Evidence map›Paper›PMID 28091549›Full record

ArticleScientific reports2017

Urinary proteomics can define distinct diagnostic inflammatory arthritis subgroups.

Stefan Siebert, Duncan Porter, Caron Paterson, Rosie Hampson, Daniel Gaya, Agnieszka Latosinska, Harald Mischak, Joost Schanstra, William Mullen, Iain McInnes

Abstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
–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

15 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Proteomics appending a complementary dimension to precision oncotherapy.Computational and structural biotechnology journal · 2024
    Review
  4. Article
  5. Review
  6. Review
  7. Article
  8. Article
  9. Review
  10. Review
  11. Review
  12. Review
  13. Review
  14. Review
  15. Article
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.

Stefan SiebertInstitute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom.
Duncan PorterRheumatology Department, NHS Greater Glasgow and Clyde, Glasgow, UK.
Caron PatersonInstitute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom.
Rosie HampsonRheumatology Department, NHS Greater Glasgow and Clyde, Glasgow, UK.
Daniel GayaGastroenterology Department, NHS Greater Glasgow and Clyde, Glasgow, UK.
Agnieszka LatosinskaMosaiques Diagnostics, Hannover, Germany.
Harald MischakMosaiques Diagnostics, Hannover, Germany.
Joost SchanstraInstitut National de la Santé et de la Recherche Médicale (INSERM), U1048, Institute of Cardiovascular and Metabolic Disease, Toulouse, France.
William MullenInstitute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK.
Iain McInnesInstitute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom.

Funding

Medical Research Council MR/N005813/1
6 · The paper itself

Abstract

Current diagnostic tests applied to inflammatory arthritis lack the necessary specificity to appropriately categorise patients. There is a need for novel approaches to classify patients with these conditions. Herein we explored whether urinary proteomic biomarkers specific for different forms of arthritis (rheumatoid arthritis (RA), psoriatic arthritis (PsA), osteoarthritis (OA)) or chronic inflammatory conditions (inflammatory bowel disease (IBD)) can be identified. Fifty subjects per group with RA, PsA, OA or IBD and 50 healthy controls were included in the study. Two-thirds of these populations were randomly selected to serve as a training set, while the remaining one-third was reserved for validation. Sequential comparison of one group to the other four enabled identification of multiple urinary peptides significantly associated with discrete pathological conditions. Classifiers for the five groups were developed and subsequently tested blind in the validation test set. Upon unblinding, the classifiers demonstrated excellent performance, with an area under the curve between 0.90 and 0.97 per group. Identification of the peptide markers pointed to dysregulation of collagen synthesis and inflammation, but also novel inflammatory markers. We conclude that urinary peptide signatures can reliably differentiate between chronic arthropathies and inflammatory conditions with discrete pathogenesis.

Indexed as

Arthritis, RheumatoidBiomarkersCase-Control StudiesDemographyFemaleHumansInflammationMaleMiddle AgedPeptidesProteomicsROC CurveBiomarkersPeptides

Identifiers

PMID28091549
PMCPMC5320079

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.