Spatial Transcriptomics In Neurodegeneration is an important component in the neurobiology of neurodegenerative diseases. This page provides detailed information about its structure, function, and role in disease processes.
Spatial transcriptomics encompasses a family of technologies that measure gene expression [@chen2022] while preserving the spatial location of cells within intact tissue sections. Unlike dissociative single-cell approaches ([single-cell-genomics](/technologies/single-cell-genomics), spatial transcriptomics retains the tissue architecture, cellular neighborhoods, and microenvironmental context that are critical for understanding neurodegenerative — where pathology is inherently spatial, with amyloid plaques, tau] tangles], [alpha-synuclein](/proteins/alpha-synuclein), and reactive glia forming complex spatial relationships with vulnerable [neurons](/entities/neurons) ([Visualization et al., 2016](https://doi.org/10.1126/science.aaf2403)). [@stickels2021]
Spatial Transcriptomics In Neurodegeneration is an important component in the neurobiology of neurodegenerative diseases. This page provides detailed information about its structure, function, and role in disease processes.
Spatial transcriptomics encompasses a family of technologies that measure gene expression [@chen2022] while preserving the spatial location of cells within intact tissue sections. Unlike dissociative single-cell approaches ([single-cell-genomics](/technologies/single-cell-genomics), spatial transcriptomics retains the tissue architecture, cellular neighborhoods, and microenvironmental context that are critical for understanding neurodegenerative — where pathology is inherently spatial, with amyloid plaques, tau] tangles], [alpha-synuclein](/proteins/alpha-synuclein), and reactive glia forming complex spatial relationships with vulnerable [neurons](/entities/neurons) ([Visualization et al., 2016](https://doi.org/10.1126/science.aaf2403)). [@stickels2021]
Since its recognition as Nature's Method of the Year in 2020, spatial transcriptomics has rapidly matured from proof-of-concept experiments to large-scale brain [@zhang2023] mapping studies. Technologies now span the resolution-throughput spectrum from whole-transcriptome profiling with ~55 mum resolution (10x Visium to single-molecule detection at subcellular resolution (MERFISH, seqFISH+, Stereo-seq), enabling researchers to map disease pathology at unprecedented molecular detail ([Ståhl et al., 2016](https://doi.org/10.1126/science.aaf2403)) ([Highly et al., 2021](https://doi.org/10.1038). [@chen2022]
10x Visium and Visium HD: The most widely adopted spatial transcriptomics platform uses barcoded oligonucleotide arrays printed on glass slides. Tissue sections are placed on the array, permeabilized, and mRNAs hybridize to spatially barcoded capture probes. After reverse transcription and sequencing, transcripts are mapped back to their spatial locations. Standard Visium captures ~5,000 genes per 55 μm spot (each containing ~1-10 cells), while Visium HD achieves 2 μm resolution approaching single-cell level ([Spatial et al., 2020](https://doi.org/10.1016/j.cell.2020.06.038)). [@zhang2023]
Slide-seq and Slide-seqV2: Uses randomly barcoded 10 μm beads arranged on a glass surface, achieving near-cellular resolution with whole-transcriptome capture. Slide-seqV2 improved sensitivity ~10-fold over the original protocol, detecting ~2,500 genes per bead ([Stickels et al., 2021](https://doi.org/10.1038). [@chen2020]
Stereo-seq (STOmics): A nanoscale platform developed by BGI that achieves 500 nm resolution using DNA nanoball arrays, enabling subcellular spatial transcriptomics. Stereo-seq has been used to create high-resolution spatial maps of mouse and human brain tissue, including mapping microglial activation patterns in alzheimers ([Chen et al., 2022](https://doi.org/10.1016/j.cell.2022.04.003)) ([Spatiotemporal et al., 2022](https://doi.org/10.1016/j.cell.2022.04.003)). [@zeng2023]
MERFISH (Multiplexed Error-Robust Fluorescence In Situ Hybridization): Developed by Xiaowei Zhuang, MERFISH uses combinatorial barcoding and sequential rounds of hybridization, imaging, and probe removal to detect hundreds to thousands of RNA species at single-molecule resolution within intact cells. The Allen Institute has used MERFISH to create comprehensive spatial cell atlases of the mouse brain, detecting ~500 genes across millions of cells ([Zhang et al., 2023](https://doi.org/10.1038) ([Molecularly et al., 2023](https://doi.org/10.1038). [@kleshchevnikov2022]
seqFISH+ and seqFISH: Uses sequential rounds of fluorescent barcoding to detect up to 10,000 genes at single-molecule resolution, providing comprehensive spatial transcriptomic coverage comparable to scRNA-seq but with spatial information preserved. [@lewis2021]
