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Anti-Integrin αvβ6 Autoantibodies as a Biomarker for Ulcerative Colitis in Patients with Axial Spondyloarthritis

2025· article· en· W4411884113 on OpenAlexaffvenue
Enoch Yau, Robert D. Inman

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsUniversity of TorontoWestern University
Fundersnot available
KeywordsMedicineUlcerative colitisAutoantibodyInternal medicineInflammatory bowel diseaseImmunologyAxial spondyloarthritisGastroenterologyBiomarkerRheumatologyDiseaseAntibodySacroiliitis

Abstract

fetched live from OpenAlex

Objectives An association between axial spondyloarthritis (axSpA) and inflammatory bowel diseases (IBD) has been well described. IgG autoantibodies against the integrin avb6 have been recently identified in the serum of patients with the ulcerative colitis (UC) form of IBD with a high sensitivity and specificity.[1,2] These anti-integrin avb6 autoantibodies (AIA) have also been discovered in patients with primary sclerosing cholangitis, another disease associated with UC.[3] We sought to determine if AIAs could similarly be found in axSpA patients with IBD or with axSpA alone and to evaluate the potential of AIA as a diagnostic test for gut involvement in axSpA patients. Methods Using a previously published ELISA protocol we measured AIA levels in sera of patients with (i) axSpA and UC (n=18), (ii) axSpA and Crohn’s Disease (CD) (n=29), (iii) axSpA alone (n=48), and healthy controls (n=48).[2] The mean + 3 SD ELISA absorbance of the healthy controls was used as a cutoff for AIA positivity. Clinical variables were compared between AIA+ and AIA− patients. Longitudinal serum samples were analyzed to determine if AIA levels changed over time or with biologic use, and if AIA levels correlated with any markers of axSpA severity. Results Patients with axSpA and UC showed a significant increase in mean absorbance compared with axSpA alone and with healthy controls (Figure 1A). 56% of patients with axSpA and UC were AIA+, compared to 26% of patients with axSpA and CD, 4% of patients with axSpA alone, and 0% of healthy controls. For diagnosis of UC among axSpA patients, this test had a sensitivity of 55.6%, specificity of 89.6%, positive likelihood ratio of 5.35 and negative likelihood ratio of 0.50. Receiver operating characteristic analysis of this test yielded an area under curve value of 0.83 as a test for UC in axSpA patients (Figure 1B). AIA positive status was associated with a family history of axSpA, a family history of IBD and, surprisingly, a decreased maximum CRP and BASDAI. While 2/4 AIA+ patients seroconverted following biologic treatment, AIA levels were generally consistent over time and did not seem to trend with CRP or BASDAI. Conclusion We found that within axSpA patients, AIA demonstrated potential as a diagnostic test for UC, and may particularly be useful in screening axSpA patients with a family history of axSpA or IBD. To our knowledge, this is the first study to date to examine AIA in axSpA. [1.] Kuwada T. Gastroenterology 2021;160;2383-2394.e2. [2.] Livanos A. Gastroenterology 2023;164;619-629. [3.] Yoshida H. J Gastroenterol 2023;58:778-789. Best Abstract on Clinical or Epidemiology Research by a Trainee – Phil Rosen Award

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.241
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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