Evidence map›Paper›PMID 25528681›Full record

ArticleGenomics2015

RNA-Seq identifies novel myocardial gene expression signatures of heart failure.

Yichuan Liu, Michael Morley, Jeffrey Brandimarto, Sridhar Hannenhalli, Yu Hu, Euan A Ashley, W H Wilson Tang, Christine S Moravec, Kenneth B Margulies, Thomas P Cappola and 2 more

Abstract read
In one paragraph

Article in Genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 203 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
203citing papers in PubMed, 5 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

203 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
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  3. Differential expression of members of SOX family of transcription factors in failing human hearts.Translational research : the journal of laboratory and clinical medicine · 2022
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143 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

12 authors.

Yichuan LiuDepartment of Biostatistics and Epidemiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, United States. Electronic address: yichuan.edwdard.liu@gmail.com.
Michael MorleyCardiovascular Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, United States. Electronic address: mmorley@mail.med.upenn.edu.
Jeffrey BrandimartoCardiovascular Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, United States. Electronic address: bjeff@mail.med.upenn.edu.
Sridhar HannenhalliCenter for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, United States. Electronic address: sridhar@umiacs.umd.edu.
Yu HuDepartment of Biostatistics and Epidemiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, United States. Electronic address: huyu1@mail.med.upenn.edu.
Euan A AshleyStanford Center for Inherited Cardiovascular Disease, Stanford University School of Medicine, Stanford, CA 94305, United States. Electronic address: euan@stanford.edu.
W H Wilson TangDepartment of Cardiovascular Medicine, Cleveland Clinic, Cleveland, OH 44195, United States. Electronic address: TANGW@ccf.org.
Christine S MoravecDepartment of Cardiovascular Medicine, Cleveland Clinic, Cleveland, OH 44195, United States. Electronic address: MORAVEC@ccf.org.
Kenneth B MarguliesCardiovascular Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, United States. Electronic address: Kenneth.Margulies@uphs.upenn.edu.
Thomas P CappolaCardiovascular Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, United States. Electronic address: thomas.cappola@uphs.upenn.edu.
Mingyao LiDepartment of Biostatistics and Epidemiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, United States. Electronic address: mingyao@mail.med.upenn.edu.
MAGNet consortium

Funding

Integrative genomics of human heart failureR01HL105993 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI ASHLEY, EUAN A, CAPPOLA, THOMAS P. · 2011 to 2014
$8.9M
Elucidation of Tissue-Specific Transcriptomic Profiles in Cardiometabolic DiseaseR01HL113147 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI LI, MINGYAO, REILLY, MUREDACH P · 2012 to 2022
$6.8M
Genomics of myocardial transcription factors in cardiac remodelingR01HL088577 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI CAPPOLA, THOMAS P. · 2007 to 2013
$5.3M
Nitrative stress in heart failureR01HL103931 · NHLBI · CLEVELAND CLINIC LERNER COM-CWRU · PI TANG, WAI HONG WILSON · 2010 to 2014
$3.8M
Developing Statistical Methods for Disease Gene DiscoveryR01HG004517 · NHGRI · VANDERBILT UNIVERSITY · PI LI, CHUN, LI, MINGYAO · 2008 to 2012
$1.9M
Endogenous Cardiac Repair in HumansR01HL089847 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI MARGULIES, KENNETH BER · 2009 to 2012
$1.9M
Integrated variation detection annotation and analysis for high-throughout sequeR01HG006465 · NHGRI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI WANG, KAI · 2012 to 2016
$1.8M
Statistical Methods for Next-Generation Sequence DataR01GM097505 · NIGMS · UNIVERSITY OF PENNSYLVANIA · PI LEE, HONGZHE · 2012 to 2015
$1.2M
Statistical Methods for Transcriptome Profiling Using RNA SequencingR01GM108600 · NIGMS · UNIVERSITY OF PENNSYLVANIA · PI LI, MINGYAO · 2014 to 2017
$1.2M
Statistical Methods for Gene Mapping Studies in Admixed PopulationsR01HG005854 · NHGRI · UNIVERSITY OF PENNSYLVANIA · PI LI, MINGYAO · 2010 to 2012
$978k
NHGRI NIH HHS R01 HG004517NHGRI NIH HHS R01 HG005854NHGRI NIH HHS R01 HG006465NHGRI NIH HHS R01HG006465NHLBI NIH HHS R01 HL088577NHLBI NIH HHS R01HL088577NHLBI NIH HHS R01 HL089847NHLBI NIH HHS R01HL089847NHLBI NIH HHS R01 HL103931NHLBI NIH HHS R01HL103931NHLBI NIH HHS R01 HL105993NHLBI NIH HHS R01 HL113147NHLBI NIH HHS R01HL113147NIGMS NIH HHS R01 GM097505NIGMS NIH HHS R01GM097505NIGMS NIH HHS R01 GM108600NIGMS NIH HHS R01GM108600
6 · The paper itself

Abstract

Heart failure is a complex clinical syndrome and has become the most common reason for adult hospitalization in developed countries. Two subtypes of heart failure, ischemic heart disease (ISCH) and dilated cardiomyopathy (DCM), have been studied using microarray platforms. However, microarray has limited resolution. Here we applied RNA sequencing (RNA-Seq) to identify gene signatures for heart failure from six individuals, including three controls, one ISCH and two DCM patients. Using genes identified from this small RNA-Seq dataset, we were able to accurately classify heart failure status in a much larger set of 313 individuals. The identified genes significantly overlapped with genes identified via genome-wide association studies for cardiometabolic traits and the promoters of those genes were enriched for binding sites for transcriptions factors. Our results indicate that it is possible to use RNA-Seq to classify disease status for complex diseases such as heart failure using an extremely small training dataset.

Indexed as

TranscriptomeCardiomyopathy, DilatedGenome-Wide Association StudyHeart FailureHeart VentriclesHumansMyocardial IschemiaPromoter Regions, GeneticSequence Analysis, RNATranscription FactorsTranscription FactorsDisease classificationHeart FailureRNA-seq

Identifiers

PMID25528681
PMCPMC4684258

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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.