Evidence map›Paper›PMID 37389432›Full record

ArticleRheumatology (Oxford, England)2024

A proteomics study of rheumatoid arthritis patients on etanercept identifies putative biomarkers associated with clinical outcome measures.

Stephanie F Ling, Chuan Fu Yap, Nisha Nair, James Bluett, Ann W Morgan, John D Isaacs, Anthony G Wilson, Kimme L Hyrich, Anne Barton, Darren Plant

Open access · hybridAbstract read
In one paragraph

Article in Rheumatology (Oxford, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 27% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Review
  2. Towards Personalized Medicine in Rheumatoid Arthritis.Open access rheumatology : research and reviews · 2024
    Review
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 at 5 institutions in 2 countries.

Stephanie F LingCentre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, The University of Manchester, Manchester, UK.ORCID 0000-0001-8148-2344
Chuan Fu YapCentre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, The University of Manchester, Manchester, UK.
Nisha NairCentre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, The University of Manchester, Manchester, UK.ORCID 0000-0001-9829-792X
James BluettCentre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, The University of Manchester, Manchester, UK.ORCID 0000-0001-5062-5779
Ann W MorganSchool of Medicine, University of Leeds, Leeds, UK.ORCID 0000-0003-1109-624X
John D IsaacsTranslational and Clinical Research Institute, Newcastle University, Newcastle-upon-Tyne, UK.
Anthony G WilsonSchool of Medicine and Medical Science, Conway Institute, University College Dublin, Dublin, Ireland.
Kimme L HyrichNIHR Biomedical Research Centre Manchester, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK.ORCID 0000-0001-8242-9262
Anne BartonCentre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, The University of Manchester, Manchester, UK.ORCID 0000-0003-3316-2527
Darren PlantCentre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, The University of Manchester, Manchester, UK.ORCID 0000-0003-1395-9344
Manchester Academic Health Science Centre · GBNewcastle upon Tyne Hospitals NHS Foundation Trust · GBUniversity College Dublin · IEUniversity of Leeds · GBUniversity of Manchester · GB

Funding

Department of Health 21754Medical Research Council G1001518Medical Research Council MR/K015346/1
6 · The paper itself

Abstract

objectivesBiologic DMARDs (bDMARDs) are widely used in patients with RA, but response to bDMARDs is heterogeneous. The objective of this work was to identify pretreatment proteomic biomarkers associated with RA clinical outcome measures in patients starting bDMARDs.

methodsSequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH-MS) was used to generate spectral maps of sera from patients with RA before and after 3 months of treatment with the bDMARD etanercept. Protein levels were regressed against RA clinical outcome measures, i.e. 28-joint DAS (DAS28) and its subcomponents and DAS28 <2.6 (i.e. remission). The proteins with the strongest evidence for association were analysed in an independent, replication dataset. Finally, subnetwork analysis was carried out using the Disease Module Detection algorithm and biological plausibility of identified proteins was assessed by enrichment analysis.

resultsA total of 180 patients with RA were included in the discovery dataset and 58 in the validation dataset from a UK-based prospective multicentre study. Ten individual proteins were found to be significantly associated with RA clinical outcome measures. The association of T-complex protein 1 subunit η with DAS28 remission was replicated in an independent cohort. Subnetwork analysis of the 10 proteins from the regression analysis identified the ontological theme, with the strongest associations being with acute phase and acute inflammatory responses.

conclusionThis longitudinal study of 180 patients with RA commencing etanercept has identified several putative protein biomarkers of treatment response to this drug, one of which was replicated in an independent cohort.

Indexed as

Antirheumatic AgentsArthritis, RheumatoidEtanerceptHumansLongitudinal StudiesOutcome Assessment, Health CareProspective StudiesProteomicsTreatment OutcomeAntirheumatic AgentsEtanerceptanti-TNFbiologicsbiomarkersetanerceptgeneticsproteomicsRAtreatment response

Identifiers

PMID37389432
PMCPMC10986807
OpenAlexW4382623146

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.