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Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
Spatial multi-omics reveals region-specific molecular signatures in a 6-OHDA model of Parkinson's disease
Sun Young Lee1, Hyun Kyong Shon1, Amos Chungwon Lee2
1Nanobio Measurement Group, Division of Biomedical Metrology, Korea Research Institute of Standards and Science, Daejeon, Republic of Korea.
Abstract:
Parkinson's disease (PD) is characterized by complex molecular and circuit-level alterations that extend beyond dopaminergic neurodegeneration, yet the spatial integration of metabolic and proteomic changes remains insufficiently explored. Here, we combined time-of-flight secondary ion mass spectrometry-based metabolite imaging with laser cell sorting proteomics to interrogate molecular alterations in the substantia nigra and striatum of the 6-hydroxydopamine toxin model of PD. Our analyses revealed distinct region-specific metabolic and proteomic signatures within primary lesion sites, and additionally uncovered unexpected and widespread off-target changes across neural circuits. These findings demonstrate that even in a toxin-induced model, PD pathology involves extensive reorganization of molecular networks and circuit-level processes, underscoring the complexity and diffuseness of disease mechanisms. By applying a spatially resolved, multilayered approach, this study expands the pathophysiological understanding of PD and provides a foundation for future investigations into the spatial and temporal dynamics of neurodegenerative disease progression.
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