利用 UPLC-MS/MS 通过血清氨基酸代谢组学分析鉴定用于虚弱诊断的新型生物标记物。

IF 2.1 4区 生物学 Q3 BIOCHEMICAL RESEARCH METHODS PROTEOMICS – Clinical Applications Pub Date : 2024-05-01 Epub Date: 2024-01-09 DOI:10.1002/prca.202300035
Mengyuan Zhou, Wenjing Sun, Jiaojiao Chu, Yingping Liao, Pengfei Xu, Xujiao Chen, Meng Li
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引用次数: 0

摘要

目的:本研究旨在分析虚弱患者的血清氨基酸代谢物谱,更好地了解虚弱的代谢机制,并评估基于代谢组学的虚弱生物标志物的诊断价值:本研究采用超高效液相色谱串联质谱法检测与虚弱相关的氨基酸。此外,我们还采用了多元统计方法、代谢组数据分析、接收者操作特征曲线(ROC)分析和通路富集分析:结果:在检测的氨基酸代谢物中,我们发现了虚弱的生物标志物。基于改良弗里德虚弱指数的虚弱诊断 ROC 曲线分析表明,色氨酸、苯丙氨酸、天冬氨酸和组合的 ROC 曲线下面积分别为 0.775、0.679、0.667 和 0.807。基于虚弱量表的虚弱诊断 ROC 曲线分析显示,胱氨酸、苯丙氨酸和氨基酸组合(胱氨酸、L-谷氨酰胺、瓜氨酸、酪氨酸、犬尿氨酸、苯丙氨酸、谷氨酰胺酸)的 ROC 曲线下面积分别为 0.834、0.708 和 0.854:本研究探讨了体弱患者的血清氨基酸代谢谱。这些代谢分析可为虚弱的潜在生物标志物和可能的致病机制提供有价值的信息:临床意义:虚弱是一种临床综合征,因此,即使根据现有的虚弱量表,也很难在疾病的早期进行识别。早期诊断和适当的患者管理是提高虚弱患者生存率和限制残疾的关键。大量有关虚弱的实验室和临床研究证明,全面分析虚弱患者的代谢水平、确定生物标志物和研究代谢物的致病途径有助于预测和早期诊断虚弱。在这项研究中,我们探讨了虚弱患者的血清氨基酸代谢物谱。这些代谢分析可为虚弱的潜在生物标志物和可能的致病机制提供有价值的信息。
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Identification of novel biomarkers for frailty diagnosis via serum amino acids metabolomic analysis using UPLC-MS/MS.

Purpose: This study was aimed to analyze serum amino acid metabolite profiles in frailty patients, gain a better understanding of the metabolic mechanisms in frailty, and assess the diagnostic value of metabolomics-based biomarkers of frailty.

Experimental design: This study utilized the ultra-performance liquid chromatography tandem mass spectrometry to examine amino acids associated with frailty. Additionally, we employed multivariate statistical methods, metabolomic data analysis, receiver operating characteristic (ROC) curve analysis, and pathway enrichment analysis.

Results: Among the assayed amino acid metabolites, we identified biomarkers for frailty. ROC curve analysis for frailty diagnosis based on the modified Fried's frailty index showed that the areas under ROC curve of tryptophan, phenylalanine, aspartic acid, and combination were 0.775, 0.679, 0.667, and 0.807, respectively. ROC curve analysis for frailty diagnosis based on Frail Scale showed that the areas under ROC curve of cystine, phenylalanine, and combination of amino acids (cystine, L-Glutamine, citrulline, tyrosine, kynurenine, phenylalanine, glutamin acid) were 0.834, 0.708, and 0.854 respectively.

Conclusion and clinical relevance: In this study, we explored the serum amino acid metabolite profiles in frailty patients. These present metabolic analyses may provide valuable information on the potential biomarkers and the possible pathogenic mechanisms of frailty.

Clinical significance: Frailty is a clinical syndrome, as a consequence it is challenging to identify at early course of the disease, even based on the existing frailty scales. Early diagnosis and appropriate patient management are the key to improve the survival and limit disabilities in frailty patients. Proven by the extensive laboratory and clinical studies on frailty, comprehensive analysis of metabolic levels in frail patients, identification of biomarkers and study of pathogenic pathways of metabolites contribute to the prediction and early diagnosis of frailty. In this study, we explored the serum amino acid metabolite profiles in frailty patients. These present metabolic analyses may provide valuable information on the potential biomarkers and the possible pathogenic mechanisms of frailty.

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来源期刊
PROTEOMICS – Clinical Applications
PROTEOMICS – Clinical Applications 医学-生化研究方法
CiteScore
5.20
自引率
5.00%
发文量
50
审稿时长
1 months
期刊介绍: PROTEOMICS - Clinical Applications has developed into a key source of information in the field of applying proteomics to the study of human disease and translation to the clinic. With 12 issues per year, the journal will publish papers in all relevant areas including: -basic proteomic research designed to further understand the molecular mechanisms underlying dysfunction in human disease -the results of proteomic studies dedicated to the discovery and validation of diagnostic and prognostic disease biomarkers -the use of proteomics for the discovery of novel drug targets -the application of proteomics in the drug development pipeline -the use of proteomics as a component of clinical trials.
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