[基于非目标代谢组学方法的不明原因复发性自然流产血浆代谢标记物研究]。

Q Liu, L N Chen, Y M Li, J Sun, Y X Wang
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引用次数: 0

摘要

目的通过非目标代谢组学方法筛选不明原因复发性自然流产(URSA)患者的血浆代谢标记物。方法:2022 年 9 月至 2023 年 5 月:收集2022年9月至2023年5月在甘肃省妇幼保健院门诊就诊的23例URSA孕妇前3个月的血浆(URSA组),以及同期22例健康孕妇前3个月产前检查的血浆(正常对照组)。采用超高效液相色谱(UPLC)结合质谱(MS)对血浆代谢组学进行分析,运用折减分析、主成分分析和偏最小二乘法判别分析筛选差异代谢物,并利用接收者操作特征曲线(ROC)和通路富集分析筛选出与URSA相关的代谢物及其通路。结果显示URSA组与正常对照组在年龄、体重指数和孕周(所有PCI:0.920-1.000)、水苏碱(AUC=0.902,95%CI:0.786-0.982)、L-亮氨酸(AUC=0.884,95%CI:0.772-0.960)、仙客来(AUC=0.881,95%CI:0.758-0.956)、咖啡因(AUC=0.875,95%CI:0.756-0.962)和 4-羟基苯甲酸丙酯(AUC=0.864,95%CI:0.732-0.946)。通过六种代谢物综合诊断 URSA 的 AUC 为 0.983(95%CI:0.929-1.000)。对差异代谢物的通路富集分析表明,URSA的发病机制与多种代谢通路有关,包括咖啡因代谢、甘油磷脂代谢和不饱和脂肪酸的生物合成。结论正常妊娠与URSA孕妇在妊娠早期的血浆代谢谱存在差异,磷脂酰乙醇胺、水合山奈酚、L-亮氨酸、cembrene、咖啡因、4-羟基苯甲酸丙酯等六种潜在代谢物及其代谢途径可能与URSA的发病机制有关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
[Study of plasma metabolic markers in unexplained recurrent spontaneous abortion based on non-target metabolomics approach].

Objective: To screen plasma metabolic markers in patients with unexplained recurrent spontaneous abortion (URSA) by non-target metabolomics approach. Methods: From September 2022 to May 2023, the plasma of 23 URSA pregnant women with threatened abortion who visited the outpatient clinic of Gansu Provincial Maternity and Child-care Hospital in the first trimester (URSA group) was collected, and the plasma of 22 healthy pregnant women in the first trimester who underwent prenatal examination during the same period (normal control group) was collected. Plasma metabolomics was analyzed by ultra performance liquid chromatography (UPLC) coupled with mass spectrometry (MS), fold change analysis, principal component analysis and partial least square discriminant analysis were applied to screen for differential metabolites, and the metabolites and their pathways associated with URSA were screened using receiver operating characteristic (ROC) curve and pathway enrichment analysis. Results: There were no significant differences in age, body mass index and gestational weeks between URSA and normal control group(all P<0.05). Metabolomics analysis using UPLC-MS showed that a total of 526 metabolites were detected from plasma, of which 33 were found to be differential metabolites associated with URSA based on the screening standards. Six potential metabolites with large area under the curve (AUC) were identified by ROC curve analysis, including phosphatidylethanolamine (AUC=0.972, 95%CI: 0.920-1.000), santene hydrate (AUC=0.902, 95%CI: 0.786-0.982), L-leucine (AUC=0.884, 95%CI: 0.772-0.960), cembrene (AUC=0.881, 95%CI: 0.758-0.956), caffeine (AUC=0.875, 95%CI: 0.756-0.962), and 4-hydroxybenzoic acid propyl ester (AUC=0.864, 95%CI: 0.732-0.946). The AUC for the combined diagnosis of URSA by the six metabolites was 0.983 (95%CI: 0.929-1.000). Pathway enrichment analysis of the differential metabolites showed that the pathogenesis of URSA was associated with a variety of metabolic pathways including caffeine metabolism, glycerophospholipid metabolism, and unsaturated fatty acid biosynthesis. Conclusion: The plasma metabolic profiles of pregnant women with normal pregnancies versus URSA differ in early pregnancy, and six potential metabolites such as phosphatidylethanolamine, santene hydrate, L-leucine, cembrene, caffeine, 4-hydroxybenzoic acid propyl ester, and their metabolic pathways may be involved in the pathogenesis of URSA.

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