Militello Rosamaria, Luti Simone, Modesti Alessandra
Department of Experimental and Clinical Biomedical Sciences, University of Florence, 50134 Florence, Italy.
Int J Mol Sci. 2025 Jun 10;26(12):5529. doi: 10.3390/ijms26125529.
The multiple health benefits of regular physical activity are well known and are the results of exercise adaptations. The study of physical training biology is not straightforward since it involves organ crosstalk and depends on numerous variables, such as type of exercise or individual physiology. A multiomic approach allows us to analyze proteins, metabolites, lipids, and epigenetic modifications on a wide scale, so it is a valid tool to identify numerous patterns and clarify how exercise exerts its beneficial effects. Stimuli given by physical activity lead the body to re-establish a new dynamic balance at the level of redox homeostasis and metabolic state. Evaluating the effect of specific training is important for maximizing the beneficial effects of physical activity. In this review we provide a brief overview of different omics technologies used in this field. For each "omics" we analyzed studies published in the last 10 years and highlighted the main molecules identified with that approach. We then described future challenges in their application from the perspective of using new bioinformatics and artificial intelligence tools.
规律体育活动对健康的多重益处广为人知,这些益处是运动适应性的结果。体育训练生物学的研究并非易事,因为它涉及器官间的相互作用,且取决于众多变量,如运动类型或个体生理状况。多组学方法使我们能够大规模分析蛋白质、代谢物、脂质和表观遗传修饰,因此它是识别众多模式并阐明运动如何发挥其有益作用的有效工具。体育活动所产生的刺激会促使身体在氧化还原稳态和代谢状态层面重新建立新的动态平衡。评估特定训练的效果对于最大化体育活动的有益效果至关重要。在本综述中,我们简要概述了该领域使用的不同组学技术。对于每种“组学”,我们分析了过去10年发表的研究,并突出了用该方法鉴定出的主要分子。然后,我们从使用新的生物信息学和人工智能工具的角度描述了它们应用中的未来挑战。