Chai Jiatong, Sun Zeyu, Xu Jiancheng
Department of Laboratory Medicine, The First Hospital of Jilin University, Changchun, People's Republic of China.
Diabetes Metab Syndr Obes. 2022 May 25;15:1605-1625. doi: 10.2147/DMSO.S357007. eCollection 2022.
High-throughput omics has been widely applied in metabolic disease, type 1 diabetes (T1D) was one of the most typical diseases. Effective prevention and early diagnosis are very important because of infancy and persistent characteristics of T1D. The occurrence and development of T1D is a chronic and continuous process, in which the production of autoantibodies (ie serum transformation) occupies the central position. Metabolomics can evaluate the metabolic characteristics of serum before seroconversion, the changes with age and T1D complications. And the addition of natural drug metabolomics is more conducive to the systematic and comprehensive diagnosis and treatment of T1D. This paper reviewed the metabolic changes and main pathogenesis from pre-diagnosis to treatment in T1D. The metabolic spectrum of significant abnormal energy and glucose-related metabolic pathway, down-regulation of lipid metabolism and up-regulation of some antioxidant pathways has appeared before seroconversion, indicating that the body has been in the dual state of disease progression and disease resistance before T1D onset. Some metabolites (such as methionine) are closely related to age, and the types of autoantibodies produced are age-specific. Some metabolites may jointly predict DN with eGFR, and metabolomics can further contribute to the pathogenesis based on the correlation between DN and DR. Many natural drug components have been proved to act on abnormal metabolic pathways of T1D and have a positive impact on some metabolic levels, which is very important for further finding therapeutic targets and developing new drugs with small side effects. Metabolomics can provide auxiliary value for the diagnosis of T1D and provide a new direction to reveal the pathogenesis of T1D and find new therapeutic targets. The development of T1D metabolomics shows that high-throughput research methods are expected to be introduced into clinical practice.
高通量组学已广泛应用于代谢性疾病,1型糖尿病(T1D)是最典型的疾病之一。由于T1D的发病初期和持续性特点,有效的预防和早期诊断非常重要。T1D的发生和发展是一个慢性且持续的过程,其中自身抗体的产生(即血清转化)占据核心地位。代谢组学可以评估血清转化前血清的代谢特征、随年龄的变化以及T1D并发症。而天然药物代谢组学的加入更有利于T1D的系统全面诊断和治疗。本文综述了T1D从诊断前到治疗过程中的代谢变化及主要发病机制。在血清转化前就已出现能量和葡萄糖相关代谢途径显著异常、脂质代谢下调以及一些抗氧化途径上调的代谢谱,表明机体在T1D发病前就已处于疾病进展和抗病的双重状态。一些代谢物(如蛋氨酸)与年龄密切相关,所产生的自身抗体类型具有年龄特异性。一些代谢物可能与估算肾小球滤过率(eGFR)共同预测糖尿病肾病(DN),基于DN与糖尿病视网膜病变(DR)的相关性,代谢组学可进一步阐明发病机制。许多天然药物成分已被证明作用于T1D的异常代谢途径,并对某些代谢水平产生积极影响,这对于进一步寻找治疗靶点和开发副作用小的新药非常重要。代谢组学可为T1D的诊断提供辅助价值,为揭示T1D的发病机制和寻找新的治疗靶点提供新方向。T1D代谢组学的发展表明,高通量研究方法有望引入临床实践。