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代谢组学和脂质组学在代谢综合征研究中的应用:对心血管疾病、1 型和 2 型糖尿病以及代谢功能障碍相关脂肪性肝病的深入了解。

Metabolomics and Lipidomics for Studying Metabolic Syndrome: Insights into Cardiovascular Diseases, Type 1 & 2 Diabetes, and Metabolic Dysfunction-Associated Steatotic Liver Disease.

机构信息

Laboratory of Translational Metabolism, Institute of Physiology of the Czech Academy of Sciences, Prague, Czech Republic.

出版信息

Physiol Res. 2024 Aug 30;73(S1):S165-S183. doi: 10.33549/physiolres.935443.

Abstract

Metabolomics and lipidomics have emerged as tools in understanding the connections of metabolic syndrome (MetS) with cardiovascular diseases (CVD), type 1 and type 2 diabetes (T1D, T2D), and metabolic dysfunction-associated steatotic liver disease (MASLD). This review highlights the applications of these omics approaches in large-scale cohort studies, emphasizing their role in biomarker discovery and disease prediction. Integrating metabolomics and lipidomics has significantly advanced our understanding of MetS pathology by identifying unique metabolic signatures associated with disease progression. However, challenges such as standardizing analytical workflows, data interpretation, and biomarker validation remain critical for translating research findings into clinical practice. Future research should focus on optimizing these methodologies to enhance their clinical utility and address the global burden of MetS-related diseases.

摘要

代谢组学和脂质组学已经成为理解代谢综合征 (MetS) 与心血管疾病 (CVD)、1 型和 2 型糖尿病 (T1D、T2D) 以及代谢功能障碍相关脂肪性肝病 (MASLD) 之间关系的工具。本综述重点介绍了这些组学方法在大规模队列研究中的应用,强调了它们在生物标志物发现和疾病预测中的作用。通过鉴定与疾病进展相关的独特代谢特征,代谢组学和脂质组学的整合显著促进了我们对 MetS 病理学的理解。然而,标准化分析工作流程、数据解释和生物标志物验证等挑战仍然是将研究结果转化为临床实践的关键。未来的研究应侧重于优化这些方法,以提高其临床实用性,并解决与 MetS 相关疾病的全球负担。

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