Evidence map›Paper›PMID 37460679›Full record

ArticleCommunications medicine2023

Toxicology knowledge graph for structural birth defects.

John Erol Evangelista, Daniel J B Clarke, Zhuorui Xie, Giacomo B Marino, Vivian Utti, Sherry L Jenkins, Taha Mohseni Ahooyi, Cristian G Bologa, Jeremy J Yang, Jessica L Binder and 8 more

Open access · goldAbstract read
In one paragraph

Article in Communications medicine, 2023. 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
5.2field-weighted citation impact, top 4% 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, 21 citations in OpenAlex.

  1. Review
  2. The Common Fund Data Ecosystem (CFDE).bioRxiv : the preprint server for biology · 2026
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  8. lncRNAlyzr: Enrichment Analysis for lncRNA Sets.Journal of molecular biology · 2025
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  10. Review
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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

18 authors at 5 institutions in 2 countries.

John Erol Evangelista *Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
Daniel J B Clarke *Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.ORCID http://orcid.org/0000-0003-3471-7416
Zhuorui XieDepartment of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.ORCID http://orcid.org/0000-0002-8256-5878
Giacomo B MarinoDepartment of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
Vivian UttiDepartment of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
Sherry L JenkinsDepartment of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.ORCID http://orcid.org/0000-0003-1730-0977
Taha Mohseni AhooyiThe Children's Hospital of Philadelphia, Department of Biomedical and Health Informatics; Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.
Cristian G BologaDepartment of Internal Medicine, Division of Translational Informatics, University of New Mexico, Albuquerque, NM, 87131, USA.ORCID http://orcid.org/0000-0003-2232-4244
Jeremy J YangDepartment of Internal Medicine, Division of Translational Informatics, University of New Mexico, Albuquerque, NM, 87131, USA.
Jessica L BinderDepartment of Internal Medicine, Division of Translational Informatics, University of New Mexico, Albuquerque, NM, 87131, USA.
Praveen KumarDepartment of Internal Medicine, Division of Translational Informatics, University of New Mexico, Albuquerque, NM, 87131, USA.ORCID http://orcid.org/0000-0002-4981-9020
Christophe G LambertDepartment of Internal Medicine, Division of Translational Informatics, University of New Mexico, Albuquerque, NM, 87131, USA.ORCID http://orcid.org/0000-0003-1994-2893
Jeffrey S GretheDepartment of Medicine, University of California San Diego, La Jolla, CA, 92093, USA.ORCID http://orcid.org/0000-0001-5212-7052
Eric WengerThe Children's Hospital of Philadelphia, Department of Biomedical and Health Informatics; Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.
Deanne TaylorThe Children's Hospital of Philadelphia, Department of Biomedical and Health Informatics; Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.
Tudor I OpreaDepartment of Internal Medicine, Division of Translational Informatics, University of New Mexico, Albuquerque, NM, 87131, USA.ORCID http://orcid.org/0000-0002-6195-6976
Bernard de BonoAuckland Bioengineering Institute, University of Auckland, Auckland, New Zealand.
Avi Ma'ayanDepartment of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA. avi.maayan@mssm.edu.ORCID http://orcid.org/0000-0002-6904-1017
Icahn School of Medicine at Mount Sinai · USUniversity of New Mexico · USChildren's Hospital of Philadelphia · USUniversity of Auckland · NZUniversity of California San Diego · US

Funding

Kids First Data Resource Center (KFDRC): Harnessing Data-Driven Opportunities in the Present on behalf of the Future of Common Fund Data Ecosystem (CFDE)OT2OD030162 · OD · CHILDREN'S HOSP OF PHILADELPHIA · PI DIGIOVANNA, JACK, HEATH, ALLISON · 2020 to 2025
$10.7M
The CFDE WorkbenchOT2OD036435 · OD · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI MA'AYAN, AVI, SUBRAMANIAM, SHANKAR · 2023 to 2025
$7.2M
The LINCS DCIC Engagement Plan with the CFDEOT2OD030160 · OD · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI MA'AYAN, AVI · 2020 to 2024
$3.4M
SPARC Engagement Plan with the Common Fund Data EcosystemOT2OD032619 · OD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI DE BONO, BERNARD, MARTONE, MARYANN E · 2021 to 2025
$3.2M
Illuminating the Druggable Genome Data Coordinating Center - Engagement Plan with the CFDEOT2OD030546 · OD · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI LAMBERT, CHRISTOPHE G., YANG, JEREMY JOSEPH · 2020 to 2025
$2.8M
NIH HHS OT2 OD030160NIH HHS OT2 OD030162NIH HHS OT2 OD030546NIH HHS OT2 OD032619NIH HHS OT2 OD036435
6 · The paper itself

Abstract

backgroundBirth defects are functional and structural abnormalities that impact about 1 in 33 births in the United States. They have been attributed to genetic and other factors such as drugs, cosmetics, food, and environmental pollutants during pregnancy, but for most birth defects there are no known causes.

methodsTo further characterize associations between small molecule compounds and their potential to induce specific birth abnormalities, we gathered knowledge from multiple sources to construct a reproductive toxicity Knowledge Graph (ReproTox-KG) with a focus on associations between birth defects, drugs, and genes. Specifically, we gathered data from drug/birth-defect associations from co-mentions in published abstracts, gene/birth-defect associations from genetic studies, drug- and preclinical-compound-induced gene expression changes in cell lines, known drug targets, genetic burden scores for human genes, and placental crossing scores for small molecules.

resultsUsing ReproTox-KG and semi-supervised learning (SSL), we scored >30,000 preclinical small molecules for their potential to cross the placenta and induce birth defects, and identified >500 birth-defect/gene/drug cliques that can be used to explain molecular mechanisms for drug-induced birth defects. The ReproTox-KG can be accessed via a web-based user interface available at https://maayanlab.cloud/reprotox-kg . This site enables users to explore the associations between birth defects, approved and preclinical drugs, and all human genes.

conclusionsReproTox-KG provides a resource for exploring knowledge about the molecular mechanisms of birth defects with the potential of predicting the likelihood of genes and preclinical small molecules to induce birth defects.

Identifiers

PMID37460679
PMCPMC10352311
OpenAlexW4384524118

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.