Rice University researchers have constructed the first complete, label-free molecular atlas of the Alzheimer’s brain in an animal model, revealing region-specific chemical changes that extend beyond amyloid plaques.
The work addresses a long-standing limitation of conventional brain-imaging approaches, which typically rely on labels, tracers, or predefined targets. Instead, the team used hyperspectral Raman imaging to capture thousands of overlapping molecular spectra across whole brain slices, generating spatially resolved chemical maps of both healthy and Alzheimer’s-affected tissue.
“Hyperspectral Raman imaging repeats this measurement thousands of times across an entire tissue slice to build a full map,” said Ziyang Wang, first author of the study, in a press release. “The result is a detailed picture showing how chemical composition varies across different regions of the brain.”
To extract biologically meaningful patterns from these large datasets, the researchers combined the imaging workflow with machine-learning analysis. Unsupervised models were first used to cluster tissue regions based solely on spectral similarity, enabling data-driven segmentation of molecularly distinct brain areas. Supervised models were then trained on healthy and Alzheimer’s samples to quantify how strongly different regions reflected disease-associated chemistry.
This combined approach revealed pronounced regional heterogeneity in Alzheimer’s-related molecular changes. Areas associated with memory – including the hippocampus and cortex – showed stronger deviations from healthy tissue than other regions, offering a potential explanation for the gradual emergence and progression of symptoms.
Beyond protein aggregation, the analysis also revealed metabolic differences between healthy and diseased brains. Variations in cholesterol- and glycogen-associated spectral features were observed across multiple regions, pointing to broader disruptions in membrane structure and local energy storage.
“Cholesterol is important for maintaining brain cell structure, and glycogen serves as a local energy reserve,” said Shengxi Huang, corresponding author of the study. “Together, these findings support the idea that Alzheimer’s involves broader disruptions in brain structure and energy balance, not only protein buildup and misfolding.”
By combining label-free chemical imaging with data-driven analysis, the researchers say the framework provides a more comprehensive view of Alzheimer’s-associated molecular changes. They suggest that extending the approach to other disease models or earlier disease stages could help clarify how metabolic and structural alterations evolve alongside classical pathological hallmarks.
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