Beyond Transcriptomes and Dissociated Cells: Spatial Proteomics for Mechanistic Neurobiology.

Abstract

Single-cell transcriptomic studies have revealed remarkable molecular heterogeneity across neuronal and glial populations during development, aging, and disease. However, dissociation-based approaches disrupt tissue architecture, and RNA measures alone incompletely capture cellular function. These limitations are particularly relevant in neurodegenerative diseases, where pathology develops within cellular microenvironments and diseased cells progressively lose canonical cell-state identity markers. Spatial proteomic approaches are beginning to address this critical gap by enabling high-dimensional molecular profiling within the intact tissue, preserving the spatial relationships between vulnerable cells and their surrounding cellular environments across scales ranging from subcellular single-cell imaging to large-volume three-dimensional mapping. Here, we discuss emerging spatial proteomic technologies and their applications in aging and neurodegeneration, emphasizing how integration with complementary modalities, including transcriptomics, glycomics, three-dimensional genome architecture, and quantitative neuropathology, is providing new insight into disease biology. We further highlight how these approaches are beginning to accelerate therapeutic target validation, biomarker discovery, and treatment response monitoring. Realizing the full potential of spatial proteomics will require continued advances in cross-platform harmonization, analytical standardization, and computational methods capable of integrating increasingly complex, multimodal datasets.

Abstract as supplied by the indexing source. © the authors / publisher.