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毒性的未充分探索的分子机制

Underexplored Molecular Mechanisms of Toxicity.

作者信息

Arowolo Olatunbosun, Suvorov Alexander

机构信息

Department of Environmental Health Sciences, School of Public Health and Health Sciences, University of Massachusetts, 686 North Pleasant Street, Amherst, MA 01003, USA.

出版信息

J Xenobiot. 2024 Jul 18;14(3):939-949. doi: 10.3390/jox14030052.

Abstract

Social biases may concentrate the attention of researchers on a small number of well-known molecules/mechanisms leaving others underexplored. In accordance with this view, central to mechanistic toxicology is a narrow range of molecular pathways that are assumed to be involved in a significant part of the responses to toxicity. It is unclear, however, if there are other molecular mechanisms which play an important role in toxicity events but are overlooked by toxicology. To identify overlooked genes sensitive to chemical exposures, we used publicly available databases. First, we used data on the published chemical-gene interactions for 17,338 genes to estimate their sensitivity to chemical exposures. Next, we extracted data on publication numbers per gene for 19,243 human genes from the Find My Understudied Genes database. Thresholds were applied to both datasets using our algorithm to identify chemically sensitive and chemically insensitive genes and well-studied and underexplored genes. A total of 1110 underexplored genes highly sensitive to chemical exposures were used in GSEA and Shiny GO analyses to identify enriched biological categories. The metabolism of fatty acids, amino acids, and glucose were identified as underexplored molecular mechanisms sensitive to chemical exposures. These findings suggest that future effort is needed to uncover the role of xenobiotics in the current epidemics of metabolic diseases.

摘要

社会偏见可能会使研究人员将注意力集中在少数知名分子/机制上,而忽略其他分子/机制。按照这种观点,机械毒理学的核心是一小部分分子途径,这些途径被认为在很大一部分毒性反应中起作用。然而,尚不清楚是否存在其他在毒性事件中起重要作用但被毒理学忽视的分子机制。为了识别对化学暴露敏感但被忽视的基因,我们使用了公开可用的数据库。首先,我们利用17338个基因已发表的化学-基因相互作用数据来估计它们对化学暴露的敏感性。接下来,我们从“找到我研究不足的基因”数据库中提取了19243个人类基因的每个基因的发表数量数据。使用我们的算法对这两个数据集应用阈值,以识别化学敏感和化学不敏感的基因以及研究充分和研究不足的基因。总共1110个对化学暴露高度敏感但研究不足的基因被用于基因集富集分析(GSEA)和Shiny GO分析,以识别富集的生物学类别。脂肪酸、氨基酸和葡萄糖的代谢被确定为对化学暴露敏感但研究不足的分子机制。这些发现表明,未来需要努力揭示外源性物质在当前代谢性疾病流行中的作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcde/11270369/b8eb622806e6/jox-14-00052-g001.jpg

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