دورية أكاديمية
أعرض في EDS

Toxicology knowledge graph for structural birth defects.

التفاصيل البيبلوغرافية
العنوان: Toxicology knowledge graph for structural birth defects.
المؤلفون: Evangelista JE; Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA., Clarke DJB; Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA., Xie Z; Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA., Marino GB; Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA., Utti V; Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA., Jenkins SL; Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA., Ahooyi TM; The 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., Bologa CG; Department of Internal Medicine, Division of Translational Informatics, University of New Mexico, Albuquerque, NM, 87131, USA., Yang JJ; Department of Internal Medicine, Division of Translational Informatics, University of New Mexico, Albuquerque, NM, 87131, USA., Binder JL; Department of Internal Medicine, Division of Translational Informatics, University of New Mexico, Albuquerque, NM, 87131, USA., Kumar P; Department of Internal Medicine, Division of Translational Informatics, University of New Mexico, Albuquerque, NM, 87131, USA., Lambert CG; Department of Internal Medicine, Division of Translational Informatics, University of New Mexico, Albuquerque, NM, 87131, USA., Grethe JS; Department of Medicine, University of California San Diego, La Jolla, CA, 92093, USA., Wenger E; The 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., Taylor D; The 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., Oprea TI; Department of Internal Medicine, Division of Translational Informatics, University of New Mexico, Albuquerque, NM, 87131, USA., de Bono B; Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand., Ma'ayan A; Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA. avi.maayan@mssm.edu.
المصدر: Communications medicine [Commun Med (Lond)] 2023 Jul 17; Vol. 3 (1), pp. 98. Date of Electronic Publication: 2023 Jul 17.
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: Nature Portfolio Country of Publication: England NLM ID: 9918250414506676 Publication Model: Electronic Cited Medium: Internet ISSN: 2730-664X (Electronic) Linking ISSN: 2730664X NLM ISO Abbreviation: Commun Med (Lond) Subsets: PubMed not MEDLINE
أسماء مطبوعة: Original Publication: [London] : Nature Portfolio, [2021]-
مستخلص: Background: Birth 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.
Methods: To 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.
Results: Using 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.
Conclusions: ReproTox-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.
(© 2023. The Author(s).)
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معلومات مُعتمدة: OT2 OD030546 United States OD NIH HHS; OT2 OD030162 United States OD NIH HHS; OT2 OD030160 United States OD NIH HHS; OT2 OD032619 United States OD NIH HHS; OT2 OD036435 United States OD NIH HHS
فهرسة مساهمة: Local Abstract: [plain-language-summary] While birth defects are common, for most birth defects there are no known causes. During pregnancy, developing babies are exposed to drugs, cosmetics, food, and environmental pollutants that may cause birth defects. However, exactly how these environmental factors are involved in producing birth defects is difficult to discern. Also, birth defects can be a consequence of the genes inherited from the parents. We combined general data about human genes and drugs with specific data previously implicating genes and drugs in inducing birth defects to create a knowledge graph representation that connects genes, drugs, and birth defects. This knowledge graph can be used to explore new links that may explain why birth defects occur, particularly those that result from a combination of inherited and environmental influences.
تواريخ الأحداث: Date Created: 20230717 Latest Revision: 20240617
رمز التحديث: 20240617
مُعرف محوري في PubMed: PMC10352311
DOI: 10.1038/s43856-023-00329-2
PMID: 37460679
قاعدة البيانات: MEDLINE
الوصف
تدمد:2730-664X
DOI:10.1038/s43856-023-00329-2