Dysregulated glycerophospholipid (GP) metabolism in the brain is associated with the progression of neurodegenerative diseases including Alzheimer’s disease (AD). Routine liquid chromatography-mass spectrometry (LC-MS)-based large-scale lipidomic methods often fail to elucidate subtle yet important structural features such as sn-position, hindering the precise interrogation of GP molecules. Leveraging high-resolution demultiplexing (HRdm) ion mobility spectrometry (IMS), we develop a four-dimensional (4D) lipidomic strategy to resolve GP sn-position isomers. We further construct a comprehensive experimental 4D GP database of 498 GPs identified from the mouse brain and an in-depth extended 4D library of 2500 GPs predicted by machine learning, enabling automated profiling of GPs with detailed acyl chain sn-position assignment. Analyzing three mouse brain regions (hippocampus, cerebellum, and cortex), we successfully identify a total of 592 GPs including 130 pairs of sn-position isomers. Further temporal GPs analysis in the three functional brain regions illustrates their metabolic alterations in AD progression.

大脑中甘油磷脂（GP）代谢失调与包括阿尔茨海默病（AD）在内的神经退行性疾病的进展有关。基于常规液相色谱-质谱 (LC-MS) 的大规模脂质组学方法通常无法阐明微妙但重要的结构特征，例如sn位置，从而阻碍了 GP 分子的精确解析。利用高分辨率解复用 (HRdm) 离子迁移谱 (IMS)，我们开发了一种四维 (4D) 脂质组学策略来解析 GP sn位置异构体。我们进一步构建了一个包含从小鼠大脑中识别的 498 个 GP 的综合实验 4D GP 数据库，以及一个包含通过机器学习预测的 2500 个 GP 的深度扩展 4D 库，从而能够通过详细的酰基链sn位置分配对 GP 进行自动分析。通过分析小鼠大脑的三个区域（海马、小脑和皮质），我们成功鉴定了总共 592 个 GP，其中包括 130 对sn位置异构体。对三个功能性大脑区域的进一步时间 GP 分析说明了 AD 进展过程中的代谢变化。