Evidence map›Paper›PMID 39611154›Full record

ArticleFrontiers in immunology2024

A targeted proteomics screen reveals serum and synovial fluid proteomic signature in patients with gout.

Zhengping Huang, Xiaoyan Zhong, Yuexi Zhang, Xinjian Li, Meng Liu, Yukai Huang, Jian Yue, Guanqun Yi, Hongji Liu, Bingyan Yuan and 3 more

Abstract read
In one paragraph

Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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  5. Peripheral CD4Frontiers in immunology · 2026
    Article
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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

13 authors.

Zhengping HuangThe Second School of Clinical Medicine, Southern Medical University, Guangzhou, China.
Xiaoyan ZhongThe Second School of Clinical Medicine, Southern Medical University, Guangzhou, China.
Yuexi ZhangDepartment of Rheumatology and Immunology, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China.
Xinjian LiDepartment of Rheumatology and Immunology, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China.
Meng LiuDepartment of Rheumatology and Immunology, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China.
Yukai HuangDepartment of Rheumatology and Immunology, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China.
Jian YueDepartment of Rheumatology and Immunology, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China.
Guanqun YiDepartment of Rheumatology and Immunology, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China.
Hongji LiuDepartment of Rheumatology and Immunology, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China.
Bingyan YuanDepartment of Rheumatology and Immunology, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China.
Xu ChenDepartment of Rheumatology and Immunology, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China.
Shaoling ZhengDepartment of Rheumatology and Immunology, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China.
Tianwang LiThe Second School of Clinical Medicine, Southern Medical University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To characterize the inflammatory proteome in both serum and synovial fluid (SF) of patients with gout, in comparison to healthy controls and individuals with osteoarthritis (OA), by utilizing a high-quality, high-throughput proteomic analysis technique. Methods: Using the Olink Target 48 Inflammation panel, we measured serum concentrations of 45 inflammatory proteins in gout, OA, and healthy controls. We analyzed protein levels in SF samples from gout and OA, performed ROC curve analyses to identify diagnostic biomarkers, evaluate efficacy, and set cut-off values. Additionally, A protein-protein interaction (PPI) network was used to study protein relationships and significance. Results: We have delineated the proteomic landscape of gout and identified 20 highly differentially expressed proteins (DEPs) in the serum of gout patients in comparison to that of healthy controls, which included VEGF-A, MMP-1, TGF-α, and OSM with corresponding area under the curve (AUC) values of 0.95, 0.95, 0.92, and 0.91 respectively. For the analysis of synovial fluid, 6 proteins were found to be elevated in gout in contrast to osteoarthritis (OA), among which IP-10, VEGF-A, IL-8, and MIP-3β had corresponding AUC values of 0.78, 0.78, 0.76, and 0.75 respectively. The protein-protein interaction (PPI) network analysis identified significantly prominent pathways in gout. Conclusion: This research marks a significant advancement in elucidating the inflammatory profile present in the serum and synovial fluid of individuals suffering from gout. Our discoveries have identified several novel proteins in both serum and synovial fluid that are potential biomarkers for diagnostic purposes and are believed to have critical roles as pathogenic factors in the pathophysiology of gout.

Indexed as

BiomarkersGoutProteomicsSynovial FluidAdultAgedCase-Control StudiesFemaleHumansMaleMiddle AgedOsteoarthritisProtein Interaction MapsProteomeBiomarkersProteomebiomarkerscrystal arthropathiescytokines and inflammatory mediatorsosteoarthritisproteomicssynovial fluid analysis

Identifiers

PMID39611154
PMCPMC11602490

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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.