Abstract：
Urine analysis has remained a fundamental and widely used method in clinical diagnostics for over a century. With its minimal invasive nature and comprehensive range of analytes, urine has established itself as a clinical diagnostic tool for various disorders, including renal, urological, metabolic, and endocrine diseases. Furthermore, urine\'s unique attributes make it an attractive matrix for biomarker discovery, as well as in assessing the metabolic and physiological states of patients and healthy individuals alike. However, limitations in our knowledge of average values and sources of urinary lipids decrease the wider clinical application of urinary lipidomics. In this context, untargeted lipidomics analysis relies heavily on the extraction and analysis of lipids in biological samples. Nevertheless, this type of analysis presents challenges in lipid identification due to the diverse nature of lipids. Therefore, proper sample treatment before analysis is crucial to obtain robust and reproducible lipidomic profiles. To address this gap, we conducted a comparative study of a urine pool sample collected from twenty healthy volunteers using four different lipid extraction methods: one biphasic and three monophasic protocols. The extracted lipids were then analyzed using UHPLC-MS and MS/MS, and the semi-quantification of all the accurately annotated lipid species was performed for each extraction method.
摘要：
一个多世纪以来，尿液分析一直是临床诊断中基本且广泛使用的方法。凭借其最小的侵入性和全面的分析物范围，尿液已成为各种疾病的临床诊断工具，包括肾,泌尿外科,新陈代谢，和内分泌疾病。此外，尿液的独特属性使其成为生物标志物发现的有吸引力的矩阵，以及评估患者和健康个体的代谢和生理状态。然而,我们对尿液脂质平均值和来源的认识的局限性降低了尿液脂质组学的更广泛的临床应用.在这种情况下，非靶向脂质组学分析在很大程度上依赖于生物样品中脂质的提取和分析。然而，由于脂质的多样性，这种类型的分析在脂质鉴定中提出了挑战。因此,分析前适当的样品处理对于获得稳健且可重复的脂质组学谱至关重要.为了解决这个差距，我们使用四种不同的脂质提取方法对20名健康志愿者的尿液池样本进行了比较研究:一种双相方案和三种单相方案.然后使用UHPLC-MS和MS/MS分析提取的脂质，并对每种提取方法进行了所有准确注释的脂质种类的半定量。
