Evidence map›Paper›PMID 27788684›Full record

ArticleArthritis research & therapy2016

Protein oxidation, nitration and glycation biomarkers for early-stage diagnosis of osteoarthritis of the knee and typing and progression of arthritic disease.

Usman Ahmed, Attia Anwar, Richard S Savage, Paul J Thornalley, Naila Rabbani

Open access · goldAbstract read
In one paragraph

Article in Arthritis research & therapy, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 3 pooled it
9.6field-weighted citation impact, top 2% of its field
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

39 citing papers in PubMed, 3 syntheses or guidelines pooled it, 79 citations in OpenAlex.

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  9. Osteoarthritis.Nature reviews. Disease primers · 2025
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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

5 authors at 2 institutions in 1 country.

Usman AhmedWarwick Medical School, Clinical Sciences Research Laboratories, University of Warwick, University Hospital, Coventry, CV2 2DX, UK.
Attia AnwarWarwick Medical School, Clinical Sciences Research Laboratories, University of Warwick, University Hospital, Coventry, CV2 2DX, UK.
Richard S SavageWarwick Systems Biology Centre, Senate House, University of Warwick, Coventry, CV4 7AL, UK.
Paul J ThornalleyWarwick Medical School, Clinical Sciences Research Laboratories, University of Warwick, University Hospital, Coventry, CV2 2DX, UK.
Naila RabbaniWarwick Medical School, Clinical Sciences Research Laboratories, University of Warwick, University Hospital, Coventry, CV2 2DX, UK. n.rabbani@warwick.ac.uk.
University of Warwick · GBUniversity Hospital Coventry · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere is currently no blood-based test for detection of early-stage osteoarthritis (OA) and the anti-cyclic citrullinated peptide (CCP) antibody test for rheumatoid arthritis (RA) has relatively low sensitivity for early-stage disease. Morbidity in arthritis could be markedly decreased if early-stage arthritis could be routinely detected and classified by clinical chemistry test. We hypothesised that damage to proteins of the joint by oxidation, nitration and glycation, and with signatures released in plasma as oxidized, nitrated and glycated amino acids may facilitate early-stage diagnosis and typing of arthritis.

methodsPatients with knee joint early-stage and advanced OA and RA or other inflammatory joint disease (non-RA) and healthy subjects with good skeletal health were recruited for the study (n = 225). Plasma/serum and synovial fluid was analysed for oxidized, nitrated and glycated proteins and amino acids by quantitative liquid chromatography-tandem mass spectrometry. Data-driven machine learning methods were employed to explore diagnostic utility of the measurements for detection and classifying early-stage OA and RA, non-RA and good skeletal health with training set and independent test set cohorts.

resultsGlycated, oxidized and nitrated proteins and amino acids were detected in synovial fluid and plasma of arthritic patients with characteristic patterns found in early and advanced OA and RA, and non-RA, with respect to healthy controls. In early-stage disease, two algorithms for consecutive use in diagnosis were developed: (1) disease versus healthy control, and (2) classification as OA, RA and non-RA. The algorithms featured 10 damaged amino acids in plasma, hydroxyproline and anti-CCP antibody status. Sensitivities/specificities were: (1) good skeletal health, 0.92/0.91; (2) early-stage OA, 0.92/0.90; early-stage RA, 0.80/0.78; and non-RA, 0.70/0.65 (training set). These were confirmed in independent test set validation. Damaged amino acids increased further in severe and advanced OA and RA.

conclusionsOxidized, nitrated and glycated amino acids combined with hydroxyproline and anti-CCP antibody status provided a plasma-based biochemical test of relatively high sensitivity and specificity for early-stage diagnosis and typing of arthritic disease.

Indexed as

Early DiagnosisProtein Processing, Post-TranslationalAdultAgedAlgorithmsAmino AcidsArea Under CurveBiomarkersChromatography, LiquidDisease ProgressionFemaleHumansMaleMiddle AgedNitrosationOsteoarthritis, KneeAmino AcidsBiomarkers3-nitrotyrosineGlycationMachine learningOsteoarthritisOxidative stressRheumatoid arthritis

Identifiers

PMID27788684
PMCPMC5081671
OpenAlexW2540445000

What OpenQuestion holds

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LicenceCC BY
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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 OpenQuestion graph.