Walther Andreas, Cannistraci Carlo Vittorio, Simons Kai, Durán Claudio, Gerl Mathias J, Wehrli Susanne, Kirschbaum Clemens
Biological Psychology, TU Dresden, Dresden Germany.
Biomedical Cybernetics Group, Biotechnology Center (BIOTEC), Center for Molecular and Cellular Bioengineering (CMCB), Center for Systems Biology Dresden (CSBD), Department of Physics, TU Dresden, Dresden, Germany.
Front Psychiatry. 2018 Oct 15;9:459. doi: 10.3389/fpsyt.2018.00459. eCollection 2018.
Omic sciences coupled with novel computational approaches such as machine intelligence offer completely new approaches to major depressive disorder (MDD) research. The complexity of MDD's pathophysiology is being integrated into studies examining MDD's biology within the omic fields. Lipidomics, as a late-comer among other omic fields, is increasingly being recognized in psychiatric research because it has allowed the investigation of global lipid perturbations in patients suffering from MDD and indicated a crucial role of specific patterns of lipid alterations in the development and progression of MDD. Combinatorial lipid-markers with high classification power are being developed in order to assist MDD diagnosis, while rodent models of depression reveal lipidome changes and thereby unveil novel treatment targets for depression. In this systematic review, we provide an overview of current breakthroughs and future trends in the field of lipidomics in MDD research and thereby paving the way for precision medicine in MDD.
组学科学与诸如机器智能等新型计算方法相结合,为重度抑郁症(MDD)的研究提供了全新的途径。MDD病理生理学的复杂性正被纳入在组学领域中研究MDD生物学特性的各项研究。脂质组学作为其他组学领域中的后来者,在精神病学研究中越来越受到认可,因为它能够对MDD患者的整体脂质紊乱情况进行研究,并表明特定脂质改变模式在MDD发生和发展过程中起着关键作用。目前正在开发具有高分类能力的组合脂质标志物,以辅助MDD的诊断,而抑郁症的啮齿动物模型则揭示了脂质组的变化,从而为抑郁症发现新的治疗靶点。在本系统综述中,我们概述了脂质组学在MDD研究领域的当前突破和未来趋势,从而为MDD的精准医学铺平道路。