Evidence map›Paper›PMID 24418963›Full record

ArticleThe pharmacogenomics journal2014

Gene-based association identifies SPATA13-AS1 as a pharmacogenomic predictor of inhaled short-acting beta-agonist response in multiple population groups.

B Padhukasahasram, J J Yang, A M Levin, M Yang, E G Burchard, R Kumar, P-Y Kwok, M A Seibold, D E Lanfear, L K Williams

Abstract read
In one paragraph

Article in The pharmacogenomics journal, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 4 pooled it
–field-weighted citation impact
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

15 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Trial
  6. Review
  7. Review
  8. Article
  9. Article
  10. Article
  11. How does race and ethnicity effect the precision treatment of asthma?Expert review of precision medicine and drug development · 2019
    Article
  12. Whole-Genome Sequencing of Pharmacogenetic Drug Response in Racially Diverse Children with Asthma.American journal of respiratory and critical care medicine · 2018
    Article
  13. Asthma Pharmacogenomics: 2015 Update.Current allergy and asthma reports · 2015
    Review
  14. Article
  15. 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

10 authors.

B PadhukasahasramCenter for Health Policy and Health Services Research, Henry Ford Health System, Detroit, MI, USA.
J J YangDepartment of Public Health Sciences, Henry Ford Health System, Detroit, MI, USA.
A M LevinDepartment of Public Health Sciences, Henry Ford Health System, Detroit, MI, USA.
M YangCenter for Health Policy and Health Services Research, Henry Ford Health System, Detroit, MI, USA.
E G Burchard1] Department of Medicine, University of California San Francisco, San Francisco, CA, USA [2] Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA.
R KumarDepartment of Pediatrics, The Ann and Robert H. Lurie Children's Hospital of Chicago, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
P-Y Kwok1] Department of Dermatology, University of California San Francisco, San Francisco, CA, USA [2] Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA, USA.
M A Seibold1] Integrated Center for Genes, Environment, and Health, National Jewish Health, Denver, CO, Colorado, USA [2] Department of Pediatrics, National Jewish Health, Denver, CO, USA [3] Division of Pulmonary Sciences and Critical Care Medicine, Department of Medicine, University of Colorado Denver, Denver, CO, USA.
D E Lanfear1] Center for Health Policy and Health Services Research, Henry Ford Health System, Detroit, MI, USA [2] Department of Medicine, Henry Ford Health System, Detroit, MI, USA.
L K Williams1] Center for Health Policy and Health Services Research, Henry Ford Health System, Detroit, MI, USA [2] Department of Medicine, Henry Ford Health System, Detroit, MI, USA.

Funding

Understanding Asthma EndotypesU19AI077439 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI PRESCOTT G WOODRUFF · 2008 to 2026
$41.1M
The EVE Asthma Genetics Consortium: Building Upon GWASRC2HL101651 · NHLBI · UNIVERSITY OF CHICAGO · PI NICOLAE, DAN LIVIU, OBER, CAROLE · 2009 to 2010
$7.4M
Gene-environments and Admixture in Latino Asthmatics (GALA 2)R01ES015794 · NIEHS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI BURCHARD, ESTEBAN GONZALEZ · 2008 to 2012
$5.4M
PHARMACOGENOMICS OF INHALED CORTICOSTEROID RESPONSIVENESS IN PATIENTS WITH ASTHMAR01AI079139 · NIAID · HENRY FORD HEALTH SYSTEM · PI WILLIAMS, KEOKI · 2009 to 2013
$3.9M
Whole Genome Analyses for Asthma in Latino PopulationsR01HL088133 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI BURCHARD, ESTEBAN GONZALEZ · 2008 to 2012
$3.8M
Impact of Race and Genetic Factors on Beta-blocker Effectiveness in Heart FailureR01HL103871 · NHLBI · HENRY FORD HEALTH SYSTEM · PI LANFEAR, DAVID E · 2011 to 2015
$3.5M
Mechanism of Endotoxin's Effect On Allergy RiskR01AI061774 · NIAID · HENRY FORD HEALTH SYSTEM · PI WILLIAMS, KEOKI · 2004 to 2008
$2.9M
VALIDATION OF ADHERENCE DATA--USE IN CLINICAL PRACTICER01DK064695 · NIDDK · HENRY FORD HEALTH SYSTEM · PI WILLIAMS, KEOKI · 2003 to 2010
$2.7M
Case-control Association Studies and Genetic ConfoundingR01HL078885 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI BURCHARD, ESTEBAN GONZALEZ · 2005 to 2009
$1.9M
USING INFORMATION TECHNOLOGY TO IMPROVE ASTHMA ADHERENCER01HL079055 · NHLBI · HENRY FORD HEALTH SYSTEM · PI WILLIAMS, KEOKI · 2005 to 2008
$1.4M
Role of Prenatal Factors and Gene-Environment Interactions in Recurrent WheezingK23HL093023 · NHLBI · LURIE CHILDREN'S HOSPITAL OF CHICAGO · PI KUMAR, RAJESH · 2008 to 2012
$672k
NHLBI NIH HHS 5RC2HL101651NHLBI NIH HHS HL078885NHLBI NIH HHS HL079055NHLBI NIH HHS HL088133NHLBI NIH HHS K23 HL093023NHLBI NIH HHS K23HL093023NHLBI NIH HHS R01 HL078885NHLBI NIH HHS R01 HL079055NHLBI NIH HHS R01 HL088133NHLBI NIH HHS R01 HL103871NHLBI NIH HHS RC2 HL101651NIAID NIH HHS AI061774NIAID NIH HHS AI077439NIAID NIH HHS AI079139NIAID NIH HHS R01 AI061774NIAID NIH HHS R01 AI079139NIAID NIH HHS U19 AI077439NIDDK NIH HHS DK064695NIDDK NIH HHS R01 DK064695NIEHS NIH HHS ES015794NIEHS NIH HHS R01 ES015794
6 · The paper itself

Abstract

Inhaled short-acting beta-agonist (SABA) medication is commonly used in asthma patients to rapidly reverse airway obstruction and improve acute symptoms. We performed a genome-wide association study of SABA medication response using gene-based association tests. A linear mixed model approach was first used for single-nucleotide polymorphism associations, and the results were later combined using GATES to generate gene-based associations. Our results identified SPATA13-AS1 as being significantly associated with SABA bronchodilator response in 328 healthy African Americans. In replication, this gene was associated with SABA response among the two separate groups of African Americans with asthma (n=1073, P=0.011 and n=1968, P=0.014), 149 healthy African Americans (P=0.003) and 556 European Americans with asthma (P=0.041). SPATA13-AS1 was also associated with longitudinal SABA medication usage in the two separate groups of African Americans with asthma (n=658, P=0.047 and n=1968, P=0.025). Future studies are needed to delineate the precise mechanism by which SPATA13-AS1 may influence SABA response.

Indexed as

Genome-Wide Association StudyPharmacogeneticsPolymorphism, Single NucleotideAdministration, InhalationAdrenergic beta-AgonistsAdultAsthmaBlack or African AmericanFemaleGuanine Nucleotide Exchange FactorsHumansMaleMiddle AgedPopulation GroupsAdrenergic beta-AgonistsGuanine Nucleotide Exchange FactorsSPATA13 protein, human

Identifiers

PMID24418963
PMCPMC4098013

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Registered trials

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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.