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测量脂质通量以推进转化研究:从经典方法到精准健康的未来。

Measurement of lipid flux to advance translational research: evolution of classic methods to the future of precision health.

机构信息

Department of Nutrition and Exercise Physiology, University of Missouri, Columbia, MO, 65212, USA.

Department of Medicine, Division of Gastroenterology and Hepatology, School of Medicine, University of Missouri, Columbia, MO, 65212, USA.

出版信息

Exp Mol Med. 2022 Sep;54(9):1348-1353. doi: 10.1038/s12276-022-00838-5. Epub 2022 Sep 8.

Abstract

Over the past 70 years, the study of lipid metabolism has led to important discoveries in identifying the underlying mechanisms of chronic diseases. Advances in the use of stable isotopes and mass spectrometry in humans have expanded our knowledge of target molecules that contribute to pathologies and lipid metabolic pathways. These advances have been leveraged within two research paths, leading to the ability (1) to quantitate lipid flux to understand the fundamentals of human physiology and pathology and (2) to perform untargeted analyses of human blood and tissues derived from a single timepoint to identify lipidomic patterns that predict disease. This review describes the physiological and analytical parameters that influence these measurements and how these issues will propel the coming together of the two fields of metabolic tracing and lipidomics. The potential of data science to advance these fields is also discussed. Future developments are needed to increase the precision of lipid measurements in human samples, leading to discoveries in how individuals vary in their production, storage, and use of lipids. New techniques are critical to support clinical strategies to prevent disease and to identify mechanisms by which treatments confer health benefits with the overall goal of reducing the burden of human disease.

摘要

在过去的 70 年中,对脂质代谢的研究导致了在鉴定慢性病潜在机制方面的重要发现。在人类中使用稳定同位素和质谱的进步扩展了我们对导致病理学和脂质代谢途径的靶分子的认识。这些进展在两条研究路径中得到了利用,从而使我们能够(1)定量脂质通量以了解人类生理学和病理学的基础,以及(2)对源自单个时间点的人体血液和组织进行非靶向分析,以识别预测疾病的脂质组学模式。这篇综述描述了影响这些测量的生理和分析参数,以及这些问题将如何推动代谢示踪和脂质组学这两个领域的融合。还讨论了数据科学在推进这些领域的潜力。需要未来的发展来提高人体样本中脂质测量的精度,从而发现个体在脂质的产生、储存和利用方面的差异。新技术对于支持预防疾病的临床策略以及确定治疗方法带来健康益处的机制至关重要,总体目标是减轻人类疾病的负担。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/884a/9534914/b85ae547abab/12276_2022_838_Fig1_HTML.jpg

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