Toxicology knowledge graph for structural birth defects.
Toxicology knowledge graph for structural birth defects.
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DOI：
10.1038/s43856-023-00329-2
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发表时间：
2023-07-17
期刊：
影响因子：
--
通讯作者：
Ma'ayan, Avi
中科院分区：
文献类型：
--
作者：
Evangelista, John Erol;Clarke, Daniel J B;Xie, Zhuorui;Marino, Giacomo B;Utti, Vivian;Jenkins, Sherry L;Ahooyi, Taha Mohseni;Bologa, Cristian G;Yang, Jeremy J;Binder, Jessica L;Kumar, Praveen;Lambert, Christophe G;Grethe, Jeffrey S;Wenger, Eric;Taylor, Deanne;Oprea, Tudor I;de Bono, Bernard;Ma'ayan, Avi
出生缺陷是功能和结构异常，在美国每33个新生儿中就有1个受到影响。它们被归因于遗传和其他因素，如药物，化妆品，食物和怀孕期间的环境污染物，但大多数出生缺陷没有已知的原因。为了进一步表征小分子化合物与其诱导特定出生异常的潜力之间的关联，我们从多个来源收集知识，构建生殖毒性知识图（ReproTox-KG），重点关注出生缺陷，药物和基因之间的关联。具体而言，我们收集了来自已发表摘要中共同提及的药物/出生缺陷关联、来自遗传研究的基因/出生缺陷关联、药物和临床前化合物诱导的细胞系基因表达变化、已知药物靶点、人类基因的遗传负担评分和小分子的胎盘交叉评分的数据。使用ReproTox-KG和半监督学习（SSL），我们对超过30，000种临床前小分子进行了评分，以确定其穿过胎盘并诱导出生缺陷的潜力，并确定了超过500种出生缺陷/基因/药物集团，可用于解释药物诱导的出生缺陷的分子机制。ReproTox-KG可通过https://maayanlab.cloud/reprotox-kg提供的基于网络的用户界面访问。该网站使用户能够探索出生缺陷，批准和临床前药物以及所有人类基因之间的关联。ReproTox-KG为探索出生缺陷的分子机制提供了一个资源，具有预测基因和临床前小分子诱导出生缺陷的可能性的潜力。虽然出生缺陷很常见，但大多数出生缺陷都没有已知的原因。在怀孕期间，发育中的婴儿暴露于可能导致出生缺陷的药物，化妆品，食物和环境污染物。然而，这些环境因素究竟如何参与产生出生缺陷是很难辨别的。此外，出生缺陷可能是遗传自父母的基因的结果。我们将有关人类基因和药物的一般数据与先前涉及基因和药物诱导出生缺陷的特定数据相结合，以创建一个连接基因，药物和出生缺陷的知识图表示。这个知识图谱可以用来探索新的联系，这些联系可以解释为什么会发生出生缺陷，特别是那些由遗传和环境影响共同导致的出生缺陷。Clarke、Evangelista等人使用知识图谱（ReproTox-KG）来表征小分子化合物与其诱导特定出生异常的潜力之间的关联。他们确定了500多个出生缺陷/基因/药物联系，可以解释药物诱导的出生缺陷的分子机制。
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. 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. 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. 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. 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. Clarke, Evangelista et al. use a knowledge graph (ReproTox-KG) to characterize associations between small molecule compounds and their potential to induce specific birth abnormalities. They identify over 500 birth defect/gene/drug connections that can explain molecular mechanisms for drug-induced birth defects.
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DOI：
10.1145/3038912.3052692
发表时间：
2017-04
期刊：
Proceedings of the ... International World-Wide Web Conference. International WWW Conference
影响因子：
--
作者：
Kamdar MR;Musen MA
通讯作者：
Musen MA
影响因子：
3
作者：
Dannenfelser R;Clark NR;Ma'ayan A
通讯作者：
Ma'ayan A
DOI：
10.1002/psp4.12357
发表时间：
2018-11
期刊：
CPT: pharmacometrics & systems pharmacology
影响因子：
--
作者：
Lesko LJ;Vozmediano V;Brown JD;Winterstein A;Zhao P;Lippert J;Höchel J;Chaturvedula A;White A;Schmidt S
通讯作者：
Schmidt S
影响因子：
3.5
作者：
Kokash N;de Bono B
通讯作者：
de Bono B