Institute of Systems Biology (INBIOSIS), Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia.
Methods Mol Biol. 2024;2745:77-90. doi: 10.1007/978-1-0716-3577-3_5.
Metabolomics can provide diagnostic, prognostic, and therapeutic biomarker profiles of individual patients because a large number of metabolites can be simultaneously measured in biological samples in an unbiased manner. Minor stimuli can result in substantial alterations, making it a valuable target for analysis. Due to the complexity and sensitivity of the metabolome, studies must be devised to maintain consistency, minimize subject-to-subject variation, and maximize information recovery. This effort has been aided by technological advances in experimental design, rodent models, and instrumentation. Proton Nuclear Magnetic Resonance (H-NMR) spectroscopy of biofluids, such as plasma, urine, and faeces provide the opportunity to identify biomarker change patterns that reflect the physiological or pathological status of an individual patient. Metabolomics has the ultimate potential to be useful in a clinical context, where it could be used to predict treatment response and survival and for early disease diagnosis. During drug treatment, an individual's metabolic status could be monitored and used to predict deleterious effects. Therefore, metabolomics has the potential to improve disease diagnosis, treatment, and follow-up care. In this chapter, we demonstrate how a metabolomics study can be used to diagnose a disease by classifying patients as either healthy or pathological, while accounting for individual variation.
代谢组学可以为个体患者提供诊断、预后和治疗生物标志物谱,因为可以以无偏倚的方式同时测量生物样本中的大量代谢物。微小的刺激也会导致实质性的改变,使其成为分析的有价值的目标。由于代谢组的复杂性和敏感性,必须设计研究来保持一致性,最大限度地减少个体间的变异,并最大限度地恢复信息。实验设计、啮齿动物模型和仪器方面的技术进步为此提供了帮助。生物流体(如血浆、尿液和粪便)的质子磁共振(H-NMR)光谱分析提供了识别生物标志物变化模式的机会,这些模式反映了个体患者的生理或病理状态。代谢组学最终有可能在临床环境中得到应用,它可以用于预测治疗反应和生存,以及早期疾病诊断。在药物治疗期间,可以监测个体的代谢状态,并用于预测有害影响。因此,代谢组学有可能改善疾病诊断、治疗和随访护理。在本章中,我们展示了如何通过对患者进行健康或病理分类来进行疾病诊断,同时考虑到个体差异。