将“Ome”放入脂质代谢中。

David M Mutch, Laetitia Fauconnot, Martin Grigorov, Laurent B Fay
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引用次数: 15

摘要

认识到脂质代谢的改变是西方社会面临的许多代谢紊乱的基础,这突出了代谢组学亚群的重要性,这里称为脂质组。虽然全面的脂质分析并不是一个最近的概念,但脂质组学方法的新颖性在于应用稳健的统计算法来突出脂质分子群体中细微但重要的变化。第一代脂质组学研究已经证明了用计算软件解释定量数据集的敏感性;然而,全面的脂质分析的固有力量往往没有被利用,因为稳健的统计模型没有被常规使用。因此,本文旨在简要介绍目前适用于脂质综合分析的技术,概述能够揭示代谢微妙变化的创新数学模型,这将改善我们对脂质生物化学的理解,并展示通过脂质组学方法发现的生物学启示及其对健康管理的潜在意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Putting the 'Ome' in lipid metabolism.

The recognition that altered lipid metabolism underlies many metabolic disorders challenging Western society highlights the importance of this metabolomic subset, herein referred to as the lipidome. Although comprehensive lipid analyses are not a recent concept, the novelty of a lipidomic approach lies with the application of robust statistical algorithms to highlight subtle, yet significant, changes in a population of lipid molecules. First-generation lipidomic studies have demonstrated the sensitivity of interpreting quantitative datasets with computational software; however, the innate power of comprehensive lipid profiling is often not exploited, as robust statistical models are not routinely utilized. Therefore, the current review aims to briefly describe the current technologies suitable for comprehensive lipid analysis, outline innovative mathematical models that have the ability to reveal subtle changes in metabolism, which will ameliorate our understanding of lipid biochemistry, and demonstrate the biological revelations found through lipidomic approaches and their potential implications for health management.

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