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Alzheimer's disease (AD) is characterized by the accumulation of amyloid-beta (Aβ) plaques in the brain, contributing to neurodegeneration. This study investigates lipid alterations within these plaques using a novel, label-free, multimodal approach. Combining infrared (IR) imaging, machine learning, laser microdissection (LMD), and flow injection analysis mass spectrometry (FIA-MS), we provide the first comprehensive lipidomic analysis of chemically unaltered Aβ plaques in post-mortem human AD brain tissue. IR imaging revealed decreased lipid unsaturation within plaques, evidenced by a reduction in the alkene (=C-H) stretching vibration band. The high spatial resolution of IR imaging, coupled with machine learning-based plaque detection, enabled precise and label-free extraction of plaques via LMD. Subsequent FIA-MS analysis confirmed a significant increase in short-chain saturated lipids and a concomitant decrease in long-chain unsaturated lipids within plaques compared to the surrounding tissue. These findings highlight a substantial depletion of unsaturated fatty acids (UFAs) in Aβ plaques, suggesting a pivotal role for lipid dysregulation and oxidative stress in AD pathology. This study advances our understanding of the molecular landscape of Aβ plaques and underscores the potential of lipid-based therapeutic strategies in AD., (© 2025 The Author(s). Journal of Neurochemistry published by John Wiley & Sons Ltd on behalf of International Society for Neurochemistry.)