Evidence map›Paper›PMID 30090940›Full record

ArticleJAMA cardiology2018

Association of Interleukin 6 Receptor Variant With Cardiovascular Disease Effects of Interleukin 6 Receptor Blocking Therapy: A Phenome-Wide Association Study.

Tianxi Cai, Yichi Zhang, Yuk-Lam Ho, Nicholas Link, Jiehuan Sun, Jie Huang, Tianrun A Cai, Scott Damrauer, Yuri Ahuja, Jacqueline Honerlaw and 13 more

Open access · hybridAbstract read
In one paragraph

Article in JAMA cardiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
61citing papers in PubMed, 2 pooled it
11.8field-weighted citation impact, top 1% 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

61 citing papers in PubMed, 2 syntheses or guidelines pooled it, 108 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
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  12. IL-6 and Cardiovascular Risk: A Narrative Review.Current atherosclerosis reports · 2024
    Review
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  14. Article
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1 more citing papers are in PubMed but not listed here.

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

23 authors at 6 institutions in 1 country.

Tianxi CaiVeterans Affairs Boston Healthcare System, Boston, Massachusetts.
Yichi ZhangVeterans Affairs Boston Healthcare System, Boston, Massachusetts.
Yuk-Lam HoVeterans Affairs Boston Healthcare System, Boston, Massachusetts.
Nicholas LinkVeterans Affairs Boston Healthcare System, Boston, Massachusetts.
Jiehuan SunVeterans Affairs Boston Healthcare System, Boston, Massachusetts.
Jie HuangVeterans Affairs Boston Healthcare System, Boston, Massachusetts.
Tianrun A CaiVeterans Affairs Boston Healthcare System, Boston, Massachusetts.
Scott DamrauerCorporal Michael Crescenz Veterans Affairs Medical Center, Perlman School of Medicine, University of Pennsylvania, Philadelphia.
Yuri AhujaHarvard Medical School, Boston, Massachusetts.
Jacqueline HonerlawVeterans Affairs Boston Healthcare System, Boston, Massachusetts.
Jie HuangVeterans Affairs Boston Healthcare System, Boston, Massachusetts.
Lauren CostaVeterans Affairs Boston Healthcare System, Boston, Massachusetts.
Petra SchubertVeterans Affairs Boston Healthcare System, Boston, Massachusetts.
Chuan HongHarvard T. H. Chan School of Public Health, Boston, Massachusetts.
David GagnonVeterans Affairs Boston Healthcare System, Boston, Massachusetts.
Yan V SunEmory University Schools of Medicine and Public Health, Atlanta, Georgia.
J Michael GazianoVeterans Affairs Boston Healthcare System, Boston, Massachusetts.
Peter WilsonEmory University Schools of Medicine and Public Health, Atlanta, Georgia.
Kelly ChoVeterans Affairs Boston Healthcare System, Boston, Massachusetts.
Philip TsaoVeterans Affairs Palo Alto Health Care System, Palo Alto, California.
Christopher J O'DonnellVeterans Affairs Boston Healthcare System, Boston, Massachusetts.
Katherine P LiaoVeterans Affairs Boston Healthcare System, Boston, Massachusetts.
VA Million Veteran Program
VA Boston Healthcare System · USHarvard University · USAtlanta Public Schools · USBrigham and Women's Hospital · USStanford University · USUniversity of Pennsylvania · US

Funding

VERITY: Value and Evidence in Rheumatology using bioInformaTics, and advanced analYticsP30AR072577 · NIAMS · BRIGHAM AND WOMEN'S HOSPITAL · PI Katherine Phoenix Liao · 2017 to 2026
$9.8M
Lipids, Inflammation, and Cardiovascular Risk in Rheumatoid ArthritisR01HL127118 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI LIAO, KATHERINE PHOENIX · 2016 to 2020
$4.1M
Cardiovascular Disease Risk Factors, Prevalent Cardiovascular Disease, and Genetics in the Million Veteran ProgramI01BX003340 · VA · VETERANS HEALTH ADMINISTRATION · PI CHO, KELLY, WILSON, PETER WYMAN · 2017 to 2017
–
BLRD VA I01 BX003340Medical Research Council MC_PC_17228Medical Research Council MC_QA137853NHLBI NIH HHS R01 HL127118NIAMS NIH HHS P30 AR072577
6 · The paper itself

Abstract

Importance: Electronic health record (EHR) biobanks containing clinical and genomic data on large numbers of individuals have great potential to inform drug discovery. Individuals with interleukin 6 receptor (IL6R) single-nucleotide polymorphisms (SNPs) who are not receiving IL6R blocking therapy have biomarker profiles similar to those treated with IL6R blockers. This gene-drug pair provides an example to test whether associations of IL6R SNPs with a broad range of phenotypes can inform which diseases may benefit from treatment with IL6R blockade. Objective: To determine whether screening for clinical associations with the IL6R SNP in a phenome-wide association study (PheWAS) using EHR biobank data can identify drug effects from IL6R clinical trials. Design, Setting, and Participants: Diagnosis codes and routine laboratory measurements were extracted from the VA Million Veteran Program (MVP); diagnosis codes were mapped to phenotype groups using published PheWAS methods. A PheWAS was performed by fitting logistic regression models for testing associations of the IL6R SNPs with 1342 phenotype groups and by fitting linear regression models for testing associations of the IL6R SNP with 26 routine laboratory measurements. Significance was reported using a false discovery rate of 0.05 or less. Findings were replicated in 2 independent cohorts using UK Biobank and Vanderbilt University Biobank data. The Million Veteran Program included 332 799 US veterans; the UK Biobank, 408 455 individuals from the general population of the United Kingdom; and the Vanderbilt University Biobank, 13 835 patients from a tertiary care center. Exposures: IL6R SNPs (rs2228145; rs4129267). Main Outcomes and Measures: Phenotypes defined by International Classification of Diseases, Ninth Revision codes. Results: Of the 332 799 veterans included in the main cohort, 305 228 (91.7%) were men, and the mean (SD) age was 66.1 (13.6) years. The IL6R SNP was most strongly associated with a reduced risk of aortic aneurysm phenotypes (odds ratio, 0.87-0.90; 95% CI, 0.84-0.93) in the MVP. We observed known off-target effects of IL6R blockade from clinical trials (eg, higher hemoglobin level). The reduced risk for aortic aneurysms among those with the IL6R SNP in the MVP was replicated in the Vanderbilt University Biobank, and the reduced risk for coronary heart disease was replicated in the UK Biobank. Conclusions and Relevance: In this proof-of-concept study, we demonstrated application of the PheWAS using large EHR biobanks to inform drug effects. The findings of an association of the IL6R SNP with reduced risk for aortic aneurysms correspond with the newest indication for IL6R blockade, giant cell arteritis, of which a major complication is aortic aneurysm.

Indexed as

Polymorphism, Single NucleotideAgedAged, 80 and overAntibodies, Monoclonal, HumanizedAortic AneurysmCardiovascular DiseasesCurrent Procedural TerminologyFemaleGenome-Wide Association StudyHumansLinear ModelsMaleMiddle AgedPhenotypeProof of Concept StudyReceptors, Interleukin-6Antibodies, Monoclonal, HumanizedIL6R protein, humanReceptors, Interleukin-6sarilumabtocilizumab

Identifiers

PMID30090940
PMCPMC6233652
OpenAlexW2885197269

What OpenQuestion holds

Textmetadata
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.