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从毒基因组学数据到累积评估组:化学品分组的框架

Sebastian Canzler¹, Julienne Lehmann^2,3, Jana Schor^2,4

¹Department Computational Biology and Chemistry, Helmholtz Centre for Environmental Research - UFZ, 04318, Leipzig, Germany. sebastian.canzler@ufz.de.

Archives of toxicology

|September 26, 2025

概括

这项研究引入了一种新的框架,使用化学基因表型疾病 (CGPD) 四分法来按分子和表型效应分组化学物质. 这有助于监管毒理学和风险评估,支持下一代方法.

科学领域:

毒理学毒理学毒理学
计算生物学计算生物学
基因组学就是基因组学.

背景情况:

化学品分组对于监管毒理学,减少数据差距和累积风险评估至关重要.
现有的方法可能无法完全捕捉不同化学品类的复杂分子和表型效应.
整合毒基因组学数据是推动风险评估方法的关键.

研究的目的:

引入一种新的化学分组框架,使用化学-基因-表型-疾病 (CGPD) 四分法.
利用公开可用的毒基因组学数据来识别和聚类具有类似作用的化学物质.
支持基于证据的监管决策和过渡到下一代风险评估.

主要方法:

使用的化学基因基因表型疾病 (CGPD) 四分法,来源于比较毒基因组学数据库 (CTD).
综合公开可用的多种化学品组 (杀虫剂,药品,工业化学品) 的毒基因组学数据.
通过比较CGPD基于四聚体的集群与EFSA建立的累积评估组 (CAG) 来验证框架.

主要成果:

基于CGPD四聚体的集群和已建立的农药累积评估小组 (CAG) 之间有明显的重叠.
确定了与风险评估相关的其他化合物,包括与内分泌干扰和代谢障碍相关的化合物.
该框架有效地将奥米克衍生分子数据与表型和疾病终点联系起来.

结论:

新的CGPD四聚框架为化学品分组提供了一个全面的工具.
这种方法支持监管毒理学,并促进累积风险评估.
该研究通过整合不同类型的数据来推动向下一代风险评估方法的过渡.

关键词:

在 CTD 基底 CTD 基底化学品的分组是化学品的分组.数据集成数据集成.文字转录学 (Transcriptomics) 是一个学科.

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