Evidence map›Paper›PMID 42618921›Full record

ReviewJournal of translational medicine2026

Single-cell and spatial transcriptomics analysis of osteoarthritis: pathway regulation, cell interaction networks, and therapeutic translation.

Dujiang Yang, Jing Lu, Qi Liu, Gaowen Gong, Junjie Chen, Zhibin Song, Zhijun Ye, Shuang Wang, Yunlong Xiao, Guoyou Wang

Abstract readReview
In one paragraph

Review in Journal of translational medicine, 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

10 authors.

Dujiang Yang *Chengdu University of Traditional Chinese Medicine, No. 37, Shierqiao Road, Chengdu, Sichuan Province, 610075, P.R. China.
Jing Lu *Department of Joint Surgery, The Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University, Luzhou, Sichuan, 646000, China.
Qi Liu *Department of Joint Surgery, The Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University, Luzhou, Sichuan, 646000, China.
Gaowen Gong *Department of Joint Surgery, The Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University, Luzhou, Sichuan, 646000, China.
Junjie ChenChengdu University of Traditional Chinese Medicine, No. 37, Shierqiao Road, Chengdu, Sichuan Province, 610075, P.R. China.
Zhibin SongDepartment of Joint Surgery, The Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University, Luzhou, Sichuan, 646000, China.
Zhijun YeDepartment of Joint Surgery, The Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University, Luzhou, Sichuan, 646000, China.
Shuang WangDepartment of Joint Surgery, The Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University, Luzhou, Sichuan, 646000, China.
Yunlong Xiao *Department of Joint Surgery, The Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University, Luzhou, Sichuan, 646000, China.
Guoyou WangDepartment of Joint Surgery, The Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University, Luzhou, Sichuan, 646000, China. wang_guoyou1981@163.com.ORCID 0000-0003-0027-0572

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOsteoarthritis (OA) transcends the outdated paradigm of mere "wear and tear" cartilage loss. It is now recognized as a complex, whole-organ disease driven by multifaceted interactions among diverse cell populations across synovium, cartilage, subchondral bone, and infrapatellar fat pad. The profound heterogeneity within these tissues and the spatiotemporal dynamics of pathological processes have, until recently, remained a "black box," limiting our understanding of disease initiation and progression. The convergence of single-cell RNA sequencing (scRNA-seq) and spatial transcriptomic (ST) has fundamentally disrupted OA research, offering an unprecedented lens to deconvolute cellular identities, fate decisions, and communication networks within their native architectural context. MAIN BODY: This review provides a comprehensive critical synthesis of how these high-resolution technologies are redefining the OA pathomechanistic landscape. We first detail the technical underpinnings and comparative advantages of key scRNA-seq and ST platforms, emphasizing burgeoning computational methodologies for their integration. We then articulate how scRNA-seq has deconvoluted the OA joint's cellular ecosystem, uncovering previously unappreciated states and trajectories. Crucially, we highlight how ST contextualizes these findings, revealing region-specific pathology and defining anatomically precise cross-tissue communication hubs such as the synovium-cartilage axis and the neuro-immune-vascular triad. A dedicated synthesis is given to the spatiotemporal regulation of signaling networks, dissecting core mechanisms of immune dysregulation, neurovascular remodeling, and the novel ECM-mitochondria-mechanics axis.

conclusionsWhile challenges persist, the path forward is clear. The integration of single-cell and spatial multi-omics is forging a new molecular pathology of OA, defined by cell-state-specific disease drivers rather than broad tissue-level changes. By mapping the precise cellular and spatial coordinates of OA pathogenesis, these technologies are rapidly translating into the discovery of novel, mechanistically grounded therapeutic targets and biomarkers, heralding a future of personalized, interceptive OA medicine.

Indexed as

Cell CommunicationOsteoarthritisSignal TransductionSingle-Cell AnalysisTranslational Research, BiomedicalAnimalsHumansSingle-Cell Gene Expression AnalysisSpatial TranscriptomicsChondrocytecytokinesMechanismOsteoarthritisReviewScRNA-seqSpatil-transcriptomic

Identifiers

PMID42618921
PMCPMC13491735

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.