Dumas Marc-Emmanuel, Davidovic Laetitia
Section of Biomolecular Medicine, Division of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, Exhibition Road, South Kensington, London, SW7 2AZ, UK.
J Neuroimmune Pharmacol. 2015 Sep;10(3):402-24. doi: 10.1007/s11481-014-9578-5. Epub 2015 Jan 24.
Metabolic phenotyping corresponds to the large-scale quantitative and qualitative analysis of the metabolome i.e., the low-molecular weight <1 KDa fraction in biological samples, and provides a key opportunity to advance neurosciences. Proton nuclear magnetic resonance and mass spectrometry are the main analytical platforms used for metabolic profiling, enabling detection and quantitation of a wide range of compounds of particular neuro-pharmacological and physiological relevance, including neurotransmitters, secondary messengers, structural lipids, as well as their precursors, intermediates and degradation products. Metabolic profiling is therefore particularly indicated for the study of central nervous system by probing metabolic and neurochemical profiles of the healthy or diseased brain, in preclinical models or in human samples. In this review, we introduce the analytical and statistical requirements for metabolic profiling. Then, we focus on key studies in the field of metabolic profiling applied to the characterization of animal models and human samples of central nervous system disorders. We highlight the potential of metabolic profiling for pharmacological and physiological evaluation, diagnosis and drug therapy monitoring of patients affected by brain disorders. Finally, we discuss the current challenges in the field, including the development of systems biology and pharmacology strategies improving our understanding of metabolic signatures and mechanisms of central nervous system diseases.
代谢表型分析对应于对代谢组进行大规模的定量和定性分析，即生物样品中分子量小于1 kDa的低分子量部分，并为推进神经科学研究提供了关键契机。质子核磁共振和质谱是用于代谢谱分析的主要分析平台，能够检测和定量多种具有特定神经药理学和生理学相关性的化合物，包括神经递质、第二信使、结构脂质及其前体、中间体和降解产物。因此，通过探测健康或患病大脑在临床前模型或人类样本中的代谢和神经化学谱，代谢谱分析特别适用于中枢神经系统的研究。在本综述中，我们介绍了代谢谱分析的分析和统计要求。然后，我们重点关注代谢谱分析领域中应用于中枢神经系统疾病动物模型和人类样本特征化的关键研究。我们强调代谢谱分析在对患有脑部疾病的患者进行药理和生理评估、诊断及药物治疗监测方面的潜力。最后，我们讨论了该领域当前面临的挑战，包括系统生物学和药理学策略的发展，这些策略有助于增进我们对中枢神经系统疾病代谢特征和机制的理解。
