Evidence map›Paper›PMID 25249829›Full record

ArticleClinical proteomics2014

The effect of disease on human cardiac protein expression profiles in paired samples from right and left ventricles.

Ben Littlejohns, Kate Heesom, Gianni D Angelini, M-Saadeh Suleiman

Open access · goldAbstract read
In one paragraph

Article in Clinical proteomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
1.0field-weighted citation impact, top 21% 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

16 citing papers in PubMed, 22 citations in OpenAlex.

  1. Remote ischaemic preconditioning in isolated aortic valve and coronary artery bypass surgery: a randomized trial†.European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery · 2019
    Trial
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  5. Tissue mechanics coevolves with fibrillar matrisomes in healthy and fibrotic tissues.Matrix biology : journal of the International Society for Matrix Biology · 2022
    Review
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  12. Review
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  14. Cardiovascular consequences of metabolic syndrome.Translational research : the journal of laboratory and clinical medicine · 2017
    Review
  15. Article
  16. 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

4 authors at 1 institution in 1 country.

Ben LittlejohnsBristol Heart Institute, School of Clinical Sciences, Faculty of Medicine & Dentistry, University of Bristol, Bristol, UK.
Kate HeesomProteomics Facility, Faculty of Medical and Veterinary Sciences, University of Bristol, Bristol, UK.
Gianni D AngeliniBristol Heart Institute, School of Clinical Sciences, Faculty of Medicine & Dentistry, University of Bristol, Bristol, UK.
M-Saadeh SuleimanBristol Heart Institute, School of Clinical Sciences, Faculty of Medicine & Dentistry, University of Bristol, Bristol, UK.
University of Bristol · GB

Funding

British Heart Foundation FS/11/57/28936
6 · The paper itself

Abstract

backgroundCardiac diseases (e.g. coronary and valve) are associated with ventricular cellular remodeling. However, ventricular biopsies from left and right ventricles from patients with different pathologies are rare and thus little is known about disease-induced cellular remodeling in both sides of the heart and between different diseases. We hypothesized that the protein expression profiles between right and left ventricles of patients with aortic valve stenosis (AVS) and patients with coronary artery disease (CAD) are different and that the protein profile is different between the two diseases. Left and right ventricular biopsies were collected from patients with either CAD or AVS. The biopsies were processed for proteomic analysis using isobaric tandem mass tagging and analyzed by reverse phase nano-LC-MS/MS. Western blot for selected proteins showed strong correlation with proteomic analysis.

resultsProteomic analysis between ventricles of the same disease (intra-disease) and between ventricles of different diseases (inter-disease) identified more than 500 proteins detected in all relevant ventricular biopsies. Comparison between ventricles and disease state was focused on proteins with relatively high fold (±1.2 fold difference) and significant (P < 0.05) differences. Intra-disease protein expression differences between left and right ventricles were largely structural for AVS patients and largely signaling/metabolism for CAD. Proteins commonly associated with hypertrophy were also different in the AVS group but with lower fold difference. Inter-disease differences between left ventricles of AVS and CAD were detected in 9 proteins. However, inter-disease differences between the right ventricles of CAD and AVS patients were associated with differences in 73 proteins. The majority of proteins which had a significant difference in one ventricle compared to the other pathology also had a similar trend in the adjacent ventricle.

conclusionsThis work demonstrates for the first time that left and right ventricles have a different proteome and that the difference is dependent on the type of disease. Inter-disease differential expression was more prominent for right ventricles. The finding that a protein change in one ventricle was often associated with a similar trend in the adjacent ventricle for a large number of proteins suggests cross-talk proteome remodeling between adjacent ventricles.

Indexed as

Aortic valve stenosisCardiacCoronary artery diseaseHumanMass spectrometryProteomicsTMT tagVentricular biopsies

Identifiers

PMID25249829
PMCPMC4158351
OpenAlexW2137520683

What OpenQuestion holds

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LicenceCC BY
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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.