Evidence map›Paper›PMID 41334506›Full record

ArticleData in brief2025

A comprehensive metabolomic dataset of human synovial fluid in osteoarthritis and healthy controls.

Ping Chen, Shuai Zhang, Long Wu, Zhiyao Yong, Qunhua Jin, Kening Sun

Abstract read
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Article in Data in brief, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Ping ChenGeneral Hospital of Ningxia Medical University, Yinchuan 750004, China.
Shuai ZhangOrthopedics Ward 3, The General Hospital of Ningxia Medical University, Yinchuan 750004, China.
Long WuOrthopedics Ward 3, The General Hospital of Ningxia Medical University, Yinchuan 750004, China.
Zhiyao YongOrthopedics Ward 3, The General Hospital of Ningxia Medical University, Yinchuan 750004, China.
Qunhua JinOrthopedics Ward 3, The General Hospital of Ningxia Medical University, Yinchuan 750004, China.
Kening SunOrthopedics Ward 3, The General Hospital of Ningxia Medical University, Yinchuan 750004, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Osteoarthritis (OA) is a prevalent degenerative joint disorder that causes chronic pain and disability. The synovial fluid (SF), which bathes the joint, reflects the pathological state and is a valuable source for biomarker discovery. However, a comprehensive metabolomic profile of SF in OA remains to be fully established. Here, we present a comprehensive metabolomic dataset derived from SF samples of 10 OA patients and 10 matched healthy controls. Using non-targeted metabolomics based on ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC-MS), we identified 23,232 features, with 1431 metabolites annotated. Comparative analysis revealed 163 significantly differential metabolites (118 upregulated, 45 downregulated). Functional enrichment and pathway analyses highlighted disruptions in amino acid metabolism, energy metabolism, and lipid pathways. Several metabolites showed high diagnostic potential in ROC analysis. This dataset provides a valuable resource for understanding OA-associated metabolic alterations and offers robust candidate biomarkers for OA diagnosis and therapeutic monitoring.

Indexed as

BiomarkersOsteoarthritisSynovial fluidUHPLC-MSUntargeted metabolomics

Identifiers

PMID41334506
PMCPMC12666683

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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 OpenQuestion graph.