Structural amyloid plaque polymorphism is associated with distinct lipid accumulations revealed by trapped ion mobility mass spectrometry imaging.

Understanding of Alzheimer's disease (AD) pathophysiology requires molecular assessment of how key pathological factors, specifically amyloid β (Aβ) plaques, influence the surrounding microenvironment. Here, neuronal lipids have been implicated in Aβ plaque pathology, though the lipid microenvironment in direct proximity to Aβ plaques is still not fully resolved. A further challenge is the microenvironmental molecular heterogeneity, across structurally polymorphic Aβ features, such as diffuse, immature, and mature, fibrillary aggregates, whose resolution requires the integration of advanced, multimodal chemical imaging tools. Herein, we used matrix-assisted laser desorption/ionization trapped ion mobility spectrometry time-of-flight based mass spectrometry imaging (MALDI TIMS TOF MSI) in combination with hyperspectral confocal microscopy to probe the lipidomic microenvironment associated with structural polymorphism of Aβ plaques in transgenic Alzheimer's disease mice (tgAPPSWE ). Using on tissue and ex situ validation, TIMS MS/MS facilitated unambiguous identification of isobaric lipid species that showed plaque pathology-associated localizations. Integrated multivariate imaging data analysis revealed multiple, Aβ plaque-enriched lipid patterns for gangliosides (GM), phosphoinositols (PI), phosphoethanolamines (PE), and phosphatidic acids (PA). Conversely, sulfatides (ST), cardiolipins (CL), and polyunsaturated fatty acid (PUFA)-conjugated phosphoserines (PS), and PE were depleted at plaques. Hyperspectral amyloid imaging further delineated the unique distribution of PA and PE species to mature plaque core regions, while PI, LPI, GM2 and GM3 lipids localized to immature Aβ aggregates present within the periphery of Aβ plaques. Finally, we followed AD pathology-associated lipid changes over time, identifying plaque- growth and maturation to be characterized by peripheral accumulation of PI (18:0/22:6). Together, these data demonstrate the potential of multimodal imaging approaches to overcome limitations associated with conventional advanced MS imaging applications. This allowed for the differentiation of both distinct lipid components in a complex micro-environment as well as their correlation to disease-relevant amyloid plaque polymorphs. Cover Image for this issue: https://doi.org/10.1111/jnc.15390.