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Record W3134780639 · doi:10.1093/jcag/gwab002.004

A5 GM-CSF AUTOANTIBODIES: PREDICTORS OF CROHN’S DISEASE DEVELOPMENT AND A NOVEL THERAPEUTIC APPROACH

2021· article· en· W3134780639 on OpenAlexaff
Siu Ling Tai, Romain Remark, Ilaria Laface, Diane M. Del Valle, Joana Torres, A Rahman, Renée M. Laird, Chad Porter, Mark S. Riddle, Joseph A. Murray, Rok Seon Choung, T. Sato, Scott E. Plevy, Miriam Mérad, J F Colombel, Sacha Gnjatic, Arthur Mortha

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAutoantibodyImmunologyMedicineUlcerative colitisInflammatory bowel diseaseGranulocyte macrophage colony-stimulating factorCytokineFlow cytometryAutoimmunityPeripheral blood mononuclear cellImmune systemDiseaseAntibodyBiologyPathologyIn vitro

Abstract

fetched live from OpenAlex

Abstract Background Crohn’s disease (CD) is a heterogenous, chronic inflammatory disorder driven by a combination of genetic, environmental, and microbiota-dependent risk factors. Mononuclear phagocytes (MNP) are crucial cells that maintain intestinal homeostasis. An important cytokine for MNP survival and function is granulocyte-macrophage colony stimulating factor (GM-CSF). Interestingly, several studies reported CD-associated genetic risk variants within the GM-CSF receptor and its downstream signaling components. Furthermore, high titers of autoantibodies specific to GM-CSF can be detected in CD patients. Taken together, this data suggests an important role for GM-CSF in abrogation of CD development in a subgroup of patients. Aims This study sought to investigate the function of GM-CSF autoantibodies in CD. Methods We retrospectively quantified and characterized GM-CSF autoantibodies in sera of 220 CD, 200 ulcerative colitis (UC) patients, and 220 healthy controls (HC) sampled at 3 time points prior to disease diagnosis and one time point after diagnosis. ELISA was used to determine GM-CSF autoantibody titers and isotypes followed by in vitro multiplexed mass cytometry (CyTOF) neutralization assays on peripheral blood mononuclear cells. Flow cytometry and CyTOF were used to map the profile of immune cells isolated from inflamed and non-inflamed CD mucosa. Results Our data demonstrates that GM-CSF autoantibodies are specific to CD, significantly elevated up to 7 years prior to diagnosis of disease, and correlate with disease location, severity, and complications at the time of diagnosis. Moreover, in contrast to GM-CSF autoantibodies in pulmonary alveolar proteinosis patients, CD-associated autoantibodies neutralize GM-CSF via specific recognition of post-translational modifications (PTM), affecting MNP function. Removal of PTM enabled GM-CSF to escape autoantibody binding and restored MNP response to GM-CSF in the presence of neutralizing antibodies, indicating a potential therapeutic avenue. Furthermore, we identified group 3 innate lymphoid cells (ILC3) as a major source of GM-CSF in the healthy intestinal tract, suggesting intriguing crosstalk of MNP and ILC3 across the GM-CSF-GM-CSFR axis. Conclusions Our results identify GM-CSF autoantibodies as predictive serological biomarker for CD in a subgroup of patients presenting with severe and complicated form of disease at the time of diagnosis. The presence of GM-CSF autoantibodies precedes the onset of CD by several years and likely abrogates homeostatic immune cell crosstalk involving ILC3 and MNP, suggesting the development of a pre-diseased state in CD patients. Funding Agencies CIHRDr. Edward Ketchum Graduate Scholarship

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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.007
GPT teacher head0.203
Teacher spread0.196 · 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".

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Citations1
Published2021
Admission routes1
Has abstractyes

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