Evidence map›Paper›PMID 25443111›Full record

ReviewJACC. Heart failure2014

Race, common genetic variation, and therapeutic response disparities in heart failure.

Mathew R Taylor, Albert Y Sun, Gordon Davis, Mona Fiuzat, Stephen B Liggett, Michael R Bristow

Open access · greenAbstract readReview
In one paragraph

Review in JACC. Heart failure, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
2.8field-weighted citation impact, top 9% 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

20 citing papers in PubMed, 1 synthesis or guideline pooled it, 47 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Review
  4. βmedRxiv : the preprint server for health sciences · 2025
    Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Practical Pharmacogenomic Approaches to Heart Failure Therapeutics.Current treatment options in cardiovascular medicine · 2016
    Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Cardiac dyssynchrony and response to cardiac resynchronisation therapy in heart failure: can genetic predisposition play a role?Netherlands heart journal : monthly journal of the Netherlands Society of Cardiology and the Netherlands Heart Foundation · 2016
    Article
  19. Article
  20. 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

6 authors at 4 institutions in 1 country.

Mathew R TaylorSection of Pharmacogenetics, University of Colorado Cardiovascular Institute, Aurora, Colorado.
Albert Y SunDivisions of Cardiology and Clinical Pharmacology, Duke University Medical Center, Durham, North Carolina.
Gordon DavisARCA biopharma, Westminster, Colorado.
Mona FiuzatDivisions of Cardiology and Clinical Pharmacology, Duke University Medical Center, Durham, North Carolina.
Stephen B LiggettCenter for Personalized Medicine and Genomics, University of South Florida, Morsani College of Medicine, Tampa, Florida.
Michael R BristowSection of Pharmacogenetics, University of Colorado Cardiovascular Institute, Aurora, Colorado; ARCA biopharma, Westminster, Colorado. Electronic address: michael.bristow@ucdenver.edu.
ARCA Biopharma (United States) · USDuke Medical Center · USUniversity of Colorado Denver · USUniversity of South Florida · US

Funding

Genetic-Adrenergic Interactions in Myocardial FailureR01HL048013 · NHLBI · UNIVERSITY OF COLORADO DENVER · PI BRISTOW, MICHAEL R. · 1993 to 2007
$4.5M
Whole genome DNA sequencing to identify novel genes in dilated cardiomyopathyR01HL109209 · NHLBI · UNIVERSITY OF COLORADO DENVER · PI TAYLOR, MATTHEW R · 2012 to 2016
$2.1M
Cardiomyocyte phenotype and mechanotransduction in Filamin C gene variants causing arrhythmogenic cardiomyopathyR01HL147064 · NHLBI · UNIVERSITY OF COLORADO DENVER · PI MESTRONI, LUISA, TAYLOR, MATTHEW R · 2020 to 2023
$2.1M
NHLBI NIH HHS 2R01HL48013NHLBI NIH HHS R01 HL048013NHLBI NIH HHS R01 HL109209NHLBI NIH HHS R01 HL147064NHLBI NIH HHS R01 HL7701
6 · The paper itself

Abstract

Because of its comparatively recent evolution, Homo sapiens exhibit relatively little within-species genomic diversity. However, because of genome size, a proportionately small amount of variation creates ample opportunities for both rare mutations that may cause disease as well as more common genetic variations that may be important in disease modification or pharmacogenetics. Primarily because of the East African origin of modern humans, individuals of African ancestry (AA) exhibit greater degrees of genetic diversity than more recently established populations, such as those of European ancestry (EA) or Asian ancestry. Those population effects extend to differences in frequency of common gene variants that may be important in heart failure natural history or therapy. For cell-signaling mechanisms important in heart failure, we review and present new data for genetic variation between AA and EA populations. Data indicate that: 1) neurohormonal signaling mechanisms frequently (16 of the 19 investigated polymorphisms) exhibit racial differences in the allele frequencies of variants comprising key constituents; 2) some of these differences in allele frequency may differentially affect the natural history of heart failure in AA compared with EA individuals; and 3) in many cases, these differences likely play a role in observed racial differences in drug or device response.

Indexed as

Adrenergic beta-AntagonistsGene FrequencyGenetic VariationGenotypeHeart FailureHumansPolymorphism, Single NucleotideRacial GroupsReceptors, AdrenergicSignal TransductionTreatment OutcomeAdrenergic beta-AntagonistsReceptors, Adrenergicgenetic polymorphismsheart failurepharmacogeneticsracial ancestry

Identifiers

PMID25443111
PMCPMC4302116
OpenAlexW2024891255

What OpenQuestion 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 OpenQuestion graph.