Evidence map›Paper›PMID 42695425›Full record

ReviewInternational journal of molecular medicine2026

Multi‑omics integration in osteoarthritis: Unraveling cell‑type‑specific gene‑metabolite networks for precision medicine (Review).

Ying Yang, Ruichen Zheng, Yun Zhang, Dongmei Ye, Jiale Xie, Changliang Zhu

Abstract readReview
In one paragraph

Review in International journal of molecular 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

6 authors.

Ying YangDepartment of Pathology, Honghui Hospital, Xi'an Jiaotong University, Xi'an, Shanxi 710054, P.R. China.
Ruichen ZhengDepartment of Intensive Care Unit, Honghui Hospital, Xi'an Jiaotong University, Xi'an, Shanxi 710054, P.R. China.
Yun ZhangDepartment of Pathology, Honghui Hospital, Xi'an Jiaotong University, Xi'an, Shanxi 710054, P.R. China.
Dongmei YeDepartment of Pathology, Honghui Hospital, Xi'an Jiaotong University, Xi'an, Shanxi 710054, P.R. China.
Jiale XieDepartment of Intensive Care Unit, Honghui Hospital, Xi'an Jiaotong University, Xi'an, Shanxi 710054, P.R. China.
Changliang ZhuDepartment of Intensive Care Unit, Honghui Hospital, Xi'an Jiaotong University, Xi'an, Shanxi 710054, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Osteoarthritis (OA) is a heterogeneous joint disorder lacking disease‑modifying therapies. Recent advances in single‑cell transcriptomics, metabolomics, lipidomics, and spatial omics have enabled the reconstruction of cell‑type‑specific gene‑metabolite networks and revealed that metabolic reprogramming differs markedly across chondrocyte subsets, synovial fibroblasts and immune cells. Lipid metabolism disturbances, particularly those involving glycerophospholipids, sphingolipids and cholesterol, are consistently linked to OA severity and pain generation. Integrative multi‑omics approaches further facilitate molecular endotyping, informing patient stratification and endotype‑driven clinical trial design. However, a systematic synthesis of these emerging findings is still lacking. This review critically synthesizes current multi‑omics integration strategies, delineates cell‑type‑specific metabolic networks derived from transcriptomic and metabolomic data and discusses their implications for precision medicine in OA, while also considering the emerging contributions of spatial omics technologies.

Indexed as

Gene Regulatory NetworksOsteoarthritisPrecision MedicineAnimalsHumansLipid MetabolismMetabolomeMetabolomicsMultiomicsTranscriptomegene‑metabolite networkslipid metabolismmetabolomicsmolecular endotypesmulti‑omics integrationosteoarthritisprecision medicinesingle‑cell transcriptomics

Identifiers

PMID42695425
PMCPMC13557440

What Socratic holds

Textmetadata
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.