Yu Zhaoer, Wang Yixiao, Fan Lili, Xiang Jinfeng, Wang Hanwei, Xu Linjie, Jia Ruizhe
Department of Obstetrics and Gynecology, Women's Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing 210004, China.
Department of Obstetrics, Women and Children's Hospital, School of Medicine, Xiamen University, Xiamen 361000, China.
J Proteome Res. 2025 Feb 7;24(2):491-498. doi: 10.1021/acs.jproteome.4c00623. Epub 2025 Jan 6.
This study used untargeted lipidomics to analyze the characteristics of lipid metabolism in the serum of women with antiphospholipid syndrome. Twenty female patients with APS and 20 healthy controls were recruited to this study. Untargeted lipidomics with liquid chromatography-tandem mass spectrometry was used to profile serum lipids. Correlation analyses were performed on the significant differential lipids. Least absolute shrinkage and selection operator (LASSO) regression and binary logistic regression analyses were performed to find possible biomarkers. Finally, receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance of biomarkers. The serum lipid profile of women with APS was significantly different from that of healthy controls. After statistical analysis and database matching, 12 lipids were found to be significantly different between the two groups, with the most obvious differences being triacylglycerols and phosphatidylcholines. LASSO regression and binary logistic regression models revealed that PC (17:0/22:6) and ACar (17:3) may be serum biomarkers of APS. ROC curve analysis shows that PC (17:0/22:6) and ACar (17:3) combined gave an area under the curve of 0.865 for the diagnosis of APS. PC (17:0/22:6) and ACar (17:3) could be used as biomarkers of APS.
本研究采用非靶向脂质组学分析抗磷脂综合征女性血清中的脂质代谢特征。本研究招募了20例抗磷脂综合征女性患者和20例健康对照。采用液相色谱-串联质谱非靶向脂质组学技术对血清脂质进行分析。对显著差异脂质进行相关性分析。进行最小绝对收缩和选择算子（LASSO）回归及二元逻辑回归分析以寻找可能的生物标志物。最后，采用受试者工作特征（ROC）曲线分析评估生物标志物的诊断性能。抗磷脂综合征女性的血清脂质谱与健康对照有显著差异。经统计分析和数据库匹配，发现两组之间有12种脂质存在显著差异，其中三酰甘油和磷脂酰胆碱的差异最为明显。LASSO回归和二元逻辑回归模型显示，PC（17:0/22:6）和ACar（17:3）可能是抗磷脂综合征的血清生物标志物。ROC曲线分析表明，PC（17:0/22:6）和ACar（17:3）联合诊断抗磷脂综合征的曲线下面积为0.865。PC（17:0/22:6）和ACar（17:3）可作为抗磷脂综合征的生物标志物。
