Evidence map›Paper›PMID 31278493›Full record

ArticleJournal of cardiovascular translational research2019

Application of Proteomics Profiling for Biomarker Discovery in Hypertrophic Cardiomyopathy.

Yuichi J Shimada, Kohei Hasegawa, Stephanie M Kochav, Pouya Mohajer, Jeeyoun Jung, Mathew S Maurer, Muredach P Reilly, Michael A Fifer

Open access · greenAbstract read
In one paragraph

Article in Journal of cardiovascular translational research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
1.0field-weighted citation impact, top 24% 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

24 citing papers in PubMed, 29 citations in OpenAlex.

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  8. Prediction of new-onset atrial fibrillation in patients with hypertrophic cardiomyopathy using plasma proteomics profiling.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2024
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  19. Review
  20. Endotyping in Heart Failure - Identifying Mechanistically Meaningful Subtypes of Disease.Circulation journal : official journal of the Japanese Circulation Society · 2021
    Review
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

8 authors at 3 institutions in 2 countries.

Yuichi J ShimadaCardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA. ys3053@cumc.columbia.edu.ORCID 0000-0002-3494-307X
Kohei HasegawaDepartment of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Stephanie M KochavDivision of Cardiology, Department of Medicine, Columbia University Medical Center, 622 West 168th Street, PH 3-342, New York, NY, 10032, USA.
Pouya MohajerCardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Jeeyoun JungClinical Medicine Division, Korea Institute of Oriental Medicine, Daejeon, Republic of Korea.
Mathew S MaurerDivision of Cardiology, Department of Medicine, Columbia University Medical Center, 622 West 168th Street, PH 3-342, New York, NY, 10032, USA.
Muredach P ReillyDivision of Cardiology, Department of Medicine, Columbia University Medical Center, 622 West 168th Street, PH 3-342, New York, NY, 10032, USA.
Michael A FiferCardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Harvard University · USColumbia University Irving Medical Center · USKorea Institute of Oriental Medicine · KR

Funding

Clinical and Translational Science AwardUL1TR001873 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI REILLY, MUREDACH P · 2016 to 2025
$99.0M
American Heart Association-American Stroke Association 18CDA34110245NCATS NIH HHS UL1 TR001873
6 · The paper itself

Abstract

High-throughput proteomics profiling has never been applied to discover biomarkers in patients with hypertrophic cardiomyopathy (HCM). The objective was to identify plasma protein biomarkers that can distinguish HCM from controls. We performed a case-control study of patients with HCM (n = 15) and controls (n = 22). We carried out plasma proteomics profiling of 1129 proteins using the SOMAscan assay. We used the sparse partial least squares discriminant analysis to identify 50 most discriminant proteins. We also determined the area under the curve (AUC) of the receiver operating characteristic curve using the Monte Carlo cross validation with balanced subsampling. The average AUC was 0.94 (95% confidence interval, 0.82-1.00) and the discriminative accuracy was 89%. In HCM, 13 out of the 50 proteins correlated with troponin I and 12 with New York Heart Association class. Proteomics profiling can be used to elucidate protein biomarkers that distinguish HCM from controls.

Indexed as

ProteomicsAgedBiomarkersBlood ProteinsCardiomyopathy, HypertrophicCase-Control StudiesFemaleHigh-Throughput Screening AssaysHumansLeast-Squares AnalysisMaleMiddle AgedPredictive Value of TestsProtein Interaction MapsBiomarkersBlood ProteinsBiomarker discoveryHypertrophic cardiomyopathyProteomics

Identifiers

PMID31278493
PMCPMC7102897
OpenAlexW2954064471

What OpenQuestion holds

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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.