Fernandes Silva Lilian, Laakso Markku
Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, 70210 Kuopio, Finland.
Division of Cardiology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA.
Int J Mol Sci. 2025 Apr 10;26(8):3572. doi: 10.3390/ijms26083572.
Type 2 diabetes (T2D) and cardiovascular diseases (CVDs) are major public health challenges worldwide. Metabolomics, the exhaustive assessment of metabolites in biological systems, offers important insights regarding the metabolic disturbances related to these disorders. Recent advances toward the integration of metabolomics into clinical practice to facilitate the discovery of novel biomarkers that can improve the diagnosis, prognosis, and treatment of T2D and CVDs are discussed in this review. Metabolomics offers the potential to characterize the key metabolic alterations associated with disease pathophysiology and treatment. T2D is a heterogeneous disease that develops through diverse pathophysiological processes and molecular mechanisms; therefore, the disease-causing pathways of T2D are not completely understood. Recent studies have identified several robust clusters of T2D variants representing biologically meaningful, distinct pathways, such as the beta cell and proinsulin cluster related to pancreatic insulin secretion, obesity, lipodystrophy, the liver/lipid cluster, glycemia, and blood pressure, and metabolic syndrome clusters representing different pathways causing insulin resistance. Regarding CVDs, recent studies have allowed the metabolomic profile to delineate pathways that contribute to atherosclerosis and heart failure, as well as to the development of targeted therapy. This review also covers the role of metabolomics in integrated metabolic genomics and other omics platforms to better understand disease mechanisms, along with the transition toward precision medicine. This review further investigates the use of metabolomics in multi-metabolite modeling to enhance risk prediction models for predicting the first occurrence of major adverse cardiovascular events among individuals with T2D, highlighting the value of such approaches in optimizing the preventive and therapeutic models used in clinical practice.
2型糖尿病（T2D）和心血管疾病（CVD）是全球主要的公共卫生挑战。代谢组学是对生物系统中代谢物进行详尽评估，它为这些疾病相关的代谢紊乱提供了重要见解。本综述讨论了代谢组学融入临床实践的最新进展，以促进发现可改善T2D和CVD诊断、预后及治疗的新型生物标志物。代谢组学有潜力表征与疾病病理生理学和治疗相关的关键代谢改变。T2D是一种异质性疾病，通过多种病理生理过程和分子机制发展而来；因此，T2D的致病途径尚未完全明确。最近的研究已经确定了几个强有力的T2D变异簇，代表生物学上有意义的、不同的途径，如与胰腺胰岛素分泌、肥胖、脂肪营养不良、肝脏/脂质簇、血糖和血压相关的β细胞和胰岛素原簇，以及代表导致胰岛素抵抗的不同途径的代谢综合征簇。关于CVD，最近的研究使代谢组学特征能够描绘出促成动脉粥样硬化和心力衰竭的途径，以及靶向治疗的发展。本综述还涵盖了代谢组学在整合代谢基因组学和其他组学平台中的作用，以更好地理解疾病机制，以及向精准医学的转变。本综述进一步研究了代谢组学在多代谢物建模中的应用，以增强预测T2D个体首次发生主要不良心血管事件的风险预测模型，强调了这些方法在优化临床实践中使用的预防和治疗模型方面的价值。
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