Correlative Chemical Imaging and Spatial Chemometrics Delineate Alzheimer Plaque Heterogeneity at High Resolution

27 June 2022, Version 2
This content is a preprint and has not undergone peer review at the time of posting.


We present a novel, correlative chemical imaging strategy based on multimodal matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI), hyperspectral microscopy, and spatial chemometrics. Our workflow overcomes challenges associated with correlative MSI data acquisition and alignment by implementing 1+1-evolutionary image registration for precise geometric alignment of multimodal imaging data. This enabled multivariate statistical modeling of multimodal imaging data using a novel multiblock orthogonal component analysis approach to identify covariations of biochemical signatures between and within imaging modalities at MSI pixel resolution. We demonstrate the method’s potential through its application towards delineating chemical traits of Alzheimer’s disease (AD) pathology. Here, trimodal MALDI MSI of transgenic AD mouse brain delineates beta-amyloid (Aβ) plaque-associated co-localization of lipids and Aβ peptides. Finally, we establish an improved image fusion approach for correlative MSI and functional amyloid microscopy. This allowed high resolution prediction of correlative, multimodal MSI signatures towards distinct amyloid structures within single plaque features critically implicated in Aβ pathogenicity.


imaging Mass Spectrometry
matrix assisted laser desorption/ionization mass spectrometry
spatial chemometrics
Multivariate Data Analysis
correlative imaging
image registration
Image fusion

Supplementary materials

Wehrli et al. 2022 Supplementary Information
Content: 1. Methods 2. Supplementary results 3. Supporting Information Figures S1-7


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