Medical Experimental Center, China Academy of Chinese Medical Sciences, Beijing 100700, China.
Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, China.
Nutrients. 2023 Sep 28;15(19):4191. doi: 10.3390/nu15194191.
(1) Many studies have attempted to utilize metabolomic approaches to explore potential biomarkers for the early detection of osteoarthritis (OA), but consistent and high-level evidence is still lacking. In this study, we performed a systematic review and meta-analysis of differential small molecule metabolites between OA patients and healthy individuals to screen promising candidates from a large number of samples with the aim of informing future prospective studies. (2) Methods: We searched the EMBASE, the Cochrane Library, PubMed, Web of Science, Wan Fang Data, VIP Date, and CNKI up to 11 August 2022, and selected relevant records based on inclusion criteria. The risk of bias was assessed using the Newcastle-Ottawa quality assessment scale. We performed qualitative synthesis by counting the frequencies of changing directions and conducted meta-analyses using the random effects model and the fixed-effects model to calculate the mean difference and 95% confidence interval. (3) Results: A total of 3798 records were identified and 13 studies with 495 participants were included. In the 13 studies, 132 kinds of small molecule differential metabolites were extracted, 58 increased, 57 decreased and 17 had direction conflicts. Among them, 37 metabolites appeared more than twice. The results of meta-analyses among four studies showed that three metabolites increased, and eight metabolites decreased compared to healthy controls (HC). (4) Conclusions: The main differential metabolites between OA and healthy subjects were amino acids (AAs) and their derivatives, including tryptophan, lysine, leucine, proline, phenylalanine, glutamine, dimethylglycine, citrulline, asparagine, acetylcarnitine and creatinine (muscle metabolic products), which could be potential biomarkers for predicting OA.
(1) 许多研究试图利用代谢组学方法来探索骨关节炎 (OA) 早期检测的潜在生物标志物，但仍缺乏一致和高水平的证据。在这项研究中，我们对 OA 患者与健康个体之间的差异小分子代谢物进行了系统评价和荟萃分析，旨在从大量样本中筛选有前途的候选物，为未来的前瞻性研究提供信息。
(2) 方法：我们检索了 EMBASE、Cochrane 图书馆、PubMed、Web of Science、万方数据、维普数据库和中国知网，截至 2022 年 8 月 11 日，并根据纳入标准筛选相关记录。使用纽卡斯尔-渥太华质量评估量表评估偏倚风险。我们通过计数变化方向的频率进行定性综合分析，并使用随机效应模型和固定效应模型进行荟萃分析，以计算均值差和 95%置信区间。
(3) 结果：共确定了 3798 条记录，纳入了 13 项研究，共 495 名参与者。在这 13 项研究中，提取了 132 种小分子差异代谢物，其中 58 种增加，57 种减少，17 种有方向冲突。其中，有 37 种代谢物出现了两次以上。四项研究的荟萃分析结果表明，与健康对照组相比，三种代谢物增加，八种代谢物减少。
(4) 结论：OA 患者与健康受试者之间的主要差异代谢物为氨基酸 (AAs)及其衍生物，包括色氨酸、赖氨酸、亮氨酸、脯氨酸、苯丙氨酸、谷氨酰胺、二甲基甘氨酸、瓜氨酸、天冬酰胺、乙酰肉碱和肌酸（肌肉代谢产物），这些代谢物可能是预测 OA 的潜在生物标志物。
