National Clinical Research Center for Metabolic Diseases, Metabolic Syndrome Research Center, Key Laboratory of Diabetes Immunology, Ministry of Education, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
Department of Dermatology, Hunan Key Laboratory of Medical Epigenomics, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
Front Cell Infect Microbiol. 2023 Mar 29;13:1165647. doi: 10.3389/fcimb.2023.1165647. eCollection 2023.
Dysregulation of metabolism plays an important role in the onset and progression of multiple pathogenic diseases, including viral hepatitis. However, a model to predict viral hepatitis risk by metabolic pathways is still lacking. Thus, we developed two risk assessment models for viral hepatitis based on metabolic pathways identified through univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analysis. The first model is designed to assess the progression of the disease by evaluating changes in the Child-Pugh class, hepatic decompensation, and the development of hepatocellular carcinoma. The second model is focused on determining the prognosis of the illness, taking into account the patient's cancer status. Our models were further validated by Kaplan-Meier plots of survival curves. In addition, we investigated the contribution of immune cells in metabolic processes and identified three distinct subsets of immune cells-CD8+ T cells, macrophages, and NK cells-that have significantly affected metabolic pathways. Specifically, our findings suggest that resting or inactive macrophages and NK cells contribute to maintaining metabolic homeostasis, particularly with regard to lipid and α-amino acid metabolism, thereby potentially reducing the risk of viral hepatitis progression. Moreover, maintaining metabolic homeostasis ensures a balance between killer-proliferative and exhausted CD8+ T cells, which helps in mitigating CD8+ T cell-mediated liver damage while preserving energy reserves. In conclusion, our study offers a useful tool for early disease detection in viral hepatitis patients through metabolic pathway analysis and sheds light on the immunological understanding of the disease through the examination of immune cell metabolic disorders.
代谢失调在多种致病疾病的发生和进展中起着重要作用，包括病毒性肝炎。然而，仍然缺乏通过代谢途径预测病毒性肝炎风险的模型。因此，我们通过单变量和最小绝对收缩和选择算子（LASSO）Cox 回归分析确定代谢途径，开发了两种基于代谢途径的病毒性肝炎风险评估模型。第一个模型旨在通过评估 Child-Pugh 分级、肝失代偿和肝细胞癌的发展来评估疾病的进展。第二个模型侧重于考虑患者的癌症状况来确定疾病的预后。我们的模型进一步通过生存曲线的 Kaplan-Meier 图进行验证。此外，我们研究了免疫细胞在代谢过程中的作用，并确定了三个不同的免疫细胞亚群——CD8+T 细胞、巨噬细胞和 NK 细胞，它们显著影响了代谢途径。具体来说，我们的研究结果表明，静止或非激活的巨噬细胞和 NK 细胞有助于维持代谢稳态，特别是在脂质和α-氨基酸代谢方面，从而可能降低病毒性肝炎进展的风险。此外，维持代谢稳态确保了杀伤增殖和耗竭的 CD8+T 细胞之间的平衡，有助于减轻 CD8+T 细胞介导的肝损伤，同时保持能量储备。总之，我们的研究通过代谢途径分析为病毒性肝炎患者的早期疾病检测提供了一种有用的工具，并通过检查免疫细胞代谢紊乱为疾病的免疫学理解提供了新的视角。
