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首页> 外文期刊>Toxicological sciences: An official journal of the Society of Toxicology >Application of Gene Set Enrichment Analysis for Identification of Chemically Induced, Biologically Relevant Transcriptomic Networks and Potential Utilization in Human Health Risk Assessment
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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:基因设定富集分析在鉴定化学诱导,生物学相关转录组网和人体健康风险评估中潜在利用的应用

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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:商业新化学发育的速度结合遗留化学品的毒性数据的缺乏,对人类健康风险评估具有独特的挑战。明确需要开发新技术并纳入新的数据流以更有效地告知毒性值。一种剥削途径在转录组织领域以及基因表达分析的应用,以对化学曝光的生物反应表征。在这种情况下,使用基因设定富集分析(GSEA)来评估在暴露于各种持续时间的多种化学物质后产生的组织特异性剂量 - 反应基因表达数据。随着时间的推移和随着剂量的增加,转录富集的模式,并且观察到与生物反应的病因相关的协调富集。 GSEA能够捕获促进适应性与长期分子反应之间分化的瞬态和持续转录的富集事件。当与基因表达数据的基准剂量(BMD)建模联合生物富集的主要驱动器时,GSEA促进了富集生物相关分子信令途径所需的剂量范围的表征,并促进了个体途径所需的活化剂量范围的比较。为最敏感的富集途径计算了中值转录BMD值,以及显着富集途径的关键基因成员的整体中值BMD值,并且两者都被观察到是最敏感的顶点BMD值的良好估计。这些努力在一起支持GSEA在定性和定量人体健康风险评估中的应用。

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