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Table_2_A serum metabolic biomarker panel for early rheumatoid arthritis.pdf

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figshare.com2023-09-01 更新2025-01-22 收录
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https://figshare.com/articles/dataset/Table_2_A_serum_metabolic_biomarker_panel_for_early_rheumatoid_arthritis_pdf/24070554/1
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ObjectiveThere is an urgent need for novel biomarkers to improve the early diagnosis of rheumatoid arthritis (ERA). Current serum biomarkers used in the management of ERA, including rheumatoid factor and anti-cyclic citrullinated peptide (ACPA), show limited specificity and sensitivity. Here, we used metabolomics to uncover new serum biomarkers of ERA.MethodsWe applied an untargeted metabolomics approach including gas chromatography time-of-flight mass spectrometry in serum samples from an ERA cohort (n=32) and healthy controls (n=19). Metabolite set enrichment analysis was performed to explore potentially important biological pathways. Partial least squares discriminant analysis and variable importance in projection analysis were performed to construct an ERA biomarker panel.ResultsSignificant differences in the content of 11/81 serum metabolites were identified in patients with ERA. Receiver operating characteristic (ROC) analysis showed that a panel of only three metabolites (glyceric acid, lactic acid, and 3-hydroxisovaleric acid) could correctly classify 96.7% of patients with ERA, with an area under the ROC curve of 0.963 and with 94.4% specificity and 93.5% sensitivity, outperforming ACPA-based diagnosis by 2.9% and, thus, improving the preclinical detection of ERA. Aminoacyl-tRNA biosynthesis and serine, glycine, and phenylalanine metabolism were the most significant dysregulated pathways in patients with ERA.ConclusionA metabolomics serum-based biomarker panel composed of glyceric acid, lactic acid, and 3-hydroxisovaleric acid offers potential for the early clinical diagnosis of RA.

研究目的:针对类风湿性关节炎(RA)的早期诊断,迫切需要开发新的生物标志物。目前用于RA管理的血清生物标志物,包括类风湿因子和抗环状瓜氨酸肽(ACPA),在特异性和敏感性方面均表现出一定的局限性。本研究中,我们采用代谢组学方法,旨在揭示新的RA血清生物标志物。研究方法:我们采用非靶向代谢组学方法,包括气相色谱-飞行时间质谱联用技术,对32例RA患者和19例健康对照组的血清样本进行了分析。通过代谢物集富集分析,探索潜在的生物学通路。采用偏最小二乘判别分析和变量重要性投影分析构建了RA生物标志物面板。研究结果:在11/81种血清代谢物中,RA患者的含量存在显著差异。受试者工作特征(ROC)分析表明,仅由三种代谢物(甘油酸、乳酸和3-羟基异戊酸)组成的面板能够正确分类96.7%的RA患者,ROC曲线下面积为0.963,特异性为94.4%,敏感性为93.5%,优于基于ACPA的诊断,从而提高了RA的早期临床检测。在RA患者中,氨基酸酰-tRNA生物合成以及丝氨酸、甘氨酸和苯丙氨酸代谢是最显著失调的通路。研究结论:由甘油酸、乳酸和3-羟基异戊酸组成的代谢组学血清生物标志物面板,为RA的早期临床诊断提供了潜在价值。
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