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Application of Gene Set Enrichment Analysis for Identification of Chemically Induced Biologically Relevant Transcriptomic Networks and Potential Utilization in Human Health Risk Assessment

机译:基因组富集分析在化学诱导的生物相关的转录组网络的识别和潜在利用中对人体健康风险评估的应用

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摘要

The rate of new chemical development in commerce combined with a paucity of toxicity data for legacy chemicals presents a unique challenge for human health risk assessment. There is a clear need to develop new technologies and incorporate novel data streams to more efficiently inform derivation of toxicity values. One avenue of exploitation lies in the field of transcriptomics and the application of gene expression analysis to characterize biological responses to chemical exposures. In this context, gene set enrichment analysis (GSEA) was employed to evaluate tissue-specific, dose-response gene expression data generated following exposure to multiple chemicals for various durations. Patterns of transcriptional enrichment were evident across time and with increasing dose, and coordinated enrichment plausibly linked to the etiology of the biological responses was observed. GSEA was able to capture both transient and sustained transcriptional enrichment events facilitating differentiation between adaptive versus longer term molecular responses. When combined with benchmark dose (BMD) modeling of gene expression data from key drivers of biological enrichment, GSEA facilitated characterization of dose ranges required for enrichment of biologically relevant molecular signaling pathways, and promoted comparison of the activation dose ranges required for individual pathways. Median transcriptional BMD values were calculated for the most sensitive enriched pathway as well as the overall median BMD value for key gene members of significantly enriched pathways, and both were observed to be good estimates of the most sensitive apical endpoint BMD value. Together, these efforts support the application of GSEA to qualitative and quantitative human health risk assessment.
机译:商业上新化学药品的开发速度以及遗留化学药品的毒性数据很少,对人类健康风险评估提出了独特的挑战。显然需要开发新技术并结合新的数据流,以更有效地告知毒性值的推导。一种利用途径是转录组学领域以及基因表达分析在表征对化学暴露的生物学反应方面的应用。在这种情况下,采用基因组富集分析(GSEA)来评估组织特异性,剂量反应基因表达数据,这些数据是在多种化学物质中暴露持续不同时间后产生的。转录富集的模式随着时间的推移和剂量的增加而明显,并且观察到了与生物反应的病因学合理相关的协调富集。 GSEA能够捕获瞬时和持续转录富集事件,从而促进了适应性和长期分子反应之间的区别。当与生物富集关键驱动因素的基因表达数据的基准剂量(BMD)模型结合使用时,GSEA有助于表征生物相关分子信号传导途径的富集所需的剂量范围,并促进了各个途径所需的活化剂量范围的比较。计算了最敏感的富集途径的中位转录BMD值以及显着富集的途径的关键基因成员的总体中值BMD值,并且观察到这两者都是对最敏感的顶端终点BMD值的良好估计。这些努力共同支持了GSEA在定性和定量人类健康风险评估中的应用。

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