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血清脂类用于 1 型糖尿病研究的精确质量和保留时间文库。

Accurate mass and retention time library of serum lipids for type 1 diabetes research.

机构信息

Department of Chemistry & Biochemistry, University of North Carolina at Greensboro, Greensboro, NC, 27412, USA.

Center for Translational Biomedical Research, University of North Carolina at Greensboro, North Carolina Research Campus, Kannapolis, NC, 28082, USA.

出版信息

Anal Bioanal Chem. 2019 Sep;411(23):5937-5949. doi: 10.1007/s00216-019-01997-7. Epub 2019 Jul 6.

Abstract

Dysregulated lipid species are linked to various disease pathologies and implicated as potential biomarkers for type 1 diabetes (T1D). However, it is challenging to comprehensively profile the blood specimen lipidome with full structural details of every lipid molecule. The commonly used reversed-phase liquid chromatography-tandem mass spectrometry (RPLC-MS/MS)-based lipidomics approach is powerful for the separation of individual lipid species, but lipids belonging to different classes may still co-elute and result in ion suppression and misidentification of lipids. Using offline mixed-mode and RPLC-based two-dimensional separations coupled with MS/MS, a comprehensive lipidomic profiling was performed on human sera pooled from healthy and T1D subjects. The elution order of lipid molecular species on RPLC showed good correlations to the total number of carbons in fatty acyl chains and total number of double bonds. This observation together with fatty acyl methyl ester analysis was used to enhance the confidence of identified lipid species. The final T1D serum lipid library database contains 753 lipid molecular species with accurate mass and RPLC retention time uniquely annotated for each of the species. This comprehensive human serum lipid library can serve as a database for high-throughput RPLC-MS-based lipidomic analysis of blood samples related to T1D and other childhood diseases. Graphical abstract.

摘要

脂质种类失调与各种疾病病理有关,并被认为是 1 型糖尿病 (T1D) 的潜在生物标志物。然而,全面描绘具有每个脂质分子完整结构细节的血液样本脂质组学图谱具有挑战性。常用的基于反相液相色谱-串联质谱 (RPLC-MS/MS) 的脂质组学方法可有效分离各个脂质种类,但属于不同类别的脂质仍可能共同洗脱,导致离子抑制和脂质误识别。本研究采用离线混合模式和基于 RPLC 的二维分离与 MS/MS 联用,对来自健康和 T1D 受试者的混合血清进行了全面的脂质组学分析。RPLC 上脂质分子种类的洗脱顺序与脂肪酸链中的碳原子总数和双键总数具有良好的相关性。这种观察结果结合脂肪酸甲酯分析可增强鉴定脂质种类的可信度。最终的 T1D 血清脂质文库数据库包含 753 种脂质分子种类,每种脂质分子种类都具有准确的质量和 RPLC 保留时间注释。该全面的人类血清脂质文库可作为基于高通量 RPLC-MS 的与 T1D 和其他儿童疾病相关的血液样本脂质组学分析的数据库。

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