STARmap and STARmap PLUS: Amplicon-based in situ sequencing methods that detect hundreds of genes simultaneously in thick tissue sections (up to 150 μm), enabling 3D spatial mapping of gene expression ([Nature et al., 2021](https://doi.org/10.1038). [@moffitt2018]
In Situ Sequencing (ISS): Padlock probes and rolling circle amplification generate bright fluorescent puncta that are sequenced in situ by sequential fluorescent imaging, providing targeted spatial gene expression at single-molecule resolution. [@cang2023]
| Platform | Resolution | Gene Panel | Throughput | Best Application | [@parkinsons]
|----------|-----------|------------|------------|------------------| [@michael]
| 10x Visium | ~55 μm | Whole transcriptome | High | Discovery, screening | [@national]
| Visium HD | 2 μm | Whole transcriptome | Moderate | Near-single-cell whole-transcriptome |
| Slide-seqV2 | 10 μm | Whole transcriptome | Moderate | High-resolution brain mapping |
| Stereo-seq | 500 nm | Whole transcriptome | High | Subcellular spatial analysis |
| MERFISH | 100 nm | 100-1,000 genes | Moderate | Single-cell/molecule resolution |
| seqFISH+ | 100 nm | Up to 10,000 genes | Low | Comprehensive single-cell spatial |
Spatial transcriptomics has been particularly transformative for alzheimers research:
Plaque-associated transcriptional programs: Visium and MERFISH studies have mapped gene expression changes as a function of distance from [amyloid-beta](/proteins/amyloid-beta) plaques, revealing that plaque-proximal [microglia[://doi.org/10.1038/[s41593-020-00764-7[://doi.org/10.1038/[s41593-020-00764-7://doi.org/10.1038).
Microglial network mapping: A 2025 study using spatial transcriptomics mapped [microglial across the cortical landscape in alzheimers, revealing that [disease-associated [microglia](/cell-types/microglia-neuroinflammation) identify genes whose expression varies significantly across tissue space, revealing spatially patterned transcriptional programs that may be missed in dissociative scRNA-seq analyses.
Spatial proximity information enables inference of cell-cell communication through ligand-receptor interaction analysis (COMMOT, stLearn, SpaTalk, NICHE-net), revealing which cell types communicate with each other in defined spatial microenvironments relevant to disease pathology.
Unsupervised methods (BayesSpace, SpaGCN, STAGATE) identify transcriptionally coherent spatial domains — analogous to tissue regions or anatomical structures — enabling data-driven discovery of disease-associated spatial patterns.
Multi-modal integration frameworks combine spatial transcriptomics with:
The Allen Institute has generated a comprehensive MERFISH spatial transcriptomics dataset of the entire adult mouse brain, detecting ~500 genes across millions of cells with single-cell resolution. This atlas provides a reference framework for mapping cell types and states across the entire brain and has been widely adopted for neurodegenerative disease studies.
Multiple consortia (SEA-AD, Human Cell Atlas, BRAIN Initiative Cell Census) are generating spatial transcriptomic maps of the human brain across development, aging, and disease, creating reference resources for the neurodegeneration research community.
Emerging methods combining expansion microscopy with spatial transcriptomics enable simultaneous visualization of subcellular RNA localization and organelle structure, potentially revealing how RNA mislocalization contributes to neurodegeneration.
Integration of spatial transcriptomics across disease progression time points will enable mapping of how pathological spatial patterns evolve over time — tracking the spread of tau] propagation], [prion-like spreading](/mechanisms/prion-like-spreading), and inflammatory zone expansion.
Spatial transcriptomics of cerebrospinal fluid cells and peripheral blood could provide spatially informed "liquid biopsies" for neurodegenerative disease diagnosis and monitoring, while spatial profiling of brain biopsy tissue could guide precision therapeutic decisions.
Large-scale efforts to map the entire human brain at single-cell spatial resolution across the lifespan and disease spectrum will provide definitive reference frameworks for understanding [neurodegeneration.
The study of Spatial Transcriptomics In Neurodegeneration has evolved significantly over the past decades. Research in this area has revealed important insights into the underlying mechanisms of neurodegeneration and continues to drive therapeutic development.
Historical context and key discoveries in this field have shaped our current understanding and will continue to guide future research directions.