Evidence mapPaperPMID 42317262Full record

ReviewMolecular neurodegeneration advances2026

Spatial transcriptomics in Alzheimer's disease: technologies, challenges and discoveries.

Christina Huan Shi, Juan C Piña-Crespo, Kevin Y Yip, Timothy Y Huang

Abstract readReview
In one paragraph

Review in Molecular neurodegeneration advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Christina Huan ShiCenter for Data Science and Artificial Intelligence, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA 92037 USA.
Juan C Piña-CrespoCenter for Neurologic Diseases, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA 92037 USA.
Kevin Y YipCenter for Neurologic Diseases, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA 92037 USA.
Timothy Y HuangCenter for Neurologic Diseases, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA 92037 USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alzheimer's disease (AD) is a complex neurodegenerative disorder that is associated with cognitive decline in the elderly. While β-amyloid (Aβ) plaques and neurofibrillary tau tangles have been used to define and stage AD onset in human brain, how these pathologies can affect various cell types nearby remains a subject of intense interest in the field. Recent developments in spatial transcriptomic technology have seen accelerated growth, and spatial transcriptomic platforms have been used independently or together with single cell transcriptomic methods to characterize cellular changes in the AD brain from mouse models and human. Here, we review current-era spatial transcriptomic technologies, analytical pipelines and their implementation in AD research. We summarize findings from spatial transcriptomics in AD, and discuss limitations and challenges associated with various spatial transcriptomic platforms. The pathological hallmarks for AD were described by Alois Alzheimer over a century ago; from the convergence of a century of AD research and technological advances in imaging and transcriptomics, a new era in AD has emerged. Although current-era spatial platforms feature limitations and challenges, evolution of spatial transcriptomics and its combined implementation with other data modalities promises significant strides in AD and related neurodegenerative disorders.

Indexed as

Alzheimer’s diseaseAβ plaquesCell–cell interactionCellular response to AD pathologyPathological AD microenvironmentRegional vulnerability and resilienceSpatial transcriptomicsTau

Identifiers

PMID42317262
PMCPMC13272225

What Socratic holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.