Metabolomic analyses of multiple biologic matrices reveal metabolic heterogeneity in diabetic complications.

IF 3.1 3区 医学 Q2 ENDOCRINOLOGY & METABOLISM
Yao Huang, Wuping Liu, Ge Song, Sheng Wu, Xuejun Li, Guiping Shen, Jianghua Feng
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Abstract

Aims: Type 2 diabetes mellitus (T2DM) arises from a complex interplay of genetic and environmental factors. Patients with T2DM are susceptible to hyperglycemia-related complications that can impair organ function, underscoring the need to explore the metabolic profiles of affected organs.

Methods: In this study, a comprehensive metabolomic analysis was conducted on the serum, kidney, and heart tissues from a rat model of diabetic complications (DC). Pattern recognition and multivariate statistical analyses were applied to identify the potential biomarkers of DC, and metabolic network analysis served to understand the specific metabolic pathways associated with DC.

Results: Fourteen significantly altered metabolites were identified in serum, 20 in the kidney, and 14 in the heart. The corresponding metabolic pathways included mineral absorption, mTOR signaling pathway, taurine and hypotaurine metabolism, glycine, serine and threonine metabolism, ABC transporters, glucagon signaling pathway, protein degradation and uptake, galactose metabolism, purine metabolism, nicotinic acid and nicotinamide metabolism, and glycolysis and gluconeogenesis. Differential metabolite network analysis revealed instinct metabolic patterns among the serum, kidney, and heart. Notably, the serum's metabolic correlation patterns were found to be somewhat similar to those observed in the kidney, whereas the heart exhibited less pronounced metabolite correlations compared to the other two biological matrices.

Conclusions: These findings provide insights into the mechanism underlying the development of diabetic complications. The integration of metabolomics and biological network analyses into diabetes research can potentially revolutionize the field by revealing novel biomarkers for early detection and personalized treatment of diabetes and its associated complications.

多种生物基质代谢组学分析揭示了糖尿病并发症的代谢异质性。
目的:2型糖尿病(T2DM)是遗传和环境因素复杂相互作用的结果。T2DM患者易患高血糖相关并发症,这些并发症可损害器官功能,因此有必要研究受影响器官的代谢特征。方法:对糖尿病并发症(DC)大鼠模型的血清、肾脏和心脏组织进行代谢组学分析。模式识别和多元统计分析用于识别DC的潜在生物标志物,代谢网络分析用于了解与DC相关的特定代谢途径。结果:在血清中鉴定出14种显著改变的代谢物,在肾脏中鉴定出20种,在心脏中鉴定出14种。相应的代谢途径包括矿物质吸收、mTOR信号通路、牛磺酸和次牛磺酸代谢、甘氨酸、丝氨酸和苏氨酸代谢、ABC转运蛋白、胰高血糖素信号通路、蛋白质降解和摄取、半乳糖代谢、嘌呤代谢、烟酸和烟酰胺代谢、糖酵解和糖异生。差异代谢物网络分析揭示了血清、肾脏和心脏之间的本能代谢模式。值得注意的是,血清的代谢相关模式被发现与在肾脏中观察到的有些相似,而与其他两种生物基质相比,心脏表现出的代谢物相关性不那么明显。结论:这些发现为糖尿病并发症的发生机制提供了新的见解。将代谢组学和生物网络分析整合到糖尿病研究中,通过揭示糖尿病及其相关并发症的早期检测和个性化治疗的新生物标志物,可能会给该领域带来革命性的变化。
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来源期刊
Acta Diabetologica
Acta Diabetologica 医学-内分泌学与代谢
CiteScore
7.30
自引率
2.60%
发文量
180
审稿时长
2 months
期刊介绍: Acta Diabetologica is a journal that publishes reports of experimental and clinical research on diabetes mellitus and related metabolic diseases. Original contributions on biochemical, physiological, pathophysiological and clinical aspects of research on diabetes and metabolic diseases are welcome. Reports are published in the form of original articles, short communications and letters to the editor. Invited reviews and editorials are also published. A Methodology forum, which publishes contributions on methodological aspects of diabetes in vivo and in vitro, is also available. The Editor-in-chief will be pleased to consider articles describing new techniques (e.g., new transplantation methods, metabolic models), of innovative importance in the field of diabetes/metabolism. Finally, workshop reports are also welcome in Acta Diabetologica.
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