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Updated: Sep 23, 2026

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
Spatial omics of neuroinflammation: insights across brain diseases
Mingming Li1,2,3, Qianying Wang1, Jian Li4
1Department of Neurology, Lanzhou University Second Hospital, Lanzhou University, Lanzhou, China.
Abstract:
Neuroinflammation is a common pathological feature of diverse brain diseases, but inflammatory activity is rarely distributed uniformly across diseased tissue. Instead, microglia, astrocytes, infiltrating immune cells and inflammatory mediators are often organized around specific pathological structures, including amyloid plaques, demyelinated lesion rims, ischemic borders, necrotic tumor regions and perivascular white matter compartments. Although bulk and dissociation-based single-cell approaches have defined many inflammatory cell states, they cannot determine where these states reside, how they relate to local pathology, or whether inferred cell-cell interactions occur within plausible spatial neighborhoods. Spatial omics addresses this limitation by preserving molecular information within intact tissue architecture. In this review, we summarize major spatial transcriptomic, proteomic, metabolomic and same-section multi-omic technologies, with emphasis on the types of neuroinflammatory questions each platform can answer. We then examine how spatial omics has reshaped the understanding of neuroinflammation across Alzheimer's disease and tauopathies, multiple sclerosis, ischemic stroke, glioma, infection-related neuroinflammation and aging. Across these settings, spatial studies have revealed plaque-associated glial niches, lipid- and iron-enriched lesion rims, core-penumbra inflammatory zonation, and hypoxic or perivascular immune microenvironments. These findings suggest that neuroinflammation should be understood not only as a set of molecular or cellular states, but also as a spatially organized tissue process shaped by local pathology, cellular adjacency and microenvironmental gradients and spatial compartments. Finally, we discuss the limitations of current spatial maps, including resolution, human tissue constraints and insufficient functional validation, and outline future directions toward integrated, temporal and clinically translatable spatial atlases.
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