MALDI Mass Spectrometry Imaging in Alzheimer's Disease Lipidomics: Matrix Selection, Spatial Lipid Pathology and...

Alzheimer's disease (AD) involves not only amyloid-β and tau pathology but also extensive disturbances in lipid metabolism, membrane organization, neuroinflammatory signaling, and tissue homeostasis. Conventional lipidomics has identified changes in phospholipids, sphingolipids, sulfatides, ceramides, gangliosides, and cholesterol-related pathways, but tissue homogenization removes their anatomical context. The aim of this review is to critically assess how matrix selection, sample preparation, ionization polarity, and emerging analytical strategies influence the detection and interpretation of spatial lipid alterations specifically associated with AD neuropathology. Current evidence shows that AD-related lipid remodeling is region- and lesion-specific, with recurrent findings including ganglioside accumulation, sulfatide depletion, ceramide-related alterations, phospholipid remodeling, lysosomal lipid changes, and disturbed cholesterol homeostasis within or around amyloid plaques. Matrix chemistry strongly influences lipid-class coverage, ionization efficiency, spectral background, adduct formation, spatial resolution, and biological interpretation. Matrix-Assisted Laser Desorption/Ionization with Laser-Induced Post-Ionization (MALDI-2), ion mobility, reactive matrices, on-tissue derivatization, structural lipidomics, single-cell imaging, and spatial multiomics are expanding molecular coverage and annotation confidence. However, broader translation requires standardized workflows, structurally validated assignments, quantitative quality control, larger human cohorts, and improved interlaboratory reproducibility. Collectively, the available evidence indicates that the principal value of Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI) in AD lies not merely in detecting altered lipid abundance, but in resolving lesion-specific lipid microenvironments whose interpretation depends directly on matrix chemistry, spatial resolution, and structural validation.