神灵白术散治疗营养不良性老年人多器官功能障碍综合征(MODSE)的代谢组学研究

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC ACS Applied Electronic Materials Pub Date : 2024-08-28 DOI:10.1016/j.jpba.2024.116423
Hui Wang , Xuemei Fan , Fuguo Han , Haiyan Hao , Xiaowen Xu , Yanli Hao , Zhiguang Sun , Zhengguang Li , Qingfei Liu
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引用次数: 0

摘要

营养不良是老年多器官功能障碍综合征(MODSE)的重要危险因素,严重影响MODSE的发生、发展和预后。神灵白术散(SBP)是传统中医的经典方剂,与肠内营养相结合,已被证实是治疗营养不良型MODSE患者的有效临床策略。本研究旨在探讨疾病发生和SBP治疗过程中的代谢变化,并发现潜在的代谢生物标志物用于诊断和疗效评估。该研究采用基于 UHPLC-Q-Orbitrap-HRMS 的非靶向代谢组学策略,揭示了营养不良 MODSE 患者(59 人)与健康对照组(33 人)之间、肠内营养治疗患者(31 人)与 SBP 联合肠内营养治疗患者(28 人)之间血清代谢物的差异。研究人员发现了明显不同的代谢物,并将其映射到代谢通路网络中,以探索该疾病导致的代谢紊乱以及 SBP 的代谢调控机制。此外,还研究了潜在生物标志物的曲线下面积(AUC),以预测疾病和 SBP 的疗效。研究发现,疾病组和对照组之间存在 60 种差异代谢物,主要与氨基酸代谢、能量代谢和碳水化合物代谢有关。同样,还发现了 50 个与 SBP 治疗相关的差异代谢物,它们主要通过调节上述代谢途径来改善体内代谢异常。最后,13 个共同的差异代谢物被选为潜在的生物标志物,每个生物标志物的 AUC 值均在 0.8-1.0 范围内,表明这些生物标志物对营养不良 MODSE 的诊断和疗效评估具有较高的预测准确性。本研究表明,基于超高效液相色谱-Q-Orbitrap-HRMS平台的血清代谢组学方法可作为一种工具,用于揭示营养不良型MODSE引起的代谢变化,而SBP在临床应用中可发挥重要作用。
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Metabolomics study of Shenling Baizhu Powder in the treatment of multiple organ dysfunction syndrome in the elderly (MODSE) with malnutrition

Malnutrition is an important risk factor for multiple organ dysfunction syndrome in the elderly (MODSE) and seriously affects the occurrence, progression and prognosis of MODSE. Shenling Baizhu Power (SBP), a classic formula from traditional Chinese medicine (TCM), when integrated with enteral nutrition, has been proven to be an effective clinical strategy for treating the patients of MODSE with malnutrition. This study aimed to investigate the metabolic changes during disease occurrence and SBP treatment, and to discover potential metabolic biomarkers for the diagnosis and efficacy evaluation. An untargeted metabolomics strategy based on UHPLC-Q-Orbitrap-HRMS was performed to reveal the differential serum metabolites between MODSE patients with malnutrition (n=59) and healthy controls (n=33), and those between patients treated with enteral nutrition (n=31) and SBP combined with enteral nutrition (n=28). Significantly different metabolites were identified and mapped onto the network of metabolic pathways to explore the metabolic disorders caused by the disease and the metabolic regulatory mechanism of SBP. Additionally, the area under the curve (AUC) of the potential biomarkers was investigated for predicting the disease and the efficacy of SBP. Sixty differential metabolites were identified between the disease and control groups, which were mainly related to amino acid metabolism, energy metabolism and carbohydrate metabolism. In the same way, 50 differential metabolites associated with SBP treatment were identified, which improved metabolic abnormalities in vivo mainly by regulating the above-mentioned metabolic pathways. Finally, 13 differential metabolites in common were selected as the potential biomarkers and the AUC value of each biomarker was within the range of 0.8–1.0, indicating that these biomarkers had high prediction accuracy for the diagnosis and efficacy evaluation of MODSE with malnutrition. This study demonstrates that serum metabolomics approaches based on the UHPLC-Q-Orbitrap-HRMS platform can be applied as a tool to reveal the metabolic changes induced by MODSE with malnutrition and SBP can play an important role in the clinical application.

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4.30%
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567
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