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Record W4391162768 · doi:10.1093/ecco-jcc/jjad212.0028

OP28 Defective STAT3 signaling in refractory Very Early Onset Inflammatory Bowel Disease is associated with a transcriptional signature which predicts response to anti-IL23-based therapies

2024· article· en· W4391162768 on OpenAlexaff
Lauren V. Collen, Noam D. Beckmann, Vanessa Mitsialis, Alal Eran, Michael Field, Dong‐Gun Kim, Beihua Bao, Jared Barends, Gwen Saccocia, Margaret Bresnahan, Jialiang Yang, Andrew J. Combs, Mark Tuthill, Richelle Bearup, Ibeawuchi Okoroafor, Izabel Patik, Leslie Grushkin-Lerner, Jodie Ouahed, Aleixo M. Muise, Christoph Klein, Barbara A. Horwitz, Eric E. Schadt, Carmen Argmann, Scott B. Snapper

Bibliographic record

VenueJournal of Crohn s and Colitis · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunodeficiency and Autoimmune Disorders
Canadian institutionsSickKids FoundationHospital for Sick Children
Fundersnot available
KeywordsInflammatory bowel diseaseRefractory (planetary science)Interleukin 23Signature (topology)STAT3MedicineDiseaseSignal transductionImmunologyBiologyInterleukinInternal medicineCytokineCell biology

Abstract

fetched live from OpenAlex

Abstract Background Very early onset inflammatory bowel disease (VEOIBD) has a monogenic cause in >5% of cases. IL10R deficiency is among the more common causes of monogenic IBD and presents with severe disease refractory to conventional therapies. For most VEOIBD patients, the molecular basis of disease is unknown. We employed flow cytometry and bulk RNA-sequencing to localize pathway-level dysfunction in VEOIBD patients with unknown molecular basis. Methods VEOIBD patients prospectively enrolled in a biorepository were screened for IL10R deficiency using a flow cytometry assay. Patient peripheral blood mononuclear cells (PBMCs) were stimulated with IL10 and control cytokine IL21 and pSTAT3 activation was measured. RNA-sequencing was performed on 115 whole blood samples, comprising VEOIBD patients with either confirmed (n=35, IL10R deficient n=4), or unknown monogenic causes (n=70), and controls (n=10). Transcriptome analysis focused on patients with abnormal STAT3 activation as determined by flow cytometry. Results We identified 6 patients with refractory VEOIBD and defective phosphorylation of STAT3 upon stimulation with both IL10 and IL21 by flow cytometry (Fig 1A), a result confirmed by Western blot (Fig 1B). All six "STAT3-defective" (STAT3-def) patients lacked deleterious mutations in known VEOIBD genes as determined by whole exome sequencing. Principal component analysis of blood transcriptome data showed the STAT3-def and IL10R deficient patients generally clustered together (Fig 1C). Cell-type de-convolution analysis of the blood transcriptomes was used to infer cell-type abundance and cell-type specific differentially expressed genes (DEGs) for the STAT3-def and IL10R deficient groups relative to the rest. Genes downregulated in estimated M1 macrophages from the STAT3-def group were enriched in the Hallmark pathway "IL6-JAK-STAT3 signaling." STAT3-def M1 macrophage DEGs were then projected on an adult colonic Crohn’s disease Bayesian network and extended out a path length of 1. The resulting STAT3-def subnetwork of 440 genes included the known VEOIBD genes STAT3, STAT1, TYMP, and TRIM22 (Fig 1D) and the top enriched signaling pathways included IL23, IL6, and IL12. This is of significant interest given three STAT3-def patients with disease refractory to anti-TNF and vedolizumab achieved remission with anti-IL23-based therapies (Table 1). Conclusion We identified 6 patients with refractory VEOIBD and a shared biochemical phenotype and blood transcriptional signature. Network analysis revealed signaling pathways targeted by existing IBD medications, including anti-IL23-based therapies. Molecular analysis of IBD patient blood has exciting potential to localize pathway-level dysfunction and guide precision medicine approaches.

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)0.000
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.006
GPT teacher head0.218
Teacher spread0.212 · 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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Citations0
Published2024
Admission routes1
Has abstractyes

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