Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Toxicol Sci. 2021 Aug 3;182(2):159-167. doi: 10.1093/toxsci/kfab060.
Big data approaches have profoundly influenced state-of-the-art in many fields of research, with toxicology being no exception. Here, we use Parkinson's disease as a window through which to explore the challenges of a dual explosion of metabolomic data addressing the myriad environmental exposures individuals experience and genetic analyses implicating many different loci as risk factors for disease. We argue that new experimental approaches are needed to convert the growing body of omics data into molecular mechanisms of disease that can be therapeutically targeted in specific patients. We outline one attractive strategy, which capitalizes on the rapid generation time and advanced molecular tools available in the fruit fly, Drosophila, to provide a platform for mechanistic dissection and drug discovery.
大数据方法深刻地影响了许多研究领域的最新进展，毒理学也不例外。在这里，我们以帕金森病为窗口，探讨代谢组学数据爆炸式增长带来的挑战，这些数据涉及个体所经历的无数环境暴露，以及遗传分析表明许多不同的基因位点是疾病的风险因素。我们认为，需要新的实验方法将日益增长的组学数据转化为疾病的分子机制，以便在特定患者中进行有针对性的治疗。我们概述了一种有吸引力的策略，该策略利用果蝇快速的世代时间和先进的分子工具，为机制剖析和药物发现提供了一个平台。
