Kostara Christina E
Laboratory of Clinical Chemistry, School of Health Sciences, Faculty of Medicine, University of Ioannina, 45110 Ioannina, Greece.
Diagnostics (Basel). 2023 Feb 15;13(4):721. doi: 10.3390/diagnostics13040721.
The increasing global burden of cardiometabolic diseases highlights the urgent clinical need for better personalized prediction and intervention strategies. Early diagnosis and prevention could greatly reduce the enormous socio-economic burden posed by these states. Plasma lipids including total cholesterol, triglycerides, HDL-C, and LDL-C have been at the center stage of the prediction and prevention strategies for cardiovascular disease; however, the bulk of cardiovascular disease events cannot be explained sufficiently by these lipid parameters. The shift from traditional serum lipid measurements that are poorly descriptive of the total serum lipidomic profile to comprehensive lipid profiling is an urgent need, since a wealth of metabolic information is currently underutilized in the clinical setting. The tremendous advances in the field of lipidomics in the last two decades has facilitated the research efforts to unravel the lipid dysregulation in cardiometabolic diseases, enabling the understanding of the underlying pathophysiological mechanisms and identification of predictive biomarkers beyond traditional lipids. This review presents an overview of the application of lipidomics in the study of serum lipoproteins in cardiometabolic diseases. Integrating the emerging multiomics with lipidomics holds great potential in moving toward this goal.
全球心血管代谢疾病负担日益加重,凸显了临床上对更好的个性化预测和干预策略的迫切需求。早期诊断和预防可大幅减轻这些疾病造成的巨大社会经济负担。包括总胆固醇、甘油三酯、高密度脂蛋白胆固醇和低密度脂蛋白胆固醇在内的血浆脂质一直处于心血管疾病预测和预防策略的核心位置;然而,这些脂质参数并不能充分解释大部分心血管疾病事件。从传统的血清脂质测量方法(其对总血清脂质组学特征的描述较差)转向全面的脂质谱分析迫在眉睫,因为目前临床环境中大量的代谢信息未得到充分利用。在过去二十年中,脂质组学领域取得的巨大进展推动了相关研究工作,以揭示心血管代谢疾病中的脂质失调,从而能够理解潜在的病理生理机制,并识别出超越传统脂质的预测性生物标志物。本综述概述了脂质组学在心血管代谢疾病血清脂蛋白研究中的应用。将新兴的多组学与脂质组学相结合,在实现这一目标方面具有巨大潜力。