-2. We found that rs1042714 and rs1042713 in ADRB2 were significantly associated with HR response to both β-blockers in whites (rs1042714 C-allele carriers, meta-analysis β = -0.95 beats per minute [bpm], meta-analysis P = 3×10

Indexed as

Adrenergic beta-AntagonistsAllelesAtenololBlack PeopleFemaleGenotypeHeart RateHeterotrimeric GTP-Binding ProteinsHumansHypertensionMaleMetoprololMiddle AgedPolymorphism, Single NucleotideReceptors, Adrenergic, beta-1Receptors, Adrenergic, beta-2ADRB1 protein, humanADRB2 protein, humanAdrenergic beta-AntagonistsAtenololGNB3 protein, humanHeterotrimeric GTP-Binding ProteinsMetoprololReceptors, Adrenergic, beta-1Receptors, Adrenergic, beta-2atenololheart ratemetoprololPharmacogeneticsβ-blockers

Identifiers

PMID31090079
PMCPMC6773496
OpenAlexW2946126771

What Socratic holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.