Evidence map›Paper›PMID 39051433›Full record

ArticleDatabase : the journal of biological databases and curation2024

Transverse aortic constriction multi-omics analysis uncovers pathophysiological cardiac molecular mechanisms.

Enio Gjerga, Matthias Dewenter, Thiago Britto-Borges, Johannes Grosso, Frank Stein, Jessica Eschenbach, Mandy Rettel, Johannes Backs, Christoph Dieterich

Abstract read
In one paragraph

Article in Database : the journal of biological databases and curation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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

2 citing papers in PubMed.

  1. Article
  2. 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

9 authors.

Enio GjergaSection of Bioinformatics and Systems Cardiology, Klaus Tschira Institute for Integrative Computational Cardiology, University Hospital Heidelberg, INF 669, Heidelberg 69120, Germany.
Matthias DewenterGerman Centre for Cardiovascular Research (DZHK)-Partner Site Heidelberg/Mannheim, Heidelberg 69120, Germany.ORCID 0000-0003-1335-4820
Thiago Britto-BorgesSection of Bioinformatics and Systems Cardiology, Klaus Tschira Institute for Integrative Computational Cardiology, University Hospital Heidelberg, INF 669, Heidelberg 69120, Germany.
Johannes GrossoGerman Centre for Cardiovascular Research (DZHK)-Partner Site Heidelberg/Mannheim, Heidelberg 69120, Germany.
Frank SteinEuropean Molecular Biology Laboratory, Meyerhofstrasse 1, Heidelberg 69117, Germany.
Jessica EschenbachSection of Bioinformatics and Systems Cardiology, Klaus Tschira Institute for Integrative Computational Cardiology, University Hospital Heidelberg, INF 669, Heidelberg 69120, Germany.
Mandy RettelEuropean Molecular Biology Laboratory, Meyerhofstrasse 1, Heidelberg 69117, Germany.
Johannes BacksGerman Centre for Cardiovascular Research (DZHK)-Partner Site Heidelberg/Mannheim, Heidelberg 69120, Germany.
Christoph DieterichSection of Bioinformatics and Systems Cardiology, Klaus Tschira Institute for Integrative Computational Cardiology, University Hospital Heidelberg, INF 669, Heidelberg 69120, Germany.ORCID 0000-0001-9468-6311

Funding

DFG, German Research Foundation 464424253 SFB 1550Klaus Tschira Stiftung gGmbH 00.013.2021
6 · The paper itself

Abstract

Time-course multi-omics data of a murine model of progressive heart failure (HF) induced by transverse aortic constriction (TAC) provide insights into the molecular mechanisms that are causatively involved in contractile failure and structural cardiac remodelling. We employ Illumina-based transcriptomics, Nanopore sequencing and mass spectrometry-based proteomics on samples from the left ventricle (LV) and right ventricle (RV, RNA only) of the heart at 1, 7, 21 and 56 days following TAC and Sham surgery. Here, we present Transverse Aortic COnstriction Multi-omics Analysis (TACOMA), as an interactive web application that integrates and visualizes transcriptomics and proteomics data collected in a TAC time-course experiment. TACOMA enables users to visualize the expression profile of known and novel genes and protein products thereof. Importantly, we capture alternative splicing events by assessing differential transcript and exon usage as well. Co-expression-based clustering algorithms and functional enrichment analysis revealed overrepresented annotations of biological processes and molecular functions at the protein and gene levels. To enhance data integration, TACOMA synchronizes transcriptomics and proteomics profiles, enabling cross-omics comparisons. With TACOMA (https://shiny.dieterichlab.org/app/tacoma), we offer a rich web-based resource to uncover molecular events and biological processes implicated in contractile failure and cardiac hypertrophy. For example, we highlight: (i) changes in metabolic genes and proteins in the time course of hypertrophic growth and contractile impairment; (ii) identification of RNA splicing changes in the expression of Tpm2 isoforms between RV and LV; and (iii) novel transcripts and genes likely contributing to the pathogenesis of HF. We plan to extend these data with additional environmental and genetic models of HF to decipher common and distinct molecular changes in heart diseases of different aetiologies. Database URL: https://shiny.dieterichlab.org/app/tacoma.

Indexed as

ProteomicsAnimalsAortaGene Expression ProfilingHeart FailureMiceMultiomicsTranscriptome

Identifiers

PMID39051433
PMCPMC11270014

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.