Evidence map›Paper›PMID 28772032›Full record

ArticleESC heart failure2017

Differentiating heart failure phenotypes using sex-specific transcriptomic and proteomic biomarker panels.

Mustafa Toma, George J Mak, Virginia Chen, Zsuzsanna Hollander, Casey P Shannon, Karen K Y Lam, Raymond T Ng, Scott J Tebbutt, Janet E Wilson-McManus, Andrew Ignaszewski and 6 more

Registry-linked trialAbstract read
In one paragraph

Article in ESC heart failure, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03575910 (HEARTBiT), which is not on this map. Cited by 22 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 2 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.

NCT03575910 completednot on this mapstarted 2018, after this paper: background citation

HEARTBiT: A Novel Multi-Marker Blood Test for Management of Acute Cardiac Allograft Rejection

TypeobservationalSponsorUniversity of British ColumbiaRan2018 to 2026Enrolled196ConditionsHeart Transplant Failure and Rejection, Heart Failure, Heart Diseases, Heart Failure,Congestive
3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  7. Using Omics to Identify Novel Therapeutic Targets in Heart Failure.Circulation. Genomic and precision medicine · 2024
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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

16 authors.

Mustafa TomaDivision of Cardiology, University of British Columbia, Vancouver, Canada.
George J MakCentre of Excellence for Prevention of Organ Failure (PROOF Centre), Vancouver, Canada.
Virginia ChenCentre of Excellence for Prevention of Organ Failure (PROOF Centre), Vancouver, Canada.
Zsuzsanna HollanderCentre of Excellence for Prevention of Organ Failure (PROOF Centre), Vancouver, Canada.
Casey P ShannonCentre of Excellence for Prevention of Organ Failure (PROOF Centre), Vancouver, Canada.
Karen K Y LamCentre of Excellence for Prevention of Organ Failure (PROOF Centre), Vancouver, Canada.
Raymond T NgCentre of Excellence for Prevention of Organ Failure (PROOF Centre), Vancouver, Canada.
Scott J TebbuttCentre of Excellence for Prevention of Organ Failure (PROOF Centre), Vancouver, Canada.
Janet E Wilson-McManusCentre of Excellence for Prevention of Organ Failure (PROOF Centre), Vancouver, Canada.
Andrew IgnaszewskiDivision of Cardiology, University of British Columbia, Vancouver, Canada.
Todd AndersonDepartment of Cardiac Sciences, University of Calgary, Faculty of Medicine Health Sciences Centre, Calgary, Canada.
Jason R B DyckDepartments of Pediatrics and Pharmacology, University of Alberta, Edmonton, Canada.
Jonathan HowlettDepartment of Cardiac Sciences, University of Calgary, Faculty of Medicine Health Sciences Centre, Calgary, Canada.
Justin EzekowitzDivision of Cardiology, University of Alberta, Edmonton, Canada.
Bruce M McManusCentre of Excellence for Prevention of Organ Failure (PROOF Centre), Vancouver, Canada.
Gavin Y OuditMazankowski Alberta Heart Institute, Edmonton, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsHeart failure with preserved ejection fraction (HFpEF) accounts for 30-50% of patients with heart failure (HF). A major obstacle in HF management is the difficulty in differentiating between HFpEF and heart failure with reduced ejection fraction (HFrEF) using conventional clinical and laboratory investigations. The aim of this study is to develop robust transcriptomic and proteomic biomarker signatures that can differentiate HFpEF from HFrEF. METHODS AND

resultsA total of 210 HF patients were recruited in participating institutions from the Alberta HEART study. An expert clinical adjudicating panel differentiated between patients with HFpEF and HFrEF. The discovery cohort consisted of 61 patients, and the replication cohort consisted of 70 patients. Transcriptomic and proteomic data were analysed to find panels of differentiating HFpEF from HFrEF. In the discovery cohort, a 22-transcript panel was found to differentiate HFpEF from HFrEF in male patients with a cross-validation AUC of 0.74, as compared with 0.70 for N-terminal pro-B-type natriuretic peptide (NT-proBNP) in those same patients. An ensemble of the transcript panel and NT-pro-BNP yielded a cross-validation AUC of 0.80. This performance improvement was also observed in the replication cohort. An ensemble of the transcriptomic panel with NT-proBNP produced a replication AUC of 0.90, as compared with 0.74 for NT-proBNP alone and 0.73 for the transcriptomic panel.

conclusionsWe have identified a male-specific transcriptomic biomarker panel that can differentiate between HFpEF and HFrEF. These biosignatures could be further replicated on other patients and potentially be developed into a blood test for better management of HF patients.

Indexed as

BiomarkersHeart failureHeart failure with preserved ejection fractionHeart failure with reduced ejection fractionProteomicsTranscriptomics

Identifiers

PMID28772032
PMCPMC5542716

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Registered trials

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.