Disease Biomarkers and Molecular Mechanisms Group, Institut d'Investigació Sanitària Pere Virgili (IISPV), Universitat Rovira i Virgili, Tarragona, Spain.
Rheumatology Department, Joan XXIII University Hospital, Tarragona, Spain.
Front Immunol. 2023 Sep 1;14:1253913. doi: 10.3389/fimmu.2023.1253913. eCollection 2023.
There 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.
We 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.
Significant 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.
A metabolomics serum-based biomarker panel composed of glyceric acid, lactic acid, and 3-hydroxisovaleric acid offers potential for the early clinical diagnosis of RA.
需要新型生物标志物来改善类风湿关节炎（ERA）的早期诊断。目前用于 ERA 管理的血清生物标志物，包括类风湿因子和抗环瓜氨酸肽（ACPA），特异性和敏感性有限。本研究采用代谢组学方法来发现 ERA 的新血清生物标志物。
我们应用非靶向代谢组学方法，包括气相色谱飞行时间质谱法，对 ERA 队列（n=32）和健康对照组（n=19）的血清样本进行分析。采用代谢物集富集分析探索潜在的重要生物学途径。采用偏最小二乘判别分析和变量重要性投影分析构建 ERA 生物标志物组合。
在 ERA 患者的血清中鉴定出 11/81 种代谢物含量存在显著差异。ROC 分析表明，仅由三种代谢物（甘油酸、乳酸和 3-羟基异戊酸）组成的面板可正确分类 96.7%的 ERA 患者，ROC 曲线下面积为 0.963，具有 94.4%的特异性和 93.5%的敏感性，优于基于 ACPA 的诊断，提高了 ERA 的临床前检测。氨基酸酰基-tRNA 合成和丝氨酸、甘氨酸和苯丙氨酸代谢是 ERA 患者最显著失调的途径。
由甘油酸、乳酸和 3-羟基异戊酸组成的基于代谢组学的血清生物标志物组合为 RA 的早期临床诊断提供了潜力。
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