Systems Biology, School of Biosciences and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK.
Centre for Mathematical and Computational Biology, CMCB, University of Surrey, Guildford, UK.
Clin Transl Med. 2022 Jul;12(7):e898. doi: 10.1002/ctm2.898.
Increasing efforts points to the understanding of how to maximize the capabilities of the adaptive immune system to fight against the development of immune and inflammatory disorders. Here we focus on the role of T cells as immune cells which subtype imbalance may lead to disease onset. Specifically, we propose that autoimmune disorders may develop as a consequence of a metabolic imbalance that modulates switching between T cell phenotypes. We highlight a Systems Biology strategy that integrates computational metabolic modelling with experimental data to investigate the metabolic requirements of T cell phenotypes, and to predict metabolic genes that may be targeted in autoimmune inflammatory diseases. Thus, we propose a new perspective of targeting T cell metabolism to modulate the immune response and prevent T cell phenotype imbalance, which may help to repurpose already existing drugs targeting metabolism for therapeutic treatment.
越来越多的研究表明，人们已经了解到如何最大限度地发挥适应性免疫系统的能力，以对抗免疫和炎症性疾病的发展。在这里，我们专注于 T 细胞作为免疫细胞的作用，其亚群失衡可能导致疾病的发生。具体来说，我们提出自身免疫性疾病可能是由于代谢失衡引起的，这种失衡调节了 T 细胞表型之间的转换。我们强调了一种系统生物学策略，该策略将计算代谢建模与实验数据相结合，以研究 T 细胞表型的代谢需求，并预测可能成为自身免疫性炎症性疾病靶点的代谢基因。因此，我们提出了一种新的观点，即靶向 T 细胞代谢以调节免疫反应并防止 T 细胞表型失衡，这可能有助于重新利用已经存在的针对代谢的药物进行治疗。
