Lista Simone, González-Domínguez Raúl, López-Ortiz Susana, González-Domínguez Álvaro, Menéndez Héctor, Martín-Hernández Juan, Lucia Alejandro, Emanuele Enzo, Centonze Diego, Imbimbo Bruno P, Triaca Viviana, Lionetto Luana, Simmaco Maurizio, Cuperlovic-Culf Miroslava, Mill Jericha, Li Lingjun, Mapstone Mark, Santos-Lozano Alejandro, Nisticò Robert
i+HeALTH Strategic Research Group, Department of Health Sciences, Miguel de Cervantes European University (UEMC), Valladolid, Spain.
Instituto de Investigación e Innovación Biomédica de Cádiz (INiBICA), Hospital Universitario Puerta del Mar, Universidad de Cádiz, Cádiz, Spain.
Ageing Res Rev. 2023 Aug;89:101987. doi: 10.1016/j.arr.2023.101987. Epub 2023 Jun 19.
Alzheimer's disease (AD) is determined by various pathophysiological mechanisms starting 10-25 years before the onset of clinical symptoms. As multiple functionally interconnected molecular/cellular pathways appear disrupted in AD, the exploitation of high-throughput unbiased omics sciences is critical to elucidating the precise pathogenesis of AD. Among different omics, metabolomics is a fast-growing discipline allowing for the simultaneous detection and quantification of hundreds/thousands of perturbed metabolites in tissues or biofluids, reproducing the fluctuations of multiple networks affected by a disease. Here, we seek to critically depict the main metabolomics methodologies with the aim of identifying new potential AD biomarkers and further elucidating AD pathophysiological mechanisms. From a systems biology perspective, as metabolic alterations can occur before the development of clinical signs, metabolomics - coupled with existing accessible biomarkers used for AD screening and diagnosis - can support early disease diagnosis and help develop individualized treatment plans. Presently, the majority of metabolomic analyses emphasized that lipid metabolism is the most consistently altered pathway in AD pathogenesis. The possibility that metabolomics may reveal crucial steps in AD pathogenesis is undermined by the difficulty in discriminating between the causal or epiphenomenal or compensatory nature of metabolic findings.
阿尔茨海默病（AD）由临床症状出现前10至25年起的多种病理生理机制所决定。由于AD中多个功能相互关联的分子/细胞途径似乎遭到破坏，利用高通量无偏倚组学科学对于阐明AD的确切发病机制至关重要。在不同的组学中，代谢组学是一门快速发展的学科，它能够同时检测和定量组织或生物流体中数百/数千种受干扰的代谢物，再现受疾病影响的多个网络的波动情况。在此，我们旨在批判性地描述主要的代谢组学方法，以识别新的潜在AD生物标志物，并进一步阐明AD的病理生理机制。从系统生物学角度来看，由于代谢改变可能在临床症状出现之前就已发生，代谢组学与现有的用于AD筛查和诊断的可获取生物标志物相结合，能够支持疾病的早期诊断，并有助于制定个性化治疗方案。目前，大多数代谢组学分析强调脂质代谢是AD发病机制中最持续改变的途径。代谢组学可能揭示AD发病机制关键步骤的可能性因难以区分代谢结果的因果、偶发现象或代偿性质而受到削弱。
