心房颤动患者的血清脂质代谢组学特点及其诊断价值

目的：心房颤动是临床最常见的心律失常，但其具体病理生理机制仍待研究，目前上缺乏用于预测诊断疾病的生物标志物。本研究主要探讨血清脂质代谢组学在心房颤动患者中的特点及其对疾病的预测价值；方法：本研究为单中心横断面研究，收集2017.1至2017.12入我科的心房颤动患者血清，并同期选取健康对照血清。使用非靶向代谢组学进行血清脂质组学检测，比较心房颤动及对照患者血清脂质组学特点。结果：使用阴离子模式及阳离子模式在纳入血清中分别监测到63及62种脂质成分。其中，阴离子模式中16:0 Lyso PC, 18:0-20:4 PE, 24:0 SM, 20:0 ceramide, 24:0 ceramide, 24:1 ceramide，以及阳离子模式中18:0 PC (DSPC) 和24:1 ceramide在心房颤动患者中改变明显。ROC分析提示阴离子模式中24:0 ceramide, 24:1 ceramide, 20:0 ceramide, 18:0-20:4 PE，以及阳离子模式中24:0 ceramide, 24:1 ceramide, 20:0 ceramide对心房颤动具有预测价值。结论：本研究通过非靶向代谢组学对心房颤动患者血清脂质组学进行分析，发现心房颤动患者中存在脂质成分改变，且脂质成分对于心房颤动具有诊断价值。

The characteristics and diagnostic value of serum lipids metabolomics profile in atrial fibrillation patients

Objective: The pathophysiologic mechanism of AF remains poorly understood, and there has been a lack of circulatory markers to diagnose and predict prognosis of AF. In this study, by measuring serum lipids metabolic profile and analyzing serum lipids levels in AF patients, we sought to determine if serum lipids metabolism was correlated to the occurrence of atrial fibrillation. Methods: In this cross-sectional study, we analyzed serum lipids profile in AF and control patients using a lipidomics approach. Consecutive patients admitted to hospital for AF were enrolled. Serum samples were obtained after overnight fast. Nontargeted metabolomics was applied to demonstrate lipids metabolic profile in control and AF patients.Results: A total of 63 and 62 lipids were detected in negative and positive ion mode respectively. Among them, 16:0 Lyso PC, 18:0-20:4 PE, 24:0 SM, 20:0 ceramide, 24:0 ceramide, 24:1 ceramide in negative ion mode and 18:0 PC (DSPC) and 24:1 ceramide in positive ion mode were significantly altered in AF as compared to control. 24:0 ceramide, 24:1 ceramide, 20:0 ceramide, 18:0-20:4 PE in negative ion mode and 24:0 ceramide, 24:1 ceramide, 20:0 ceramide in positive ion mode showed prediction value for AF.Conclusions: Using non-targeted metabolomics profiling, we have successfully identified a group of circulating lipids that were significantly altered in AF. The lipids metabolic signatures shed light on potential new biomarkers and therapeutics for preventing and treating AF.