Evidence map›Paper›PMID 38422168›Full record

ArticlePLoS computational biology2024

Identifying metabolic adaptations characteristic of cardiotoxicity using paired transcriptomics and metabolomics data integrated with a computational model of heart metabolism.

Bonnie V Dougherty, Connor J Moore, Kristopher D Rawls, Matthew L Jenior, Bryan Chun, Sarbajeet Nagdas, Jeffrey J Saucerman, Glynis L Kolling, Anders Wallqvist, Jason A Papin

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.4field-weighted citation impact, top 20% 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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

10 authors at 3 institutions in 1 country.

Bonnie V DoughertyDepartment of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America.
Connor J MooreDepartment of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America.
Kristopher D RawlsDepartment of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America.ORCID 0000-0001-5873-0127
Matthew L JeniorDepartment of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America.
Bryan ChunDepartment of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America.
Sarbajeet NagdasDepartment of Microbiology, Immunology, and Cancer Biology, University of Virginia Health System, Charlottesville, Virginia, United States of America.
Jeffrey J SaucermanDepartment of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America.
Glynis L KollingDepartment of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America.
Anders WallqvistDepartment of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Development Command, Fort Detrick, Maryland, United States of America.ORCID 0000-0002-9775-7469
Jason A PapinDepartment of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America.ORCID 0000-0002-2769-5805
University of Virginia · USTelemedicine & Advanced Technology Research Center · USUniversity of Virginia Health System · US

Funding

Population-Based Characterization of Metabolic Pathways to Predict Pediatric Crohn's Disease OutcomesR01DK132369 · NIDDK · UNIVERSITY OF VIRGINIA · PI Sana Syed · 2022 to 2026
$3.4M
Systems Pharmacology Model of Cardiac HypertrophyR01HL162925 · NHLBI · UNIVERSITY OF VIRGINIA · PI SAUCERMAN, JEFFREY J., WOLF, MATTHEW J · 2022 to 2025
$3.1M
Systems Pharmacology Model for Spatial Control of Cardiac FibrosisR01HL137755 · NHLBI · UNIVERSITY OF VIRGINIA · PI HOLMES, JEFFREY W, SAUCERMAN, JEFFREY J. · 2017 to 2020
$1.9M
Interdisciplinary Training in Systems & Biomolecular Data ScienceT32GM145443 · NIGMS · UNIVERSITY OF VIRGINIA · PI Kevin A Janes, Jason Papin · 2022 to 2026
$1.5M
NHLBI NIH HHS R01 HL137755NHLBI NIH HHS R01 HL162925NIDDK NIH HHS R01 DK132369NIGMS NIH HHS T32 GM145443
6 · The paper itself

Abstract

Improvements in the diagnosis and treatment of cancer have revealed long-term side effects of chemotherapeutics, particularly cardiotoxicity. Here, we present paired transcriptomics and metabolomics data characterizing in vitro cardiotoxicity to three compounds: 5-fluorouracil, acetaminophen, and doxorubicin. Standard gene enrichment and metabolomics approaches identify some commonly affected pathways and metabolites but are not able to readily identify metabolic adaptations in response to cardiotoxicity. The paired data was integrated with a genome-scale metabolic network reconstruction of the heart to identify shifted metabolic functions, unique metabolic reactions, and changes in flux in metabolic reactions in response to these compounds. Using this approach, we confirm previously seen changes in the p53 pathway by doxorubicin and RNA synthesis by 5-fluorouracil, we find evidence for an increase in phospholipid metabolism in response to acetaminophen, and we see a shift in central carbon metabolism suggesting an increase in metabolic demand after treatment with doxorubicin and 5-fluorouracil.

Indexed as

AcetaminophenCardiotoxicityDoxorubicinFluorouracilGene Expression ProfilingHumansMetabolomicsAcetaminophenDoxorubicinFluorouracil

Identifiers

PMID38422168
PMCPMC10931521
OpenAlexW4392283040

What OpenQuestion holds

Textmetadata
LicenceCC0
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.